When does female multiple mating evolve to adjust inbreeding? Effects of inbreeding depression, direct costs, mating constraints, and polyandry as a threshold trait.

PubMed

Duthie, A Bradley; Bocedi, Greta; Reid, Jane M

2016-09-01

Polyandry is often hypothesized to evolve to allow females to adjust the degree to which they inbreed. Multiple factors might affect such evolution, including inbreeding depression, direct costs, constraints on male availability, and the nature of polyandry as a threshold trait. Complex models are required to evaluate when evolution of polyandry to adjust inbreeding is predicted to arise. We used a genetically explicit individual-based model to track the joint evolution of inbreeding strategy and polyandry defined as a polygenic threshold trait. Evolution of polyandry to avoid inbreeding only occurred given strong inbreeding depression, low direct costs, and severe restrictions on initial versus additional male availability. Evolution of polyandry to prefer inbreeding only occurred given zero inbreeding depression and direct costs, and given similarly severe restrictions on male availability. However, due to its threshold nature, phenotypic polyandry was frequently expressed even when strongly selected against and hence maladaptive. Further, the degree to which females adjusted inbreeding through polyandry was typically very small, and often reflected constraints on male availability rather than adaptive reproductive strategy. Evolution of polyandry solely to adjust inbreeding might consequently be highly restricted in nature, and such evolution cannot necessarily be directly inferred from observed magnitudes of inbreeding adjustment. © 2016 The Author(s). Evolution published by Wiley Periodicals, Inc. on behalf of The Society for the Study of Evolution.

Maximizing capture of gene co-expression relationships through pre-clustering of input expression samples: an Arabidopsis case study.

PubMed

Feltus, F Alex; Ficklin, Stephen P; Gibson, Scott M; Smith, Melissa C

2013-06-05

In genomics, highly relevant gene interaction (co-expression) networks have been constructed by finding significant pair-wise correlations between genes in expression datasets. These networks are then mined to elucidate biological function at the polygenic level. In some cases networks may be constructed from input samples that measure gene expression under a variety of different conditions, such as for different genotypes, environments, disease states and tissues. When large sets of samples are obtained from public repositories it is often unmanageable to associate samples into condition-specific groups, and combining samples from various conditions has a negative effect on network size. A fixed significance threshold is often applied also limiting the size of the final network. Therefore, we propose pre-clustering of input expression samples to approximate condition-specific grouping of samples and individual network construction of each group as a means for dynamic significance thresholding. The net effect is increase sensitivity thus maximizing the total co-expression relationships in the final co-expression network compendium. A total of 86 Arabidopsis thaliana co-expression networks were constructed after k-means partitioning of 7,105 publicly available ATH1 Affymetrix microarray samples. We term each pre-sorted network a Gene Interaction Layer (GIL). Random Matrix Theory (RMT), an un-supervised thresholding method, was used to threshold each of the 86 networks independently, effectively providing a dynamic (non-global) threshold for the network. The overall gene count across all GILs reached 19,588 genes (94.7% measured gene coverage) and 558,022 unique co-expression relationships. In comparison, network construction without pre-sorting of input samples yielded only 3,297 genes (15.9%) and 129,134 relationships. in the global network. Here we show that pre-clustering of microarray samples helps approximate condition-specific networks and allows for dynamic thresholding using un-supervised methods. Because RMT ensures only highly significant interactions are kept, the GIL compendium consists of 558,022 unique high quality A. thaliana co-expression relationships across almost all of the measurable genes on the ATH1 array. For A. thaliana, these networks represent the largest compendium to date of significant gene co-expression relationships, and are a means to explore complex pathway, polygenic, and pleiotropic relationships for this focal model plant. The networks can be explored at sysbio.genome.clemson.edu. Finally, this method is applicable to any large expression profile collection for any organism and is best suited where a knowledge-independent network construction method is desired.

Maximizing capture of gene co-expression relationships through pre-clustering of input expression samples: an Arabidopsis case study

PubMed Central

2013-01-01

Background In genomics, highly relevant gene interaction (co-expression) networks have been constructed by finding significant pair-wise correlations between genes in expression datasets. These networks are then mined to elucidate biological function at the polygenic level. In some cases networks may be constructed from input samples that measure gene expression under a variety of different conditions, such as for different genotypes, environments, disease states and tissues. When large sets of samples are obtained from public repositories it is often unmanageable to associate samples into condition-specific groups, and combining samples from various conditions has a negative effect on network size. A fixed significance threshold is often applied also limiting the size of the final network. Therefore, we propose pre-clustering of input expression samples to approximate condition-specific grouping of samples and individual network construction of each group as a means for dynamic significance thresholding. The net effect is increase sensitivity thus maximizing the total co-expression relationships in the final co-expression network compendium. Results A total of 86 Arabidopsis thaliana co-expression networks were constructed after k-means partitioning of 7,105 publicly available ATH1 Affymetrix microarray samples. We term each pre-sorted network a Gene Interaction Layer (GIL). Random Matrix Theory (RMT), an un-supervised thresholding method, was used to threshold each of the 86 networks independently, effectively providing a dynamic (non-global) threshold for the network. The overall gene count across all GILs reached 19,588 genes (94.7% measured gene coverage) and 558,022 unique co-expression relationships. In comparison, network construction without pre-sorting of input samples yielded only 3,297 genes (15.9%) and 129,134 relationships. in the global network. Conclusions Here we show that pre-clustering of microarray samples helps approximate condition-specific networks and allows for dynamic thresholding using un-supervised methods. Because RMT ensures only highly significant interactions are kept, the GIL compendium consists of 558,022 unique high quality A. thaliana co-expression relationships across almost all of the measurable genes on the ATH1 array. For A. thaliana, these networks represent the largest compendium to date of significant gene co-expression relationships, and are a means to explore complex pathway, polygenic, and pleiotropic relationships for this focal model plant. The networks can be explored at sysbio.genome.clemson.edu. Finally, this method is applicable to any large expression profile collection for any organism and is best suited where a knowledge-independent network construction method is desired. PMID:23738693

Variability in working memory performance explained by epistasis vs polygenic scores in the ZNF804A pathway.

PubMed

Nicodemus, Kristin K; Hargreaves, April; Morris, Derek; Anney, Richard; Gill, Michael; Corvin, Aiden; Donohoe, Gary

2014-07-01

We investigated the variation in neuropsychological function explained by risk alleles at the psychosis susceptibility gene ZNF804A and its interacting partners using single nucleotide polymorphisms (SNPs), polygenic scores, and epistatic analyses. Of particular importance was the relative contribution of the polygenic score vs epistasis in variation explained. To (1) assess the association between SNPs in ZNF804A and the ZNF804A polygenic score with measures of cognition in cases with psychosis and (2) assess whether epistasis within the ZNF804A pathway could explain additional variation above and beyond that explained by the polygenic score. Patients with psychosis (n = 424) were assessed in areas of cognitive ability impaired in schizophrenia including IQ, memory, attention, and social cognition. We used the Psychiatric GWAS Consortium 1 schizophrenia genome-wide association study to calculate a polygenic score based on identified risk variants within this genetic pathway. Cognitive measures significantly associated with the polygenic score were tested for an epistatic component using a training set (n = 170), which was used to develop linear regression models containing the polygenic score and 2-SNP interactions. The best-fitting models were tested for replication in 2 independent test sets of cases: (1) 170 individuals with schizophrenia or schizoaffective disorder and (2) 84 patients with broad psychosis (including bipolar disorder, major depressive disorder, and other psychosis). Participants completed a neuropsychological assessment battery designed to target the cognitive deficits of schizophrenia including general cognitive function, episodic memory, working memory, attentional control, and social cognition. Higher polygenic scores were associated with poorer performance among patients on IQ, memory, and social cognition, explaining 1% to 3% of variation on these scores (range, P = .01 to .03). Using a narrow psychosis training set and independent test sets of narrow phenotype psychosis (schizophrenia and schizoaffective disorder), broad psychosis, and control participants (n = 89), the addition of 2 interaction terms containing 2 SNPs each increased the R2 for spatial working memory strategy in the independent psychosis test sets from 1.2% using the polygenic score only to 4.8% (P = .11 and .001, respectively) but did not explain additional variation in control participants. These data support a role for the ZNF804A pathway in IQ, memory, and social cognition in cases. Furthermore, we showed that epistasis increases the variation explained above the contribution of the polygenic score.

Empirical Bayes Estimation of Semi-parametric Hierarchical Mixture Models for Unbiased Characterization of Polygenic Disease Architectures

PubMed Central

Nishino, Jo; Kochi, Yuta; Shigemizu, Daichi; Kato, Mamoru; Ikari, Katsunori; Ochi, Hidenori; Noma, Hisashi; Matsui, Kota; Morizono, Takashi; Boroevich, Keith A.; Tsunoda, Tatsuhiko; Matsui, Shigeyuki

2018-01-01

Genome-wide association studies (GWAS) suggest that the genetic architecture of complex diseases consists of unexpectedly numerous variants with small effect sizes. However, the polygenic architectures of many diseases have not been well characterized due to lack of simple and fast methods for unbiased estimation of the underlying proportion of disease-associated variants and their effect-size distribution. Applying empirical Bayes estimation of semi-parametric hierarchical mixture models to GWAS summary statistics, we confirmed that schizophrenia was extremely polygenic [~40% of independent genome-wide SNPs are risk variants, most within odds ratio (OR = 1.03)], whereas rheumatoid arthritis was less polygenic (~4 to 8% risk variants, significant portion reaching OR = 1.05 to 1.1). For rheumatoid arthritis, stratified estimations revealed that expression quantitative loci in blood explained large genetic variance, and low- and high-frequency derived alleles were prone to be risk and protective, respectively, suggesting a predominance of deleterious-risk and advantageous-protective mutations. Despite genetic correlation, effect-size distributions for schizophrenia and bipolar disorder differed across allele frequency. These analyses distinguished disease polygenic architectures and provided clues for etiological differences in complex diseases. PMID:29740473

Genetic correlates of insight in schizophrenia.

PubMed

Xavier, Rose Mary; Vorderstrasse, Allison; Keefe, Richard S E; Dungan, Jennifer R

2018-05-01

Insight in schizophrenia is clinically important as it is associated with several adverse outcomes. Genetic contributions to insight are unknown. We examined genetic contributions to insight by investigating if polygenic risk scores (PRS) and candidate regions were associated with insight. Schizophrenia case-only analysis of the Clinical Antipsychotics Trials of Intervention Effectiveness trial. Schizophrenia PRS was constructed using Psychiatric Genomics Consortium (PGC) leave-one out GWAS as discovery data set. For candidate regions, we selected 105 schizophrenia-associated autosomal loci and 11 schizophrenia-related oligodendrocyte genes. We used regressions to examine PRS associations and set-based testing for candidate analysis. We examined data from 730 subjects. Best-fit PRS at p-threshold of 1e-07 was associated with total insight (R 2 =0.005, P=0.05, empirical P=0.054) and treatment insight (R 2 =0.005, P=0.048, empirical P=0.048). For models that controlled for neurocognition, PRS significantly predicted treatment insight but at higher p-thresholds (0.1 to 0.5) but did not survive correction. Patients with highest polygenic burden had 5.9 times increased risk for poor insight compared to patients with lowest burden. PRS explained 3.2% (P=0.002, empirical P=0.011) of variance in poor insight. Set-based analyses identified two variants associated with poor insight- rs320703, an intergenic variant (within-set P=6e-04, FDR P=0.046) and rs1479165 in SOX2-OT (within-set P=9e-04, FDR P=0.046). To the best of our knowledge, this is the first study examining genetic basis of insight. We provide evidence for genetic contributions to impaired insight. Relevance of findings and necessity for replication are discussed. Copyright © 2017 Elsevier B.V. All rights reserved.

Genetic heterogeneity in depressive symptoms following the death of a spouse: Polygenic score analysis of the US Health and Retirement Study

PubMed Central

Domingue, Benjamin W.; Liu, Hexuan; Okbay, Aysu; Belsky, Daniel W.

2017-01-01

Objective Experience of stressful life events is associated with risk of depression. Yet many exposed individuals do not become depressed. A controversial hypothesis is that genetic factors influence vulnerability to depression following stress. This hypothesis is often tested with a “diathesis-stress” model, in which genes confer excess vulnerability. We tested an alternative formulation of this model: genes may buffer against depressogenic effects of life stress. Method We measured the hypothesized genetic buffer using a polygenic score derived from a published genome-wide association study (GWAS) of subjective wellbeing. We tested if married older adults who had higher polygenic scores were less vulnerable to depressive symptoms following the death of their spouse as compared to age-peers who had also lost their spouse and who had lower polygenic scores. We analyzed data from N=8,588 non-Hispanic white adults in the Health and Retirement Study (HRS), a population-representative longitudinal study of older adults in the United States. Results HRS adults with higher wellbeing polygenic scores experienced fewer depressive symptoms during follow-up. Those who survived death of their spouses (n=1,647) experienced a sharp increase in depressive symptoms following the death and returned toward baseline over the following two years. Having a higher polygenic score buffered against increased depressive symptoms following a spouse’s death. Conclusions Effects were small and clinical relevance is uncertain, although polygenic score analyses may provide clues to behavioral pathways that can serve as therapeutic targets. Future studies of gene-environment interplay in depression may benefit from focus on genetics discovered for putative protective factors. PMID:28335623

Polygenic Score × Intervention Moderation: an Application of Discrete-Time Survival Analysis to Model the Timing of First Marijuana Use Among Urban Youth.

PubMed

Musci, Rashelle J; Fairman, Brian; Masyn, Katherine E; Uhl, George; Maher, Brion; Sisto, Danielle Y; Kellam, Sheppard G; Ialongo, Nicholas S

2018-01-01

The present study examines the interaction between a polygenic score and an elementary school-based universal preventive intervention trial and its effects on a discrete-time survival analysis of time to first smoking marijuana. Research has suggested that initiation of substances is both genetically and environmentally driven (Rhee et al., Archives of general psychiatry 60:1256-1264, 2003; Verweij et al., Addiction 105:417-430, 2010). A previous work has found a significant interaction between the polygenic score and the same elementary school-based intervention with tobacco smoking (Musci et al., in press). The polygenic score reflects the contribution of multiple genes and has been shown in prior research to be predictive of smoking cessation, tobacco use, and marijuana use (Uhl et al., Molecular Psychiatry 19:50-54, 2014). Using data from a longitudinal preventive intervention study (N = 678), we examined age of first marijuana use from sixth grade to age 18. Genetic data were collected during emerging adulthood and were genotyped using the Affymetrix 6.0 microarray (N = 545). The polygenic score was computed using these data. Discrete-time survival analysis was employed to test for intervention main and interaction effects with the polygenic score. We found main effect of the polygenic score approaching significance, with the participants with higher polygenic scores reporting their first smoking marijuana at an age significantly later than controls (p = .050). We also found a significant intervention × polygenic score interaction effect at p = .003, with participants at the higher end of the polygenic score benefiting the most from the intervention in terms of delayed age of first use. These results suggest that genetics may play an important role in the age of first use of marijuana and that differences in genetics may account for the differential effectiveness of classroom-based interventions in delaying substance use experimentation.

Association of Polygenic Score for Schizophrenia and HLA Antigen and Inflammation Genes With Response to Lithium in Bipolar Affective Disorder: A Genome-Wide Association Study.

PubMed

Amare, Azmeraw T; Schubert, Klaus Oliver; Hou, Liping; Clark, Scott R; Papiol, Sergi; Heilbronner, Urs; Degenhardt, Franziska; Tekola-Ayele, Fasil; Hsu, Yi-Hsiang; Shekhtman, Tatyana; Adli, Mazda; Akula, Nirmala; Akiyama, Kazufumi; Ardau, Raffaella; Arias, Bárbara; Aubry, Jean-Michel; Backlund, Lena; Bhattacharjee, Abesh Kumar; Bellivier, Frank; Benabarre, Antonio; Bengesser, Susanne; Biernacka, Joanna M; Birner, Armin; Brichant-Petitjean, Clara; Cervantes, Pablo; Chen, Hsi-Chung; Chillotti, Caterina; Cichon, Sven; Cruceanu, Cristiana; Czerski, Piotr M; Dalkner, Nina; Dayer, Alexandre; Del Zompo, Maria; DePaulo, J Raymond; Étain, Bruno; Falkai, Peter; Forstner, Andreas J; Frisen, Louise; Frye, Mark A; Fullerton, Janice M; Gard, Sébastien; Garnham, Julie S; Goes, Fernando S; Grigoroiu-Serbanescu, Maria; Grof, Paul; Hashimoto, Ryota; Hauser, Joanna; Herms, Stefan; Hoffmann, Per; Hofmann, Andrea; Jamain, Stephane; Jiménez, Esther; Kahn, Jean-Pierre; Kassem, Layla; Kuo, Po-Hsiu; Kato, Tadafumi; Kelsoe, John; Kittel-Schneider, Sarah; Kliwicki, Sebastian; König, Barbara; Kusumi, Ichiro; Laje, Gonzalo; Landén, Mikael; Lavebratt, Catharina; Leboyer, Marion; Leckband, Susan G; Tortorella, Alfonso; Manchia, Mirko; Martinsson, Lina; McCarthy, Michael J; McElroy, Susan; Colom, Francesc; Mitjans, Marina; Mondimore, Francis M; Monteleone, Palmiero; Nievergelt, Caroline M; Nöthen, Markus M; Novák, Tomas; O'Donovan, Claire; Ozaki, Norio; Ösby, Urban; Pfennig, Andrea; Potash, James B; Reif, Andreas; Reininghaus, Eva; Rouleau, Guy A; Rybakowski, Janusz K; Schalling, Martin; Schofield, Peter R; Schweizer, Barbara W; Severino, Giovanni; Shilling, Paul D; Shimoda, Katzutaka; Simhandl, Christian; Slaney, Claire M; Squassina, Alessio; Stamm, Thomas; Stopkova, Pavla; Maj, Mario; Turecki, Gustavo; Vieta, Eduard; Volkert, Julia; Witt, Stephanie; Wright, Adam; Zandi, Peter P; Mitchell, Philip B; Bauer, Michael; Alda, Martin; Rietschel, Marcella; McMahon, Francis J; Schulze, Thomas G; Baune, Bernhard T

2018-01-01

Lithium is a first-line mood stabilizer for the treatment of bipolar affective disorder (BPAD). However, the efficacy of lithium varies widely, with a nonresponse rate of up to 30%. Biological response markers are lacking. Genetic factors are thought to mediate treatment response to lithium, and there is a previously reported genetic overlap between BPAD and schizophrenia (SCZ). To test whether a polygenic score for SCZ is associated with treatment response to lithium in BPAD and to explore the potential molecular underpinnings of this association. A total of 2586 patients with BPAD who had undergone lithium treatment were genotyped and assessed for long-term response to treatment between 2008 and 2013. Weighted SCZ polygenic scores were computed at different P value thresholds using summary statistics from an international multicenter genome-wide association study (GWAS) of 36 989 individuals with SCZ and genotype data from patients with BPAD from the Consortium on Lithium Genetics. For functional exploration, a cross-trait meta-GWAS and pathway analysis was performed, combining GWAS summary statistics on SCZ and response to treatment with lithium. Data analysis was performed from September 2016 to February 2017. Treatment response to lithium was defined on both the categorical and continuous scales using the Retrospective Criteria of Long-Term Treatment Response in Research Subjects with Bipolar Disorder score. The effect measures include odds ratios and the proportion of variance explained. Of the 2586 patients in the study (mean [SD] age, 47.2 [13.9] years), 1478 were women and 1108 were men. The polygenic score for SCZ was inversely associated with lithium treatment response in the categorical outcome, at a threshold P < 5 × 10-2. Patients with BPAD who had a low polygenic load for SCZ responded better to lithium, with odds ratios for lithium response ranging from 3.46 (95% CI, 1.42-8.41) at the first decile to 2.03 (95% CI, 0.86-4.81) at the ninth decile, compared with the patients in the 10th decile of SCZ risk. In the cross-trait meta-GWAS, 15 genetic loci that may have overlapping effects on lithium treatment response and susceptibility to SCZ were identified. Functional pathway and network analysis of these loci point to the HLA antigen complex and inflammatory cytokines. This study provides evidence for a negative association between high genetic loading for SCZ and poor response to lithium in patients with BPAD. These results suggest the potential for translational research aimed at personalized prescribing of lithium.

Identification of Gene Loci That Overlap Between Schizophrenia and Educational Attainment

PubMed Central

Le Hellard, Stéphanie; Wang, Yunpeng; Witoelar, Aree; Zuber, Verena; Bettella, Francesco; Hugdahl, Kenneth; Espeseth, Thomas; Steen, Vidar M.; Melle, Ingrid; Desikan, Rahul; Schork, Andrew J.; Thompson, Wesley K.; Dale, Anders M.; Djurovic, Srdjan

2017-01-01

Abstract There is evidence for genetic overlap between cognitive abilities and schizophrenia (SCZ), and genome-wide association studies (GWAS) demonstrate that both SCZ and general cognitive abilities have a strong polygenic component with many single-nucleotide polymorphisms (SNPs) each with a small effect. Here we investigated the shared genetic architecture between SCZ and educational attainment, which is regarded as a “proxy phenotype” for cognitive abilities, but may also reflect other traits. We applied a conditional false discovery rate (condFDR) method to GWAS of SCZ (n = 82 315), college completion (“College,” n = 95 427), and years of education (“EduYears,” n = 101 069). Variants associated with College or EduYears showed enrichment of association with SCZ, demonstrating polygenic overlap. This was confirmed by an increased replication rate in SCZ. By applying a condFDR threshold <0.01, we identified 18 genomic loci associated with SCZ after conditioning on College and 15 loci associated with SCZ after conditioning on EduYears. Ten of these loci overlapped. Using conjunctional FDR, we identified 10 loci shared between SCZ and College, and 29 loci shared between SCZ and EduYears. The majority of these loci had effects in opposite directions. Our results provide evidence for polygenic overlap between SCZ and educational attainment, and identify novel pleiotropic loci. Other studies have reported genetic overlap between SCZ and cognition, or SCZ and educational attainment, with negative correlation. Importantly, our methods enable identification of bi-directional effects, which highlight the complex relationship between SCZ and educational attainment, and support polygenic mechanisms underlying both cognitive dysfunction and creativity in SCZ. PMID:27338279

Identification of Gene Loci That Overlap Between Schizophrenia and Educational Attainment.

PubMed

Le Hellard, Stéphanie; Wang, Yunpeng; Witoelar, Aree; Zuber, Verena; Bettella, Francesco; Hugdahl, Kenneth; Espeseth, Thomas; Steen, Vidar M; Melle, Ingrid; Desikan, Rahul; Schork, Andrew J; Thompson, Wesley K; Dale, Anders M; Djurovic, Srdjan; Andreassen, Ole A

2017-05-01

There is evidence for genetic overlap between cognitive abilities and schizophrenia (SCZ), and genome-wide association studies (GWAS) demonstrate that both SCZ and general cognitive abilities have a strong polygenic component with many single-nucleotide polymorphisms (SNPs) each with a small effect. Here we investigated the shared genetic architecture between SCZ and educational attainment, which is regarded as a "proxy phenotype" for cognitive abilities, but may also reflect other traits. We applied a conditional false discovery rate (condFDR) method to GWAS of SCZ (n = 82 315), college completion ("College," n = 95 427), and years of education ("EduYears," n = 101 069). Variants associated with College or EduYears showed enrichment of association with SCZ, demonstrating polygenic overlap. This was confirmed by an increased replication rate in SCZ. By applying a condFDR threshold <0.01, we identified 18 genomic loci associated with SCZ after conditioning on College and 15 loci associated with SCZ after conditioning on EduYears. Ten of these loci overlapped. Using conjunctional FDR, we identified 10 loci shared between SCZ and College, and 29 loci shared between SCZ and EduYears. The majority of these loci had effects in opposite directions. Our results provide evidence for polygenic overlap between SCZ and educational attainment, and identify novel pleiotropic loci. Other studies have reported genetic overlap between SCZ and cognition, or SCZ and educational attainment, with negative correlation. Importantly, our methods enable identification of bi-directional effects, which highlight the complex relationship between SCZ and educational attainment, and support polygenic mechanisms underlying both cognitive dysfunction and creativity in SCZ. © The Author 2016. Published by Oxford University Press on behalf of the Maryland Psychiatric Research Center. All rights reserved. For permissions, please email: journals.permissions@oup.com.

Association of the Polygenic Scores for Personality Traits and Response to Selective Serotonin Reuptake Inhibitors in Patients with Major Depressive Disorder

PubMed Central

Amare, Azmeraw T.; Schubert, Klaus Oliver; Tekola-Ayele, Fasil; Hsu, Yi-Hsiang; Sangkuhl, Katrin; Jenkins, Gregory; Whaley, Ryan M.; Barman, Poulami; Batzler, Anthony; Altman, Russ B.; Arolt, Volker; Brockmöller, Jürgen; Chen, Chia-Hui; Domschke, Katharina; Hall-Flavin, Daniel K.; Hong, Chen-Jee; Illi, Ari; Ji, Yuan; Kampman, Olli; Kinoshita, Toshihiko; Leinonen, Esa; Liou, Ying-Jay; Mushiroda, Taisei; Nonen, Shinpei; Skime, Michelle K.; Wang, Liewei; Kato, Masaki; Liu, Yu-Li; Praphanphoj, Verayuth; Stingl, Julia C.; Bobo, William V.; Tsai, Shih-Jen; Kubo, Michiaki; Klein, Teri E.; Weinshilboum, Richard M.; Biernacka, Joanna M.; Baune, Bernhard T.

2018-01-01

Studies reported a strong genetic correlation between the Big Five personality traits and major depressive disorder (MDD). Moreover, personality traits are thought to be associated with response to antidepressants treatment that might partly be mediated by genetic factors. In this study, we examined whether polygenic scores (PGSs) derived from the Big Five personality traits predict treatment response and remission in patients with MDD who were prescribed selective serotonin reuptake inhibitors (SSRIs). In addition, we performed meta-analyses of genome-wide association studies (GWASs) on these traits to identify genetic variants underpinning the cross-trait polygenic association. The PGS analysis was performed using data from two cohorts: the Pharmacogenomics Research Network Antidepressant Medication Pharmacogenomic Study (PGRN-AMPS, n = 529) and the International SSRI Pharmacogenomics Consortium (ISPC, n = 865). The cross-trait GWAS meta-analyses were conducted by combining GWAS summary statistics on SSRIs treatment outcome and on the personality traits. The results showed that the PGS for openness and neuroticism were associated with SSRIs treatment outcomes at p < 0.05 across PT thresholds in both cohorts. A significant association was also found between the PGS for conscientiousness and SSRIs treatment response in the PGRN-AMPS sample. In the cross-trait GWAS meta-analyses, we identified eight loci associated with (a) SSRIs response and conscientiousness near YEATS4 gene and (b) SSRI remission and neuroticism eight loci near PRAG1, MSRA, XKR6, ELAVL2, PLXNC1, PLEKHM1, and BRUNOL4 genes. An assessment of a polygenic load for personality traits may assist in conjunction with clinical data to predict whether MDD patients might respond favorably to SSRIs. PMID:29559929

Widespread covariation of early environmental exposures and trait-associated polygenic variation.

PubMed

Krapohl, E; Hannigan, L J; Pingault, J-B; Patel, H; Kadeva, N; Curtis, C; Breen, G; Newhouse, S J; Eley, T C; O'Reilly, P F; Plomin, R

2017-10-31

Although gene-environment correlation is recognized and investigated by family studies and recently by SNP-heritability studies, the possibility that genetic effects on traits capture environmental risk factors or protective factors has been neglected by polygenic prediction models. We investigated covariation between trait-associated polygenic variation identified by genome-wide association studies (GWASs) and specific environmental exposures, controlling for overall genetic relatedness using a genomic relatedness matrix restricted maximum-likelihood model. In a UK-representative sample ( n = 6,710), we find widespread covariation between offspring trait-associated polygenic variation and parental behavior and characteristics relevant to children's developmental outcomes-independently of population stratification. For instance, offspring genetic risk for schizophrenia was associated with paternal age ( R 2 = 0.002; P = 1e-04), and offspring education-associated variation was associated with variance in breastfeeding ( R 2 = 0.021; P = 7e-30), maternal smoking during pregnancy ( R 2 = 0.008; P = 5e-13), parental smacking ( R 2 = 0.01; P = 4e-15), household income ( R 2 = 0.032; P = 1e-22), watching television ( R 2 = 0.034; P = 5e-47), and maternal education ( R 2 = 0.065; P = 3e-96). Education-associated polygenic variation also captured covariation between environmental exposures and children's inattention/hyperactivity, conduct problems, and educational achievement. The finding that genetic variation identified by trait GWASs partially captures environmental risk factors or protective factors has direct implications for risk prediction models and the interpretation of GWAS findings.

Single Nucleotide Polymorphisms Associated with Reading Ability Show Connection to Socio-Economic Outcomes.

PubMed

Luciano, Michelle; Hagenaars, Saskia P; Cox, Simon R; Hill, William David; Davies, Gail; Harris, Sarah E; Deary, Ian J; Evans, David M; Martin, Nicholas G; Wright, Margaret J; Bates, Timothy C

2017-09-01

Impairments in reading and in language have negative consequences on life outcomes, but it is not known to what extent genetic effects influence this association. We constructed polygenic scores for difficulties with language and learning to read from genome-wide data in ~6,600 children, adolescents and young adults, and tested their association with health, socioeconomic outcomes and brain structure measures collected in adults (maximal N = 111,749). Polygenic risk of reading difficulties was associated with reduced income, educational attainment, self-rated health and verbal-numerical reasoning (p < 0.00055). Polygenic risk of language difficulties predicted income (p = 0.0005). The small effect sizes ranged 0.01-0.03 of a standard deviation, but these will increase as genetic studies for reading ability get larger. Polygenic scores for childhood cognitive ability and educational attainment were correlated with polygenic scores of reading and language (up to 0.09 and 0.05, respectively). But when they were included in the prediction models, the observed associations between polygenic reading and adult outcomes mostly remained. This suggests that the pathway from reading ability to social outcomes is not only via associated polygenic loads for general cognitive function and educational attainment. The presence of non-overlapping genetic effect is indicated by the genetic correlations of around 0.40 (childhood intelligence) and 0.70 (educational attainment) with reading ability. Mendelian randomization approaches will be important to dissociate any causal and moderating effects of reading and related traits on social outcomes.

Fingerprint Ridge Count: A Polygenic Trait Useful in Classroom Instruction.

ERIC Educational Resources Information Center

Mendenhall, Gordon; And Others

1989-01-01

Describes the use of the polygenic trait of total fingerprint ridge count in the classroom as a laboratory investigation. Presents information on background of topic, fingerprint patterns which are classified into three major groups, ridge count, the inheritance model, and activities. Includes an example data sheet format for fingerprints. (RT)

Maintenance of polygenic sex determination in a fluctuating environment: an individual-based model.

PubMed

Bateman, A W; Anholt, B R

2017-05-01

R. A. Fisher predicted that individuals should invest equally in offspring of both sexes, and that the proportion of males and females produced (the primary sex ratio) should evolve towards 1:1 when unconstrained. For many species, sex determination is dependent on sex chromosomes, creating a strong tendency for balanced sex ratios, but in other cases, multiple autosomal genes interact to determine sex. In such cases, the maintenance of multiple sex-determining alleles at multiple loci and the consequent among-family variability in sex ratios presents a puzzle, as theory predicts that such systems should be unstable. Theory also predicts that environmental influences on sex can complicate outcomes of genetic sex determination, and that population structure may play a role. Tigriopus californicus, a copepod that lives in splash-pool metapopulations and exhibits polygenic and environment-dependent sex determination, presents a test case for relevant theory. We use this species as a model for parameterizing an individual-based simulation to investigate conditions that could maintain polygenic sex determination. We find that metapopulation structure can delay the degradation of polygenic sex determination and that periods of alternating frequency-dependent selection, imposed by seasonal fluctuations in environmental conditions, can maintain polygenic sex determination indefinitely. © 2017 European Society For Evolutionary Biology. Journal of Evolutionary Biology © 2017 European Society For Evolutionary Biology.

Parenting Interacts with Oxytocin Polymorphisms to Predict Adolescent Social Anxiety Symptom Development: A Novel Polygenic Approach.

PubMed

Nelemans, Stefanie A; van Assche, Evelien; Bijttebier, Patricia; Colpin, Hilde; van Leeuwen, Karla; Verschueren, Karine; Claes, Stephan; van den Noortgate, Wim; Goossens, Luc

2018-04-26

Guided by a developmental psychopathology framework, research has increasingly focused on the interplay of genetics and environment as a predictor of different forms of psychopathology, including social anxiety. In these efforts, the polygenic nature of complex phenotypes such as social anxiety is increasingly recognized, but studies applying polygenic approaches are still scarce. In this study, we applied Principal Covariates Regression as a novel approach to creating polygenic components for the oxytocin system, which has recently been put forward as particularly relevant to social anxiety. Participants were 978 adolescents (49.4% girls; M age T 1  = 13.8 years). Across 3 years, questionnaires were used to assess adolescent social anxiety symptoms and multi-informant reports of parental psychological control and autonomy support. All adolescents were genotyped for 223 oxytocin single nucleotide polymorphisms (SNPs) in 14 genes. Using Principal Covariates Regression, these SNPs could be reduced to five polygenic components. Four components reflected the underlying linkage disequilibrium and ancestry structure, whereas the fifth component, which consisted of small contributions of many SNPs across multiple genes, was strongly positively associated with adolescent social anxiety symptoms, pointing to an index of genetic risk. Moreover, significant interactions were found with this polygenic component and the environmental variables of interest. Specifically, adolescents who scored high on this polygenic component and experienced less adequate parenting (i.e., high psychological control or low autonomy support) showed the highest levels of social anxiety. Implications of these findings are discussed in the context of individual-by-environment models.

pLARmEB: integration of least angle regression with empirical Bayes for multilocus genome-wide association studies.

PubMed

Zhang, J; Feng, J-Y; Ni, Y-L; Wen, Y-J; Niu, Y; Tamba, C L; Yue, C; Song, Q; Zhang, Y-M

2017-06-01

Multilocus genome-wide association studies (GWAS) have become the state-of-the-art procedure to identify quantitative trait nucleotides (QTNs) associated with complex traits. However, implementation of multilocus model in GWAS is still difficult. In this study, we integrated least angle regression with empirical Bayes to perform multilocus GWAS under polygenic background control. We used an algorithm of model transformation that whitened the covariance matrix of the polygenic matrix K and environmental noise. Markers on one chromosome were included simultaneously in a multilocus model and least angle regression was used to select the most potentially associated single-nucleotide polymorphisms (SNPs), whereas the markers on the other chromosomes were used to calculate kinship matrix as polygenic background control. The selected SNPs in multilocus model were further detected for their association with the trait by empirical Bayes and likelihood ratio test. We herein refer to this method as the pLARmEB (polygenic-background-control-based least angle regression plus empirical Bayes). Results from simulation studies showed that pLARmEB was more powerful in QTN detection and more accurate in QTN effect estimation, had less false positive rate and required less computing time than Bayesian hierarchical generalized linear model, efficient mixed model association (EMMA) and least angle regression plus empirical Bayes. pLARmEB, multilocus random-SNP-effect mixed linear model and fast multilocus random-SNP-effect EMMA methods had almost equal power of QTN detection in simulation experiments. However, only pLARmEB identified 48 previously reported genes for 7 flowering time-related traits in Arabidopsis thaliana.

Comparison of Two New Mouse Models of Polygenic Type 2 Diabetes at the Jackson Laboratory, NONcNZO10Lt/J and TALLYHO/JngJ

PubMed Central

Leiter, Edward H.; Strobel, Marjorie; Schultz, David; Schile, Andrew; Reifsnyder, Peter C.

2013-01-01

This review compares two novel polygenic mouse models of type 2 diabetes (T2D), TALLYHO/JngJ and NONcNZO10/LtJ, and contrasts both with the well-known C57BLKS/J-Leprdb (db/db) monogenic diabesity model. We posit that the new polygenic models are more representative of the “garden variety” obesity underlying human T2D in terms of their polygenetic rather than monogenic etiology. Moreover, the clinical phenotypes in these new models are less extreme, for example, more moderated development of obesity coupled with less extreme endocrine disturbances. The more progressive development of obesity produces a maturity-onset development of hyperglycemia in contrast to the juvenile-onset diabetes observed in the morbidly obese db/db model. Unlike the leptin receptor-deficient db/db models with central leptin resistance, the new models develop a progressive peripheral leptin resistance and are able to maintain reproductive function. Although the T2D pathophysiology in both TALLYHO/JngJ and NONcNZO10/LtJ is remarkably similar, their genetic etiologies are clearly different, underscoring the genetic heterogeneity underlying T2D in humans. PMID:23671854

Comparison of Two New Mouse Models of Polygenic Type 2 Diabetes at the Jackson Laboratory, NONcNZO10Lt/J and TALLYHO/JngJ.

PubMed

Leiter, Edward H; Strobel, Marjorie; O'Neill, Adam; Schultz, David; Schile, Andrew; Reifsnyder, Peter C

2013-01-01

This review compares two novel polygenic mouse models of type 2 diabetes (T2D), TALLYHO/JngJ and NONcNZO10/LtJ, and contrasts both with the well-known C57BLKS/J-Lepr(db) (db/db) monogenic diabesity model. We posit that the new polygenic models are more representative of the "garden variety" obesity underlying human T2D in terms of their polygenetic rather than monogenic etiology. Moreover, the clinical phenotypes in these new models are less extreme, for example, more moderated development of obesity coupled with less extreme endocrine disturbances. The more progressive development of obesity produces a maturity-onset development of hyperglycemia in contrast to the juvenile-onset diabetes observed in the morbidly obese db/db model. Unlike the leptin receptor-deficient db/db models with central leptin resistance, the new models develop a progressive peripheral leptin resistance and are able to maintain reproductive function. Although the T2D pathophysiology in both TALLYHO/JngJ and NONcNZO10/LtJ is remarkably similar, their genetic etiologies are clearly different, underscoring the genetic heterogeneity underlying T2D in humans.

S187. SEARCHING FOR BRAIN CO-EXPRESSION MODULES THAT CONTRIBUTE DISPROPORTIONATELY TO THE COMMON POLYGENIC RISK FOR SCHIZOPHRENIA

PubMed Central

Costas, Javier; Paramo, Mario; Arrojo, Manuel

2018-01-01

Abstract Background Genomic research has revealed that schizophrenia is a highly polygenic disease. Recent estimates indicate that at least 71% of genomic segments of 1 Mb include one or more risk loci for schizophrenia (Loh et al., Nature Genet 2015). This extremely high polygenicity represents a challenge to decipher the biological basis of schizophrenia, as it is expected that any set of SNPs with enough size will be associated with the disorder. Among the different gene sets available for study (such as those from Gene Ontology, KEGG pathway, Reactome pathways or protein protein interaction datasets), those based on brain co-expression networks represent putative functional relationships in the relevant tissue. The aim of this work was to identify brain co-expression networks that contribute disproportionately to the common polygenic risk for schizophrenia to get more insight on schizophrenia etiopathology. Methods We analyzed a case -control dataset consisting of 582 schizophrenia patients from Galicia, NW Spain, and 591 ancestrally matched controls, genotyped with the Illumina PsychArray. Using as discovery sample the summary results from the largest GWAS of schizophrenia to date (Psychiatric Genomics Consortium, SCZ2), we generated polygenic risk scores (PRS) in our sample based on SNPs located at genes belonging to brain co-expression modules determined by the CommonMind Consortium (Fromer et al., Nature Neurosci 2016). PRS were generated using the clumping procedure of PLINK, considering several different thresholds to select SNPs from the discovery sample. In order to test if any specific module increased risk to schizophrenia more than expected by their size, we generated up to 10,000 random permutations of the same number of SNPs, matched by frequency, distance to nearest gene, number of SNPs in LD and gene density, using SNPsnap. Results As expected, most modules with enough number of independent SNPs belonging to them showed a significant increase in Nagelkerke’s R2 in our case-control sample after the addition of the module-specific PRS in a logistic regression model. Our permutation strategy revealed that most modules did not show an excess of risk, measured by increase in Nagelkerke’s R2, in comparison to equal number of SNPs with similar characteristics. But one module, M2c from Fromer et al., remained highly significant after multiple tests’ correction. Reactome pathways analysis revealed an over-representation of genes involved in “Neuronal System” and “Axon guidance” among genes from this module. Using the same protocol, we detected that the 84 genes from the neuronal system pathway at this module, representing less than 6% of the genes from the module, explained a higher level of risk than expected. “Voltage-gated Potassium channels” and “Neurexins and neuroligins” are overrepresented among the Neuronal System genes from module M2c. Discussion Here, we show that, in spite of the high polygenicity of schizophrenia, it is possible to identify gene sets contributing disproportionately to total risk, as it was the case for the M2c module from Fromer et al. These authors have previously reported that the M2c module was enriched in GWAS signals, as well as CNVs and rare variants associated with schizophrenia. Therefore, this module shows a disproportionately contribution to schizophrenia risk. Study supported by Grant PI14/01020 from Instituto de Salud Carlos III, Ministry of Health, Spanish Government.

The associations between a polygenic score, reproductive and menstrual risk factors and breast cancer risk.

PubMed

Warren Andersen, Shaneda; Trentham-Dietz, Amy; Gangnon, Ronald E; Hampton, John M; Figueroa, Jonine D; Skinner, Halcyon G; Engelman, Corinne D; Klein, Barbara E; Titus, Linda J; Newcomb, Polly A

2013-07-01

We evaluated whether 13 single nucleotide polymorphisms (SNPs) identified in genome-wide association studies interact with one another and with reproductive and menstrual risk factors in association with breast cancer risk. DNA samples and information on parity, breastfeeding, age at menarche, age at first birth, and age at menopause were collected through structured interviews from 1,484 breast cancer cases and 1,307 controls who participated in a population-based case-control study conducted in three US states. A polygenic score was created as the sum of risk allele copies multiplied by the corresponding log odds estimate. Logistic regression was used to test the associations between SNPs, the score, reproductive and menstrual factors, and breast cancer risk. Nonlinearity of the score was assessed by the inclusion of a quadratic term for polygenic score. Interactions between the aforementioned variables were tested by including a cross-product term in models. We confirmed associations between rs13387042 (2q35), rs4973768 (SLC4A7), rs10941679 (5p12), rs2981582 (FGFR2), rs3817198 (LSP1), rs3803662 (TOX3), and rs6504950 (STXBP4) with breast cancer. Women in the score's highest quintile had 2.2-fold increased risk when compared to women in the lowest quintile (95 % confidence interval: 1.67-2.88). The quadratic polygenic score term was not significant in the model (p = 0.85), suggesting that the established breast cancer loci are not associated with increased risk more than the sum of risk alleles. Modifications of menstrual and reproductive risk factors associations with breast cancer risk by polygenic score were not observed. Our results suggest that the interactions between breast cancer susceptibility loci and reproductive factors are not strong contributors to breast cancer risk.

Whole-Genome Resequencing of Experimental Populations Reveals Polygenic Basis of Egg-Size Variation in Drosophila melanogaster

PubMed Central

Jha, Aashish R.; Miles, Cecelia M.; Lippert, Nodia R.; Brown, Christopher D.; White, Kevin P.; Kreitman, Martin

2015-01-01

Complete genome resequencing of populations holds great promise in deconstructing complex polygenic traits to elucidate molecular and developmental mechanisms of adaptation. Egg size is a classic adaptive trait in insects, birds, and other taxa, but its highly polygenic architecture has prevented high-resolution genetic analysis. We used replicated experimental evolution in Drosophila melanogaster and whole-genome sequencing to identify consistent signatures of polygenic egg-size adaptation. A generalized linear-mixed model revealed reproducible allele frequency differences between replicated experimental populations selected for large and small egg volumes at approximately 4,000 single nucleotide polymorphisms (SNPs). Several hundred distinct genomic regions contain clusters of these SNPs and have lower heterozygosity than the genomic background, consistent with selection acting on polymorphisms in these regions. These SNPs are also enriched among genes expressed in Drosophila ovaries and many of these genes have well-defined functions in Drosophila oogenesis. Additional genes regulating egg development, growth, and cell size show evidence of directional selection as genes regulating these biological processes are enriched for highly differentiated SNPs. Genetic crosses performed with a subset of candidate genes demonstrated that these genes influence egg size, at least in the large genetic background. These findings confirm the highly polygenic architecture of this adaptive trait, and suggest the involvement of many novel candidate genes in regulating egg size. PMID:26044351

Stability and Response of Polygenic Traits to Stabilizing Selection and Mutation

PubMed Central

de Vladar, Harold P.; Barton, Nick

2014-01-01

When polygenic traits are under stabilizing selection, many different combinations of alleles allow close adaptation to the optimum. If alleles have equal effects, all combinations that result in the same deviation from the optimum are equivalent. Furthermore, the genetic variance that is maintained by mutation–selection balance is 2μ/S per locus, where μ is the mutation rate and S the strength of stabilizing selection. In reality, alleles vary in their effects, making the fitness landscape asymmetric and complicating analysis of the equilibria. We show that that the resulting genetic variance depends on the fraction of alleles near fixation, which contribute by 2μ/S, and on the total mutational effects of alleles that are at intermediate frequency. The interplay between stabilizing selection and mutation leads to a sharp transition: alleles with effects smaller than a threshold value of 2μ/S remain polymorphic, whereas those with larger effects are fixed. The genetic load in equilibrium is less than for traits of equal effects, and the fitness equilibria are more similar. We find that if the optimum is displaced, alleles with effects close to the threshold value sweep first, and their rate of increase is bounded by μS. Long-term response leads in general to well-adapted traits, unlike the case of equal effects that often end up at a suboptimal fitness peak. However, the particular peaks to which the populations converge are extremely sensitive to the initial states and to the speed of the shift of the optimum trait value. PMID:24709633

Genetic risk for neurodegenerative disorders, and its overlap with cognitive ability and physical function.

PubMed

Hagenaars, Saskia P; Radaković, Ratko; Crockford, Christopher; Fawns-Ritchie, Chloe; Harris, Sarah E; Gale, Catharine R; Deary, Ian J

2018-01-01

Neurodegenerative disorders are associated with impaired cognitive function and worse physical health outcomes. This study aims to test whether polygenic risk for Alzheimer's disease, Amyotrophic Lateral Sclerosis (ALS), or frontotemporal dementia (FTD) is associated with cognitive function and physical health in the UK Biobank, a cohort of healthy individuals. Group-based analyses were then performed to compare the top and bottom 10% for the three neurodegenerative polygenic risk scores; these groups were compared on the cognitive and physical health variables. Higher polygenic risk for AD, ALS, and FTD was associated with lower cognitive performance. Higher polygenic risk for FTD was also associated with increased forced expiratory volume in 1s and peak expiratory flow. A significant group difference was observed on the symbol digit substitution task between individuals with high polygenic risk for FTD and high polygenic risk for ALS. The results suggest some overlap between polygenic risk for neurodegenerative disorders, cognitive function and physical health.

Whole-Genome Resequencing of Experimental Populations Reveals Polygenic Basis of Egg-Size Variation in Drosophila melanogaster.

PubMed

Jha, Aashish R; Miles, Cecelia M; Lippert, Nodia R; Brown, Christopher D; White, Kevin P; Kreitman, Martin

2015-10-01

Complete genome resequencing of populations holds great promise in deconstructing complex polygenic traits to elucidate molecular and developmental mechanisms of adaptation. Egg size is a classic adaptive trait in insects, birds, and other taxa, but its highly polygenic architecture has prevented high-resolution genetic analysis. We used replicated experimental evolution in Drosophila melanogaster and whole-genome sequencing to identify consistent signatures of polygenic egg-size adaptation. A generalized linear-mixed model revealed reproducible allele frequency differences between replicated experimental populations selected for large and small egg volumes at approximately 4,000 single nucleotide polymorphisms (SNPs). Several hundred distinct genomic regions contain clusters of these SNPs and have lower heterozygosity than the genomic background, consistent with selection acting on polymorphisms in these regions. These SNPs are also enriched among genes expressed in Drosophila ovaries and many of these genes have well-defined functions in Drosophila oogenesis. Additional genes regulating egg development, growth, and cell size show evidence of directional selection as genes regulating these biological processes are enriched for highly differentiated SNPs. Genetic crosses performed with a subset of candidate genes demonstrated that these genes influence egg size, at least in the large genetic background. These findings confirm the highly polygenic architecture of this adaptive trait, and suggest the involvement of many novel candidate genes in regulating egg size. © The Author 2015. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.

Association between polygenic risk for schizophrenia, neurocognition and social cognition across development

PubMed Central

Germine, L; Robinson, E B; Smoller, J W; Calkins, M E; Moore, T M; Hakonarson, H; Daly, M J; Lee, P H; Holmes, A J; Buckner, R L; Gur, R C; Gur, R E

2016-01-01

Breakthroughs in genomics have begun to unravel the genetic architecture of schizophrenia risk, providing methods for quantifying schizophrenia polygenic risk based on common genetic variants. Our objective in the current study was to understand the relationship between schizophrenia genetic risk variants and neurocognitive development in healthy individuals. We first used combined genomic and neurocognitive data from the Philadelphia Neurodevelopmental Cohort (4303 participants ages 8–21 years) to screen 26 neurocognitive phenotypes for their association with schizophrenia polygenic risk. Schizophrenia polygenic risk was estimated for each participant based on summary statistics from the most recent schizophrenia genome-wide association analysis (Psychiatric Genomics Consortium 2014). After correction for multiple comparisons, greater schizophrenia polygenic risk was significantly associated with reduced speed of emotion identification and verbal reasoning. These associations were significant by age 9 years and there was no evidence of interaction between schizophrenia polygenic risk and age on neurocognitive performance. We then looked at the association between schizophrenia polygenic risk and emotion identification speed in the Harvard/MGH Brain Genomics Superstruct Project sample (695 participants ages 18–35 years), where we replicated the association between schizophrenia polygenic risk and emotion identification speed. These analyses provide evidence for a replicable association between polygenic risk for schizophrenia and a specific aspect of social cognition. Our findings indicate that individual differences in genetic risk for schizophrenia are linked with the development of aspects of social cognition and potentially verbal reasoning, and that these associations emerge relatively early in development. PMID:27754483

Association between polygenic risk for schizophrenia, neurocognition and social cognition across development.

PubMed

Germine, L; Robinson, E B; Smoller, J W; Calkins, M E; Moore, T M; Hakonarson, H; Daly, M J; Lee, P H; Holmes, A J; Buckner, R L; Gur, R C; Gur, R E

2016-10-18

Breakthroughs in genomics have begun to unravel the genetic architecture of schizophrenia risk, providing methods for quantifying schizophrenia polygenic risk based on common genetic variants. Our objective in the current study was to understand the relationship between schizophrenia genetic risk variants and neurocognitive development in healthy individuals. We first used combined genomic and neurocognitive data from the Philadelphia Neurodevelopmental Cohort (4303 participants ages 8-21 years) to screen 26 neurocognitive phenotypes for their association with schizophrenia polygenic risk. Schizophrenia polygenic risk was estimated for each participant based on summary statistics from the most recent schizophrenia genome-wide association analysis (Psychiatric Genomics Consortium 2014). After correction for multiple comparisons, greater schizophrenia polygenic risk was significantly associated with reduced speed of emotion identification and verbal reasoning. These associations were significant by age 9 years and there was no evidence of interaction between schizophrenia polygenic risk and age on neurocognitive performance. We then looked at the association between schizophrenia polygenic risk and emotion identification speed in the Harvard/MGH Brain Genomics Superstruct Project sample (695 participants ages 18-35 years), where we replicated the association between schizophrenia polygenic risk and emotion identification speed. These analyses provide evidence for a replicable association between polygenic risk for schizophrenia and a specific aspect of social cognition. Our findings indicate that individual differences in genetic risk for schizophrenia are linked with the development of aspects of social cognition and potentially verbal reasoning, and that these associations emerge relatively early in development.

Genetic contribution to 'theory of mind' in adolescence.

PubMed

Warrier, Varun; Baron-Cohen, Simon

2018-02-22

Difficulties in 'theory of mind' (the ability to attribute mental states to oneself or others, and to make predictions about another's behaviour based on these attributions) have been observed in several psychiatric conditions. We investigate the genetic architecture of theory of mind in 4,577 13-year-olds who completed the Emotional Triangles Task (Triangles Task), a first-order test of theory of mind. We observe a small but significant female-advantage on the Triangles Task (Cohen's d = 0.19, P < 0.01), in keeping with previous work using other tests of theory of mind. Genome-wide association analyses did not identify any significant loci, and SNP heritability was non-significant. Polygenic scores for six psychiatric conditions (ADHD, anorexia, autism, bipolar disorder, depression, and schizophrenia), and empathy were not associated with scores on the Triangles Task. However, polygenic scores of cognitive aptitude, and cognitive empathy, a term synonymous with theory of mind and measured using the "Reading the Mind in the Eyes" Test, were significantly associated with scores on the Triangles Task at multiple P-value thresholds, suggesting shared genetics between different measures of theory of mind and cognition.

Polygenic influences on dyslipidemias.

PubMed

Dron, Jacqueline S; Hegele, Robert A

2018-04-01

Rare large-effect genetic variants underlie monogenic dyslipidemias, whereas common small-effect genetic variants - single nucleotide polymorphisms (SNPs) - have modest influences on lipid traits. Over the past decade, these small-effect SNPs have been shown to cumulatively exert consistent effects on lipid phenotypes under a polygenic framework, which is the focus of this review. Several groups have reported polygenic risk scores assembled from lipid-associated SNPs, and have applied them to their respective phenotypes. For lipid traits in the normal population distribution, polygenic effects quantified by a score that integrates several common polymorphisms account for about 20-30% of genetic variation. Among individuals at the extremes of the distribution, that is, those with clinical dyslipidemia, the polygenic component includes both rare variants with large effects and common polymorphisms: depending on the trait, 20-50% of susceptibility can be accounted for by this assortment of genetic variants. Accounting for polygenic effects increases the numbers of dyslipidemic individuals who can be explained genetically, but a substantial proportion of susceptibility remains unexplained. Whether documenting the polygenic basis of dyslipidemia will affect outcomes in clinical trials or prospective observational studies remains to be determined.

Polygenic risk of Alzheimer disease is associated with early- and late-life processes.

PubMed

Mormino, Elizabeth C; Sperling, Reisa A; Holmes, Avram J; Buckner, Randy L; De Jager, Philip L; Smoller, Jordan W; Sabuncu, Mert R

2016-08-02

To examine associations between aggregate genetic risk and Alzheimer disease (AD) markers in stages preceding the clinical symptoms of dementia using data from 2 large observational cohort studies. We computed polygenic risk scores (PGRS) using summary statistics from the International Genomics of Alzheimer's Project genome-wide association study of AD. Associations between PGRS and AD markers (cognitive decline, clinical progression, hippocampus volume, and β-amyloid) were assessed within older participants with dementia. Associations between PGRS and hippocampus volume were additionally examined within healthy younger participants (age 18-35 years). Within participants without dementia, elevated PGRS was associated with worse memory (p = 0.002) and smaller hippocampus (p = 0.002) at baseline, as well as greater longitudinal cognitive decline (memory: p = 0.0005, executive function: p = 0.01) and clinical progression (p < 0.00001). High PGRS was associated with AD-like levels of β-amyloid burden as measured with florbetapir PET (p = 0.03) but did not reach statistical significance for CSF β-amyloid (p = 0.11). Within the younger group, higher PGRS was associated with smaller hippocampus volume (p = 0.05). This pattern was evident when examining a PGRS that included many loci below the genome-wide association study (GWAS)-level significance threshold (16,123 single nucleotide polymorphisms), but not when PGRS was restricted to GWAS-level significant loci (18 single nucleotide polymorphisms). Effects related to common genetic risk loci distributed throughout the genome are detectable among individuals without dementia. The influence of this genetic risk may begin in early life and make an individual more susceptible to cognitive impairment in late life. Future refinement of polygenic risk scores may help identify individuals at risk for AD dementia. © 2016 American Academy of Neurology.

Polygenic risk of Alzheimer disease is associated with early- and late-life processes

PubMed Central

Sperling, Reisa A.; Holmes, Avram J.; Buckner, Randy L.; De Jager, Philip L.; Smoller, Jordan W.; Sabuncu, Mert R.

2016-01-01

Objective: To examine associations between aggregate genetic risk and Alzheimer disease (AD) markers in stages preceding the clinical symptoms of dementia using data from 2 large observational cohort studies. Methods: We computed polygenic risk scores (PGRS) using summary statistics from the International Genomics of Alzheimer's Project genome-wide association study of AD. Associations between PGRS and AD markers (cognitive decline, clinical progression, hippocampus volume, and β-amyloid) were assessed within older participants with dementia. Associations between PGRS and hippocampus volume were additionally examined within healthy younger participants (age 18–35 years). Results: Within participants without dementia, elevated PGRS was associated with worse memory (p = 0.002) and smaller hippocampus (p = 0.002) at baseline, as well as greater longitudinal cognitive decline (memory: p = 0.0005, executive function: p = 0.01) and clinical progression (p < 0.00001). High PGRS was associated with AD-like levels of β-amyloid burden as measured with florbetapir PET (p = 0.03) but did not reach statistical significance for CSF β-amyloid (p = 0.11). Within the younger group, higher PGRS was associated with smaller hippocampus volume (p = 0.05). This pattern was evident when examining a PGRS that included many loci below the genome-wide association study (GWAS)–level significance threshold (16,123 single nucleotide polymorphisms), but not when PGRS was restricted to GWAS-level significant loci (18 single nucleotide polymorphisms). Conclusions: Effects related to common genetic risk loci distributed throughout the genome are detectable among individuals without dementia. The influence of this genetic risk may begin in early life and make an individual more susceptible to cognitive impairment in late life. Future refinement of polygenic risk scores may help identify individuals at risk for AD dementia. PMID:27385740

Polygenic variation maintained by balancing selection: pleiotropy, sex-dependent allelic effects and G x E interactions.

PubMed Central

Turelli, Michael; Barton, N H

2004-01-01

We investigate three alternative selection-based scenarios proposed to maintain polygenic variation: pleiotropic balancing selection, G x E interactions (with spatial or temporal variation in allelic effects), and sex-dependent allelic effects. Each analysis assumes an additive polygenic trait with n diallelic loci under stabilizing selection. We allow loci to have different effects and consider equilibria at which the population mean departs from the stabilizing-selection optimum. Under weak selection, each model produces essentially identical, approximate allele-frequency dynamics. Variation is maintained under pleiotropic balancing selection only at loci for which the strength of balancing selection exceeds the effective strength of stabilizing selection. In addition, for all models, polymorphism requires that the population mean be close enough to the optimum that directional selection does not overwhelm balancing selection. This balance allows many simultaneously stable equilibria, and we explore their properties numerically. Both spatial and temporal G x E can maintain variation at loci for which the coefficient of variation (across environments) of the effect of a substitution exceeds a critical value greater than one. The critical value depends on the correlation between substitution effects at different loci. For large positive correlations (e.g., rho(ij)2>3/4), even extreme fluctuations in allelic effects cannot maintain variation. Surprisingly, this constraint on correlations implies that sex-dependent allelic effects cannot maintain polygenic variation. We present numerical results that support our analytical approximations and discuss our results in connection to relevant data and alternative variance-maintaining mechanisms. PMID:15020487

Prefrontal gray matter volume mediates genetic risks for obesity.

PubMed

Opel, N; Redlich, R; Kaehler, C; Grotegerd, D; Dohm, K; Heindel, W; Kugel, H; Thalamuthu, A; Koutsouleris, N; Arolt, V; Teuber, A; Wersching, H; Baune, B T; Berger, K; Dannlowski, U

2017-05-01

Genetic and neuroimaging research has identified neurobiological correlates of obesity. However, evidence for an integrated model of genetic risk and brain structural alterations in the pathophysiology of obesity is still absent. Here we investigated the relationship between polygenic risk for obesity, gray matter structure and body mass index (BMI) by the use of univariate and multivariate analyses in two large, independent cohorts (n=330 and n=347). Higher BMI and higher polygenic risk for obesity were significantly associated with medial prefrontal gray matter decrease, and prefrontal gray matter was further shown to significantly mediate the effect of polygenic risk for obesity on BMI in both samples. Building on this, the successful individualized prediction of BMI by means of multivariate pattern classification algorithms trained on whole-brain imaging data and external validations in the second cohort points to potential clinical applications of this imaging trait marker.

Early-acting inbreeding depression and reproductive success in the highbush blueberry, Vaccinium corymbosum L.

PubMed

Krebs, S L; Hancock, J F

1990-06-01

Tetraploid Vaccinium corymbosum genotypes exhibit wide variability in seed set following self- and cross-pollinations. In this paper, a post-zygotic mechanism (seed abortion) under polygenic control is proposed as the basis for fertility differences in this species. A pollen chase experiment indicated that self-pollen tubes fertilize ovules, but are also 'outcompeted' by foreign male gametes in pollen mixtures. Matings among cultivars derived from a pedigree showed a linear decrease in seed number per fruit, and increase in seed abortion, with increasing relatedness among parents. Selfed (S1) progeny from self-fertile parents were largely self-sterile. At zygotic levels of inbreeding of F>0.3 there was little or no fertility, suggesting that an inbreeding threshold regulates reproductive success in V. corymbosum matings. Individuals below the threshold are facultative selfers, while those above it are obligate outcrossers. Inbreeding also caused a decrease in pollen viability, and reduced female fertility more rapidly than male fertility. These phenomena are discussed in terms of two models of genetic load: (1) mutational load - homozygosity for recessive embryolethal or sub-lethal mutations and (2) segregational load - loss of allelic interactions essential for embryonic vigor. Self-infertility in highbush blueberries is placed in the context of 'late-acting' self-incompatibility versus 'early-acting' inbreeding depression in angiosperms.

The Genetics of Success: How Single-Nucleotide Polymorphisms Associated With Educational Attainment Relate to Life-Course Development.

PubMed

Belsky, Daniel W; Moffitt, Terrie E; Corcoran, David L; Domingue, Benjamin; Harrington, HonaLee; Hogan, Sean; Houts, Renate; Ramrakha, Sandhya; Sugden, Karen; Williams, Benjamin S; Poulton, Richie; Caspi, Avshalom

2016-07-01

A previous genome-wide association study (GWAS) of more than 100,000 individuals identified molecular-genetic predictors of educational attainment. We undertook in-depth life-course investigation of the polygenic score derived from this GWAS using the four-decade Dunedin Study (N = 918). There were five main findings. First, polygenic scores predicted adult economic outcomes even after accounting for educational attainments. Second, genes and environments were correlated: Children with higher polygenic scores were born into better-off homes. Third, children's polygenic scores predicted their adult outcomes even when analyses accounted for their social-class origins; social-mobility analysis showed that children with higher polygenic scores were more upwardly mobile than children with lower scores. Fourth, polygenic scores predicted behavior across the life course, from early acquisition of speech and reading skills through geographic mobility and mate choice and on to financial planning for retirement. Fifth, polygenic-score associations were mediated by psychological characteristics, including intelligence, self-control, and interpersonal skill. Effect sizes were small. Factors connecting DNA sequence with life outcomes may provide targets for interventions to promote population-wide positive development. © The Author(s) 2016.

Polygenic scores predict alcohol problems in an independent sample and show moderation by the environment.

PubMed

Salvatore, Jessica E; Aliev, Fazil; Edwards, Alexis C; Evans, David M; Macleod, John; Hickman, Matthew; Lewis, Glyn; Kendler, Kenneth S; Loukola, Anu; Korhonen, Tellervo; Latvala, Antti; Rose, Richard J; Kaprio, Jaakko; Dick, Danielle M

2014-04-10

Alcohol problems represent a classic example of a complex behavioral outcome that is likely influenced by many genes of small effect. A polygenic approach, which examines aggregate measured genetic effects, can have predictive power in cases where individual genes or genetic variants do not. In the current study, we first tested whether polygenic risk for alcohol problems-derived from genome-wide association estimates of an alcohol problems factor score from the age 18 assessment of the Avon Longitudinal Study of Parents and Children (ALSPAC; n = 4304 individuals of European descent; 57% female)-predicted alcohol problems earlier in development (age 14) in an independent sample (FinnTwin12; n = 1162; 53% female). We then tested whether environmental factors (parental knowledge and peer deviance) moderated polygenic risk to predict alcohol problems in the FinnTwin12 sample. We found evidence for both polygenic association and for additive polygene-environment interaction. Higher polygenic scores predicted a greater number of alcohol problems (range of Pearson partial correlations 0.07-0.08, all p-values ≤ 0.01). Moreover, genetic influences were significantly more pronounced under conditions of low parental knowledge or high peer deviance (unstandardized regression coefficients (b), p-values (p), and percent of variance (R2) accounted for by interaction terms: b = 1.54, p = 0.02, R2 = 0.33%; b = 0.94, p = 0.04, R2 = 0.30%, respectively). Supplementary set-based analyses indicated that the individual top single nucleotide polymorphisms (SNPs) contributing to the polygenic scores were not individually enriched for gene-environment interaction. Although the magnitude of the observed effects are small, this study illustrates the usefulness of polygenic approaches for understanding the pathways by which measured genetic predispositions come together with environmental factors to predict complex behavioral outcomes.

The Genetics of Success: How SNPs Associated with Educational Attainment Relate to Life-Course Development

PubMed Central

Belsky, Daniel W; Moffitt, Terrie E; Corcoran, David L; Domingue, Benjamin; Harrington, HonaLee; Hogan, Sean; Houts, Renate; Ramrakha, Sandhya; Sugden, Karen; Williams, Benjamin; Poulton, Richie; Caspi, Avshalom

2016-01-01

Previous genome-wide association analysis (GWAS) of >100,000 individuals identified molecular-genetic predictors of educational attainment. We undertook in-depth life-course investigation of the polygenic score derived from this GWAS using the four-decade Dunedin Study (N=918). There were five main findings. First, polygenic scores predicted adult economic outcomes over and above completed education. Second, genes and environments were correlated; children with higher polygenic scores were born into better-off homes. Third, polygenic scores predicted children’s adult outcomes net of social-class origins; children with higher scores tended to be upwardly-socially-mobile. Fourth, polygenic scores predicted behavior across the life-course, from learning to talk earlier to acquiring reading skills more quickly, through geographic mobility and mate choice, on to financial planning for retirement. Fifth, polygenic-score associations were mediated by psychological characteristics including intelligence, self-control, and interpersonal skill. Effects were small. Factors connecting DNA sequence with life outcomes may provide targets for interventions to promote population-wide positive development. PMID:27251486

Prediction of individual genetic risk to prostate cancer using a polygenic score.

PubMed

Szulkin, Robert; Whitington, Thomas; Eklund, Martin; Aly, Markus; Eeles, Rosalind A; Easton, Douglas; Kote-Jarai, Z Sofia; Amin Al Olama, Ali; Benlloch, Sara; Muir, Kenneth; Giles, Graham G; Southey, Melissa C; Fitzgerald, Liesel M; Henderson, Brian E; Schumacher, Fredrick; Haiman, Christopher A; Schleutker, Johanna; Wahlfors, Tiina; Tammela, Teuvo L J; Nordestgaard, Børge G; Key, Tim J; Travis, Ruth C; Neal, David E; Donovan, Jenny L; Hamdy, Freddie C; Pharoah, Paul; Pashayan, Nora; Khaw, Kay-Tee; Stanford, Janet L; Thibodeau, Stephen N; McDonnell, Shannon K; Schaid, Daniel J; Maier, Christiane; Vogel, Walther; Luedeke, Manuel; Herkommer, Kathleen; Kibel, Adam S; Cybulski, Cezary; Lubiński, Jan; Kluźniak, Wojciech; Cannon-Albright, Lisa; Brenner, Hermann; Butterbach, Katja; Stegmaier, Christa; Park, Jong Y; Sellers, Thomas; Lin, Hui-Yi; Lim, Hui-Yi; Slavov, Chavdar; Kaneva, Radka; Mitev, Vanio; Batra, Jyotsna; Clements, Judith A; Spurdle, Amanda; Teixeira, Manuel R; Paulo, Paula; Maia, Sofia; Pandha, Hardev; Michael, Agnieszka; Kierzek, Andrzej; Gronberg, Henrik; Wiklund, Fredrik

2015-09-01

Polygenic risk scores comprising established susceptibility variants have shown to be informative classifiers for several complex diseases including prostate cancer. For prostate cancer it is unknown if inclusion of genetic markers that have so far not been associated with prostate cancer risk at a genome-wide significant level will improve disease prediction. We built polygenic risk scores in a large training set comprising over 25,000 individuals. Initially 65 established prostate cancer susceptibility variants were selected. After LD pruning additional variants were prioritized based on their association with prostate cancer. Six-fold cross validation was performed to assess genetic risk scores and optimize the number of additional variants to be included. The final model was evaluated in an independent study population including 1,370 cases and 1,239 controls. The polygenic risk score with 65 established susceptibility variants provided an area under the curve (AUC) of 0.67. Adding an additional 68 novel variants significantly increased the AUC to 0.68 (P = 0.0012) and the net reclassification index with 0.21 (P = 8.5E-08). All novel variants were located in genomic regions established as associated with prostate cancer risk. Inclusion of additional genetic variants from established prostate cancer susceptibility regions improves disease prediction. © 2015 Wiley Periodicals, Inc.

Individual and shared effects of social environment and polygenic risk scores on adolescent body mass index.

PubMed

Coleman, Jonathan R I; Krapohl, Eva; Eley, Thalia C; Breen, Gerome

2018-04-20

Juvenile obesity is associated with adverse health outcomes. Understanding genetic and environmental influences on body mass index (BMI) during adolescence could inform interventions. We investigated independent and interactive effects of parenting, socioeconomic status (SES) and polygenic risk on BMI pre-adolescence, and on the rate of change in BMI across adolescence. Genome-wide genotype data, BMI and child perceptions of parental warmth and punitive discipline were available at 11 years old, and parental SES was available from birth on 3,414 unrelated participants. Linear models were used to test the effects of social environment and polygenic risk on pre-adolescent BMI. Change in BMI across adolescence was assessed in a subset (N = 1943). Sex-specific effects were assessed. Higher genetic risk was associated with increased BMI pre-adolescence and across adolescence (p < 0.00417, corrected for multiple tests). Negative parenting was not significantly associated with either phenotype, but lower SES was associated with increased BMI pre-adolescence. No interactions passed correction for multiple testing. Polygenic risk scores from adult GWAS meta-analyses are associated with BMI in juveniles, suggesting a stable genetic component. Pre-adolescent BMI was associated with social environment, but parental style has, at most, a small effect.

Personality Polygenes, Positive Affect, and Life Satisfaction

PubMed Central

Weiss, Alexander; Baselmans, Bart M. L.; Hofer, Edith; Yang, Jingyun; Okbay, Aysu; Lind, Penelope A.; Miller, Mike B.; Nolte, Ilja M.; Zhao, Wei; Hagenaars, Saskia P.; Hottenga, Jouke-Jan; Matteson, Lindsay K.; Snieder, Harold; Faul, Jessica D.; Hartman, Catharina A.; Boyle, Patricia A.; Tiemeier, Henning; Mosing, Miriam A.; Pattie, Alison; Davies, Gail; Liewald, David C.; Schmidt, Reinhold; De Jager, Philip L.; Heath, Andrew C.; Jokela, Markus; Starr, John M.; Oldehinkel, Albertine J.; Johannesson, Magnus; Cesarini, David; Hofman, Albert; Harris, Sarah E.; Smith, Jennifer A.; Keltikangas-Järvinen, Liisa; Pulkki-Råback, Laura; Schmidt, Helena; Smith, Jacqui; Iacono, William G.; McGue, Matt; Bennett, David A.; Pedersen, Nancy L.; Magnusson, Patrik K. E.; Deary, Ian J.; Martin, Nicholas G.; Boomsma, Dorret I.; Bartels, Meike; Luciano, Michelle

2016-01-01

Approximately half of the variation in wellbeing measures overlaps with variation in personality traits. Studies of non-human primate pedigrees and human twins suggest that this is due to common genetic influences. We tested whether personality polygenic scores for the NEO Five-Factor Inventory (NEO-FFI) domains and for item response theory (IRT) derived extraversion and neuroticism scores predict variance in wellbeing measures. Polygenic scores were based on published genome-wide association (GWA) results in over 17,000 individuals for the NEO-FFI and in over 63,000 for the IRT extraversion and neuroticism traits. The NEO-FFI polygenic scores were used to predict life satisfaction in 7 cohorts, positive affect in 12 cohorts, and general wellbeing in 1 cohort (maximal N = 46,508). Meta-analysis of these results showed no significant association between NEO-FFI personality polygenic scores and the wellbeing measures. IRT extraversion and neuroticism polygenic scores were used to predict life satisfaction and positive affect in almost 37,000 individuals from UK Biobank. Significant positive associations (effect sizes <0.05%) were observed between the extraversion polygenic score and wellbeing measures, and a negative association was observed between the polygenic neuroticism score and life satisfaction. Furthermore, using GWA data, genetic correlations of −0.49 and −0.55 were estimated between neuroticism with life satisfaction and positive affect, respectively. The moderate genetic correlation between neuroticism and wellbeing is in line with twin research showing that genetic influences on wellbeing are also shared with other independent personality domains. PMID:27546527

The TallyHo polygenic mouse model of diabetes: implications in wound healing.

PubMed

Buck, Donald W; Jin, Da P; Geringer, Matthew; Hong, Seok Jong; Galiano, Robert D; Mustoe, Thomas A

2011-11-01

Impairments in wound healing represent a significant source of morbidity and mortality in patients with diabetes. To help uncover the derangements associated with diabetic wound healing, murine animal models have been extensively used. In this article, the authors present results, and the accompanying wound healing implications, from experiments across three validated wound healing models using a newer polygenic strain of diabetes. The authors investigated the wound healing impairments of the TallyHo/JnJ diabetic mouse strain, using three validated wound healing models: an incisional model, a splinted excisional model, and a cutaneous ischemia-reperfusion injury model. Appropriate control strain mice were used for comparison. Wounds were analyzed using gross, histologic, and molecular techniques. TallyHo mice displayed deficits across all three wound healing models. There was a reduced resistance/response to oxidative stress and a global decrease in the initial inflammatory response to healing. In addition, there was a global decrease in the stimulus for angiogenesis and collagen formation, ultimately leading to reduced reepithelialization, granulation tissue formation, wound contraction, and wound tensile strength. Gross and histologic findings were corroborated with molecular data, which revealed a significant down-regulation of important cytokines, including vascular endothelial growth factor, neutrophilic attractant protein-2, monocyte chemoattractant protien-1, heme oxygenase-1, interleukin-1β, and interleukin-6, when normalized to the control strain (p<0.05). The TallyHo polygenic mouse model of diabetes demonstrates predictable and clinically relevant wound healing impairments that offer important implications into the derangements of diabetic wound healing observed clinically. Therapeutics targeting these specific derangements could provide improvements in the care of diabetic wounds.

Major depressive disorder and current psychological distress moderate the effect of polygenic risk for obesity on body mass index.

PubMed

Clarke, T-K; Hall, L S; Fernandez-Pujals, A M; MacIntyre, D J; Thomson, P; Hayward, C; Smith, B H; Padmanabhan, S; Hocking, L J; Deary, I J; Porteous, D J; McIntosh, A M

2015-06-30

Major depressive disorder (MDD) and obesity are frequently co-morbid and this correlation is partly due to genetic factors. Although specific genetic risk variants are associated with body mass index (BMI) and with larger effect sizes in depressed individuals, the genetic overlap and interaction with depression has not been addressed using whole-genome data. Polygenic profile scores for MDD and BMI were created in 13,921 members of Generation Scotland: the Scottish Family Health Study and tested for their association with BMI, MDD, neuroticism and scores on the General Health Questionnaire (GHQ) (current psychological distress). The association between BMI polygenic profile scores and BMI was tested fitting GHQ, neuroticism or MDD status as an interaction term to test for a moderating effect of mood disorder. BMI polygenic profile scores were not associated with lifetime MDD status or neuroticism although a significant positive association with GHQ scores was found (P = 0.0001, β = 0.034, r(2) = 0.001). Polygenic risk for MDD was not associated with BMI. A significant interaction between BMI polygenic profile scores and MDD (P = 0.0003, β = 0.064), GHQ (P = 0.0005, β = 0.027) and neuroticism (P = 0.003, β = 0.023) was found when BMI was the dependent variable. The effect of BMI-increasing alleles was greater in those with MDD, high neuroticism or current psychological distress. MDD, neuroticism and current psychological distress amplify the effect of BMI polygenic profile scores on BMI. Depressed individuals with a greater polygenic load for obesity are at greater risk of becoming obese than control individuals.

Genetic Predisposition to Obesity and Medicare Expenditures.

PubMed

Wehby, George L; Domingue, Benjamin W; Ullrich, Fred; Wolinsky, Fredric D

2017-12-12

The relationship between obesity and health expenditures is not well understood. We examined the relationship between genetic predisposition to obesity measured by a polygenic risk score for body mass index (BMI) and Medicare expenditures. Biennial interview data from the Health and Retirement Survey for a nationally representative sample of older adults enrolled in fee-for-service Medicare were obtained from 1991 through 2010 and linked to Medicare claims for the same period and to Genome-Wide Association Study (GWAS) data. The study included 6,628 Medicare beneficiaries who provided 68,627 complete person-year observations during the study period. Outcomes were total and service-specific Medicare expenditures and indicators for expenditures exceeding the 75th and 90th percentiles. The BMI polygenic risk score was derived from GWAS data. Regression models were used to examine how the BMI polygenic risk score was related to health expenditures adjusting for demographic factors and GWAS-derived ancestry. Greater genetic predisposition to obesity was associated with higher Medicare expenditures. Specifically, a 1 SD increase in the BMI polygenic risk score was associated with a $805 (p < .001) increase in annual Medicare expenditures per person in 2010 dollars (~15% increase), a $370 (p < .001) increase in inpatient expenses, and a $246 (p < .001) increase in outpatient services. A 1 SD increase in the polygenic risk score was also related to increased likelihood of expenditures exceeding the 75th percentile by 18% (95% CI: 10%-28%) and the 90th percentile by 27% (95% CI: 15%-40%). Greater genetic predisposition to obesity is associated with higher Medicare expenditures. © The Author(s) 2017. Published by Oxford University Press on behalf of The Gerontological Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Bayesian segregation analysis of production traits in two strains of laying chickens.

PubMed

Szydłowski, M; Szwaczkowski, T

2001-02-01

A bayesian marker-free segregation analysis was applied to search for evidence of segregating genes affecting production traits in two strains of laying hens under long-term selection. The study used data from 6 generations of Leghorn (H77) and New Hampshire (N88) breeding nuclei. Estimation of marginal posterior means of variance components and parameters of a single autosomal locus was performed by use of the Gibbs sampler. The results showed evidence for a mixed major gene: -polygenic inheritance of BW and age at sexual maturity (ASM) in both strains. Single genes affecting BW and ASM explained one-third of the genetic variance. For ASM large overdominance effect at single locus was estimated. Initial egg production (IEP) and average egg weight (EW) showed a polygenic model of inheritance. The polygenic heritability estimates for BW, ASM, IEP, and EW were 0.32, 0.25, 0.23, and 0.08 in Strain H77 and 0.25, 0.24, 0.11, and 0.38 in Strain N88, respectively.

Trans-10, cis-12-conjugated linoleic acid alters hepatic gene expression in a polygenic obese line of mice displaying hepatic lipidosis.

PubMed

Ashwell, Melissa S; Ceddia, Ryan P; House, Ralph L; Cassady, Joseph P; Eisen, Eugene J; Eling, Thomas E; Collins, Jennifer B; Grissom, Sherry F; Odle, Jack

2010-09-01

The trans-10, cis-12 isomer of conjugated linoleic acid (CLA) causes a rapid reduction of body and adipose mass in mice. In addition to changes in adipose tissue, numerous studies have reported alterations in hepatic lipid metabolism. Livers of CLA-fed mice gain mass, partly due to lipid accumulation; however, the precise molecular mechanisms are unknown. To elucidate these mechanisms, we examined fatty acid composition and gene expression profiles of livers from a polygenic obese line of mice fed 1% trans-10, cis-12-CLA for 14 days. Analysis of gene expression data led to the identification of 1393 genes differentially expressed in the liver of CLA-fed male mice at a nominal P value of .01, and 775 were considered significant using a false discovery rate (FDR) threshold of .05. While surprisingly few genes in lipid metabolism were impacted, pathway analysis found that protein kinase A (PKA) and cyclic adenosine monophosphate (cAMP) pathways signaling pathways were affected by CLA treatment and 98 of the 775 genes were found to be regulated by hepatocyte nuclear factor 4alpha, a transcription factor important in controlling liver metabolic status. Copyright 2010 Elsevier Inc. All rights reserved.

Polygenic scores via penalized regression on summary statistics.

PubMed

Mak, Timothy Shin Heng; Porsch, Robert Milan; Choi, Shing Wan; Zhou, Xueya; Sham, Pak Chung

2017-09-01

Polygenic scores (PGS) summarize the genetic contribution of a person's genotype to a disease or phenotype. They can be used to group participants into different risk categories for diseases, and are also used as covariates in epidemiological analyses. A number of possible ways of calculating PGS have been proposed, and recently there is much interest in methods that incorporate information available in published summary statistics. As there is no inherent information on linkage disequilibrium (LD) in summary statistics, a pertinent question is how we can use LD information available elsewhere to supplement such analyses. To answer this question, we propose a method for constructing PGS using summary statistics and a reference panel in a penalized regression framework, which we call lassosum. We also propose a general method for choosing the value of the tuning parameter in the absence of validation data. In our simulations, we showed that pseudovalidation often resulted in prediction accuracy that is comparable to using a dataset with validation phenotype and was clearly superior to the conservative option of setting the tuning parameter of lassosum to its lowest value. We also showed that lassosum achieved better prediction accuracy than simple clumping and P-value thresholding in almost all scenarios. It was also substantially faster and more accurate than the recently proposed LDpred. © 2017 WILEY PERIODICALS, INC.

pKWmEB: integration of Kruskal-Wallis test with empirical Bayes under polygenic background control for multi-locus genome-wide association study.

PubMed

Ren, Wen-Long; Wen, Yang-Jun; Dunwell, Jim M; Zhang, Yuan-Ming

2018-03-01

Although nonparametric methods in genome-wide association studies (GWAS) are robust in quantitative trait nucleotide (QTN) detection, the absence of polygenic background control in single-marker association in genome-wide scans results in a high false positive rate. To overcome this issue, we proposed an integrated nonparametric method for multi-locus GWAS. First, a new model transformation was used to whiten the covariance matrix of polygenic matrix K and environmental noise. Using the transferred model, Kruskal-Wallis test along with least angle regression was then used to select all the markers that were potentially associated with the trait. Finally, all the selected markers were placed into multi-locus model, these effects were estimated by empirical Bayes, and all the nonzero effects were further identified by a likelihood ratio test for true QTN detection. This method, named pKWmEB, was validated by a series of Monte Carlo simulation studies. As a result, pKWmEB effectively controlled false positive rate, although a less stringent significance criterion was adopted. More importantly, pKWmEB retained the high power of Kruskal-Wallis test, and provided QTN effect estimates. To further validate pKWmEB, we re-analyzed four flowering time related traits in Arabidopsis thaliana, and detected some previously reported genes that were not identified by the other methods.

Frequencies of Null Alleles at Enzyme Loci in Natural Populations of Ponderosa and Red Pine

PubMed Central

Allendorf, Fred W.; Knudsen, Kathy L.; Blake, George M.

1982-01-01

Pinus ponderosa and P. resinosa population samples have mean frequencies of enzymatically inactive alleles of 0.0031 and 0.0028 at 29 and 27 enzyme loci, respectively. Such alleles are rare and are apparently maintained by selection-mutation balance. Ponderosa pine have much higher amounts of allozymic and polygenic phenotypic variation than red pine, yet both species have similar frequencies of null alleles. Thus, null alleles apparently do not contribute to polygenic variation, as has been suggested. The concordance between allozymic and polygenic variation adds support to the view that allozyme studies may be valuable in predicting the relative amount of polygenic variation in populations. PMID:17246067

LD Score Regression Distinguishes Confounding from Polygenicity in Genome-Wide Association Studies

PubMed Central

Bulik-Sullivan, Brendan K.; Loh, Po-Ru; Finucane, Hilary; Ripke, Stephan; Yang, Jian; Patterson, Nick; Daly, Mark J.; Price, Alkes L.; Neale, Benjamin M.

2015-01-01

Both polygenicity (i.e., many small genetic effects) and confounding biases, such as cryptic relatedness and population stratification, can yield an inflated distribution of test statistics in genome-wide association studies (GWAS). However, current methods cannot distinguish between inflation from true polygenic signal and bias. We have developed an approach, LD Score regression, that quantifies the contribution of each by examining the relationship between test statistics and linkage disequilibrium (LD). The LD Score regression intercept can be used to estimate a more powerful and accurate correction factor than genomic control. We find strong evidence that polygenicity accounts for the majority of test statistic inflation in many GWAS of large sample size. PMID:25642630

Association of polygenic risk for major psychiatric illness with subcortical volumes and white matter integrity in UK Biobank

PubMed Central

Reus, L. M.; Shen, X.; Gibson, J.; Wigmore, E.; Ligthart, L.; Adams, M. J.; Davies, G.; Cox, S. R.; Hagenaars, S. P.; Bastin, M. E.; Deary, I. J.; Whalley, H. C.; McIntosh, A. M.

2017-01-01

Major depressive disorder (MDD), schizophrenia (SCZ) and bipolar disorder (BP) are common, disabling and heritable psychiatric diseases with a complex overlapping polygenic architecture. Individuals with these disorders, as well as their unaffected relatives, show widespread structural differences in corticostriatal and limbic networks. Structural variation in many of these brain regions is also heritable and polygenic but whether their genetic architecture overlaps with that of major psychiatric disorders is unknown. We sought to address this issue by examining the impact of polygenic risk of MDD, SCZ, and BP on subcortical brain volumes and white matter (WM) microstructure in a large single sample of neuroimaging data; the UK Biobank Imaging study. The first release of UK Biobank imaging data comprised participants with overlapping genetic data and subcortical volumes (N = 978) and WM measures (N = 816). The calculation of polygenic risk scores was based on genome-wide association study results generated by the Psychiatric Genomics Consortium. Our findings indicated no statistically significant associations between either subcortical volumes or WM microstructure, and polygenic risk for MDD, SCZ or BP. These findings suggest that subcortical brain volumes and WM microstructure may not be closely linked to the genetic mechanisms of major psychiatric disorders. PMID:28186152

Association of polygenic risk for major psychiatric illness with subcortical volumes and white matter integrity in UK Biobank.

PubMed

Reus, L M; Shen, X; Gibson, J; Wigmore, E; Ligthart, L; Adams, M J; Davies, G; Cox, S R; Hagenaars, S P; Bastin, M E; Deary, I J; Whalley, H C; McIntosh, A M

2017-02-10

Major depressive disorder (MDD), schizophrenia (SCZ) and bipolar disorder (BP) are common, disabling and heritable psychiatric diseases with a complex overlapping polygenic architecture. Individuals with these disorders, as well as their unaffected relatives, show widespread structural differences in corticostriatal and limbic networks. Structural variation in many of these brain regions is also heritable and polygenic but whether their genetic architecture overlaps with that of major psychiatric disorders is unknown. We sought to address this issue by examining the impact of polygenic risk of MDD, SCZ, and BP on subcortical brain volumes and white matter (WM) microstructure in a large single sample of neuroimaging data; the UK Biobank Imaging study. The first release of UK Biobank imaging data comprised participants with overlapping genetic data and subcortical volumes (N = 978) and WM measures (N = 816). The calculation of polygenic risk scores was based on genome-wide association study results generated by the Psychiatric Genomics Consortium. Our findings indicated no statistically significant associations between either subcortical volumes or WM microstructure, and polygenic risk for MDD, SCZ or BP. These findings suggest that subcortical brain volumes and WM microstructure may not be closely linked to the genetic mechanisms of major psychiatric disorders.

High Loading of Polygenic Risk for ADHD in Children With Comorbid Aggression

PubMed Central

Hamshere, Marian L.; Langley, Kate; Martin, Joanna; Agha, Sharifah Shameem; Stergiakouli, Evangelia; Anney, Richard J.L.; Buitelaar, Jan; Faraone, Stephen V.; Lesch, Klaus-Peter; Neale, Benjamin M.; Franke, Barbara; Sonuga-Barke, Edmund; Asherson, Philip; Merwood, Andrew; Kuntsi, Jonna; Medland, Sarah E.; Ripke, Stephan; Steinhausen, Hans-Christoph; Freitag, Christine; Reif, Andreas; Renner, Tobias J.; Romanos, Marcel; Romanos, Jasmin; Warnke, Andreas; Meyer, Jobst; Palmason, Haukur; Vasquez, Alejandro Arias; Lambregts-Rommelse, Nanda; Roeyers, Herbert; Biederman, Joseph; Doyle, Alysa E.; Hakonarson, Hakon; Rothenberger, Aribert; Banaschewski, Tobias; Oades, Robert D.; McGough, James J.; Kent, Lindsey; Williams, Nigel; Owen, Michael J.; Holmans, Peter

2013-01-01

Objective Although attention deficit hyperactivity disorder (ADHD) is highly heritable, genome-wide association studies (GWAS) have not yet identified any common genetic variants that contribute to risk. There is evidence that aggression or conduct disorder in children with ADHD indexes higher genetic loading and clinical severity. The authors examine whether common genetic variants considered en masse as polygenic scores for ADHD are especially enriched in children with comorbid conduct disorder. Method Polygenic scores derived from an ADHD GWAS meta-analysis were calculated in an independent ADHD sample (452 case subjects, 5,081 comparison subjects). Multivariate logistic regression analyses were employed to compare polygenic scores in the ADHD and comparison groups and test for higher scores in ADHD case subjects with comorbid conduct disorder relative to comparison subjects and relative to those without comorbid conduct disorder. Association with symptom scores was tested using linear regression. Results Polygenic risk for ADHD, derived from the meta-analysis, was higher in the independent ADHD group than in the comparison group. Polygenic score was significantly higher in ADHD case subjects with conduct disorder relative to ADHD case subjects without conduct disorder. ADHD polygenic score showed significant association with comorbid conduct disorder symptoms. This relationship was explained by the aggression items. Conclusions Common genetic variation is relevant to ADHD, especially in individuals with comorbid aggression. The findings suggest that the previously published ADHD GWAS meta-analysis contains weak but true associations with common variants, support for which falls below genome-wide significance levels. The findings also highlight the fact that aggression in ADHD indexes genetic as well as clinical severity. PMID:23599091

Pleiotropic Models of Polygenic Variation, Stabilizing Selection, and Epistasis

PubMed Central

Gavrilets, S.; de-Jong, G.

1993-01-01

We show that in polymorphic populations many polygenic traits pleiotropically related to fitness are expected to be under apparent ``stabilizing selection'' independently of the real selection acting on the population. This occurs, for example, if the genetic system is at a stable polymorphic equilibrium determined by selection and the nonadditive contributions of the loci to the trait value either are absent, or are random and independent of those to fitness. Stabilizing selection is also observed if the polygenic system is at an equilibrium determined by a balance between selection and mutation (or migration) when both additive and nonadditive contributions of the loci to the trait value are random and independent of those to fitness. We also compare different viability models that can maintain genetic variability at many loci with respect to their ability to account for the strong stabilizing selection on an additive trait. Let V(m) be the genetic variance supplied by mutation (or migration) each generation, V(g) be the genotypic variance maintained in the population, and n be the number of the loci influencing fitness. We demonstrate that in mutation (migration)-selection balance models the strength of apparent stabilizing selection is order V(m)/V(g). In the overdominant model and in the symmetric viability model the strength of apparent stabilizing selection is approximately 1/(2n) that of total selection on the whole phenotype. We show that a selection system that involves pairwise additive by additive epistasis in maintaining variability can lead to a lower genetic load and genetic variance in fitness (approximately 1/(2n) times) than an equivalent selection system that involves overdominance. We show that, in the epistatic model, the apparent stabilizing selection on an additive trait can be as strong as the total selection on the whole phenotype. PMID:8325491

Common variants explain a large fraction of the variability in the liability to psoriasis in a Han Chinese population.

PubMed

Yin, Xianyong; Wineinger, Nathan E; Cheng, Hui; Cui, Yong; Zhou, Fusheng; Zuo, Xianbo; Zheng, Xiaodong; Yang, Sen; Schork, Nicholas J; Zhang, Xuejun

2014-01-30

Psoriasis is a common inflammatory skin disease with a known genetic component. Our previously published psoriasis genome-wide association study identified dozens of novel susceptibility loci in Han Chinese. However, these markers explained only a small fraction of the estimated heritable component of psoriasis. To better understand the unknown yet likely polygenic architecture in psoriasis, we applied a linear mixed model to quantify the variation in the liability to psoriasis explained by common genetic markers (minor allele frequency > 0.01) in a Han Chinese population. We explored the polygenic genetic architecture of psoriasis using genome-wide association data from 2,271 Han Chinese individuals. We estimated that 34.9% (s.e. = 6.0%, P = 9 × 10-9) of the variation in the liability to psoriasis is captured by common genotyped and imputed variants. We discuss these results in the context of the strong association between HLA variants and psoriasis. We also show that the variance explained by each chromosome is linearly correlated to its length (R2 = 0.27, P=0.01), and quantify the impact of a polygenic effect on the prediction and diagnosis of psoriasis. Our results suggest that psoriasis has a substantial polygenic component, which not only has implications for the development of genetic diagnostics and prognostics for psoriasis, but also suggests that more individual variants contributing to psoriasis may be detected if sample sizes in future association studies are increased.

Predictive accuracy of combined genetic and environmental risk scores.

PubMed

Dudbridge, Frank; Pashayan, Nora; Yang, Jian

2018-02-01

The substantial heritability of most complex diseases suggests that genetic data could provide useful risk prediction. To date the performance of genetic risk scores has fallen short of the potential implied by heritability, but this can be explained by insufficient sample sizes for estimating highly polygenic models. When risk predictors already exist based on environment or lifestyle, two key questions are to what extent can they be improved by adding genetic information, and what is the ultimate potential of combined genetic and environmental risk scores? Here, we extend previous work on the predictive accuracy of polygenic scores to allow for an environmental score that may be correlated with the polygenic score, for example when the environmental factors mediate the genetic risk. We derive common measures of predictive accuracy and improvement as functions of the training sample size, chip heritabilities of disease and environmental score, and genetic correlation between disease and environmental risk factors. We consider simple addition of the two scores and a weighted sum that accounts for their correlation. Using examples from studies of cardiovascular disease and breast cancer, we show that improvements in discrimination are generally small but reasonable degrees of reclassification could be obtained with current sample sizes. Correlation between genetic and environmental scores has only minor effects on numerical results in realistic scenarios. In the longer term, as the accuracy of polygenic scores improves they will come to dominate the predictive accuracy compared to environmental scores. © 2017 WILEY PERIODICALS, INC.

Predictive accuracy of combined genetic and environmental risk scores

PubMed Central

Pashayan, Nora; Yang, Jian

2017-01-01

ABSTRACT The substantial heritability of most complex diseases suggests that genetic data could provide useful risk prediction. To date the performance of genetic risk scores has fallen short of the potential implied by heritability, but this can be explained by insufficient sample sizes for estimating highly polygenic models. When risk predictors already exist based on environment or lifestyle, two key questions are to what extent can they be improved by adding genetic information, and what is the ultimate potential of combined genetic and environmental risk scores? Here, we extend previous work on the predictive accuracy of polygenic scores to allow for an environmental score that may be correlated with the polygenic score, for example when the environmental factors mediate the genetic risk. We derive common measures of predictive accuracy and improvement as functions of the training sample size, chip heritabilities of disease and environmental score, and genetic correlation between disease and environmental risk factors. We consider simple addition of the two scores and a weighted sum that accounts for their correlation. Using examples from studies of cardiovascular disease and breast cancer, we show that improvements in discrimination are generally small but reasonable degrees of reclassification could be obtained with current sample sizes. Correlation between genetic and environmental scores has only minor effects on numerical results in realistic scenarios. In the longer term, as the accuracy of polygenic scores improves they will come to dominate the predictive accuracy compared to environmental scores. PMID:29178508

Exploring the predictive power of polygenic scores derived from genome-wide association studies: a study of 10 complex traits.

PubMed

So, Hon-Cheong; Sham, Pak C

2017-03-15

It is hoped that advances in our knowledge in disease genomics will contribute to personalized medicine such as individualized preventive strategies or early diagnoses of diseases. With the growth of genome-wide association studies (GWAS) in the past decade, how far have we reached this goal? In this study we explored the predictive ability of polygenic risk scores (PRSs) derived from GWAS for a range of complex disease and traits. We first proposed a new approach to evaluate predictive performances of PRS at arbitrary P -value thresholds. The method was based on corrected estimates of effect sizes, accounting for possible false positives and selection bias. This approach requires no distributional assumptions and only requires summary statistics as input. The validity of the approach was verified in simulations. We explored the predictive power of PRS for ten complex traits, including type 2 diabetes (DM), coronary artery disease (CAD), triglycerides, high- and low-density lipoprotein, total cholesterol, schizophrenia (SCZ), bipolar disorder (BD), major depressive disorder and anxiety disorders. We found that the predictive ability of PRS for CAD and DM were modest (best AUC = 0.608 and 0.607) while for lipid traits the prediction R-squared ranged from 16.1 to 29.8%. For psychiatric disorders, the predictive power for SCZ was estimated to be the highest (best AUC 0.820), followed by BD. Predictive performance of other psychiatric disorders ranged from 0.543 to 0.585. Psychiatric traits tend to have more gradual rise in AUC when significance thresholds increase and achieve the best predictive power at higher P -values than cardiometabolic traits. hcso@cuhk.edu.hk ; pcsham@hku.hk. Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

Public health genomics and personalized prevention: lessons from the COGS project.

PubMed

Pashayan, N; Hall, A; Chowdhury, S; Dent, T; Pharoah, P D P; Burton, H

2013-11-01

Using the principles of public health genomics, we examined the opportunities and challenges of implementing personalized prevention programmes for cancer at the population level. Our model-based estimates indicate that polygenic risk stratification can potentially improve the effectiveness and cost-effectiveness of screening programmes. However, compared with 'one-size-fits-all' screening programmes, personalized screening adds further layers of complexity to the organization of screening services and raises ethical, legal and social challenges. Before polygenic inheritance is translated into population screening strategy, evidence from empirical research and engagement with and education of the public and the health professionals are needed. © 2013 The Association for the Publication of the Journal of Internal Medicine.

Polygenic hazard score to guide screening for aggressive prostate cancer: development and validation in large scale cohorts.

PubMed

Seibert, Tyler M; Fan, Chun Chieh; Wang, Yunpeng; Zuber, Verena; Karunamuni, Roshan; Parsons, J Kellogg; Eeles, Rosalind A; Easton, Douglas F; Kote-Jarai, ZSofia; Al Olama, Ali Amin; Garcia, Sara Benlloch; Muir, Kenneth; Grönberg, Henrik; Wiklund, Fredrik; Aly, Markus; Schleutker, Johanna; Sipeky, Csilla; Tammela, Teuvo Lj; Nordestgaard, Børge G; Nielsen, Sune F; Weischer, Maren; Bisbjerg, Rasmus; Røder, M Andreas; Iversen, Peter; Key, Tim J; Travis, Ruth C; Neal, David E; Donovan, Jenny L; Hamdy, Freddie C; Pharoah, Paul; Pashayan, Nora; Khaw, Kay-Tee; Maier, Christiane; Vogel, Walther; Luedeke, Manuel; Herkommer, Kathleen; Kibel, Adam S; Cybulski, Cezary; Wokolorczyk, Dominika; Kluzniak, Wojciech; Cannon-Albright, Lisa; Brenner, Hermann; Cuk, Katarina; Saum, Kai-Uwe; Park, Jong Y; Sellers, Thomas A; Slavov, Chavdar; Kaneva, Radka; Mitev, Vanio; Batra, Jyotsna; Clements, Judith A; Spurdle, Amanda; Teixeira, Manuel R; Paulo, Paula; Maia, Sofia; Pandha, Hardev; Michael, Agnieszka; Kierzek, Andrzej; Karow, David S; Mills, Ian G; Andreassen, Ole A; Dale, Anders M

2018-01-10

To develop and validate a genetic tool to predict age of onset of aggressive prostate cancer (PCa) and to guide decisions of who to screen and at what age. Analysis of genotype, PCa status, and age to select single nucleotide polymorphisms (SNPs) associated with diagnosis. These polymorphisms were incorporated into a survival analysis to estimate their effects on age at diagnosis of aggressive PCa (that is, not eligible for surveillance according to National Comprehensive Cancer Network guidelines; any of Gleason score ≥7, stage T3-T4, PSA (prostate specific antigen) concentration ≥10 ng/L, nodal metastasis, distant metastasis). The resulting polygenic hazard score is an assessment of individual genetic risk. The final model was applied to an independent dataset containing genotype and PSA screening data. The hazard score was calculated for these men to test prediction of survival free from PCa. Multiple institutions that were members of international PRACTICAL consortium. All consortium participants of European ancestry with known age, PCa status, and quality assured custom (iCOGS) array genotype data. The development dataset comprised 31 747 men; the validation dataset comprised 6411 men. Prediction with hazard score of age of onset of aggressive cancer in validation set. In the independent validation set, the hazard score calculated from 54 single nucleotide polymorphisms was a highly significant predictor of age at diagnosis of aggressive cancer (z=11.2, P<10 -16 ). When men in the validation set with high scores (>98th centile) were compared with those with average scores (30th-70th centile), the hazard ratio for aggressive cancer was 2.9 (95% confidence interval 2.4 to 3.4). Inclusion of family history in a combined model did not improve prediction of onset of aggressive PCa (P=0.59), and polygenic hazard score performance remained high when family history was accounted for. Additionally, the positive predictive value of PSA screening for aggressive PCa was increased with increasing polygenic hazard score. Polygenic hazard scores can be used for personalised genetic risk estimates that can predict for age at onset of aggressive PCa. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

The genetic association between personality and major depression or bipolar disorder. A polygenic score analysis using genome-wide association data

PubMed Central

Middeldorp, C M; de Moor, M H M; McGrath, L M; Gordon, S D; Blackwood, D H; Costa, P T; Terracciano, A; Krueger, R F; de Geus, E J C; Nyholt, D R; Tanaka, T; Esko, T; Madden, P A F; Derringer, J; Amin, N; Willemsen, G; Hottenga, J-J; Distel, M A; Uda, M; Sanna, S; Spinhoven, P; Hartman, C A; Ripke, S; Sullivan, P F; Realo, A; Allik, J; Heath, A C; Pergadia, M L; Agrawal, A; Lin, P; Grucza, R A; Widen, E; Cousminer, D L; Eriksson, J G; Palotie, A; Barnett, J H; Lee, P H; Luciano, M; Tenesa, A; Davies, G; Lopez, L M; Hansell, N K; Medland, S E; Ferrucci, L; Schlessinger, D; Montgomery, G W; Wright, M J; Aulchenko, Y S; Janssens, A C J W; Oostra, B A; Metspalu, A; Abecasis, G R; Deary, I J; Räikkönen, K; Bierut, L J; Martin, N G; Wray, N R; van Duijn, C M; Smoller, J W; Penninx, B W J H; Boomsma, D I

2011-01-01

The relationship between major depressive disorder (MDD) and bipolar disorder (BD) remains controversial. Previous research has reported differences and similarities in risk factors for MDD and BD, such as predisposing personality traits. For example, high neuroticism is related to both disorders, whereas openness to experience is specific for BD. This study examined the genetic association between personality and MDD and BD by applying polygenic scores for neuroticism, extraversion, openness to experience, agreeableness and conscientiousness to both disorders. Polygenic scores reflect the weighted sum of multiple single-nucleotide polymorphism alleles associated with the trait for an individual and were based on a meta-analysis of genome-wide association studies for personality traits including 13 835 subjects. Polygenic scores were tested for MDD in the combined Genetic Association Information Network (GAIN-MDD) and MDD2000+ samples (N=8921) and for BD in the combined Systematic Treatment Enhancement Program for Bipolar Disorder and Wellcome Trust Case–Control Consortium samples (N=6329) using logistic regression analyses. At the phenotypic level, personality dimensions were associated with MDD and BD. Polygenic neuroticism scores were significantly positively associated with MDD, whereas polygenic extraversion scores were significantly positively associated with BD. The explained variance of MDD and BD, ∼0.1%, was highly comparable to the variance explained by the polygenic personality scores in the corresponding personality traits themselves (between 0.1 and 0.4%). This indicates that the proportions of variance explained in mood disorders are at the upper limit of what could have been expected. This study suggests shared genetic risk factors for neuroticism and MDD on the one hand and for extraversion and BD on the other. PMID:22833196

Polygenic Versus Monogenic Causes of Hypercholesterolemia Ascertained Clinically.

PubMed

Wang, Jian; Dron, Jacqueline S; Ban, Matthew R; Robinson, John F; McIntyre, Adam D; Alazzam, Maher; Zhao, Pei Jun; Dilliott, Allison A; Cao, Henian; Huff, Murray W; Rhainds, David; Low-Kam, Cécile; Dubé, Marie-Pierre; Lettre, Guillaume; Tardif, Jean-Claude; Hegele, Robert A

2016-12-01

Next-generation sequencing technology is transforming our understanding of heterozygous familial hypercholesterolemia, including revision of prevalence estimates and attribution of polygenic effects. Here, we examined the contributions of monogenic and polygenic factors in patients with severe hypercholesterolemia referred to a specialty clinic. We applied targeted next-generation sequencing with custom annotation, coupled with evaluation of large-scale copy number variation and polygenic scores for raised low-density lipoprotein cholesterol in a cohort of 313 individuals with severe hypercholesterolemia, defined as low-density lipoprotein cholesterol >5.0 mmol/L (>194 mg/dL). We found that (1) monogenic familial hypercholesterolemia-causing mutations detected by targeted next-generation sequencing were present in 47.3% of individuals; (2) the percentage of individuals with monogenic mutations increased to 53.7% when copy number variations were included; (3) the percentage further increased to 67.1% when individuals with extreme polygenic scores were included; and (4) the percentage of individuals with an identified genetic component increased from 57.0% to 92.0% as low-density lipoprotein cholesterol level increased from 5.0 to >8.0 mmol/L (194 to >310 mg/dL). In a clinically ascertained sample with severe hypercholesterolemia, we found that most patients had a discrete genetic basis detected using a comprehensive screening approach that includes targeted next-generation sequencing, an assay for copy number variations, and polygenic trait scores. © 2016 American Heart Association, Inc.

Schizophrenia-associated methylomic variation: molecular signatures of disease and polygenic risk burden across multiple brain regions.

PubMed

Viana, Joana; Hannon, Eilis; Dempster, Emma; Pidsley, Ruth; Macdonald, Ruby; Knox, Olivia; Spiers, Helen; Troakes, Claire; Al-Saraj, Safa; Turecki, Gustavo; Schalkwyk, Leonard C; Mill, Jonathan

2017-01-01

Genetic association studies provide evidence for a substantial polygenic component to schizophrenia, although the neurobiological mechanisms underlying the disorder remain largely undefined. Building on recent studies supporting a role for developmentally regulated epigenetic variation in the molecular aetiology of schizophrenia, this study aimed to identify epigenetic variation associated with both a diagnosis of schizophrenia and elevated polygenic risk burden for the disease across multiple brain regions. Genome-wide DNA methylation was quantified in 262 post-mortem brain samples, representing tissue from four brain regions (prefrontal cortex, striatum, hippocampus and cerebellum) from 41 schizophrenia patients and 47 controls. We identified multiple disease-associated and polygenic risk score-associated differentially methylated positions and regions, which are not enriched in genomic regions identified in genetic studies of schizophrenia and do not reflect direct genetic effects on DNA methylation. Our study represents the first analysis of epigenetic variation associated with schizophrenia across multiple brain regions and highlights the utility of polygenic risk scores for identifying molecular pathways associated with aetiological variation in complex disease. © The Author 2016. Published by Oxford University Press.

Gene expression profiling assigns CHEK2 1100delC breast cancers to the luminal intrinsic subtypes.

PubMed

Nagel, Jord H A; Peeters, Justine K; Smid, Marcel; Sieuwerts, Anieta M; Wasielewski, Marijke; de Weerd, Vanja; Trapman-Jansen, Anita M A C; van den Ouweland, Ans; Brüggenwirth, Hennie; van I Jcken, Wilfred F J; Klijn, Jan G M; van der Spek, Peter J; Foekens, John A; Martens, John W M; Schutte, Mieke; Meijers-Heijboer, Hanne

2012-04-01

CHEK2 1100delC is a moderate-risk cancer susceptibility allele that confers a high breast cancer risk in a polygenic setting. Gene expression profiling of CHEK2 1100delC breast cancers may reveal clues to the nature of the polygenic CHEK2 model and its genes involved. Here, we report global gene expression profiles of a cohort of 155 familial breast cancers, including 26 CHEK2 1100delC mutant tumors. In line with previous work, all CHEK2 1100delC mutant tumors clustered among the hormone receptor-positive breast cancers. In the hormone receptor-positive subset, a 40-gene CHEK2 signature was subsequently defined that significantly associated with CHEK2 1100delC breast cancers. The identification of a CHEK2 gene signature implies an unexpected biological homogeneity among the CHEK2 1100delC breast cancers. In addition, all 26 CHEK2 1100delC tumors classified as luminal intrinsic subtype breast cancers, with 8 luminal A and 18 luminal B tumors. This biological make-up of CHEK2 1100delC breast cancers suggests that a relatively limited number of additional susceptibility alleles are involved in the polygenic CHEK2 model. Identification of these as-yet-unknown susceptibility alleles should be aided by clues from the 40-gene CHEK2 signature.

Bipolar polygenic loading and bipolar spectrum features in major depressive disorder

PubMed Central

Wiste, Anna; Robinson, Elise B; Milaneschi, Yuri; Meier, Sandra; Ripke, Stephan; Clements, Caitlin C; Fitzmaurice, Garrett M; Rietschel, Marcella; Penninx, Brenda W; Smoller, Jordan W; Perlis, Roy H

2014-01-01

Objectives Family and genetic studies indicate overlapping liability for major depressive disorder and bipolar disorder. The purpose of this study was to determine whether this shared genetic liability influences clinical presentation. Methods A polygenic risk score for bipolar disorder, derived from a large genome-wide association meta-analysis, was generated for each subject of European–American ancestry (n = 1,274) in the Sequential Treatment Alternatives to Relieve Depression study (STAR*D) outpatient major depressive disorder cohort. A hypothesis-driven approach was used to test for association between bipolar disorder risk score and features of depression associated with bipolar disorder in the literature. Follow-up analyses were performed in two additional cohorts. Results A generalized linear mixed model including seven features hypothesized to be associated with bipolar spectrum illness was significantly associated with bipolar polygenic risk score [F = 2.07, degrees of freedom (df) = 7, p = 0.04). Features included early onset, suicide attempt, recurrent depression, atypical depression, subclinical mania, subclinical psychosis, and severity. Post-hoc univariate analyses demonstrated that the major contributors to this omnibus association were onset of illness at age ≤ 18 years [odds ratio (OR) = 1.2, p = 0.003], history of suicide attempt (OR = 1.21, p = 0.03), and presence of at least one manic symptom (OR = 1.16, p = 0.02). The maximal variance in these traits explained by polygenic score ranged from 0.8–1.1%. However, analyses in two replication cohorts testing a five feature model did not support this association. Conclusions Bipolar genetic loading appeared to be associated with bipolar-like presentation in major depressive disorder in the primary analysis. However, results are at most inconclusive because of lack of replication. Replication efforts are challenged by different ascertainment and assessment strategies in the different cohorts. The methodological approach described here may prove useful in applying genetic data to clarify psychiatric nosology in future studies. PMID:24725193

Phenotypic Manifestation of Genetic Risk for Schizophrenia During Adolescence in the General Population.

PubMed

Jones, Hannah J; Stergiakouli, Evie; Tansey, Katherine E; Hubbard, Leon; Heron, Jon; Cannon, Mary; Holmans, Peter; Lewis, Glyn; Linden, David E J; Jones, Peter B; Davey Smith, George; O'Donovan, Michael C; Owen, Michael J; Walters, James T; Zammit, Stanley

2016-03-01

Schizophrenia is a highly heritable, polygenic condition characterized by a relatively diverse phenotype and frequent comorbid conditions, such as anxiety and depression. At present, limited evidence explains how genetic risk for schizophrenia is manifest in the general population. To investigate the extent to which genetic risk for schizophrenia is associated with different phenotypes during adolescence in a population-based birth cohort. This cohort study used data from the Avon Longitudinal Study of Parents and Children (ALSPAC). Of 14,062 children in the birth cohort, genetic data were available for 9912 adolescents. Data were collected periodically from September 6, 1990, and collection is ongoing. Data were analyzed from March 4 to August 13, 2015. Polygenic risk scores (PRSs) for schizophrenia generated for individuals in the ALSPAC cohort using results of the second Psychiatric Genomics Consortium Schizophrenia genome-wide association study as a training set. Logistic regression was used to assess associations between the schizophrenia PRS and (1) psychotic experiences (Psychosis-Like Symptom Interview at 12 and 18 years of age), (2) negative symptoms (Community Assessment of Psychic Experiences at 16.5 years of age), (3) depressive disorder (Development and Well-Being Assessment at 15.5 years of age), and (4) anxiety disorder (Development and Well-Being Assessment at 15.5 years of age) in adolescence. Of the 8230 ALSPAC participants whose genetic data passed quality control checks (51.2% male, 48.8% female), 3676 to 5444 participated in assessments from 12 to 18 years of age. The PRSs created using single-nucleotide polymorphisms with a training-set P ≤ .05 threshold were associated with negative symptoms (odds ratio [OR] per SD increase in PRS, 1.21; 95% CI, 1.08-1.36; R(2) = 0.007) and anxiety disorder (OR per SD increase in PRS, 1.17; 95% CI, 1.06- 1.29; R(2) = 0.005). No evidence was found of an association between schizophrenia PRS and psychotic experiences (OR per SD increase in PRS, 1.08; 95% CI, 0.98-1.19; R(2) = 0.001) or depressive disorder (OR per SD increase in PRS, 1.02; 95% CI, 0.91-1.13; R(2) = 0.00005). Results were mostly consistent across different training-set P value thresholds and using different cutoffs and measures of the psychopathological outcomes. This study demonstrates polygenic overlaps between common genetic polymorphisms associated with schizophrenia and negative symptoms and anxiety disorder but not with psychotic experiences or depression. Because the genetic risk for schizophrenia appears to be manifest as anxiety and negative symptoms during adolescence, a greater focus on these phenotypes rather than on psychotic experiences might be required for prediction of transition in at-risk samples.

Polygenic risk for coronary artery disease is associated with cognitive ability in older adults

PubMed Central

Hagenaars, Saskia P; Harris, Sarah E; Clarke, Toni-Kim; Hall, Lynsey; Luciano, Michelle; Fernandez-Pujals, Ana Maria; Davies, Gail; Hayward, Caroline; Starr, John M; Porteous, David J; McIntosh, Andrew M; Deary, Ian J

2016-01-01

Abstract Background: Coronary artery disease (CAD) is associated with cognitive decrements and risk of later dementia, but it is not known if shared genetic factors underlie this association. We tested whether polygenic risk for CAD was associated with cognitive ability in community-dwelling cohorts of middle-aged and older adults. Methods: Individuals from Generation Scotland: Scottish Family Health Study (GS:SFHS, N = 9865) and from the Lothian Birth Cohorts of 1921 (LBC1921, N  = 517) and 1936 (LBC1936, N  = 1005) provided cognitive data and genome-wide genotype data. Polygenic risk profile scores for CAD were calculated for all of the cohorts using the largest available genome-wide association studies (GWAS) data set, the CARDIoGRAM consortium (22 233 cases and 64 762 controls). Polygenic risk profile scores for CAD were then tested for their association with cognitive abilities in the presence and absence of manifest cardiovascular disease. Results: A meta-analysis of all three cohorts showed a negative association between CAD polygenic risk and fluid cognitive ability (β = −0.022, P  = 0.016), verbal intelligence (β = −0.024, P  = 0.011) and memory (β = −0.021, P  = 0.028). Conclusions: Increased polygenic risk for CAD is associated with lower cognitive ability in older adults. Common genetic variants may underlie some of the association between age-related cognitive decrements and the risk for CAD. PMID:26822939

Alternative models in genetic analyses of carcass traits measured by ultrasonography in Guzerá cattle: A Bayesian approach

USDA-ARS?s Scientific Manuscript database

The objective was to study alternative models for genetic analyses of carcass traits assessed by ultrasonography in Guzerá cattle. Data from 947 measurements (655 animals) of Rib-eye area (REA), rump fat thickness (RFT) and backfat thickness (BFT) were used. Finite polygenic models (FPM), infinitesi...

Polygenic Risk Score, Parental Socioeconomic Status, Family History of Psychiatric Disorders, and the Risk for Schizophrenia: A Danish Population-Based Study and Meta-analysis.

PubMed

Agerbo, Esben; Sullivan, Patrick F; Vilhjálmsson, Bjarni J; Pedersen, Carsten B; Mors, Ole; Børglum, Anders D; Hougaard, David M; Hollegaard, Mads V; Meier, Sandra; Mattheisen, Manuel; Ripke, Stephan; Wray, Naomi R; Mortensen, Preben B

2015-07-01

Schizophrenia has a complex etiology influenced both by genetic and nongenetic factors but disentangling these factors is difficult. To estimate (1) how strongly the risk for schizophrenia relates to the mutual effect of the polygenic risk score, parental socioeconomic status, and family history of psychiatric disorders; (2) the fraction of cases that could be prevented if no one was exposed to these factors; (3) whether family background interacts with an individual's genetic liability so that specific subgroups are particularly risk prone; and (4) to what extent a proband's genetic makeup mediates the risk associated with familial background. We conducted a nested case-control study based on Danish population-based registers. The study consisted of 866 patients diagnosed as having schizophrenia between January 1, 1994, and December 31, 2006, and 871 matched control individuals. Genome-wide data and family psychiatric and socioeconomic background information were obtained from neonatal biobanks and national registers. Results from a separate meta-analysis (34,600 cases and 45,968 control individuals) were applied to calculate polygenic risk scores. Polygenic risk scores, parental socioeconomic status, and family psychiatric history. Odds ratios (ORs), attributable risks, liability R2 values, and proportions mediated. Schizophrenia was associated with the polygenic risk score (OR, 8.01; 95% CI, 4.53-14.16 for highest vs lowest decile), socioeconomic status (OR, 8.10; 95% CI, 3.24-20.3 for 6 vs no exposures), and a history of schizophrenia/psychoses (OR, 4.18; 95% CI, 2.57-6.79). The R2 values were 3.4% (95% CI, 2.1-4.6) for the polygenic risk score, 3.1% (95% CI, 1.9-4.3) for parental socioeconomic status, and 3.4% (95% CI, 2.1-4.6) for family history. Socioeconomic status and psychiatric history accounted for 45.8% (95% CI, 36.1-55.5) and 25.8% (95% CI, 21.2-30.5) of cases, respectively. There was an interaction between the polygenic risk score and family history (P = .03). A total of 17.4% (95% CI, 9.1-26.6) of the effect associated with family history of schizophrenia/psychoses was mediated through the polygenic risk score. Schizophrenia was associated with the polygenic risk score, family psychiatric history, and socioeconomic status. Our study demonstrated that family history of schizophrenia/psychoses is partly mediated through the individual's genetic liability.

Multifactorial disease risk calculator: Risk prediction for multifactorial disease pedigrees.

PubMed

Campbell, Desmond D; Li, Yiming; Sham, Pak C

2018-03-01

Construction of multifactorial disease models from epidemiological findings and their application to disease pedigrees for risk prediction is nontrivial for all but the simplest of cases. Multifactorial Disease Risk Calculator is a web tool facilitating this. It provides a user-friendly interface, extending a reported methodology based on a liability-threshold model. Multifactorial disease models incorporating all the following features in combination are handled: quantitative risk factors (including polygenic scores), categorical risk factors (including major genetic risk loci), stratified age of onset curves, and the partition of the population variance in disease liability into genetic, shared, and unique environment effects. It allows the application of such models to disease pedigrees. Pedigree-related outputs are (i) individual disease risk for pedigree members, (ii) n year risk for unaffected pedigree members, and (iii) the disease pedigree's joint liability distribution. Risk prediction for each pedigree member is based on using the constructed disease model to appropriately weigh evidence on disease risk available from personal attributes and family history. Evidence is used to construct the disease pedigree's joint liability distribution. From this, lifetime and n year risk can be predicted. Example disease models and pedigrees are provided at the website and are used in accompanying tutorials to illustrate the features available. The website is built on an R package which provides the functionality for pedigree validation, disease model construction, and risk prediction. Website: http://grass.cgs.hku.hk:3838/mdrc/current. © 2017 WILEY PERIODICALS, INC.

Identification of Traits Associated with Stuttering

ERIC Educational Resources Information Center

Subramanian, Anu; Yairi, Ehud

2006-01-01

Stuttering has been considered a heritable disorder since the 1930s. There have been different models of transmission that have been proposed most involving a polygenic component with or without a major locus. In spite of these models, the characteristics being transmitted are not known. This study used two different tasks--a tapping task that is…

Comparison on genomic predictions using three GBLUP methods and two single-step blending methods in the Nordic Holstein population

PubMed Central

2012-01-01

Background A single-step blending approach allows genomic prediction using information of genotyped and non-genotyped animals simultaneously. However, the combined relationship matrix in a single-step method may need to be adjusted because marker-based and pedigree-based relationship matrices may not be on the same scale. The same may apply when a GBLUP model includes both genomic breeding values and residual polygenic effects. The objective of this study was to compare single-step blending methods and GBLUP methods with and without adjustment of the genomic relationship matrix for genomic prediction of 16 traits in the Nordic Holstein population. Methods The data consisted of de-regressed proofs (DRP) for 5 214 genotyped and 9 374 non-genotyped bulls. The bulls were divided into a training and a validation population by birth date, October 1, 2001. Five approaches for genomic prediction were used: 1) a simple GBLUP method, 2) a GBLUP method with a polygenic effect, 3) an adjusted GBLUP method with a polygenic effect, 4) a single-step blending method, and 5) an adjusted single-step blending method. In the adjusted GBLUP and single-step methods, the genomic relationship matrix was adjusted for the difference of scale between the genomic and the pedigree relationship matrices. A set of weights on the pedigree relationship matrix (ranging from 0.05 to 0.40) was used to build the combined relationship matrix in the single-step blending method and the GBLUP method with a polygenetic effect. Results Averaged over the 16 traits, reliabilities of genomic breeding values predicted using the GBLUP method with a polygenic effect (relative weight of 0.20) were 0.3% higher than reliabilities from the simple GBLUP method (without a polygenic effect). The adjusted single-step blending and original single-step blending methods (relative weight of 0.20) had average reliabilities that were 2.1% and 1.8% higher than the simple GBLUP method, respectively. In addition, the GBLUP method with a polygenic effect led to less bias of genomic predictions than the simple GBLUP method, and both single-step blending methods yielded less bias of predictions than all GBLUP methods. Conclusions The single-step blending method is an appealing approach for practical genomic prediction in dairy cattle. Genomic prediction from the single-step blending method can be improved by adjusting the scale of the genomic relationship matrix. PMID:22455934

Structural brain MRI trait polygenic score prediction of cognitive abilities

PubMed Central

Luciano, Michelle; Marioni, Riccardo E; Hernández, Maria Valdés; Maniega, Susana Munoz; Hamilton, Iona F; Royle, Natalie A.; Scotland, Generation; Chauhan, Ganesh; Bis, Joshua C.; Debette, Stephanie; DeCarli, Charles; Fornage, Myriam; Schmidt, Reinhold; Ikram, M. Arfan; Launer, Lenore J.; Seshadri, Sudha; Bastin, Mark E.; Porteous, David J.; Wardlaw, Joanna; Deary, Ian J

2016-01-01

Structural brain magnetic resonance imaging (MRI) traits share part of their genetic variance with cognitive traits. Here, we use genetic association results from large meta-analytic studies of genome-wide association for brain infarcts, white matter hyperintensities, intracranial, hippocampal and total brain volumes to estimate polygenic scores for these traits in three Scottish samples: Generation Scotland: Scottish Family Health Study (GS:SFHS), and the Lothian Birth Cohorts of 1936 (LBC1936) and 1921 (LBC1921). These five brain MRI trait polygenic scores were then used to 1) predict corresponding MRI traits in the LBC1936 (numbers ranged 573 to 630 across traits) and 2) predict cognitive traits in all three cohorts (in 8,115 to 8,250 persons). In the LBC1936, all MRI phenotypic traits were correlated with at least one cognitive measure; and polygenic prediction of MRI traits was observed for intracranial volume. Meta-analysis of the correlations between MRI polygenic scores and cognitive traits revealed a significant negative correlation (maximal r=0.08) between the hippocampal volume polygenic score and measures of global cognitive ability collected in childhood and in old age in the Lothian Birth Cohorts. The lack of association to a related general cognitive measure when including the GS:SFHS points to either type 1 error or the importance of using prediction samples that closely match the demographics of the genome-wide association samples from which prediction is based. Ideally, these analyses should be repeated in larger samples with data on both MRI and cognition, and using MRI GWA results from even larger meta-analysis studies. PMID:26427786

A family study of dermatoglyphic traits in India: segregation analysis of accessory palmar triradii and the atd angle.

PubMed

Gilligan, S B; Borecki, I B; Mathew, S; Vijaykumar, M; Malhotra, K C; Rao, D C

1987-09-01

Accessory triradii and the atd angle were examined via complex segregation analysis in order to evaluate possible genetic effects on these dermatoglyphic traits, measured in an endogamous Brahmin caste of peninsular India. The phenotypes considered included: presence of accessory palmar triradii a' and d', associated with the interdigital areas II and IV, respectively; presence of an accessory axial triradius tt' associated with the proximal margin of the palm; and an arctanh-transformation of the atd angle measurement. For all accessory triradii considered in the present investigation familial resemblance was evident. The most parsimonious model which could account for the observed resemblance was a multifactorial model that includes polygenic effects as well as transmissible environmental effects that are inherited in the same pattern as polygenes. Evidence of familial resemblance was also found for the arctanh-transformed atd angle, which could be attributed, initially, to both a major effect and a multifactorial component. Tests of transmission of a putative major gene were performed which yielded results consistent with Mendelian transmission, although an alternative test of no transmission of the major effect also fit the data. In light of these contrasting results we are precluded from accepting with confidence the notion of a major gene influence on the atd angle. We have concluded that the accessory triradii a', d', and tt', and the atd angle are influenced by multifactorial effects, including additive polygenes and possible environmental factors, such as intrauterine effects.

Traumatic Stress Interacts With Bipolar Disorder Genetic Risk to Increase Risk for Suicide Attempts

PubMed Central

Wilcox, Holly C.; Fullerton, Janice M.; Glowinski, Anne L.; Benke, Kelly; Kamali, Masoud; Hulvershorn, Leslie A.; Stapp, Emma K.; Edenberg, Howard J.; Roberts, Gloria M.P.; Ghaziuddin, Neera; Fisher, Carrie; Brucksch, Christine; Frankland, Andrew; Toma, Claudio; Shaw, Alex D.; Kastelic, Elizabeth; Miller, Leslie; McInnis, Melvin G.; Mitchell, Philip B.; Nurnberger, John I.

2018-01-01

Objective Bipolar disorder (BD) is one of the most heritable psychiatric conditions and is associated with high suicide risk. To explore the reasons for this link, this study examined the interaction between traumatic stress and BD polygenic risk score in relation to suicidal ideation, suicide attempt, and nonsuicidal self-injury (NSSI) in adolescent and young adult offspring and relatives of persons with BD (BD-relatives) compared with adolescent and young adult offspring of individuals without psychiatric disorders (controls). Method Data were collected from 4 sites in the United States and 1 site in Australia from 2006 through 2012. Generalized estimating equation models were used to compare rates of ideation, attempts, and NSSI between BD-relatives (n = 307) and controls (n = 166) and to determine the contribution of demographic factors, traumatic stress exposure, lifetime mood or substance (alcohol/drug) use disorders, and BD polygenic risk score. Results After adjusting for demographic characteristics and mood and substance use disorders, BD-relatives were at increased risk for suicidal ideation and attempts but not for NSSI. Independent of BD-relative versus control status, demographic factors, or mood and substance use disorders, exposure to trauma within the past year (including bullying, sexual abuse, and domestic violence) was associated with suicide attempts (p = .014), and BD polygenic risk score was marginally associated with attempts (p = .061). Importantly, the interaction between BD polygenic risk score and traumatic event exposures was significantly associated with attempts, independent of demographics, relative versus control status, and mood and substance use disorders (p = .041). Conclusion BD-relatives are at increased risk for suicide attempts and ideation, especially if they are exposed to trauma and have evidence of increased genetic vulnerability. PMID:29173741

Polygenic Risk, Personality Dimensions, and Adolescent Alcohol Use Problems: A Longitudinal Study

PubMed Central

Li, James J.; Savage, Jeanne E.; Kendler, Kenneth S.; Hickman, Matthew; Mahedy, Liam; Macleod, John; Kaprio, Jaakko; Rose, Richard J.; Dick, Danielle M.

2017-01-01

Objective: Alcohol use problems are common during adolescence and can predict serious negative outcomes in adulthood, including substance dependence and psychopathology. The current study examines the notion that alcohol use problems are driven by polygenic influences and that genetic influences may indirectly affect alcohol use problems through multiple pathways of risk, including variations in personality. Method: We used a genome-wide approach to examine associations between genetic risk for alcohol use problems, personality dimensions, and adolescent alcohol use problems in two separate longitudinal population-based samples, the Finnish Twin Cohort (FinnTwin12) and the Avon Longitudinal Study of Parents and Children (ALSPAC). Participants were 1,035 young adults from FinnTwin12 and 3,160 adolescents from ALSPAC. Polygenic risk scores (PRS) were calculated for ALSPAC using genome-wide association results (on alcohol dependence symptoms as defined by the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition) from FinnTwin12. A parallel multiple mediator model was tested to examine whether the association between PRS and alcohol use problems assessed at age 16 could be explained by variations in personality dimensions assessed at age 13, including sensation seeking and negative emotionality. Results: PRS were marginally predictive of age 16 alcohol use problems; this association was partially mediated by sensation seeking. Polygenic variation underlying risk for alcohol use problems may directly influence the effects of sensation seeking, which in turn influence the development of alcohol use problems in later adolescence. Conclusions: These findings contribute to the increasing evidence regarding the salience of sensation seeking during early adolescence as a potential constituent in the risk pathway underlying the development of alcohol use problems. PMID:28499112

A Population Genetic Signal of Polygenic Adaptation

PubMed Central

Berg, Jeremy J.; Coop, Graham

2014-01-01

Adaptation in response to selection on polygenic phenotypes may occur via subtle allele frequencies shifts at many loci. Current population genomic techniques are not well posed to identify such signals. In the past decade, detailed knowledge about the specific loci underlying polygenic traits has begun to emerge from genome-wide association studies (GWAS). Here we combine this knowledge from GWAS with robust population genetic modeling to identify traits that may have been influenced by local adaptation. We exploit the fact that GWAS provide an estimate of the additive effect size of many loci to estimate the mean additive genetic value for a given phenotype across many populations as simple weighted sums of allele frequencies. We use a general model of neutral genetic value drift for an arbitrary number of populations with an arbitrary relatedness structure. Based on this model, we develop methods for detecting unusually strong correlations between genetic values and specific environmental variables, as well as a generalization of comparisons to test for over-dispersion of genetic values among populations. Finally we lay out a framework to identify the individual populations or groups of populations that contribute to the signal of overdispersion. These tests have considerably greater power than their single locus equivalents due to the fact that they look for positive covariance between like effect alleles, and also significantly outperform methods that do not account for population structure. We apply our tests to the Human Genome Diversity Panel (HGDP) dataset using GWAS data for height, skin pigmentation, type 2 diabetes, body mass index, and two inflammatory bowel disease datasets. This analysis uncovers a number of putative signals of local adaptation, and we discuss the biological interpretation and caveats of these results. PMID:25102153

cerebral Markers of the Serotonergic System in Rat Models of Obesity and After Roux-en-Y Gastric Bypass

PubMed Central

Ratner, Cecilia; Ettrup, Anders; Bueter, Marco; Haahr, Mette E.; Compan, Valérie; le Roux, Carel W.; Levin, Barry; Hansen, Henrik H.; Knudsen, Gitte M.

2013-01-01

Food intake and body weight are regulated by a complex system of neural and hormonal signals, of which the anorexigenic neurotransmitter serotonin (5-hydroxytryptamine or 5-HT) is central. In this study, rat models of obesity and weight loss intervention were compared with regard to several 5-HT markers. Using receptor autoradiography, brain regional-densities of the serotonin transporter (SERT) and the 5-HT2A and 5-HT4 receptors were measured in (i) selectively bred polygenic diet-induced obese (pgDIO) rats, (ii) outbred DIO rats, and (iii) Roux-en-Y gastric bypass (RYGB)-operated rats. pgDIO rats had higher 5-HT4 and 5-HT2A receptor binding and lower SERT binding when compared to polygenic diet-resistant (pgDR) rats. The most pronounced difference between pgDIO and pgDR rats was observed in the nucleus accumbens shell (NAcS), a brain region regulating reward aspects of feeding. No differences were found in the 5-HT markers between DIO rats, chow-fed control rats, and DIO rats experiencing a weight loss. The 5-HT markers were also similar in RYGB and sham-operated rats except for a downregulation of 5-HT2A receptors in the NAcS. The higher receptor and lower SERT binding in pgDIO as compared to pgDR rats corresponds to what is reported in overweight humans and suggests that the dysfunctions of the 5-HT system associated with overeating or propensity to become overweight are polygenically determined. Our results support that the obesity-prone rat model has high translational value and suggests that susceptibility to develop obesity is associated with changed 5-HT tone in the brain that may also regulate hedonic aspects of feeding. PMID:22450706

Signatures of positive selection: from selective sweeps at individual loci to subtle allele frequency changes in polygenic adaptation.

PubMed

Stephan, Wolfgang

2016-01-01

In the past 15 years, numerous methods have been developed to detect selective sweeps underlying adaptations. These methods are based on relatively simple population genetic models, including one or two loci at which positive directional selection occurs, and one or two marker loci at which the impact of selection on linked neutral variation is quantified. Information about the phenotype under selection is not included in these models (except for fitness). In contrast, in the quantitative genetic models of adaptation, selection acts on one or more phenotypic traits, such that a genotype-phenotype map is required to bridge the gap to population genetics theory. Here I describe the range of population genetic models from selective sweeps in a panmictic population of constant size to evolutionary traffic when simultaneous sweeps at multiple loci interfere, and I also consider the case of polygenic selection characterized by subtle allele frequency shifts at many loci. Furthermore, I present an overview of the statistical tests that have been proposed based on these population genetics models to detect evidence for positive selection in the genome. © 2015 John Wiley & Sons Ltd.

Genome-wide Polygenic Burden of Rare Deleterious Variants in Sudden Unexpected Death in Epilepsy.

PubMed

Leu, Costin; Balestrini, Simona; Maher, Bridget; Hernández-Hernández, Laura; Gormley, Padhraig; Hämäläinen, Eija; Heggeli, Kristin; Schoeler, Natasha; Novy, Jan; Willis, Joseph; Plagnol, Vincent; Ellis, Rachael; Reavey, Eleanor; O'Regan, Mary; Pickrell, William O; Thomas, Rhys H; Chung, Seo-Kyung; Delanty, Norman; McMahon, Jacinta M; Malone, Stephen; Sadleir, Lynette G; Berkovic, Samuel F; Nashef, Lina; Zuberi, Sameer M; Rees, Mark I; Cavalleri, Gianpiero L; Sander, Josemir W; Hughes, Elaine; Helen Cross, J; Scheffer, Ingrid E; Palotie, Aarno; Sisodiya, Sanjay M

2015-09-01

Sudden unexpected death in epilepsy (SUDEP) represents the most severe degree of the spectrum of epilepsy severity and is the commonest cause of epilepsy-related premature mortality. The precise pathophysiology and the genetic architecture of SUDEP remain elusive. Aiming to elucidate the genetic basis of SUDEP, we analysed rare, protein-changing variants from whole-exome sequences of 18 people who died of SUDEP, 87 living people with epilepsy and 1479 non-epilepsy disease controls. Association analysis revealed a significantly increased genome-wide polygenic burden per individual in the SUDEP cohort when compared to epilepsy (P = 5.7 × 10(- 3)) and non-epilepsy disease controls (P = 1.2 × 10(- 3)). The polygenic burden was driven both by the number of variants per individual, and over-representation of variants likely to be deleterious in the SUDEP cohort. As determined by this study, more than a thousand genes contribute to the observed polygenic burden within the framework of this study. Subsequent gene-based association analysis revealed five possible candidate genes significantly associated with SUDEP or epilepsy, but no one single gene emerges as common to the SUDEP cases. Our findings provide further evidence for a genetic susceptibility to SUDEP, and suggest an extensive polygenic contribution to SUDEP causation. Thus, an overall increased burden of deleterious variants in a highly polygenic background might be important in rendering a given individual more susceptible to SUDEP. Our findings suggest that exome sequencing in people with epilepsy might eventually contribute to generating SUDEP risk estimates, promoting stratified medicine in epilepsy, with the eventual aim of reducing an individual patient's risk of SUDEP.

Genetic risk for attention-deficit/hyperactivity disorder contributes to neurodevelopmental traits in the general population.

PubMed

Martin, Joanna; Hamshere, Marian L; Stergiakouli, Evangelia; O'Donovan, Michael C; Thapar, Anita

2014-10-15

Attention-deficit/hyperactivity disorder (ADHD) can be viewed as the extreme end of traits in the general population. Epidemiological and twin studies suggest that ADHD frequently co-occurs with and shares genetic susceptibility with autism spectrum disorder (ASD) and ASD-related traits. The aims of this study were to determine whether a composite of common molecular genetic variants, previously found to be associated with clinically diagnosed ADHD, predicts ADHD and ASD-related traits in the general population. Polygenic risk scores were calculated in the Avon Longitudinal Study of Parents and Children (ALSPAC) population sample (N = 8229) based on a discovery case-control genome-wide association study of childhood ADHD. Regression analyses were used to assess whether polygenic scores predicted ADHD traits and ASD-related measures (pragmatic language abilities and social cognition) in the ALSPAC sample. Polygenic scores were also compared in boys and girls endorsing any (rating ≥ 1) ADHD item (n = 3623). Polygenic risk for ADHD showed a positive association with ADHD traits (hyperactive-impulsive, p = .0039; inattentive, p = .037). Polygenic risk for ADHD was also negatively associated with pragmatic language abilities (p = .037) but not with social cognition (p = .43). In children with a rating ≥ 1 for ADHD traits, girls had a higher polygenic score than boys (p = .003). These findings provide molecular genetic evidence that risk alleles for the categorical disorder of ADHD influence hyperactive-impulsive and attentional traits in the general population. The results further suggest that common genetic variation that contributes to ADHD diagnosis may also influence ASD-related traits, which at their extreme are a characteristic feature of ASD. Copyright © 2014 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

Genome-wide Polygenic Burden of Rare Deleterious Variants in Sudden Unexpected Death in Epilepsy

PubMed Central

Leu, Costin; Balestrini, Simona; Maher, Bridget; Hernández-Hernández, Laura; Gormley, Padhraig; Hämäläinen, Eija; Heggeli, Kristin; Schoeler, Natasha; Novy, Jan; Willis, Joseph; Plagnol, Vincent; Ellis, Rachael; Reavey, Eleanor; O'Regan, Mary; Pickrell, William O.; Thomas, Rhys H.; Chung, Seo-Kyung; Delanty, Norman; McMahon, Jacinta M.; Malone, Stephen; Sadleir, Lynette G.; Berkovic, Samuel F.; Nashef, Lina; Zuberi, Sameer M.; Rees, Mark I.; Cavalleri, Gianpiero L.; Sander, Josemir W.; Hughes, Elaine; Helen Cross, J.; Scheffer, Ingrid E.; Palotie, Aarno; Sisodiya, Sanjay M.

2015-01-01

Sudden unexpected death in epilepsy (SUDEP) represents the most severe degree of the spectrum of epilepsy severity and is the commonest cause of epilepsy-related premature mortality. The precise pathophysiology and the genetic architecture of SUDEP remain elusive. Aiming to elucidate the genetic basis of SUDEP, we analysed rare, protein-changing variants from whole-exome sequences of 18 people who died of SUDEP, 87 living people with epilepsy and 1479 non-epilepsy disease controls. Association analysis revealed a significantly increased genome-wide polygenic burden per individual in the SUDEP cohort when compared to epilepsy (P = 5.7 × 10− 3) and non-epilepsy disease controls (P = 1.2 × 10− 3). The polygenic burden was driven both by the number of variants per individual, and over-representation of variants likely to be deleterious in the SUDEP cohort. As determined by this study, more than a thousand genes contribute to the observed polygenic burden within the framework of this study. Subsequent gene-based association analysis revealed five possible candidate genes significantly associated with SUDEP or epilepsy, but no one single gene emerges as common to the SUDEP cases. Our findings provide further evidence for a genetic susceptibility to SUDEP, and suggest an extensive polygenic contribution to SUDEP causation. Thus, an overall increased burden of deleterious variants in a highly polygenic background might be important in rendering a given individual more susceptible to SUDEP. Our findings suggest that exome sequencing in people with epilepsy might eventually contribute to generating SUDEP risk estimates, promoting stratified medicine in epilepsy, with the eventual aim of reducing an individual patient's risk of SUDEP. PMID:26501104

The potential of large studies for building genetic risk prediction models

Cancer.gov

NCI scientists have developed a new paradigm to assess hereditary risk prediction in common diseases, such as prostate cancer. This genetic risk prediction concept is based on polygenic analysis—the study of a group of common DNA sequences, known as singl

Predicting Substance Use in Emerging Adulthood: A Genetically Informed Study of Developmental Transactions between Impulsivity and Family Conflict

PubMed Central

Elam, Kit K.; Wang, Frances L.; Bountress, Kaitlin; Chassin, Laurie; Pandika, Danielle; Lemery-Chalfant, Kathryn

2016-01-01

Deviance proneness models propose a multi-level interplay in which transactions among genetic, individual, and family risk factors place children at increased risk for substance use. We examined bidirectional transactions between impulsivity and family conflict from middle childhood to adolescence and their contributions to substance use in adolescence and emerging adulthood (n = 380). Moreover, we examined children’s, mothers’ and fathers’ polygenic risk scores for behavioral undercontrol, and mothers’ and fathers’ interparental conflict and substance disorder diagnoses as predictors of these transactions. Results support a developmental cascade model in which children’s polygenic risk scores predicted greater impulsivity in middle childhood. Impulsivity in middle childhood predicted greater family conflict in late childhood, which in turn predicted greater impulsivity in late adolescence. Adolescent impulsivity subsequently predicted greater substance use in emerging adulthood. Results are discussed with respect to evocative genotype-environment correlations within developmental cascades and applications to prevention efforts. PMID:27427799

Common variants at 30 loci contribute to polygenic dyslipidemia

USDA-ARS?s Scientific Manuscript database

Blood low-density lipoprotein (LDL) cholesterol, high-density lipoprotein (HDL)cholesterol and triglyceride levels are risk factors for cardiovascular disease. To dissect the polygenic basis of these traits, we conducted genome-wide association screens in 19,840 individuals and replication in up to ...

The nature of nurture: Effects of parental genotypes.

PubMed

Kong, Augustine; Thorleifsson, Gudmar; Frigge, Michael L; Vilhjalmsson, Bjarni J; Young, Alexander I; Thorgeirsson, Thorgeir E; Benonisdottir, Stefania; Oddsson, Asmundur; Halldorsson, Bjarni V; Masson, Gisli; Gudbjartsson, Daniel F; Helgason, Agnar; Bjornsdottir, Gyda; Thorsteinsdottir, Unnur; Stefansson, Kari

2018-01-26

Sequence variants in the parental genomes that are not transmitted to a child (the proband) are often ignored in genetic studies. Here we show that nontransmitted alleles can affect a child through their impacts on the parents and other relatives, a phenomenon we call "genetic nurture." Using results from a meta-analysis of educational attainment, we find that the polygenic score computed for the nontransmitted alleles of 21,637 probands with at least one parent genotyped has an estimated effect on the educational attainment of the proband that is 29.9% ( P = 1.6 × 10 -14 ) of that of the transmitted polygenic score. Genetic nurturing effects of this polygenic score extend to other traits. Paternal and maternal polygenic scores have similar effects on educational attainment, but mothers contribute more than fathers to nutrition- and heath-related traits. Copyright © 2018, The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.

Affiliation with substance-using peers: Examining gene-environment correlations among parent monitoring, polygenic risk, and children's impulsivity.

PubMed

Elam, Kit K; Chassin, Laurie; Lemery-Chalfant, Kathryn; Pandika, Danielle; Wang, Frances L; Bountress, Kaitlin; Dick, Danielle; Agrawal, Arpana

2017-07-01

Parental monitoring can buffer the effect of deviant peers on adolescents' substance use by reducing affiliation with substance-using peers. However, children's genetic predispositions may evoke poorer monitoring, contributing to negative child outcomes. We examined evocative genotype-environment correlations underlying children's genetic predisposition for behavioral undercontrol and parental monitoring in early adolescence via children's impulsivity in middle childhood, and the influence of parental monitoring on affiliation with substance-using peers a year and a half later (n = 359). Genetic predisposition for behavioral undercontrol was captured using a polygenic risk score, and a portion of passive rGE was controlled by including parents' polygenic risk scores. Children's polygenic risk predicted poorer parental monitoring via greater children's impulsivity, indicating evocative rGE, controlling for a portion of passive rGE. Poorer parental monitoring predicted greater children's affiliation with substance-using peers a year and a half later. Results are discussed with respect to gene-environment correlations within developmental cascades. © 2017 Wiley Periodicals, Inc.

Genetics and Crime: Integrating New Genomic Discoveries Into Psychological Research About Antisocial Behavior.

PubMed

Wertz, J; Caspi, A; Belsky, D W; Beckley, A L; Arseneault, L; Barnes, J C; Corcoran, D L; Hogan, S; Houts, R M; Morgan, N; Odgers, C L; Prinz, J A; Sugden, K; Williams, B S; Poulton, R; Moffitt, T E

2018-05-01

Drawing on psychological and sociological theories of crime causation, we tested the hypothesis that genetic risk for low educational attainment (assessed via a genome-wide polygenic score) is associated with criminal offending. We further tested hypotheses of how polygenic risk relates to the development of antisocial behavior from childhood through adulthood. Across the Dunedin and Environmental Risk (E-Risk) birth cohorts of individuals growing up 20 years and 20,000 kilometers apart, education polygenic scores predicted risk of a criminal record with modest effects. Polygenic risk manifested during primary schooling in lower cognitive abilities, lower self-control, academic difficulties, and truancy, and it was associated with a life-course-persistent pattern of antisocial behavior that onsets in childhood and persists into adulthood. Crime is central in the nature-nurture debate, and findings reported here demonstrate how molecular-genetic discoveries can be incorporated into established theories of antisocial behavior. They also suggest that improving school experiences might prevent genetic influences on crime from unfolding.

Genetics and crime: Integrating new genomic discoveries into psychological research about antisocial behavior

PubMed Central

Wertz, J.; Caspi, A.; Belsky, D. W.; Beckley, A. L.; Arseneault, L.; Barnes, J. C.; Corcoran, D. L.; Hogan, S.; Houts, R. M.; Morgan, N.; Odgers, C. L.; Prinz, J. A.; Sugden, K.; Williams, B. S.; Poulton, R.; Moffitt, T. E.

2018-01-01

Drawing on psychological and sociological theories of crime causation, we tested the hypothesis that genetic risk for low educational attainment (assessed via a genome-wide polygenic score) is associated with offending. We further tested hypotheses of how polygenic risk relates to the development of antisocial behavior from childhood through adulthood. Across the Dunedin and E-Risk birth cohorts of individuals growing up 20 years and 20,000 kilometres apart, education polygenic scores predicted risk of a criminal record, with modest effects. Polygenic risk manifested during primary schooling, in lower cognitive abilities, lower self-control, academic difficulties, and truancy, and predicted a life-course persistent pattern of antisocial behavior that onsets in childhood and persists into adulthood. Crime is central in the nature/nurture debate, and findings reported here demonstrate how molecular-genetic discoveries can be incorporated into established theories of antisocial behavior. They also suggest the hypothesis that improving school experiences might prevent genetic influences on crime from unfolding. PMID:29513605

Association Between Schizophrenia-Related Polygenic Liability and the Occurrence and Level of Mood-Incongruent Psychotic Symptoms in Bipolar Disorder.

PubMed

Allardyce, Judith; Leonenko, Ganna; Hamshere, Marian; Pardiñas, Antonio F; Forty, Liz; Knott, Sarah; Gordon-Smith, Katherine; Porteous, David J; Haywood, Caroline; Di Florio, Arianna; Jones, Lisa; McIntosh, Andrew M; Owen, Michael J; Holmans, Peter; Walters, James T R; Craddock, Nicholas; Jones, Ian; O'Donovan, Michael C; Escott-Price, Valentina

2018-01-01

Bipolar disorder (BD) overlaps schizophrenia in its clinical presentation and genetic liability. Alternative approaches to patient stratification beyond current diagnostic categories are needed to understand the underlying disease processes and mechanisms. To investigate the association between common-variant liability for schizophrenia, indexed by polygenic risk scores (PRSs), and psychotic presentations of BD. This case-control study in the United Kingdom used multinomial logistic regression to estimate differential PRS associations across categories of cases and controls. Participants included in the final analyses were 4436 cases of BD from the Bipolar Disorder Research Network. These cases were compared with the genotypic data for 4976 cases of schizophrenia and 9012 controls from the Type 1 Diabetes Genetics Consortium study and the Generation Scotland study. Data were collected between January 1, 2000, and December 31, 2013. Data analysis was conducted from March 1, 2016, to February 28, 2017. Standardized PRSs, calculated using alleles with an association threshold of P < .05 in the second Psychiatric Genomics Consortium genome-wide association study of schizophrenia, were adjusted for the first 10 population principal components and genotyping platforms. Multinomial logit models estimated PRS associations with BD stratified by Research Diagnostic Criteria subtypes of BD, by lifetime occurrence of psychosis, and by lifetime mood-incongruent psychotic features. Ordinal logistic regression examined PRS associations across levels of mood incongruence. Ratings were derived from the Schedules for Clinical Assessment in Neuropsychiatry interview and the Bipolar Affective Disorder Dimension Scale. Of the 4436 cases of BD, 2966 (67%) were female patients, and the mean (SD) age at interview was 46 [12] years. Across clinical phenotypes, there was an exposure-response gradient, with the strongest PRS association for schizophrenia (risk ratio [RR] = 1.94; 95% CI, 1.86-2.01), followed by schizoaffective BD (RR = 1.37; 95% CI, 1.22-1.54), bipolar I disorder subtype (RR = 1.30; 95% CI, 1.24-1.36), and bipolar II disorder subtype (RR = 1.04; 95% CI, 0.97-1.11). Within BD cases, there was an effect gradient, indexed by the nature of psychosis. Prominent mood-incongruent psychotic features had the strongest association (RR = 1.46; 95% CI, 1.36-1.57), followed by mood-congruent psychosis (RR = 1.24; 95% CI, 1.17-1.33) and BD with no history of psychosis (RR = 1.09; 95% CI, 1.04-1.15). For the first time to date, a study shows a polygenic-risk gradient across schizophrenia and BD, indexed by the occurrence and level of mood-incongruent psychotic symptoms.

Multifactorial inheritance with cultural transmission and assortative mating. II. a general model of combined polygenic and cultural inheritance.

PubMed Central

Cloninger, C R; Rice, J; Reich, T

1979-01-01

A general linear model of combined polygenic-cultural inheritance is described. The model allows for phenotypic assortative mating, common environment, maternal and paternal effects, and genic-cultural correlation. General formulae for phenotypic correlation between family members in extended pedigrees are given for both primary and secondary assortative mating. A FORTRAN program BETA, available upon request, is used to provide maximum likelihood estimates of the parameters from reported correlations. American data about IQ and Burks' culture index are analyzed. Both cultural and genetic components of phenotypic variance are observed to make significant and substantial contributions to familial resemblance in IQ. The correlation between the environments of DZ twins is found to equal that of singleton sibs, not that of MZ twins. Burks' culture index is found to be an imperfect measure of midparent IQ rather than an index of home environment as previously assumed. Conditions under which the parameters of the model may be uniquely and precisely estimated are discussed. Interpretation of variance components in the presence of assortative mating and genic-cultural covariance is reviewed. A conservative, but robust, approach to the use of environmental indices is described. PMID:453202

A Comparison Study of Multivariate Fixed Models and Gene Association with Multiple Traits (GAMuT) for Next-Generation Sequencing

PubMed Central

Chiu, Chi-yang; Jung, Jeesun; Wang, Yifan; Weeks, Daniel E.; Wilson, Alexander F.; Bailey-Wilson, Joan E.; Amos, Christopher I.; Mills, James L.; Boehnke, Michael; Xiong, Momiao; Fan, Ruzong

2016-01-01

In this paper, extensive simulations are performed to compare two statistical methods to analyze multiple correlated quantitative phenotypes: (1) approximate F-distributed tests of multivariate functional linear models (MFLM) and additive models of multivariate analysis of variance (MANOVA), and (2) Gene Association with Multiple Traits (GAMuT) for association testing of high-dimensional genotype data. It is shown that approximate F-distributed tests of MFLM and MANOVA have higher power and are more appropriate for major gene association analysis (i.e., scenarios in which some genetic variants have relatively large effects on the phenotypes); GAMuT has higher power and is more appropriate for analyzing polygenic effects (i.e., effects from a large number of genetic variants each of which contributes a small amount to the phenotypes). MFLM and MANOVA are very flexible and can be used to perform association analysis for: (i) rare variants, (ii) common variants, and (iii) a combination of rare and common variants. Although GAMuT was designed to analyze rare variants, it can be applied to analyze a combination of rare and common variants and it performs well when (1) the number of genetic variants is large and (2) each variant contributes a small amount to the phenotypes (i.e., polygenes). MFLM and MANOVA are fixed effect models which perform well for major gene association analysis. GAMuT can be viewed as an extension of sequence kernel association tests (SKAT). Both GAMuT and SKAT are more appropriate for analyzing polygenic effects and they perform well not only in the rare variant case, but also in the case of a combination of rare and common variants. Data analyses of European cohorts and the Trinity Students Study are presented to compare the performance of the two methods. PMID:27917525

QTL meta-analysis provides a comprehensive view of loci controlling partial resistance to Aphanomyces euteiches in four sources of resistance in pea

USDA-ARS?s Scientific Manuscript database

More knowledge about diversity of Quantitative Trait Loci (QTL) controlling polygenic disease resistance in natural genetic variation of crop species is required for durably improving plant genetic resistances to pathogens. Polygenic partial resistance to Aphanomyces root rot, due to Aphanomcyces eu...

Polygenic risk for five psychiatric disorders and cross-disorder and disorder-specific neural connectivity in two independent populations.

PubMed

Wang, Tianqi; Zhang, Xiaolong; Li, Ang; Zhu, Meifang; Liu, Shu; Qin, Wen; Li, Jin; Yu, Chunshui; Jiang, Tianzi; Liu, Bing

2017-01-01

Major psychiatric disorders, including attention deficit hyperactivity disorder (ADHD), autism (AUT), bipolar disorder (BD), major depressive disorder (MDD), and schizophrenia (SZ), are highly heritable and polygenic. Evidence suggests that these five disorders have both shared and distinct genetic risks and neural connectivity abnormalities. To measure aggregate genetic risks, the polygenic risk score (PGRS) was computed. Two independent general populations (N = 360 and N = 323) were separately examined to investigate whether the cross-disorder PGRS and PGRS for a specific disorder were associated with individual variability in functional connectivity. Consistent altered functional connectivity was found with the bilateral insula: for the left supplementary motor area and the left superior temporal gyrus with the cross-disorder PGRS, for the left insula and right middle and superior temporal lobe associated with the PGRS for autism, for the bilateral midbrain, posterior cingulate, cuneus, and precuneus associated with the PGRS for BD, and for the left angular gyrus and the left dorsolateral prefrontal cortex associated with the PGRS for schizophrenia. No significant functional connectivity was found associated with the PGRS for ADHD and MDD. Our findings indicated that genetic effects on the cross-disorder and disorder-specific neural connectivity of common genetic risk loci are detectable in the general population. Our findings also indicated that polygenic risk contributes to the main neurobiological phenotypes of psychiatric disorders and that identifying cross-disorder and specific functional connectivity related to polygenic risks may elucidate the neural pathways for these disorders.

A systematic review of associations between functional MRI activity and polygenic risk for schizophrenia and bipolar disorder.

PubMed

Dezhina, Zalina; Ranlund, Siri; Kyriakopoulos, Marinos; Williams, Steve C R; Dima, Danai

2018-05-10

Genetic factors account for up to 80% of the liability for schizophrenia (SCZ) and bipolar disorder (BD). Genome-wide association studies have successfully identified several genes associated with increased risk for both disorders. This has allowed researchers to model the aggregate effect of genes associated with disease status and create a polygenic risk score (PGRS) for each individual. The interest in imaging genetics using PGRS has grown in recent years, with several studies now published. We have conducted a systematic review to examine the effects of PGRS of SCZ, BD and cross psychiatric disorders on brain function and connectivity using fMRI data. Results indicate that the effect of genetic load for SCZ and BD on brain function affects task-related recruitment, with frontal areas having a more prominent role, independent of task. Additionally, the results suggest that the polygenic architecture of psychotic disorders is not regionally confined but impacts on the task-dependent recruitment of multiple brain regions. Future imaging genetics studies with large samples, especially population studies, would be uniquely informative in mapping the spatial distribution of the genetic risk to psychiatric disorders on brain processes during various cognitive tasks and may lead to the discovery of biological pathways that could be crucial in mediating the link between genetic factors and alterations in brain networks.

Cross-disorder genome-wide analyses suggest a complex genetic relationship between Tourette's syndrome and OCD.

PubMed

Yu, Dongmei; Mathews, Carol A; Scharf, Jeremiah M; Neale, Benjamin M; Davis, Lea K; Gamazon, Eric R; Derks, Eske M; Evans, Patrick; Edlund, Christopher K; Crane, Jacquelyn; Fagerness, Jesen A; Osiecki, Lisa; Gallagher, Patience; Gerber, Gloria; Haddad, Stephen; Illmann, Cornelia; McGrath, Lauren M; Mayerfeld, Catherine; Arepalli, Sampath; Barlassina, Cristina; Barr, Cathy L; Bellodi, Laura; Benarroch, Fortu; Berrió, Gabriel Bedoya; Bienvenu, O Joseph; Black, Donald W; Bloch, Michael H; Brentani, Helena; Bruun, Ruth D; Budman, Cathy L; Camarena, Beatriz; Campbell, Desmond D; Cappi, Carolina; Silgado, Julio C Cardona; Cavallini, Maria C; Chavira, Denise A; Chouinard, Sylvain; Cook, Edwin H; Cookson, M R; Coric, Vladimir; Cullen, Bernadette; Cusi, Daniele; Delorme, Richard; Denys, Damiaan; Dion, Yves; Eapen, Valsama; Egberts, Karin; Falkai, Peter; Fernandez, Thomas; Fournier, Eduardo; Garrido, Helena; Geller, Daniel; Gilbert, Donald L; Girard, Simon L; Grabe, Hans J; Grados, Marco A; Greenberg, Benjamin D; Gross-Tsur, Varda; Grünblatt, Edna; Hardy, John; Heiman, Gary A; Hemmings, Sian M J; Herrera, Luis D; Hezel, Dianne M; Hoekstra, Pieter J; Jankovic, Joseph; Kennedy, James L; King, Robert A; Konkashbaev, Anuar I; Kremeyer, Barbara; Kurlan, Roger; Lanzagorta, Nuria; Leboyer, Marion; Leckman, James F; Lennertz, Leonhard; Liu, Chunyu; Lochner, Christine; Lowe, Thomas L; Lupoli, Sara; Macciardi, Fabio; Maier, Wolfgang; Manunta, Paolo; Marconi, Maurizio; McCracken, James T; Mesa Restrepo, Sandra C; Moessner, Rainald; Moorjani, Priya; Morgan, Jubel; Muller, Heike; Murphy, Dennis L; Naarden, Allan L; Nurmi, Erika; Ochoa, William Cornejo; Ophoff, Roel A; Pakstis, Andrew J; Pato, Michele T; Pato, Carlos N; Piacentini, John; Pittenger, Christopher; Pollak, Yehuda; Rauch, Scott L; Renner, Tobias; Reus, Victor I; Richter, Margaret A; Riddle, Mark A; Robertson, Mary M; Romero, Roxana; Rosário, Maria C; Rosenberg, David; Ruhrmann, Stephan; Sabatti, Chiara; Salvi, Erika; Sampaio, Aline S; Samuels, Jack; Sandor, Paul; Service, Susan K; Sheppard, Brooke; Singer, Harvey S; Smit, Jan H; Stein, Dan J; Strengman, Eric; Tischfield, Jay A; Turiel, Maurizio; Valencia Duarte, Ana V; Vallada, Homero; Veenstra-VanderWeele, Jeremy; Walitza, Susanne; Wang, Ying; Weale, Mike; Weiss, Robert; Wendland, Jens R; Westenberg, Herman G M; Shugart, Yin Yao; Hounie, Ana G; Miguel, Euripedes C; Nicolini, Humberto; Wagner, Michael; Ruiz-Linares, Andres; Cath, Danielle C; McMahon, William; Posthuma, Danielle; Oostra, Ben A; Nestadt, Gerald; Rouleau, Guy A; Purcell, Shaun; Jenike, Michael A; Heutink, Peter; Hanna, Gregory L; Conti, David V; Arnold, Paul D; Freimer, Nelson B; Stewart, S Evelyn; Knowles, James A; Cox, Nancy J; Pauls, David L

2015-01-01

Obsessive-compulsive disorder (OCD) and Tourette's syndrome are highly heritable neurodevelopmental disorders that are thought to share genetic risk factors. However, the identification of definitive susceptibility genes for these etiologically complex disorders remains elusive. The authors report a combined genome-wide association study (GWAS) of Tourette's syndrome and OCD. The authors conducted a GWAS in 2,723 cases (1,310 with OCD, 834 with Tourette's syndrome, 579 with OCD plus Tourette's syndrome/chronic tics), 5,667 ancestry-matched controls, and 290 OCD parent-child trios. GWAS summary statistics were examined for enrichment of functional variants associated with gene expression levels in brain regions. Polygenic score analyses were conducted to investigate the genetic architecture within and across the two disorders. Although no individual single-nucleotide polymorphisms (SNPs) achieved genome-wide significance, the GWAS signals were enriched for SNPs strongly associated with variations in brain gene expression levels (expression quantitative loci, or eQTLs), suggesting the presence of true functional variants that contribute to risk of these disorders. Polygenic score analyses identified a significant polygenic component for OCD (p=2×10(-4)), predicting 3.2% of the phenotypic variance in an independent data set. In contrast, Tourette's syndrome had a smaller, nonsignificant polygenic component, predicting only 0.6% of the phenotypic variance (p=0.06). No significant polygenic signal was detected across the two disorders, although the sample is likely underpowered to detect a modest shared signal. Furthermore, the OCD polygenic signal was significantly attenuated when cases with both OCD and co-occurring Tourette's syndrome/chronic tics were included in the analysis (p=0.01). Previous work has shown that Tourette's syndrome and OCD have some degree of shared genetic variation. However, the data from this study suggest that there are also distinct components to the genetic architectures of these two disorders. Furthermore, OCD with co-occurring Tourette's syndrome/chronic tics may have different underlying genetic susceptibility compared with OCD alone.

Polygenic sex determination in the cichlid fish Astatotilapia burtoni.

PubMed

Roberts, Natalie B; Juntti, Scott A; Coyle, Kaitlin P; Dumont, Bethany L; Stanley, M Kaitlyn; Ryan, Allyson Q; Fernald, Russell D; Roberts, Reade B

2016-10-26

The East African riverine cichlid species Astatotilapia burtoni serves as an important laboratory model for sexually dimorphic physiology and behavior, and also serves as an outgroup species for the explosive adaptive radiations of cichlid species in Lake Malawi and Lake Victoria. An astounding diversity of genetic sex determination systems have been revealed within the adaptive radiation of East African cichlids thus far, including polygenic sex determination systems involving the epistatic interaction of multiple, independently segregating sex determination alleles. However, sex determination has remained unmapped in A. burtoni. Here we present mapping results supporting the presence of multiple, novel sex determination alleles, and thus the presence of polygenic sex determination in A. burtoni. Using mapping in small families in conjunction with restriction-site associated DNA sequencing strategies, we identify associations with sex at loci on linkage group 13 and linkage group 5-14. Inheritance patterns support an XY sex determination system on linkage group 5-14 (a chromosome fusion relative to other cichlids studied), and an XYW system on linkage group 13, and these associations are replicated in multiple families. Additionally, combining our genetic data with comparative genomic analysis identifies another fusion that is unassociated with sex, with linkage group 8-24 and linkage group 16-21 fused in A. burtoni relative to other East African cichlid species. We identify genetic signals supporting the presence of three previously unidentified sex determination alleles at two loci in the species A. burtoni, strongly supporting the presence of polygenic sex determination system in the species. These results provide a foundation for future mapping of multiple sex determination genes and their interactions. A better understanding of sex determination in A. burtoni provides important context for their use in behavioral studies, as well as studies of the evolution of genetic sex determination and sexual conflicts in East African cichlids.

Traumatic Stress Interacts With Bipolar Disorder Genetic Risk to Increase Risk for Suicide Attempts.

PubMed

Wilcox, Holly C; Fullerton, Janice M; Glowinski, Anne L; Benke, Kelly; Kamali, Masoud; Hulvershorn, Leslie A; Stapp, Emma K; Edenberg, Howard J; Roberts, Gloria M P; Ghaziuddin, Neera; Fisher, Carrie; Brucksch, Christine; Frankland, Andrew; Toma, Claudio; Shaw, Alex D; Kastelic, Elizabeth; Miller, Leslie; McInnis, Melvin G; Mitchell, Philip B; Nurnberger, John I

2017-12-01

Bipolar disorder (BD) is one of the most heritable psychiatric conditions and is associated with high suicide risk. To explore the reasons for this link, this study examined the interaction between traumatic stress and BD polygenic risk score in relation to suicidal ideation, suicide attempt, and nonsuicidal self-injury (NSSI) in adolescent and young adult offspring and relatives of persons with BD (BD-relatives) compared with adolescent and young adult offspring of individuals without psychiatric disorders (controls). Data were collected from 4 sites in the United States and 1 site in Australia from 2006 through 2012. Generalized estimating equation models were used to compare rates of ideation, attempts, and NSSI between BD-relatives (n = 307) and controls (n = 166) and to determine the contribution of demographic factors, traumatic stress exposure, lifetime mood or substance (alcohol/drug) use disorders, and BD polygenic risk score. After adjusting for demographic characteristics and mood and substance use disorders, BD-relatives were at increased risk for suicidal ideation and attempts but not for NSSI. Independent of BD-relative versus control status, demographic factors, or mood and substance use disorders, exposure to trauma within the past year (including bullying, sexual abuse, and domestic violence) was associated with suicide attempts (p = .014), and BD polygenic risk score was marginally associated with attempts (p = .061). Importantly, the interaction between BD polygenic risk score and traumatic event exposures was significantly associated with attempts, independent of demographics, relative versus control status, and mood and substance use disorders (p = .041). BD-relatives are at increased risk for suicide attempts and ideation, especially if they are exposed to trauma and have evidence of increased genetic vulnerability. Copyright © 2017 American Academy of Child and Adolescent Psychiatry. Published by Elsevier Inc. All rights reserved.

SNP-based heritability estimates of the personality dimensions and polygenic prediction of both neuroticism and major depression: findings from CONVERGE.

PubMed

Docherty, A R; Moscati, A; Peterson, R; Edwards, A C; Adkins, D E; Bacanu, S A; Bigdeli, T B; Webb, B T; Flint, J; Kendler, K S

2016-10-25

Biometrical genetic studies suggest that the personality dimensions, including neuroticism, are moderately heritable (~0.4 to 0.6). Quantitative analyses that aggregate the effects of many common variants have recently further informed genetic research on European samples. However, there has been limited research to date on non-European populations. This study examined the personality dimensions in a large sample of Han Chinese descent (N=10 064) from the China, Oxford, and VCU Experimental Research on Genetic Epidemiology study, aimed at identifying genetic risk factors for recurrent major depression among a rigorously ascertained cohort. Heritability of neuroticism as measured by the Eysenck Personality Questionnaire (EPQ) was estimated to be low but statistically significant at 10% (s.e.=0.03, P=0.0001). In addition to EPQ, neuroticism based on a three-factor model, data for the Big Five (BF) personality dimensions (neuroticism, openness, conscientiousness, extraversion and agreeableness) measured by the Big Five Inventory were available for controls (n=5596). Heritability estimates of the BF were not statistically significant despite high power (>0.85) to detect heritabilities of 0.10. Polygenic risk scores constructed by best linear unbiased prediction weights applied to split-half samples failed to significantly predict any of the personality traits, but polygenic risk for neuroticism, calculated with LDpred and based on predictive variants previously identified from European populations (N=171 911), significantly predicted major depressive disorder case-control status (P=0.0004) after false discovery rate correction. The scores also significantly predicted EPQ neuroticism (P=6.3 × 10 -6 ). Factor analytic results of the measures indicated that any differences in heritabilities across samples may be due to genetic variation or variation in haplotype structure between samples, rather than measurement non-invariance. Findings demonstrate that neuroticism can be significantly predicted across ancestry, and highlight the importance of studying polygenic contributions to personality in non-European populations.

How could fully scaled carps appear in natural waters in Madagascar?

PubMed Central

Hervet, Caroline

2016-01-01

The capacity of organisms to rapidly evolve in response to environmental changes is a key feature of evolution, and studying mutation compensation is a way to evaluate whether alternative routes of evolution are possible or not. Common carps (Cyprinus carpio) carrying a homozygous loss-of-function mutation for the scale cover gene fgfr1a1, causing the ‘mirror’ reduced scale cover, were introduced in Madagascar a century ago. Here we show that carps in Malagasy natural waters are now predominantly covered with scales, though they still all carry the homozygous mutation. We also reveal that the number of scales in mutated carps is under strong polygenic genetic control, with a heritability of 0.49. As a whole, our results suggest that carps submitted to natural selection could evolve a wild-type-like scale cover in less than 40 generations from standing polygenic genetic variation, confirming similar findings mainly retrieved from model organisms. PMID:27559059

Exome Sequencing Provides Evidence of Polygenic Adaptation to a Fat-Rich Animal Diet in Indigenous Siberian Populations.

PubMed

Hsieh, PingHsun; Hallmark, Brian; Watkins, Joseph; Karafet, Tatiana M; Osipova, Ludmila P; Gutenkunst, Ryan N; Hammer, Michael F

2017-11-01

Siberia is one of the coldest environments on Earth and has great seasonal temperature variation. Long-term settlement in northern Siberia undoubtedly required biological adaptation to severe cold stress, dramatic variation in photoperiod, and limited food resources. In addition, recent archeological studies show that humans first occupied Siberia at least 45,000 years ago; yet our understanding of the demographic history of modern indigenous Siberians remains incomplete. In this study, we use whole-exome sequencing data from the Nganasans and Yakuts to infer the evolutionary history of these two indigenous Siberian populations. Recognizing the complexity of the adaptive process, we designed a model-based test to systematically search for signatures of polygenic selection. Our approach accounts for stochasticity in the demographic process and the hitchhiking effect of classic selective sweeps, as well as potential biases resulting from recombination rate and mutation rate heterogeneity. Our demographic inference shows that the Nganasans and Yakuts diverged ∼12,000-13,000 years ago from East-Asian ancestors in a process involving continuous gene flow. Our polygenic selection scan identifies seven candidate gene sets with Siberian-specific signals. Three of these gene sets are related to diet, especially to fat metabolism, consistent with the hypothesis of adaptation to a fat-rich animal diet. Additional testing rejects the effect of hitchhiking and favors a model in which selection yields small allele frequency changes at multiple unlinked genes. © The Author 2017. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Comparing the predictive abilities of phenotypic and marker-assisted selection methods in a biparental lettuce population

USDA-ARS?s Scientific Manuscript database

Breeding and selection for the traits with polygenic inheritance is a challenging task that can be done by phenotypic selection, by marker-assisted selection or by genome wide selection. We tested predictive ability of four selection models in a biparental population genotyped with 95 SNP markers an...

Sequence-Based Prioritization of Nonsynonymous Single-Nucleotide Polymorphisms for the Study of Disease Mutations

PubMed Central

Jiang, Rui ; Yang, Hua ; Zhou, Linqi ; Kuo, C.-C. Jay ; Sun, Fengzhu ; Chen, Ting 

2007-01-01

The increasing demand for the identification of genetic variation responsible for common diseases has translated into a need for sophisticated methods for effectively prioritizing mutations occurring in disease-associated genetic regions. In this article, we prioritize candidate nonsynonymous single-nucleotide polymorphisms (nsSNPs) through a bioinformatics approach that takes advantages of a set of improved numeric features derived from protein-sequence information and a new statistical learning model called “multiple selection rule voting” (MSRV). The sequence-based features can maximize the scope of applications of our approach, and the MSRV model can capture subtle characteristics of individual mutations. Systematic validation of the approach demonstrates that this approach is capable of prioritizing causal mutations for both simple monogenic diseases and complex polygenic diseases. Further studies of familial Alzheimer diseases and diabetes show that the approach can enrich mutations underlying these polygenic diseases among the top of candidate mutations. Application of this approach to unclassified mutations suggests that there are 10 suspicious mutations likely to cause diseases, and there is strong support for this in the literature. PMID:17668383

Polygenic Risk for Schizophrenia Influences Cortical Gyrification in 2 Independent General Populations.

PubMed

Liu, Bing; Zhang, Xiaolong; Cui, Yue; Qin, Wen; Tao, Yan; Li, Jin; Yu, Chunshui; Jiang, Tianzi

2017-05-01

Schizophrenia is highly heritable, whereas the effect of each genetic variant is very weak. Since clinical heterogeneity and complexity of schizophrenia is high, considerable effort has been made to relate genetic variants to underlying neurobiological aspects of schizophrenia (endophenotypes). Given the polygenic nature of schizophrenia, our goal was to form a measure of additive genetic risk and explore its relationship to cortical morphology. Utilizing the data from a recent genome-wide association study that included nearly 37 000 cases of schizophrenia, we computed a polygenic risk score (PGRS) for each subject in 2 independent and healthy general populations. We then investigated the effect of polygenic risk for schizophrenia on cortical gyrification calculated from 3.0T structural imaging data in the discovery dataset (N = 315) and replication dataset (N = 357). We found a consistent effect of the polygenic risk for schizophrenia on cortical gyrification in the inferior parietal lobules in 2 independent general-population samples. A higher PGRS was significantly associated with a lower local gyrification index in the bilateral inferior parietal lobles, where case-control differences have been reported in previous studies on schizophrenia. Our findings strongly support the effectiveness of both PGRSs and endophenotypes in establishing the genetic architecture of psychiatry. Our findings may provide some implications regarding individual differences in the genetic risk for schizophrenia to cortical morphology and brain development. © The Author 2016. Published by Oxford University Press on behalf of the Maryland Psychiatric Research Center. All rights reserved. For permissions, please email: journals.permissions@oup.com.

Lifelong obesity in a polygenic mouse model prevents age- and diet-induced glucose intolerance- obesity is no road to late-onset diabetes in mice.

PubMed

Renne, Ulla; Langhammer, Martina; Brenmoehl, Julia; Walz, Christina; Zeissler, Anja; Tuchscherer, Armin; Piechotta, Marion; Wiesner, Rudolf J; Bielohuby, Maximilian; Hoeflich, Andreas

2013-01-01

Visceral obesity holds a central position in the concept of the metabolic syndrome characterized by glucose intolerance in humans. However, until now it is unclear if obesity by itself is responsible for the development of glucose intolerance. We have used a novel polygenic mouse model characterized by genetically fixed obesity (DU6) and addressed age- and high fat diet-dependent glucose tolerance. Phenotype selection over 146 generations increased body weight by about 2.7-fold in male 12-week DU6 mice (P<0.0001) if compared to unselected controls (Fzt:DU). Absolute epididymal fat mass was particularly responsive to weight selection and increased by more than 5-fold (P<0.0001) in male DU6 mice. At an age of 6 weeks DU6 mice consumed about twice as much food if compared to unselected controls (P<0.001). Absolute food consumption was higher at all time points measured in DU6 mice than in Fzt:DU mice. Between 6 and 12 weeks of age, absolute food intake was reduced by 15% in DU6 mice (P<0.001) but not in Fzt:DU mice. In both mouse lines feeding of the high fat diet elevated body mass if compared to the control diet (P<0.05). In contrast to controls, DU6 mice did not display high fat diet-induced increases of epididymal and renal fat. Control mice progressively developed glucose intolerance with advancing age and even more in response to the high fat diet. In contrast, obese DU6 mice did neither develop a glucose intolerant phenotype with progressive age nor when challenged with a high fat diet. Our results from a polygenic mouse model demonstrate that genetically pre-determined and life-long obesity is no precondition of glucose intolerance later in life.

Assessing the complex architecture of polygenic traits in diverged yeast populations.

PubMed

Cubillos, Francisco A; Billi, Eleonora; Zörgö, Enikö; Parts, Leopold; Fargier, Patrick; Omholt, Stig; Blomberg, Anders; Warringer, Jonas; Louis, Edward J; Liti, Gianni

2011-04-01

Phenotypic variation arising from populations adapting to different niches has a complex underlying genetic architecture. A major challenge in modern biology is to identify the causative variants driving phenotypic variation. Recently, the baker's yeast, Saccharomyces cerevisiae has emerged as a powerful model for dissecting complex traits. However, past studies using a laboratory strain were unable to reveal the complete architecture of polygenic traits. Here, we present a linkage study using 576 recombinant strains obtained from crosses of isolates representative of the major lineages. The meiotic recombinational landscape appears largely conserved between populations; however, strain-specific hotspots were also detected. Quantitative measurements of growth in 23 distinct ecologically relevant environments show that our recombinant population recapitulates most of the standing phenotypic variation described in the species. Linkage analysis detected an average of 6.3 distinct QTLs for each condition tested in all crosses, explaining on average 39% of the phenotypic variation. The QTLs detected are not constrained to a small number of loci, and the majority are specific to a single cross-combination and to a specific environment. Moreover, crosses between strains of similar phenotypes generate greater variation in the offspring, suggesting the presence of many antagonistic alleles and epistatic interactions. We found that subtelomeric regions play a key role in defining individual quantitative variation, emphasizing the importance of the adaptive nature of these regions in natural populations. This set of recombinant strains is a powerful tool for investigating the complex architecture of polygenic traits. © 2011 Blackwell Publishing Ltd.

Using an Alzheimer Disease Polygenic Risk Score to Predict Memory Decline in Black and White Americans Over 14 Years of Follow-up.

PubMed

Marden, Jessica R; Mayeda, Elizabeth R; Walter, Stefan; Vivot, Alexandre; Tchetgen Tchetgen, Eric J; Kawachi, Ichiro; Glymour, M Maria

2016-01-01

Evidence on whether genetic predictors of Alzheimer disease (AD) also predict memory decline is inconsistent, and limited data are available for African ancestry populations. For 8253 non-Hispanic white (NHW) and non-Hispanic black (NHB) Health and Retirement Study participants with memory scores measured 1 to 8 times between 1998 and 2012 (average baseline age=62), we calculated weighted polygenic risk scores [AD Genetic Risk Score (AD-GRS)] using the top 22 AD-associated loci, and an alternative score excluding apolipoprotein E (APOE) (AD-GRSexAPOE). We used generalized linear models with AD-GRS-by-age and AD-GRS-by-age interactions (age centered at 70) to predict memory decline. Average NHB decline was 26% faster than NHW decline (P<0.001). Among NHW, 10% higher AD-GRS predicted faster memory decline (linear β=-0.058 unit decrease over 10 y; 95% confidence interval,-0.074 to -0.043). AD-GRSexAPOE also predicted faster decline for NHW, although less strongly. Among NHB, AD-GRS predicted faster memory decline (linear β=-0.050; 95% confidence interval, -0.106 to 0.006), but AD-GRSexAPOE did not. Our nonsignificant estimate among NHB may reflect insufficient statistical power or a misspecified AD-GRS among NHB as an overwhelming majority of genome-wide association studies are conducted in NHW. A polygenic score based on previously identified AD loci predicts memory loss in US blacks and whites.

Selection in action: dissecting the molecular underpinnings of the increasing muscle mass of Belgian Blue Cattle.

PubMed

Druet, Tom; Ahariz, Naima; Cambisano, Nadine; Tamma, Nico; Michaux, Charles; Coppieters, Wouter; Charlier, Carole; Georges, Michel

2014-09-17

Belgian Blue cattle are famous for their exceptional muscular development or "double-muscling". This defining feature emerged following the fixation of a loss-of-function variant in the myostatin gene in the eighties. Since then, sustained selection has further increased muscle mass of Belgian Blue animals to a comparable extent. In the present paper, we study the genetic determinants of this second wave of muscle growth. A scan for selective sweeps did not reveal the recent fixation of another allele with major effect on muscularity. However, a genome-wide association study identified two genome-wide significant and three suggestive quantitative trait loci (QTL) affecting specific muscle groups and jointly explaining 8-21% of the heritability. The top two QTL are caused by presumably recent mutations on unique haplotypes that have rapidly risen in frequency in the population. While one appears on its way to fixation, the ascent of the other is compromised as the likely underlying MRC2 mutation causes crooked tail syndrome in homozygotes. Genomic prediction models indicate that the residual additive variance is largely polygenic. Contrary to complex traits in humans which have a near-exclusive polygenic architecture, muscle mass in beef cattle (as other production traits under directional selection), appears to be controlled by (i) a handful of recent mutations with large effect that rapidly sweep through the population, and (ii) a large number of presumably older variants with very small effects that rise slowly in the population (polygenic adaptation).

Genome-Wide Polygenic Scores Predict Reading Performance throughout the School Years

ERIC Educational Resources Information Center

Selzam, Saskia; Dale, Philip S.; Wagner, Richard K.; DeFries, John C.; Cederlöf, Martin; O'Reilly, Paul F.; Krapohl, Eva; Plomin, Robert

2017-01-01

It is now possible to create individual-specific genetic scores, called genome-wide polygenic scores (GPS). We used a GPS for years of education ("EduYears") to predict reading performance assessed at UK National Curriculum Key Stages 1 (age 7), 2 (age 12) and 3 (age 14) and on reading tests administered at ages 7 and 12 in a UK sample…

Genome-wide association study of response to cognitive-behavioural therapy in children with anxiety disorders.

PubMed

Coleman, Jonathan R I; Lester, Kathryn J; Keers, Robert; Roberts, Susanna; Curtis, Charles; Arendt, Kristian; Bögels, Susan; Cooper, Peter; Creswell, Cathy; Dalgleish, Tim; Hartman, Catharina A; Heiervang, Einar R; Hötzel, Katrin; Hudson, Jennifer L; In-Albon, Tina; Lavallee, Kristen; Lyneham, Heidi J; Marin, Carla E; Meiser-Stedman, Richard; Morris, Talia; Nauta, Maaike H; Rapee, Ronald M; Schneider, Silvia; Schneider, Sophie C; Silverman, Wendy K; Thastum, Mikael; Thirlwall, Kerstin; Waite, Polly; Wergeland, Gro Janne; Breen, Gerome; Eley, Thalia C

2016-09-01

Anxiety disorders are common, and cognitive-behavioural therapy (CBT) is a first-line treatment. Candidate gene studies have suggested a genetic basis to treatment response, but findings have been inconsistent. To perform the first genome-wide association study (GWAS) of psychological treatment response in children with anxiety disorders (n = 980). Presence and severity of anxiety was assessed using semi-structured interview at baseline, on completion of treatment (post-treatment), and 3 to 12 months after treatment completion (follow-up). DNA was genotyped using the Illumina Human Core Exome-12v1.0 array. Linear mixed models were used to test associations between genetic variants and response (change in symptom severity) immediately post-treatment and at 6-month follow-up. No variants passed a genome-wide significance threshold (P = 5 × 10(-8)) in either analysis. Four variants met criteria for suggestive significance (P<5 × 10(-6)) in association with response post-treatment, and three variants in the 6-month follow-up analysis. This is the first genome-wide therapygenetic study. It suggests no common variants of very high effect underlie response to CBT. Future investigations should maximise power to detect single-variant and polygenic effects by using larger, more homogeneous cohorts. © The Royal College of Psychiatrists 2016.

Genome-wide association study of response to cognitive–behavioural therapy in children with anxiety disorders

PubMed Central

Coleman, Jonathan R. I.; Lester, Kathryn J.; Keers, Robert; Roberts, Susanna; Curtis, Charles; Arendt, Kristian; Bögels, Susan; Cooper, Peter; Creswell, Cathy; Dalgleish, Tim; Hartman, Catharina A.; Heiervang, Einar R.; Hötzel, Katrin; Hudson, Jennifer L.; In-Albon, Tina; Lavallee, Kristen; Lyneham, Heidi J.; Marin, Carla E.; Meiser-Stedman, Richard; Morris, Talia; Nauta, Maaike H.; Rapee, Ronald M.; Schneider, Silvia; Schneider, Sophie C.; Silverman, Wendy K.; Thastum, Mikael; Thirlwall, Kerstin; Waite, Polly; Wergeland, Gro Janne; Breen, Gerome; Eley, Thalia C.

2016-01-01

Background Anxiety disorders are common, and cognitive–behavioural therapy (CBT) is a first-line treatment. Candidate gene studies have suggested a genetic basis to treatment response, but findings have been inconsistent. Aims To perform the first genome-wide association study (GWAS) of psychological treatment response in children with anxiety disorders (n = 980). Method Presence and severity of anxiety was assessed using semi-structured interview at baseline, on completion of treatment (post-treatment), and 3 to 12 months after treatment completion (follow-up). DNA was genotyped using the Illumina Human Core Exome-12v1.0 array. Linear mixed models were used to test associations between genetic variants and response (change in symptom severity) immediately post-treatment and at 6-month follow-up. Results No variants passed a genome-wide significance threshold (P = 5 × 10−8) in either analysis. Four variants met criteria for suggestive significance (P<5 × 10−6) in association with response post-treatment, and three variants in the 6-month follow-up analysis. Conclusions This is the first genome-wide therapygenetic study. It suggests no common variants of very high effect underlie response to CBT. Future investigations should maximise power to detect single-variant and polygenic effects by using larger, more homogeneous cohorts. PMID:26989097

The Contribution of GWAS Loci in Familial Dyslipidemias

PubMed Central

Söderlund, Sanni; Surakka, Ida; Matikainen, Niina; Pirinen, Matti; Pajukanta, Päivi; Service, Susan K.; Laurila, Pirkka-Pekka; Ehnholm, Christian; Salomaa, Veikko; Wilson, Richard K.; Palotie, Aarno; Freimer, Nelson B.; Taskinen, Marja-Riitta; Ripatti, Samuli

2016-01-01

Familial combined hyperlipidemia (FCH) is a complex and common familial dyslipidemia characterized by elevated total cholesterol and/or triglyceride levels with over five-fold risk of coronary heart disease. The genetic architecture and contribution of rare Mendelian and common variants to FCH susceptibility is unknown. In 53 Finnish FCH families, we genotyped and imputed nine million variants in 715 family members with DNA available. We studied the enrichment of variants previously implicated with monogenic dyslipidemias and/or lipid levels in the general population by comparing allele frequencies between the FCH families and population samples. We also constructed weighted polygenic scores using 212 lipid-associated SNPs and estimated the relative contributions of Mendelian variants and polygenic scores to the risk of FCH in the families. We identified, across the whole allele frequency spectrum, an enrichment of variants known to elevate, and a deficiency of variants known to lower LDL-C and/or TG levels among both probands and affected FCH individuals. The score based on TG associated SNPs was particularly high among affected individuals compared to non-affected family members. Out of 234 affected FCH individuals across the families, seven (3%) carried Mendelian variants and 83 (35%) showed high accumulation of either known LDL-C or TG elevating variants by having either polygenic score over the 90th percentile in the population. The positive predictive value of high score was much higher for affected FCH individuals than for similar sporadic cases in the population. FCH is highly polygenic, supporting the hypothesis that variants across the whole allele frequency spectrum contribute to this complex familial trait. Polygenic SNP panels improve identification of individuals affected with FCH, but their clinical utility remains to be defined. PMID:27227539

Contributions of polygenic risk for obesity to PTSD-related metabolic syndrome and cortical thickness.

PubMed

Wolf, Erika J; Miller, Danielle R; Logue, Mark W; Sumner, Jennifer; Stoop, Tawni B; Leritz, Elizabeth C; Hayes, Jasmeet P; Stone, Annjanette; Schichman, Steven A; McGlinchey, Regina E; Milberg, William P; Miller, Mark W

2017-10-01

Research suggests that posttraumatic stress disorder (PTSD) is associated with metabolic syndrome (MetS) and that PTSD-associated MetS is related to decreased cortical thickness. However, the role of genetic factors in these associations is unclear. This study evaluated contributions of polygenic obesity risk and PTSD to MetS and of MetS and polygenic obesity risk to cortical thickness. 196 white, non-Hispanic veterans of the wars in Iraq and Afghanistan underwent clinical diagnostic interviews, physiological assessments, and genome-wide genotyping; 168 also completed magnetic resonance imaging scans. Polygenic risk scores (PRSs) for obesity were calculated from results of a prior genome-wide association study (Speliotes et al., 2010) and PTSD and MetS severity factor scores were obtained. Obesity PRS (β=0.15, p=0.009) and PTSD (β=0.17, p=0.005) predicted MetS and interacted such that the association between PTSD and MetS was stronger in individuals with greater polygenic obesity risk (β=0.13, p=0.02). Whole-brain vertex-wise analyses suggested that obesity PRS interacted with MetS to predict decreased cortical thickness in left rostral middle frontal gyrus (β=-0.40, p<0.001). Results suggest that PTSD, genetic variability, and MetS are related in a transactional fashion wherein obesity genetic risk increases stress-related metabolic pathology, and compounds the ill health effects of MetS on the brain. Genetic proclivity towards MetS should be considered in PTSD patients when prescribing psychotropic medications with adverse metabolic profiles. Results are consistent with a growing literature suggestive of PTSD-related accelerated aging. Published by Elsevier Inc.

Effects of aqueous extracts of dried calyx of sour tea (Hibiscus sabdariffa L.) on polygenic dyslipidemia: A randomized clinical trial.

PubMed

Hajifaraji, Majid; Matlabi, Mohammad; Ahmadzadeh-Sani, Farihe; Mehrabi, Yadollah; Rezaee, Mohammad Salem; Hajimehdipour, Homa; Hasanzadeh, Abbas; Roghani, Katayoun

2018-01-01

Dyslipidemia has been considered as a major risk factor for coronary heart disease. Alternative medicine has a significant role in treatment of dyslipidemia. There are controversial findings regarding the effects of sour tea on dyslipidemia. The aim of this study was to evaluate the impact of aqueous extract of dried calyx of sour tea on polygenic dyslipidemia. This clinical trial was done on 43 adults (30-60 years old) with polygenic dyslipidemia that were randomly assigned to the intervention and control groups. The control group was trained in lifestyle modifications at baseline. The intervention group was trained for lifestyle modifications at baseline and received two cups of sour tea daily, and both groups were followed up for 12 weeks. Lipid profile was evaluated at baseline, and six and 12 weeks following the intervention. In addition, dietary and physical activity assessed at baseline for twelve weeks. Mean concentration of total cholesterol, HDL-C and LDL-C significantly decreased by up to 9.46%, 8.33%, and 9.80%, respectively, after 12 weeks in the intervention group in comparison to their baseline values. However, LDL-C/HDL-C ratio significantly increased by up to 3.15%, following 12 weeks in the control group in comparison to their baseline values. This study showed no difference in lipid profiles between the two groups, except for HDL-C concentrations. sour tea may have significant positive effects on lipid profile of polygenic dyslipidemia subjects and these effect might be attributed to its anthocyanins and inflation factor content. Therefore, sour tea intake with recommended dietary patterns and physical activity can be useful in regulation of lipid profile in patients with polygenic dyslipidemia.

Cross-Disorder Genome-Wide Analyses Suggest a Complex Genetic Relationship Between Tourette Syndrome and Obsessive-Compulsive Disorder

PubMed Central

Yu, Dongmei; Mathews, Carol A.; Scharf, Jeremiah M.; Neale, Benjamin M.; Davis, Lea K.; Gamazon, Eric R.; Derks, Eske M.; Evans, Patrick; Edlund, Christopher K.; Crane, Jacquelyn; Fagerness, Jesen A.; Osiecki, Lisa; Gallagher, Patience; Gerber, Gloria; Haddad, Stephen; Illmann, Cornelia; McGrath, Lauren M.; Mayerfeld, Catherine; Arepalli, Sampath; Barlassina, Cristina; Barr, Cathy L.; Bellodi, Laura; Benarroch, Fortu; Berrió, Gabriel Bedoya; Bienvenu, O. Joseph; Black, Donald; Bloch, Michael H.; Brentani, Helena; Bruun, Ruth D.; Budman, Cathy L.; Camarena, Beatriz; Campbell, Desmond D.; Cappi, Carolina; Cardona Silgado, Julio C.; Cavallini, Maria C.; Chavira, Denise A.; Chouinard, Sylvain; Cook, Edwin H.; Cookson, M. R.; Coric, Vladimir; Cullen, Bernadette; Cusi, Daniele; Delorme, Richard; Denys, Damiaan; Dion, Yves; Eapen, Valsama; Egberts, Karin; Falkai, Peter; Fernandez, Thomas; Fournier, Eduardo; Garrido, Helena; Geller, Daniel; Gilbert, Donald; Girard, Simon L.; Grabe, Hans J.; Grados, Marco A.; Greenberg, Benjamin D.; Gross-Tsur, Varda; Grünblatt, Edna; Hardy, John; Heiman, Gary A.; Hemmings, Sian M.J.; Herrera, Luis D.; Hezel, Dianne M.; Hoekstra, Pieter J.; Jankovic, Joseph; Kennedy, James L.; King, Robert A.; Konkashbaev, Anuar I.; Kremeyer, Barbara; Kurlan, Roger; Lanzagorta, Nuria; Leboyer, Marion; Leckman, James F.; Lennertz, Leonhard; Liu, Chunyu; Lochner, Christine; Lowe, Thomas L.; Lupoli, Sara; Macciardi, Fabio; Maier, Wolfgang; Manunta, Paolo; Marconi, Maurizio; McCracken, James T.; Mesa Restrepo, Sandra C.; Moessner, Rainald; Moorjani, Priya; Morgan, Jubel; Muller, Heike; Murphy, Dennis L.; Naarden, Allan L.; Ochoa, William Cornejo; Ophoff, Roel A.; Pakstis, Andrew J.; Pato, Michele T.; Pato, Carlos N.; Piacentini, John; Pittenger, Christopher; Pollak, Yehuda; Rauch, Scott L.; Renner, Tobias; Reus, Victor I.; Richter, Margaret A.; Riddle, Mark A.; Robertson, Mary M.; Romero, Roxana; Rosário, Maria C.; Rosenberg, David; Ruhrmann, Stephan; Sabatti, Chiara; Salvi, Erika; Sampaio, Aline S.; Samuels, Jack; Sandor, Paul; Service, Susan K.; Sheppard, Brooke; Singer, Harvey S.; Smit, Jan H.; Stein, Dan J.; Strengman, Eric; Tischfield, Jay A.; Turiel, Maurizio; Valencia Duarte, Ana V.; Vallada, Homero; Veenstra-VanderWeele, Jeremy; Walitza, Susanne; Walkup, John; Wang, Ying; Weale, Mike; Weiss, Robert; Wendland, Jens R.; Westenberg, Herman G.M.; Yao, Yin; Hounie, Ana G.; Miguel, Euripedes C.; Nicolini, Humberto; Wagner, Michael; Ruiz-Linares, Andres; Cath, Danielle C.; McMahon, William; Posthuma, Danielle; Oostra, Ben A.; Nestadt, Gerald; Rouleau, Guy A.; Purcell, Shaun; Jenike, Michael A.; Heutink, Peter; Hanna, Gregory L.; Conti, David V.; Arnold, Paul D.; Freimer, Nelson; Stewart, S. Evelyn; Knowles, James A.; Cox, Nancy J.; Pauls, David L.

2014-01-01

Obsessive-compulsive disorder (OCD) and Tourette Syndrome (TS) are highly heritable neurodevelopmental disorders that are thought to share genetic risk factors. However, the identification of definitive susceptibility genes for these etiologically complex disorders remains elusive. Here, we report a combined genome-wide association study (GWAS) of TS and OCD in 2723 cases (1310 with OCD, 834 with TS, 579 with OCD plus TS/chronic tics (CT)), 5667 ancestry-matched controls, and 290 OCD parent-child trios. Although no individual single nucleotide polymorphisms (SNPs) achieved genome-wide significance, the GWAS signals were enriched for SNPs strongly associated with variations in brain gene expression levels, i.e. expression quantitative loci (eQTLs), suggesting the presence of true functional variants that contribute to risk of these disorders. Polygenic score analyses identified a significant polygenic component for OCD (p=2×10−4), predicting 3.2% of the phenotypic variance in an independent data set. In contrast, TS had a smaller, non-significant polygenic component, predicting only 0.6% of the phenotypic variance (p=0.06). No significant polygenic signal was detected across the two disorders, although the sample is likely underpowered to detect a modest shared signal. Furthermore, the OCD polygenic signal was significantly attenuated when cases with both OCD and TS/CT were included in the analysis (p=0.01). Previous work has shown that TS and OCD have some degree of shared genetic variation. However, the data from this study suggest that there are also distinct components to the genetic architectures of TS and OCD. Furthermore, OCD with co-occurring TS/CT may have different underlying genetic susceptibility compared to OCD alone. PMID:25158072

Investigating the genetic variation underlying episodicity in major depressive disorder: suggestive evidence for a bipolar contribution.

PubMed

Ferentinos, Panagiotis; Rivera, Margarita; Ising, Marcus; Spain, Sarah L; Cohen-Woods, Sarah; Butler, Amy W; Craddock, Nicholas; Owen, Michael J; Korszun, Ania; Jones, Lisa; Jones, Ian; Gill, Michael; Rice, John P; Maier, Wolfgang; Mors, Ole; Rietschel, Marcella; Lucae, Susanne; Binder, Elisabeth B; Preisig, Martin; Tozzi, Federica; Muglia, Pierandrea; Breen, Gerome; Craig, Ian W; Farmer, Anne E; Müller-Myhsok, Bertram; McGuffin, Peter; Lewis, Cathryn M

2014-02-01

Highly recurrent major depressive disorder (MDD) has reportedly increased risk of shifting to bipolar disorder; high recurrence frequency has, therefore, featured as evidence of 'soft bipolarity'. We aimed to investigate the genetic underpinnings of total depressive episode count in recurrent MDD. Our primary sample included 1966 MDD cases with negative family history of bipolar disorder from the RADIANT studies. Total episode count was adjusted for gender, age, MDD duration, study and center before being tested for association with genotype in two separate genome-wide analyses (GWAS), in the full set and in a subset of 1364 cases with positive family history of MDD (FH+). We also calculated polygenic scores from the Psychiatric Genomics Consortium MDD and bipolar disorder studies. Episodicity (especially intermediate episode counts) was an independent index of MDD familial aggregation, replicating previous reports. The GWAS produced no genome-wide significant findings. The strongest signals were detected in the full set at MAGI1 (p=5.1×10(-7)), previously associated with bipolar disorder, and in the FH+ subset at STIM1 (p=3.9×10(-6) after imputation), a calcium channel signaling gene. However, these findings failed to replicate in an independent Munich cohort. In the full set polygenic profile analyses, MDD polygenes predicted episodicity better than bipolar polygenes; however, in the FH+ subset, both polygenic scores performed similarly. Episode count was self-reported and, therefore, subject to recall bias. Our findings lend preliminary support to the hypothesis that highly recurrent MDD with FH+ is part of a 'soft bipolar spectrum' but await replication in larger cohorts. © 2013 Published by Elsevier B.V.

Genome-wide association study of clinical dimensions of schizophrenia: polygenic effect on disorganized symptoms.

PubMed

Fanous, Ayman H; Zhou, Baiyu; Aggen, Steven H; Bergen, Sarah E; Amdur, Richard L; Duan, Jubao; Sanders, Alan R; Shi, Jianxin; Mowry, Bryan J; Olincy, Ann; Amin, Farooq; Cloninger, C Robert; Silverman, Jeremy M; Buccola, Nancy G; Byerley, William F; Black, Donald W; Freedman, Robert; Dudbridge, Frank; Holmans, Peter A; Ripke, Stephan; Gejman, Pablo V; Kendler, Kenneth S; Levinson, Douglas F

2012-12-01

Multiple sources of evidence suggest that genetic factors influence variation in clinical features of schizophrenia. The authors present the first genome-wide association study (GWAS) of dimensional symptom scores among individuals with schizophrenia. Based on the Lifetime Dimensions of Psychosis Scale ratings of 2,454 case subjects of European ancestry from the Molecular Genetics of Schizophrenia (MGS) sample, three symptom factors (positive, negative/disorganized, and mood) were identified with exploratory factor analysis. Quantitative scores for each factor from a confirmatory factor analysis were analyzed for association with 696,491 single-nucleotide polymorphisms (SNPs) using linear regression, with correction for age, sex, clinical site, and ancestry. Polygenic score analysis was carried out to determine whether case and comparison subjects in 16 Psychiatric GWAS Consortium (PGC) schizophrenia samples (excluding MGS samples) differed in scores computed by weighting their genotypes by MGS association test results for each symptom factor. No genome-wide significant associations were observed between SNPs and factor scores. Most of the SNPs producing the strongest evidence for association were in or near genes involved in neurodevelopment, neuroprotection, or neurotransmission, including genes playing a role in Mendelian CNS diseases, but no statistically significant effect was observed for any defined gene pathway. Finally, polygenic scores based on MGS GWAS results for the negative/disorganized factor were significantly different between case and comparison subjects in the PGC data set; for MGS subjects, negative/disorganized factor scores were correlated with polygenic scores generated using case-control GWAS results from the other PGC samples. The polygenic signal that has been observed in cross-sample analyses of schizophrenia GWAS data sets could be in part related to genetic effects on negative and disorganized symptoms (i.e., core features of chronic schizophrenia).

Single Nucleotide Variants Associated With Polygenic Hypercholesterolemia in Families Diagnosed Clinically With Familial Hypercholesterolemia.

PubMed

Lamiquiz-Moneo, Itziar; Pérez-Ruiz, María Rosario; Jarauta, Estíbaliz; Tejedor, María Teresa; Bea, Ana M; Mateo-Gallego, Rocío; Pérez-Calahorra, Sofía; Baila-Rueda, Lucía; Marco-Benedí, Victoria; de Castro-Orós, Isabel; Cenarro, Ana; Civeira, Fernando

2018-05-01

Approximately 20% to 40% of clinically defined familial hypercholesterolemia cases do not show a causative mutation in candidate genes, and some of them may have a polygenic origin. A cholesterol gene risk score for the diagnosis of polygenic hypercholesterolemia has been demonstrated to be valuable to differentiate polygenic and monogenic hypercholesterolemia. The aim of this study was to determine the contribution to low-density lipoprotein cholesterol (LDL-C) of the single nucleotide variants associated with polygenic hypercholesterolemia in probands with genetic hypercholesterolemia without mutations in candidate genes (nonfamilial hypercholesterolemia genetic hypercholesterolemia) and the genetic score in cascade screening in their family members. We recruited 49 nonfamilial hypercholesterolemia genetic hypercholesterolemia families (294 participants) and calculated cholesterol gene scores, derived from single nucleotide variants in SORT1, APOB, ABCG8, APOE and LDLR and lipoprotein(a) plasma concentration. Risk alleles in SORT1, ABCG8, APOE, and LDLR showed a statistically significantly higher frequency in blood relatives than in the 1000 Genomes Project. However, there were no differences between affected and nonaffected members. The contribution of the cholesterol gene score to LDL-C was significantly higher in affected than in nonaffected participants (P = .048). The percentage of the LDL-C variation explained by the score was 3.1%, and this percentage increased to 6.9% in those families with the highest genetic score in the proband. Nonfamilial hypercholesterolemia genetic hypercholesterolemia families concentrate risk alleles for high LDL-C. Their contribution varies greatly among families, indicating the complexity and heterogeneity of these forms of hypercholesterolemias. The gene score explains a small percentage of LDL-C, which limits its use in diagnosis. Copyright © 2017 Sociedad Española de Cardiología. Published by Elsevier España, S.L.U. All rights reserved.

Shared molecular neuropathology across major psychiatric disorders parallels polygenic overlap.

PubMed

Gandal, Michael J; Haney, Jillian R; Parikshak, Neelroop N; Leppa, Virpi; Ramaswami, Gokul; Hartl, Chris; Schork, Andrew J; Appadurai, Vivek; Buil, Alfonso; Werge, Thomas M; Liu, Chunyu; White, Kevin P; Horvath, Steve; Geschwind, Daniel H

2018-02-09

The predisposition to neuropsychiatric disease involves a complex, polygenic, and pleiotropic genetic architecture. However, little is known about how genetic variants impart brain dysfunction or pathology. We used transcriptomic profiling as a quantitative readout of molecular brain-based phenotypes across five major psychiatric disorders-autism, schizophrenia, bipolar disorder, depression, and alcoholism-compared with matched controls. We identified patterns of shared and distinct gene-expression perturbations across these conditions. The degree of sharing of transcriptional dysregulation is related to polygenic (single-nucleotide polymorphism-based) overlap across disorders, suggesting a substantial causal genetic component. This comprehensive systems-level view of the neurobiological architecture of major neuropsychiatric illness demonstrates pathways of molecular convergence and specificity. Copyright © 2018 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.

Polygenic determinants in extremes of high-density lipoprotein cholesterol[S

PubMed Central

Dron, Jacqueline S.; Wang, Jian; Low-Kam, Cécile; Khetarpal, Sumeet A.; Robinson, John F.; McIntyre, Adam D.; Ban, Matthew R.; Cao, Henian; Rhainds, David; Dubé, Marie-Pierre; Rader, Daniel J.; Lettre, Guillaume; Tardif, Jean-Claude

2017-01-01

HDL cholesterol (HDL-C) remains a superior biochemical predictor of CVD risk, but its genetic basis is incompletely defined. In patients with extreme HDL-C concentrations, we concurrently evaluated the contributions of multiple large- and small-effect genetic variants. In a discovery cohort of 255 unrelated lipid clinic patients with extreme HDL-C levels, we used a targeted next-generation sequencing panel to evaluate rare variants in known HDL metabolism genes, simultaneously with common variants bundled into a polygenic trait score. Two additional cohorts were used for validation and included 1,746 individuals from the Montréal Heart Institute Biobank and 1,048 individuals from the University of Pennsylvania. Findings were consistent between cohorts: we found rare heterozygous large-effect variants in 18.7% and 10.9% of low- and high-HDL-C patients, respectively. We also found common variant accumulation, indicated by extreme polygenic trait scores, in an additional 12.8% and 19.3% of overall cases of low- and high-HDL-C extremes, respectively. Thus, the genetic basis of extreme HDL-C concentrations encountered clinically is frequently polygenic, with contributions from both rare large-effect and common small-effect variants. Multiple types of genetic variants should be considered as contributing factors in patients with extreme dyslipidemia. PMID:28870971

Polygenic determinants in extremes of high-density lipoprotein cholesterol.

PubMed

Dron, Jacqueline S; Wang, Jian; Low-Kam, Cécile; Khetarpal, Sumeet A; Robinson, John F; McIntyre, Adam D; Ban, Matthew R; Cao, Henian; Rhainds, David; Dubé, Marie-Pierre; Rader, Daniel J; Lettre, Guillaume; Tardif, Jean-Claude; Hegele, Robert A

2017-11-01

HDL cholesterol (HDL-C) remains a superior biochemical predictor of CVD risk, but its genetic basis is incompletely defined. In patients with extreme HDL-C concentrations, we concurrently evaluated the contributions of multiple large- and small-effect genetic variants. In a discovery cohort of 255 unrelated lipid clinic patients with extreme HDL-C levels, we used a targeted next-generation sequencing panel to evaluate rare variants in known HDL metabolism genes, simultaneously with common variants bundled into a polygenic trait score. Two additional cohorts were used for validation and included 1,746 individuals from the Montréal Heart Institute Biobank and 1,048 individuals from the University of Pennsylvania. Findings were consistent between cohorts: we found rare heterozygous large-effect variants in 18.7% and 10.9% of low- and high-HDL-C patients, respectively. We also found common variant accumulation, indicated by extreme polygenic trait scores, in an additional 12.8% and 19.3% of overall cases of low- and high-HDL-C extremes, respectively. Thus, the genetic basis of extreme HDL-C concentrations encountered clinically is frequently polygenic, with contributions from both rare large-effect and common small-effect variants. Multiple types of genetic variants should be considered as contributing factors in patients with extreme dyslipidemia. Copyright © 2017 by the American Society for Biochemistry and Molecular Biology, Inc.

Polygenic risk for psychiatric disorders correlates with executive function in typical development.

PubMed

Schork, A J; Brown, T T; Hagler, D J; Thompson, W K; Chen, C-H; Dale, A M; Jernigan, T L; Akshoomoff, N

2018-04-16

Executive functions are a diverse and critical suite of cognitive abilities that are often disrupted in individuals with psychiatric disorders. Despite their moderate to high heritability, little is known about the molecular genetic factors that contribute to variability in executive functions and how these factors may be related to those that predispose to psychiatric disorders. We examined the relationship between polygenic risk scores built from large genome-wide association studies of psychiatric disorders and executive functioning in typically developing children. In our discovery sample (N = 417), consistent with previous reports on general cognitive abilities, polygenic risk for autism spectrum disorder was associated with better performance on the Dimensional Change Card Sort test from the NIH Cognition Toolbox, with the largest effect in the youngest children. Polygenic risk for major depressive disorder was associated with poorer performance on the Flanker test in the same sample. This second association replicated for performance on the Penn Conditional Exclusion Test in an independent cohort (N = 3681). Our results suggest that the molecular genetic factors contributing to variability in executive function during typical development are at least partially overlapping with those associated with psychiatric disorders, although larger studies and further replication are needed. © 2018 John Wiley & Sons Ltd and International Behavioural and Neural Genetics Society.

How could fully scaled carps appear in natural waters in Madagascar?

PubMed

Hubert, Jean-Noël; Allal, François; Hervet, Caroline; Ravakarivelo, Monique; Jeney, Zsigmond; Vergnet, Alain; Guyomard, René; Vandeputte, Marc

2016-08-31

The capacity of organisms to rapidly evolve in response to environmental changes is a key feature of evolution, and studying mutation compensation is a way to evaluate whether alternative routes of evolution are possible or not. Common carps (Cyprinus carpio) carrying a homozygous loss-of-function mutation for the scale cover gene fgfr1a1, causing the 'mirror' reduced scale cover, were introduced in Madagascar a century ago. Here we show that carps in Malagasy natural waters are now predominantly covered with scales, though they still all carry the homozygous mutation. We also reveal that the number of scales in mutated carps is under strong polygenic genetic control, with a heritability of 0.49. As a whole, our results suggest that carps submitted to natural selection could evolve a wild-type-like scale cover in less than 40 generations from standing polygenic genetic variation, confirming similar findings mainly retrieved from model organisms. © 2016 The Author(s).

Genome-Wide Polygenic Scores Predict Reading Performance Throughout the School Years.

PubMed

Selzam, Saskia; Dale, Philip S; Wagner, Richard K; DeFries, John C; Cederlöf, Martin; O'Reilly, Paul F; Krapohl, Eva; Plomin, Robert

2017-07-04

It is now possible to create individual-specific genetic scores, called genome-wide polygenic scores (GPS). We used a GPS for years of education ( EduYears ) to predict reading performance assessed at UK National Curriculum Key Stages 1 (age 7), 2 (age 12) and 3 (age 14) and on reading tests administered at ages 7 and 12 in a UK sample of 5,825 unrelated individuals. EduYears GPS accounts for up to 5% of the variance in reading performance at age 14. GPS predictions remained significant after accounting for general cognitive ability and family socioeconomic status. Reading performance of children in the lowest and highest 12.5% of the EduYears GPS distribution differed by a mean growth in reading ability of approximately two school years. It seems certain that polygenic scores will be used to predict strengths and weaknesses in education.

Genome-Wide Polygenic Scores Predict Reading Performance Throughout the School Years

PubMed Central

Selzam, Saskia; Dale, Philip S.; Wagner, Richard K.; DeFries, John C.; Cederlöf, Martin; O’Reilly, Paul F.; Krapohl, Eva; Plomin, Robert

2017-01-01

ABSTRACT It is now possible to create individual-specific genetic scores, called genome-wide polygenic scores (GPS). We used a GPS for years of education (EduYears) to predict reading performance assessed at UK National Curriculum Key Stages 1 (age 7), 2 (age 12) and 3 (age 14) and on reading tests administered at ages 7 and 12 in a UK sample of 5,825 unrelated individuals. EduYears GPS accounts for up to 5% of the variance in reading performance at age 14. GPS predictions remained significant after accounting for general cognitive ability and family socioeconomic status. Reading performance of children in the lowest and highest 12.5% of the EduYears GPS distribution differed by a mean growth in reading ability of approximately two school years. It seems certain that polygenic scores will be used to predict strengths and weaknesses in education. PMID:28706435

Polygenic Scores for Major Depressive Disorder and Risk of Alcohol Dependence.

PubMed

Andersen, Allan M; Pietrzak, Robert H; Kranzler, Henry R; Ma, Li; Zhou, Hang; Liu, Xiaoming; Kramer, John; Kuperman, Samuel; Edenberg, Howard J; Nurnberger, John I; Rice, John P; Tischfield, Jay A; Goate, Alison; Foroud, Tatiana M; Meyers, Jacquelyn L; Porjesz, Bernice; Dick, Danielle M; Hesselbrock, Victor; Boerwinkle, Eric; Southwick, Steven M; Krystal, John H; Weissman, Myrna M; Levinson, Douglas F; Potash, James B; Gelernter, Joel; Han, Shizhong

2017-11-01

Major depressive disorder (MDD) and alcohol dependence (AD) are heritable disorders with significant public health burdens, and they are frequently comorbid. Common genetic factors that influence the co-occurrence of MDD and AD have been sought in family, twin, and adoption studies, and results to date have been promising but inconclusive. To examine whether AD and MDD overlap genetically, using a polygenic score approach. Association analyses were conducted between MDD polygenic risk score (PRS) and AD case-control status in European ancestry samples from 4 independent genome-wide association study (GWAS) data sets: the Collaborative Study on the Genetics of Alcoholism (COGA); the Study of Addiction, Genetics, and Environment (SAGE); the Yale-Penn genetic study of substance dependence; and the National Health and Resilience in Veterans Study (NHRVS). Results from a meta-analysis of MDD (9240 patients with MDD and 9519 controls) from the Psychiatric Genomics Consortium were applied to calculate PRS at thresholds from P < .05 to P ≤ .99 in each AD GWAS data set. Association between MDD PRS and AD. Participants analyzed included 788 cases (548 [69.5%] men; mean [SD] age, 38.2 [10.8] years) and 522 controls (151 [28.9.%] men; age [SD], 43.9 [11.6] years) from COGA; 631 cases (333 [52.8%] men; age [SD], 35.0 [7.7] years) and 756 controls (260 [34.4%] male; age [SD] 36.1 [7.7] years) from SAGE; 2135 cases (1375 [64.4%] men; age [SD], 39.4 [11.5] years) and 350 controls (126 [36.0%] men; age [SD], 43.5 [13.9] years) from Yale-Penn; and 317 cases (295 [93.1%] men; age [SD], 59.1 [13.1] years) and 1719 controls (1545 [89.9%] men; age [SD], 64.5 [13.3] years) from NHRVS. Higher MDD PRS was associated with a significantly increased risk of AD in all samples (COGA: best P = 1.7 × 10-6, R2 = 0.026; SAGE: best P = .001, R2 = 0.01; Yale-Penn: best P = .035, R2 = 0.0018; and NHRVS: best P = .004, R2 = 0.0074), with stronger evidence for association after meta-analysis of the 4 samples (best P = 3.3 × 10-9). In analyses adjusted for MDD status in 3 AD GWAS data sets, similar patterns of association were observed (COGA: best P = 7.6 × 10-6, R2 = 0.023; Yale-Penn: best P = .08, R2 = 0.0013; and NHRVS: best P = .006, R2 = 0.0072). After recalculating MDD PRS using MDD GWAS data sets without comorbid MDD-AD cases, significant evidence was observed for an association between the MDD PRS and AD in the meta-analysis of 3 GWAS AD samples without MDD cases (best P = .007). These results suggest that shared genetic susceptibility contributes modestly to MDD and AD comorbidity. Individuals with elevated polygenic risk for MDD may also be at risk for AD.

Prevalence and Penetrance of Major Genes and Polygenes for Colorectal Cancer

PubMed Central

Win, Aung Ko; Jenkins, Mark A.; Dowty, James G.; Antoniou, Antonis C.; Lee, Andrew; Giles, Graham G.; Buchanan, Daniel D.; Clendenning, Mark; Rosty, Christophe; Ahnen, Dennis J.; Thibodeau, Stephen N.; Casey, Graham; Gallinger, Steven; Le Marchand, Loïc; Haile, Robert W.; Potter, John D.; Zheng, Yingye; Lindor, Noralane M.; Newcomb, Polly A.; Hopper, John L.; MacInnis, Robert J.

2016-01-01

Background While high-risk mutations in identified major susceptibility genes (DNA mismatch repair genes and MUTYH) account for some familial aggregation of colorectal cancer, their population prevalence and the causes of the remaining familial aggregation are not known. Methods We studied the families of 5,744 colorectal cancer cases (probands) recruited from population cancer registries in the USA, Canada and Australia and screened probands for mutations in mismatch repair genes and MUTYH. We conducted modified segregation analyses using the cancer history of first-degree relatives, conditional on the proband’s age at diagnosis. We estimated the prevalence of mutations in the identified genes, the prevalence of and hazard ratio for unidentified major gene mutations, and the variance of the residual polygenic component. Results We estimated that 1 in 279 of the population carry mutations in mismatch repair genes (MLH1= 1 in 1946, MSH2= 1 in 2841, MSH6= 1 in 758, PMS2= 1 in 714), 1 in 45 carry mutations in MUTYH, and 1 in 504 carry mutations associated with an average 31-fold increased risk of colorectal cancer in unidentified major genes. The estimated polygenic variance was reduced by 30–50% after allowing for unidentified major genes and decreased from 3.3 for age <40 years to 0.5 for age ≥70 years (equivalent to sibling relative risks of 5.1 to 1.3, respectively). Conclusion Unidentified major genes might explain one-third to one-half of the missing heritability of colorectal cancer. Impact Our findings could aid gene discovery and development of better colorectal cancer risk prediction models. PMID:27799157

THE INVOLVEMENT OF HUMAN MONOGENIC CARDIOMYOPATHY GENES IN EXPERIMENTAL POLYGENIC CARDIAC HYPERTROPHY.

PubMed

Prestes, Priscilla R; Marques, Francine Z; Lopez-Campos, Guillermo; Lewandowski, Paul; Delbridge, Lea M D; Charchar, Fadi J; Harrap, Stephen B

2018-05-18

Hypertrophic cardiomyopathy thickens heart muscles reducing functionality and increasing risk of cardiac disease and morbidity. Genetic factors are involved, but their contribution is poorly understood. We used the hypertrophic heart rat (HHR), a unique normotensive polygenic model of cardiac hypertrophy and heart failure to investigate the role of genes associated with monogenic human cardiomyopathy. We selected 42 genes involved in monogenic human cardiomyopathies to study: 1) DNA variants, by sequencing the whole-genome of 13-week old HHR and age-matched normal heart rat (NHR), its genetic control strain; 2) mRNA expression, by targeted RNA-sequencing in left ventricles of HHR and NHR at five ages (2-days old, 4-, 13-, 33- and 50-weeks old) compared to human idiopathic dilated data; and 3) microRNA expression, with rat microRNA microarrays in left ventricles of 2-days old HHR and age-matched NHR. We also investigated experimentally validated microRNA-mRNA interactions. Whole-genome sequencing revealed unique variants mostly located in non-coding regions of HHR and NHR. We found 29 genes differentially expressed in at least one age. Genes encoding desmoglein 2 (Dsg2) and transthyretin (Ttr) were significantly differentially expressed at all ages in the HHR, but only Ttr was also differentially expressed in human idiopathic cardiomyopathy. Lastly, only two microRNAs differentially expressed in the HHR were present in our comparison of validated microRNA-mRNA interactions. These two microRNAs interact with five of the genes studied. Our study shows that genes involved in monogenic forms of human cardiomyopathies may also influence polygenic forms of the disease.

Polygenic dissection of diagnosis and clinical dimensions of bipolar disorder and schizophrenia.

PubMed

Ruderfer, Douglas M; Fanous, Ayman H; Ripke, Stephan; McQuillin, Andrew; Amdur, Richard L; Gejman, Pablo V; O'Donovan, Michael C; Andreassen, Ole A; Djurovic, Srdjan; Hultman, Christina M; Kelsoe, John R; Jamain, Stephane; Landén, Mikael; Leboyer, Marion; Nimgaonkar, Vishwajit; Nurnberger, John; Smoller, Jordan W; Craddock, Nick; Corvin, Aiden; Sullivan, Patrick F; Holmans, Peter; Sklar, Pamela; Kendler, Kenneth S

2014-09-01

Bipolar disorder and schizophrenia are two often severe disorders with high heritabilities. Recent studies have demonstrated a large overlap of genetic risk loci between these disorders but diagnostic and molecular distinctions still remain. Here, we perform a combined genome-wide association study (GWAS) of 19 779 bipolar disorder (BP) and schizophrenia (SCZ) cases versus 19 423 controls, in addition to a direct comparison GWAS of 7129 SCZ cases versus 9252 BP cases. In our case-control analysis, we identify five previously identified regions reaching genome-wide significance (CACNA1C, IFI44L, MHC, TRANK1 and MAD1L1) and a novel locus near PIK3C2A. We create a polygenic risk score that is significantly different between BP and SCZ and show a significant correlation between a BP polygenic risk score and the clinical dimension of mania in SCZ patients. Our results indicate that first, combining diseases with similar genetic risk profiles improves power to detect shared risk loci and second, that future direct comparisons of BP and SCZ are likely to identify loci with significant differential effects. Identifying these loci should aid in the fundamental understanding of how these diseases differ biologically. These findings also indicate that combining clinical symptom dimensions and polygenic signatures could provide additional information that may someday be used clinically.

Inference of the genetic architecture underlying BMI and height with the use of 20,240 sibling pairs.

PubMed

Hemani, Gibran; Yang, Jian; Vinkhuyzen, Anna; Powell, Joseph E; Willemsen, Gonneke; Hottenga, Jouke-Jan; Abdellaoui, Abdel; Mangino, Massimo; Valdes, Ana M; Medland, Sarah E; Madden, Pamela A; Heath, Andrew C; Henders, Anjali K; Nyholt, Dale R; de Geus, Eco J C; Magnusson, Patrik K E; Ingelsson, Erik; Montgomery, Grant W; Spector, Timothy D; Boomsma, Dorret I; Pedersen, Nancy L; Martin, Nicholas G; Visscher, Peter M

2013-11-07

Evidence that complex traits are highly polygenic has been presented by population-based genome-wide association studies (GWASs) through the identification of many significant variants, as well as by family-based de novo sequencing studies indicating that several traits have a large mutational target size. Here, using a third study design, we show results consistent with extreme polygenicity for body mass index (BMI) and height. On a sample of 20,240 siblings (from 9,570 nuclear families), we used a within-family method to obtain narrow-sense heritability estimates of 0.42 (SE = 0.17, p = 0.01) and 0.69 (SE = 0.14, p = 6 × 10(-)(7)) for BMI and height, respectively, after adjusting for covariates. The genomic inflation factors from locus-specific linkage analysis were 1.69 (SE = 0.21, p = 0.04) for BMI and 2.18 (SE = 0.21, p = 2 × 10(-10)) for height. This inflation is free of confounding and congruent with polygenicity, consistent with observations of ever-increasing genomic-inflation factors from GWASs with large sample sizes, implying that those signals are due to true genetic signals across the genome rather than population stratification. We also demonstrate that the distribution of the observed test statistics is consistent with both rare and common variants underlying a polygenic architecture and that previous reports of linkage signals in complex traits are probably a consequence of polygenic architecture rather than the segregation of variants with large effects. The convergent empirical evidence from GWASs, de novo studies, and within-family segregation implies that family-based sequencing studies for complex traits require very large sample sizes because the effects of causal variants are small on average. Copyright © 2013 The American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.

Polygenic obesity in humans.

PubMed

Hinney, Anke; Hebebrand, Johannes

2008-01-01

The molecular genetic analysis of obesity has led to the identification of a limited number of confirmed major genes. While such major genes have a clear influence on the development of the phenotype, the underlying mutations are however (extremely) infrequent and thus of minor clinical importance only. The genetic predisposition to obesity must thus be polygenic; a number of such variants should be found in most obese subjects; however, these variants predisposing to obesity are also found in normal weight and even lean individuals. Therefore, a polygene can only be identified and validated by statistical analyses: the appropriate gene variant (allele) occurs more frequently in obese than in non-obese subjects. Each single polygene makes only a small contribution to the development of obesity. The 103Ile allele of the Val103Ile single nucleotide polymorphism (SNP) of the melanocortin-4 receptor gene (MC4R) was the first confirmed polygenetic variant with an influence on the body mass index (BMI); the more common Val103 allele is more frequent in obese individuals. As determined in a recent, large-scaled meta-analysis the effect size of this allele on mean BMI was approximately -0.5 kg/m(2). The first genome-wide association study (GWA) for obesity, based on approximately 100,000 SNPs analyzed in families of the Framingham study, revealed that a SNP in the proximity of the insulin-induced gene 2 (INSIG2) was associated with obesity. The positive result was replicated in independent samples; however, some other study groups detected no association. Currently, a meta-analysis is ongoing; its result will contribute to the evaluation of the importance of the INSIG2 polymorphism in body weight regulation. SNP alleles in intron 1 of the fat mass and obesity associated gene (FTO) confer the most relevant polygenic effect on obesity. In the first GWA for extreme early onset obesity we substantiated that variation in FTO strongly contributes to early onset obesity. Copyright 2008 S. Karger AG, Basel.

Breast cancer risk prediction using a clinical risk model and polygenic risk score.

PubMed

Shieh, Yiwey; Hu, Donglei; Ma, Lin; Huntsman, Scott; Gard, Charlotte C; Leung, Jessica W T; Tice, Jeffrey A; Vachon, Celine M; Cummings, Steven R; Kerlikowske, Karla; Ziv, Elad

2016-10-01

Breast cancer risk assessment can inform the use of screening and prevention modalities. We investigated the performance of the Breast Cancer Surveillance Consortium (BCSC) risk model in combination with a polygenic risk score (PRS) comprised of 83 single nucleotide polymorphisms identified from genome-wide association studies. We conducted a nested case-control study of 486 cases and 495 matched controls within a screening cohort. The PRS was calculated using a Bayesian approach. The contributions of the PRS and variables in the BCSC model to breast cancer risk were tested using conditional logistic regression. Discriminatory accuracy of the models was compared using the area under the receiver operating characteristic curve (AUROC). Increasing quartiles of the PRS were positively associated with breast cancer risk, with OR 2.54 (95 % CI 1.69-3.82) for breast cancer in the highest versus lowest quartile. In a multivariable model, the PRS, family history, and breast density remained strong risk factors. The AUROC of the PRS was 0.60 (95 % CI 0.57-0.64), and an Asian-specific PRS had AUROC 0.64 (95 % CI 0.53-0.74). A combined model including the BCSC risk factors and PRS had better discrimination than the BCSC model (AUROC 0.65 versus 0.62, p = 0.01). The BCSC-PRS model classified 18 % of cases as high-risk (5-year risk ≥3 %), compared with 7 % using the BCSC model. The PRS improved discrimination of the BCSC risk model and classified more cases as high-risk. Further consideration of the PRS's role in decision-making around screening and prevention strategies is merited.

Breast Cancer Risk Prediction Using a Clinical Risk Model and Polygenic Risk Score

PubMed Central

Shieh, Yiwey; Hu, Donglei; Ma, Lin; Huntsman, Scott; Gard, Charlotte C.; Leung, Jessica W.T.; Tice, Jeffrey A.; Vachon, Celine M.; Cummings, Steven R.; Kerlikowske, Karla; Ziv, Elad

2016-01-01

Purpose Breast cancer risk assessment can inform the use of screening and prevention modalities. We investigated the performance of the Breast Cancer Surveillance Consortium (BCSC) risk model in combination with a polygenic risk score (PRS) comprised of 83 single nucleotide polymorphisms identified from genome wide association studies. Methods We conducted a nested case-control study of 486 cases and 495 matched controls within a screening cohort. The PRS was calculated using a Bayesian approach. The contributions of the PRS and variables in the BCSC model to breast cancer risk were tested using conditional logistic regression. Discriminatory accuracy of the models was compared using the area under the receiver operating characteristic curve (AUROC). Results Increasing quartiles of the PRS were positively associated with breast cancer risk, with OR 2.54 (95% CI 1.69-3.82) for breast cancer in the highest versus lowest quartile. In a multivariable model, the PRS, family history, and breast density remained strong risk factors. The AUROC of the PRS was 0.60 (95% CI 0.57-0.64), and an Asian-specific PRS had AUROC 0.64 (95% CI 0.53-0.74). A combined model including the BCSC risk factors and PRS had better discrimination than the BCSC model (AUROC 0.65 versus 0.62, p = 0.01). The BCSC-PRS model classified 18% of cases as high-risk (5-year risk ≥ 3%), compared with 7% using the BCSC model. Conclusion The PRS improved discrimination of the BCSC risk model and classified more cases as high-risk. Impact Further consideration of the PRS's role in decision-making around screening and prevention strategies is merited. PMID:27565998

The M16 mouse: an outbred animal model of early onset polygenic obesity and diabesity.

PubMed

Allan, Mark F; Eisen, Eugene J; Pomp, Daniel

2004-09-01

To characterize the phenotypic consequences of long-term selective breeding for rapid weight gain, with an emphasis on obesity and obesity-induced diabetes (diabesity). M16 is the result of long-term selection for 3- to 6-week weight gain from an ICR base population. Experiment 1 characterized males from both lines for body weights (3, 6, and 8 weeks), feed (4 to 8 weeks) and H(2)O (6 to 8 weeks) consumption, and heat loss, body composition, and levels of several plasma proteins at 8 weeks of age. Experiment 2 characterized differences between lines for both sexes at three ages (6, 8, and 16 weeks) and fed two diets (high and normal fat). Body weight, composition, blood glucose, and plasma insulin and leptin levels were evaluated after an 8-hour fast. At all ages measured, M16 mice were heavier, fatter, hyperphagic, hyperinsulinemic, and hyperleptinemic relative to ICR. M16 males and females were hyperglycemic relative to ICR, with 56% and 22% higher fasted blood glucose levels at 8 weeks of age. M16 mice represent an outbred animal model to facilitate gene discovery and pathway regulation controlling early onset polygenic obesity and type 2 diabetic phenotypes. Phenotypes prevalent in the M16 model, with obesity and diabesity exhibited at a young age, closely mirror current trends in human populations.

[Genetic testing in polygenic diseases : Atrial fibrillation, arterial hypertension and coronary artery disease].

PubMed

Trenkwalder, T; Kessler, T; Schunkert, H

2017-08-01

Genetic testing plays an increasing role in cardiovascular medicine. Advances in technology and the development of novel and more affordable (high throughput) methods have led to the identification of genetic risk factors in research and clinical practice. Also, this progress has simplified the screening of patients and individuals at risk. In case of rare monogenic diseases, diagnostics, risk stratification, and, in some cases, treatment decisions have become easier. For common, polygenic cardiovascular diseases, the situation is more complex due to interaction of modifiable external risk factors and nonmodifiable factors like genetic predisposition. Over the last few years, it has been shown that multiple genes are involved in the pathophysiology of these cardiovascular diseases rather than one single gene. In the following article, we give an overview of the genetic risk factors in polygenic cardiovascular diseases as atrial fibrillation, arterial hypertension and coronary artery disease. Furthermore, we aim to illustrate in which cases genetic testing is recommended in these diseases.

Genetic variants linked to education predict longevity

PubMed Central

Marioni, Riccardo E.; Ritchie, Stuart J.; Joshi, Peter K.; Hagenaars, Saskia P.; Fischer, Krista; Adams, Mark J.; Hill, W. David; Davies, Gail; Nagy, Reka; Amador, Carmen; Läll, Kristi; Metspalu, Andres; Liewald, David C.; Wilson, James F.; Hayward, Caroline; Esko, Tõnu; Porteous, David J.; Gale, Catharine R.; Deary, Ian J.

2016-01-01

Educational attainment is associated with many health outcomes, including longevity. It is also known to be substantially heritable. Here, we used data from three large genetic epidemiology cohort studies (Generation Scotland, n = ∼17,000; UK Biobank, n = ∼115,000; and the Estonian Biobank, n = ∼6,000) to test whether education-linked genetic variants can predict lifespan length. We did so by using cohort members’ polygenic profile score for education to predict their parents’ longevity. Across the three cohorts, meta-analysis showed that a 1 SD higher polygenic education score was associated with ∼2.7% lower mortality risk for both mothers (total ndeaths = 79,702) and ∼2.4% lower risk for fathers (total ndeaths = 97,630). On average, the parents of offspring in the upper third of the polygenic score distribution lived 0.55 y longer compared with those of offspring in the lower third. Overall, these results indicate that the genetic contributions to educational attainment are useful in the prediction of human longevity. PMID:27799538

Genetic variants linked to education predict longevity.

PubMed

Marioni, Riccardo E; Ritchie, Stuart J; Joshi, Peter K; Hagenaars, Saskia P; Okbay, Aysu; Fischer, Krista; Adams, Mark J; Hill, W David; Davies, Gail; Nagy, Reka; Amador, Carmen; Läll, Kristi; Metspalu, Andres; Liewald, David C; Campbell, Archie; Wilson, James F; Hayward, Caroline; Esko, Tõnu; Porteous, David J; Gale, Catharine R; Deary, Ian J

2016-11-22

Educational attainment is associated with many health outcomes, including longevity. It is also known to be substantially heritable. Here, we used data from three large genetic epidemiology cohort studies (Generation Scotland, n = ∼17,000; UK Biobank, n = ∼115,000; and the Estonian Biobank, n = ∼6,000) to test whether education-linked genetic variants can predict lifespan length. We did so by using cohort members' polygenic profile score for education to predict their parents' longevity. Across the three cohorts, meta-analysis showed that a 1 SD higher polygenic education score was associated with ∼2.7% lower mortality risk for both mothers (total n deaths = 79,702) and ∼2.4% lower risk for fathers (total n deaths = 97,630). On average, the parents of offspring in the upper third of the polygenic score distribution lived 0.55 y longer compared with those of offspring in the lower third. Overall, these results indicate that the genetic contributions to educational attainment are useful in the prediction of human longevity.

Polygenic formation model of the planet's bituminous belts

NASA Astrophysics Data System (ADS)

Dmitrievsky, A. N.; Balanyuk, I. E.

2011-05-01

In recent years, much attention has been paid to nontraditional hydrocarbon sources. Today the portion of nontraditional gas in the world extraction is 15% or 450 billion cubic meters, which hat makes up the volume of total gas exports from Russia. As is known, the easy-prospecting oil has been already found. The innovative technologies in geophysics, drilling, and excavation and the increased extraction coefficient expect further development and industrial compliance with these requirements. Based on calculations, the world oil reserves are now one trillion of stock tank barrels and one trillion barrels have been already extracted. The evergrowing demand for energy gives rise to the necessity of searching for and extracting more oil resources, and both these aspects are unique problems. The search for profitable petroleum deposits has become more and more difficult even in the leading companies. The increment of the world resources is a key vital question; therefore, the elaboration of criteria for the discovery of nontraditional deposits take on special significance in the economic respect. The authors are working out a conception that will be a guideline for future finding of the richest oil deposits in active geodynamic zones. For the first time, we suggest the polygenic formation model of the planet's bituminous belts.

Genome editing as a tool to achieve the crop ideotype and de novo domestication of wild relatives: Case study in tomato.

PubMed

Zsögön, Agustin; Cermak, Tomas; Voytas, Dan; Peres, Lázaro Eustáquio Pereira

2017-03-01

The ideotype is a theoretical model of an archetypal cultivated plant. Recent progress in genome editing is aiding the pursuit of this ideal in crop breeding. Breeding is relatively straightforward when the traits in question are monogenic in nature and show Mendelian inheritance. Conversely, traits with a diffuse, polygenic basis such as abiotic stress resistance are more difficult to harness. In recent years, many genes have been identified that are important for plant domestication and act by increasing yield, grain or fruit size or altering plant architecture. Here, we propose that (a) key monogenic traits whose physiology has been unveiled can be molecularly tailored to achieve the ideotype; and (b) wild relatives of crops harboring polygenic stress resistance genes or other traits of interest could be de novo domesticated by manipulating monogenic yield-related traits through state-of-the-art gene editing techniques. An overview of the genomic and physiological challenges in the world's main staple crops is provided. We focus on tomato and its wild Solanum (section Lycopersicon) relatives as a suitable model for molecular design in the pursuit of the ideotype for elite cultivars and to test de novo domestication of wild relatives. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Breast Cancer Screening in the Precision Medicine Era: Risk-Based Screening in a Population-Based Trial.

PubMed

Shieh, Yiwey; Eklund, Martin; Madlensky, Lisa; Sawyer, Sarah D; Thompson, Carlie K; Stover Fiscalini, Allison; Ziv, Elad; Van't Veer, Laura J; Esserman, Laura J; Tice, Jeffrey A

2017-01-01

Ongoing controversy over the optimal approach to breast cancer screening has led to discordant professional society recommendations, particularly in women age 40 to 49 years. One potential solution is risk-based screening, where decisions around the starting age, stopping age, frequency, and modality of screening are based on individual risk to maximize the early detection of aggressive cancers and minimize the harms of screening through optimal resource utilization. We present a novel approach to risk-based screening that integrates clinical risk factors, breast density, a polygenic risk score representing the cumulative effects of genetic variants, and sequencing for moderate- and high-penetrance germline mutations. We demonstrate how thresholds of absolute risk estimates generated by our prediction tools can be used to stratify women into different screening strategies (biennial mammography, annual mammography, annual mammography with adjunctive magnetic resonance imaging, defer screening at this time) while informing the starting age of screening for women age 40 to 49 years. Our risk thresholds and corresponding screening strategies are based on current evidence but need to be tested in clinical trials. The Women Informed to Screen Depending On Measures of risk (WISDOM) Study, a pragmatic, preference-tolerant randomized controlled trial of annual vs personalized screening, will study our proposed approach. WISDOM will evaluate the efficacy, safety, and acceptability of risk-based screening beginning in the fall of 2016. The adaptive design of this trial allows continued refinement of our risk thresholds as the trial progresses, and we discuss areas where we anticipate emerging evidence will impact our approach. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Genetic predictors of antipsychotic response to lurasidone identified in a genome wide association study and by schizophrenia risk genes.

PubMed

Li, Jiang; Yoshikawa, Akane; Brennan, Mark D; Ramsey, Timothy L; Meltzer, Herbert Y

2018-02-01

Biomarkers which predict response to atypical antipsychotic drugs (AAPDs) increases their benefit/risk ratio. We sought to identify common variants in genes which predict response to lurasidone, an AAPD, by associating genome-wide association study (GWAS) data and changes (Δ) in Positive And Negative Syndrome Scale (PANSS) scores from two 6-week randomized, placebo-controlled trials of lurasidone in schizophrenia (SCZ) patients. We also included SCZ risk SNPs identified by the Psychiatric Genomics Consortium using a polygenic risk analysis. The top genomic loci, with uncorrected p<10 -4 , include: 1) synaptic adhesion (PTPRD, LRRC4C, NRXN1, ILIRAPL1, SLITRK1) and scaffolding (MAGI1, MAGI2, NBEA) genes, both essential for synaptic function; 2) other synaptic plasticity-related genes (NRG1/3 and KALRN); 3) the neuron-specific RNA splicing regulator, RBFOX1; and 4) ion channel genes, e.g. KCNA10, KCNAB1, KCNK9 and CACNA2D3). Some genes predicted response for patients with both European and African Ancestries. We replicated some SNPs reported to predict response to other atypical APDs in other GWAS. Although none of the biomarkers reached genome-wide significance, many of the genes and associated pathways have previously been linked to SCZ. Two polygenic modeling approaches, GCTA-GREML and PLINK-Polygenic Risk Score, demonstrated that some risk genes related to neurodevelopment, synaptic biology, immune response, and histones, also contributed to prediction of response. The top hits predicting response to lurasidone did not predict improvement with placebo. This is the first evidence from clinical trials that SCZ risk SNPs are related to clinical response to an AAPD. These results need to be replicated in an independent sample. Copyright © 2017. Published by Elsevier B.V.

Associations between Polygenic Risk for Psychiatric Disorders and Substance Involvement.

PubMed

Carey, Caitlin E; Agrawal, Arpana; Bucholz, Kathleen K; Hartz, Sarah M; Lynskey, Michael T; Nelson, Elliot C; Bierut, Laura J; Bogdan, Ryan

2016-01-01

Despite evidence of substantial comorbidity between psychiatric disorders and substance involvement, the extent to which common genetic factors contribute to their co-occurrence remains understudied. In the current study, we tested for associations between polygenic risk for psychiatric disorders and substance involvement (i.e., ranging from ever-use to severe dependence) among 2573 non-Hispanic European-American participants from the Study of Addiction: Genetics and Environment. Polygenic risk scores (PRS) for cross-disorder psychopathology (CROSS) were generated based on the Psychiatric Genomics Consortium's Cross-Disorder meta-analysis and then tested for associations with a factor representing general liability to alcohol, cannabis, cocaine, nicotine, and opioid involvement (GENSUB). Follow-up analyses evaluated specific associations between each of the five psychiatric disorders which comprised CROSS-attention deficit hyperactivity disorder (ADHD), autism spectrum disorder (AUT), bipolar disorder (BIP), major depressive disorder (MDD), and schizophrenia (SCZ)-and involvement with each component substance included in GENSUB. CROSS PRS explained 1.10% of variance in GENSUB in our sample (p < 0.001). After correction for multiple testing in our follow-up analyses of polygenic risk for each individual disorder predicting involvement with each component substance, associations remained between: (A) MDD PRS and non-problem cannabis use, (B) MDD PRS and severe cocaine dependence, (C) SCZ PRS and non-problem cannabis use and severe cannabis dependence, and (D) SCZ PRS and severe cocaine dependence. These results suggest that shared covariance from common genetic variation contributes to psychiatric and substance involvement comorbidity.

Sequencing chromosomal abnormalities reveals neurodevelopmental loci that confer risk across diagnostic boundaries

PubMed Central

Talkowski, Michael E.; Rosenfeld, Jill A.; Blumenthal, Ian; Pillalamarri, Vamsee; Chiang, Colby; Heilbut, Adrian; Ernst, Carl; Hanscom, Carrie; Rossin, Elizabeth; Lindgren, Amelia; Pereira, Shahrin; Ruderfer, Douglas; Kirby, Andrew; Ripke, Stephan; Harris, David; Lee, Ji-Hyun; Ha, Kyungsoo; Kim, Hyung-Goo; Solomon, Benjamin D.; Gropman, Andrea L.; Lucente, Diane; Sims, Katherine; Ohsumi, Toshiro K.; Borowsky, Mark L.; Loranger, Stephanie; Quade, Bradley; Lage, Kasper; Miles, Judith; Wu, Bai-Lin; Shen, Yiping; Neale, Benjamin; Shaffer, Lisa G.; Daly, Mark J.; Morton, Cynthia C.; Gusella, James F.

2012-01-01

SUMMARY Balanced chromosomal abnormalities (BCAs) represent a reservoir of single gene disruptions in neurodevelopmental disorders (NDD). We sequenced BCAs in autism and related NDDs, revealing disruption of 33 loci in four general categories: 1) genes associated with abnormal neurodevelopment (e.g., AUTS2, FOXP1, CDKL5), 2) single gene contributors to microdeletion syndromes (MBD5, SATB2, EHMT1, SNURF-SNRPN), 3) novel risk loci (e.g., CHD8, KIRREL3, ZNF507), and 4) genes associated with later onset psychiatric disorders (e.g., TCF4, ZNF804A, PDE10A, GRIN2B, ANK3). We also discovered profoundly increased burden of copy number variants among 19,556 neurodevelopmental cases compared to 13,991 controls (p = 2.07×10−47) and enrichment of polygenic risk alleles from autism and schizophrenia genome-wide association studies (p = 0.0018 and 0.0009, respectively). Our findings suggest a polygenic risk model of autism incorporating loci of strong effect and indicate that some neurodevelopmental genes are sensitive to perturbation by multiple mutational mechanisms, leading to variable phenotypic outcomes that manifest at different life stages. PMID:22521361

SRC-2 orchestrates polygenic inputs for fine-tuning glucose homeostasis

PubMed Central

Fleet, Tiffany; Zhang, Bin; Lin, Fumin; Zhu, Bokai; Dasgupta, Subhamoy; Stashi, Erin; Tackett, Bryan; Thevananther, Sundararajah; Rajapakshe, Kimal I.; Gonzales, Naomi; Dean, Adam; Mao, Jianqiang; Timchenko, Nikolai; Malovannaya, Anna; Qin, Jun; Coarfa, Cristian; DeMayo, Francesco; Dacso, Clifford C.; Foulds, Charles E.; O’Malley, Bert W.; York, Brian

2015-01-01

Despite extensive efforts to understand the monogenic contributions to perturbed glucose homeostasis, the complexity of genetic events that fractionally contribute to the spectrum of this pathology remain poorly understood. Proper maintenance of glucose homeostasis is the central feature of a constellation of comorbidities that define the metabolic syndrome. The ability of the liver to balance carbohydrate uptake and release during the feeding-to-fasting transition is essential to the regulation of peripheral glucose availability. The liver coordinates the expression of gene programs that control glucose absorption, storage, and secretion. Herein, we demonstrate that Steroid Receptor Coactivator 2 (SRC-2) orchestrates a hierarchy of nutritionally responsive transcriptional complexes to precisely modulate plasma glucose availability. Using DNA pull-down technology coupled with mass spectrometry, we have identified SRC-2 as an indispensable integrator of transcriptional complexes that control the rate-limiting steps of hepatic glucose release and accretion. Collectively, these findings position SRC-2 as a major regulator of polygenic inputs to metabolic gene regulation and perhaps identify a previously unappreciated model that helps to explain the clinical spectrum of glucose dysregulation. PMID:26487680

Genetic and Environmental Factors Associated with Cannabis Involvement

PubMed Central

Bogdan, Ryan; Winstone, Jonathan MA; Agrawal, Arpana

2016-01-01

Approximately 50-70% of the variation in cannabis use and use disorders can be attributed to heritable factors. For cannabis use, the remaining variance can be parsed in to familial and person-specific environmental factors while for use disorders, only the latter contribute. While numerous candidate gene studies have identified the role of common variation influencing liability to cannabis involvement, replication has been elusive. To date, no genomewide association study has been sufficiently powered to identify significant loci. Despite this, studies adopting polygenic techniques and integrating genetic variation with neural phenotypes and measures of environmental risk, such as childhood adversity, are providing promising new leads. It is likely that the small effect sizes associated with variants related to cannabis involvement will only be robustly identified in substantially larger samples. Results of such large-scale efforts will provide valuable single variant targets for translational research in neurogenetic, pharmacogenetic and non-human animal models as well as polygenic risk indices that can be used to explore a host of other genetic hypotheses related to cannabis use and misuse. PMID:27642547

Genetic and Environmental Risk for Chronic Pain and the Contribution of Risk Variants for Major Depressive Disorder: A Family-Based Mixed-Model Analysis

PubMed Central

McIntosh, Andrew M.; Zeng, Yanni; Davies, Gail; Clarke, Toni-Kim; Hayward, Caroline; Haley, Chris S.; Porteous, David J.; Deary, Ian J.; Smith, Daniel J.; Hinds, David A.; Jones, Amy V.; Scollen, Serena; Meng, Weihua; Hocking, Lynne J.

2016-01-01

Background Chronic pain is highly prevalent and a significant source of disability, yet its genetic and environmental risk factors are poorly understood. Its relationship with major depressive disorder (MDD) is of particular importance. We sought to test the contribution of genetic factors and shared and unique environment to risk of chronic pain and its correlation with MDD in Generation Scotland: Scottish Family Health Study (GS:SFHS). We then sought to replicate any significant findings in the United Kingdom Biobank study. Methods and Findings Using family-based mixed-model analyses, we examined the contribution of genetics and shared family environment to chronic pain by spouse, sibling, and household relationships. These analyses were conducted in GS:SFHS (n = 23,960), a family- and population-based study of individuals recruited from the Scottish population through their general practitioners. We then examined and partitioned the correlation between chronic pain and MDD and estimated the contribution of genetic factors and shared environment in GS:SFHS. Finally, we used data from two independent genome-wide association studies to test whether chronic pain has a polygenic architecture and examine whether genomic risk of psychiatric disorder predicted chronic pain and whether genomic risk of chronic pain predicted MDD. These analyses were conducted in GS:SFHS and repeated in UK Biobank, a study of 500,000 from the UK population, of whom 112,151 had genotyping and phenotypic data. Chronic pain is a moderately heritable trait (heritability = 38.4%, 95% CI 33.6% to 43.9%) that is significantly concordant in spouses (variance explained 18.7%, 95% CI 9.5% to 25.1%). Chronic pain is positively correlated with depression (ρ = 0.13, 95% CI 0.11 to 0.15, p = 2.72x10-68) and shows a tendency to cluster within families for genetic reasons (genetic correlation = 0.51, 95%CI 0.40 to 0.62, p = 8.24x10-19). Polygenic risk profiles for pain, generated using independent GWAS data, were associated with chronic pain in both GS:SFHS (maximum β = 6.18x10-2, 95% CI 2.84 x10-2 to 9.35 x10-2, p = 4.3x10-4) and UK Biobank (maximum β = 5.68 x 10−2, 95% CI 4.70x10-2 to 6.65x10-2 , p < 3x10-4). Genomic risk of MDD is also significantly associated with chronic pain in both GS:SFHS (maximum β = 6.62x10-2, 95% CI 2.82 x10-2 to 9.76 x10-2 , p = 4.3x10-4) and UK Biobank (maximum β = 2.56x10-2, 95% CI 1.62x10-2 to 3.63x10-2 , p < 3x10-4). Limitations of the current study include the possibility that spouse effects may be due to assortative mating and the relatively small polygenic risk score effect sizes. Conclusions Genetic factors, as well as chronic pain in a partner or spouse, contribute substantially to the risk of chronic pain for an individual. Chronic pain is genetically correlated with MDD, has a polygenic architecture, and is associated with polygenic risk of MDD. PMID:27529168

Genetic and Environmental Risk for Chronic Pain and the Contribution of Risk Variants for Major Depressive Disorder: A Family-Based Mixed-Model Analysis.

PubMed

McIntosh, Andrew M; Hall, Lynsey S; Zeng, Yanni; Adams, Mark J; Gibson, Jude; Wigmore, Eleanor; Hagenaars, Saskia P; Davies, Gail; Fernandez-Pujals, Ana Maria; Campbell, Archie I; Clarke, Toni-Kim; Hayward, Caroline; Haley, Chris S; Porteous, David J; Deary, Ian J; Smith, Daniel J; Nicholl, Barbara I; Hinds, David A; Jones, Amy V; Scollen, Serena; Meng, Weihua; Smith, Blair H; Hocking, Lynne J

2016-08-01

Chronic pain is highly prevalent and a significant source of disability, yet its genetic and environmental risk factors are poorly understood. Its relationship with major depressive disorder (MDD) is of particular importance. We sought to test the contribution of genetic factors and shared and unique environment to risk of chronic pain and its correlation with MDD in Generation Scotland: Scottish Family Health Study (GS:SFHS). We then sought to replicate any significant findings in the United Kingdom Biobank study. Using family-based mixed-model analyses, we examined the contribution of genetics and shared family environment to chronic pain by spouse, sibling, and household relationships. These analyses were conducted in GS:SFHS (n = 23,960), a family- and population-based study of individuals recruited from the Scottish population through their general practitioners. We then examined and partitioned the correlation between chronic pain and MDD and estimated the contribution of genetic factors and shared environment in GS:SFHS. Finally, we used data from two independent genome-wide association studies to test whether chronic pain has a polygenic architecture and examine whether genomic risk of psychiatric disorder predicted chronic pain and whether genomic risk of chronic pain predicted MDD. These analyses were conducted in GS:SFHS and repeated in UK Biobank, a study of 500,000 from the UK population, of whom 112,151 had genotyping and phenotypic data. Chronic pain is a moderately heritable trait (heritability = 38.4%, 95% CI 33.6% to 43.9%) that is significantly concordant in spouses (variance explained 18.7%, 95% CI 9.5% to 25.1%). Chronic pain is positively correlated with depression (ρ = 0.13, 95% CI 0.11 to 0.15, p = 2.72x10-68) and shows a tendency to cluster within families for genetic reasons (genetic correlation = 0.51, 95%CI 0.40 to 0.62, p = 8.24x10-19). Polygenic risk profiles for pain, generated using independent GWAS data, were associated with chronic pain in both GS:SFHS (maximum β = 6.18x10-2, 95% CI 2.84 x10-2 to 9.35 x10-2, p = 4.3x10-4) and UK Biobank (maximum β = 5.68 x 10-2, 95% CI 4.70x10-2 to 6.65x10-2, p < 3x10-4). Genomic risk of MDD is also significantly associated with chronic pain in both GS:SFHS (maximum β = 6.62x10-2, 95% CI 2.82 x10-2 to 9.76 x10-2, p = 4.3x10-4) and UK Biobank (maximum β = 2.56x10-2, 95% CI 1.62x10-2 to 3.63x10-2, p < 3x10-4). Limitations of the current study include the possibility that spouse effects may be due to assortative mating and the relatively small polygenic risk score effect sizes. Genetic factors, as well as chronic pain in a partner or spouse, contribute substantially to the risk of chronic pain for an individual. Chronic pain is genetically correlated with MDD, has a polygenic architecture, and is associated with polygenic risk of MDD.

Polygenic risk score analysis of pathologically confirmed Alzheimer disease.

PubMed

Escott-Price, Valentina; Myers, Amanda J; Huentelman, Matt; Hardy, John

2017-08-01

Previous estimates of the utility of polygenic risk score analysis for the prediction of Alzheimer disease have given area under the curve (AUC) estimates of <80%. However, these have been based on the genetic analysis of clinical case-control series. Here, we apply the same analytic approaches to a pathological case-control series and show a predictive AUC of 84%. We suggest that this analysis has clinical utility and that there is limited room for further improvement using genetic data. Ann Neurol 2017;82:311-314. © 2017 American Neurological Association.

PLASMA LIPIDOMIC PROFILE SIGNATURE OF HYPERTENSION IN MEXICAN AMERICAN FAMILIES: SPECIFIC ROLE OF DIACYLGLYCEROLS

PubMed Central

Kulkarni, Hemant; Meikle, Peter J.; Mamtani, Manju; Weir, Jacquelyn M.; Barlow, Christopher K.; Jowett, Jeremy B.; Bellis, Claire; Dyer, Thomas D.; Johnson, Matthew P.; Rainwater, David L.; Almasy, Laura; Mahaney, Michael C.; Commuzzie, Anthony G.; Blangero, John; Curran, Joanne E.

2013-01-01

Both as a component of metabolic syndrome and as an independent entity, hypertension poses a continued challenge with regard to its diagnosis, pathogenesis and treatment. Previous studies have documented connections between hypertension and indicators of lipid metabolism. Novel technologies like plasma lipidomic profiling promise a better understanding of disorders in which there is a derangement of the lipid metabolism. However, association of plasma lipidomic profiles with hypertension in a high-risk population, like Mexican Americans, has not been evaluated before. Using the rich data and sample resource from the ongoing San Antonio Family Heart Study, we conducted plasma lipidomic profiling by combining high performance liquid chromatography with tandem mass spectroscopy to characterize 319 lipid species in 1192 individuals from 42 large and extended Mexican American families. Robust statistical analyses employing polygenic regression models, liability threshold models and bivariate trait analyses implemented in the SOLAR software were conducted after accounting for obesity, insulin resistance and relative abundance of various lipoprotein fractions. Diacylglycerols in general and the DG 16:0/22:5 and DG 16:0/22:6 lipid species in particular were significantly associated with systolic, diastolic and mean arterial pressures as well as liability of incident hypertension measured during 7767.42 person-years of follow-up. Four lipid species, including the DG 16:0/22:5 and DG 16:0/22:6 species, showed significant genetic correlations with the liability of hypertension in bivariate trait analyses. Our results demonstrate the value of plasma lipidomic profiling in the context of hypertension and identify disturbance of diacyglycerol metabolism as an independent biomarker of hypertension. PMID:23798346

Genetics of Migraine: Insights into the Molecular Basis of Migraine Disorders.

PubMed

Sutherland, Heidi G; Griffiths, Lyn R

2017-04-01

Migraine is a complex, debilitating neurovascular disorder, typically characterized by recurring, incapacitating attacks of severe headache often accompanied by nausea and neurological disturbances. It has a strong genetic basis demonstrated by rare migraine disorders caused by mutations in single genes (monogenic), as well as familial clustering of common migraine which is associated with polymorphisms in many genes (polygenic). Hemiplegic migraine is a dominantly inherited, severe form of migraine with associated motor weakness. Family studies have found that mutations in three different ion channels genes, CACNA1A, ATP1A2, and SCN1A can be causal. Functional studies of these mutations has shown that they can result in defective regulation of glutamatergic neurotransmission and the excitatory/inhibitory balance in the brain, which lowers the threshold for cortical spreading depression, a wave of cortical depolarization thought to be involved in headache initiation mechanisms. Other putative genes for monogenic migraine include KCKN18, PRRT2, and CSNK1D, which can also be involved with other disorders. There are a number of primarily vascular disorders caused by mutations in single genes, which are often accompanied by migraine symptoms. Mutations in NOTCH3 causes cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL), a hereditary cerebrovascular disease that leads to ischemic strokes and dementia, but in which migraine is often present, sometimes long before the onset of other symptoms. Mutations in the TREX1 and COL4A1 also cause vascular disorders, but often feature migraine. With respect to common polygenic migraine, genome-wide association studies have now identified single nucleotide polymorphisms at 38 loci significantly associated with migraine risk. Functions assigned to the genes in proximity to these loci suggest that both neuronal and vascular pathways also contribute to the pathophysiology of common migraine. Further studies are required to fully understand these findings and translate them into treatment options for migraine patients. © 2017 American Headache Society.

Posttraumatic stress disorder symptom severity is associated with reduced default mode network connectivity in individuals with elevated genetic risk for psychopathology.

PubMed

Miller, Danielle R; Logue, Mark W; Wolf, Erika J; Maniates, Hannah; Robinson, Meghan E; Hayes, Jasmeet P; Stone, Annjanette; Schichman, Steven; McGlinchey, Regina E; Milberg, William P; Miller, Mark W

2017-07-01

Accumulating evidence suggests that posttraumatic stress disorder (PTSD) is associated with disrupted default mode network (DMN) connectivity, but findings across studies have not been uniform. Individual differences in relevant genes may account for some of the reported variability in the relationship between DMN connectivity and PTSD. In this study, we investigated this possibility using genome-wide association study (GWAS) derived polygenic risk scores (PRSs) for relevant psychiatric traits. We hypothesized that the association between PTSD and DMN connectivity would be moderated by genetic risk for one or more psychiatric traits such that individuals with elevated polygenic risk for psychopathology and severe PTSD would exhibit disrupted DMN connectivity. Participants were 156 white, non-Hispanic veterans of the wars in Iraq and Afghanistan who were genotyped and underwent resting state functional magnetic resonance imaging and clinical assessment. PRSs for neuroticism, anxiety, major depressive disorder, and cross-disorder risk (based on five psychiatric disorders) were calculated using summary statistics from published large-scale consortia-based GWASs. Cross-disorder polygenic risk influenced the relationship between DMN connectivity and PTSD symptom severity such that individuals at greater genetic risk showed a significant negative association between PTSD symptom severity and connectivity between the posterior cingulate cortex and right middle temporal gyrus. Polygenic risk for neuroticism, anxiety, and major depressive disorder did not influence DMN connectivity directly or through an interaction with PTSD. Findings illustrate the potential power of genome-wide PRSs to advance understanding of the relationship between PTSD and DMN connectivity, a putative neural endophenotype of the disorder. © 2017 Wiley Periodicals, Inc.

Signatures of polygenic adaptation associated with climate across the range of a threatened fish species with high genetic connectivity.

PubMed

Harrisson, Katherine A; Amish, Stephen J; Pavlova, Alexandra; Narum, Shawn R; Telonis-Scott, Marina; Rourke, Meaghan L; Lyon, Jarod; Tonkin, Zeb; Gilligan, Dean M; Ingram, Brett A; Lintermans, Mark; Gan, Han Ming; Austin, Christopher M; Luikart, Gordon; Sunnucks, Paul

2017-11-01

Adaptive differences across species' ranges can have important implications for population persistence and conservation management decisions. Despite advances in genomic technologies, detecting adaptive variation in natural populations remains challenging. Key challenges in gene-environment association studies involve distinguishing the effects of drift from those of selection and identifying subtle signatures of polygenic adaptation. We used paired-end restriction site-associated DNA sequencing data (6,605 biallelic single nucleotide polymorphisms; SNPs) to examine population structure and test for signatures of adaptation across the geographic range of an iconic Australian endemic freshwater fish species, the Murray cod Maccullochella peelii. Two univariate gene-association methods identified 61 genomic regions associated with climate variation. We also tested for subtle signatures of polygenic adaptation using a multivariate method (redundancy analysis; RDA). The RDA analysis suggested that climate (temperature- and precipitation-related variables) and geography had similar magnitudes of effect in shaping the distribution of SNP genotypes across the sampled range of Murray cod. Although there was poor agreement among the candidate SNPs identified by the univariate methods, the top 5% of SNPs contributing to significant RDA axes included 67% of the SNPs identified by univariate methods. We discuss the potential implications of our findings for the management of Murray cod and other species generally, particularly in relation to informing conservation actions such as translocations to improve evolutionary resilience of natural populations. Our results highlight the value of using a combination of different approaches, including polygenic methods, when testing for signatures of adaptation in landscape genomic studies. © 2017 John Wiley & Sons Ltd.

Association Between Substance Use Disorder and Polygenic Liability to Schizophrenia.

PubMed

Hartz, Sarah M; Horton, Amy C; Oehlert, Mary; Carey, Caitlin E; Agrawal, Arpana; Bogdan, Ryan; Chen, Li-Shiun; Hancock, Dana B; Johnson, Eric O; Pato, Carlos N; Pato, Michele T; Rice, John P; Bierut, Laura J

2017-11-15

There are high levels of comorbidity between schizophrenia and substance use disorder, but little is known about the genetic etiology of this comorbidity. We tested the hypothesis that shared genetic liability contributes to the high rates of comorbidity between schizophrenia and substance use disorder. To do this, polygenic risk scores for schizophrenia derived from a large meta-analysis by the Psychiatric Genomics Consortium were computed in three substance use disorder datasets: the Collaborative Genetic Study of Nicotine Dependence (ascertained for tobacco use disorder; n = 918 cases; 988 control subjects), the Collaborative Study on the Genetics of Alcoholism (ascertained for alcohol use disorder; n = 643 cases; 384 control subjects), and the Family Study of Cocaine Dependence (ascertained for cocaine use disorder; n = 210 cases; 317 control subjects). Phenotypes were harmonized across the three datasets and standardized analyses were performed. Genome-wide genotypes were imputed to the 1000 Genomes reference panel. In each individual dataset and in the mega-analysis, strong associations were observed between any substance use disorder diagnosis and the polygenic risk score for schizophrenia (mega-analysis pseudo-R 2 range 0.8-3.7%; minimum p = 4 × 10 -23 ). These results suggest that comorbidity between schizophrenia and substance use disorder is partially attributable to shared polygenic liability. This shared liability is most consistent with a general risk for substance use disorder rather than specific risks for individual substance use disorders and adds to increasing evidence of a blurred boundary between schizophrenia and substance use disorder. Copyright © 2017 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

Artificial Selection Response due to Polygenic Adaptation from a Multilocus, Multiallelic Genetic Architecture.

PubMed

Zan, Yanjun; Sheng, Zheya; Lillie, Mette; Rönnegård, Lars; Honaker, Christa F; Siegel, Paul B; Carlborg, Örjan

2017-10-01

The ability of a population to adapt to changes in their living conditions, whether in nature or captivity, often depends on polymorphisms in multiple genes across the genome. In-depth studies of such polygenic adaptations are difficult in natural populations, but can be approached using the resources provided by artificial selection experiments. Here, we dissect the genetic mechanisms involved in long-term selection responses of the Virginia chicken lines, populations that after 40 generations of divergent selection for 56-day body weight display a 9-fold difference in the selected trait. In the F15 generation of an intercross between the divergent lines, 20 loci explained >60% of the additive genetic variance for the selected trait. We focused particularly on fine-mapping seven major QTL that replicated in this population and found that only two fine-mapped to single, bi-allelic loci; the other five contained linked loci, multiple alleles or were epistatic. This detailed dissection of the polygenic adaptations in the Virginia lines provides a deeper understanding of the range of different genome-wide mechanisms that have been involved in these long-term selection responses. The results illustrate that the genetic architecture of a highly polygenic trait can involve a broad range of genetic mechanisms, and that this can be the case even in a small population bred from founders with limited genetic diversity. © The Author 2017. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Additive Genetic Risk from Five Serotonin System Polymorphisms Interacts with Interpersonal Stress to Predict Depression

PubMed Central

Vrshek-Schallhorn, Suzanne; Stroud, Catherine B.; Mineka, Susan; Zinbarg, Richard E.; Adam, Emma K.; Redei, Eva E.; Hammen, Constance; Craske, Michelle G.

2016-01-01

Behavioral genetic research supports polygenic models of depression in which many genetic variations each contribute a small amount of risk, and prevailing diathesis-stress models suggest gene-environment interactions (GxE). Multilocus profile scores of additive risk offer an approach that is consistent with polygenic models of depression risk. In a first demonstration of this approach in a GxE predicting depression, we created an additive multilocus profile score from five serotonin system polymorphisms (one each in the genes HTR1A, HTR2A, HTR2C, and two in TPH2). Analyses focused on two forms of interpersonal stress as environmental risk factors. Using five years of longitudinal diagnostic and life stress interviews from 387 emerging young adults in the Youth Emotion Project, survival analyses show that this multilocus profile score interacts with major interpersonal stressful life events to predict major depressive episode onsets (HR = 1.815, p = .007). Simultaneously, there was a significant protective effect of the profile score without a recent event (HR = 0.83, p = .030). The GxE effect with interpersonal chronic stress was not significant (HR = 1.15, p = .165). Finally, effect sizes for genetic factors examined ignoring stress suggested such an approach could lead to overlooking or misinterpreting genetic effects. Both the GxE effect and the protective simple main effect were replicated in a sample of early adolescent girls (N = 105). We discuss potential benefits of the multilocus genetic profile score approach and caveats for future research. PMID:26595467

Effects of Schizophrenia Polygenic Risk Scores on Brain Activity and Performance During Working Memory Subprocesses in Healthy Young Adults.

PubMed

Miller, Jacob A; Scult, Matthew A; Conley, Emily Drabant; Chen, Qiang; Weinberger, Daniel R; Hariri, Ahmad R

2018-06-06

Recent work has begun to shed light on the neural correlates and possible mechanisms of polygenic risk for schizophrenia. Here, we map a schizophrenia polygenic risk profile score (PRS) based on genome-wide association study significant loci onto variability in the activity and functional connectivity of a frontoparietal network supporting the manipulation versus maintenance of information during a numerical working memory (WM) task in healthy young adults (n = 99, mean age = 19.8). Our analyses revealed that higher PRS was associated with hypoactivity of the dorsolateral prefrontal cortex (dlPFC) during the manipulation but not maintenance of information in WM (r2 = .0576, P = .018). Post hoc analyses revealed that PRS-modulated dlPFC hypoactivity correlated with faster reaction times during WM manipulation (r2 = .0967, P = .002), and faster processing speed (r2 = .0967, P = .003) on a separate behavioral task. These PRS-associated patterns recapitulate dlPFC hypoactivity observed in patients with schizophrenia during central executive manipulation of information in WM on this task.

Multilocus genetic profile in dopaminergic pathway modulates the striatum and working memory.

PubMed

Wang, Chao; Liu, Bing; Zhang, Xiaolong; Cui, Yue; Yu, Chunshui; Jiang, Tianzi

2018-03-29

Dopamine is critical in pathophysiology and therapy of schizophrenia. Many studies have reported altered dopaminergic activity in the dorsal but not ventral striatum in schizophrenia. Based on the largest genome-wide association study of schizophrenia to date, we calculated the polygenic risk score (PGRS) of each subject in a healthy general group, including all variations in the set of functionally related genes involved in dopamine neurotransmitter system. We aimed to test whether the genetic variations in the dopaminergic pathway that have been identified as associated with schizophrenia are related to the function of the striatum and to working memory. We found that a higher PGRS was significantly associated with impairment in working memory. Moreover, resting-state functional connectivity analysis revealed that as the polygenic risk score increased, the connections between left putamen and caudate and the default mode network grew stronger, while the connections with the fronto-parietal network grew weaker. Our findings may shed light on the biological mechanism underlying the "dopamine hypothesis" of schizophrenia and provide some implications regarding the polygenic effects on the dopaminergic activity in the risk for schizophrenia.

On the maintenance of genetic variation and adaptation to environmental change: considerations from population genomics in fishes.

PubMed

Bernatchez, L

2016-12-01

The first goal of this paper was to overview modern approaches to local adaptation, with a focus on the use of population genomics data to detect signals of natural selection in fishes. Several mechanisms are discussed that may enhance the maintenance of genetic variation and evolutionary potential, which have been overlooked and should be considered in future theoretical development and predictive models: the prevalence of soft sweeps, polygenic basis of adaptation, balancing selection and transient polymorphisms, parallel evolution, as well as epigenetic variation. Research on fish population genomics has provided ample evidence for local adaptation at the genome level. Pervasive adaptive evolution, however, seems to almost never involve the fixation of beneficial alleles. Instead, adaptation apparently proceeds most commonly by soft sweeps entailing shifts in frequencies of alleles being shared between differentially adapted populations. One obvious factor contributing to the maintenance of standing genetic variation in the face of selective pressures is that adaptive phenotypic traits are most often highly polygenic, and consequently the response to selection should derive mostly from allelic co-variances among causative loci rather than pronounced allele frequency changes. Balancing selection in its various forms may also play an important role in maintaining adaptive genetic variation and the evolutionary potential of species to cope with environmental change. A large body of literature on fishes also shows that repeated evolution of adaptive phenotypes is a ubiquitous evolutionary phenomenon that seems to occur most often via different genetic solutions, further adding to the potential options of species to cope with a changing environment. Moreover, a paradox is emerging from recent fish studies whereby populations of highly reduced effective population sizes and impoverished genetic diversity can apparently retain their adaptive potential in some circumstances. Although more empirical support is needed, several recent studies suggest that epigenetic variation could account for this apparent paradox. Therefore, epigenetic variation should be fully integrated with considerations pertaining to role of soft sweeps, polygenic and balancing selection, as well as repeated adaptation involving different genetic basis towards improving models predicting the evolutionary potential of species to cope with a changing world. © 2016 The Fisheries Society of the British Isles.

[Genome-wide association study for adolescent idiopathic scoliosis].

PubMed

Ogura, Yoji; Kou, Ikuyo; Scoliosis, Japan; Matsumoto, Morio; Watanabe, Kota; Ikegawa, Shiro

2016-04-01

Adolescent idiopathic scoliosis(AIS)is a polygenic disease. Genome-wide association studies(GWASs)have been performed for a lot of polygenic diseases. For AIS, we conducted GWAS and identified the first AIS locus near LBX1. After the discovery, we have extended our study by increasing the numbers of subjects and SNPs. In total, our Japanese GWAS has identified four susceptibility genes. GWASs for AIS have also been performed in the USA and China, which identified one and three susceptibility genes, respectively. Here we review GWASs in Japan and abroad and functional analysis to clarify the pathomechanism of AIS.

Histocompatibility antigens and genetic control of the immune response in guinea-pigs. V. Evidence from further breeding studies for the polygenic control of the cellular immune response to structurally unrelated antigens in the guinea-pig.

PubMed

Geczy, A F; de Weck, A L

1977-10-01

Further breeding studies were carried out to investigate the polygenic control of the cellular immune response in the guinea-pig to low doses of aspirin anhydride (ASAN), penicilloylated bovine immunoglobulin (BPO-BGG) and to the multi-chain copolymer (T, G)-A-L. Although responsiveness to these three antigens is controlled by three independently segregating loci, at least one gene required for these responses is linked to the strain 13 haplotype.

Laboratory animals as surrogate models of human obesity

PubMed Central

Nilsson, Cecilia; Raun, Kirsten; Yan, Fei-fei; Larsen, Marianne O; Tang-Christensen, Mads

2012-01-01

Obesity and obesity-related metabolic diseases represent a growing socioeconomic problem throughout the world. Great emphasis has been put on establishing treatments for this condition, including pharmacological intervention. However, there are many obstacles and pitfalls in the development process from pre-clinical research to the pharmacy counter, and there is no certainty that what has been observed pre-clinically will translate into an improvement in human health. Hence, it is important to test potential new drugs in a valid translational model early in their development. In the current mini-review, a number of monogenetic and polygenic models of obesity will be discussed in view of their translational character. PMID:22301857

Polygenic susceptibility to testicular cancer: implications for personalised health care.

PubMed

Litchfield, Kevin; Mitchell, Jonathan S; Shipley, Janet; Huddart, Robert; Rajpert-De Meyts, Ewa; Skakkebæk, Niels E; Houlston, Richard S; Turnbull, Clare

2015-11-17

The increasing incidence of testicular germ cell tumour (TGCT) combined with its strong heritable basis suggests that stratified screening for the early detection of TGCT may be clinically useful. We modelled the efficiency of such a personalised screening approach, based on genetic risk profiling in combination with other diagnostic tools. We compared the number of cases potentially detectable in the population under a number of screening models. The polygenic risk scoring (PRS) model was assumed to have a log-normal relative risk distribution across the 19 currently known TGCT susceptibility variants. The diagnostic performance of testicular biopsy and non-invasive semen analysis was also assessed, within a simulated combined screening programme. The area under the curve for the TGCT PRS model was 0.72 with individuals in the top 1% of the PRS having a nine-fold increased TGCT risk compared with the population median. Results from population-screening simulations only achieved a maximal positive predictive value (PPV) of 60%, highlighting broader clinical factors that challenge such strategies, not least the rare nature of TGCT. In terms of future improvements, heritability estimates suggest that a significant number of additional genetic risk factors for TGCT remain to be discovered, identification of which would potentially yield improvement of the PPV to 80-90%. While personalised screening models may offer enhanced TGCT risk discrimination, presently the case for population-level testing is not compelling. However, future advances, such as more routine generation of whole genome data is likely to alter the landscape. More targeted screening programs may plausibly then offer clinical benefit, particularly given the significant survivorship issues associated with the successful treatment of TGCT.

Strategy and model building in the fourth dimension: a null model for genotype x age interaction as a Gaussian stationary stochastic process.

PubMed

Diego, Vincent P; Almasy, Laura; Dyer, Thomas D; Soler, Júlia M P; Blangero, John

2003-12-31

Using univariate and multivariate variance components linkage analysis methods, we studied possible genotype x age interaction in cardiovascular phenotypes related to the aging process from the Framingham Heart Study. We found evidence for genotype x age interaction for fasting glucose and systolic blood pressure. There is polygenic genotype x age interaction for fasting glucose and systolic blood pressure and quantitative trait locus x age interaction for a linkage signal for systolic blood pressure phenotypes located on chromosome 17 at 67 cM.

Assessing the presence of shared genetic architecture between Alzheimer's disease and major depressive disorder using genome-wide association data

PubMed Central

Gibson, J; Russ, T C; Adams, M J; Clarke, T-K; Howard, D M; Hall, L S; Fernandez-Pujals, A M; Wigmore, E M; Hayward, C; Davies, G; Murray, A D; Smith, B H; Porteous, D J; Deary, I J; McIntosh, A M

2017-01-01

Major depressive disorder (MDD) and Alzheimer's disease (AD) are both common in older age and frequently co-occur. Numerous phenotypic studies based on clinical diagnoses suggest that a history of depression increases risk of subsequent AD, although the basis of this relationship is uncertain. Both illnesses are polygenic, and shared genetic risk factors could explain some of the observed association. We used genotype data to test whether MDD and AD have an overlapping polygenic architecture in two large population-based cohorts, Generation Scotland's Scottish Family Health Study (GS:SFHS; N=19 889) and UK Biobank (N=25 118), and whether age of depression onset influences any relationship. Using two complementary techniques, we found no evidence that the disorders are influenced by common genetic variants. Using linkage disequilibrium score regression with genome-wide association study (GWAS) summary statistics from the International Genomics of Alzheimer's Project, we report no significant genetic correlation between AD and MDD (rG=−0.103, P=0.59). Polygenic risk scores (PRS) generated using summary data from International Genomics of Alzheimer's Project (IGAP) and the Psychiatric Genomics Consortium were used to assess potential pleiotropy between the disorders. PRS for MDD were nominally associated with participant-recalled AD family history in GS:SFHS, although this association did not survive multiple comparison testing. AD PRS were not associated with depression status or late-onset depression, and a survival analysis showed no association between age of depression onset and genetic risk for AD. This study found no evidence to support a common polygenic structure for AD and MDD, suggesting that the comorbidity of these disorders is not explained by common genetic variants. PMID:28418403

Is Multifactorial Sex Determination in the House Fly, Musca domestica (L.), Stable Over Time?

PubMed

Meisel, Richard P; Davey, Taira; Son, Jae Hak; Gerry, Alec C; Shono, Toshio; Scott, Jeffrey G

2016-01-01

Sex determination pathways evolve rapidly, usually because of turnover of master regulatory genes at the top of the developmental pathway. Polygenic sex determination is expected to be a transient state between ancestral and derived conditions. However, polygenic sex determination has been observed in numerous animal species, including the house fly, Musca domestica House fly males carry a male-determining factor (M) that can be located on any chromosome, and an individual male may have multiple M factors. Females lack M and/or have a dominant allele of the Md-tra gene (Md-tra D ) that acts as a female-determining locus even in the presence of multiple copies of M. We found the frequency and linkage of M in house flies collected in Chino, CA (USA) was relatively unchanged between 1982 and 2014. The frequency of females with Md-tra D in the 2014 collection was 33.6% (n = 140). Analysis of these results, plus previously published data, revealed a strong correlation between the frequencies of Md-tra D and multiple M males, and we find that these populations are expected to have balanced sex ratios. We also find that fitness values that allow for the invasion and maintenance of multiple sex determining loci suggest that sexually antagonistic selection could be responsible for maintaining polygenic sex determination in house fly populations. The stability over time and equilibrium frequencies within populations suggest the house fly polygenic sex determination system is not in transition, and provide guidance for future investigations on the factors responsible for the polymorphism. © The American Genetic Association 2016. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Polygenic Risk Score for Alzheimer's Disease: Implications for Memory Performance and Hippocampal Volumes in Early Life.

PubMed

Axelrud, Luiza K; Santoro, Marcos L; Pine, Daniel S; Talarico, Fernanda; Gadelha, Ary; Manfro, Gisele G; Pan, Pedro M; Jackowski, Andrea; Picon, Felipe; Brietzke, Elisa; Grassi-Oliveira, Rodrigo; Bressan, Rodrigo A; Miguel, Eurípedes C; Rohde, Luis A; Hakonarson, Hakon; Pausova, Zdenka; Belangero, Sintia; Paus, Tomas; Salum, Giovanni A

2018-06-01

Alzheimer's disease is a heritable neurodegenerative disorder in which early-life precursors may manifest in cognition and brain structure. The authors evaluate this possibility by examining, in youths, associations among polygenic risk score for Alzheimer's disease, cognitive abilities, and hippocampal volume. Participants were children 6-14 years of age in two Brazilian cities, constituting the discovery (N=364) and replication samples (N=352). As an additional replication, data from a Canadian sample (N=1,029), with distinct tasks, MRI protocol, and genetic risk, were included. Cognitive tests quantified memory and executive function. Reading and writing abilities were assessed by standardized tests. Hippocampal volumes were derived from the Multiple Automatically Generated Templates (MAGeT) multi-atlas segmentation brain algorithm. Genetic risk for Alzheimer's disease was quantified using summary statistics from the International Genomics of Alzheimer's Project. Analyses showed that for the Brazilian discovery sample, each one-unit increase in z-score for Alzheimer's polygenic risk score significantly predicted a 0.185 decrement in z-score for immediate recall and a 0.282 decrement for delayed recall. Findings were similar for the Brazilian replication sample (immediate and delayed recall, β=-0.259 and β=-0.232, both significant). Quantile regressions showed lower hippocampal volumes bilaterally for individuals with high polygenic risk scores. Associations fell short of significance for the Canadian sample. Genetic risk for Alzheimer's disease may affect early-life cognition and hippocampal volumes, as shown in two independent samples. These data support previous evidence that some forms of late-life dementia may represent developmental conditions with roots in childhood. This result may vary depending on a sample's genetic risk and may be specific to some types of memory tasks.

A Polygenic Risk Score of glutamatergic SNPs associated with schizophrenia predicts attentional behavior and related brain activity in healthy humans.

PubMed

Rampino, Antonio; Taurisano, Paolo; Fanelli, Giuseppe; Attrotto, Mariateresa; Torretta, Silvia; Antonucci, Linda Antonella; Miccolis, Grazia; Pergola, Giulio; Ursini, Gianluca; Maddalena, Giancarlo; Romano, Raffaella; Masellis, Rita; Di Carlo, Pasquale; Pignataro, Patrizia; Blasi, Giuseppe; Bertolino, Alessandro

2017-09-01

Multiple genetic variations impact on risk for schizophrenia. Recent analyses by the Psychiatric Genomics Consortium (PGC2) identified 128 SNPs genome-wide associated with the disorder. Furthermore, attention and working memory deficits are core features of schizophrenia, are heritable and have been associated with variation in glutamatergic neurotransmission. Based on this evidence, in a sample of healthy volunteers, we used SNPs associated with schizophrenia in PGC2 to construct a Polygenic-Risk-Score (PRS) reflecting the cumulative risk for schizophrenia, along with a Polygenic-Risk-Score including only SNPs related to genes implicated in glutamatergic signaling (Glu-PRS). We performed Factor Analysis for dimension reduction of indices of cognitive performance. Furthermore, both PRS and Glu-PRS were used as predictors of cognitive functioning in the domains of Attention, Speed of Processing and Working Memory. The association of the Glu-PRS on brain activity during the Variable Attention Control (VAC) task was also explored. Finally, in a second independent sample of healthy volunteers we sought to confirm the association between the Glu-PRS and both performance in the domain of Attention and brain activity during the VAC.We found that performance in Speed of Processing and Working Memory was not associated with any of the Polygenic-Risk-Scores. The Glu-PRS, but not the PRS was associated with Attention and brain activity during the VAC. The specific effects of Glu-PRS on Attention and brain activity during the VAC were also confirmed in the replication sample.Our results suggest a pathway specificity in the relationship between genetic risk for schizophrenia, the associated cognitive dysfunction and related brain processing. Copyright © 2017 Elsevier B.V. and ECNP. All rights reserved.

Genetic liability for schizophrenia predicts risk of immune disorders.

PubMed

Stringer, Sven; Kahn, René S; de Witte, Lot D; Ophoff, Roel A; Derks, Eske M

2014-11-01

Schizophrenia patients and their parents have an increased risk of immune disorders compared to population controls and their parents. This may be explained by genetic overlap in the pathogenesis of both types of disorders. The purpose of this study was to investigate the genetic overlap between schizophrenia and three immune disorders and to compare with the overlap between schizophrenia and two disorders not primarily characterized by immune dysregulation: bipolar disorder and type 2 diabetes. We performed a polygenic risk score analysis using results from the schizophrenia Psychiatric GWAS consortium (PGC) (8922 cases and 9528 controls) and five Wellcome Trust Case Control Consortium (WTCCC) case samples as target cases: bipolar disorder (n=1998), type 1 diabetes (n=2000), Crohn's diseases (n=2005), rheumatoid arthritis (n=1999), and type 2 diabetes (n=1999). The WTCCC British Birth Cohort and National Blood Service samples (n=3004) were used as target controls. Additionally, we tested whether schizophrenia polygenic risk scores significantly differed between patients with immune disorder, bipolar disorder, and type 2 diabetes respectively. Polygenic risk scores for schizophrenia significantly predicted disease status in all three immune disorder samples (Nagelkerke-R(2) 1.1%-1.3%; p<0.05). The polygenic risk of schizophrenia in patients with immune disorders was significantly lower than in patients with bipolar disorder (Nagelkerke-R(2) 6.0%; p<0.05), but higher than in type 2 diabetes patients (Nagelkerke-R(2) 0.5%; p<0.05). Our results suggest that genetic factors are shared between schizophrenia and immune disorders. This contributes to an accumulating body of evidence that immune processes may play a role in the etiology of schizophrenia. Copyright © 2014 Elsevier B.V. All rights reserved.

Shared genetic influences between attention-deficit/hyperactivity disorder (ADHD) traits in children and clinical ADHD.

PubMed

Stergiakouli, Evie; Martin, Joanna; Hamshere, Marian L; Langley, Kate; Evans, David M; St Pourcain, Beate; Timpson, Nicholas J; Owen, Michael J; O'Donovan, Michael; Thapar, Anita; Davey Smith, George

2015-04-01

Twin studies and genome-wide complex trait analysis (GCTA) are not in agreement regarding heritability estimates for behavioral traits in children from the general population. This has sparked a debate on the possible difference in genetic architecture between behavioral traits and psychiatric disorders. In this study, we test whether polygenic risk scores associated with variation in attention-deficit/hyperactivity disorder (ADHD) trait levels in children from the general population predict ADHD diagnostic status and severity in an independent clinical sample. Single nucleotide polymorphisms (SNPs) with p < .5 from a genome-wide association study of ADHD traits in 4,546 children (mean age, 7 years 7 months) from the Avon Longitudinal Study of Parents and Children (ALSPAC; general population sample) were selected to calculate polygenic risk scores in 508 children with an ADHD diagnosis (independent clinical sample) and 5,081 control participants. Polygenic scores were tested for association with case-control status and severity of disorder in the clinical sample. Increased polygenic score for ADHD traits predicted ADHD case-control status (odds ratio = 1.17 [95% CI = 1.08-1.28], p = .0003), higher ADHD symptom severity (β = 0.29 [95% CI = 0.04-0.54], p = 0.02), and symptom domain severity in the clinical sample. This study highlights the relevance of additive genetic variance in ADHD, and provides evidence that shared genetic factors contribute to both behavioral traits in the general population and psychiatric disorders at least in the case of ADHD. Copyright © 2015 American Academy of Child and Adolescent Psychiatry. Published by Elsevier Inc. All rights reserved.

Polygenic interactions with environmental adversity in the aetiology of major depressive disorder.

PubMed

Mullins, N; Power, R A; Fisher, H L; Hanscombe, K B; Euesden, J; Iniesta, R; Levinson, D F; Weissman, M M; Potash, J B; Shi, J; Uher, R; Cohen-Woods, S; Rivera, M; Jones, L; Jones, I; Craddock, N; Owen, M J; Korszun, A; Craig, I W; Farmer, A E; McGuffin, P; Breen, G; Lewis, C M

2016-03-01

Major depressive disorder (MDD) is a common and disabling condition with well-established heritability and environmental risk factors. Gene-environment interaction studies in MDD have typically investigated candidate genes, though the disorder is known to be highly polygenic. This study aims to test for interaction between polygenic risk and stressful life events (SLEs) or childhood trauma (CT) in the aetiology of MDD. The RADIANT UK sample consists of 1605 MDD cases and 1064 controls with SLE data, and a subset of 240 cases and 272 controls with CT data. Polygenic risk scores (PRS) were constructed using results from a mega-analysis on MDD by the Psychiatric Genomics Consortium. PRS and environmental factors were tested for association with case/control status and for interaction between them. PRS significantly predicted depression, explaining 1.1% of variance in phenotype (p = 1.9 × 10(-6)). SLEs and CT were also associated with MDD status (p = 2.19 × 10(-4) and p = 5.12 × 10(-20), respectively). No interactions were found between PRS and SLEs. Significant PRSxCT interactions were found (p = 0.002), but showed an inverse association with MDD status, as cases who experienced more severe CT tended to have a lower PRS than other cases or controls. This relationship between PRS and CT was not observed in independent replication samples. CT is a strong risk factor for MDD but may have greater effect in individuals with lower genetic liability for the disorder. Including environmental risk along with genetics is important in studying the aetiology of MDD and PRS provide a useful approach to investigating gene-environment interactions in complex traits.

Evidence of Common Genetic Overlap Between Schizophrenia and Cognition

PubMed Central

Hubbard, Leon; Tansey, Katherine E.; Rai, Dheeraj; Jones, Peter; Ripke, Stephan; Chambert, Kimberly D.; Moran, Jennifer L.; McCarroll, Steven A.; Linden, David E. J.; Owen, Michael J.; O’Donovan, Michael C.; Walters, James T. R.; Zammit, Stanley

2016-01-01

Cognitive impairment is a core feature of schizophrenia but there is limited understanding of the genetic relationship between cognition in the general population and schizophrenia. We examine how common variants associated with schizophrenia en masse contribute to childhood cognitive ability in a population-based sample, and the extent to which common genetic variants associated with childhood cognition explain variation in schizophrenia. Schizophrenia polygenic risk scores were derived from the Psychiatric Genomics Consortium (n = 69 516) and tested for association with IQ, attention, processing speed, working memory, problem solving, and social cognition in over 5000 children aged 8 from the Avon Longitudinal Study of Parents and Children birth cohort. Polygenic scores for these cognitive domains were tested for association with schizophrenia in a large UK schizophrenia sample (n = 11 853). Bivariate genome-wide complex trait analysis (GCTA) estimated the amount of shared genetic factors between schizophrenia and cognitive domains. Schizophrenia polygenic risk score was associated with lower performance IQ (P = .001) and lower full IQ (P = .013). Polygenic score for performance IQ was associated with increased risk for schizophrenia (P = 3.56E-04). Bivariate GCTA revealed moderate genetic correlation between schizophrenia and both performance IQ (r G = −.379, P = 6.62E-05) and full IQ (r G = −.202, P = 5.00E-03), with approximately 14% of the genetic component of schizophrenia shared with that for performance IQ. Our results support the presence of shared common genetic factors between schizophrenia and childhood cognitive ability. We observe a genetic relationship between schizophrenia and performance IQ but not verbal IQ or other cognitive variables, which may have implications for studies utilizing cognitive endophenotypes for psychosis. PMID:26678674

Evidence of Common Genetic Overlap Between Schizophrenia and Cognition.

PubMed

Hubbard, Leon; Tansey, Katherine E; Rai, Dheeraj; Jones, Peter; Ripke, Stephan; Chambert, Kimberly D; Moran, Jennifer L; McCarroll, Steven A; Linden, David E J; Owen, Michael J; O'Donovan, Michael C; Walters, James T R; Zammit, Stanley

2016-05-01

Cognitive impairment is a core feature of schizophrenia but there is limited understanding of the genetic relationship between cognition in the general population and schizophrenia. We examine how common variants associated with schizophreniaen massecontribute to childhood cognitive ability in a population-based sample, and the extent to which common genetic variants associated with childhood cognition explain variation in schizophrenia. Schizophrenia polygenic risk scores were derived from the Psychiatric Genomics Consortium (n= 69 516) and tested for association with IQ, attention, processing speed, working memory, problem solving, and social cognition in over 5000 children aged 8 from the Avon Longitudinal Study of Parents and Children birth cohort. Polygenic scores for these cognitive domains were tested for association with schizophrenia in a large UK schizophrenia sample (n= 11 853). Bivariate genome-wide complex trait analysis (GCTA) estimated the amount of shared genetic factors between schizophrenia and cognitive domains. Schizophrenia polygenic risk score was associated with lower performance IQ (P= .001) and lower full IQ (P= .013). Polygenic score for performance IQ was associated with increased risk for schizophrenia (P= 3.56E-04). Bivariate GCTA revealed moderate genetic correlation between schizophrenia and both performance IQ (rG= -.379,P= 6.62E-05) and full IQ (rG= -.202,P= 5.00E-03), with approximately 14% of the genetic component of schizophrenia shared with that for performance IQ. Our results support the presence of shared common genetic factors between schizophrenia and childhood cognitive ability. We observe a genetic relationship between schizophrenia and performance IQ but not verbal IQ or other cognitive variables, which may have implications for studies utilizing cognitive endophenotypes for psychosis. © The Author 2015. Published by Oxford University Press on behalf of the Maryland Psychiatric Research Center.

Identification of two heritable cross-disorder endophenotypes for Tourette Syndrome

PubMed Central

Darrow, Sabrina M.; Hirschtritt, Matthew E.; Davis, Lea K.; Illmann, Cornelia; Osiecki, Lisa; Grados, Marco; Sandor, Paul; Dion, Yves; King, Robert; Pauls, David; Budman, Cathy L.; Cath, Danielle C.; Greenberg, Erica; Lyon, Gholson J.; Yu, Dongmei; McGrath, Lauren M.; McMahon, William M.; Lee, Paul C.; Delucchi, Kevin L.; Scharf, Jeremiah M.; Mathews, Carol A.

2016-01-01

Objective Phenotypic heterogeneity in Tourette syndrome (TS) is partly due to complex genetic relationships between TS, obsessive-compulsive disorder (OCD) and attention deficit/hyperactivity disorder (ADHD). Identifying symptom-based endophenotypes across diagnoses may aid gene-finding efforts. Method 3494 individuals recruited for genetic studies were assessed for TS, OCD, and ADHD symptoms. Symptom-level factor and latent class analyses were conducted in TS families and replicated in an independent sample. Classes were characterized by comorbidity rates and proportion of parents. Heritability and TS-, OCD-, and ADHD-associated polygenic load were estimated. Results We identified two cross-disorder symptom-based phenotypes across analyses: symmetry (symmetry, evening up, checking obsessions; ordering, arranging, counting, writing-rewriting compulsions, repetitive writing tics) and disinhibition (uttering syllables/words, echolalia/palilalia, coprolalia/copropraxia and obsessive urges to offend/mutilate/be destructive). Heritability estimates for both endophenotypes were high (disinhibition factor= 0.35, SE=0.03, p= 4.2 ×10−34; symmetry factor= 0.39, SE=0.03, p= 7.2 ×10−31; symmetry class=0.38, SE=0.10, p=0.001). Mothers of TS probands had high rates of symmetry (49%) but not disinhibition (5%). Polygenic risk scores derived from a TS genome-wide association study (GWAS) were associated with symmetry (p= 0.02), while risk scores derived from an OCD GWAS were not. OCD polygenic risk scores were associated with disinhibition (p =0.03), while TS and ADHD risk scores were not. Conclusions We identified two heritable TS-related endophenotypes that cross traditional diagnostic boundaries. The symmetry phenotype correlated with TS polygenic load, and was present in otherwise “TS-unaffected” mothers, suggesting that this phenotype may reflect additional TS (rather than OCD) genetic liability that is not captured by traditional DSM-based diagnoses. PMID:27809572

Identification of Two Heritable Cross-Disorder Endophenotypes for Tourette Syndrome.

PubMed

Darrow, Sabrina M; Hirschtritt, Matthew E; Davis, Lea K; Illmann, Cornelia; Osiecki, Lisa; Grados, Marco; Sandor, Paul; Dion, Yves; King, Robert; Pauls, David; Budman, Cathy L; Cath, Danielle C; Greenberg, Erica; Lyon, Gholson J; Yu, Dongmei; McGrath, Lauren M; McMahon, William M; Lee, Paul C; Delucchi, Kevin L; Scharf, Jeremiah M; Mathews, Carol A

2017-04-01

Phenotypic heterogeneity in Tourette syndrome is partly due to complex genetic relationships among Tourette syndrome, obsessive-compulsive disorder (OCD), and attention deficit hyperactivity disorder (ADHD). Identifying symptom-based endophenotypes across diagnoses may aid gene-finding efforts. Assessments for Tourette syndrome, OCD, and ADHD symptoms were conducted in a discovery sample of 3,494 individuals recruited for genetic studies. Symptom-level factor and latent class analyses were conducted in Tourette syndrome families and replicated in an independent sample of 882 individuals. Classes were characterized by comorbidity rates and proportion of parents included. Heritability and polygenic load associated with Tourette syndrome, OCD, and ADHD were estimated. The authors identified two cross-disorder symptom-based phenotypes across analyses: symmetry (symmetry, evening up, checking obsessions; ordering, arranging, counting, writing-rewriting compulsions, repetitive writing tics) and disinhibition (uttering syllables/words, echolalia/palilalia, coprolalia/copropraxia, and obsessive urges to offend/mutilate/be destructive). Heritability estimates for both endophenotypes were high and statistically significant (disinhibition factor=0.35, SE=0.03; symmetry factor=0.39, SE=0.03; symmetry class=0.38, SE=0.10). Mothers of Tourette syndrome probands had high rates of symmetry (49%) but not disinhibition (5%). Polygenic risk scores derived from a Tourette syndrome genome-wide association study (GWAS) were significantly associated with symmetry, while risk scores derived from an OCD GWAS were not. OCD polygenic risk scores were significantly associated with disinhibition, while Tourette syndrome and ADHD risk scores were not. The analyses identified two heritable endophenotypes related to Tourette syndrome that cross traditional diagnostic boundaries. The symmetry phenotype correlated with Tourette syndrome polygenic load and was present in otherwise Tourette-unaffected mothers, suggesting that this phenotype may reflect additional Tourette syndrome (rather than OCD) genetic liability that is not captured by traditional DSM-based diagnoses.

Assessing the presence of shared genetic architecture between Alzheimer's disease and major depressive disorder using genome-wide association data.

PubMed

Gibson, J; Russ, T C; Adams, M J; Clarke, T-K; Howard, D M; Hall, L S; Fernandez-Pujals, A M; Wigmore, E M; Hayward, C; Davies, G; Murray, A D; Smith, B H; Porteous, D J; Deary, I J; McIntosh, A M

2017-04-18

Major depressive disorder (MDD) and Alzheimer's disease (AD) are both common in older age and frequently co-occur. Numerous phenotypic studies based on clinical diagnoses suggest that a history of depression increases risk of subsequent AD, although the basis of this relationship is uncertain. Both illnesses are polygenic, and shared genetic risk factors could explain some of the observed association. We used genotype data to test whether MDD and AD have an overlapping polygenic architecture in two large population-based cohorts, Generation Scotland's Scottish Family Health Study (GS:SFHS; N=19 889) and UK Biobank (N=25 118), and whether age of depression onset influences any relationship. Using two complementary techniques, we found no evidence that the disorders are influenced by common genetic variants. Using linkage disequilibrium score regression with genome-wide association study (GWAS) summary statistics from the International Genomics of Alzheimer's Project, we report no significant genetic correlation between AD and MDD (r G =-0.103, P=0.59). Polygenic risk scores (PRS) generated using summary data from International Genomics of Alzheimer's Project (IGAP) and the Psychiatric Genomics Consortium were used to assess potential pleiotropy between the disorders. PRS for MDD were nominally associated with participant-recalled AD family history in GS:SFHS, although this association did not survive multiple comparison testing. AD PRS were not associated with depression status or late-onset depression, and a survival analysis showed no association between age of depression onset and genetic risk for AD. This study found no evidence to support a common polygenic structure for AD and MDD, suggesting that the comorbidity of these disorders is not explained by common genetic variants.

Evaluation of polygenic cause in Korean patients with familial hypercholesterolemia - A study supported by Korean Society of Lipidology and Atherosclerosis.

PubMed

Kwon, Manjae; Han, Soo Min; Kim, Do-Il; Rhee, Moo-Yong; Lee, Byoung-Kwon; Ahn, Young Keun; Cho, Byung Ryul; Woo, Jeongtaek; Hur, Seung-Ho; Jeong, Jin-Ok; Jang, Yangsoo; Lee, Sang-Hak; Lee, Ji Hyun

2015-09-01

Familial hypercholesterolemia (FH) is an autosomal dominant disorder caused by mutations in LDLR, APOB, or PCSK9. Polygenicity is a plausible cause in mutation-negative FH patients based on LDL cholesterol (LDL-C)-associated single nucleotide polymorphisms (SNPs) identified by the Global Lipids Genetics Consortium (GLGC). However, there are limited data regarding the polygenic cause of FH in Asians. We gathered data from 66 mutation-negative and 31 mutation-positive Korean FH patients, as well as from 2274 controls who participated in the Korean Health Examinee (HEXA) shared control study. We genotyped the patients for six GLGC SNPs and four East Asian LDL-C-associated SNPs and compared SNP scores among patient groups and controls. Weighted mean 6- and 4-SNP scores (0.67 [SD = 0.07] and 0.46 [0.11], respectively) were both significantly associated with LDL-C levels in controls (p = 2.1 × 10(-4), R(2) = 0.01 and p = 5.0 × 10(-12), R(2) = 0.02, respectively). Mutation-negative FH patients had higher 6-SNP (0.72 [0.07]) and 4-SNP (0.49 [0.08]) scores than controls (p = 1.8 × 10(-8) and p = 3.6 × 10(-3), respectively). We also observed higher scores in mutation-positive FH patients compared with controls, but the difference did not reach statistical significance. The present study demonstrates the utility of SNP score analysis for identifying polygenic FH in Korean patients by showing that small-effect common SNPs may cumulatively elevate LDL-C levels. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Characterizing the genetic influences on risk aversion.

PubMed

Harrati, Amal

2014-01-01

Risk aversion has long been cited as an important factor in retirement decisions, investment behavior, and health. Some of the heterogeneity in individual risk tolerance is well understood, reflecting age gradients, wealth gradients, and similar effects, but much remains unexplained. This study explores genetic contributions to heterogeneity in risk aversion among older Americans. Using over 2 million genetic markers per individual from the U.S. Health and Retirement Study, I report results from a genome-wide association study (GWAS) on risk preferences using a sample of 10,455 adults. None of the single-nucleotide polymorphisms (SNPs) are found to be statistically significant determinants of risk preferences at levels stricter than 5 × 10(-8). These results suggest that risk aversion is a complex trait that is highly polygenic. The analysis leads to upper bounds on the number of genetic effects that could exceed certain thresholds of significance and still remain undetected at the current sample size. The findings suggest that the known heritability in risk aversion is likely to be driven by large numbers of genetic variants, each with a small effect size.

Common Variant Burden Contributes to the Familial Aggregation of Migraine in 1,589 Families.

PubMed

Gormley, Padhraig; Kurki, Mitja I; Hiekkala, Marjo Eveliina; Veerapen, Kumar; Häppölä, Paavo; Mitchell, Adele A; Lal, Dennis; Palta, Priit; Surakka, Ida; Kaunisto, Mari Anneli; Hämäläinen, Eija; Vepsäläinen, Salli; Havanka, Hannele; Harno, Hanna; Ilmavirta, Matti; Nissilä, Markku; Säkö, Erkki; Sumelahti, Marja-Liisa; Liukkonen, Jarmo; Sillanpää, Matti; Metsähonkala, Liisa; Koskinen, Seppo; Lehtimäki, Terho; Raitakari, Olli; Männikkö, Minna; Ran, Caroline; Belin, Andrea Carmine; Jousilahti, Pekka; Anttila, Verneri; Salomaa, Veikko; Artto, Ville; Färkkilä, Markus; Runz, Heiko; Daly, Mark J; Neale, Benjamin M; Ripatti, Samuli; Kallela, Mikko; Wessman, Maija; Palotie, Aarno

2018-05-16

Complex traits, including migraine, often aggregate in families, but the underlying genetic architecture behind this is not well understood. The aggregation could be explained by rare, penetrant variants that segregate according to Mendelian inheritance or by the sufficient polygenic accumulation of common variants, each with an individually small effect, or a combination of the two hypotheses. In 8,319 individuals across 1,589 migraine families, we calculated migraine polygenic risk scores (PRS) and found a significantly higher common variant burden in familial cases (n = 5,317, OR = 1.76, 95% CI = 1.71-1.81, p = 1.7 × 10 -109 ) compared to population cases from the FINRISK cohort (n = 1,101, OR = 1.32, 95% CI = 1.25-1.38, p = 7.2 × 10 -17 ). The PRS explained 1.6% of the phenotypic variance in the population cases and 3.5% in the familial cases (including 2.9% for migraine without aura, 5.5% for migraine with typical aura, and 8.2% for hemiplegic migraine). The results demonstrate a significant contribution of common polygenic variation to the familial aggregation of migraine. Copyright © 2018 Elsevier Inc. All rights reserved.

The Geographic Distribution of Genetic Risk as Compared to Social Risk for Chronic Diseases in the United States.

PubMed

Rehkopf, David H; Domingue, Benjamin W; Cullen, Mark R

2016-01-01

There is an association between chronic disease and geography, and there is evidence that the environment plays a critical role in this relationship. Yet at the same time, there is known to be substantial geographic variation by ancestry across the United States. Resulting geographic genetic variation-that is, the extent to which single nucleotide polymorphisms (SNPs) related to chronic disease vary spatially-could thus drive some part of the association between geography and disease. We describe the variation in chronic disease genetic risk by state of birth by taking risk SNPs from genome-wide association study meta-analyses for coronary artery disease, diabetes, and ischemic stroke and creating polygenic risk scores. We compare the amount of variability across state of birth in these polygenic scores to the variability in parental education, own education, earnings, and wealth. Our primary finding is that the polygenic risk scores are only weakly differentially distributed across U.S. states. The magnitude of the differences in geographic distribution is very small in comparison to the distribution of social and economic factors and thus is not likely sufficient to have a meaningful effect on geographic disease differences by U.S. state.

Polygenic Profile and Exercise-Induced Muscle Damage by a Competitive Half-Ironman.

PubMed

Del Coso, Juan; Salinero, Juan J; Lara, Beatriz; Gallo-Salazar, César; Areces, Francisco; Herrero, David; Puente, Carlos

2017-11-14

Del Coso, J, Salinero, JJ, Lara, B, Gallo-Salazar, C, Areces, F, Herrero, D, and Puente, C. Polygenic profile and exercise-induced muscle damage by a competitive half-ironman. J Strength Cond Res XX(X): 000-000, 2017-To date, it is still unknown why some individuals develop higher levels of muscle damage than other individuals, despite participating in exercise with comparable levels of physical intensity. The aim of this investigation was to analyze 7 single-nucleotide polymorphisms (SNPs) that are candidates to explain individual variations in the level of muscle damage attained during a half-ironman competition. Using the model of Williams and Folland (2, 1, and 0 points for optimal, intermediate, and suboptimal genotype), we determined the total genotype score from the accumulated combination of 7 SNPs (ACE = 287bp Ins/Del; ACTN3 = p.R577X; creatine kinase, muscle type = NcoI; insulin-like growth factor 2 = C13790G; interleukin-6 = 174G>C; myosin light chain kinase = C37885A; and tumor necrosis factor-α = 308G>A) in 22 experienced triathletes. Before and after the race, a sample of venous blood was obtained to measure serum markers of muscle damage. Two groups of triathletes were established according to their postcompetition serum CK concentration: low CK responders (n = 10; 377 ± 86 U·L) vs. high CK responders (n = 12; 709 ± 136 U·L). At the end of the race, low CK responders had lower serum myoglobin concentrations (384 ± 243 vs. 597 ± 293 ng·ml, p = 0.04). Although the groups were similar in age, anthropometric characteristics, and training habits, total genotype score was higher in low CK responders than in high CK responders (7.7 ± 1.1 vs. 5.5 ± 1.1 point, p < 0.01). A favorable polygenic profile can contribute to reducing the level of muscle damage developed during endurance exercise.

Additive genetic risk from five serotonin system polymorphisms interacts with interpersonal stress to predict depression.

PubMed

Vrshek-Schallhorn, Suzanne; Stroud, Catherine B; Mineka, Susan; Zinbarg, Richard E; Adam, Emma K; Redei, Eva E; Hammen, Constance; Craske, Michelle G

2015-11-01

Behavioral genetic research supports polygenic models of depression in which many genetic variations each contribute a small amount of risk, and prevailing diathesis-stress models suggest gene-environment interactions (G×E). Multilocus profile scores of additive risk offer an approach that is consistent with polygenic models of depression risk. In a first demonstration of this approach in a G×E predicting depression, we created an additive multilocus profile score from 5 serotonin system polymorphisms (1 each in the genes HTR1A, HTR2A, HTR2C, and 2 in TPH2). Analyses focused on 2 forms of interpersonal stress as environmental risk factors. Using 5 years of longitudinal diagnostic and life stress interviews from 387 emerging young adults in the Youth Emotion Project, survival analyses show that this multilocus profile score interacts with major interpersonal stressful life events to predict major depressive episode onsets (hazard ratio [HR] = 1.815, p = .007). Simultaneously, there was a significant protective effect of the profile score without a recent event (HR = 0.83, p = .030). The G×E effect with interpersonal chronic stress was not significant (HR = 1.15, p = .165). Finally, effect sizes for genetic factors examined ignoring stress suggested such an approach could lead to overlooking or misinterpreting genetic effects. Both the G×E effect and the protective simple main effect were replicated in a sample of early adolescent girls (N = 105). We discuss potential benefits of the multilocus genetic profile score approach and caveats for future research. (c) 2015 APA, all rights reserved).

Continuous variation caused by genes with graduated effects.

PubMed Central

Matthysse, S; Lange, K; Wagener, D K

1979-01-01

The classical polygenic theory of inheritance postulates a large number of genes with small, and essentially similar, effects. We propose instead a model with genes of gradually decreasing effects. The resulting phenotypic distribution is not normal; if the gene effects are geometrically decreasing, it can be triangular. The joint distribution of parent and offspring genic value is calculated. The most readily testable difference between the two models is that, in the decreasing-effect model, the variance of the offspring distribution from given parents depends on the parents' genic values. The more the parents deviate from the mean, the smaller the variance of the offspring should be. In the equal-effect model the offspring variance is independent of the parents' genic values. PMID:288073

Scrotal tongue and geographic tongue: polygenic and associated traits.

PubMed

Eidelman, E; Chosack, A; Cohen, T

1976-11-01

The familial nature of scrotal and geographic tongue was investigated in parents and siblings of 156 probands having these conditions. The prevalence in parents and siblings was significantly higher than that in the control populations. The prevalence in sibilings from families in which at least one parent was also affected was significantly higher than that in siblings from families in which neither parent was affected. The prevalence of scrotal tongue alone in siblins was similar irrespective of the condition in the proband. The prevalence of geographic tongue alone was highest in siblins of probands having only geographic tongue. A polygenic mode of inheritance with some genes common to both conditions is suggested.

Imaging Genetics and Genomics in Psychiatry: A Critical Review of Progress and Potential.

PubMed

Bogdan, Ryan; Salmeron, Betty Jo; Carey, Caitlin E; Agrawal, Arpana; Calhoun, Vince D; Garavan, Hugh; Hariri, Ahmad R; Heinz, Andreas; Hill, Matthew N; Holmes, Andrew; Kalin, Ned H; Goldman, David

2017-08-01

Imaging genetics and genomics research has begun to provide insight into the molecular and genetic architecture of neural phenotypes and the neural mechanisms through which genetic risk for psychopathology may emerge. As it approaches its third decade, imaging genetics is confronted by many challenges, including the proliferation of studies using small sample sizes and diverse designs, limited replication, problems with harmonization of neural phenotypes for meta-analysis, unclear mechanisms, and evidence that effect sizes may be more modest than originally posited, with increasing evidence of polygenicity. These concerns have encouraged the field to grow in many new directions, including the development of consortia and large-scale data collection projects and the use of novel methods (e.g., polygenic approaches, machine learning) that enhance the quality of imaging genetic studies but also introduce new challenges. We critically review progress in imaging genetics and offer suggestions and highlight potential pitfalls of novel approaches. Ultimately, the strength of imaging genetics and genomics lies in their translational and integrative potential with other research approaches (e.g., nonhuman animal models, psychiatric genetics, pharmacologic challenge) to elucidate brain-based pathways that give rise to the vast individual differences in behavior as well as risk for psychopathology. Copyright © 2017 Society of Biological Psychiatry. All rights reserved.

Polygenic risk score and heritability estimates reveals a genetic relationship between ASD and OCD.

PubMed

Guo, W; Samuels, J F; Wang, Y; Cao, H; Ritter, M; Nestadt, P S; Krasnow, J; Greenberg, B D; Fyer, A J; McCracken, J T; Geller, D A; Murphy, D L; Knowles, J A; Grados, M A; Riddle, M A; Rasmussen, S A; McLaughlin, N C; Nurmi, E L; Askland, K D; Cullen, B A; Piacentini, J; Pauls, D L; Bienvenu, O J; Stewart, S E; Goes, F S; Maher, B; Pulver, A E; Valle, D; Mattheisen, M; Qian, J; Nestadt, G; Shugart, Y Y

2017-07-01

Obsessive-compulsive disorder (OCD) and Autism spectrum disorder (ASD) are both highly heritable neurodevelopmental disorders that conceivably share genetic risk factors. However, the underlying genetic determinants remain largely unknown. In this work, the authors describe a combined genome-wide association study (GWAS) of ASD and OCD. The OCD dataset includes 2998 individuals in nuclear families. The ASD dataset includes 6898 individuals in case-parents trios. GWAS summary statistics were examined for potential enrichment of functional variants associated with gene expression levels in brain regions. The top ranked SNP is rs4785741 (chromosome 16) with P value=6.9×10 -7 in our re-analysis. Polygenic risk score analyses were conducted to investigate the genetic relationship within and across the two disorders. These analyses identified a significant polygenic component of ASD, predicting 0.11% of the phenotypic variance in an independent OCD data set. In addition, we examined the genomic architecture of ASD and OCD by estimating heritability on different chromosomes and different allele frequencies, analyzing genome-wide common variant data by using the Genome-wide Complex Trait Analysis (GCTA) program. The estimated global heritability of OCD is 0.427 (se=0.093) and 0.174 (se=0.053) for ASD in these imputed data. Published by Elsevier B.V.

Genome‐wide association study of facial emotion recognition in children and association with polygenic risk for mental health disorders

PubMed Central

Coleman, Jonathan R.I.; Lester, Kathryn J.; Keers, Robert; Munafò, Marcus R.; Breen, Gerome

2017-01-01

Emotion recognition is disrupted in many mental health disorders, which may reflect shared genetic aetiology between this trait and these disorders. We explored genetic influences on emotion recognition and the relationship between these influences and mental health phenotypes. Eight‐year‐old participants (n = 4,097) from the Avon Longitudinal Study of Parents and Children (ALSPAC) completed the Diagnostic Analysis of Non‐Verbal Accuracy (DANVA) faces test. Genome‐wide genotype data was available from the Illumina HumanHap550 Quad microarray. Genome‐wide association studies were performed to assess associations with recognition of individual emotions and emotion in general. Exploratory polygenic risk scoring was performed using published genomic data for schizophrenia, bipolar disorder, depression, autism spectrum disorder, anorexia, and anxiety disorders. No individual genetic variants were identified at conventional levels of significance in any analysis although several loci were associated at a level suggestive of significance. SNP‐chip heritability analyses did not identify a heritable component of variance for any phenotype. Polygenic scores were not associated with any phenotype. The effect sizes of variants influencing emotion recognition are likely to be small. Previous studies of emotion identification have yielded non‐zero estimates of SNP‐heritability. This discrepancy is likely due to differences in the measurement and analysis of the phenotype. PMID:28608620

Hundreds of variants clustered in genomic loci and biological pathways affect human height

PubMed Central

Lango Allen, Hana; Estrada, Karol; Lettre, Guillaume; Berndt, Sonja I.; Weedon, Michael N.; Rivadeneira, Fernando; Willer, Cristen J.; Jackson, Anne U.; Vedantam, Sailaja; Raychaudhuri, Soumya; Ferreira, Teresa; Wood, Andrew R.; Weyant, Robert J.; Segrè, Ayellet V.; Speliotes, Elizabeth K.; Wheeler, Eleanor; Soranzo, Nicole; Park, Ju-Hyun; Yang, Jian; Gudbjartsson, Daniel; Heard-Costa, Nancy L.; Randall, Joshua C.; Qi, Lu; Smith, Albert Vernon; Mägi, Reedik; Pastinen, Tomi; Liang, Liming; Heid, Iris M.; Luan, Jian'an; Thorleifsson, Gudmar; Winkler, Thomas W.; Goddard, Michael E.; Lo, Ken Sin; Palmer, Cameron; Workalemahu, Tsegaselassie; Aulchenko, Yurii S.; Johansson, Åsa; Zillikens, M.Carola; Feitosa, Mary F.; Esko, Tõnu; Johnson, Toby; Ketkar, Shamika; Kraft, Peter; Mangino, Massimo; Prokopenko, Inga; Absher, Devin; Albrecht, Eva; Ernst, Florian; Glazer, Nicole L.; Hayward, Caroline; Hottenga, Jouke-Jan; Jacobs, Kevin B.; Knowles, Joshua W.; Kutalik, Zoltán; Monda, Keri L.; Polasek, Ozren; Preuss, Michael; Rayner, Nigel W.; Robertson, Neil R.; Steinthorsdottir, Valgerdur; Tyrer, Jonathan P.; Voight, Benjamin F.; Wiklund, Fredrik; Xu, Jianfeng; Zhao, Jing Hua; Nyholt, Dale R.; Pellikka, Niina; Perola, Markus; Perry, John R.B.; Surakka, Ida; Tammesoo, Mari-Liis; Altmaier, Elizabeth L.; Amin, Najaf; Aspelund, Thor; Bhangale, Tushar; Boucher, Gabrielle; Chasman, Daniel I.; Chen, Constance; Coin, Lachlan; Cooper, Matthew N.; Dixon, Anna L.; Gibson, Quince; Grundberg, Elin; Hao, Ke; Junttila, M. Juhani; Kaplan, Lee M.; Kettunen, Johannes; König, Inke R.; Kwan, Tony; Lawrence, Robert W.; Levinson, Douglas F.; Lorentzon, Mattias; McKnight, Barbara; Morris, Andrew P.; Müller, Martina; Ngwa, Julius Suh; Purcell, Shaun; Rafelt, Suzanne; Salem, Rany M.; Salvi, Erika; Sanna, Serena; Shi, Jianxin; Sovio, Ulla; Thompson, John R.; Turchin, Michael C.; Vandenput, Liesbeth; Verlaan, Dominique J.; Vitart, Veronique; White, Charles C.; Ziegler, Andreas; Almgren, Peter; Balmforth, Anthony J.; Campbell, Harry; Citterio, Lorena; De Grandi, Alessandro; Dominiczak, Anna; Duan, Jubao; Elliott, Paul; Elosua, Roberto; Eriksson, Johan G.; Freimer, Nelson B.; Geus, Eco J.C.; Glorioso, Nicola; Haiqing, Shen; Hartikainen, Anna-Liisa; Havulinna, Aki S.; Hicks, Andrew A.; Hui, Jennie; Igl, Wilmar; Illig, Thomas; Jula, Antti; Kajantie, Eero; Kilpeläinen, Tuomas O.; Koiranen, Markku; Kolcic, Ivana; Koskinen, Seppo; Kovacs, Peter; Laitinen, Jaana; Liu, Jianjun; Lokki, Marja-Liisa; Marusic, Ana; Maschio, Andrea; Meitinger, Thomas; Mulas, Antonella; Paré, Guillaume; Parker, Alex N.; Peden, John F.; Petersmann, Astrid; Pichler, Irene; Pietiläinen, Kirsi H.; Pouta, Anneli; Ridderstråle, Martin; Rotter, Jerome I.; Sambrook, Jennifer G.; Sanders, Alan R.; Schmidt, Carsten Oliver; Sinisalo, Juha; Smit, Jan H.; Stringham, Heather M.; Walters, G.Bragi; Widen, Elisabeth; Wild, Sarah H.; Willemsen, Gonneke; Zagato, Laura; Zgaga, Lina; Zitting, Paavo; Alavere, Helene; Farrall, Martin; McArdle, Wendy L.; Nelis, Mari; Peters, Marjolein J.; Ripatti, Samuli; van Meurs, Joyce B.J.; Aben, Katja K.; Ardlie, Kristin G; Beckmann, Jacques S.; Beilby, John P.; Bergman, Richard N.; Bergmann, Sven; Collins, Francis S.; Cusi, Daniele; den Heijer, Martin; Eiriksdottir, Gudny; Gejman, Pablo V.; Hall, Alistair S.; Hamsten, Anders; Huikuri, Heikki V.; Iribarren, Carlos; Kähönen, Mika; Kaprio, Jaakko; Kathiresan, Sekar; Kiemeney, Lambertus; Kocher, Thomas; Launer, Lenore J.; Lehtimäki, Terho; Melander, Olle; Mosley, Tom H.; Musk, Arthur W.; Nieminen, Markku S.; O'Donnell, Christopher J.; Ohlsson, Claes; Oostra, Ben; Palmer, Lyle J.; Raitakari, Olli; Ridker, Paul M.; Rioux, John D.; Rissanen, Aila; Rivolta, Carlo; Schunkert, Heribert; Shuldiner, Alan R.; Siscovick, David S.; Stumvoll, Michael; Tönjes, Anke; Tuomilehto, Jaakko; van Ommen, Gert-Jan; Viikari, Jorma; Heath, Andrew C.; Martin, Nicholas G.; Montgomery, Grant W.; Province, Michael A.; Kayser, Manfred; Arnold, Alice M.; Atwood, Larry D.; Boerwinkle, Eric; Chanock, Stephen J.; Deloukas, Panos; Gieger, Christian; Grönberg, Henrik; Hall, Per; Hattersley, Andrew T.; Hengstenberg, Christian; Hoffman, Wolfgang; Lathrop, G.Mark; Salomaa, Veikko; Schreiber, Stefan; Uda, Manuela; Waterworth, Dawn; Wright, Alan F.; Assimes, Themistocles L.; Barroso, Inês; Hofman, Albert; Mohlke, Karen L.; Boomsma, Dorret I.; Caulfield, Mark J.; Cupples, L.Adrienne; Erdmann, Jeanette; Fox, Caroline S.; Gudnason, Vilmundur; Gyllensten, Ulf; Harris, Tamara B.; Hayes, Richard B.; Jarvelin, Marjo-Riitta; Mooser, Vincent; Munroe, Patricia B.; Ouwehand, Willem H.; Penninx, Brenda W.; Pramstaller, Peter P.; Quertermous, Thomas; Rudan, Igor; Samani, Nilesh J.; Spector, Timothy D.; Völzke, Henry; Watkins, Hugh; Wilson, James F.; Groop, Leif C.; Haritunians, Talin; Hu, Frank B.; Kaplan, Robert C.; Metspalu, Andres; North, Kari E.; Schlessinger, David; Wareham, Nicholas J.; Hunter, David J.; O'Connell, Jeffrey R.; Strachan, David P.; Wichmann, H.-Erich; Borecki, Ingrid B.; van Duijn, Cornelia M.; Schadt, Eric E.; Thorsteinsdottir, Unnur; Peltonen, Leena; Uitterlinden, André; Visscher, Peter M.; Chatterjee, Nilanjan; Loos, Ruth J.F.; Boehnke, Michael; McCarthy, Mark I.; Ingelsson, Erik; Lindgren, Cecilia M.; Abecasis, Gonçalo R.; Stefansson, Kari; Frayling, Timothy M.; Hirschhorn, Joel N

2010-01-01

Most common human traits and diseases have a polygenic pattern of inheritance: DNA sequence variants at many genetic loci influence phenotype. Genome-wide association (GWA) studies have identified >600 variants associated with human traits1, but these typically explain small fractions of phenotypic variation, raising questions about the utility of further studies. Here, using 183,727 individuals, we show that hundreds of genetic variants, in at least 180 loci, influence adult height, a highly heritable and classic polygenic trait2,3. The large number of loci reveals patterns with important implications for genetic studies of common human diseases and traits. First, the 180 loci are not random, but instead are enriched for genes that are connected in biological pathways (P=0.016), and that underlie skeletal growth defects (P<0.001). Second, the likely causal gene is often located near the most strongly associated variant: in 13 of 21 loci containing a known skeletal growth gene, that gene was closest to the associated variant. Third, at least 19 loci have multiple independently associated variants, suggesting that allelic heterogeneity is a frequent feature of polygenic traits, that comprehensive explorations of already-discovered loci should discover additional variants, and that an appreciable fraction of associated loci may have been identified. Fourth, associated variants are enriched for likely functional effects on genes, being over-represented amongst variants that alter amino acid structure of proteins and expression levels of nearby genes. Our data explain ∼10% of the phenotypic variation in height, and we estimate that unidentified common variants of similar effect sizes would increase this figure to ∼16% of phenotypic variation (∼20% of heritable variation). Although additional approaches are needed to fully dissect the genetic architecture of polygenic human traits, our findings indicate that GWA studies can identify large numbers of loci that implicate biologically relevant genes and pathways. PMID:20881960

Polygenic risk for depression and the neural correlates of working memory in healthy subjects.

PubMed

Yüksel, Dilara; Dietsche, Bruno; Forstner, Andreas J; Witt, Stephanie H; Maier, Robert; Rietschel, Marcella; Konrad, Carsten; Nöthen, Markus M; Dannlowski, Udo; Baune, Bernhard T; Kircher, Tilo; Krug, Axel

2017-10-03

Major depressive disorder (MDD) patients show impairments of cognitive functioning such as working memory (WM), and furthermore alterations during WM-fMRI tasks especially in frontal and parietal brain regions. The calculation of a polygenic risk score (PRS) can be used to describe the genetic influence on MDD, hence imaging genetic studies aspire to combine both genetics and neuroimaging data to identify the influence of genetic factors on brain functioning. We aimed to detect the effect of MDD-PRS on brain activation during a WM task measured with fMRI and expect healthy individuals with a higher PRS to be more resembling to MDD patients. In total, n=137 (80 men, 57 women, aged 34.5, SD=10.4years) healthy subjects performed a WM n-back task [0-back (baseline), 2-back and 3-back condition] in a 3T-MRI-tomograph. The sample was genotyped using the Infinium PsychArray BeadChip and a polygenic risk score was calculated for MDD using PGC MDD GWAS results. A lower MDD risk score was associated with increased activation in the bilateral middle occipital gyri (MOG), the bilateral middle frontal gyri (MFG) and the right precentral gyrus (PCG) during the 2-back vs. baseline condition. Moreover, a lower PRS was associated with increased brain activation during the 3-back vs. baseline condition in the bilateral cerebellum, the right MFG and the left inferior parietal lobule. A higher polygenic risk score was associated with hyperactivation in brain regions comprising the right MFG and the right supplementary motor area during the 3-back vs. 2-back condition. The results suggest that part of the WM-related brain activation patterns might be explained by genetic variants captured by the MDD-PRS. Furthermore we were able to detect MDD-associated activation patterns in healthy individuals depending on the MDD-PRS and the task complexity. Additional gene loci could contribute to these task-dependent brain activation patterns. Copyright © 2017 Elsevier Inc. All rights reserved.

Passive rGE or developmental gene-environment cascade? An investigation of the role of xenobiotic metabolism genes in the association between smoke exposure during pregnancy and child birth weight

PubMed Central

Marceau, Kristine; Palmer, Rohan H.C.; Neiderhiser, Jenae M.; Smith, Taylor F.; McGeary, John E.; Knopik, Valerie S.

2016-01-01

There is considerable evidence that smoke exposure during pregnancy (SDP) environmentally influences birth weight after controlling for genetic influences and maternal characteristics. However, maternal smoking during pregnancy – the behavior that leads to smoke exposure during pregnancy – is also genetically-influenced, indicating the potential role of passive gene-environment correlation. An alternative to passive gene-SDP correlation is a cascading effect whereby maternal and child genetic influences are causally linked to prenatal exposures, which then have an ‘environmental’ effect on the development of the child’s biology and behavior. We describe and demonstrate a conceptual framework for disentangling passive rGE from this cascading GE effect using a systems-based polygenic scoring approach comprised of genes shown to be important in the xenobiotic (substances foreign to the body) metabolism pathway. Data were drawn from 5,044 families from the Avon Longitudinal Study of Parents and Children with information on maternal SDP, birth weight, and genetic polymorphisms in the xenobiotic pathway. Within a k-fold cross-validation approach (k=5), we created weighted maternal and child polygenic scores using 18 polymorphisms from 10 genes that have been implicated in the xenobiotic metabolism pathway. Mothers and children shared variation in xenobiotic metabolism genes. Amongst mothers who smoked during pregnancy, neither maternal nor child xenobiotic metabolism polygenic scores were associated with a higher likelihood of smoke exposure during pregnancy, or the severity of smoke exposure during pregnancy (and therefore, neither proposed mechanism was supported), or with child birth weight. SDP was consistently associated with lower child birth weight controlling for the polygenic scores, maternal educational attainment, social class, psychiatric problems, and age. Limitations of the study design and the potential of the framework using other designs are discussed. PMID:26803317

Dissection of major depressive disorder using polygenic risk scores for schizophrenia in two independent cohorts.

PubMed

Whalley, H C; Adams, M J; Hall, L S; Clarke, T-K; Fernandez-Pujals, A M; Gibson, J; Wigmore, E; Hafferty, J; Hagenaars, S P; Davies, G; Campbell, A; Hayward, C; Lawrie, S M; Porteous, D J; Deary, I J; McIntosh, A M

2016-11-01

Major depressive disorder (MDD) is known for its substantial clinical and suspected causal heterogeneity. It is characterized by low mood, psychomotor slowing and increased levels of the personality trait neuroticism; factors also associated with schizophrenia (SCZ). It is possible that some cases of MDD may have a substantial genetic loading for SCZ. The presence of SCZ-like MDD subgroups would be indicated by an interaction between MDD status and polygenic risk of SCZ on cognitive, personality and mood measures. Here, we hypothesized that higher SCZ polygenic risk would define larger MDD case-control differences in cognitive ability, and smaller differences in distress and neuroticism. Polygenic risk scores (PRSs) for SCZ and their association with cognitive variables, neuroticism, mood and psychological distress were estimated in a large population-based cohort (Generation Scotland: Scottish Family Health Study, GS:SFHS). The individuals were divided into those with, and without, depression (n=2587 and n=16 764, respectively) to test for the interactions between MDD status and schizophrenia risk. Replication was sought in UK Biobank (UKB; n=6049 and n=27 476 cases and controls, respectively). In both the cohorts, we found significant interactions between SCZ-PRS and MDD status for measures of psychological distress (β GS =-0.04, P GS =0.014 and β UKB =-0.09, P UKB ⩽0.001 for GS:SFHS and UKB, respectively) and neuroticism (β GS =-0.04, P GS =0.002 and β UKB =-0.06, P UKB =0.023). In both the cohorts, there was a reduction of case-control differences on a background of higher genetic risk of SCZ. These findings suggest that depression on a background of high genetic risk for SCZ may show attenuated associations with distress and neuroticism. This may represent a causally distinct form of MDD more closely related to SCZ.

Effect of IGF1, GH, and PIT1 markers on the genetic parameters of growth and reproduction traits in Canchim cattle.

PubMed

Grossi, Daniela do Amaral; Buzanskas, Marcos Eli; Grupioni, Natalia Vinhal; de Paz, Claudia Cristina Paro; Regitano, Luciana Correia de Almeida; de Alencar, Maurício Mello; Schenkel, Flávio Schramm; Munari, Danísio Prado

2015-01-01

The availability of dense genomic information has increased genome-wide association studies for the bovine species; however research to assess the effect of single genes on production traits is still important to elucidate the genes functions. On this study the association of IGF1, GH, and PIT1 markers with growth and reproductive traits (birth weight, weaning weight, weight at 12 and 18 months of age, preweaning average daily weight gain, age and weight at first calving, and scrotal circumference at 12 and 18 months of age) were assessed by means of the variance component approach. The phenotypes were adjusted and then analyzed under two animal models, one which considered the polygenic and genotype (IGF1, GH or PIT1 markers) effects (Model 1), and the other which considers only the polygenic effect (Model 2). When the likelihood ratio test and the Bonferroni correction was applied at 5 % significance level, the genetic markers for the IGF1, GH, and PIT1 genes did not influence significantly the traits (p > 0.002). However, evidence of association of IGF1 with birth weight (p = 0.06) and GH with weight at first calving (p = 0.03) and with weight at 12 months of age (p = 0.08) was observed. In conclusion we could not confirm the associations between IGF1, GH, and PIT1 and growth traits that were previously reported in Canchim cattle, and no association was observed between these genes and reproductive traits. Future studies involving functional markers of IGF1, GH and PIT1 genes may help to clarify the role of these genes in growth and reproductive processes.

Improving glucose tolerance by reducing weight gain in a polygenic obese mouse model: use of a high protein diet.

PubMed

Blair, A R; Strube, M L; Proietto, J; Andrikopoulos, S

2015-03-01

Diets to decrease body weight have limited success in achieving and importantly maintaining this weight loss long-term. It has recently been suggested that energy intake can be regulated by the amount of protein ingested, termed the protein leverage hypothesis. In this study, we determined whether a high protein diet would be effective in achieving and maintaining weight loss in a genetically obese model, the New Zealand Obese (NZO) mouse. NZO and C57BL/6J (C57) control mice were fed a high protein or chow diet for 5 weeks from weaning (3 weeks of age). Body weight and food intake were determined. Mice on the same diet were bred to produce offspring that were fed either a chow or high protein diet. Body weight, food intake, and glucose tolerance were determined. Feeding NZO and C57 mice a high protein diet for 5 weeks resulted in reduced food intake and consequently energy intake and body weight gain compared with mice on a chow diet. NZO mice fed a high protein diet showed a significant improvement in glucose tolerance compared with their chow-fed counterparts, while no difference was seen in C57 mice fed chow or protein diet. The offspring of NZO mice that were fed a high protein diet during gestation and weaning were also lighter and displayed improved glucose tolerance compared with chow fed animals. We conclude that a high protein diet is a reasonable strategy to reduce body weight gain and improve glucose tolerance in the NZO mouse, a polygenic model of obesity. © Georg Thieme Verlag KG Stuttgart · New York.

Child Maltreatment, Impulsivity, and Antisocial Behavior in African-American Children: Moderation Effects from a Cumulative Dopaminergic Gene Index

PubMed Central

Thibodeau, Eric L.; Cicchetti, Dante; Rogosch, Fred A.

2015-01-01

A model examining the effects of an increasing number of maltreatment subtypes experienced on antisocial behavior, as mediated by impulsivity and moderated by a polygenic index of dopaminergic genotypes, was investigated. An African American sample of children (N = 1012, M age = 10.07) with and without maltreatment histories participated. Indicators of aggression, delinquency, and disruptive peer behavior were obtained from peer and counselor rated measures to form a latent variable of antisocial behavior; impulsivity was assessed by counselor report. Five genotypes in four dopaminergic genes (DRD4, DRD2, DAT1, and COMT) conferring heightened environmental sensitivity were combined into one polygenic index. Using SEM, a first-stage, moderated-mediation model was evaluated. Age and sex were entered as covariates, both as main effects and in interaction with maltreatment and the gene index. The model had excellent fit: χ2(32, N =1012) = 86..51, p<0.001; CFI = 0.982; TLI = 0.977; RMSEA = 0.041; SRMR = 0.022. The effect of maltreatment subtypes on antisocial behavior was partially mediated by impulsivity (β= 0.173, p<0.001), and these relations were moderated by the number of differentiating dopaminergic genotypes. Specifically, a significant GxE interaction (b = 0.016, p = 0.013) indicated that the relation between maltreatment and impulsivity was stronger as children evinced more differentiating genotypes, thereby strengthening the mediational effect of impulsivity on antisocial behavior. These findings elucidate the manner by which maltreated children develop early signs of antisocial behavior, and the genetic mechanisms involved in greater vulnerability for maladaptation in impulse-control within context of child maltreatment. PMID:26535948

Browning of subcutaneous fat and higher surface temperature in response to phenotype selection for advanced endurance exercise performance in male DUhTP mice.

PubMed

Brenmoehl, J; Ohde, D; Albrecht, E; Walz, C; Tuchscherer, A; Hoeflich, A

2017-02-01

For the assessment of genetic or conditional factors of fat cell browning, novel and polygenic animal models are required. Therefore, the long-term selected polygenic mouse line DUhTP originally established in Dummerstorf for high treadmill performance is used. DUhTP mice are characterized by increased fat accumulation in the sedentary condition and elevated fat mobilization during mild voluntary physical activity. In the present study, the phenotype of fat cell browning of subcutaneous fat and a potential effect on oral glucose tolerance, an indicator of metabolic health, were addressed in DUhTP mice. Analysis of peripheral fat pads revealed increased brite (brown-in-white) subcutaneous adipose tissues and in subcutaneous fat from DUhTP mice higher levels of irisin and different markers of fat cell browning like T-box transcription factor (Tbx1), PPARα, and uncoupling protein (UCP1) (P < 0.05) when compared to unselected controls. UCP1 was further increased in subcutaneous fat from DUhTP mice in response to mild exercise (fourfold, P < 0.05). In addition, surface temperature of DUhTP mice was increased when compared to controls indicating a physiological effect of increased UCP1 expression. The present study suggests that DUhTP mice exhibit different markers of mitochondrial biogenesis and fat browning without external stimuli. At an age of 43 days, sedentary DUhTP mice have improved metabolic health as judged from lower levels of blood glucose after an oral glucose tolerance test. Consequently, the non-inbred mouse model DUhTP represents a novel model for the identification of fat cell browning mechanisms in white adipose tissues.

Polygenic risk score, genome-wide association, and gene set analyses of cognitive domain deficits in schizophrenia.

PubMed

Nakahara, Soichiro; Medland, Sarah; Turner, Jessica A; Calhoun, Vince D; Lim, Kelvin O; Mueller, Bryon A; Bustillo, Juan R; O'Leary, Daniel S; Vaidya, Jatin G; McEwen, Sarah; Voyvodic, James; Belger, Aysenil; Mathalon, Daniel H; Ford, Judith M; Guffanti, Guia; Macciardi, Fabio; Potkin, Steven G; van Erp, Theo G M

2018-06-12

This study assessed genetic contributions to six cognitive domains, identified by the MATRICS Cognitive Consensus Battery as relevant for schizophrenia, cognition-enhancing, clinical trials. Psychiatric Genomics Consortium Schizophrenia polygenic risk scores showed significant negative correlations with each cognitive domain. Genome-wide association analyses identified loci associated with attention/vigilance (rs830786 within HNF4G), verbal memory (rs67017972 near NDUFS4), and reasoning/problem solving (rs76872642 within HDAC9). Gene set analysis identified unique and shared genes across cognitive domains. These findings suggest involvement of common and unique mechanisms across cognitive domains and may contribute to the discovery of new therapeutic targets to treat cognitive deficits in schizophrenia. Copyright © 2018 Elsevier B.V. All rights reserved.

Common polygenic variation contributes to risk of schizophrenia that overlaps with bipolar disorder

PubMed Central

2013-01-01

Schizophrenia (SCZ) is a severe mental disorder with a lifetime risk of about 1%, characterized by hallucinations, delusions and cognitive deficits with heritability estimated at up to 80%1,2. We adopted two analytic approaches to determine the extent to which common genetic variation underlies risk of SCZ using genome-wide association study (GWAS) data from 3,322 European individuals with SCZ and 3,587 controls. First, we implicate the major histocompatibility complex (MHC). Second, we provide molecular genetic evidence for a substantial polygenic component to risk of SCZ involving thousands of common alleles of very small effect. We show that this component also contributes to risk of bipolar disorder (BPD), but not to multiple non-psychiatric diseases. PMID:19571811

Polygenic hazard scores in preclinical Alzheimer disease.

PubMed

Tan, Chin Hong; Hyman, Bradley T; Tan, Jacinth J X; Hess, Christopher P; Dillon, William P; Schellenberg, Gerard D; Besser, Lilah M; Kukull, Walter A; Kauppi, Karolina; McEvoy, Linda K; Andreassen, Ole A; Dale, Anders M; Fan, Chun Chieh; Desikan, Rahul S

2017-09-01

Identifying asymptomatic older individuals at elevated risk for developing Alzheimer disease (AD) is of clinical importance. Among 1,081 asymptomatic older adults, a recently validated polygenic hazard score (PHS) significantly predicted time to AD dementia and steeper longitudinal cognitive decline, even after controlling for APOE ɛ4 carrier status. Older individuals in the highest PHS percentiles showed the highest AD incidence rates. PHS predicted longitudinal clinical decline among older individuals with moderate to high Consortium to Establish a Registry for Alzheimer's Disease (amyloid) and Braak (tau) scores at autopsy, even among APOE ɛ4 noncarriers. Beyond APOE, PHS may help identify asymptomatic individuals at highest risk for developing Alzheimer neurodegeneration. Ann Neurol 2017;82:484-488. © 2017 American Neurological Association.

The genetic architecture of maize height.

PubMed

Peiffer, Jason A; Romay, Maria C; Gore, Michael A; Flint-Garcia, Sherry A; Zhang, Zhiwu; Millard, Mark J; Gardner, Candice A C; McMullen, Michael D; Holland, James B; Bradbury, Peter J; Buckler, Edward S

2014-04-01

Height is one of the most heritable and easily measured traits in maize (Zea mays L.). Given a pedigree or estimates of the genomic identity-by-state among related plants, height is also accurately predictable. But, mapping alleles explaining natural variation in maize height remains a formidable challenge. To address this challenge, we measured the plant height, ear height, flowering time, and node counts of plants grown in >64,500 plots across 13 environments. These plots contained >7300 inbreds representing most publically available maize inbreds in the United States and families of the maize Nested Association Mapping (NAM) panel. Joint-linkage mapping of quantitative trait loci (QTL), fine mapping in near isogenic lines (NILs), genome-wide association studies (GWAS), and genomic best linear unbiased prediction (GBLUP) were performed. The heritability of maize height was estimated to be >90%. Mapping NAM family-nested QTL revealed the largest explained 2.1 ± 0.9% of height variation. The effects of two tropical alleles at this QTL were independently validated by fine mapping in NIL families. Several significant associations found by GWAS colocalized with established height loci, including brassinosteroid-deficient dwarf1, dwarf plant1, and semi-dwarf2. GBLUP explained >80% of height variation in the panels and outperformed bootstrap aggregation of family-nested QTL models in evaluations of prediction accuracy. These results revealed maize height was under strong genetic control and had a highly polygenic genetic architecture. They also showed that multiple models of genetic architecture differing in polygenicity and effect sizes can plausibly explain a population's variation in maize height, but they may vary in predictive efficacy.

Bayesian inference of selection in a heterogeneous environment from genetic time-series data.

PubMed

Gompert, Zachariah

2016-01-01

Evolutionary geneticists have sought to characterize the causes and molecular targets of selection in natural populations for many years. Although this research programme has been somewhat successful, most statistical methods employed were designed to detect consistent, weak to moderate selection. In contrast, phenotypic studies in nature show that selection varies in time and that individual bouts of selection can be strong. Measurements of the genomic consequences of such fluctuating selection could help test and refine hypotheses concerning the causes of ecological specialization and the maintenance of genetic variation in populations. Herein, I proposed a Bayesian nonhomogeneous hidden Markov model to estimate effective population sizes and quantify variable selection in heterogeneous environments from genetic time-series data. The model is described and then evaluated using a series of simulated data, including cases where selection occurs on a trait with a simple or polygenic molecular basis. The proposed method accurately distinguished neutral loci from non-neutral loci under strong selection, but not from those under weak selection. Selection coefficients were accurately estimated when selection was constant or when the fitness values of genotypes varied linearly with the environment, but these estimates were less accurate when fitness was polygenic or the relationship between the environment and the fitness of genotypes was nonlinear. Past studies of temporal evolutionary dynamics in laboratory populations have been remarkably successful. The proposed method makes similar analyses of genetic time-series data from natural populations more feasible and thereby could help answer fundamental questions about the causes and consequences of evolution in the wild. © 2015 John Wiley & Sons Ltd.

Makeup of the genetic correlation between milk production traits using genome-wide single nucleotide polymorphism information.

PubMed

van Binsbergen, R; Veerkamp, R F; Calus, M P L

2012-04-01

The correlated responses between traits may differ depending on the makeup of genetic covariances, and may differ from the predictions of polygenic covariances. Therefore, the objective of the present study was to investigate the makeup of the genetic covariances between the well-studied traits: milk yield, fat yield, protein yield, and their percentages in more detail. Phenotypic records of 1,737 heifers of research farms in 4 different countries were used after homogenizing and adjusting for management effects. All cows had a genotype for 37,590 single nucleotide polymorphisms (SNP). A bayesian stochastic search variable selection model was used to estimate the SNP effects for each trait. About 0.5 to 1.0% of the SNP had a significant effect on 1 or more traits; however, the SNP without a significant effect explained most of the genetic variances and covariances of the traits. Single nucleotide polymorphism correlations differed from the polygenic correlations, but only 10 regions were found with an effect on multiple traits; in 1 of these regions the DGAT1 gene was previously reported with an effect on multiple traits. This region explained up to 41% of the variances of 4 traits and explained a major part of the correlation between fat yield and fat percentage and contributes to asymmetry in correlated response between fat yield and fat percentage. Overall, for the traits in this study, the infinitesimal model is expected to be sufficient for the estimation of the variances and covariances. Copyright © 2012 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Genetic risk of major depressive disorder: the moderating and mediating effects of neuroticism and psychological resilience on clinical and self-reported depression.

PubMed

Navrady, L B; Adams, M J; Chan, S W Y; Ritchie, S J; McIntosh, A M

2017-11-29

Polygenic risk scores (PRS) for depression correlate with depression status and chronicity, and provide causal anchors to identify depressive mechanisms. Neuroticism is phenotypically and genetically positively associated with depression, whereas psychological resilience demonstrates negative phenotypic associations. Whether increased neuroticism and reduced resilience are downstream mediators of genetic risk for depression, and whether they contribute independently to risk remains unknown. Moderating and mediating relationships between depression PRS, neuroticism, resilience and both clinical and self-reported depression were examined in a large, population-based cohort, Generation Scotland: Scottish Family Health Study (N = 4166), using linear regression and structural equation modelling. Neuroticism and resilience were measured by the Eysenck Personality Scale Short Form Revised and the Brief Resilience Scale, respectively. PRS for depression was associated with increased likelihood of self-reported and clinical depression. No interaction was found between PRS and neuroticism, or between PRS and resilience. Neuroticism was associated with increased likelihood of self-reported and clinical depression, whereas resilience was associated with reduced risk. Structural equation modelling suggested the association between PRS and self-reported and clinical depression was mediated by neuroticism (43-57%), while resilience mediated the association in the opposite direction (37-40%). For both self-reported and clinical diagnoses, the genetic risk for depression was independently mediated by neuroticism and resilience. Findings suggest polygenic risk for depression increases vulnerability for self-reported and clinical depression through independent effects on increased neuroticism and reduced psychological resilience. In addition, two partially independent mechanisms - neuroticism and resilience - may form part of the pathway of vulnerability to depression.

Multiethnic GWAS Reveals Polygenic Architecture of Earlobe Attachment.

PubMed

Shaffer, John R; Li, Jinxi; Lee, Myoung Keun; Roosenboom, Jasmien; Orlova, Ekaterina; Adhikari, Kaustabh; Gallo, Carla; Poletti, Giovanni; Schuler-Faccini, Lavinia; Bortolini, Maria-Cátira; Canizales-Quinteros, Samuel; Rothhammer, Francisco; Bedoya, Gabriel; González-José, Rolando; Pfeffer, Paige E; Wollenschlaeger, Christopher A; Hecht, Jacqueline T; Wehby, George L; Moreno, Lina M; Ding, Anan; Jin, Li; Yang, Yajun; Carlson, Jenna C; Leslie, Elizabeth J; Feingold, Eleanor; Marazita, Mary L; Hinds, David A; Cox, Timothy C; Wang, Sijia; Ruiz-Linares, Andrés; Weinberg, Seth M

2017-12-07

The genetic basis of earlobe attachment has been a matter of debate since the early 20 th century, such that geneticists argue both for and against polygenic inheritance. Recent genetic studies have identified a few loci associated with the trait, but large-scale analyses are still lacking. Here, we performed a genome-wide association study of lobe attachment in a multiethnic sample of 74,660 individuals from four cohorts (three with the trait scored by an expert rater and one with the trait self-reported). Meta-analysis of the three expert-rater-scored cohorts revealed six associated loci harboring numerous candidate genes, including EDAR, SP5, MRPS22, ADGRG6 (GPR126), KIAA1217, and PAX9. The large self-reported 23andMe cohort recapitulated each of these six loci. Moreover, meta-analysis across all four cohorts revealed a total of 49 significant (p < 5 × 10 -8 ) loci. Annotation and enrichment analyses of these 49 loci showed strong evidence of genes involved in ear development and syndromes with auricular phenotypes. RNA sequencing data from both human fetal ear and mouse second branchial arch tissue confirmed that genes located among associated loci showed evidence of expression. These results provide strong evidence for the polygenic nature of earlobe attachment and offer insights into the biological basis of normal and abnormal ear development. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

Modelling clinical systemic lupus erythematosus: similarities, differences and success stories

PubMed Central

Celhar, Teja

2017-01-01

Abstract Mouse models of SLE have been indispensable tools to study disease pathogenesis, to identify genetic susceptibility loci and targets for drug development, and for preclinical testing of novel therapeutics. Recent insights into immunological mechanisms of disease progression have boosted a revival in SLE drug development. Despite promising results in mouse studies, many novel drugs have failed to meet clinical end points. This is probably because of the complexity of the disease, which is driven by polygenic predisposition and diverse environmental factors, resulting in a heterogeneous clinical presentation. Each mouse model recapitulates limited aspects of lupus, especially in terms of the mechanism underlying disease progression. The main mouse models have been fairly successful for the evaluation of broad-acting immunosuppressants. However, the advent of targeted therapeutics calls for a selection of the most appropriate model(s) for testing and, ultimately, identification of patients who will be most likely to respond. PMID:28013204

Six low-penetrance SNPs for the estimation of breast cancer heritability: A family-based study in Caucasian Italian patients

PubMed Central

De Summa, Simona; Graziano, Francesca; Pilato, Brunella; Pinto, Rosamaria; Danza, Katia; Lacalamita, Rosanna; Serratì, Simona; Sambiasi, Domenico; Grassi, Mario; Tommasi, Stefania

2017-01-01

Breast cancer is a malignancy with a strong heritable component. Genetic counseling has been principally focused on families carrying high-penetrance breast cancer 1/2, early onset genes. Current modeling suggests that the majority of the unexplained fraction of familial risk is likely to be explained by a polygenic model. The aim of the present study was to estimate the heritability (h2) of breast cancer susceptibility through the analysis of 6 single nucleotide polymorphisms (SNPs), nuclear mitotic apparatus protein 1, cyclin D1, cytochrome C oxidase copper chaperone, fibroblast growth factor receptor 2, TOX high mobility group box family member 3 and solute carrier family 4 member 7. These 6 SNPs, previously identified by genome-wide association studies, were considered to evaluate the additive and common environmental components that contribute to the development of breast cancer in nuclear (pedigrees including only first degree relationships) and in extended families (with at most third degree relationships). A total of 22 extended pedigrees, subsequently split into 52 nuclear pedigrees were analyzed. An example of splitting process from extended to nuclear pedigree is shown in Fig. 1. Firstly, an underline latent continuous trait (Y*) using breast cancer status and information of 6 breast cancer-associated SNPs was calculated. This novel trait summarized the susceptibility of breast cancer in each individual. Secondly, the h2 of Y* was estimated using an additive polygenic-common environment-unique error model. h2 was evaluated in extended and immediate pedigrees, obtaining comparable results. h2 accounts for ~40% of the total phenotypic variance, indicating a fairly strong additive genetic effect of breast cancer susceptibility. The present study indicated the importance of the evaluation and consideration of these six SNPs, which can be used as instrumental variables in order to obtain improved genetic models that are useful for h2 analysis. PMID:28943953

Evaluation of polygenic risk scores for predicting breast and prostate cancer risk.

PubMed

Machiela, Mitchell J; Chen, Chia-Yen; Chen, Constance; Chanock, Stephen J; Hunter, David J; Kraft, Peter

2011-09-01

Recently, polygenic risk scores (PRS) have been shown to be associated with certain complex diseases. The approach has been based on the contribution of counting multiple alleles associated with disease across independent loci, without requiring compelling evidence that every locus had already achieved definitive genome-wide statistical significance. Whether PRS assist in the prediction of risk of common cancers is unknown. We built PRS from lists of genetic markers prioritized by their association with breast cancer (BCa) or prostate cancer (PCa) in a training data set and evaluated whether these scores could improve current genetic prediction of these specific cancers in independent test samples. We used genome-wide association data on 1,145 BCa cases and 1,142 controls from the Nurses' Health Study and 1,164 PCa cases and 1,113 controls from the Prostate Lung Colorectal and Ovarian Cancer Screening Trial. Ten-fold cross validation was used to build and evaluate PRS with 10 to 60,000 independent single nucleotide polymorphisms (SNPs). For both BCa and PCa, the models that included only published risk alleles maximized the cross-validation estimate of the area under the ROC curve (0.53 for breast and 0.57 for prostate). We found no significant evidence that PRS using common variants improved risk prediction for BCa and PCa over replicated SNP scores. © 2011 Wiley-Liss, Inc.

Shared genetic basis for migraine and ischemic stroke

PubMed Central

Malik, Rainer; Freilinger, Tobias; Winsvold, Bendik S.; Anttila, Verneri; Vander Heiden, Jason; Traylor, Matthew; de Vries, Boukje; Holliday, Elizabeth G.; Terwindt, Gisela M.; Sturm, Jonathan; Bis, Joshua C.; Hopewell, Jemma C.; Ferrari, Michel D.; Rannikmae, Kristiina; Wessman, Maija; Kallela, Mikko; Kubisch, Christian; Fornage, Myriam; Meschia, James F.; Lehtimäki, Terho; Sudlow, Cathie; Clarke, Robert; Chasman, Daniel I.; Mitchell, Braxton D.; Maguire, Jane; Kaprio, Jaakko; Farrall, Martin; Raitakari, Olli T.; Kurth, Tobias; Ikram, M. Arfan; Reiner, Alex P.; Longstreth, W.T.; Rothwell, Peter M.; Strachan, David P.; Sharma, Pankaj; Seshadri, Sudha; Quaye, Lydia; Cherkas, Lynn; Schürks, Markus; Rosand, Jonathan; Ligthart, Lannie; Boncoraglio, Giorgio B.; Davey Smith, George; van Duijn, Cornelia M.; Stefansson, Kari; Worrall, Bradford B.; Nyholt, Dale R.; Markus, Hugh S.; van den Maagdenberg, Arn M.J.M.; Cotsapas, Chris; Zwart, John A.; Palotie, Aarno

2015-01-01

Objective: To quantify genetic overlap between migraine and ischemic stroke (IS) with respect to common genetic variation. Methods: We applied 4 different approaches to large-scale meta-analyses of genome-wide data on migraine (23,285 cases and 95,425 controls) and IS (12,389 cases and 62,004 controls). First, we queried known genome-wide significant loci for both disorders, looking for potential overlap of signals. We then analyzed the overall shared genetic load using polygenic scores and estimated the genetic correlation between disease subtypes using data derived from these models. We further interrogated genomic regions of shared risk using analysis of covariance patterns between the 2 phenotypes using cross-phenotype spatial mapping. Results: We found substantial genetic overlap between migraine and IS using all 4 approaches. Migraine without aura (MO) showed much stronger overlap with IS and its subtypes than migraine with aura (MA). The strongest overlap existed between MO and large artery stroke (LAS; p = 6.4 × 10−28 for the LAS polygenic score in MO) and between MO and cardioembolic stroke (CE; p = 2.7 × 10−20 for the CE score in MO). Conclusions: Our findings indicate shared genetic susceptibility to migraine and IS, with a particularly strong overlap between MO and both LAS and CE pointing towards shared mechanisms. Our observations on MA are consistent with a limited role of common genetic variants in this subtype. PMID:25934857

Polygenic Risk Score Identifies Subgroup With Higher Burden of Atherosclerosis and Greater Relative Benefit From Statin Therapy in the Primary Prevention Setting.

PubMed

Natarajan, Pradeep; Young, Robin; Stitziel, Nathan O; Padmanabhan, Sandosh; Baber, Usman; Mehran, Roxana; Sartori, Samantha; Fuster, Valentin; Reilly, Dermot F; Butterworth, Adam; Rader, Daniel J; Ford, Ian; Sattar, Naveed; Kathiresan, Sekar

2017-05-30

Relative risk reduction with statin therapy has been consistent across nearly all subgroups studied to date. However, in analyses of 2 randomized controlled primary prevention trials (ASCOT [Anglo-Scandinavian Cardiac Outcomes Trial-Lipid-Lowering Arm] and JUPITER [Justification for the Use of Statins in Prevention: An Intervention Trial Evaluating Rosuvastatin]), statin therapy led to a greater relative risk reduction among a subgroup at high genetic risk. Here, we aimed to confirm this observation in a third primary prevention randomized controlled trial. In addition, we assessed whether those at high genetic risk had a greater burden of subclinical coronary atherosclerosis. We studied participants from a randomized controlled trial of primary prevention with statin therapy (WOSCOPS [West of Scotland Coronary Prevention Study]; n=4910) and 2 observational cohort studies (CARDIA [Coronary Artery Risk Development in Young Adults] and BioImage; n=1154 and 4392, respectively). For each participant, we calculated a polygenic risk score derived from up to 57 common DNA sequence variants previously associated with coronary heart disease. We compared the relative efficacy of statin therapy in those at high genetic risk (top quintile of polygenic risk score) versus all others (WOSCOPS), as well as the association between the polygenic risk score and coronary artery calcification (CARDIA) and carotid artery plaque burden (BioImage). Among WOSCOPS trial participants at high genetic risk, statin therapy was associated with a relative risk reduction of 44% (95% confidence interval [CI], 22-60; P <0.001), whereas in all others, the relative risk reduction was 24% (95% CI, 8-37; P =0.004) despite similar low-density lipoprotein cholesterol lowering. In a study-level meta-analysis across the WOSCOPS, ASCOT, and JUPITER primary prevention, relative risk reduction in those at high genetic risk was 46% versus 26% in all others ( P for heterogeneity=0.05). Across all 3 studies, the absolute risk reduction with statin therapy was 3.6% (95% CI, 2.0-5.1) among those in the high genetic risk group and 1.3% (95% CI, 0.6-1.9) in all others. Each 1-SD increase in the polygenic risk score was associated with 1.32-fold (95% CI, 1.04-1.68) greater likelihood of having coronary artery calcification and 9.7% higher (95% CI, 2.2-17.8) burden of carotid plaque. Those at high genetic risk have a greater burden of subclinical atherosclerosis and derive greater relative and absolute benefit from statin therapy to prevent a first coronary heart disease event. URL: http://www.clinicaltrials.gov. Unique identifiers: NCT00738725 (BioImage) and NCT00005130 (CARDIA). WOSCOPS was carried out and completed before the requirement for clinical trial registration. © 2017 American Heart Association, Inc.

Wild worm embryogenesis harbors ubiquitous polygenic modifier variation.

PubMed

Paaby, Annalise B; White, Amelia G; Riccardi, David D; Gunsalus, Kristin C; Piano, Fabio; Rockman, Matthew V

2015-08-22

Embryogenesis is an essential and stereotypic process that nevertheless evolves among species. Its essentiality may favor the accumulation of cryptic genetic variation (CGV) that has no effect in the wild-type but that enhances or suppresses the effects of rare disruptions to gene function. Here, we adapted a classical modifier screen to interrogate the alleles segregating in natural populations of Caenorhabditis elegans: we induced gene knockdowns and used quantitative genetic methodology to examine how segregating variants modify the penetrance of embryonic lethality. Each perturbation revealed CGV, indicating that wild-type genomes harbor myriad genetic modifiers that may have little effect individually but which in aggregate can dramatically influence penetrance. Phenotypes were mediated by many modifiers, indicating high polygenicity, but the alleles tend to act very specifically, indicating low pleiotropy. Our findings demonstrate the extent of conditional functionality in complex trait architecture.

Monogenic autoimmune diseases of the endocrine system.

PubMed

Johnson, Matthew B; Hattersley, Andrew T; Flanagan, Sarah E

2016-10-01

The most common endocrine diseases, type 1 diabetes, hyperthyroidism, and hypothyroidism, are the result of autoimmunity. Clustering of autoimmune endocrinopathies can result from polygenic predisposition, or more rarely, may present as part of a wider syndrome due to a mutation within one of seven genes. These monogenic autoimmune diseases show highly variable phenotypes both within and between families with the same mutations. The average age of onset of the monogenic forms of autoimmune endocrine disease is younger than that of the common polygenic forms, and this feature combined with the manifestation of other autoimmune diseases, specific hallmark features, or both, can inform clinicians as to the relevance of genetic testing. A genetic diagnosis can guide medical management, give an insight into prognosis, inform families of recurrence risk, and facilitate prenatal diagnoses. Copyright © 2016 Elsevier Ltd. All rights reserved.

Genetic loci associated with coronary artery disease harbor evidence of selection and antagonistic pleiotropy.

PubMed

Byars, Sean G; Huang, Qin Qin; Gray, Lesley-Ann; Bakshi, Andrew; Ripatti, Samuli; Abraham, Gad; Stearns, Stephen C; Inouye, Michael

2017-06-01

Traditional genome-wide scans for positive selection have mainly uncovered selective sweeps associated with monogenic traits. While selection on quantitative traits is much more common, very few signals have been detected because of their polygenic nature. We searched for positive selection signals underlying coronary artery disease (CAD) in worldwide populations, using novel approaches to quantify relationships between polygenic selection signals and CAD genetic risk. We identified new candidate adaptive loci that appear to have been directly modified by disease pressures given their significant associations with CAD genetic risk. These candidates were all uniquely and consistently associated with many different male and female reproductive traits suggesting selection may have also targeted these because of their direct effects on fitness. We found that CAD loci are significantly enriched for lifetime reproductive success relative to the rest of the human genome, with evidence that the relationship between CAD and lifetime reproductive success is antagonistic. This supports the presence of antagonistic-pleiotropic tradeoffs on CAD loci and provides a novel explanation for the maintenance and high prevalence of CAD in modern humans. Lastly, we found that positive selection more often targeted CAD gene regulatory variants using HapMap3 lymphoblastoid cell lines, which further highlights the unique biological significance of candidate adaptive loci underlying CAD. Our study provides a novel approach for detecting selection on polygenic traits and evidence that modern human genomes have evolved in response to CAD-induced selection pressures and other early-life traits sharing pleiotropic links with CAD.

Polygenicity and Epistasis Underlie Fitness-Proximal Traits in the Caenorhabditis elegans Multiparental Experimental Evolution (CeMEE) Panel.

PubMed

Noble, Luke M; Chelo, Ivo; Guzella, Thiago; Afonso, Bruno; Riccardi, David D; Ammerman, Patrick; Dayarian, Adel; Carvalho, Sara; Crist, Anna; Pino-Querido, Ania; Shraiman, Boris; Rockman, Matthew V; Teotónio, Henrique

2017-12-01

Understanding the genetic basis of complex traits remains a major challenge in biology. Polygenicity, phenotypic plasticity, and epistasis contribute to phenotypic variance in ways that are rarely clear. This uncertainty can be problematic for estimating heritability, for predicting individual phenotypes from genomic data, and for parameterizing models of phenotypic evolution. Here, we report an advanced recombinant inbred line (RIL) quantitative trait locus mapping panel for the hermaphroditic nematode Caenorhabditis elegans , the C. elegans multiparental experimental evolution (CeMEE) panel. The CeMEE panel, comprising 507 RILs at present, was created by hybridization of 16 wild isolates, experimental evolution for 140-190 generations, and inbreeding by selfing for 13-16 generations. The panel contains 22% of single-nucleotide polymorphisms known to segregate in natural populations, and complements existing C. elegans mapping resources by providing fine resolution and high nucleotide diversity across > 95% of the genome. We apply it to study the genetic basis of two fitness components, fertility and hermaphrodite body size at time of reproduction, with high broad-sense heritability in the CeMEE. While simulations show that we should detect common alleles with additive effects as small as 5%, at gene-level resolution, the genetic architectures of these traits do not feature such alleles. We instead find that a significant fraction of trait variance, approaching 40% for fertility, can be explained by sign epistasis with main effects below the detection limit. In congruence, phenotype prediction from genomic similarity, while generally poor ([Formula: see text]), requires modeling epistasis for optimal accuracy, with most variance attributed to the rapidly evolving chromosome arms. Copyright © 2017 by the Genetics Society of America.

Polygenicity and Epistasis Underlie Fitness-Proximal Traits in the Caenorhabditis elegans Multiparental Experimental Evolution (CeMEE) Panel

PubMed Central

Noble, Luke M.; Chelo, Ivo; Guzella, Thiago; Afonso, Bruno; Riccardi, David D.; Ammerman, Patrick; Dayarian, Adel; Carvalho, Sara; Crist, Anna; Pino-Querido, Ania; Shraiman, Boris; Rockman, Matthew V.; Teotónio, Henrique

2017-01-01

Understanding the genetic basis of complex traits remains a major challenge in biology. Polygenicity, phenotypic plasticity, and epistasis contribute to phenotypic variance in ways that are rarely clear. This uncertainty can be problematic for estimating heritability, for predicting individual phenotypes from genomic data, and for parameterizing models of phenotypic evolution. Here, we report an advanced recombinant inbred line (RIL) quantitative trait locus mapping panel for the hermaphroditic nematode Caenorhabditis elegans, the C. elegans multiparental experimental evolution (CeMEE) panel. The CeMEE panel, comprising 507 RILs at present, was created by hybridization of 16 wild isolates, experimental evolution for 140–190 generations, and inbreeding by selfing for 13–16 generations. The panel contains 22% of single-nucleotide polymorphisms known to segregate in natural populations, and complements existing C. elegans mapping resources by providing fine resolution and high nucleotide diversity across > 95% of the genome. We apply it to study the genetic basis of two fitness components, fertility and hermaphrodite body size at time of reproduction, with high broad-sense heritability in the CeMEE. While simulations show that we should detect common alleles with additive effects as small as 5%, at gene-level resolution, the genetic architectures of these traits do not feature such alleles. We instead find that a significant fraction of trait variance, approaching 40% for fertility, can be explained by sign epistasis with main effects below the detection limit. In congruence, phenotype prediction from genomic similarity, while generally poor (r2<10%), requires modeling epistasis for optimal accuracy, with most variance attributed to the rapidly evolving chromosome arms. PMID:29066469

Genotype-driven identification of a molecular network predictive of advanced coronary calcium in ClinSeq® and Framingham Heart Study cohorts.

PubMed

Oguz, Cihan; Sen, Shurjo K; Davis, Adam R; Fu, Yi-Ping; O'Donnell, Christopher J; Gibbons, Gary H

2017-10-26

One goal of personalized medicine is leveraging the emerging tools of data science to guide medical decision-making. Achieving this using disparate data sources is most daunting for polygenic traits. To this end, we employed random forests (RFs) and neural networks (NNs) for predictive modeling of coronary artery calcium (CAC), which is an intermediate endo-phenotype of coronary artery disease (CAD). Model inputs were derived from advanced cases in the ClinSeq®; discovery cohort (n=16) and the FHS replication cohort (n=36) from 89 th -99 th CAC score percentile range, and age-matched controls (ClinSeq®; n=16, FHS n=36) with no detectable CAC (all subjects were Caucasian males). These inputs included clinical variables and genotypes of 56 single nucleotide polymorphisms (SNPs) ranked highest in terms of their nominal correlation with the advanced CAC state in the discovery cohort. Predictive performance was assessed by computing the areas under receiver operating characteristic curves (ROC-AUC). RF models trained and tested with clinical variables generated ROC-AUC values of 0.69 and 0.61 in the discovery and replication cohorts, respectively. In contrast, in both cohorts, the set of SNPs derived from the discovery cohort were highly predictive (ROC-AUC ≥0.85) with no significant change in predictive performance upon integration of clinical and genotype variables. Using the 21 SNPs that produced optimal predictive performance in both cohorts, we developed NN models trained with ClinSeq®; data and tested with FHS data and obtained high predictive accuracy (ROC-AUC=0.80-0.85) with several topologies. Several CAD and "vascular aging" related biological processes were enriched in the network of genes constructed from the predictive SNPs. We identified a molecular network predictive of advanced coronary calcium using genotype data from ClinSeq®; and FHS cohorts. Our results illustrate that machine learning tools, which utilize complex interactions between disease predictors intrinsic to the pathogenesis of polygenic disorders, hold promise for deriving predictive disease models and networks.

Nonlinear threshold effect in the Z-scan method of characterizing limiters for high-intensity laser light

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tereshchenko, S. A., E-mail: tsa@miee.ru; Savelyev, M. S.; Podgaetsky, V. M.

A threshold model is described which permits one to determine the properties of limiters for high-powered laser light. It takes into account the threshold characteristics of the nonlinear optical interaction between the laser beam and the limiter working material. The traditional non-threshold model is a particular case of the threshold model when the limiting threshold is zero. The nonlinear characteristics of carbon nanotubes in liquid and solid media are obtained from experimental Z-scan data. Specifically, the nonlinear threshold effect was observed for aqueous dispersions of nanotubes, but not for nanotubes in solid polymethylmethacrylate. The threshold model fits the experimental Z-scanmore » data better than the non-threshold model. Output characteristics were obtained that integrally describe the nonlinear properties of the optical limiters.« less

Comparison of multipoint linkage analyses for quantitative traits in the CEPH data: parametric LOD scores, variance components LOD scores, and Bayes factors.

PubMed

Sung, Yun Ju; Di, Yanming; Fu, Audrey Q; Rothstein, Joseph H; Sieh, Weiva; Tong, Liping; Thompson, Elizabeth A; Wijsman, Ellen M

2007-01-01

We performed multipoint linkage analyses with multiple programs and models for several gene expression traits in the Centre d'Etude du Polymorphisme Humain families. All analyses provided consistent results for both peak location and shape. Variance-components (VC) analysis gave wider peaks and Bayes factors gave fewer peaks. Among programs from the MORGAN package, lm_multiple performed better than lm_markers, resulting in less Markov-chain Monte Carlo (MCMC) variability between runs, and the program lm_twoqtl provided higher LOD scores by also including either a polygenic component or an additional quantitative trait locus.

Comparison of multipoint linkage analyses for quantitative traits in the CEPH data: parametric LOD scores, variance components LOD scores, and Bayes factors

PubMed Central

Sung, Yun Ju; Di, Yanming; Fu, Audrey Q; Rothstein, Joseph H; Sieh, Weiva; Tong, Liping; Thompson, Elizabeth A; Wijsman, Ellen M

2007-01-01

We performed multipoint linkage analyses with multiple programs and models for several gene expression traits in the Centre d'Etude du Polymorphisme Humain families. All analyses provided consistent results for both peak location and shape. Variance-components (VC) analysis gave wider peaks and Bayes factors gave fewer peaks. Among programs from the MORGAN package, lm_multiple performed better than lm_markers, resulting in less Markov-chain Monte Carlo (MCMC) variability between runs, and the program lm_twoqtl provided higher LOD scores by also including either a polygenic component or an additional quantitative trait locus. PMID:18466597

Investigation of the pathogenesis of autoimmune diseases by iPS cells.

PubMed

Natsumoto, Bunki; Shoda, Hirofumi; Fujio, Keishi; Otsu, Makoto; Yamamoto, Kazuhiko

2017-01-01

The pluripotent stem cells have a self-renewal ability and can be differentiated into theoretically all of cell types. The induced pluripotent stem (iPS) cells overcame the ethical problems of the human embryonic stem (ES) cell, and enable pathologic analysis of intractable diseases and drug discovery. The in vitro disease model using disease-specific iPS cells enables repeated analyses of human cells without influence of environment factors. Even though autoimmune diseases are polygenic diseases, autoimmune disease-specific iPS cells are thought to be a promising tool for analyzing the pathogenesis of the diseases and drug discovery in future.

Telomere length and genetics are independent colorectal tumour risk factors in an evaluation of biomarkers in normal bowel.

PubMed

Fernandez-Rozadilla, Ceres; Kartsonaki, Christiana; Woolley, Connor; McClellan, Michael; Whittington, Deb; Horgan, Gareth; Leedham, Simon; Kriaucionis, Skirmantas; East, James; Tomlinson, Ian

2018-03-06

Colorectal cancer (CRC) screening might be improved by using a measure of prior risk to modulate screening intensity or the faecal immunochemical test threshold. Intermediate molecular biomarkers could aid risk prediction by capturing both known and unknown risk factors. We sampled normal bowel mucosa from the proximal colon, distal colon and rectum of 317 individuals undergoing colonoscopy. We defined cases as having a personal history of colorectal polyp(s)/cancer, and controls as having no history of colorectal neoplasia. Molecular analyses were performed for: telomere length (TL); global methylation; and the expression of genes in molecular pathways associated with colorectal tumourigenesis. We also calculated a polygenic risk score (PRS) based on CRC susceptibility polymorphisms. Bowel TL was significantly longer in cases than controls, but was not associated with blood TL. PRS was significantly and independently higher in cases. Hypermethylation showed a suggestive association with case:control status. No gene or pathway was differentially expressed between cases and controls. Gene expression often varied considerably between bowel locations. PRS and bowel TL (but not blood TL) may be clinically-useful predictors of CRC risk. Sample collection to assess these biomarkers is feasible in clinical practice, especially where population screening uses flexible sigmoidoscopy or colonoscopy.

Shared genetic basis for migraine and ischemic stroke: A genome-wide analysis of common variants.

PubMed

Malik, Rainer; Freilinger, Tobias; Winsvold, Bendik S; Anttila, Verneri; Vander Heiden, Jason; Traylor, Matthew; de Vries, Boukje; Holliday, Elizabeth G; Terwindt, Gisela M; Sturm, Jonathan; Bis, Joshua C; Hopewell, Jemma C; Ferrari, Michel D; Rannikmae, Kristiina; Wessman, Maija; Kallela, Mikko; Kubisch, Christian; Fornage, Myriam; Meschia, James F; Lehtimäki, Terho; Sudlow, Cathie; Clarke, Robert; Chasman, Daniel I; Mitchell, Braxton D; Maguire, Jane; Kaprio, Jaakko; Farrall, Martin; Raitakari, Olli T; Kurth, Tobias; Ikram, M Arfan; Reiner, Alex P; Longstreth, W T; Rothwell, Peter M; Strachan, David P; Sharma, Pankaj; Seshadri, Sudha; Quaye, Lydia; Cherkas, Lynn; Schürks, Markus; Rosand, Jonathan; Ligthart, Lannie; Boncoraglio, Giorgio B; Davey Smith, George; van Duijn, Cornelia M; Stefansson, Kari; Worrall, Bradford B; Nyholt, Dale R; Markus, Hugh S; van den Maagdenberg, Arn M J M; Cotsapas, Chris; Zwart, John A; Palotie, Aarno; Dichgans, Martin

2015-05-26

To quantify genetic overlap between migraine and ischemic stroke (IS) with respect to common genetic variation. We applied 4 different approaches to large-scale meta-analyses of genome-wide data on migraine (23,285 cases and 95,425 controls) and IS (12,389 cases and 62,004 controls). First, we queried known genome-wide significant loci for both disorders, looking for potential overlap of signals. We then analyzed the overall shared genetic load using polygenic scores and estimated the genetic correlation between disease subtypes using data derived from these models. We further interrogated genomic regions of shared risk using analysis of covariance patterns between the 2 phenotypes using cross-phenotype spatial mapping. We found substantial genetic overlap between migraine and IS using all 4 approaches. Migraine without aura (MO) showed much stronger overlap with IS and its subtypes than migraine with aura (MA). The strongest overlap existed between MO and large artery stroke (LAS; p = 6.4 × 10(-28) for the LAS polygenic score in MO) and between MO and cardioembolic stroke (CE; p = 2.7 × 10(-20) for the CE score in MO). Our findings indicate shared genetic susceptibility to migraine and IS, with a particularly strong overlap between MO and both LAS and CE pointing towards shared mechanisms. Our observations on MA are consistent with a limited role of common genetic variants in this subtype. © 2015 American Academy of Neurology.

Bad Science and Its Social Implications.

ERIC Educational Resources Information Center

Zeidler, Dana L.; Sadler, Troy D.; Berson, Michael J.; Fogelman, Aimee L.

2002-01-01

Investigates three types of bad science: (1) cultural prejudice based on scientific errors (polygenism, phrenology, reification through intelligence testing); (2) unethical science (Tuskegee syphilis experiments, tobacco companies and research); and (3) unwitting errors (pesticides, chlorofluorocarbons). (Contains 50 references.) (SK)

Wild worm embryogenesis harbors ubiquitous polygenic modifier variation

PubMed Central

Paaby, Annalise B; White, Amelia G; Riccardi, David D; Gunsalus, Kristin C; Piano, Fabio; Rockman, Matthew V

2015-01-01

Embryogenesis is an essential and stereotypic process that nevertheless evolves among species. Its essentiality may favor the accumulation of cryptic genetic variation (CGV) that has no effect in the wild-type but that enhances or suppresses the effects of rare disruptions to gene function. Here, we adapted a classical modifier screen to interrogate the alleles segregating in natural populations of Caenorhabditis elegans: we induced gene knockdowns and used quantitative genetic methodology to examine how segregating variants modify the penetrance of embryonic lethality. Each perturbation revealed CGV, indicating that wild-type genomes harbor myriad genetic modifiers that may have little effect individually but which in aggregate can dramatically influence penetrance. Phenotypes were mediated by many modifiers, indicating high polygenicity, but the alleles tend to act very specifically, indicating low pleiotropy. Our findings demonstrate the extent of conditional functionality in complex trait architecture. DOI: http://dx.doi.org/10.7554/eLife.09178.001 PMID:26297805

A polygenic burden of rare disruptive mutations in schizophrenia

PubMed Central

Purcell, Shaun M.; Moran, Jennifer L.; Fromer, Menachem; Ruderfer, Douglas; Solovieff, Nadia; Roussos, Panos; O’Dushlaine, Colm; Chambert, Kimberly; Bergen, Sarah E.; Kähler, Anna; Duncan, Laramie; Stahl, Eli; Genovese, Giulio; Fernández, Esperanza; Collins, Mark O; Komiyama, Noboru H.; Choudhary, Jyoti S.; Magnusson, Patrik K. E.; Banks, Eric; Shakir, Khalid; Garimella, Kiran; Fennell, Tim; de Pristo, Mark; Grant, Seth G.N.; Haggarty, Stephen; Gabriel, Stacey; Scolnick, Edward M.; Lander, Eric S.; Hultman, Christina; Sullivan, Patrick F.; McCarroll, Steven A.; Sklar, Pamela

2014-01-01

By analyzing the exome sequences of 2,536 schizophrenia cases and 2,543 controls, we have demonstrated a polygenic burden primarily arising from rare (<1/10,000), disruptive mutations distributed across many genes. Especially enriched genesets included the voltage-gated calcium ion channel and the signaling complex formed by the activity-regulated cytoskeleton-associated (ARC) scaffold protein of the postsynaptic density (PSD), sets previously implicated by genome-wide association studies (GWAS) and copy-number variation (CNV) studies. Similar to reports in autism, targets of the fragile × mental retardation protein (FMRP, product of FMR1) were enriched for case mutations. No individual gene-based test achieved significance after correction for multiple testing and we did not detect any alleles of moderately low frequency (~0.5-1%) and moderately large effect. Taken together, these data suggest that population-based exome sequencing can discover risk alleles and complements established gene mapping paradigms in neuropsychiatric disease. PMID:24463508

Intelligence: shared genetic basis between Mendelian disorders and a polygenic trait.

PubMed

Franić, Sanja; Groen-Blokhuis, Maria M; Dolan, Conor V; Kattenberg, Mathijs V; Pool, René; Xiao, Xiangjun; Scheet, Paul A; Ehli, Erik A; Davies, Gareth E; van der Sluis, Sophie; Abdellaoui, Abdel; Hansell, Narelle K; Martin, Nicholas G; Hudziak, James J; van Beijsterveldt, Catherina E M; Swagerman, Suzanne C; Hulshoff Pol, Hilleke E; de Geus, Eco J C; Bartels, Meike; Ropers, H Hilger; Hottenga, Jouke-Jan; Boomsma, Dorret I

2015-10-01

Multiple inquiries into the genetic etiology of human traits indicated an overlap between genes underlying monogenic disorders (eg, skeletal growth defects) and those affecting continuous variability of related quantitative traits (eg, height). Extending the idea of a shared genetic basis between a Mendelian disorder and a classic polygenic trait, we performed an association study to examine the effect of 43 genes implicated in autosomal recessive cognitive disorders on intelligence in an unselected Dutch population (N=1316). Using both single-nucleotide polymorphism (SNP)- and gene-based association testing, we detected an association between intelligence and the genes of interest, with genes ELP2, TMEM135, PRMT10, and RGS7 showing the strongest associations. This is a demonstration of the relevance of genes implicated in monogenic disorders of intelligence to normal-range intelligence, and a corroboration of the utility of employing knowledge on monogenic disorders in identifying the genetic variability underlying complex traits.

Endurance Exercise Ability in the Horse: A Trait with Complex Polygenic Determinism

PubMed Central

Ricard, Anne; Robert, Céline; Blouin, Christine; Baste, Fanny; Torquet, Gwendoline; Morgenthaler, Caroline; Rivière, Julie; Mach, Nuria; Mata, Xavier; Schibler, Laurent; Barrey, Eric

2017-01-01

Endurance horses are able to run at more than 20 km/h for 160 km (in bouts of 30–40 km). This level of performance is based on intense aerobic metabolism, effective body heat dissipation and the ability to endure painful exercise. The known heritabilities of endurance performance and exercise-related physiological traits in Arabian horses suggest that adaptation to extreme endurance exercise is influenced by genetic factors. The objective of the present genome-wide association study (GWAS) was to identify single nucleotide polymorphisms (SNPs) related to endurance racing performance in 597 Arabian horses. The performance traits studied were the total race distance, average race speed and finishing status (qualified, eliminated or retired). We used three mixed models that included a fixed allele or genotype effect and a random, polygenic effect. Quantile-quantile plots were acceptable, and the regression coefficients for actual vs. expected log10 p-values ranged from 0.865 to 1.055. The GWAS revealed five significant quantitative trait loci (QTL) corresponding to 6 SNPs on chromosomes 6, 1, 7, 16, and 29 (two SNPs) with corrected p-values from 1.7 × 10−6 to 1.8 × 10−5. Annotation of these 5 QTL revealed two genes: sortilin-related VPS10-domain-containing receptor 3 (SORCS3) on chromosome 1 is involved in protein trafficking, and solute carrier family 39 member 12 (SLC39A12) on chromosome 29 is active in zinc transport and cell homeostasis. These two coding genes could be involved in neuronal tissues (CNS). The other QTL on chromosomes 6, 7, and 16 may be involved in the regulation of the gene expression through non-coding RNAs, CpG islands and transcription factor binding sites. On chromosome 6, a new candidate equine long non-coding RNA (KCNQ1OT1 ortholog: opposite antisense transcript 1 of potassium voltage-gated channel subfamily Q member 1 gene) was predicted in silico and validated by RT-qPCR in primary cultures of equine myoblasts and fibroblasts. This lncRNA could be one element of the cardiac rhythm regulation. Our GWAS revealed that equine performance during endurance races is a complex polygenic trait, and is partially governed by at least 5 QTL: two coding genes involved in neuronal tissues and three other loci with many regulatory functions such as slowing down heart rate. PMID:28702049

Endurance Exercise Ability in the Horse: A Trait with Complex Polygenic Determinism.

PubMed

Ricard, Anne; Robert, Céline; Blouin, Christine; Baste, Fanny; Torquet, Gwendoline; Morgenthaler, Caroline; Rivière, Julie; Mach, Nuria; Mata, Xavier; Schibler, Laurent; Barrey, Eric

2017-01-01

Endurance horses are able to run at more than 20 km/h for 160 km (in bouts of 30-40 km). This level of performance is based on intense aerobic metabolism, effective body heat dissipation and the ability to endure painful exercise. The known heritabilities of endurance performance and exercise-related physiological traits in Arabian horses suggest that adaptation to extreme endurance exercise is influenced by genetic factors. The objective of the present genome-wide association study (GWAS) was to identify single nucleotide polymorphisms (SNPs) related to endurance racing performance in 597 Arabian horses. The performance traits studied were the total race distance, average race speed and finishing status (qualified, eliminated or retired). We used three mixed models that included a fixed allele or genotype effect and a random, polygenic effect. Quantile-quantile plots were acceptable, and the regression coefficients for actual vs. expected log 10 p -values ranged from 0.865 to 1.055. The GWAS revealed five significant quantitative trait loci (QTL) corresponding to 6 SNPs on chromosomes 6, 1, 7, 16, and 29 (two SNPs) with corrected p -values from 1.7 × 10 -6 to 1.8 × 10 -5 . Annotation of these 5 QTL revealed two genes: sortilin-related VPS10-domain-containing receptor 3 ( SORCS3 ) on chromosome 1 is involved in protein trafficking, and solute carrier family 39 member 12 ( SLC39A12 ) on chromosome 29 is active in zinc transport and cell homeostasis. These two coding genes could be involved in neuronal tissues (CNS). The other QTL on chromosomes 6, 7, and 16 may be involved in the regulation of the gene expression through non-coding RNAs, CpG islands and transcription factor binding sites. On chromosome 6, a new candidate equine long non-coding RNA ( KCNQ1OT1 ortholog: opposite antisense transcript 1 of potassium voltage-gated channel subfamily Q member 1 gene) was predicted in silico and validated by RT-qPCR in primary cultures of equine myoblasts and fibroblasts. This lncRNA could be one element of the cardiac rhythm regulation. Our GWAS revealed that equine performance during endurance races is a complex polygenic trait, and is partially governed by at least 5 QTL: two coding genes involved in neuronal tissues and three other loci with many regulatory functions such as slowing down heart rate.

Endophenotypes, Epigenetics, Polygenicity and More: Irv Gottesman’s Dynamic Legacy

PubMed Central

Braff, David L.; Tamminga, Carol A.

2017-01-01

First, we describe the hallmark contributions of Irv Gottesman’s pioneering scholarship for schizophrenia research including concepts of polygenicity, gene × environment interactions, epigenetics and the endophenotype concept. Gottesman and colleagues’ twin studies showed that genes, not social factors, mediate schizophrenia risk. He then showed that schizophrenia is highly polygenic. Next, he introduced the concept of epigenetics into schizophrenia research. Gottesman then introduced the quantitative endophenotype concept. Endophenotypes are laboratory-based measures that show deficits in schizophrenia patients and lesser deficits in their first degree “unaffected” relatives and are viewed as being more proximal to genes and having a simpler genetic architecture than are “fuzzy” qualitative diagnostic disorders. Endophenotypes offer an exciting path to gene discovery, neural circuits, genetic architecture and new treatment pathways of schizophrenia and related psychotic disorders. Second, we were asked to discuss 2 of many endophenotype Consortia and related studies, in order to illustrate the impact of Gottesman’s work. We describe the Consortium on the Genetics of Schizophrenia (COGS) exploring neurocognitive and neurophysiological endophenotypes in family and case-control studies. Association, linkage, sequencing and epigenetic studies are described. The Bipolar and Schizophrenia Network for Intermediate Phenotypes (BSNIP) uses an array of endophenotypes including brain imaging in studies across the psychosis dimension, allowing for dimensional analyses. BSNIP results have led to the concept of biotypes, advancing the field. Irv Gottesman was imaginatively prescient in generating novel insights and predicting many major issues which challenge schizophrenia researchers who still use his concepts to guide current research approaches. PMID:27872267

Short communication: Genetic association between schizophrenia and cannabis use.

PubMed

Verweij, Karin J H; Abdellaoui, Abdel; Nivard, Michel G; Sainz Cort, Alberto; Ligthart, Lannie; Draisma, Harmen H M; Minică, Camelia C; Gillespie, Nathan A; Willemsen, Gonneke; Hottenga, Jouke-Jan; Boomsma, Dorret I; Vink, Jacqueline M

2017-02-01

Previous studies have shown a relationship between schizophrenia and cannabis use. As both traits are substantially heritable, a shared genetic liability could explain the association. We use two recently developed genomics methods to investigate the genetic overlap between schizophrenia and cannabis use. Firstly, polygenic risk scores for schizophrenia were created based on summary statistics from the largest schizophrenia genome-wide association (GWA) meta-analysis to date. We analysed the association between these schizophrenia polygenic scores and multiple cannabis use phenotypes (lifetime use, regular use, age at initiation, and quantity and frequency of use) in a sample of 6,931 individuals. Secondly, we applied LD-score regression to the GWA summary statistics of schizophrenia and lifetime cannabis use to calculate the genome-wide genetic correlation. Polygenic risk scores for schizophrenia were significantly (α<0.05) associated with five of the eight cannabis use phenotypes, including lifetime use, regular use, and quantity of use, with risk scores explaining up to 0.5% of the variance. Associations were not significant for age at initiation of use and two measures of frequency of use analyzed in lifetime users only, potentially because of reduced power due to a smaller sample size. The LD-score regression revealed a significant genetic correlation of r g =0.22 (SE=0.07, p=0.003) between schizophrenia and lifetime cannabis use. Common genetic variants underlying schizophrenia and lifetime cannabis use are partly overlapping. Individuals with a stronger genetic predisposition to schizophrenia are more likely to initiate cannabis use, use cannabis more regularly, and consume more cannabis over their lifetime. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Shared genetic aetiology between cognitive functions and physical and mental health in UK Biobank (N=112 151) and 24 GWAS consortia.

PubMed

Hagenaars, S P; Harris, S E; Davies, G; Hill, W D; Liewald, D C M; Ritchie, S J; Marioni, R E; Fawns-Ritchie, C; Cullen, B; Malik, R; Worrall, B B; Sudlow, C L M; Wardlaw, J M; Gallacher, J; Pell, J; McIntosh, A M; Smith, D J; Gale, C R; Deary, I J

2016-11-01

Causes of the well-documented association between low levels of cognitive functioning and many adverse neuropsychiatric outcomes, poorer physical health and earlier death remain unknown. We used linkage disequilibrium regression and polygenic profile scoring to test for shared genetic aetiology between cognitive functions and neuropsychiatric disorders and physical health. Using information provided by many published genome-wide association study consortia, we created polygenic profile scores for 24 vascular-metabolic, neuropsychiatric, physiological-anthropometric and cognitive traits in the participants of UK Biobank, a very large population-based sample (N=112 151). Pleiotropy between cognitive and health traits was quantified by deriving genetic correlations using summary genome-wide association study statistics and to the method of linkage disequilibrium score regression. Substantial and significant genetic correlations were observed between cognitive test scores in the UK Biobank sample and many of the mental and physical health-related traits and disorders assessed here. In addition, highly significant associations were observed between the cognitive test scores in the UK Biobank sample and many polygenic profile scores, including coronary artery disease, stroke, Alzheimer's disease, schizophrenia, autism, major depressive disorder, body mass index, intracranial volume, infant head circumference and childhood cognitive ability. Where disease diagnosis was available for UK Biobank participants, we were able to show that these results were not confounded by those who had the relevant disease. These findings indicate that a substantial level of pleiotropy exists between cognitive abilities and many human mental and physical health disorders and traits and that it can be used to predict phenotypic variance across samples.

Genetic loci associated with coronary artery disease harbor evidence of selection and antagonistic pleiotropy

PubMed Central

Byars, Sean G.; Gray, Lesley-Ann; Ripatti, Samuli; Stearns, Stephen C.; Inouye, Michael

2017-01-01

Traditional genome-wide scans for positive selection have mainly uncovered selective sweeps associated with monogenic traits. While selection on quantitative traits is much more common, very few signals have been detected because of their polygenic nature. We searched for positive selection signals underlying coronary artery disease (CAD) in worldwide populations, using novel approaches to quantify relationships between polygenic selection signals and CAD genetic risk. We identified new candidate adaptive loci that appear to have been directly modified by disease pressures given their significant associations with CAD genetic risk. These candidates were all uniquely and consistently associated with many different male and female reproductive traits suggesting selection may have also targeted these because of their direct effects on fitness. We found that CAD loci are significantly enriched for lifetime reproductive success relative to the rest of the human genome, with evidence that the relationship between CAD and lifetime reproductive success is antagonistic. This supports the presence of antagonistic-pleiotropic tradeoffs on CAD loci and provides a novel explanation for the maintenance and high prevalence of CAD in modern humans. Lastly, we found that positive selection more often targeted CAD gene regulatory variants using HapMap3 lymphoblastoid cell lines, which further highlights the unique biological significance of candidate adaptive loci underlying CAD. Our study provides a novel approach for detecting selection on polygenic traits and evidence that modern human genomes have evolved in response to CAD-induced selection pressures and other early-life traits sharing pleiotropic links with CAD. PMID:28640878

Genetic effects influencing risk for major depressive disorder in China and Europe.

PubMed

Bigdeli, T B; Ripke, S; Peterson, R E; Trzaskowski, M; Bacanu, S-A; Abdellaoui, A; Andlauer, T F M; Beekman, A T F; Berger, K; Blackwood, D H R; Boomsma, D I; Breen, G; Buttenschøn, H N; Byrne, E M; Cichon, S; Clarke, T-K; Couvy-Duchesne, B; Craddock, N; de Geus, E J C; Degenhardt, F; Dunn, E C; Edwards, A C; Fanous, A H; Forstner, A J; Frank, J; Gill, M; Gordon, S D; Grabe, H J; Hamilton, S P; Hardiman, O; Hayward, C; Heath, A C; Henders, A K; Herms, S; Hickie, I B; Hoffmann, P; Homuth, G; Hottenga, J-J; Ising, M; Jansen, R; Kloiber, S; Knowles, J A; Lang, M; Li, Q S; Lucae, S; MacIntyre, D J; Madden, P A F; Martin, N G; McGrath, P J; McGuffin, P; McIntosh, A M; Medland, S E; Mehta, D; Middeldorp, C M; Milaneschi, Y; Montgomery, G W; Mors, O; Müller-Myhsok, B; Nauck, M; Nyholt, D R; Nöthen, M M; Owen, M J; Penninx, B W J H; Pergadia, M L; Perlis, R H; Peyrot, W J; Porteous, D J; Potash, J B; Rice, J P; Rietschel, M; Riley, B P; Rivera, M; Schoevers, R; Schulze, T G; Shi, J; Shyn, S I; Smit, J H; Smoller, J W; Streit, F; Strohmaier, J; Teumer, A; Treutlein, J; Van der Auwera, S; van Grootheest, G; van Hemert, A M; Völzke, H; Webb, B T; Weissman, M M; Wellmann, J; Willemsen, G; Witt, S H; Levinson, D F; Lewis, C M; Wray, N R; Flint, J; Sullivan, P F; Kendler, K S

2017-03-28

Major depressive disorder (MDD) is a common, complex psychiatric disorder and a leading cause of disability worldwide. Despite twin studies indicating its modest heritability (~30-40%), extensive heterogeneity and a complex genetic architecture have complicated efforts to detect associated genetic risk variants. We combined single-nucleotide polymorphism (SNP) summary statistics from the CONVERGE and PGC studies of MDD, representing 10 502 Chinese (5282 cases and 5220 controls) and 18 663 European (9447 cases and 9215 controls) subjects. We determined the fraction of SNPs displaying consistent directions of effect, assessed the significance of polygenic risk scores and estimated the genetic correlation of MDD across ancestries. Subsequent trans-ancestry meta-analyses combined SNP-level evidence of association. Sign tests and polygenic score profiling weakly support an overlap of SNP effects between East Asian and European populations. We estimated the trans-ancestry genetic correlation of lifetime MDD as 0.33; female-only and recurrent MDD yielded estimates of 0.40 and 0.41, respectively. Common variants downstream of GPHN achieved genome-wide significance by Bayesian trans-ancestry meta-analysis (rs9323497; log 10 Bayes Factor=8.08) but failed to replicate in an independent European sample (P=0.911). Gene-set enrichment analyses indicate enrichment of genes involved in neuronal development and axonal trafficking. We successfully demonstrate a partially shared polygenic basis of MDD in East Asian and European populations. Taken together, these findings support a complex etiology for MDD and possible population differences in predisposing genetic factors, with important implications for future genetic studies.

Genetic effects influencing risk for major depressive disorder in China and Europe

PubMed Central

Bigdeli, T B; Ripke, S; Peterson, R E; Trzaskowski, M; Bacanu, S-A; Abdellaoui, A; Andlauer, T F M; Beekman, A T F; Berger, K; Blackwood, D H R; Boomsma, D I; Breen, G; Buttenschøn, H N; Byrne, E M; Cichon, S; Clarke, T-K; Couvy-Duchesne, B; Craddock, N; de Geus, E J C; Degenhardt, F; Dunn, E C; Edwards, A C; Fanous, A H; Forstner, A J; Frank, J; Gill, M; Gordon, S D; Grabe, H J; Hamilton, S P; Hardiman, O; Hayward, C; Heath, A C; Henders, A K; Herms, S; Hickie, I B; Hoffmann, P; Homuth, G; Hottenga, J-J; Ising, M; Jansen, R; Kloiber, S; Knowles, J A; Lang, M; Li, Q S; Lucae, S; MacIntyre, D J; Madden, P A F; Martin, N G; McGrath, P J; McGuffin, P; McIntosh, A M; Medland, S E; Mehta, D; Middeldorp, C M; Milaneschi, Y; Montgomery, G W; Mors, O; Müller-Myhsok, B; Nauck, M; Nyholt, D R; Nöthen, M M; Owen, M J; Penninx, B W J H; Pergadia, M L; Perlis, R H; Peyrot, W J; Porteous, D J; Potash, J B; Rice, J P; Rietschel, M; Riley, B P; Rivera, M; Schoevers, R; Schulze, T G; Shi, J; Shyn, S I; Smit, J H; Smoller, J W; Streit, F; Strohmaier, J; Teumer, A; Treutlein, J; Van der Auwera, S; van Grootheest, G; van Hemert, A M; Völzke, H; Webb, B T; Weissman, M M; Wellmann, J; Willemsen, G; Witt, S H; Levinson, D F; Lewis, C M; Wray, N R; Flint, J; Sullivan, P F; Kendler, K S

2017-01-01

Major depressive disorder (MDD) is a common, complex psychiatric disorder and a leading cause of disability worldwide. Despite twin studies indicating its modest heritability (~30–40%), extensive heterogeneity and a complex genetic architecture have complicated efforts to detect associated genetic risk variants. We combined single-nucleotide polymorphism (SNP) summary statistics from the CONVERGE and PGC studies of MDD, representing 10 502 Chinese (5282 cases and 5220 controls) and 18 663 European (9447 cases and 9215 controls) subjects. We determined the fraction of SNPs displaying consistent directions of effect, assessed the significance of polygenic risk scores and estimated the genetic correlation of MDD across ancestries. Subsequent trans-ancestry meta-analyses combined SNP-level evidence of association. Sign tests and polygenic score profiling weakly support an overlap of SNP effects between East Asian and European populations. We estimated the trans-ancestry genetic correlation of lifetime MDD as 0.33; female-only and recurrent MDD yielded estimates of 0.40 and 0.41, respectively. Common variants downstream of GPHN achieved genome-wide significance by Bayesian trans-ancestry meta-analysis (rs9323497; log10 Bayes Factor=8.08) but failed to replicate in an independent European sample (P=0.911). Gene-set enrichment analyses indicate enrichment of genes involved in neuronal development and axonal trafficking. We successfully demonstrate a partially shared polygenic basis of MDD in East Asian and European populations. Taken together, these findings support a complex etiology for MDD and possible population differences in predisposing genetic factors, with important implications for future genetic studies. PMID:28350396

Analysis of Polygenic Mutants Suggests a Role for Mediator in Regulating Transcriptional Activation Distance in Saccharomyces cerevisiae.

PubMed

Reavey, Caitlin T; Hickman, Mark J; Dobi, Krista C; Botstein, David; Winston, Fred

2015-10-01

Studies of natural populations of many organisms have shown that traits are often complex, caused by contributions of mutations in multiple genes. In contrast, genetic studies in the laboratory primarily focus on studying the phenotypes caused by mutations in a single gene. However, the single mutation approach may be limited with respect to the breadth and degree of new phenotypes that can be found. We have taken the approach of isolating complex, or polygenic mutants in the lab to study the regulation of transcriptional activation distance in yeast. While most aspects of eukaryotic transcription are conserved from yeast to human, transcriptional activation distance is not. In Saccharomyces cerevisiae, the upstream activating sequence (UAS) is generally found within 450 base pairs of the transcription start site (TSS) and when the UAS is moved too far away, activation no longer occurs. In contrast, metazoan enhancers can activate from as far as several hundred kilobases from the TSS. Previously, we identified single mutations that allow transcription activation to occur at a greater-than-normal distance from the GAL1 UAS. As the single mutant phenotypes were weak, we have now isolated polygenic mutants that possess strong long-distance phenotypes. By identification of the causative mutations we have accounted for most of the heritability of the phenotype in each strain and have provided evidence that the Mediator coactivator complex plays both positive and negative roles in the regulation of transcription activation distance. Copyright © 2015 by the Genetics Society of America.

The impact of manual threshold selection in medical additive manufacturing.

PubMed

van Eijnatten, Maureen; Koivisto, Juha; Karhu, Kalle; Forouzanfar, Tymour; Wolff, Jan

2017-04-01

Medical additive manufacturing requires standard tessellation language (STL) models. Such models are commonly derived from computed tomography (CT) images using thresholding. Threshold selection can be performed manually or automatically. The aim of this study was to assess the impact of manual and default threshold selection on the reliability and accuracy of skull STL models using different CT technologies. One female and one male human cadaver head were imaged using multi-detector row CT, dual-energy CT, and two cone-beam CT scanners. Four medical engineers manually thresholded the bony structures on all CT images. The lowest and highest selected mean threshold values and the default threshold value were used to generate skull STL models. Geometric variations between all manually thresholded STL models were calculated. Furthermore, in order to calculate the accuracy of the manually and default thresholded STL models, all STL models were superimposed on an optical scan of the dry female and male skulls ("gold standard"). The intra- and inter-observer variability of the manual threshold selection was good (intra-class correlation coefficients >0.9). All engineers selected grey values closer to soft tissue to compensate for bone voids. Geometric variations between the manually thresholded STL models were 0.13 mm (multi-detector row CT), 0.59 mm (dual-energy CT), and 0.55 mm (cone-beam CT). All STL models demonstrated inaccuracies ranging from -0.8 to +1.1 mm (multi-detector row CT), -0.7 to +2.0 mm (dual-energy CT), and -2.3 to +4.8 mm (cone-beam CT). This study demonstrates that manual threshold selection results in better STL models than default thresholding. The use of dual-energy CT and cone-beam CT technology in its present form does not deliver reliable or accurate STL models for medical additive manufacturing. New approaches are required that are based on pattern recognition and machine learning algorithms.

Complex segregation analysis of craniomandibular osteopathy in Deutsch Drahthaar dogs.

PubMed

Vagt, J; Distl, O

2018-01-01

This study investigated familial relationships among Deutsch Drahthaar dogs with craniomandibular osteopathy and examined the most likely mode of inheritance. Sixteen Deutsch Drahthaar dogs with craniomandibular osteopathy were diagnosed using clinical findings, radiography or computed tomography. All 16 dogs with craniomandibular osteopathy had one common ancestor. Complex segregation analyses rejected models explaining the segregation of craniomandibular osteopathy through random environmental variation, monogenic inheritance or an additive sex effect. Polygenic and mixed major gene models sufficiently explained the segregation of craniomandibular osteopathy in the pedigree analysis and offered the most likely hypotheses. The SLC37A2:c.1332C>T variant was not found in a sample of Deutsch Drahthaar dogs with craniomandibular osteopathy, nor in healthy controls. Craniomandibular osteopathy is an inherited condition in Deutsch Drahthaar dogs and the inheritance seems to be more complex than a simple Mendelian model. Copyright © 2017 Elsevier Ltd. All rights reserved.

Evaluation of a 7-Gene Genetic Profile for Athletic Endurance Phenotype in Ironman Championship Triathletes

PubMed Central

Grealy, Rebecca; Herruer, Jasper; Smith, Carl L. E.; Hiller, Doug; Haseler, Luke J.; Griffiths, Lyn R.

2015-01-01

Polygenic profiling has been proposed for elite endurance performance, using an additive model determining the proportion of optimal alleles in endurance athletes. To investigate this model’s utility for elite triathletes, we genotyped seven polymorphisms previously associated with an endurance polygenic profile (ACE Ins/Del, ACTN3 Arg577Ter, AMPD1 Gln12Ter, CKMM 1170bp/985+185bp, HFE His63Asp, GDF8 Lys153Arg and PPARGC1A Gly482Ser) in a cohort of 196 elite athletes who participated in the 2008 Kona Ironman championship triathlon. Mean performance time (PT) was not significantly different in individual marker analysis. Age, sex, and continent of origin had a significant influence on PT and were adjusted for. Only the AMPD1 endurance-optimal Gln allele was found to be significantly associated with an improvement in PT (model p = 5.79 x 10−17, AMPD1 genotype p = 0.01). Individual genotypes were combined into a total genotype score (TGS); TGS distribution ranged from 28.6 to 92.9, concordant with prior studies in endurance athletes (mean±SD: 60.75±12.95). TGS distribution was shifted toward higher TGS in the top 10% of athletes, though the mean TGS was not significantly different (p = 0.164) and not significantly associated with PT even when adjusted for age, sex, and origin. Receiver operating characteristic curve analysis determined that TGS alone could not significantly predict athlete finishing time with discriminating sensitivity and specificity for three outcomes (less than median PT, less than mean PT, or in the top 10%), though models with the age, sex, continent of origin, and either TGS or AMPD1 genotype could. These results suggest three things: that more sophisticated genetic models may be necessary to accurately predict athlete finishing time in endurance events; that non-genetic factors such as training are hugely influential and should be included in genetic analyses to prevent confounding; and that large collaborations may be necessary to obtain sufficient sample sizes for powerful and complex analyses of endurance performance. PMID:26716680

Nonlinear time series modeling and forecasting the seismic data of the Hindu Kush region

NASA Astrophysics Data System (ADS)

Khan, Muhammad Yousaf; Mittnik, Stefan

2018-01-01

In this study, we extended the application of linear and nonlinear time models in the field of earthquake seismology and examined the out-of-sample forecast accuracy of linear Autoregressive (AR), Autoregressive Conditional Duration (ACD), Self-Exciting Threshold Autoregressive (SETAR), Threshold Autoregressive (TAR), Logistic Smooth Transition Autoregressive (LSTAR), Additive Autoregressive (AAR), and Artificial Neural Network (ANN) models for seismic data of the Hindu Kush region. We also extended the previous studies by using Vector Autoregressive (VAR) and Threshold Vector Autoregressive (TVAR) models and compared their forecasting accuracy with linear AR model. Unlike previous studies that typically consider the threshold model specifications by using internal threshold variable, we specified these models with external transition variables and compared their out-of-sample forecasting performance with the linear benchmark AR model. The modeling results show that time series models used in the present study are capable of capturing the dynamic structure present in the seismic data. The point forecast results indicate that the AR model generally outperforms the nonlinear models. However, in some cases, threshold models with external threshold variables specification produce more accurate forecasts, indicating that specification of threshold time series models is of crucial importance. For raw seismic data, the ACD model does not show an improved out-of-sample forecasting performance over the linear AR model. The results indicate that the AR model is the best forecasting device to model and forecast the raw seismic data of the Hindu Kush region.

Childhood intelligence is heritable, highly polygenic and associated with FNBP1L

PubMed Central

Benyamin, B; Pourcain, BSt; Davis, OS; Davies, G; Hansell, NK; Brion, M-JA; Kirkpatrick, RM; Cents, RAM; Franić, S; Miller, MB; Haworth, CMA; Meaburn, E; Price, TS; Evans, DM; Timpson, N; Kemp, J; Ring, S; McArdle, W; Medland, SE; Yang, J; Harris, SE; Liewald, DC; Scheet, P; Xiao, X; Hudziak, JJ; de Geus, EJC; Jaddoe, VWV; Starr, JM; Verhulst, FC; Pennell, C; Tiemeier, H; Iacono, WG; Palmer, LJ; Montgomery, GW; Martin, NG; Boomsma, DI; Posthuma, D; McGue, M; Wright, MJ; Smith, G Davey; Deary, IJ; Plomin, R; Visscher, PM

2014-01-01

Intelligence in childhood, as measured by psychometric cognitive tests, is a strong predictor of many important life outcomes, including educational attainment, income, health and lifespan. Results from twin, family and adoption studies are consistent with general intelligence being highly heritable and genetically stable throughout the life course. No robustly associated genetic loci or variants for childhood intelligence have been reported. Here, we report the first genome-wide association study (GWAS) on childhood intelligence (age range 6–18 years) from 17 989 individuals in six discovery and three replication samples. Although no individual single-nucleotide polymorphisms (SNPs) were detected with genome-wide significance, we show that the aggregate effects of common SNPs explain 22–46% of phenotypic variation in childhood intelligence in the three largest cohorts (P = 3.9 × 10−15, 0.014 and 0.028). FNBP1L, previously reported to be the most significantly associated gene for adult intelligence, was also significantly associated with childhood intelligence (P = 0.003). Polygenic prediction analyses resulted in a significant correlation between predictor and outcome in all replication cohorts. The proportion of childhood intelligence explained by the predictor reached 1.2% (P = 6 × 10−5), 3.5% (P = 10−3) and 0.5% (P = 6 × 10−5) in three independent validation cohorts. Given the sample sizes, these genetic prediction results are consistent with expectations if the genetic architecture of childhood intelligence is like that of body mass index or height. Our study provides molecular support for the heritability and polygenic nature of childhood intelligence. Larger sample sizes will be required to detect individual variants with genome-wide significance. PMID:23358156

Is adult ADHD a childhood-onset neurodevelopmental disorder? Evidence from a 4-decade longitudinal cohort study

PubMed Central

Moffitt, Terrie E.; Houts, Renate; Asherson, Philip; Belsky, Daniel W; Corcoran, David L; Hammerle, Maggie; Harrington, Honalee; Hogan, Sean; Meier, Madeline; Polanczyk, Guilherme V.; Poulton, Richie; Ramrakha, Sandhya; Sugden, Karen; Williams, Benjamin; Rohde, Luis Augusto; Caspi, Avshalom

2015-01-01

Objective Despite a prevailing assumption that adult ADHD is a childhood-onset neurodevelopmental disorder, no prospective-longitudinal study has described the childhoods of the adult-ADHD population. We report follow-back analyses of ADHD cases diagnosed in adulthood, alongside follow-forward analyses of ADHD cases diagnosed in childhood, in one cohort. Method Participants belonged to a representative birth cohort of 1,037 individuals born in Dunedin, New Zealand in 1972-73 and followed to age 38, with 95% retention. Symptoms of ADHD, associated clinical features, comorbid disorders, neuropsychological deficits, GWAS-derived polygenic risk, and life impairment indicators were assessed. Data sources were participants, parents, teachers, informants, neuropsychological testing, and administrative records. Adult ADHD diagnoses used DSM5 criteria, apart from onset-age and cross-setting corroboration, which were study outcomes. Results As expected, the childhood-ADHD group showed 6% prevalence, male excess, childhood comorbid disorders, neurocognitive deficits, polygenic risk, and, despite having outgrown their ADHD diagnosis, residual adult life impairment. As expected, the adult-ADHD group showed 3% prevalence, gender balance, adult substance dependence, adult life impairment, and treatment contact. Unexpectedly, the childhood-ADHD and adult-ADHD groups comprised virtually non-overlapping sets; 90% of adult-ADHD cases lacked a history of childhood ADHD. Also unexpectedly, the adult-ADHD group did not show tested neuropsychological deficits in childhood or adulthood, nor did they show polygenic risk for childhood ADHD. Conclusion Findings raise the possibility that adults presenting with the ADHD symptom picture may not have a childhood-onset neurodevelopmental disorder. If this finding is replicated, then the disorder's place in the classification system must be reconsidered, and research must investigate the etiology of adult ADHD. PMID:25998281

Shared genetic aetiology between cognitive functions and physical and mental health in UK Biobank (N=112 151) and 24 GWAS consortia

PubMed Central

Hagenaars, S P; Harris, S E; Davies, G; Hill, W D; Liewald, D C M; Ritchie, S J; Marioni, R E; Fawns-Ritchie, C; Cullen, B; Malik, R; Worrall, B B; Sudlow, C L M; Wardlaw, J M; Gallacher, J; Pell, J; McIntosh, A M; Smith, D J; Gale, C R; Deary, I J

2016-01-01

Causes of the well-documented association between low levels of cognitive functioning and many adverse neuropsychiatric outcomes, poorer physical health and earlier death remain unknown. We used linkage disequilibrium regression and polygenic profile scoring to test for shared genetic aetiology between cognitive functions and neuropsychiatric disorders and physical health. Using information provided by many published genome-wide association study consortia, we created polygenic profile scores for 24 vascular–metabolic, neuropsychiatric, physiological–anthropometric and cognitive traits in the participants of UK Biobank, a very large population-based sample (N=112 151). Pleiotropy between cognitive and health traits was quantified by deriving genetic correlations using summary genome-wide association study statistics and to the method of linkage disequilibrium score regression. Substantial and significant genetic correlations were observed between cognitive test scores in the UK Biobank sample and many of the mental and physical health-related traits and disorders assessed here. In addition, highly significant associations were observed between the cognitive test scores in the UK Biobank sample and many polygenic profile scores, including coronary artery disease, stroke, Alzheimer's disease, schizophrenia, autism, major depressive disorder, body mass index, intracranial volume, infant head circumference and childhood cognitive ability. Where disease diagnosis was available for UK Biobank participants, we were able to show that these results were not confounded by those who had the relevant disease. These findings indicate that a substantial level of pleiotropy exists between cognitive abilities and many human mental and physical health disorders and traits and that it can be used to predict phenotypic variance across samples. PMID:26809841

Methylomic profiling of cortex samples from completed suicide cases implicates a role for PSORS1C3 in major depression and suicide.

PubMed

Murphy, T M; Crawford, B; Dempster, E L; Hannon, E; Burrage, J; Turecki, G; Kaminsky, Z; Mill, J

2017-01-03

Major depressive disorder (MDD) represents a major social and economic health issue and constitutes a major risk factor for suicide. The molecular pathology of suicidal depression remains poorly understood, although it has been hypothesised that regulatory genomic processes are involved in the pathology of both MDD and suicidality. In this study, genome-wide patterns of DNA methylation were assessed in depressed suicide completers (n=20) and compared with non-psychiatric, sudden-death controls (n=20) using tissue from two cortical brain regions (Brodmann Area 11 (BA11) and Brodmann Area 25 (BA25)). Analyses focused on identifying differentially methylated regions (DMRs) associated with suicidal depression and epigenetic variation were explored in the context of polygenic risk scores for major depression and suicide. Weighted gene co-methylation network analysis was used to identify modules of co-methylated loci associated with depressed suicide completers and polygenic burden for MDD and suicide attempt. We identified a DMR upstream of the PSORS1C3 gene, subsequently validated using bisulfite pyrosequencing and replicated in a second set of suicide samples, which is characterised by significant hypomethylation in both cortical brain regions in MDD suicide cases. We also identified discrete modules of co-methylated loci associated with polygenic risk burden for suicide attempt, but not major depression. Suicide-associated co-methylation modules were enriched among gene networks implicating biological processes relevant to depression and suicidality, including nervous system development and mitochondria function. Our data suggest that there are coordinated changes in DNA methylation associated with suicide that may offer novel insights into the molecular pathology associated with depressed suicide completers.

Individual Differences in Amygdala-Medial Prefrontal Anatomy Link Negative Affect, Impaired Social Functioning, and Polygenic Depression Risk

PubMed Central

Holmes, Avram J.; Lee, Phil H.; Hollinshead, Marisa O.; Bakst, Leah; Roffman, Joshua L.; Smoller, Jordan W.; Buckner, Randy L.

2013-01-01

Individual differences in affective and social processes may arise from variability in amygdala-medial prefrontal (mPFC) circuitry and related genetic heterogeneity. To explore this possibility in humans, we examined the structural correlates of trait negative affect in a sample of 1050 healthy young adults with no history of psychiatric illness. Analyses revealed that heightened negative affect was associated with increased amygdala volume and reduced thickness in a left mPFC region encompassing the subgenual and rostral anterior cingulate cortex. The most extreme individuals displayed an inverse correlation between amygdala volume and mPFC thickness, suggesting that imbalance between these structures is linked to negative affect in the general population. Subgroups of participants were further evaluated on social (n = 206) and emotional (n = 533) functions. Individuals with decreased mPFC thickness exhibited the poorest social cognition and were least able to correctly identify facial emotion. Given prior links between disrupted amygdala–mPFC circuitry and the presence of major depressive disorder (MDD), we explored whether the individual differences in anatomy observed here in healthy young adults were associated with polygenic risk for MDD (n = 438) using risk scores derived from a large genome-wide association analysis (n = 18,759). Analyses revealed associations between increasing polygenic burden for MDD and reduced cortical thickness in the left mPFC. These collective findings suggest that, within the healthy population, there is significant variability in amygdala–mPFC circuitry that is associated with poor functioning across affective and social domains. Individual differences in this circuitry may arise, in part, from common genetic variability that contributes to risk for MDD. PMID:23238724

Methylomic profiling of cortex samples from completed suicide cases implicates a role for PSORS1C3 in major depression and suicide

PubMed Central

Murphy, T M; Crawford, B; Dempster, E L; Hannon, E; Burrage, J; Turecki, G; Kaminsky, Z; Mill, J

2017-01-01

Major depressive disorder (MDD) represents a major social and economic health issue and constitutes a major risk factor for suicide. The molecular pathology of suicidal depression remains poorly understood, although it has been hypothesised that regulatory genomic processes are involved in the pathology of both MDD and suicidality. In this study, genome-wide patterns of DNA methylation were assessed in depressed suicide completers (n=20) and compared with non-psychiatric, sudden-death controls (n=20) using tissue from two cortical brain regions (Brodmann Area 11 (BA11) and Brodmann Area 25 (BA25)). Analyses focused on identifying differentially methylated regions (DMRs) associated with suicidal depression and epigenetic variation were explored in the context of polygenic risk scores for major depression and suicide. Weighted gene co-methylation network analysis was used to identify modules of co-methylated loci associated with depressed suicide completers and polygenic burden for MDD and suicide attempt. We identified a DMR upstream of the PSORS1C3 gene, subsequently validated using bisulfite pyrosequencing and replicated in a second set of suicide samples, which is characterised by significant hypomethylation in both cortical brain regions in MDD suicide cases. We also identified discrete modules of co-methylated loci associated with polygenic risk burden for suicide attempt, but not major depression. Suicide-associated co-methylation modules were enriched among gene networks implicating biological processes relevant to depression and suicidality, including nervous system development and mitochondria function. Our data suggest that there are coordinated changes in DNA methylation associated with suicide that may offer novel insights into the molecular pathology associated with depressed suicide completers. PMID:28045465

A Genome-Wide Test of the Differential Susceptibility Hypothesis Reveals a Genetic Predictor of Differential Response to Psychological Treatments for Child Anxiety Disorders

PubMed Central

Keers, Robert; Coleman, Jonathan R.I.; Lester, Kathryn J.; Roberts, Susanna; Breen, Gerome; Thastum, Mikael; Bögels, Susan; Schneider, Silvia; Heiervang, Einar; Meiser-Stedman, Richard; Nauta, Maaike; Creswell, Cathy; Thirlwall, Kerstin; Rapee, Ronald M.; Hudson, Jennifer L.; Lewis, Cathryn; Plomin, Robert; Eley, Thalia C.

2016-01-01

Background The differential susceptibly hypothesis suggests that certain genetic variants moderate the effects of both negative and positive environments on mental health and may therefore be important predictors of response to psychological treatments. Nevertheless, the identification of such variants has so far been limited to preselected candidate genes. In this study we extended the differential susceptibility hypothesis from a candidate gene to a genome-wide approach to test whether a polygenic score of environmental sensitivity predicted response to cognitive behavioural therapy (CBT) in children with anxiety disorders. Methods We identified variants associated with environmental sensitivity using a novel method in which within-pair variability in emotional problems in 1,026 monozygotic twin pairs was examined as a function of the pairs' genotype. We created a polygenic score of environmental sensitivity based on the whole-genome findings and tested the score as a moderator of parenting on emotional problems in 1,406 children and response to individual, group and brief parent-led CBT in 973 children with anxiety disorders. Results The polygenic score significantly moderated the effects of parenting on emotional problems and the effects of treatment. Individuals with a high score responded significantly better to individual CBT than group CBT or brief parent-led CBT (remission rates: 70.9, 55.5 and 41.6%, respectively). Conclusions Pending successful replication, our results should be considered exploratory. Nevertheless, if replicated, they suggest that individuals with the greatest environmental sensitivity may be more likely to develop emotional problems in adverse environments but also benefit more from the most intensive types of treatment. PMID:27043157

Genome-Wide Significant Association between Alcohol Dependence and a Variant in the ADH Gene Cluster

PubMed Central

Frank, Josef; Cichon, Sven; Treutlein, Jens; Ridinger, Monika; Mattheisen, Manuel; Hoffmann, Per; Herms, Stefan; Wodarz, Norbert; Soyka, Michael; Zill, Peter; Maier, Wolfgang; Mössner, Rainald; Gaebel, Wolfgang; Dahmen, Norbert; Scherbaum, Norbert; Schmäl, Christine; Steffens, Michael; Lucae, Susanne; Ising, Marcus; Müller-Myhsok, Bertram; Nöthen, Markus M; Mann, Karl; Kiefer, Falk; Rietschel, Marcella

2011-01-01

Alcohol dependence (AD) is an important contributory factor to the global burden of disease. The etiology of AD involves both environmental and genetic factors, and the disorder has a heritability of around 50%. The aim of the present study was to identify susceptibility genes for AD by performing a genome-wide association study (GWAS). The sample comprised 1,333 male in-patients with severe DSM-IV AD and 2,168 controls. These included 487 patients and 1,358 controls from a previous GWAS study by our group. All individuals were of German descent. Single marker tests and a polygenic score based analysis to assess the combined contribution of multiple markers with small effects were performed. The SNP rs1789891, which is located between the ADH1B and ADH1C genes, achieved genome-wide significance (p=1.27E–8; OR=1.46). Other markers from this region were also associated with AD, and conditional analyses indicated that these made a partially independent contribution. The SNP rs1789891 is in complete linkage disequilibrium with the functional Arg272Gln variant (p=1.24E–7, OR=1.31) of the ADH1C gene, which has been reported to modify the rate of ethanol oxidation to acetaldehyde in vitro. A polygenic score based approach produced a significant result (p=9.66E–9). This is the first GWAS of AD to provide genome-wide significant support for the role of the ADH gene cluster and to suggest a polygenic component to the etiology of AD. The latter result suggests that many more AD susceptibility genes still await identification. PMID:22004471

Polygenic Risk for Depression Increases Risk of Ischemic Stroke: From the Stroke Genetics Network Study.

PubMed

Wassertheil-Smoller, Sylvia; Qi, Qibin; Dave, Tushar; Mitchell, Braxton D; Jackson, Rebecca D; Liu, Simin; Park, Ki; Salinas, Joel; Dunn, Erin C; Leira, Enrique C; Xu, Huichun; Ryan, Kathleen; Smoller, Jordan W

2018-03-01

Although depression is a risk factor for stroke in large prospective studies, it is unknown whether these conditions have a shared genetic basis. We applied a polygenic risk score (PRS) for major depressive disorder derived from European ancestry analyses by the Psychiatric Genomics Consortium to a genome-wide association study of ischemic stroke in the Stroke Genetics Network of National Institute of Neurological Disorders and Stroke. Included in separate analyses were 12 577 stroke cases and 25 643 controls of European ancestry and 1353 cases and 2383 controls of African ancestry. We examined the association between depression PRS and ischemic stroke overall and with pathogenic subtypes using logistic regression analyses. The depression PRS was associated with higher risk of ischemic stroke overall in both European ( P =0.025) and African ancestry ( P =0.011) samples from the Stroke Genetics Network. Ischemic stroke risk increased by 3.0% (odds ratio, 1.03; 95% confidence interval, 1.00-1.05) for every 1 SD increase in PRS for those of European ancestry and by 8% (odds ratio, 1.08; 95% confidence interval, 1.04-1.13) for those of African ancestry. Among stroke subtypes, elevated risk of small artery occlusion was observed in both European and African ancestry samples. Depression PRS was also associated with higher risk of cardioembolic stroke in European ancestry and large artery atherosclerosis in African ancestry persons. Higher polygenic risk for major depressive disorder is associated with increased risk of ischemic stroke overall and with small artery occlusion. Additional associations with ischemic stroke subtypes differed by ancestry. © 2018 American Heart Association, Inc.

Pathway-specific polygenic risk scores as predictors of β-amyloid deposition and cognitive function in a sample at increased risk for Alzheimer’s disease

PubMed Central

Darst, Burcu F.; Koscik, Rebecca L.; Racine, Annie M.; Oh, Jennifer M.; Krause, Rachel A.; Carlsson, Cynthia M.; Zetterberg, Henrik; Blennow, Kaj; Christian, Bradley T.; Bendlin, Barbara B.; Okonkwo, Ozioma C.; Hogan, Kirk J.; Hermann, Bruce P.; Sager, Mark A.; Asthana, Sanjay; Johnson, Sterling C.; Engelman, Corinne D.

2016-01-01

Polygenic risk scores (PRSs) have been used to combine the effects of variants with small effects identified by genome-wide association studies. We explore the potential for using pathway-specific PRSs as predictors of early changes in Alzheimer’s disease (AD)-related biomarkers and cognitive function. Participants were from the Wisconsin Registry for Alzheimer’s Prevention, a longitudinal study of adults who were cognitively asymptomatic at enrollment and enriched for a parental history of AD. Using genes associated with AD in the International Genomics of Alzheimer’s Project’s meta-analysis, we identified clusters of genes that grouped into pathways involved in β-amyloid (Aβ) deposition and neurodegeneration: Aβ clearance, cholesterol metabolism, and immune response. Weighted pathway-specific and overall PRSs were developed and compared to APOE alone. Mixed models were used to assess whether each PRS was associated with cognition in 1,200 individuals, cerebral Aβ deposition measured using amyloid ligand (Pittsburgh compound B) positron emission imaging (PET) in 168 individuals, and cerebrospinal fluid (CSF) Aβ deposition, neurodegeneration, and tau pathology in 111 individuals, with replication performed in an independent sample. We found that PRSs including APOE appeared to be driven by the inclusion of APOE, suggesting that the pathway-specific PRSs used here were not more predictive than an overall PRS or APOE alone. However, pathway-specific PRSs could prove to be useful as more knowledge is gained on the genetic variants involved in specific biological pathways of AD. PMID:27662287

Polygenic Sex Determination System in Zebrafish

PubMed Central

Liew, Woei Chang; Bartfai, Richard; Lim, Zijie; Sreenivasan, Rajini; Siegfried, Kellee R.; Orban, Laszlo

2012-01-01

Background Despite the popularity of zebrafish as a research model, its sex determination (SD) mechanism is still unknown. Most cytogenetic studies failed to find dimorphic sex chromosomes and no primary sex determining switch has been identified even though the assembly of zebrafish genome sequence is near to completion and a high resolution genetic map is available. Recent publications suggest that environmental factors within the natural range have minimal impact on sex ratios of zebrafish populations. The primary aim of this study is to find out more about how sex is determined in zebrafish. Methodology/Principal Findings Using classical breeding experiments, we found that sex ratios across families were wide ranging (4.8% to 97.3% males). On the other hand, repeated single pair crossings produced broods of very similar sex ratios, indicating that parental genotypes have a role in the sex ratio of the offspring. Variation among family sex ratios was reduced after selection for breeding pairs with predominantly male or female offspring, another indication that zebrafish sex is regulated genetically. Further examinations by a PCR-based “blind assay" and array comparative genomic hybridization both failed to find universal sex-linked differences between the male and female genomes. Together with the ability to increase the sex bias of lines by selective breeding, these data suggest that zebrafish is unlikely to utilize a chromosomal sex determination (CSD) system. Conclusions/Significance Taken together, our study suggests that zebrafish sex is genetically determined with limited, secondary influences from the environment. As we have not found any sign for CSD in the species, we propose that the zebrafish has a polygenic sex determination system. PMID:22506019

Adolescent externalizing behaviour, psychological control, and peer rejection: Transactional links and dopaminergic moderation.

PubMed

Janssens, Annelies; Van Den Noortgate, Wim; Goossens, Luc; Verschueren, Karine; Colpin, Hilde; Claes, Stephan; Van Heel, Martijn; Van Leeuwen, Karla

2017-09-01

This study investigated (1) reciprocal links among parental psychological control, peer rejection, and adolescent externalizing (aggressive and rule-breaking behaviour), and (2) the moderating effect of an adolescent genetic factor (biologically informed polygenic score for dopamine signalling). Three-year longitudinal data from 1,116 adolescents (51% boys; M age = 13.79) and their parents included psychological measures (adolescent-reported psychological control, peer-reported rejection, and parent-reported aggressive and rule-breaking behaviour). Cross-lagged analyses showed bidirectional effects between psychological control and both aggressive and rule-breaking behaviour and a unidirectional effect of peer rejection on both forms of problem behaviour over time. Multigroup structural equation modelling revealed genetic moderation only for rule-breaking behaviour: for adolescents with intermediate levels of dopamine signalling significant environmental effects were present, whereas adolescent effects of rule-breaking behaviour on psychological control were significant for adolescents with both intermediate and high profiles and effects on peer rejection only for adolescents with high dopamine profiles. Statement of contribution What is already known on this subject? Parental psychological control is related to adolescent externalizing problems. Experiencing peer rejection reinforces aggressive and rule-breaking behaviour. Single-gene studies show that dopaminergic genes influence externalizing problems directly or in interaction with the environment. What does this study add? Parental psychological control and adolescent aggressive and rule-breaking behaviour exacerbate one another longitudinally. Longitudinal associations between peer rejection and both subtypes of externalizing behaviour are unidirectional. With a polygenic approach, dopaminergic moderation is present for rule-breaking behaviour only. © 2017 The British Psychological Society.

Whole genome prediction and heritability of childhood asthma phenotypes.

PubMed

McGeachie, Michael J; Clemmer, George L; Croteau-Chonka, Damien C; Castaldi, Peter J; Cho, Michael H; Sordillo, Joanne E; Lasky-Su, Jessica A; Raby, Benjamin A; Tantisira, Kelan G; Weiss, Scott T

2016-12-01

While whole genome prediction (WGP) methods have recently demonstrated successes in the prediction of complex genetic diseases, they have not yet been applied to asthma and related phenotypes. Longitudinal patterns of lung function differ between asthmatics, but these phenotypes have not been assessed for heritability or predictive ability. Herein, we assess the heritability and genetic predictability of asthma-related phenotypes. We applied several WGP methods to a well-phenotyped cohort of 832 children with mild-to-moderate asthma from CAMP. We assessed narrow-sense heritability and predictability for airway hyperresponsiveness, serum immunoglobulin E, blood eosinophil count, pre- and post-bronchodilator forced expiratory volume in 1 sec (FEV 1 ), bronchodilator response, steroid responsiveness, and longitudinal patterns of lung function (normal growth, reduced growth, early decline, and their combinations). Prediction accuracy was evaluated using a training/testing set split of the cohort. We found that longitudinal lung function phenotypes demonstrated significant narrow-sense heritability (reduced growth, 95%; normal growth with early decline, 55%). These same phenotypes also showed significant polygenic prediction (areas under the curve [AUCs] 56% to 62%). Including additional demographic covariates in the models increased prediction 4-8%, with reduced growth increasing from 62% to 66% AUC. We found that prediction with a genomic relatedness matrix was improved by filtering available SNPs based on chromatin evidence, and this result extended across cohorts. Longitudinal reduced lung function growth displayed extremely high heritability. All phenotypes with significant heritability showed significant polygenic prediction. Using SNP-prioritization increased prediction across cohorts. WGP methods show promise in predicting asthma-related heritable traits.

Threshold effect under nonlinear limitation of the intensity of high-power light

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tereshchenko, S A; Podgaetskii, V M; Gerasimenko, A Yu

2015-04-30

A model is proposed to describe the properties of limiters of high-power laser radiation, which takes into account the threshold character of nonlinear interaction of radiation with the working medium of the limiter. The generally accepted non-threshold model is a particular case of the threshold model if the threshold radiation intensity is zero. Experimental z-scan data are used to determine the nonlinear optical characteristics of media with carbon nanotubes, polymethine and pyran dyes, zinc selenide, porphyrin-graphene and fullerene-graphene. A threshold effect of nonlinear interaction between laser radiation and some of investigated working media of limiters is revealed. It is shownmore » that the threshold model more adequately describes experimental z-scan data. (nonlinear optical phenomena)« less

Inbreeding Depression and IQ.

ERIC Educational Resources Information Center

Kamin, Leon J.

1980-01-01

This article reviews sex studies of children of cousin marriages and three studies of children of incestuous matings. It is argued that these studies, taken as a whole, provide no substantial evidence for an inbreeding depression effect within the polygenic system commonly asserted to determine IQ. (Author/DB)

Gene Expression Elucidates Functional Impact of Polygenic Risk for Schizophrenia

PubMed Central

Fromer, Menachem; Roussos, Panos; Sieberts, Solveig K; Johnson, Jessica S; Kavanagh, David H; Perumal, Thanneer M; Ruderfer, Douglas M; Oh, Edwin C; Topol, Aaron; Shah, Hardik R; Klei, Lambertus L; Kramer, Robin; Pinto, Dalila; Gümüş, Zeynep H; Cicek, A. Ercument; Dang, Kristen K; Browne, Andrew; Lu, Cong; Xie, Lu; Readhead, Ben; Stahl, Eli A; Parvizi, Mahsa; Hamamsy, Tymor; Fullard, John F; Wang, Ying-Chih; Mahajan, Milind C; Derry, Jonathan M J; Dudley, Joel; Hemby, Scott E; Logsdon, Benjamin A; Talbot, Konrad; Raj, Towfique; Bennett, David A; De Jager, Philip L; Zhu, Jun; Zhang, Bin; Sullivan, Patrick F; Chess, Andrew; Purcell, Shaun M; Shinobu, Leslie A; Mangravite, Lara M; Toyoshiba, Hiroyoshi; Gur, Raquel E; Hahn, Chang-Gyu; Lewis, David A; Haroutunian, Vahram; Peters, Mette A; Lipska, Barbara K; Buxbaum, Joseph D; Schadt, Eric E; Hirai, Keisuke; Roeder, Kathryn; Brennand, Kristen J; Katsanis, Nicholas; Domenici, Enrico; Devlin, Bernie; Sklar, Pamela

2016-01-01

Over 100 genetic loci harbor schizophrenia associated variants, yet how these variants confer liability is uncertain. The CommonMind Consortium sequenced RNA from dorsolateral prefrontal cortex of schizophrenia cases (N = 258) and control subjects (N = 279), creating a resource of gene expression and its genetic regulation. Using this resource, ~20% of schizophrenia loci have variants that could contribute to altered gene expression and liability. In five loci, only a single gene was involved: FURIN, TSNARE1, CNTN4, CLCN3, or SNAP91. Altering expression of FURIN, TSNARE1, or CNTN4 changes neurodevelopment in zebrafish; knockdown of FURIN in human neural progenitor cells yields abnormal migration. Of 693 genes showing significant case/control differential expression, their fold changes are ≤ 1.33, and an independent cohort yields similar results. Gene co-expression implicates a network relevant for schizophrenia. Our findings show schizophrenia is polygenic and highlight the utility of this resource for mechanistic interpretations of genetic liability for brain diseases. PMID:27668389

Gene expression elucidates functional impact of polygenic risk for schizophrenia.

PubMed

Fromer, Menachem; Roussos, Panos; Sieberts, Solveig K; Johnson, Jessica S; Kavanagh, David H; Perumal, Thanneer M; Ruderfer, Douglas M; Oh, Edwin C; Topol, Aaron; Shah, Hardik R; Klei, Lambertus L; Kramer, Robin; Pinto, Dalila; Gümüş, Zeynep H; Cicek, A Ercument; Dang, Kristen K; Browne, Andrew; Lu, Cong; Xie, Lu; Readhead, Ben; Stahl, Eli A; Xiao, Jianqiu; Parvizi, Mahsa; Hamamsy, Tymor; Fullard, John F; Wang, Ying-Chih; Mahajan, Milind C; Derry, Jonathan M J; Dudley, Joel T; Hemby, Scott E; Logsdon, Benjamin A; Talbot, Konrad; Raj, Towfique; Bennett, David A; De Jager, Philip L; Zhu, Jun; Zhang, Bin; Sullivan, Patrick F; Chess, Andrew; Purcell, Shaun M; Shinobu, Leslie A; Mangravite, Lara M; Toyoshiba, Hiroyoshi; Gur, Raquel E; Hahn, Chang-Gyu; Lewis, David A; Haroutunian, Vahram; Peters, Mette A; Lipska, Barbara K; Buxbaum, Joseph D; Schadt, Eric E; Hirai, Keisuke; Roeder, Kathryn; Brennand, Kristen J; Katsanis, Nicholas; Domenici, Enrico; Devlin, Bernie; Sklar, Pamela

2016-11-01

Over 100 genetic loci harbor schizophrenia-associated variants, yet how these variants confer liability is uncertain. The CommonMind Consortium sequenced RNA from dorsolateral prefrontal cortex of people with schizophrenia (N = 258) and control subjects (N = 279), creating a resource of gene expression and its genetic regulation. Using this resource, ∼20% of schizophrenia loci have variants that could contribute to altered gene expression and liability. In five loci, only a single gene was involved: FURIN, TSNARE1, CNTN4, CLCN3 or SNAP91. Altering expression of FURIN, TSNARE1 or CNTN4 changed neurodevelopment in zebrafish; knockdown of FURIN in human neural progenitor cells yielded abnormal migration. Of 693 genes showing significant case-versus-control differential expression, their fold changes were ≤ 1.33, and an independent cohort yielded similar results. Gene co-expression implicates a network relevant for schizophrenia. Our findings show that schizophrenia is polygenic and highlight the utility of this resource for mechanistic interpretations of genetic liability for brain diseases.

Addiction Genetics and Pleiotropic Effects of Common Haplotypes that Make Polygenic Contributions to Vulnerability to Substance Dependence

PubMed Central

Uhl, George R.; Drgon, Tomas; Johnson, Catherine; Liu, Qing-Rong

2016-01-01

Abundant evidence from family, adoption, and twin studies point to large genetic contributions to individual differences in vulnerability to develop dependence on one or more addictive substances. Twin data suggest that most of this genetic vulnerability is shared by individuals who are dependent on a variety of addictive substances. Molecular genetic studies, especially genomewide and candidate gene association studies, have elucidated common haplotypes in dozens of genes that appear to make polygenic contributions to vulnerability to developing dependence. Most genes that harbor currently identified addiction-associated haplotypes are expressed in the brain. Haplotypes in many of the same genes are identified in genomewide association studies that compare allele frequencies in substance dependent vs. control individuals from European, African, and Asian racial/ethnic backgrounds. Many of these addiction-associated haplotypes display pleiotropic influences on a variety of related brain-based phenotypes that display 1) substantial heritability and 2) clinical cooccurence with substance dependence. PMID:19152208

Multigenerational response to artificial selection for biased clutch sex ratios in Tigriopus californicus populations.

PubMed

Alexander, H J; Richardson, J M L; Anholt, B R

2014-09-01

Polygenic sex determination (PSD) is relatively rare and theoretically evolutionary unstable, yet has been reported across a range of taxa. Evidence for multilocus PSD is provided by (i) large between-family variance in sex ratio, (ii) paternal and maternal effects on family sex ratio and (iii) response to selection for family sex ratio. This study tests the polygenic hypothesis of sex determination in the harpacticoid copepod Tigriopus californicus using the criterion of response to selection. We report the first multigenerational quantitative evidence that clutch sex ratio responds to artificial selection in both directions (selection for male- and female-biased families) and in multiple populations of T. californicus. In the five of six lines that showed a response to selection, realized heritability estimated by multigenerational analysis ranged from 0.24 to 0.58. Divergence of clutch sex ratio between selection lines is rapid, with response to selection detectable within the first four generations of selection. © 2014 The Authors. Journal of Evolutionary Biology © 2014 European Society For Evolutionary Biology.

Interaction between Calpain 5, Peroxisome proliferator-activated receptor-gamma and Peroxisome proliferator-activated receptor-delta genes: a polygenic approach to obesity

PubMed Central

Sáez, María E; Grilo, Antonio; Morón, Francisco J; Manzano, Luis; Martínez-Larrad, María T; González-Pérez, Antonio; Serrano-Hernando, Javier; Ruiz, Agustín; Ramírez-Lorca, Reposo; Serrano-Ríos, Manuel

2008-01-01

Context Obesity is a multifactorial disorder, that is, a disease determined by the combined effect of genes and environment. In this context, polygenic approaches are needed. Objective To investigate the possibility of the existence of a crosstalk between the CALPAIN 10 homologue CALPAIN 5 and nuclear receptors of the peroxisome proliferator-activated receptors family. Design Cross-sectional, genetic association study and gene-gene interaction analysis. Subjects The study sample comprise 1953 individuals, 725 obese (defined as body mass index ≥ 30) and 1228 non obese subjects. Results In the monogenic analysis, only the peroxisome proliferator-activated receptor delta (PPARD) gene was associated with obesity (OR = 1.43 [1.04–1.97], p = 0.027). In addition, we have found a significant interaction between CAPN5 and PPARD genes (p = 0.038) that reduces the risk for obesity in a 55%. Conclusion Our results suggest that CAPN5 and PPARD gene products may also interact in vivo. PMID:18657264

Polygenic loading for major depression is associated with specific medical comorbidity

PubMed Central

McCoy, T H; Castro, V M; Snapper, L; Hart, K; Januzzi, J L; Huffman, J C; Perlis, R H

2017-01-01

Major depressive disorder frequently co-occurs with medical disorders, raising the possibility of shared genetic liability. Recent identification of 15 novel genetic loci associated with depression allows direct investigation of this question. In cohorts of individuals participating in biobanks at two academic medical centers, we calculated polygenic loading for risk loci reported to be associated with depression. We then examined the association between such loading and 50 groups of clinical diagnoses, or topics, drawn from these patients' electronic health records, determined using a novel application of latent Dirichilet allocation. Three topics showed experiment-wide association with the depression liability score; these included diagnostic groups representing greater prevalence of mood and anxiety disorders, greater prevalence of cardiac ischemia, and a decreased prevalence of heart failure. The latter two associations persisted even among individuals with no mood disorder diagnosis. This application of a novel method for grouping related diagnoses in biobanks indicate shared genetic risk for depression and cardiac disease, with a pattern suggesting greater ischemic risk and diminished heart failure risk. PMID:28926002

Misbehaving macrophages in the pathogenesis of psoriasis.

PubMed

Clark, Rachael A; Kupper, Thomas S

2006-08-01

Psoriasis is a chronic inflammatory skin disease unique to humans. In this issue of the JCI, 2 studies of very different mouse models of psoriasis both report that macrophages play a key role in inducing psoriasis-like skin disease. Psoriasis is clearly a polygenic, inherited disease of uncontrolled cutaneous inflammation. The debate that currently rages in the field is whether psoriasis is a disease of autoreactive T cells or whether it reflects an intrinsic defect within the skin--or both. However, these questions have proven difficult to dissect using molecular genetic tools. In the current studies, the authors have used 2 different animal models to address the role of macrophages in disease pathogenesis: Wang et al. use a mouse model in which inflammation is T cell dependent, whereas the model used by Stratis et al. is T cell independent (see the related articles beginning on pages 2105 and 2094, respectively). Strikingly, both groups report an important contribution by macrophages, implying that macrophages can contribute to both epithelial-based and T cell-mediated pathways of inflammation.

A Methodology for Phased Array Radar Threshold Modeling Using the Advanced Propagation Model (APM)

DTIC Science & Technology

2017-10-01

TECHNICAL REPORT 3079 October 2017 A Methodology for Phased Array Radar Threshold Modeling Using the Advanced Propagation Model (APM...Head 55190 Networks Division iii EXECUTIVE SUMMARY This report summarizes the methodology developed to improve the radar threshold modeling...PHASED ARRAY RADAR CONFIGURATION ..................................................................... 1 3. METHODOLOGY

A Stratified Transcriptomics Analysis of Polygenic Fat and Lean Mouse Adipose Tissues Identifies Novel Candidate Obesity Genes

PubMed Central

Morton, Nicholas M.; Nelson, Yvonne B.; Michailidou, Zoi; Di Rollo, Emma M.; Ramage, Lynne; Hadoke, Patrick W. F.; Seckl, Jonathan R.; Bunger, Lutz; Horvat, Simon; Kenyon, Christopher J.; Dunbar, Donald R.

2011-01-01

Background Obesity and metabolic syndrome results from a complex interaction between genetic and environmental factors. In addition to brain-regulated processes, recent genome wide association studies have indicated that genes highly expressed in adipose tissue affect the distribution and function of fat and thus contribute to obesity. Using a stratified transcriptome gene enrichment approach we attempted to identify adipose tissue-specific obesity genes in the unique polygenic Fat (F) mouse strain generated by selective breeding over 60 generations for divergent adiposity from a comparator Lean (L) strain. Results To enrich for adipose tissue obesity genes a ‘snap-shot’ pooled-sample transcriptome comparison of key fat depots and non adipose tissues (muscle, liver, kidney) was performed. Known obesity quantitative trait loci (QTL) information for the model allowed us to further filter genes for increased likelihood of being causal or secondary for obesity. This successfully identified several genes previously linked to obesity (C1qr1, and Np3r) as positional QTL candidate genes elevated specifically in F line adipose tissue. A number of novel obesity candidate genes were also identified (Thbs1, Ppp1r3d, Tmepai, Trp53inp2, Ttc7b, Tuba1a, Fgf13, Fmr) that have inferred roles in fat cell function. Quantitative microarray analysis was then applied to the most phenotypically divergent adipose depot after exaggerating F and L strain differences with chronic high fat feeding which revealed a distinct gene expression profile of line, fat depot and diet-responsive inflammatory, angiogenic and metabolic pathways. Selected candidate genes Npr3 and Thbs1, as well as Gys2, a non-QTL gene that otherwise passed our enrichment criteria were characterised, revealing novel functional effects consistent with a contribution to obesity. Conclusions A focussed candidate gene enrichment strategy in the unique F and L model has identified novel adipose tissue-enriched genes contributing to obesity. PMID:21915269

Stability of orbits around planetary satellites considering a disturbing body in an elliptical orbit: Applications to Europa and Ganymede

NASA Astrophysics Data System (ADS)

Cardoso dos Santos, Josué; Carvalho, Jean Paulo; Vilhena de Moraes, Rodolpho

Europa and Ganymede are two of the four Jupiter’s moons which compose the Galilean satellite. These ones are planetary satellites of greater interest at the present moment among the scientific community. There are some missions being planned to visit them and and the Jovian system. One of them is the cooperation between NASA and ESA for the Europa Jupiter System Mission (EJSM). In this mission are planned the insertion of the spacecrafts JEO (Jupiter Europa Orbiter) and JGO (Jupiter Ganymede Orbiter) into Europa and Ganymede’s orbit. Thus, there is a great necessity for having a better comprehension of the dynamics of the orbits around this planetary satellite. This comprehension is essential for the success of this type of mission. In this context, this work aims to perform a search for low-altitude orbits around these planetary satellites. An emphasis is given in polar orbits. These orbits can be useful in the planning of aerospace activities to be conducted around this planetary satellite, with respect to the stability of orbits of artificial satellites. The study considers orbits of an artificial satellite around Europa and Ganymede under the influence of the third-body perturbation (the gravitational attraction of Jupiter) and the polygenic perturbations. These last ones occur due to forces such as the non-uniform distribution of mass (J2 and J3) of the main (central) body. A simplified dynamic model for polygenic perturbations is used. A new model for the third-body disturbance is presented considering it in an elliptical orbit. The Lagrange planetary equations, which compose a system of nonlinear differential equations, are used to describe the orbital motion of the artificial satellite around Ganymede. The equations showed here are developed in closed form to avoid expansions in inclination and eccentricity.

A stratified transcriptomics analysis of polygenic fat and lean mouse adipose tissues identifies novel candidate obesity genes.

PubMed

Morton, Nicholas M; Nelson, Yvonne B; Michailidou, Zoi; Di Rollo, Emma M; Ramage, Lynne; Hadoke, Patrick W F; Seckl, Jonathan R; Bunger, Lutz; Horvat, Simon; Kenyon, Christopher J; Dunbar, Donald R

2011-01-01

Obesity and metabolic syndrome results from a complex interaction between genetic and environmental factors. In addition to brain-regulated processes, recent genome wide association studies have indicated that genes highly expressed in adipose tissue affect the distribution and function of fat and thus contribute to obesity. Using a stratified transcriptome gene enrichment approach we attempted to identify adipose tissue-specific obesity genes in the unique polygenic Fat (F) mouse strain generated by selective breeding over 60 generations for divergent adiposity from a comparator Lean (L) strain. To enrich for adipose tissue obesity genes a 'snap-shot' pooled-sample transcriptome comparison of key fat depots and non adipose tissues (muscle, liver, kidney) was performed. Known obesity quantitative trait loci (QTL) information for the model allowed us to further filter genes for increased likelihood of being causal or secondary for obesity. This successfully identified several genes previously linked to obesity (C1qr1, and Np3r) as positional QTL candidate genes elevated specifically in F line adipose tissue. A number of novel obesity candidate genes were also identified (Thbs1, Ppp1r3d, Tmepai, Trp53inp2, Ttc7b, Tuba1a, Fgf13, Fmr) that have inferred roles in fat cell function. Quantitative microarray analysis was then applied to the most phenotypically divergent adipose depot after exaggerating F and L strain differences with chronic high fat feeding which revealed a distinct gene expression profile of line, fat depot and diet-responsive inflammatory, angiogenic and metabolic pathways. Selected candidate genes Npr3 and Thbs1, as well as Gys2, a non-QTL gene that otherwise passed our enrichment criteria were characterised, revealing novel functional effects consistent with a contribution to obesity. A focussed candidate gene enrichment strategy in the unique F and L model has identified novel adipose tissue-enriched genes contributing to obesity.

A Genome-Wide Association Study Identifies Genetic Variants Associated with Mathematics Ability

PubMed Central

Chen, Huan; Gu, Xiao-hong; Zhou, Yuxi; Ge, Zeng; Wang, Bin; Siok, Wai Ting; Wang, Guoqing; Huen, Michael; Jiang, Yuyang; Tan, Li-Hai; Sun, Yimin

2017-01-01

Mathematics ability is a complex cognitive trait with polygenic heritability. Genome-wide association study (GWAS) has been an effective approach to investigate genetic components underlying mathematic ability. Although previous studies reported several candidate genetic variants, none of them exceeded genome-wide significant threshold in general populations. Herein, we performed GWAS in Chinese elementary school students to identify potential genetic variants associated with mathematics ability. The discovery stage included 494 and 504 individuals from two independent cohorts respectively. The replication stage included another cohort of 599 individuals. In total, 28 of 81 candidate SNPs that met validation criteria were further replicated. Combined meta-analysis of three cohorts identified four SNPs (rs1012694, rs11743006, rs17778739 and rs17777541) of SPOCK1 gene showing association with mathematics ability (minimum p value 5.67 × 10−10, maximum β −2.43). The SPOCK1 gene is located on chromosome 5q31.2 and encodes a highly conserved glycoprotein testican-1 which was associated with tumor progression and prognosis as well as neurogenesis. This is the first study to report genome-wide significant association of individual SNPs with mathematics ability in general populations. Our preliminary results further supported the role of SPOCK1 during neurodevelopment. The genetic complexities underlying mathematics ability might contribute to explain the basis of human cognition and intelligence at genetic level. PMID:28155865

A Genome-Wide Association Study Identifies Genetic Variants Associated with Mathematics Ability.

PubMed

Chen, Huan; Gu, Xiao-Hong; Zhou, Yuxi; Ge, Zeng; Wang, Bin; Siok, Wai Ting; Wang, Guoqing; Huen, Michael; Jiang, Yuyang; Tan, Li-Hai; Sun, Yimin

2017-02-03

Mathematics ability is a complex cognitive trait with polygenic heritability. Genome-wide association study (GWAS) has been an effective approach to investigate genetic components underlying mathematic ability. Although previous studies reported several candidate genetic variants, none of them exceeded genome-wide significant threshold in general populations. Herein, we performed GWAS in Chinese elementary school students to identify potential genetic variants associated with mathematics ability. The discovery stage included 494 and 504 individuals from two independent cohorts respectively. The replication stage included another cohort of 599 individuals. In total, 28 of 81 candidate SNPs that met validation criteria were further replicated. Combined meta-analysis of three cohorts identified four SNPs (rs1012694, rs11743006, rs17778739 and rs17777541) of SPOCK1 gene showing association with mathematics ability (minimum p value 5.67 × 10 -10 , maximum β -2.43). The SPOCK1 gene is located on chromosome 5q31.2 and encodes a highly conserved glycoprotein testican-1 which was associated with tumor progression and prognosis as well as neurogenesis. This is the first study to report genome-wide significant association of individual SNPs with mathematics ability in general populations. Our preliminary results further supported the role of SPOCK1 during neurodevelopment. The genetic complexities underlying mathematics ability might contribute to explain the basis of human cognition and intelligence at genetic level.

Feed efficiency and the microbiota of the alimentary tract

USDA-ARS?s Scientific Manuscript database

There is considerable variation in the efficiency that cattle convert feed for maintenance and product (body weight gain, milk, and conceptus). Both intake and gain are polygenic traits and to better understand factors that contribute to variation in feed efficiency more defined phenotypes are need...

Early Cannabis Use, Polygenic Risk Score for Schizophrenia and Brain Maturation in Adolescence.

PubMed

French, Leon; Gray, Courtney; Leonard, Gabriel; Perron, Michel; Pike, G Bruce; Richer, Louis; Séguin, Jean R; Veillette, Suzanne; Evans, C John; Artiges, Eric; Banaschewski, Tobias; Bokde, Arun W L; Bromberg, Uli; Bruehl, Ruediger; Buchel, Christian; Cattrell, Anna; Conrod, Patricia J; Flor, Herta; Frouin, Vincent; Gallinat, Jurgen; Garavan, Hugh; Gowland, Penny; Heinz, Andreas; Lemaitre, Herve; Martinot, Jean-Luc; Nees, Frauke; Orfanos, Dimitri Papadopoulos; Pangelinan, Melissa Marie; Poustka, Luise; Rietschel, Marcella; Smolka, Michael N; Walter, Henrik; Whelan, Robert; Timpson, Nic J; Schumann, Gunter; Smith, George Davey; Pausova, Zdenka; Paus, Tomáš

2015-10-01

Cannabis use during adolescence is known to increase the risk for schizophrenia in men. Sex differences in the dynamics of brain maturation during adolescence may be of particular importance with regard to vulnerability of the male brain to cannabis exposure. To evaluate whether the association between cannabis use and cortical maturation in adolescents is moderated by a polygenic risk score for schizophrenia. Observation of 3 population-based samples included initial analysis in 1024 adolescents of both sexes from the Canadian Saguenay Youth Study (SYS) and follow-up in 426 adolescents of both sexes from the IMAGEN Study from 8 European cities and 504 male youth from the Avon Longitudinal Study of Parents and Children (ALSPAC) based in England. A total of 1577 participants (aged 12-21 years; 899 [57.0%] male) had (1) information about cannabis use; (2) imaging studies of the brain; and (3) a polygenic risk score for schizophrenia across 108 genetic loci identified by the Psychiatric Genomics Consortium. Data analysis was performed from March 1 through December 31, 2014. Cortical thickness derived from T1-weighted magnetic resonance images. Linear regression tests were used to assess the relationships between cannabis use, cortical thickness, and risk score. Across the 3 samples of 1574 participants, a negative association was observed between cannabis use in early adolescence and cortical thickness in male participants with a high polygenic risk score. This observation was not the case for low-risk male participants or for the low- or high-risk female participants. Thus, in SYS male participants, cannabis use interacted with risk score vis-à-vis cortical thickness (P = .009); higher scores were associated with lower thickness only in males who used cannabis. Similarly, in the IMAGEN male participants, cannabis use interacted with increased risk score vis-à-vis a change in decreasing cortical thickness from 14.5 to 18.5 years of age (t137 = -2.36; P = .02). Finally, in the ALSPAC high-risk group of male participants, those who used cannabis most frequently (≥61 occasions) had lower cortical thickness than those who never used cannabis (difference in cortical thickness, 0.07 [95% CI, 0.01-0.12]; P = .02) and those with light use (<5 occasions) (difference in cortical thickness, 0.11 [95% CI, 0.03-0.18]; P = .004). Cannabis use in early adolescence moderates the association between the genetic risk for schizophrenia and cortical maturation among male individuals. This finding implicates processes underlying cortical maturation in mediating the link between cannabis use and liability to schizophrenia.

Evaluation of polygenic risks for narcolepsy and essential hypersomnia.

PubMed

Yamasaki, Maria; Miyagawa, Taku; Toyoda, Hiromi; Khor, Seik-Soon; Liu, Xiaoxi; Kuwabara, Hitoshi; Kano, Yukiko; Shimada, Takafumi; Sugiyama, Toshiro; Nishida, Hisami; Sugaya, Nagisa; Tochigi, Mamoru; Otowa, Takeshi; Okazaki, Yuji; Kaiya, Hisanobu; Kawamura, Yoshiya; Miyashita, Akinori; Kuwano, Ryozo; Kasai, Kiyoto; Tanii, Hisashi; Sasaki, Tsukasa; Honda, Yutaka; Honda, Makoto; Tokunaga, Katsushi

2016-10-01

In humans, narcolepsy is a sleep disorder that is characterized by sleepiness, cataplexy and rapid eye movement (REM) sleep abnormalities. Essential hypersomnia (EHS) is another type of sleep disorder that is characterized by excessive daytime sleepiness without cataplexy. A human leukocyte antigen (HLA) class II allele, HLA-DQB1*06:02, is a major genetic factor for narcolepsy. Almost all narcoleptic patients are carriers of this HLA allele, while 30-50% of EHS patients and 12% of all healthy individuals in Japan carry this allele. The pathogenesis of narcolepsy and EHS is thought to be partially shared. To evaluate the contribution of common single-nucleotide polymorphisms (SNPs) to narcolepsy onset and to assess the common genetic background of narcolepsy and EHS, we conducted a polygenic analysis that included 393 narcoleptic patients, 38 EHS patients with HLA-DQB1*06:02, 119 EHS patients without HLA-DQB1*06:02 and 1582 healthy individuals. We also included 376 individuals with panic disorder and 213 individuals with autism to confirm whether the results were biased. Polygenic risks in narcolepsy were estimated to explain 58.1% (P HLA-DQB1*06:02 =2.30 × 10 -48 , P whole genome without HLA-DQB1*06:02 =6.73 × 10 -2 ) including HLA-DQB1*06:02 effects and 1.3% (P whole genome without HLA-DQB1*06:02 =2.43 × 10 -2 ) excluding HLA-DQB1*06:02 effects. The results also indicated that small-effect SNPs contributed to the development of narcolepsy. Reported susceptibility SNPs for narcolepsy in the Japanese population, CPT1B (carnitine palmitoyltransferase 1B), TRA@ (T-cell receptor alpha) and P2RY11 (purinergic receptor P2Y, G-protein coupled, 11), were found to explain 0.8% of narcolepsy onset (P whole genome without HLA-DQB1*06:02 =9.74 × 10 -2 ). EHS patients with HLA-DQB1*06:02 were estimated to have higher shared genetic background to narcoleptic patients than EHS patients without HLA-DQB1*06:02 even when the effects of HLA-DQB1*06:02 were excluded (EHS with HLA-DQB1*06:02: 40.4%, P HLA-DQB1*06:02 =7.02 × 10 - 14 , P whole genome without HLA-DQB1*06:02 =1.34 × 10 - 1 , EHS without HLA-DQB1*06:02: 0.4%, P whole genome without HLA-DQB1*06:02 =3.06 × 10 - 1 ). Meanwhile, the polygenic risks for narcolepsy could not explain the onset of panic disorder and autism, suggesting that our results were reasonable.

Spike-Threshold Variability Originated from Separatrix-Crossing in Neuronal Dynamics

PubMed Central

Wang, Longfei; Wang, Hengtong; Yu, Lianchun; Chen, Yong

2016-01-01

The threshold voltage for action potential generation is a key regulator of neuronal signal processing, yet the mechanism of its dynamic variation is still not well described. In this paper, we propose that threshold phenomena can be classified as parameter thresholds and state thresholds. Voltage thresholds which belong to the state threshold are determined by the ‘general separatrix’ in state space. We demonstrate that the separatrix generally exists in the state space of neuron models. The general form of separatrix was assumed as the function of both states and stimuli and the previously assumed threshold evolving equation versus time is naturally deduced from the separatrix. In terms of neuronal dynamics, the threshold voltage variation, which is affected by different stimuli, is determined by crossing the separatrix at different points in state space. We suggest that the separatrix-crossing mechanism in state space is the intrinsic dynamic mechanism for threshold voltages and post-stimulus threshold phenomena. These proposals are also systematically verified in example models, three of which have analytic separatrices and one is the classic Hodgkin-Huxley model. The separatrix-crossing framework provides an overview of the neuronal threshold and will facilitate understanding of the nature of threshold variability. PMID:27546614

Spike-Threshold Variability Originated from Separatrix-Crossing in Neuronal Dynamics.

PubMed

Wang, Longfei; Wang, Hengtong; Yu, Lianchun; Chen, Yong

2016-08-22

The threshold voltage for action potential generation is a key regulator of neuronal signal processing, yet the mechanism of its dynamic variation is still not well described. In this paper, we propose that threshold phenomena can be classified as parameter thresholds and state thresholds. Voltage thresholds which belong to the state threshold are determined by the 'general separatrix' in state space. We demonstrate that the separatrix generally exists in the state space of neuron models. The general form of separatrix was assumed as the function of both states and stimuli and the previously assumed threshold evolving equation versus time is naturally deduced from the separatrix. In terms of neuronal dynamics, the threshold voltage variation, which is affected by different stimuli, is determined by crossing the separatrix at different points in state space. We suggest that the separatrix-crossing mechanism in state space is the intrinsic dynamic mechanism for threshold voltages and post-stimulus threshold phenomena. These proposals are also systematically verified in example models, three of which have analytic separatrices and one is the classic Hodgkin-Huxley model. The separatrix-crossing framework provides an overview of the neuronal threshold and will facilitate understanding of the nature of threshold variability.

A threshold method for immunological correlates of protection

PubMed Central

2013-01-01

Background Immunological correlates of protection are biological markers such as disease-specific antibodies which correlate with protection against disease and which are measurable with immunological assays. It is common in vaccine research and in setting immunization policy to rely on threshold values for the correlate where the accepted threshold differentiates between individuals who are considered to be protected against disease and those who are susceptible. Examples where thresholds are used include development of a new generation 13-valent pneumococcal conjugate vaccine which was required in clinical trials to meet accepted thresholds for the older 7-valent vaccine, and public health decision making on vaccination policy based on long-term maintenance of protective thresholds for Hepatitis A, rubella, measles, Japanese encephalitis and others. Despite widespread use of such thresholds in vaccine policy and research, few statistical approaches have been formally developed which specifically incorporate a threshold parameter in order to estimate the value of the protective threshold from data. Methods We propose a 3-parameter statistical model called the a:b model which incorporates parameters for a threshold and constant but different infection probabilities below and above the threshold estimated using profile likelihood or least squares methods. Evaluation of the estimated threshold can be performed by a significance test for the existence of a threshold using a modified likelihood ratio test which follows a chi-squared distribution with 3 degrees of freedom, and confidence intervals for the threshold can be obtained by bootstrapping. The model also permits assessment of relative risk of infection in patients achieving the threshold or not. Goodness-of-fit of the a:b model may be assessed using the Hosmer-Lemeshow approach. The model is applied to 15 datasets from published clinical trials on pertussis, respiratory syncytial virus and varicella. Results Highly significant thresholds with p-values less than 0.01 were found for 13 of the 15 datasets. Considerable variability was seen in the widths of confidence intervals. Relative risks indicated around 70% or better protection in 11 datasets and relevance of the estimated threshold to imply strong protection. Goodness-of-fit was generally acceptable. Conclusions The a:b model offers a formal statistical method of estimation of thresholds differentiating susceptible from protected individuals which has previously depended on putative statements based on visual inspection of data. PMID:23448322

Nonlinear Dynamic Modeling of Neuron Action Potential Threshold During Synaptically Driven Broadband Intracellular Activity

PubMed Central

Roach, Shane M.; Song, Dong; Berger, Theodore W.

2012-01-01

Activity-dependent variation of neuronal thresholds for action potential (AP) generation is one of the key determinants of spike-train temporal-pattern transformations from presynaptic to postsynaptic spike trains. In this study, we model the nonlinear dynamics of the threshold variation during synaptically driven broadband intracellular activity. First, membrane potentials of single CA1 pyramidal cells were recorded under physiologically plausible broadband stimulation conditions. Second, a method was developed to measure AP thresholds from the continuous recordings of membrane potentials. It involves measuring the turning points of APs by analyzing the third-order derivatives of the membrane potentials. Four stimulation paradigms with different temporal patterns were applied to validate this method by comparing the measured AP turning points and the actual AP thresholds estimated with varying stimulation intensities. Results show that the AP turning points provide consistent measurement of the AP thresholds, except for a constant offset. It indicates that 1) the variation of AP turning points represents the nonlinearities of threshold dynamics; and 2) an optimization of the constant offset is required to achieve accurate spike prediction. Third, a nonlinear dynamical third-order Volterra model was built to describe the relations between the threshold dynamics and the AP activities. Results show that the model can predict threshold accurately based on the preceding APs. Finally, the dynamic threshold model was integrated into a previously developed single neuron model and resulted in a 33% improvement in spike prediction. PMID:22156947

A critique of the use of indicator-species scores for identifying thresholds in species responses

USGS Publications Warehouse

Cuffney, Thomas F.; Qian, Song S.

2013-01-01

Identification of ecological thresholds is important both for theoretical and applied ecology. Recently, Baker and King (2010, King and Baker 2010) proposed a method, threshold indicator analysis (TITAN), to calculate species and community thresholds based on indicator species scores adapted from Dufrêne and Legendre (1997). We tested the ability of TITAN to detect thresholds using models with (broken-stick, disjointed broken-stick, dose-response, step-function, Gaussian) and without (linear) definitive thresholds. TITAN accurately and consistently detected thresholds in step-function models, but not in models characterized by abrupt changes in response slopes or response direction. Threshold detection in TITAN was very sensitive to the distribution of 0 values, which caused TITAN to identify thresholds associated with relatively small differences in the distribution of 0 values while ignoring thresholds associated with large changes in abundance. Threshold identification and tests of statistical significance were based on the same data permutations resulting in inflated estimates of statistical significance. Application of bootstrapping to the split-point problem that underlies TITAN led to underestimates of the confidence intervals of thresholds. Bias in the derivation of the z-scores used to identify TITAN thresholds and skewedness in the distribution of data along the gradient produced TITAN thresholds that were much more similar than the actual thresholds. This tendency may account for the synchronicity of thresholds reported in TITAN analyses. The thresholds identified by TITAN represented disparate characteristics of species responses that, when coupled with the inability of TITAN to identify thresholds accurately and consistently, does not support the aggregation of individual species thresholds into a community threshold.

Combining quantitative trait loci analysis with physiological models to predict genotype-specific transpiration rates.

PubMed

Reuning, Gretchen A; Bauerle, William L; Mullen, Jack L; McKay, John K

2015-04-01

Transpiration is controlled by evaporative demand and stomatal conductance (gs ), and there can be substantial genetic variation in gs . A key parameter in empirical models of transpiration is minimum stomatal conductance (g0 ), a trait that can be measured and has a large effect on gs and transpiration. In Arabidopsis thaliana, g0 exhibits both environmental and genetic variation, and quantitative trait loci (QTL) have been mapped. We used this information to create a genetically parameterized empirical model to predict transpiration of genotypes. For the parental lines, this worked well. However, in a recombinant inbred population, the predictions proved less accurate. When based only upon their genotype at a single g0 QTL, genotypes were less distinct than our model predicted. Follow-up experiments indicated that both genotype by environment interaction and a polygenic inheritance complicate the application of genetic effects into physiological models. The use of ecophysiological or 'crop' models for predicting transpiration of novel genetic lines will benefit from incorporating further knowledge of the genetic control and degree of independence of core traits/parameters underlying gs variation. © 2014 John Wiley & Sons Ltd.

Use of the FDA nozzle model to illustrate validation techniques in computational fluid dynamics (CFD) simulations

PubMed Central

Hariharan, Prasanna; D’Souza, Gavin A.; Horner, Marc; Morrison, Tina M.; Malinauskas, Richard A.; Myers, Matthew R.

2017-01-01

A “credible” computational fluid dynamics (CFD) model has the potential to provide a meaningful evaluation of safety in medical devices. One major challenge in establishing “model credibility” is to determine the required degree of similarity between the model and experimental results for the model to be considered sufficiently validated. This study proposes a “threshold-based” validation approach that provides a well-defined acceptance criteria, which is a function of how close the simulation and experimental results are to the safety threshold, for establishing the model validity. The validation criteria developed following the threshold approach is not only a function of Comparison Error, E (which is the difference between experiments and simulations) but also takes in to account the risk to patient safety because of E. The method is applicable for scenarios in which a safety threshold can be clearly defined (e.g., the viscous shear-stress threshold for hemolysis in blood contacting devices). The applicability of the new validation approach was tested on the FDA nozzle geometry. The context of use (COU) was to evaluate if the instantaneous viscous shear stress in the nozzle geometry at Reynolds numbers (Re) of 3500 and 6500 was below the commonly accepted threshold for hemolysis. The CFD results (“S”) of velocity and viscous shear stress were compared with inter-laboratory experimental measurements (“D”). The uncertainties in the CFD and experimental results due to input parameter uncertainties were quantified following the ASME V&V 20 standard. The CFD models for both Re = 3500 and 6500 could not be sufficiently validated by performing a direct comparison between CFD and experimental results using the Student’s t-test. However, following the threshold-based approach, a Student’s t-test comparing |S-D| and |Threshold-S| showed that relative to the threshold, the CFD and experimental datasets for Re = 3500 were statistically similar and the model could be considered sufficiently validated for the COU. However, for Re = 6500, at certain locations where the shear stress is close the hemolysis threshold, the CFD model could not be considered sufficiently validated for the COU. Our analysis showed that the model could be sufficiently validated either by reducing the uncertainties in experiments, simulations, and the threshold or by increasing the sample size for the experiments and simulations. The threshold approach can be applied to all types of computational models and provides an objective way of determining model credibility and for evaluating medical devices. PMID:28594889

Use of the FDA nozzle model to illustrate validation techniques in computational fluid dynamics (CFD) simulations.

PubMed

Hariharan, Prasanna; D'Souza, Gavin A; Horner, Marc; Morrison, Tina M; Malinauskas, Richard A; Myers, Matthew R

2017-01-01

A "credible" computational fluid dynamics (CFD) model has the potential to provide a meaningful evaluation of safety in medical devices. One major challenge in establishing "model credibility" is to determine the required degree of similarity between the model and experimental results for the model to be considered sufficiently validated. This study proposes a "threshold-based" validation approach that provides a well-defined acceptance criteria, which is a function of how close the simulation and experimental results are to the safety threshold, for establishing the model validity. The validation criteria developed following the threshold approach is not only a function of Comparison Error, E (which is the difference between experiments and simulations) but also takes in to account the risk to patient safety because of E. The method is applicable for scenarios in which a safety threshold can be clearly defined (e.g., the viscous shear-stress threshold for hemolysis in blood contacting devices). The applicability of the new validation approach was tested on the FDA nozzle geometry. The context of use (COU) was to evaluate if the instantaneous viscous shear stress in the nozzle geometry at Reynolds numbers (Re) of 3500 and 6500 was below the commonly accepted threshold for hemolysis. The CFD results ("S") of velocity and viscous shear stress were compared with inter-laboratory experimental measurements ("D"). The uncertainties in the CFD and experimental results due to input parameter uncertainties were quantified following the ASME V&V 20 standard. The CFD models for both Re = 3500 and 6500 could not be sufficiently validated by performing a direct comparison between CFD and experimental results using the Student's t-test. However, following the threshold-based approach, a Student's t-test comparing |S-D| and |Threshold-S| showed that relative to the threshold, the CFD and experimental datasets for Re = 3500 were statistically similar and the model could be considered sufficiently validated for the COU. However, for Re = 6500, at certain locations where the shear stress is close the hemolysis threshold, the CFD model could not be considered sufficiently validated for the COU. Our analysis showed that the model could be sufficiently validated either by reducing the uncertainties in experiments, simulations, and the threshold or by increasing the sample size for the experiments and simulations. The threshold approach can be applied to all types of computational models and provides an objective way of determining model credibility and for evaluating medical devices.

Assessing regional and interspecific variation in threshold responses of forest breeding birds through broad scale analyses.

PubMed

van der Hoek, Yntze; Renfrew, Rosalind; Manne, Lisa L

2013-01-01

Identifying persistence and extinction thresholds in species-habitat relationships is a major focal point of ecological research and conservation. However, one major concern regarding the incorporation of threshold analyses in conservation is the lack of knowledge on the generality and transferability of results across species and regions. We present a multi-region, multi-species approach of modeling threshold responses, which we use to investigate whether threshold effects are similar across species and regions. We modeled local persistence and extinction dynamics of 25 forest-associated breeding birds based on detection/non-detection data, which were derived from repeated breeding bird atlases for the state of Vermont. We did not find threshold responses to be particularly well-supported, with 9 species supporting extinction thresholds and 5 supporting persistence thresholds. This contrasts with a previous study based on breeding bird atlas data from adjacent New York State, which showed that most species support persistence and extinction threshold models (15 and 22 of 25 study species respectively). In addition, species that supported a threshold model in both states had associated average threshold estimates of 61.41% (SE = 6.11, persistence) and 66.45% (SE = 9.15, extinction) in New York, compared to 51.08% (SE = 10.60, persistence) and 73.67% (SE = 5.70, extinction) in Vermont. Across species, thresholds were found at 19.45-87.96% forest cover for persistence and 50.82-91.02% for extinction dynamics. Through an approach that allows for broad-scale comparisons of threshold responses, we show that species vary in their threshold responses with regard to habitat amount, and that differences between even nearby regions can be pronounced. We present both ecological and methodological factors that may contribute to the different model results, but propose that regardless of the reasons behind these differences, our results merit a warning that threshold values cannot simply be transferred across regions or interpreted as clear-cut targets for ecosystem management and conservation.

Genome-wide association mapping of partial resistance to Aphanomyces euteiches in pea

USDA-ARS?s Scientific Manuscript database

Genome-wide association mapping has recently emerged as a valuable approach to refine genetic basis of polygenic resistance to plant diseases, which are increasingly used in integrated strategies for durable crop protection. Aphanomyces euteiches is a soil borne pathogen of pea and other legumes wor...

Modelling the regulatory system for diabetes mellitus with a threshold window

NASA Astrophysics Data System (ADS)

Yang, Jin; Tang, Sanyi; Cheke, Robert A.

2015-05-01

Piecewise (or non-smooth) glucose-insulin models with threshold windows for type 1 and type 2 diabetes mellitus are proposed and analyzed with a view to improving understanding of the glucose-insulin regulatory system. For glucose-insulin models with a single threshold, the existence and stability of regular, virtual, pseudo-equilibria and tangent points are addressed. Then the relations between regular equilibria and a pseudo-equilibrium are studied. Furthermore, the sufficient and necessary conditions for the global stability of regular equilibria and the pseudo-equilibrium are provided by using qualitative analysis techniques of non-smooth Filippov dynamic systems. Sliding bifurcations related to boundary node bifurcations were investigated with theoretical and numerical techniques, and insulin clinical therapies are discussed. For glucose-insulin models with a threshold window, the effects of glucose thresholds or the widths of threshold windows on the durations of insulin therapy and glucose infusion were addressed. The duration of the effects of an insulin injection is sensitive to the variation of thresholds. Our results indicate that blood glucose level can be maintained within a normal range using piecewise glucose-insulin models with a single threshold or a threshold window. Moreover, our findings suggest that it is critical to individualise insulin therapy for each patient separately, based on initial blood glucose levels.

Genetic variants in Alzheimer disease – molecular and brain network approaches

PubMed Central

Gaiteri, Chris; Mostafavi, Sara; Honey, Christopher; De Jager, Philip L.; Bennett, David A.

2016-01-01

Genetic studies in late-onset Alzheimer disease (LOAD) are aimed at identifying core disease mechanisms and providing potential biomarkers and drug candidates to improve clinical care for AD. However, due to the complexity of LOAD, including pathological heterogeneity and disease polygenicity, extracting actionable guidance from LOAD genetics has been challenging. Past attempts to summarize the effects of LOAD-associated genetic variants have used pathway analysis and collections of small-scale experiments to hypothesize functional convergence across several variants. In this review, we discuss how the study of molecular, cellular and brain networks provides additional information on the effect of LOAD-associated genetic variants. We then discuss emerging combinations of omic data types in multiscale models, which provide a more comprehensive representation of the effect of LOAD-associated genetic variants at multiple biophysical scales. Further, we highlight the clinical potential of mechanistically coupling genetic variants and disease phenotypes with multiscale brain models. PMID:27282653

A generalized methodology for identification of threshold for HRU delineation in SWAT model

NASA Astrophysics Data System (ADS)

M, J.; Sudheer, K.; Chaubey, I.; Raj, C.

2016-12-01

The distributed hydrological model, Soil and Water Assessment Tool (SWAT) is a comprehensive hydrologic model widely used for making various decisions. The simulation accuracy of the distributed hydrological model differs due to the mechanism involved in the subdivision of the watershed. Soil and Water Assessment Tool (SWAT) considers sub-dividing the watershed and the sub-basins into small computing units known as 'hydrologic response units (HRU). The delineation of HRU is done based on unique combinations of land use, soil types, and slope within the sub-watersheds, which are not spatially defined. The computations in SWAT are done at HRU level and are then aggregated up to the sub-basin outlet, which is routed through the stream system. Generally, the HRUs are delineated by considering a threshold percentage of land use, soil and slope are to be given by the modeler to decrease the computation time of the model. The thresholds constrain the minimum area for constructing an HRU. In the current HRU delineation practice in SWAT, the land use, soil and slope of the watershed within a sub-basin, which is less than the predefined threshold, will be surpassed by the dominating land use, soil and slope, and introduce some level of ambiguity in the process simulations in terms of inappropriate representation of the area. But the loss of information due to variation in the threshold values depends highly on the purpose of the study. Therefore this research studies the effects of threshold values of HRU delineation on the hydrological modeling of SWAT on sediment simulations and suggests guidelines for selecting the appropriate threshold values considering the sediment simulation accuracy. The preliminary study was done on Illinois watershed by assigning different thresholds for land use and soil. A general methodology was proposed for identifying an appropriate threshold for HRU delineation in SWAT model that considered computational time and accuracy of the simulation. The methodology can be adopted for identifying an appropriate threshold for SWAT model simulation in any watershed with a single simulation of the model with a zero-zero threshold.

Patterns of threshold evolution in polyphenic insects under different developmental models.

PubMed

Tomkins, Joseph L; Moczek, Armin P

2009-02-01

Two hypotheses address the evolution of polyphenic traits in insects. Under the developmental reprogramming model, individuals exceeding a threshold follow a different developmental pathway from individuals below the threshold. This decoupling is thought to free selection to independently hone alternative morphologies, increasing phenotypic plasticity and morphological diversity. Under the alternative model, extreme positive allometry explains the existence of alternative phenotypes and divergent phenotypes are developmentally coupled by a continuous reaction norm, such that selection on either morph acts on both. We test the hypothesis that continuous reaction norm polyphenisms, evolve through changes in the allometric parameters of even the smallest males with minimal trait expression, whereas threshold polyphenisms evolve independent of the allometric parameters of individuals below the threshold. We compare two polyphenic species; the dung beetle Onthophagus taurus, whose allometry has been modeled both as a threshold polyphenism and a continuous reaction norm and the earwig Forficula auricularia, whose allometry is best modeled with a discontinuous threshold. We find that across populations of both species, variation in forceps or horn allometry in minor males are correlated to the population's threshold. These findings suggest that regardless of developmental mode, alternative morphs do not evolve independently of one another.

Variable-Threshold Threshold Elements,

DTIC Science & Technology

A threshold element is a mathematical model of certain types of logic gates and of a biological neuron. Much work has been done on the subject of... threshold elements with fixed thresholds; this study concerns itself with elements in which the threshold may be varied, variable- threshold threshold ...elements. Physical realizations include resistor-transistor elements, in which the threshold is simply a voltage. Variation of the threshold causes the

Development and validation of a prediction model for measurement variability of lung nodule volumetry in patients with pulmonary metastases.

PubMed

Hwang, Eui Jin; Goo, Jin Mo; Kim, Jihye; Park, Sang Joon; Ahn, Soyeon; Park, Chang Min; Shin, Yeong-Gil

2017-08-01

To develop a prediction model for the variability range of lung nodule volumetry and validate the model in detecting nodule growth. For model development, 50 patients with metastatic nodules were prospectively included. Two consecutive CT scans were performed to assess volumetry for 1,586 nodules. Nodule volume, surface voxel proportion (SVP), attachment proportion (AP) and absolute percentage error (APE) were calculated for each nodule and quantile regression analyses were performed to model the 95% percentile of APE. For validation, 41 patients who underwent metastasectomy were included. After volumetry of resected nodules, sensitivity and specificity for diagnosis of metastatic nodules were compared between two different thresholds of nodule growth determination: uniform 25% volume change threshold and individualized threshold calculated from the model (estimated 95% percentile APE). SVP and AP were included in the final model: Estimated 95% percentile APE = 37.82 · SVP + 48.60 · AP-10.87. In the validation session, the individualized threshold showed significantly higher sensitivity for diagnosis of metastatic nodules than the uniform 25% threshold (75.0% vs. 66.0%, P = 0.004) CONCLUSION: Estimated 95% percentile APE as an individualized threshold of nodule growth showed greater sensitivity in diagnosing metastatic nodules than a global 25% threshold. • The 95 % percentile APE of a particular nodule can be predicted. • Estimated 95 % percentile APE can be utilized as an individualized threshold. • More sensitive diagnosis of metastasis can be made with an individualized threshold. • Tailored nodule management can be provided during nodule growth follow-up.

Application of linear mixed models to study genetic stability of height and body mass index across countries and time.

PubMed

Trzaskowski, Maciej; Lichtenstein, Paul; Magnusson, Patrik K; Pedersen, Nancy L; Plomin, Robert

2016-01-27

It is now possible to estimate genetic correlations between two independent samples when there is no overlapping phenotypic information. We applied the latest bivariate genomic methods to children in the UK and older adults in Sweden to ask two questions. Are the same variants driving individual differences in anthropometric traits in these two populations, and are these variants as important in childhood as they are later in life? A sample of 3152 11-year-old children in the UK was compared with a sample of 6813 adults with an average age of 65 in Sweden. Genotypes were imputed from 1000 genomes with combined 9 767 136 single nucleotide polymorphisms meeting quality control criteria in both samples. Two cross-sample GCTA-GREML analyses and linkage disequilibrium (LD) score regressions were conducted to assess genetic correlations across more than 50 years: child versus adult height and child versus adult body mass index (BMI). Consistency of effects was tested using the recently proposed polygenic scoring method. For height, GCTA-GREML and LD score indicated strong genetic stability between children and adults, 0.58 (0.16) and 1.335 (1.09), respectively. For BMI, both methods produced similarly strong estimates of genetic stability 0.75 (0.26) and 0.855 (0.49), respectively. In height, adult polygenic score explained 60% of genetic variance in childhood and 10% of variance in BMI. Here we replicated and extended previous findings of longitudinal genetic stability in anthropometric traits to cross-cultural dimensions, and showed that for height but not BMI these variants are as important in childhood as they are in adulthood. © The Author 2016. Published by Oxford University Press on behalf of the International Epidemiological Association.

Two candidate genes for two quantitative trait loci epistatically attenuate hypertension in a novel pathway.

PubMed

Chauvet, Cristina; Ménard, Annie; Deng, Alan Y

2015-09-01

Multiple quantitative trait loci (QTLs) for blood pressure (BP) have been detected in rat models of human polygenic hypertension. They influence BP physiologically via epistatic modules. Little is known about the causal genes and virtually nothing is known on modularized mechanisms governing their regulatory connections. Two genes responsible for two individual BP QTLs on rat Chromosome 18 have been identified that belong to the same epistatic module. Treacher Collins-Franceschetti syndrome 1 (Tcof1) gene is the only function candidate for C18QTL3. Haloacid dehalogenase like hydrolase domain containing 2 (Hdhd2), although a gene of previously unknown function, is C18QTL4, and encodes a newly identified phosphatase. The current work has provided the premier evidence that Hdhd2/C18QTL4 and Tcof1/C18QTL3 may be involved in polygenic hypertension. Hdhd2/C18QTL4 can regulate the function of Tcof1/C18QTL3 via de-phosphorylation, and, for the first time, furbishes a molecular mechanism in support of a genetically epistatic hierarchy between two BP QTLs, and thus authenticates the epistasis-common pathway paradigm. The pathway initiated by Hdhd2/C18QTL4 upstream of Tcof1/C18QTL3 reveals novel mechanistic insights into BP modulations. Their discovery might yield innovative therapeutic targets and diagnostic tools predicated on a novel BP cause and mechanism that is determined by a regulatory hierarchy. Optimizing the de-phosphorylation capability and its downstream target could be antihypertensive. The conceptual paradigm of an order and regulatory hierarchy may help unravel genetic and molecular relationships among certain human BP QTLs.

PEPIS: A Pipeline for Estimating Epistatic Effects in Quantitative Trait Locus Mapping and Genome-Wide Association Studies.

PubMed

Zhang, Wenchao; Dai, Xinbin; Wang, Qishan; Xu, Shizhong; Zhao, Patrick X

2016-05-01

The term epistasis refers to interactions between multiple genetic loci. Genetic epistasis is important in regulating biological function and is considered to explain part of the 'missing heritability,' which involves marginal genetic effects that cannot be accounted for in genome-wide association studies. Thus, the study of epistasis is of great interest to geneticists. However, estimating epistatic effects for quantitative traits is challenging due to the large number of interaction effects that must be estimated, thus significantly increasing computing demands. Here, we present a new web server-based tool, the Pipeline for estimating EPIStatic genetic effects (PEPIS), for analyzing polygenic epistatic effects. The PEPIS software package is based on a new linear mixed model that has been used to predict the performance of hybrid rice. The PEPIS includes two main sub-pipelines: the first for kinship matrix calculation, and the second for polygenic component analyses and genome scanning for main and epistatic effects. To accommodate the demand for high-performance computation, the PEPIS utilizes C/C++ for mathematical matrix computing. In addition, the modules for kinship matrix calculations and main and epistatic-effect genome scanning employ parallel computing technology that effectively utilizes multiple computer nodes across our networked cluster, thus significantly improving the computational speed. For example, when analyzing the same immortalized F2 rice population genotypic data examined in a previous study, the PEPIS returned identical results at each analysis step with the original prototype R code, but the computational time was reduced from more than one month to about five minutes. These advances will help overcome the bottleneck frequently encountered in genome wide epistatic genetic effect analysis and enable accommodation of the high computational demand. The PEPIS is publically available at http://bioinfo.noble.org/PolyGenic_QTL/.

Association of polygenic risk score with the risk of chronic lymphocytic leukemia and monoclonal B-cell lymphocytosis.

PubMed

Kleinstern, Geffen; Camp, Nicola J; Goldin, Lynn R; Vachon, Celine M; Vajdic, Claire M; de Sanjose, Silvia; Weinberg, J Brice; Benavente, Yolanda; Casabonne, Delphine; Liebow, Mark; Nieters, Alexandra; Hjalgrim, Henrik; Melbye, Mads; Glimelius, Bengt; Adami, Hans-Olov; Boffetta, Paolo; Brennan, Paul; Maynadie, Marc; McKay, James; Cocco, Pier Luigi; Shanafelt, Tait D; Call, Timothy G; Norman, Aaron D; Hanson, Curtis; Robinson, Dennis; Chaffee, Kari G; Brooks-Wilson, Angela R; Monnereau, Alain; Clavel, Jacqueline; Glenn, Martha; Curtin, Karen; Conde, Lucia; Bracci, Paige M; Morton, Lindsay M; Cozen, Wendy; Severson, Richard K; Chanock, Stephen J; Spinelli, John J; Johnston, James B; Rothman, Nathaniel; Skibola, Christine F; Leis, Jose F; Kay, Neil E; Smedby, Karin E; Berndt, Sonja I; Cerhan, James R; Caporaso, Neil; Slager, Susan L

2018-06-07

Inherited loci have been found to be associated with risk of chronic lymphocytic leukemia (CLL). A combined polygenic risk score (PRS) of representative single nucleotide polymorphisms (SNPs) from these loci may improve risk prediction over individual SNPs. Herein, we evaluated the association of a PRS with CLL risk and its precursor, monoclonal B-cell lymphocytosis (MBL). We assessed its validity and discriminative ability in an independent sample and evaluated effect modification and confounding by family history (FH) of hematological cancers. For discovery, we pooled genotype data on 41 representative SNPs from 1499 CLL and 2459 controls from the InterLymph Consortium. For validation, we used data from 1267 controls from Mayo Clinic and 201 CLL, 95 MBL, and 144 controls with a FH of CLL from the Genetic Epidemiology of CLL Consortium. We used odds ratios (ORs) to estimate disease associations with PRS and c-statistics to assess discriminatory accuracy. In InterLymph, the continuous PRS was strongly associated with CLL risk (OR, 2.49; P = 4.4 × 10 -94 ). We replicated these findings in the Genetic Epidemiology of CLL Consortium and Mayo controls (OR, 3.02; P = 7.8 × 10 -30 ) and observed high discrimination (c-statistic = 0.78). When jointly modeled with FH, PRS retained its significance, along with FH status. Finally, we found a highly significant association of the continuous PRS with MBL risk (OR, 2.81; P = 9.8 × 10 -16 ). In conclusion, our validated PRS was strongly associated with CLL risk, adding information beyond FH. The PRS provides a means of identifying those individuals at greater risk for CLL as well as those at increased risk of MBL, a condition that has potential clinical impact beyond CLL.

Cardiorespiratory fitness alters the influence of a polygenic risk score on biomarkers of AD.

PubMed

Schultz, Stephanie A; Boots, Elizabeth A; Darst, Burcu F; Zetterberg, Henrik; Blennow, Kaj; Edwards, Dorothy F; Koscik, Rebecca L; Carlsson, Cynthia M; Gallagher, Catherine L; Bendlin, Barbara B; Asthana, Sanjay; Sager, Mark A; Hogan, Kirk J; Hermann, Bruce P; Cook, Dane B; Johnson, Sterling C; Engelman, Corinne D; Okonkwo, Ozioma C

2017-04-25

To examine whether a polygenic risk score (PRS) derived from APOE4, CLU, and ABCA7 is associated with CSF biomarkers of Alzheimer disease (AD) pathology and whether higher cardiorespiratory fitness (CRF) modifies the association between the PRS and CSF biomarkers. Ninety-five individuals from the Wisconsin Registry for Alzheimer's Prevention were included in these cross-sectional analyses. They were genotyped for APOE4 , CLU , and ABCA7 , from which a PRS was calculated for each participant. The participants underwent lumbar puncture for CSF collection. β-Amyloid 42 (Aβ 42 ), Aβ 40 , total tau (t-tau), and phosphorylated tau (p-tau) were quantified by immunoassays, and Aβ 42 /Aβ 40 and tau/Aβ 42 ratios were computed. CRF was estimated from a validated equation incorporating sex, age, body mass index, resting heart rate, and self-reported physical activity. Covariate-adjusted regression analyses were used to test for associations between the PRS and CSF biomarkers. In addition, by including a PRS×CRF term in the models, we examined whether these associations were modified by CRF. A higher PRS was associated with lower Aβ 42 /Aβ 40 ( p < 0.001), higher t-tau/Aβ 42 ( p = 0.012), and higher p-tau/Aβ 42 ( p = 0.040). Furthermore, we observed PRS × CRF interactions for Aβ 42 /Aβ 40 ( p = 0.003), t-tau/Aβ 42 ( p = 0.003), and p-tau/Aβ 42 ( p = 0.001). Specifically, the association between the PRS and these CSF biomarkers was diminished in those with higher CRF. In a late-middle-aged cohort, CRF attenuates the adverse influence of genetic vulnerability on CSF biomarkers. These findings support the notion that increased cardiorespiratory fitness may be beneficial to those at increased genetic risk for AD. © 2017 American Academy of Neurology.

The Random-Threshold Generalized Unfolding Model and Its Application of Computerized Adaptive Testing

ERIC Educational Resources Information Center

Wang, Wen-Chung; Liu, Chen-Wei; Wu, Shiu-Lien

2013-01-01

The random-threshold generalized unfolding model (RTGUM) was developed by treating the thresholds in the generalized unfolding model as random effects rather than fixed effects to account for the subjective nature of the selection of categories in Likert items. The parameters of the new model can be estimated with the JAGS (Just Another Gibbs…

Verification of the tumor volume delineation method using a fixed threshold of peak standardized uptake value.

PubMed

Koyama, Kazuya; Mitsumoto, Takuya; Shiraishi, Takahiro; Tsuda, Keisuke; Nishiyama, Atsushi; Inoue, Kazumasa; Yoshikawa, Kyosan; Hatano, Kazuo; Kubota, Kazuo; Fukushi, Masahiro

2017-09-01

We aimed to determine the difference in tumor volume associated with the reconstruction model in positron-emission tomography (PET). To reduce the influence of the reconstruction model, we suggested a method to measure the tumor volume using the relative threshold method with a fixed threshold based on peak standardized uptake value (SUV peak ). The efficacy of our method was verified using 18 F-2-fluoro-2-deoxy-D-glucose PET/computed tomography images of 20 patients with lung cancer. The tumor volume was determined using the relative threshold method with a fixed threshold based on the SUV peak . The PET data were reconstructed using the ordered-subset expectation maximization (OSEM) model, the OSEM + time-of-flight (TOF) model, and the OSEM + TOF + point-spread function (PSF) model. The volume differences associated with the reconstruction algorithm (%VD) were compared. For comparison, the tumor volume was measured using the relative threshold method based on the maximum SUV (SUV max ). For the OSEM and TOF models, the mean %VD values were -0.06 ± 8.07 and -2.04 ± 4.23% for the fixed 40% threshold according to the SUV max and the SUV peak, respectively. The effect of our method in this case seemed to be minor. For the OSEM and PSF models, the mean %VD values were -20.41 ± 14.47 and -13.87 ± 6.59% for the fixed 40% threshold according to the SUV max and SUV peak , respectively. Our new method enabled the measurement of tumor volume with a fixed threshold and reduced the influence of the changes in tumor volume associated with the reconstruction model.

Assessing Regional and Interspecific Variation in Threshold Responses of Forest Breeding Birds through Broad Scale Analyses

PubMed Central

van der Hoek, Yntze; Renfrew, Rosalind; Manne, Lisa L.

2013-01-01

Background Identifying persistence and extinction thresholds in species-habitat relationships is a major focal point of ecological research and conservation. However, one major concern regarding the incorporation of threshold analyses in conservation is the lack of knowledge on the generality and transferability of results across species and regions. We present a multi-region, multi-species approach of modeling threshold responses, which we use to investigate whether threshold effects are similar across species and regions. Methodology/Principal Findings We modeled local persistence and extinction dynamics of 25 forest-associated breeding birds based on detection/non-detection data, which were derived from repeated breeding bird atlases for the state of Vermont. We did not find threshold responses to be particularly well-supported, with 9 species supporting extinction thresholds and 5 supporting persistence thresholds. This contrasts with a previous study based on breeding bird atlas data from adjacent New York State, which showed that most species support persistence and extinction threshold models (15 and 22 of 25 study species respectively). In addition, species that supported a threshold model in both states had associated average threshold estimates of 61.41% (SE = 6.11, persistence) and 66.45% (SE = 9.15, extinction) in New York, compared to 51.08% (SE = 10.60, persistence) and 73.67% (SE = 5.70, extinction) in Vermont. Across species, thresholds were found at 19.45–87.96% forest cover for persistence and 50.82–91.02% for extinction dynamics. Conclusions/Significance Through an approach that allows for broad-scale comparisons of threshold responses, we show that species vary in their threshold responses with regard to habitat amount, and that differences between even nearby regions can be pronounced. We present both ecological and methodological factors that may contribute to the different model results, but propose that regardless of the reasons behind these differences, our results merit a warning that threshold values cannot simply be transferred across regions or interpreted as clear-cut targets for ecosystem management and conservation. PMID:23409106

The social genome of friends and schoolmates in the National Longitudinal Study of Adolescent to Adult Health

PubMed Central

Boardman, Jason D.; Harris, Kathleen Mullan

2018-01-01

Humans tend to form social relationships with others who resemble them. Whether this sorting of like with like arises from historical patterns of migration, meso-level social structures in modern society, or individual-level selection of similar peers remains unsettled. Recent research has evaluated the possibility that unobserved genotypes may play an important role in the creation of homophilous relationships. We extend this work by using data from 5,500 adolescents from the National Longitudinal Study of Adolescent to Adult Health (Add Health) to examine genetic similarities among pairs of friends. Although there is some evidence that friends have correlated genotypes, both at the whole-genome level as well as at trait-associated loci (via polygenic scores), further analysis suggests that meso-level forces, such as school assignment, are a principal source of genetic similarity between friends. We also observe apparent social–genetic effects in which polygenic scores of an individual’s friends and schoolmates predict the individual’s own educational attainment. In contrast, an individual’s height is unassociated with the height genetics of peers. PMID:29317533

Concordance between actual and pharmacogenetic predicted desvenlafaxine dose needed to achieve remission in major depressive disorder: a 10-week open-label study

PubMed Central

Müller, Daniel J.; Ng, Chee H.; Byron, Keith; Berk, Michael; Singh, Ajeet B.

2017-01-01

Background Pharmacogenetic-based dosing support tools have been developed to personalize antidepressant-prescribing practice. However, the clinical validity of these tools has not been adequately tested, particularly for specific antidepressants. Objective To examine the concordance between the actual dose and a polygene pharmacogenetic predicted dose of desvenlafaxine needed to achieve symptom remission. Materials and methods A 10-week, open-label, prospective trial of desvenlafaxine among Caucasian adults with major depressive disorder (n=119) was conducted. Dose was clinically adjusted and at the completion of the trial, the clinical dose needed to achieve remission was compared with the predicted dose needed to achieve remission. Results Among remitters (n=95), there was a strong concordance (Kendall’s τ-b=0.84, P=0.0001; Cohen’s κ=0.82, P=0.0001) between the actual and the predicted dose need to achieve symptom remission, showing high sensitivity (≥85%), specificity (≥86%), and accuracy (≥89%) of the tool. Conclusion Findings provide initial evidence for the clinical validity of a polygene pharmacogenetic-based tool for desvenlafaxine dosing. PMID:27779571

GlobAl Distribution of GEnetic Traits (GADGET) web server: polygenic trait scores worldwide.

PubMed

Chande, Aroon T; Wang, Lu; Rishishwar, Lavanya; Conley, Andrew B; Norris, Emily T; Valderrama-Aguirre, Augusto; Jordan, I King

2018-05-18

Human populations from around the world show striking phenotypic variation across a wide variety of traits. Genome-wide association studies (GWAS) are used to uncover genetic variants that influence the expression of heritable human traits; accordingly, population-specific distributions of GWAS-implicated variants may shed light on the genetic basis of human phenotypic diversity. With this in mind, we developed the GlobAl Distribution of GEnetic Traits web server (GADGET http://gadget.biosci.gatech.edu). The GADGET web server provides users with a dynamic visual platform for exploring the relationship between worldwide genetic diversity and the genetic architecture underlying numerous human phenotypes. GADGET integrates trait-implicated single nucleotide polymorphisms (SNPs) from GWAS, with population genetic data from the 1000 Genomes Project, to calculate genome-wide polygenic trait scores (PTS) for 818 phenotypes in 2504 individual genomes. Population-specific distributions of PTS are shown for 26 human populations across 5 continental population groups, with traits ordered based on the extent of variation observed among populations. Users of GADGET can also upload custom trait SNP sets to visualize global PTS distributions for their own traits of interest.

Combinations of SNP genotypes from the Wellcome Trust Case Control Study of bipolar patients.

PubMed

Mellerup, Erling; Jørgensen, Martin Balslev; Dam, Henrik; Møller, Gert Lykke

2018-04-01

Combinations of genetic variants are the basis for polygenic disorders. We examined combinations of SNP genotypes taken from the 446 729 SNPs in The Wellcome Trust Case Control Study of bipolar patients. Parallel computing by graphics processing units, cloud computing, and data mining tools were used to scan The Wellcome Trust data set for combinations. Two clusters of combinations were significantly associated with bipolar disorder. One cluster contained 68 combinations, each of which included five SNP genotypes. Of the 1998 patients, 305 had combinations from this cluster in their genome, but none of the 1500 controls had any of these combinations in their genome. The other cluster contained six combinations, each of which included five SNP genotypes. Of the 1998 patients, 515 had combinations from the cluster in their genome, but none of the 1500 controls had any of these combinations in their genome. Clusters of combinations of genetic variants can be considered general risk factors for polygenic disorders, whereas accumulation of combinations from the clusters in the genome of a patient can be considered a personal risk factor.

Peptide biomarkers used for the selective breeding of a complex polygenic trait in honey bees.

PubMed

Guarna, M Marta; Hoover, Shelley E; Huxter, Elizabeth; Higo, Heather; Moon, Kyung-Mee; Domanski, Dominik; Bixby, Miriam E F; Melathopoulos, Andony P; Ibrahim, Abdullah; Peirson, Michael; Desai, Suresh; Micholson, Derek; White, Rick; Borchers, Christoph H; Currie, Robert W; Pernal, Stephen F; Foster, Leonard J

2017-08-21

We present a novel way to select for highly polygenic traits. For millennia, humans have used observable phenotypes to selectively breed stronger or more productive livestock and crops. Selection on genotype, using single-nucleotide polymorphisms (SNPs) and genome profiling, is also now applied broadly in livestock breeding programs; however, selection on protein/peptide or mRNA expression markers has not yet been proven useful. Here we demonstrate the utility of protein markers to select for disease-resistant hygienic behavior in the European honey bee (Apis mellifera L.). Robust, mechanistically-linked protein expression markers, by integrating cis- and trans- effects from many genomic loci, may overcome limitations of genomic markers to allow for selection. After three generations of selection, the resulting marker-selected stock outperformed an unselected benchmark stock in terms of hygienic behavior, and had improved survival when challenged with a bacterial disease or a parasitic mite, similar to bees selected using a phenotype-based assessment for this trait. This is the first demonstration of the efficacy of protein markers for industrial selective breeding in any agricultural species, plant or animal.

Concordance between actual and pharmacogenetic predicted desvenlafaxine dose needed to achieve remission in major depressive disorder: a 10-week open-label study.

PubMed

Bousman, Chad A; Müller, Daniel J; Ng, Chee H; Byron, Keith; Berk, Michael; Singh, Ajeet B

2017-01-01

Pharmacogenetic-based dosing support tools have been developed to personalize antidepressant-prescribing practice. However, the clinical validity of these tools has not been adequately tested, particularly for specific antidepressants. To examine the concordance between the actual dose and a polygene pharmacogenetic predicted dose of desvenlafaxine needed to achieve symptom remission. A 10-week, open-label, prospective trial of desvenlafaxine among Caucasian adults with major depressive disorder (n=119) was conducted. Dose was clinically adjusted and at the completion of the trial, the clinical dose needed to achieve remission was compared with the predicted dose needed to achieve remission. Among remitters (n=95), there was a strong concordance (Kendall's τ-b=0.84, P=0.0001; Cohen's κ=0.82, P=0.0001) between the actual and the predicted dose need to achieve symptom remission, showing high sensitivity (≥85%), specificity (≥86%), and accuracy (≥89%) of the tool. Findings provide initial evidence for the clinical validity of a polygene pharmacogenetic-based tool for desvenlafaxine dosing.

Rare and low-frequency coding variants alter human adult height

PubMed Central

Marouli, Eirini; Graff, Mariaelisa; Medina-Gomez, Carolina; Lo, Ken Sin; Wood, Andrew R; Kjaer, Troels R; Fine, Rebecca S; Lu, Yingchang; Schurmann, Claudia; Highland, Heather M; Rüeger, Sina; Thorleifsson, Gudmar; Justice, Anne E; Lamparter, David; Stirrups, Kathleen E; Turcot, Valérie; Young, Kristin L; Winkler, Thomas W; Esko, Tõnu; Karaderi, Tugce; Locke, Adam E; Masca, Nicholas GD; Ng, Maggie CY; Mudgal, Poorva; Rivas, Manuel A; Vedantam, Sailaja; Mahajan, Anubha; Guo, Xiuqing; Abecasis, Goncalo; Aben, Katja K; Adair, Linda S; Alam, Dewan S; Albrecht, Eva; Allin, Kristine H; Allison, Matthew; Amouyel, Philippe; Appel, Emil V; Arveiler, Dominique; Asselbergs, Folkert W; Auer, Paul L; Balkau, Beverley; Banas, Bernhard; Bang, Lia E; Benn, Marianne; Bergmann, Sven; Bielak, Lawrence F; Blüher, Matthias; Boeing, Heiner; Boerwinkle, Eric; Böger, Carsten A; Bonnycastle, Lori L; Bork-Jensen, Jette; Bots, Michiel L; Bottinger, Erwin P; Bowden, Donald W; Brandslund, Ivan; Breen, Gerome; Brilliant, Murray H; Broer, Linda; Burt, Amber A; Butterworth, Adam S; Carey, David J; Caulfield, Mark J; Chambers, John C; Chasman, Daniel I; Chen, Yii-Der Ida; Chowdhury, Rajiv; Christensen, Cramer; Chu, Audrey Y; Cocca, Massimiliano; Collins, Francis S; Cook, James P; Corley, Janie; Galbany, Jordi Corominas; Cox, Amanda J; Cuellar-Partida, Gabriel; Danesh, John; Davies, Gail; de Bakker, Paul IW; de Borst, Gert J.; de Denus, Simon; de Groot, Mark CH; de Mutsert, Renée; Deary, Ian J; Dedoussis, George; Demerath, Ellen W; den Hollander, Anneke I; Dennis, Joe G; Di Angelantonio, Emanuele; Drenos, Fotios; Du, Mengmeng; Dunning, Alison M; Easton, Douglas F; Ebeling, Tapani; Edwards, Todd L; Ellinor, Patrick T; Elliott, Paul; Evangelou, Evangelos; Farmaki, Aliki-Eleni; Faul, Jessica D; Feitosa, Mary F; Feng, Shuang; Ferrannini, Ele; Ferrario, Marco M; Ferrieres, Jean; Florez, Jose C; Ford, Ian; Fornage, Myriam; Franks, Paul W; Frikke-Schmidt, Ruth; Galesloot, Tessel E; Gan, Wei; Gandin, Ilaria; Gasparini, Paolo; Giedraitis, Vilmantas; Giri, Ayush; Girotto, Giorgia; Gordon, Scott D; Gordon-Larsen, Penny; Gorski, Mathias; Grarup, Niels; Grove, Megan L.; Gudnason, Vilmundur; Gustafsson, Stefan; Hansen, Torben; Harris, Kathleen Mullan; Harris, Tamara B; Hattersley, Andrew T; Hayward, Caroline; He, Liang; Heid, Iris M; Heikkilä, Kauko; Helgeland, Øyvind; Hernesniemi, Jussi; Hewitt, Alex W; Hocking, Lynne J; Hollensted, Mette; Holmen, Oddgeir L; Hovingh, G. Kees; Howson, Joanna MM; Hoyng, Carel B; Huang, Paul L; Hveem, Kristian; Ikram, M. Arfan; Ingelsson, Erik; Jackson, Anne U; Jansson, Jan-Håkan; Jarvik, Gail P; Jensen, Gorm B; Jhun, Min A; Jia, Yucheng; Jiang, Xuejuan; Johansson, Stefan; Jørgensen, Marit E; Jørgensen, Torben; Jousilahti, Pekka; Jukema, J Wouter; Kahali, Bratati; Kahn, René S; Kähönen, Mika; Kamstrup, Pia R; Kanoni, Stavroula; Kaprio, Jaakko; Karaleftheri, Maria; Kardia, Sharon LR; Karpe, Fredrik; Kee, Frank; Keeman, Renske; Kiemeney, Lambertus A; Kitajima, Hidetoshi; Kluivers, Kirsten B; Kocher, Thomas; Komulainen, Pirjo; Kontto, Jukka; Kooner, Jaspal S; Kooperberg, Charles; Kovacs, Peter; Kriebel, Jennifer; Kuivaniemi, Helena; Küry, Sébastien; Kuusisto, Johanna; La Bianca, Martina; Laakso, Markku; Lakka, Timo A; Lange, Ethan M; Lange, Leslie A; Langefeld, Carl D; Langenberg, Claudia; Larson, Eric B; Lee, I-Te; Lehtimäki, Terho; Lewis, Cora E; Li, Huaixing; Li, Jin; Li-Gao, Ruifang; Lin, Honghuang; Lin, Li-An; Lin, Xu; Lind, Lars; Lindström, Jaana; Linneberg, Allan; Liu, Yeheng; Liu, Yongmei; Lophatananon, Artitaya; Luan, Jian'an; Lubitz, Steven A; Lyytikäinen, Leo-Pekka; Mackey, David A; Madden, Pamela AF; Manning, Alisa K; Männistö, Satu; Marenne, Gaëlle; Marten, Jonathan; Martin, Nicholas G; Mazul, Angela L; Meidtner, Karina; Metspalu, Andres; Mitchell, Paul; Mohlke, Karen L; Mook-Kanamori, Dennis O; Morgan, Anna; Morris, Andrew D; Morris, Andrew P; Müller-Nurasyid, Martina; Munroe, Patricia B; Nalls, Mike A; Nauck, Matthias; Nelson, Christopher P; Neville, Matt; Nielsen, Sune F; Nikus, Kjell; Njølstad, Pål R; Nordestgaard, Børge G; Ntalla, Ioanna; O'Connel, Jeffrey R; Oksa, Heikki; Loohuis, Loes M Olde; Ophoff, Roel A; Owen, Katharine R; Packard, Chris J; Padmanabhan, Sandosh; Palmer, Colin NA; Pasterkamp, Gerard; Patel, Aniruddh P; Pattie, Alison; Pedersen, Oluf; Peissig, Peggy L; Peloso, Gina M; Pennell, Craig E; Perola, Markus; Perry, James A; Perry, John R.B.; Person, Thomas N; Pirie, Ailith; Polasek, Ozren; Posthuma, Danielle; Raitakari, Olli T; Rasheed, Asif; Rauramaa, Rainer; Reilly, Dermot F; Reiner, Alex P; Renström, Frida; Ridker, Paul M; Rioux, John D; Robertson, Neil; Robino, Antonietta; Rolandsson, Olov; Rudan, Igor; Ruth, Katherine S; Saleheen, Danish; Salomaa, Veikko; Samani, Nilesh J; Sandow, Kevin; Sapkota, Yadav; Sattar, Naveed; Schmidt, Marjanka K; Schreiner, Pamela J; Schulze, Matthias B; Scott, Robert A; Segura-Lepe, Marcelo P; Shah, Svati; Sim, Xueling; Sivapalaratnam, Suthesh; Small, Kerrin S; Smith, Albert Vernon; Smith, Jennifer A; Southam, Lorraine; Spector, Timothy D; Speliotes, Elizabeth K; Starr, John M; Steinthorsdottir, Valgerdur; Stringham, Heather M; Stumvoll, Michael; Surendran, Praveen; Hart, Leen M ‘t; Tansey, Katherine E; Tardif, Jean-Claude; Taylor, Kent D; Teumer, Alexander; Thompson, Deborah J; Thorsteinsdottir, Unnur; Thuesen, Betina H; Tönjes, Anke; Tromp, Gerard; Trompet, Stella; Tsafantakis, Emmanouil; Tuomilehto, Jaakko; Tybjaerg-Hansen, Anne; Tyrer, Jonathan P; Uher, Rudolf; Uitterlinden, André G; Ulivi, Sheila; van der Laan, Sander W; Van Der Leij, Andries R; van Duijn, Cornelia M; van Schoor, Natasja M; van Setten, Jessica; Varbo, Anette; Varga, Tibor V; Varma, Rohit; Edwards, Digna R Velez; Vermeulen, Sita H; Vestergaard, Henrik; Vitart, Veronique; Vogt, Thomas F; Vozzi, Diego; Walker, Mark; Wang, Feijie; Wang, Carol A; Wang, Shuai; Wang, Yiqin; Wareham, Nicholas J; Warren, Helen R; Wessel, Jennifer; Willems, Sara M; Wilson, James G; Witte, Daniel R; Woods, Michael O; Wu, Ying; Yaghootkar, Hanieh; Yao, Jie; Yao, Pang; Yerges-Armstrong, Laura M; Young, Robin; Zeggini, Eleftheria; Zhan, Xiaowei; Zhang, Weihua; Zhao, Jing Hua; Zhao, Wei; Zhao, Wei; Zheng, He; Zhou, Wei; Rotter, Jerome I; Boehnke, Michael; Kathiresan, Sekar; McCarthy, Mark I; Willer, Cristen J; Stefansson, Kari; Borecki, Ingrid B; Liu, Dajiang J; North, Kari E; Heard-Costa, Nancy L; Pers, Tune H; Lindgren, Cecilia M; Oxvig, Claus; Kutalik, Zoltán; Rivadeneira, Fernando; Loos, Ruth JF; Frayling, Timothy M; Hirschhorn, Joel N; Deloukas, Panos; Lettre, Guillaume

2016-01-01

Summary Height is a highly heritable, classic polygenic trait with ∼700 common associated variants identified so far through genome-wide association studies. Here, we report 83 height-associated coding variants with lower minor allele frequencies (range of 0.1-4.8%) and effects of up to 2 cm/allele (e.g. in IHH, STC2, AR and CRISPLD2), >10 times the average effect of common variants. In functional follow-up studies, rare height-increasing alleles of STC2 (+1-2 cm/allele) compromised proteolytic inhibition of PAPP-A and increased cleavage of IGFBP-4 in vitro, resulting in higher bioavailability of insulin-like growth factors. These 83 height-associated variants overlap genes mutated in monogenic growth disorders and highlight new biological candidates (e.g. ADAMTS3, IL11RA, NOX4) and pathways (e.g. proteoglycan/glycosaminoglycan synthesis) involved in growth. Our results demonstrate that sufficiently large sample sizes can uncover rare and low-frequency variants of moderate to large effect associated with polygenic human phenotypes, and that these variants implicate relevant genes and pathways. PMID:28146470

Single-Nucleotide-Polymorphism-Based Association Mapping of Dog Stereotypes

PubMed Central

Jones, Paul; Chase, Kevin; Martin, Alan; Davern, Pluis; Ostrander, Elaine A.; Lark, Karl G.

2008-01-01

Phenotypic stereotypes are traits, often polygenic, that have been stringently selected to conform to specific criteria. In dogs, Canis familiaris, stereotypes result from breed standards set for conformation, performance (behaviors), etc. As a consequence, phenotypic values measured on a few individuals are representative of the breed stereotype. We used DNA samples isolated from 148 dog breeds to associate SNP markers with breed stereotypes. Using size as a trait to test the method, we identified six significant quantitative trait loci (QTL) on five chromosomes that include candidate genes appropriate to regulation of size (e.g., IGF1, IGF2BP2 SMAD2, etc.). Analysis of other morphological stereotypes, also under extreme selection, identified many additional significant loci. Less well-documented data for behavioral stereotypes tentatively identified loci for herding, pointing, boldness, and trainability. Four significant loci were identified for longevity, a breed characteristic not under direct selection, but inversely correlated with breed size. The strengths and limitations of the approach are discussed as well as its potential to identify loci regulating the within-breed incidence of specific polygenic diseases. PMID:18505865

Identifying the most appropriate age threshold for TNM stage grouping of well-differentiated thyroid cancer.

PubMed

Hendrickson-Rebizant, J; Sigvaldason, H; Nason, R W; Pathak, K A

2015-08-01

Age is integrated in most risk stratification systems for well-differentiated thyroid cancer (WDTC). The most appropriate age threshold for stage grouping of WDTC is debatable. The objective of this study was to evaluate the best age threshold for stage grouping by comparing multivariable models designed to evaluate the independent impact of various prognostic factors, including age based stage grouping, on the disease specific survival (DSS) of our population-based cohort. Data from population-based thyroid cancer cohort of 2125 consecutive WDTC, diagnosed during 1970-2010, with a median follow-up of 11.5 years, was used to calculate DSS using the Kaplan Meier method. Multivariable analysis with Cox proportional hazard model was used to assess independent impact of different prognostic factors on DSS. The Akaike information criterion (AIC), a measure of statistical model fit, was used to identify the most appropriate age threshold model. Delta AIC, Akaike weight, and evidence ratios were calculated to compare the relative strength of different models. The mean age of the patients was 47.3 years. DSS of the cohort was 95.6% and 92.8% at 10 and 20 years respectively. A threshold of 55 years, with the lowest AIC, was identified as the best model. Akaike weight indicated an 85% chance that this age threshold is the best among the compared models, and is 16.8 times more likely to be the best model as compared to a threshold of 45 years. The age threshold of 55 years was found to be the best for TNM stage grouping. Copyright © 2015 Elsevier Ltd. All rights reserved.

Rainfall thresholds for the initiation of debris flows at La Honda, California

USGS Publications Warehouse

Wilson, R.C.; Wieczorek, G.F.

1995-01-01

A simple numerical model, based on the physical analogy of a leaky barrel, can simulate significant features of the interaction between rainfall and shallow-hillslope pore pressures. The leaky-barrel-model threshold is consistent with, but slightly higher than, an earlier, purely empirical, threshold. The number of debris flows triggered by a storm can be related to the time and amount by which the leaky-barrel-model response exceeded the threshold during the storm. -from Authors

Two-threshold model for scaling laws of noninteracting snow avalanches

USGS Publications Warehouse

Faillettaz, J.; Louchet, F.; Grasso, J.-R.

2004-01-01

A two-threshold model was proposed for scaling laws of noninteracting snow avalanches. It was found that the sizes of the largest avalanches just preceding the lattice system were power-law distributed. The proposed model reproduced the range of power-law exponents observe for land, rock or snow avalanches, by tuning the maximum value of the ratio of the two failure thresholds. A two-threshold 2D cellular automation was introduced to study the scaling for gravity-driven systems.

Multimarker analysis suggests the involvement of BDNF signaling and microRNA biosynthesis in suicidal behavior.

PubMed

Pulay, Attila J; Réthelyi, János M

2016-09-01

Despite moderate heritability estimates the genetics of suicidal behavior remains unclear, genome-wide association and candidate gene studies focusing on single nucleotide associations reported inconsistent findings. Our study explored biologically informed, multimarker candidate gene associations with suicidal behavior in mood disorders. We analyzed the GAIN Whole Genome Association Study of Bipolar Disorder version 3 (n = 999, suicidal n = 358) and the GAIN Major Depression: Stage 1 Genomewide Association in Population-Based Samples (n = 1,753, suicidal n = 245) datasets. Suicidal behavior was defined as severe suicidal ideation or attempt. Candidate genes were selected based on literature search (Geneset1, n = 35), gene expression data of microRNA genes, (Geneset2, n = 68) and their target genes (Geneset3, n = 11,259). Quality control, dosage analyses were carried out with PLINK. Gene-based associations of Geneset1 were analyzed with KGG. Polygenic profile scores of suicidal behavior were computed in the major depression dataset both with PRSice and LDpred and validated in the bipolar disorder data. Several nominally significant gene-based associations were detected, but only DICER1 associated with suicidal behavior in both samples, while only the associations of NTRK2 in the depression sample reached family wise and experiment wise significance. Polygenic profile scores negatively predicted suicidal behavior in the bipolar sample for only Geneset2, with the strongest prediction by PRSice at Pt  < 0.03 (Nagelkerke R(2)  = 0.01, P < 0.007). Gene-based association results confirmed the potential involvement of the BDNF-NTRK2-CREB pathway in the pathogenesis of suicide and the cross-disorder association of DICER1. Polygenic risk prediction of the selected miRNA genes indicates that the miRNA system may play a mediating role, but with considerable pleiotropy. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Shared Genetic Risk Factors of Intracranial, Abdominal, and Thoracic Aneurysms.

PubMed

van 't Hof, Femke N G; Ruigrok, Ynte M; Lee, Cue Hyunkyu; Ripke, Stephan; Anderson, Graig; de Andrade, Mariza; Baas, Annette F; Blankensteijn, Jan D; Böttinger, Erwin P; Bown, Matthew J; Broderick, Joseph; Bijlenga, Philippe; Carrell, David S; Crawford, Dana C; Crosslin, David R; Ebeling, Christian; Eriksson, Johan G; Fornage, Myriam; Foroud, Tatiana; von Und Zu Fraunberg, Mikael; Friedrich, Christoph M; Gaál, Emília I; Gottesman, Omri; Guo, Dong-Chuan; Harrison, Seamus C; Hernesniemi, Juha; Hofman, Albert; Inoue, Ituro; Jääskeläinen, Juha E; Jones, Gregory T; Kiemeney, Lambertus A L M; Kivisaari, Riku; Ko, Nerissa; Koskinen, Seppo; Kubo, Michiaki; Kullo, Iftikhar J; Kuivaniemi, Helena; Kurki, Mitja I; Laakso, Aki; Lai, Dongbing; Leal, Suzanne M; Lehto, Hanna; LeMaire, Scott A; Low, Siew-Kee; Malinowski, Jennifer; McCarty, Catherine A; Milewicz, Dianna M; Mosley, Thomas H; Nakamura, Yusuke; Nakaoka, Hirofumi; Niemelä, Mika; Pacheco, Jennifer; Peissig, Peggy L; Pera, Joanna; Rasmussen-Torvik, Laura; Ritchie, Marylyn D; Rivadeneira, Fernando; van Rij, Andre M; Santos-Cortez, Regie Lyn P; Saratzis, Athanasios; Slowik, Agnieszka; Takahashi, Atsushi; Tromp, Gerard; Uitterlinden, André G; Verma, Shefali S; Vermeulen, Sita H; Wang, Gao T; Han, Buhm; Rinkel, Gabriël J E; de Bakker, Paul I W

2016-07-14

Intracranial aneurysms (IAs), abdominal aortic aneurysms (AAAs), and thoracic aortic aneurysms (TAAs) all have a familial predisposition. Given that aneurysm types are known to co-occur, we hypothesized that there may be shared genetic risk factors for IAs, AAAs, and TAAs. We performed a mega-analysis of 1000 Genomes Project-imputed genome-wide association study (GWAS) data of 4 previously published aneurysm cohorts: 2 IA cohorts (in total 1516 cases, 4305 controls), 1 AAA cohort (818 cases, 3004 controls), and 1 TAA cohort (760 cases, 2212 controls), and observed associations of 4 known IA, AAA, and/or TAA risk loci (9p21, 18q11, 15q21, and 2q33) with consistent effect directions in all 4 cohorts. We calculated polygenic scores based on IA-, AAA-, and TAA-associated SNPs and tested these scores for association to case-control status in the other aneurysm cohorts; this revealed no shared polygenic effects. Similarly, linkage disequilibrium-score regression analyses did not show significant correlations between any pair of aneurysm subtypes. Last, we evaluated the evidence for 14 previously published aneurysm risk single-nucleotide polymorphisms through collaboration in extended aneurysm cohorts, with a total of 6548 cases and 16 843 controls (IA) and 4391 cases and 37 904 controls (AAA), and found nominally significant associations for IA risk locus 18q11 near RBBP8 to AAA (odds ratio [OR]=1.11; P=4.1×10(-5)) and for TAA risk locus 15q21 near FBN1 to AAA (OR=1.07; P=1.1×10(-3)). Although there was no evidence for polygenic overlap between IAs, AAAs, and TAAs, we found nominally significant effects of two established risk loci for IAs and TAAs in AAAs. These two loci will require further replication. © 2016 The Authors. Published on behalf of the American Heart Association, Inc., by Wiley Blackwell.

Are genetic risk factors for psychosis also associated with dimension-specific psychotic experiences in adolescence?

PubMed

Sieradzka, Dominika; Power, Robert A; Freeman, Daniel; Cardno, Alastair G; McGuire, Philip; Plomin, Robert; Meaburn, Emma L; Dudbridge, Frank; Ronald, Angelica

2014-01-01

Psychosis has been hypothesised to be a continuously distributed quantitative phenotype and disorders such as schizophrenia and bipolar disorder represent its extreme manifestations. Evidence suggests that common genetic variants play an important role in liability to both schizophrenia and bipolar disorder. Here we tested the hypothesis that these common variants would also influence psychotic experiences measured dimensionally in adolescents in the general population. Our aim was to test whether schizophrenia and bipolar disorder polygenic risk scores (PRS), as well as specific single nucleotide polymorphisms (SNPs) previously identified as risk variants for schizophrenia, were associated with adolescent dimension-specific psychotic experiences. Self-reported Paranoia, Hallucinations, Cognitive Disorganisation, Grandiosity, Anhedonia, and Parent-rated Negative Symptoms, as measured by the Specific Psychotic Experiences Questionnaire (SPEQ), were assessed in a community sample of 2,152 16-year-olds. Polygenic risk scores were calculated using estimates of the log of odds ratios from the Psychiatric Genomics Consortium GWAS stage-1 mega-analysis of schizophrenia and bipolar disorder. The polygenic risk analyses yielded no significant associations between schizophrenia and bipolar disorder PRS and the SPEQ measures. The analyses on the 28 individual SNPs previously associated with schizophrenia found that two SNPs in TCF4 returned a significant association with the SPEQ Paranoia dimension, rs17512836 (p-value = 2.57×10⁻⁴) and rs9960767 (p-value = 6.23×10⁻⁴). Replication in an independent sample of 16-year-olds (N = 3,427) assessed using the Psychotic-Like Symptoms Questionnaire (PLIKS-Q), a composite measure of multiple positive psychotic experiences, failed to yield significant results. Future research with PRS derived from larger samples, as well as larger adolescent validation samples, would improve the predictive power to test these hypotheses further. The challenges of relating adult clinical diagnostic constructs such as schizophrenia to adolescent psychotic experiences at a genetic level are discussed.

Breeding and Genetics Symposium: networks and pathways to guide genomic selection.

PubMed

Snelling, W M; Cushman, R A; Keele, J W; Maltecca, C; Thomas, M G; Fortes, M R S; Reverter, A

2013-02-01

Many traits affecting profitability and sustainability of meat, milk, and fiber production are polygenic, with no single gene having an overwhelming influence on observed variation. No knowledge of the specific genes controlling these traits has been needed to make substantial improvement through selection. Significant gains have been made through phenotypic selection enhanced by pedigree relationships and continually improving statistical methodology. Genomic selection, recently enabled by assays for dense SNP located throughout the genome, promises to increase selection accuracy and accelerate genetic improvement by emphasizing the SNP most strongly correlated to phenotype although the genes and sequence variants affecting phenotype remain largely unknown. These genomic predictions theoretically rely on linkage disequilibrium (LD) between genotyped SNP and unknown functional variants, but familial linkage may increase effectiveness when predicting individuals related to those in the training data. Genomic selection with functional SNP genotypes should be less reliant on LD patterns shared by training and target populations, possibly allowing robust prediction across unrelated populations. Although the specific variants causing polygenic variation may never be known with certainty, a number of tools and resources can be used to identify those most likely to affect phenotype. Associations of dense SNP genotypes with phenotype provide a 1-dimensional approach for identifying genes affecting specific traits; in contrast, associations with multiple traits allow defining networks of genes interacting to affect correlated traits. Such networks are especially compelling when corroborated by existing functional annotation and established molecular pathways. The SNP occurring within network genes, obtained from public databases or derived from genome and transcriptome sequences, may be classified according to expected effects on gene products. As illustrated by functionally informed genomic predictions being more accurate than naive whole-genome predictions of beef tenderness, coupling evidence from livestock genotypes, phenotypes, gene expression, and genomic variants with existing knowledge of gene functions and interactions may provide greater insight into the genes and genomic mechanisms affecting polygenic traits and facilitate functional genomic selection for economically important traits.

Modeling spatially-varying landscape change points in species occurrence thresholds

USGS Publications Warehouse

Wagner, Tyler; Midway, Stephen R.

2014-01-01

Predicting species distributions at scales of regions to continents is often necessary, as large-scale phenomena influence the distributions of spatially structured populations. Land use and land cover are important large-scale drivers of species distributions, and landscapes are known to create species occurrence thresholds, where small changes in a landscape characteristic results in abrupt changes in occurrence. The value of the landscape characteristic at which this change occurs is referred to as a change point. We present a hierarchical Bayesian threshold model (HBTM) that allows for estimating spatially varying parameters, including change points. Our model also allows for modeling estimated parameters in an effort to understand large-scale drivers of variability in land use and land cover on species occurrence thresholds. We use range-wide detection/nondetection data for the eastern brook trout (Salvelinus fontinalis), a stream-dwelling salmonid, to illustrate our HBTM for estimating and modeling spatially varying threshold parameters in species occurrence. We parameterized the model for investigating thresholds in landscape predictor variables that are measured as proportions, and which are therefore restricted to values between 0 and 1. Our HBTM estimated spatially varying thresholds in brook trout occurrence for both the proportion agricultural and urban land uses. There was relatively little spatial variation in change point estimates, although there was spatial variability in the overall shape of the threshold response and associated uncertainty. In addition, regional mean stream water temperature was correlated to the change point parameters for the proportion of urban land use, with the change point value increasing with increasing mean stream water temperature. We present a framework for quantify macrosystem variability in spatially varying threshold model parameters in relation to important large-scale drivers such as land use and land cover. Although the model presented is a logistic HBTM, it can easily be extended to accommodate other statistical distributions for modeling species richness or abundance.

Genetic variance of tolerance and the toxicant threshold model.

PubMed

Tanaka, Yoshinari; Mano, Hiroyuki; Tatsuta, Haruki

2012-04-01

A statistical genetics method is presented for estimating the genetic variance (heritability) of tolerance to pollutants on the basis of a standard acute toxicity test conducted on several isofemale lines of cladoceran species. To analyze the genetic variance of tolerance in the case when the response is measured as a few discrete states (quantal endpoints), the authors attempted to apply the threshold character model in quantitative genetics to the threshold model separately developed in ecotoxicology. The integrated threshold model (toxicant threshold model) assumes that the response of a particular individual occurs at a threshold toxicant concentration and that the individual tolerance characterized by the individual's threshold value is determined by genetic and environmental factors. As a case study, the heritability of tolerance to p-nonylphenol in the cladoceran species Daphnia galeata was estimated by using the maximum likelihood method and nested analysis of variance (ANOVA). Broad-sense heritability was estimated to be 0.199 ± 0.112 by the maximum likelihood method and 0.184 ± 0.089 by ANOVA; both results implied that the species examined had the potential to acquire tolerance to this substance by evolutionary change. Copyright © 2012 SETAC.

Evidence for the contribution of a threshold retrieval process to semantic memory.

PubMed

Kempnich, Maria; Urquhart, Josephine A; O'Connor, Akira R; Moulin, Chris J A

2017-10-01

It is widely held that episodic retrieval can recruit two processes: a threshold context retrieval process (recollection) and a continuous signal strength process (familiarity). Conversely the processes recruited during semantic retrieval are less well specified. We developed a semantic task analogous to single-item episodic recognition to interrogate semantic recognition receiver-operating characteristics (ROCs) for a marker of a threshold retrieval process. We fitted observed ROC points to three signal detection models: two models typically used in episodic recognition (unequal variance and dual-process signal detection models) and a novel dual-process recollect-to-reject (DP-RR) signal detection model that allows a threshold recollection process to aid both target identification and lure rejection. Given the nature of most semantic questions, we anticipated the DP-RR model would best fit the semantic task data. Experiment 1 (506 participants) provided evidence for a threshold retrieval process in semantic memory, with overall best fits to the DP-RR model. Experiment 2 (316 participants) found within-subjects estimates of episodic and semantic threshold retrieval to be uncorrelated. Our findings add weight to the proposal that semantic and episodic memory are served by similar dual-process retrieval systems, though the relationship between the two threshold processes needs to be more fully elucidated.

Early Cannabis Use, Polygenic Risk Score for Schizophrenia, and Brain Maturation in Adolescence

PubMed Central

French, Leon; Gray, Courtney; Leonard, Gabriel; Perron, Michel; Pike, G. Bruce; Richer, Louis; Séguin, Jean R.; Veillette, Suzanne; Evans, C. John; Artiges, Eric; Banaschewski, Tobias; Bokde, Arun W. L.; Bromberg, Uli; Bruehl, Ruediger; Buchel, Christian; Cattrell, Anna; Conrod, Patricia J.; Flor, Herta; Frouin, Vincent; Gallinat, Jurgen; Garavan, Hugh; Gowland, Penny; Heinz, Andreas; Lemaitre, Herve; Martinot, Jean-Luc; Nees, Frauke; Orfanos, Dimitri Papadopoulos; Pangelinan, Melissa Marie; Poustka, Luise; Rietschel, Marcella; Smolka, Michael N.; Walter, Henrik; Whelan, Robert; Timpson, Nic J.; Schumann, Gunter; Smith, George Davey; Pausova, Zdenka; Paus, Tomáš

2016-01-01

IMPORTANCE Cannabis use during adolescence is known to increase the risk for schizophrenia in men. Sex differences in the dynamics of brain maturation during adolescence may be of particular importance with regard to vulnerability of the male brain to cannabis exposure. OBJECTIVE To evaluate whether the association between cannabis use and cortical maturation in adolescents is moderated by a polygenic risk score for schizophrenia. DESIGN, SETTING, AND PARTICIPANTS Observation of 3 population-based samples included initial analysis in 1024 adolescents of both sexes from the Canadian Saguenay Youth Study (SYS) and follow-up in 426 adolescents of both sexes from the IMAGEN Study from 8 European cities and 504 male youth from the Avon Longitudinal Study of Parents and Children (ALSPAC) based in England. A total of 1577 participants (aged 12–21 years; 899 [57.0%] male) had (1) information about cannabis use; (2) imaging studies of the brain; and (3) a polygenic risk score for schizophrenia across 108 genetic loci identified by the Psychiatric Genomics Consortium. Data analysis was performed from March 1 through December 31, 2014. MAIN OUTCOMES AND MEASURES Cortical thickness derived from T1-weighted magnetic resonance images. Linear regression tests were used to assess the relationships between cannabis use, cortical thickness, and risk score. RESULTS Across the 3 samples of 1574 participants, a negative association was observed between cannabis use in early adolescence and cortical thickness in male participants with a high polygenic risk score. This observation was not the case for low-risk male participants or for the low- or high-risk female participants. Thus, in SYS male participants, cannabis use interacted with risk score vis-à-vis cortical thickness (P = .009); higher scores were associated with lower thickness only in males who used cannabis. Similarly, in the IMAGEN male participants, cannabis use interacted with increased risk score vis-à-vis a change in decreasing cortical thickness from 14.5 to 18.5 years of age (t137 = −2.36; P = .02). Finally, in the ALSPAC high-risk group of male participants, those who used cannabis most frequently (≥61 occasions) had lower cortical thickness than those who never used cannabis (difference in cortical thickness, 0.07 [95% CI, 0.01–0.12]; P = .02) and those with light use (<5 occasions) (difference in cortical thickness, 0.11 [95% CI, 0.03–0.18]; P = .004). CONCLUSIONS AND RELEVANCE Cannabis use in early adolescence moderates the association between the genetic risk for schizophrenia and cortical maturation among male individuals. This finding implicates processes underlying cortical maturation in mediating the link between cannabis use and liability to schizophrenia. PMID:26308966

Misbehaving macrophages in the pathogenesis of psoriasis

PubMed Central

Clark, Rachael A.; Kupper, Thomas S.

2006-01-01

Psoriasis is a chronic inflammatory skin disease unique to humans. In this issue of the JCI, 2 studies of very different mouse models of psoriasis both report that macrophages play a key role in inducing psoriasis-like skin disease. Psoriasis is clearly a polygenic, inherited disease of uncontrolled cutaneous inflammation. The debate that currently rages in the field is whether psoriasis is a disease of autoreactive T cells or whether it reflects an intrinsic defect within the skin — or both. However, these questions have proven difficult to dissect using molecular genetic tools. In the current studies, the authors have used 2 different animal models to address the role of macrophages in disease pathogenesis: Wang et al. use a mouse model in which inflammation is T cell dependent, whereas the model used by Stratis et al. is T cell independent (see the related articles beginning on pages 2105 and 2094, respectively). Strikingly, both groups report an important contribution by macrophages, implying that macrophages can contribute to both epithelial-based and T cell–mediated pathways of inflammation. PMID:16886055

Recognition ROCS Are Curvilinear--Or Are They? On Premature Arguments against the Two-High-Threshold Model of Recognition

ERIC Educational Resources Information Center

Broder, Arndt; Schutz, Julia

2009-01-01

Recent reviews of recognition receiver operating characteristics (ROCs) claim that their curvilinear shape rules out threshold models of recognition. However, the shape of ROCs based on confidence ratings is not diagnostic to refute threshold models, whereas ROCs based on experimental bias manipulations are. Also, fitting predicted frequencies to…

Epidemic spreading with activity-driven awareness diffusion on multiplex network.

PubMed

Guo, Quantong; Lei, Yanjun; Jiang, Xin; Ma, Yifang; Huo, Guanying; Zheng, Zhiming

2016-04-01

There has been growing interest in exploring the interplay between epidemic spreading with human response, since it is natural for people to take various measures when they become aware of epidemics. As a proper way to describe the multiple connections among people in reality, multiplex network, a set of nodes interacting through multiple sets of edges, has attracted much attention. In this paper, to explore the coupled dynamical processes, a multiplex network with two layers is built. Specifically, the information spreading layer is a time varying network generated by the activity driven model, while the contagion layer is a static network. We extend the microscopic Markov chain approach to derive the epidemic threshold of the model. Compared with extensive Monte Carlo simulations, the method shows high accuracy for the prediction of the epidemic threshold. Besides, taking different spreading models of awareness into consideration, we explored the interplay between epidemic spreading with awareness spreading. The results show that the awareness spreading can not only enhance the epidemic threshold but also reduce the prevalence of epidemics. When the spreading of awareness is defined as susceptible-infected-susceptible model, there exists a critical value where the dynamical process on the awareness layer can control the onset of epidemics; while if it is a threshold model, the epidemic threshold emerges an abrupt transition with the local awareness ratio α approximating 0.5. Moreover, we also find that temporal changes in the topology hinder the spread of awareness which directly affect the epidemic threshold, especially when the awareness layer is threshold model. Given that the threshold model is a widely used model for social contagion, this is an important and meaningful result. Our results could also lead to interesting future research about the different time-scales of structural changes in multiplex networks.

Epidemic spreading with activity-driven awareness diffusion on multiplex network

NASA Astrophysics Data System (ADS)

Guo, Quantong; Lei, Yanjun; Jiang, Xin; Ma, Yifang; Huo, Guanying; Zheng, Zhiming

2016-04-01

There has been growing interest in exploring the interplay between epidemic spreading with human response, since it is natural for people to take various measures when they become aware of epidemics. As a proper way to describe the multiple connections among people in reality, multiplex network, a set of nodes interacting through multiple sets of edges, has attracted much attention. In this paper, to explore the coupled dynamical processes, a multiplex network with two layers is built. Specifically, the information spreading layer is a time varying network generated by the activity driven model, while the contagion layer is a static network. We extend the microscopic Markov chain approach to derive the epidemic threshold of the model. Compared with extensive Monte Carlo simulations, the method shows high accuracy for the prediction of the epidemic threshold. Besides, taking different spreading models of awareness into consideration, we explored the interplay between epidemic spreading with awareness spreading. The results show that the awareness spreading can not only enhance the epidemic threshold but also reduce the prevalence of epidemics. When the spreading of awareness is defined as susceptible-infected-susceptible model, there exists a critical value where the dynamical process on the awareness layer can control the onset of epidemics; while if it is a threshold model, the epidemic threshold emerges an abrupt transition with the local awareness ratio α approximating 0.5. Moreover, we also find that temporal changes in the topology hinder the spread of awareness which directly affect the epidemic threshold, especially when the awareness layer is threshold model. Given that the threshold model is a widely used model for social contagion, this is an important and meaningful result. Our results could also lead to interesting future research about the different time-scales of structural changes in multiplex networks.

Genetical genomics of Populus leaf shape variation

DOE PAGES

Drost, Derek R.; Puranik, Swati; Novaes, Evandro; ...

2015-06-30

Leaf morphology varies extensively among plant species and is under strong genetic control. Mutagenic screens in model systems have identified genes and established molecular mechanisms regulating leaf initiation, development, and shape. However, it is not known whether this diversity across plant species is related to naturally occurring variation at these genes. Quantitative trait locus (QTL) analysis has revealed a polygenic control for leaf shape variation in different species suggesting that loci discovered by mutagenesis may only explain part of the naturally occurring variation in leaf shape. Here we undertook a genetical genomics study in a poplar intersectional pseudo-backcross pedigree tomore » identify genetic factors controlling leaf shape. Here, the approach combined QTL discovery in a genetic linkage map anchored to the Populus trichocarpa reference genome sequence and transcriptome analysis.« less

Non-Linear Concentration-Response Relationships between Ambient Ozone and Daily Mortality.

PubMed

Bae, Sanghyuk; Lim, Youn-Hee; Kashima, Saori; Yorifuji, Takashi; Honda, Yasushi; Kim, Ho; Hong, Yun-Chul

2015-01-01

Ambient ozone (O3) concentration has been reported to be significantly associated with mortality. However, linearity of the relationships and the presence of a threshold has been controversial. The aim of the present study was to examine the concentration-response relationship and threshold of the association between ambient O3 concentration and non-accidental mortality in 13 Japanese and Korean cities from 2000 to 2009. We selected Japanese and Korean cities which have population of over 1 million. We constructed Poisson regression models adjusting daily mean temperature, daily mean PM10, humidity, time trend, season, year, day of the week, holidays and yearly population. The association between O3 concentration and mortality was examined using linear, spline and linear-threshold models. The thresholds were estimated for each city, by constructing linear-threshold models. We also examined the city-combined association using a generalized additive mixed model. The mean O3 concentration did not differ greatly between Korea and Japan, which were 26.2 ppb and 24.2 ppb, respectively. Seven out of 13 cities showed better fits for the spline model compared with the linear model, supporting a non-linear relationships between O3 concentration and mortality. All of the 7 cities showed J or U shaped associations suggesting the existence of thresholds. The range of city-specific thresholds was from 11 to 34 ppb. The city-combined analysis also showed a non-linear association with a threshold around 30-40 ppb. We have observed non-linear concentration-response relationship with thresholds between daily mean ambient O3 concentration and daily number of non-accidental death in Japanese and Korean cities.

Uncertainties in the Modelled CO2 Threshold for Antarctic Glaciation

NASA Technical Reports Server (NTRS)

Gasson, E.; Lunt, D. J.; DeConto, R.; Goldner, A.; Heinemann, M.; Huber, M.; LeGrande, A. N.; Pollard, D.; Sagoo, N.; Siddall, M.;

Experimental evidence of a pathogen invasion threshold

PubMed Central

Krkošek, Martin

2018-01-01

Host density thresholds to pathogen invasion separate regions of parameter space corresponding to endemic and disease-free states. The host density threshold is a central concept in theoretical epidemiology and a common target of human and wildlife disease control programmes, but there is mixed evidence supporting the existence of thresholds, especially in wildlife populations or for pathogens with complex transmission modes (e.g. environmental transmission). Here, we demonstrate the existence of a host density threshold for an environmentally transmitted pathogen by combining an epidemiological model with a microcosm experiment. Experimental epidemics consisted of replicate populations of naive crustacean zooplankton (Daphnia dentifera) hosts across a range of host densities (20–640 hosts l−1) that were exposed to an environmentally transmitted fungal pathogen (Metschnikowia bicuspidata). Epidemiological model simulations, parametrized independently of the experiment, qualitatively predicted experimental pathogen invasion thresholds. Variability in parameter estimates did not strongly influence outcomes, though systematic changes to key parameters have the potential to shift pathogen invasion thresholds. In summary, we provide one of the first clear experimental demonstrations of pathogen invasion thresholds in a replicated experimental system, and provide evidence that such thresholds may be predictable using independently constructed epidemiological models. PMID:29410876

The threshold of a stochastic delayed SIR epidemic model with vaccination

NASA Astrophysics Data System (ADS)

Liu, Qun; Jiang, Daqing

2016-11-01

In this paper, we study the threshold dynamics of a stochastic delayed SIR epidemic model with vaccination. We obtain sufficient conditions for extinction and persistence in the mean of the epidemic. The threshold between persistence in the mean and extinction of the stochastic system is also obtained. Compared with the corresponding deterministic model, the threshold affected by the white noise is smaller than the basic reproduction number Rbar0 of the deterministic system. Results show that time delay has important effects on the persistence and extinction of the epidemic.

Chromosomal Anomalies in Individuals with Autism: A Strategy Towards the Identification of Genes Involved in Autism

ERIC Educational Resources Information Center

Castermans, Dries; Wilquet, Valerie; Steyaert, Jean; van de Ven, Wim; Fryns, Jean-Pierre; Devriendt, Koen

2004-01-01

We review the different strategies currently used to try to identify susceptibility genes for idiopathic autism. Although identification of genes is usually straightforward in Mendelian disorders, it has proved to be much more difficult to establish in polygenic disorders like autism. Neither genome screens of affected siblings nor the large…

Genotyping by sequencing for SNP-based linkage analysis and identification of QTLs linked to fruit quality traits in Japanese plum (Prunus salicina Lindl.)

USDA-ARS?s Scientific Manuscript database

Marker-assisted selection (MAS) in stone fruit (Prunus species) breeding is currently difficult to achieve due to the polygenic nature of themost relevant agronomic traits linked to fruit quality. Genotyping by sequencing (GBS), however, provides a large quantity of useful data suitable for finemapp...

New consistent QTL in pea associated with partial resistance to Aphanomyces euteiches in multiple field and controlled environments from France and the United States

USDA-ARS?s Scientific Manuscript database

Partial resistances, often controlled by QTL (Quantitative Trait Loci), are considered to be more durable than monogenic resistances. Prior to develop efficient breeding programs for polygenic resistance to pathogens, a higher understanding of genetic diversity and stability of resistance QTL in pla...

Definition of temperature thresholds: the example of the French heat wave warning system.

PubMed

Pascal, Mathilde; Wagner, Vérène; Le Tertre, Alain; Laaidi, Karine; Honoré, Cyrille; Bénichou, Françoise; Beaudeau, Pascal

2013-01-01

Heat-related deaths should be somewhat preventable. In France, some prevention measures are activated when minimum and maximum temperatures averaged over three days reach city-specific thresholds. The current thresholds were computed based on a descriptive analysis of past heat waves and on local expert judgement. We tested whether a different method would confirm these thresholds. The study was set in the six cities of Paris, Lyon, Marseille, Nantes, Strasbourg and Limoges between 1973 and 2003. For each city, we estimated the excess in mortality associated with different temperature thresholds, using a generalised additive model, controlling for long-time trends, seasons and days of the week. These models were used to compute the mortality predicted by different percentiles of temperatures. The thresholds were chosen as the percentiles associated with a significant excess mortality. In all cities, there was a good correlation between current thresholds and the thresholds derived from the models, with 0°C to 3°C differences for averaged maximum temperatures. Both set of thresholds were able to anticipate the main periods of excess mortality during the summers of 1973 to 2003. A simple method relying on descriptive analysis and expert judgement is sufficient to define protective temperature thresholds and to prevent heat wave mortality. As temperatures are increasing along with the climate change and adaptation is ongoing, more research is required to understand if and when thresholds should be modified.

Study of blur discrimination for 3D stereo viewing

NASA Astrophysics Data System (ADS)

Subedar, Mahesh; Karam, Lina J.

2014-03-01

Blur is an important attribute in the study and modeling of the human visual system. Blur discrimination was studied extensively using 2D test patterns. In this study, we present the details of subjective tests performed to measure blur discrimination thresholds using stereoscopic 3D test patterns. Specifically, the effect of disparity on the blur discrimination thresholds is studied on a passive stereoscopic 3D display. The blur discrimination thresholds are measured using stereoscopic 3D test patterns with positive, negative and zero disparity values, at multiple reference blur levels. A disparity value of zero represents the 2D viewing case where both the eyes will observe the same image. The subjective test results indicate that the blur discrimination thresholds remain constant as we vary the disparity value. This further indicates that binocular disparity does not affect blur discrimination thresholds and the models developed for 2D blur discrimination thresholds can be extended to stereoscopic 3D blur discrimination thresholds. We have presented fitting of the Weber model to the 3D blur discrimination thresholds measured from the subjective experiments.

MARRIAGE GAP IN CHRISTIANS AND MUSLIMS.

PubMed

Fieder, Martin; Huber, Susanne; Pichl, Elmar; Wallner, Bernard; Seidler, Horst

2018-03-01

For modern Western societies with a regime of monogamy, it has recently been demonstrated that the socioeconomic status of men is positively associated with being or having been married. This study aims to compare marriage patterns (if a person has been married at least once) for cultures with a tradition of monogamy and polygyny. As no worldwide data on polygyny exist, religion was used as a proxy for monogamy (Christians) vs polygyny (Muslims). The analyses were based on 2000-2011 census data from 39 countries worldwide for 52,339,594 men and women, controlling for sex, sex ratio, age, education, migration within the last 5 years and employment. Overall, a higher proportion of Muslims were married compared with Christians, but the difference in the fraction of married men compared with married women at a certain age (the 'marriage gap') was much more pronounced in Muslims than in Christians, i.e. compared with Christians, a substantially higher proportion of Muslim women than men were married up to the age of approximately 31 years. As expected for a tradition of polygyny, the results indicate that the socioeconomic threshold for entering marriage is higher for Muslim than Christian men, and Muslim women in particular face a negative effect of socioeconomic status on the probability of ever being married. The large 'marriage gap' at a certain age in Muslim societies leads to high numbers of married women and unmarried young men, and may put such polygenic societies under pressure.

Scaling of Precipitation Extremes Modelled by Generalized Pareto Distribution

NASA Astrophysics Data System (ADS)

Rajulapati, C. R.; Mujumdar, P. P.

2017-12-01

Precipitation extremes are often modelled with data from annual maximum series or peaks over threshold series. The Generalized Pareto Distribution (GPD) is commonly used to fit the peaks over threshold series. Scaling of precipitation extremes from larger time scales to smaller time scales when the extremes are modelled with the GPD is burdened with difficulties arising from varying thresholds for different durations. In this study, the scale invariance theory is used to develop a disaggregation model for precipitation extremes exceeding specified thresholds. A scaling relationship is developed for a range of thresholds obtained from a set of quantiles of non-zero precipitation of different durations. The GPD parameters and exceedance rate parameters are modelled by the Bayesian approach and the uncertainty in scaling exponent is quantified. A quantile based modification in the scaling relationship is proposed for obtaining the varying thresholds and exceedance rate parameters for shorter durations. The disaggregation model is applied to precipitation datasets of Berlin City, Germany and Bangalore City, India. From both the applications, it is observed that the uncertainty in the scaling exponent has a considerable effect on uncertainty in scaled parameters and return levels of shorter durations.

Absolute auditory threshold: testing the absolute.

PubMed

Heil, Peter; Matysiak, Artur

2017-11-02

The mechanisms underlying the detection of sounds in quiet, one of the simplest tasks for auditory systems, are debated. Several models proposed to explain the threshold for sounds in quiet and its dependence on sound parameters include a minimum sound intensity ('hard threshold'), below which sound has no effect on the ear. Also, many models are based on the assumption that threshold is mediated by integration of a neural response proportional to sound intensity. Here, we test these ideas. Using an adaptive forced choice procedure, we obtained thresholds of 95 normal-hearing human ears for 18 tones (3.125 kHz carrier) in quiet, each with a different temporal amplitude envelope. Grand-mean thresholds and standard deviations were well described by a probabilistic model according to which sensory events are generated by a Poisson point process with a low rate in the absence, and higher, time-varying rates in the presence, of stimulation. The subject actively evaluates the process and bases the decision on the number of events observed. The sound-driven rate of events is proportional to the temporal amplitude envelope of the bandpass-filtered sound raised to an exponent. We find no evidence for a hard threshold: When the model is extended to include such a threshold, the fit does not improve. Furthermore, we find an exponent of 3, consistent with our previous studies and further challenging models that are based on the assumption of the integration of a neural response that, at threshold sound levels, is directly proportional to sound amplitude or intensity. © 2017 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.

[Estimation of individual breast cancer risk: relevance and limits of risk estimation models].

PubMed

De Pauw, A; Stoppa-Lyonnet, D; Andrieu, N; Asselain, B

2009-10-01

Several risk estimation models for breast or ovarian cancers have been developed these last decades. All these models take into account the family history, with different levels of sophistication. Gail model was developed in 1989 taking into account the family history (0, 1 or > or = 2 affected relatives) and several environmental factors. In 1990, Claus model was the first to integrate explicit assumptions about genetic effects, assuming a single gene dominantly inherited occurring with a low frequency in the population. BRCAPRO model, posterior to the identification of BRCA1 and BRCA2, assumes a restricted transmission with only these two dominantly inherited genes. BOADICEA model adds the effect of a polygenic component to the effect of BRCA1 and BRCA2 to explain the residual clustering of breast cancer. At last, IBIS model assumes a third dominantly inherited gene to explain this residual clustering. Moreover, this model incorporates environmental factors. We applied the Claus, BRCAPRO, BOADICEA and IBIS models to four clinical situations, corresponding to more or less heavy family histories, in order to study the consistency of the risk estimates. The three more recent models (BRCAPRO, BOADICEA and IBIS) gave the closer estimations. These estimates could be useful in clinical practice in front of complex analysis of breast and/or ovarian cancers family history.

When is rational to order a diagnostic test, or prescribe treatment: the threshold model as an explanation of practice variation.

PubMed

Djulbegovic, Benjamin; van den Ende, Jef; Hamm, Robert M; Mayrhofer, Thomas; Hozo, Iztok; Pauker, Stephen G

2015-05-01

The threshold model represents an important advance in the field of medical decision-making. It is a linchpin between evidence (which exists on the continuum of credibility) and decision-making (which is a categorical exercise - we decide to act or not act). The threshold concept is closely related to the question of rational decision-making. When should the physician act, that is order a diagnostic test, or prescribe treatment? The threshold model embodies the decision theoretic rationality that says the most rational decision is to prescribe treatment when the expected treatment benefit outweighs its expected harms. However, the well-documented large variation in the way physicians order diagnostic tests or decide to administer treatments is consistent with a notion that physicians' individual action thresholds vary. We present a narrative review summarizing the existing literature on physicians' use of a threshold strategy for decision-making. We found that the observed variation in decision action thresholds is partially due to the way people integrate benefits and harms. That is, explanation of variation in clinical practice can be reduced to a consideration of thresholds. Limited evidence suggests that non-expected utility threshold (non-EUT) models, such as regret-based and dual-processing models, may explain current medical practice better. However, inclusion of costs and recognition of risk attitudes towards uncertain treatment effects and comorbidities may improve the explanatory and predictive value of the EUT-based threshold models. The decision when to act is closely related to the question of rational choice. We conclude that the medical community has not yet fully defined criteria for rational clinical decision-making. The traditional notion of rationality rooted in EUT may need to be supplemented by reflective rationality, which strives to integrate all aspects of medical practice - medical, humanistic and socio-economic - within a coherent reasoning system. © 2015 Stichting European Society for Clinical Investigation Journal Foundation.

Fractal Approach to Erosion Threshold of Bentonites

NASA Astrophysics Data System (ADS)

Xu, Y. F.; Li, X. Y.

Bentonite has been considered as a candidate buffer material for the disposal of high-level radioactive waste (HLW) because of its low permeability, high sorption capacity, self-sealing characteristics and durability in a natural environment. Bentonite erosion caused by groundwater flow may take place at the interface of the compacted bentonite and fractured granite. Surface erosion of bentonite flocs is represented typically as an erosion threshold. Predicting the erosion threshold of bentonite flocs requires taking into account cohesion, which results from interactions between clay particles. Beyond the usual dependence on grain size, a significant correlation between erosion threshold and porosity measurements is confirmed for bentonite flocs. A fractal model for erosion threshold of bentonite flocs is proposed. Cohesion forces, the long-range van der Waals interaction between two clay particles are taken as the resource of the erosion threshold. The model verification is conducted by the comparison with experiments published in the literature. The results show that the proposed model for erosion threshold is in good agreement with the experimental data.

Genetic assessment of age-associated Alzheimer disease risk: Development and validation of a polygenic hazard score

PubMed Central

Cupples, L. Adrienne; Thompson, Wesley K.; Besser, Lilah; Kukull, Walter A.; Holland, Dominic; Chen, Chi-Hua; Brewer, James B.; Karow, David S.; Kauppi, Karolina; Bonham, Luke W.; Rosen, Howard J.; Miller, Bruce L.; Dillon, William P.; Wilson, David M.; Pericak-Vance, Margaret; Haines, Jonathan L.; Farrer, Lindsay A.; Mayeux, Richard; Hardy, John; Goate, Alison M.; Schellenberg, Gerard D.; Andreassen, Ole A.

2017-01-01

Background Identifying individuals at risk for developing Alzheimer disease (AD) is of utmost importance. Although genetic studies have identified AD-associated SNPs in APOE and other genes, genetic information has not been integrated into an epidemiological framework for risk prediction. Methods and findings Using genotype data from 17,008 AD cases and 37,154 controls from the International Genomics of Alzheimer’s Project (IGAP Stage 1), we identified AD-associated SNPs (at p < 10−5). We then integrated these AD-associated SNPs into a Cox proportional hazard model using genotype data from a subset of 6,409 AD patients and 9,386 older controls from Phase 1 of the Alzheimer’s Disease Genetics Consortium (ADGC), providing a polygenic hazard score (PHS) for each participant. By combining population-based incidence rates and the genotype-derived PHS for each individual, we derived estimates of instantaneous risk for developing AD, based on genotype and age, and tested replication in multiple independent cohorts (ADGC Phase 2, National Institute on Aging Alzheimer’s Disease Center [NIA ADC], and Alzheimer’s Disease Neuroimaging Initiative [ADNI], total n = 20,680). Within the ADGC Phase 1 cohort, individuals in the highest PHS quartile developed AD at a considerably lower age and had the highest yearly AD incidence rate. Among APOE ε3/3 individuals, the PHS modified expected age of AD onset by more than 10 y between the lowest and highest deciles (hazard ratio 3.34, 95% CI 2.62–4.24, p = 1.0 × 10−22). In independent cohorts, the PHS strongly predicted empirical age of AD onset (ADGC Phase 2, r = 0.90, p = 1.1 × 10−26) and longitudinal progression from normal aging to AD (NIA ADC, Cochran–Armitage trend test, p = 1.5 × 10−10), and was associated with neuropathology (NIA ADC, Braak stage of neurofibrillary tangles, p = 3.9 × 10−6, and Consortium to Establish a Registry for Alzheimer’s Disease score for neuritic plaques, p = 6.8 × 10−6) and in vivo markers of AD neurodegeneration (ADNI, volume loss within the entorhinal cortex, p = 6.3 × 10−6, and hippocampus, p = 7.9 × 10−5). Additional prospective validation of these results in non-US, non-white, and prospective community-based cohorts is necessary before clinical use. Conclusions We have developed a PHS for quantifying individual differences in age-specific genetic risk for AD. Within the cohorts studied here, polygenic architecture plays an important role in modifying AD risk beyond APOE. With thorough validation, quantification of inherited genetic variation may prove useful for stratifying AD risk and as an enrichment strategy in therapeutic trials. PMID:28323831

Genetic assessment of age-associated Alzheimer disease risk: Development and validation of a polygenic hazard score.

PubMed

Desikan, Rahul S; Fan, Chun Chieh; Wang, Yunpeng; Schork, Andrew J; Cabral, Howard J; Cupples, L Adrienne; Thompson, Wesley K; Besser, Lilah; Kukull, Walter A; Holland, Dominic; Chen, Chi-Hua; Brewer, James B; Karow, David S; Kauppi, Karolina; Witoelar, Aree; Karch, Celeste M; Bonham, Luke W; Yokoyama, Jennifer S; Rosen, Howard J; Miller, Bruce L; Dillon, William P; Wilson, David M; Hess, Christopher P; Pericak-Vance, Margaret; Haines, Jonathan L; Farrer, Lindsay A; Mayeux, Richard; Hardy, John; Goate, Alison M; Hyman, Bradley T; Schellenberg, Gerard D; McEvoy, Linda K; Andreassen, Ole A; Dale, Anders M

2017-03-01

Identifying individuals at risk for developing Alzheimer disease (AD) is of utmost importance. Although genetic studies have identified AD-associated SNPs in APOE and other genes, genetic information has not been integrated into an epidemiological framework for risk prediction. Using genotype data from 17,008 AD cases and 37,154 controls from the International Genomics of Alzheimer's Project (IGAP Stage 1), we identified AD-associated SNPs (at p < 10-5). We then integrated these AD-associated SNPs into a Cox proportional hazard model using genotype data from a subset of 6,409 AD patients and 9,386 older controls from Phase 1 of the Alzheimer's Disease Genetics Consortium (ADGC), providing a polygenic hazard score (PHS) for each participant. By combining population-based incidence rates and the genotype-derived PHS for each individual, we derived estimates of instantaneous risk for developing AD, based on genotype and age, and tested replication in multiple independent cohorts (ADGC Phase 2, National Institute on Aging Alzheimer's Disease Center [NIA ADC], and Alzheimer's Disease Neuroimaging Initiative [ADNI], total n = 20,680). Within the ADGC Phase 1 cohort, individuals in the highest PHS quartile developed AD at a considerably lower age and had the highest yearly AD incidence rate. Among APOE ε3/3 individuals, the PHS modified expected age of AD onset by more than 10 y between the lowest and highest deciles (hazard ratio 3.34, 95% CI 2.62-4.24, p = 1.0 × 10-22). In independent cohorts, the PHS strongly predicted empirical age of AD onset (ADGC Phase 2, r = 0.90, p = 1.1 × 10-26) and longitudinal progression from normal aging to AD (NIA ADC, Cochran-Armitage trend test, p = 1.5 × 10-10), and was associated with neuropathology (NIA ADC, Braak stage of neurofibrillary tangles, p = 3.9 × 10-6, and Consortium to Establish a Registry for Alzheimer's Disease score for neuritic plaques, p = 6.8 × 10-6) and in vivo markers of AD neurodegeneration (ADNI, volume loss within the entorhinal cortex, p = 6.3 × 10-6, and hippocampus, p = 7.9 × 10-5). Additional prospective validation of these results in non-US, non-white, and prospective community-based cohorts is necessary before clinical use. We have developed a PHS for quantifying individual differences in age-specific genetic risk for AD. Within the cohorts studied here, polygenic architecture plays an important role in modifying AD risk beyond APOE. With thorough validation, quantification of inherited genetic variation may prove useful for stratifying AD risk and as an enrichment strategy in therapeutic trials.

Threshold model of cascades in empirical temporal networks

NASA Astrophysics Data System (ADS)

Karimi, Fariba; Holme, Petter

2013-08-01

Threshold models try to explain the consequences of social influence like the spread of fads and opinions. Along with models of epidemics, they constitute a major theoretical framework of social spreading processes. In threshold models on static networks, an individual changes her state if a certain fraction of her neighbors has done the same. When there are strong correlations in the temporal aspects of contact patterns, it is useful to represent the system as a temporal network. In such a system, not only contacts but also the time of the contacts are represented explicitly. In many cases, bursty temporal patterns slow down disease spreading. However, as we will see, this is not a universal truth for threshold models. In this work we propose an extension of Watts’s classic threshold model to temporal networks. We do this by assuming that an agent is influenced by contacts which lie a certain time into the past. I.e., the individuals are affected by contacts within a time window. In addition to thresholds in the fraction of contacts, we also investigate the number of contacts within the time window as a basis for influence. To elucidate the model’s behavior, we run the model on real and randomized empirical contact datasets.

The role of glacier changes and threshold definition in the characterisation of future streamflow droughts in glacierised catchments

NASA Astrophysics Data System (ADS)

Van Tiel, Marit; Teuling, Adriaan J.; Wanders, Niko; Vis, Marc J. P.; Stahl, Kerstin; Van Loon, Anne F.

2018-01-01

Glaciers are essential hydrological reservoirs, storing and releasing water at various timescales. Short-term variability in glacier melt is one of the causes of streamflow droughts, here defined as deficiencies from the flow regime. Streamflow droughts in glacierised catchments have a wide range of interlinked causing factors related to precipitation and temperature on short and long timescales. Climate change affects glacier storage capacity, with resulting consequences for discharge regimes and streamflow drought. Future projections of streamflow drought in glacierised basins can, however, strongly depend on the modelling strategies and analysis approaches applied. Here, we examine the effect of different approaches, concerning the glacier modelling and the drought threshold, on the characterisation of streamflow droughts in glacierised catchments. Streamflow is simulated with the Hydrologiska Byråns Vattenbalansavdelning (HBV-light) model for two case study catchments, the Nigardsbreen catchment in Norway and the Wolverine catchment in Alaska, and two future climate change scenarios (RCP4.5 and RCP8.5). Two types of glacier modelling are applied, a constant and dynamic glacier area conceptualisation. Streamflow droughts are identified with the variable threshold level method and their characteristics are compared between two periods, a historical (1975-2004) and future (2071-2100) period. Two existing threshold approaches to define future droughts are employed: (1) the threshold from the historical period; (2) a transient threshold approach, whereby the threshold adapts every year in the future to the changing regimes. Results show that drought characteristics differ among the combinations of glacier area modelling and thresholds. The historical threshold combined with a dynamic glacier area projects extreme increases in drought severity in the future, caused by the regime shift due to a reduction in glacier area. The historical threshold combined with a constant glacier area results in a drastic decrease of the number of droughts. The drought characteristics between future and historical periods are more similar when the transient threshold is used, for both glacier area conceptualisations. With the transient threshold, factors causing future droughts can be analysed. This study revealed the different effects of methodological choices on future streamflow drought projections and it highlights how the options can be used to analyse different aspects of future droughts: the transient threshold for analysing future drought processes, the historical threshold to assess changes between periods, the constant glacier area to analyse the effect of short-term climate variability on droughts and the dynamic glacier area to model more realistic future discharges under climate change.

A Continuous Threshold Expectile Model.

PubMed

Zhang, Feipeng; Li, Qunhua

2017-12-01

Expectile regression is a useful tool for exploring the relation between the response and the explanatory variables beyond the conditional mean. A continuous threshold expectile regression is developed for modeling data in which the effect of a covariate on the response variable is linear but varies below and above an unknown threshold in a continuous way. The estimators for the threshold and the regression coefficients are obtained using a grid search approach. The asymptotic properties for all the estimators are derived, and the estimator for the threshold is shown to achieve root-n consistency. A weighted CUSUM type test statistic is proposed for the existence of a threshold at a given expectile, and its asymptotic properties are derived under both the null and the local alternative models. This test only requires fitting the model under the null hypothesis in the absence of a threshold, thus it is computationally more efficient than the likelihood-ratio type tests. Simulation studies show that the proposed estimators and test have desirable finite sample performance in both homoscedastic and heteroscedastic cases. The application of the proposed method on a Dutch growth data and a baseball pitcher salary data reveals interesting insights. The proposed method is implemented in the R package cthreshER .

Thresholds and the rising pion inclusive cross section

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jones, S.T.

In the context of the hypothesis of the Pomeron-f identity, it is shown that the rising pion inclusive cross section can be explained over a wide range of energies as a series of threshold effects. Low-mass thresholds are seen to be important. In order to understand the contributions of high-mass thresholds (flavoring), a simple two-channel multiperipheral model is examined. The analysis sheds light on the relation between thresholds and Mueller-Regge couplings. In particular, it is seen that inclusive-, and total-cross-section threshold mechanisms may differ. A quantitative model based on this idea and utilizing previous total-cross-section fits is seen to agreemore » well with experiment.« less

Genetic Analysis and QTL Mapping of Fruit Peduncle Length in Cucumber (Cucumis sativus L.)

PubMed Central

Zhang, Song; Wang, Ye; Zhang, Sheng-Ping; Gu, Xing-Fang

2016-01-01

Mechanized harvesting of cucumbers offers significant advantages compared to manual labor as both shortages and costs of labor increase. However the efficient use of machines depends on breeding plants with longer peduncles, but the genetic and molecular basis of fruit peduncle development in cucumber is not well understood. In this study, F2 populations were developed from a cross between two inbred lines, 1101 with a long peduncle and 1694 with a short peduncle. These were grown at two field sites, Hainan, with a tropical marine climate, in December 2014, and Beijing, with a warm temperate climate, in May 2015. Electron microscope examination of the pith cells in the peduncles of the two parental lines showed that line 1101 had significantly greater numbers of smaller cells compared to line 1694. The inheritance of cucumber fruit peduncle length (FPL) was investigated by the mixed major gene and polygene inheritance model. Genetic analysis indicated that FPL in cucumber is quantitatively inherited and controlled by one additive major gene and additive-dominant polygenes (D-2 model). A total of 1460 pairs of SSR (simple sequence repeat) primers were analyzed to identify quantitative trait loci (QTLs). Two similar genetic maps with 78 SSR markers which covered 720.6 cM in seven linkage groups were constructed based on two F2 populations. QTL analysis from the data collected at the two field sites showed that there are two minor QTLs on chromosome 1, named qfpl1.1 and qfpl1.2, and one major QTL on chromosome 6, named qfpl6.1. The marker UW021226, which was the closest one to qfpl6.1, had an accuracy rate of 79.0% when tested against plants selected from populations of the two parents. The results from this study provide insights into the inheritance and molecular mechanism of the variation of FPL in cucumber, and further research will be carried out to fine map qfpl6.1 to develop more accurate markers for MAS breeding. PMID:27936210

Mathematical Model of Naive T Cell Division and Survival IL-7 Thresholds.

PubMed

Reynolds, Joseph; Coles, Mark; Lythe, Grant; Molina-París, Carmen

2013-01-01

We develop a mathematical model of the peripheral naive T cell population to study the change in human naive T cell numbers from birth to adulthood, incorporating thymic output and the availability of interleukin-7 (IL-7). The model is formulated as three ordinary differential equations: two describe T cell numbers, in a resting state and progressing through the cell cycle. The third is introduced to describe changes in IL-7 availability. Thymic output is a decreasing function of time, representative of the thymic atrophy observed in aging humans. Each T cell is assumed to possess two interleukin-7 receptor (IL-7R) signaling thresholds: a survival threshold and a second, higher, proliferation threshold. If the IL-7R signaling strength is below its survival threshold, a cell may undergo apoptosis. When the signaling strength is above the survival threshold, but below the proliferation threshold, the cell survives but does not divide. Signaling strength above the proliferation threshold enables entry into cell cycle. Assuming that individual cell thresholds are log-normally distributed, we derive population-average rates for apoptosis and entry into cell cycle. We have analyzed the adiabatic change in homeostasis as thymic output decreases. With a parameter set representative of a healthy individual, the model predicts a unique equilibrium number of T cells. In a parameter range representative of persistent viral or bacterial infection, where naive T cell cycle progression is impaired, a decrease in thymic output may result in the collapse of the naive T cell repertoire.

A study of life prediction differences for a nickel-base Alloy 690 using a threshold and a non-threshold model

NASA Astrophysics Data System (ADS)

Young, B. A.; Gao, Xiaosheng; Srivatsan, T. S.

2009-10-01

In this paper we compare and contrast the crack growth rate of a nickel-base superalloy (Alloy 690) in the Pressurized Water Reactor (PWR) environment. Over the last few years, a preponderance of test data has been gathered on both Alloy 690 thick plate and Alloy 690 tubing. The original model, essentially based on a small data set for thick plate, compensated for temperature, load ratio and stress-intensity range but did not compensate for the fatigue threshold of the material. As additional test data on both plate and tube product became available the model was gradually revised to account for threshold properties. Both the original and revised models generated acceptable results for data that were above 1 × 10 -11 m/s. However, the test data at the lower growth rates were over-predicted by the non-threshold model. Since the original model did not take the fatigue threshold into account, this model predicted no operating stress below which the material would effectively undergo fatigue crack growth. Because of an over-prediction of the growth rate below 1 × 10 -11 m/s, due to a combination of low stress, small crack size and long rise-time, the model in general leads to an under-prediction of the total available life of the components.

How to determine an optimal threshold to classify real-time crash-prone traffic conditions?

PubMed

Yang, Kui; Yu, Rongjie; Wang, Xuesong; Quddus, Mohammed; Xue, Lifang

2018-08-01

One of the proactive approaches in reducing traffic crashes is to identify hazardous traffic conditions that may lead to a traffic crash, known as real-time crash prediction. Threshold selection is one of the essential steps of real-time crash prediction. And it provides the cut-off point for the posterior probability which is used to separate potential crash warnings against normal traffic conditions, after the outcome of the probability of a crash occurring given a specific traffic condition on the basis of crash risk evaluation models. There is however a dearth of research that focuses on how to effectively determine an optimal threshold. And only when discussing the predictive performance of the models, a few studies utilized subjective methods to choose the threshold. The subjective methods cannot automatically identify the optimal thresholds in different traffic and weather conditions in real application. Thus, a theoretical method to select the threshold value is necessary for the sake of avoiding subjective judgments. The purpose of this study is to provide a theoretical method for automatically identifying the optimal threshold. Considering the random effects of variable factors across all roadway segments, the mixed logit model was utilized to develop the crash risk evaluation model and further evaluate the crash risk. Cross-entropy, between-class variance and other theories were employed and investigated to empirically identify the optimal threshold. And K-fold cross-validation was used to validate the performance of proposed threshold selection methods with the help of several evaluation criteria. The results indicate that (i) the mixed logit model can obtain a good performance; (ii) the classification performance of the threshold selected by the minimum cross-entropy method outperforms the other methods according to the criteria. This method can be well-behaved to automatically identify thresholds in crash prediction, by minimizing the cross entropy between the original dataset with continuous probability of a crash occurring and the binarized dataset after using the thresholds to separate potential crash warnings against normal traffic conditions. Copyright © 2018 Elsevier Ltd. All rights reserved.

How much crosstalk can be allowed in a stereoscopic system at various grey levels?

NASA Astrophysics Data System (ADS)

Shestak, Sergey; Kim, Daesik; Kim, Yongie

2012-03-01

We have calculated a perceptual threshold of stereoscopic crosstalk on the basis of mathematical model of human vision sensitivity. Instead of linear model of just noticeable difference (JND) known as Weber's law we applied nonlinear Barten's model. The predicted crosstalk threshold varies with the background luminance. The calculated values of threshold are in a reasonable agreement with known experimental data. We calculated perceptual threshold of crosstalk for various combinations of the applied grey level. This result can be applied for the assessment of grey-to-grey crosstalk compensation. Further computational analysis of the applied model predicts the increase of the displayable image contrast with reduction of the maximum displayable luminance.

Sliding mode control of outbreaks of emerging infectious diseases.

PubMed

Xiao, Yanni; Xu, Xiaxia; Tang, Sanyi

2012-10-01

This paper proposes and analyzes a mathematical model of an infectious disease system with a piecewise control function concerning threshold policy for disease management strategy. The proposed models extend the classic models by including a piecewise incidence rate to represent control or precautionary measures being triggered once the number of infected individuals exceeds a threshold level. The long-term behaviour of the proposed non-smooth system under this strategy consists of the so-called sliding motion-a very rapid switching between application and interruption of the control action. Model solutions ultimately approach either one of two endemic states for two structures or the sliding equilibrium on the switching surface, depending on the threshold level. Our findings suggest that proper combinations of threshold densities and control intensities based on threshold policy can either preclude outbreaks or lead the number of infected to a previously chosen level.

Genome-wide association study of handedness excludes simple genetic models

PubMed Central

Armour, J AL; Davison, A; McManus, I C

2014-01-01

Handedness is a human behavioural phenotype that appears to be congenital, and is often assumed to be inherited, but for which the developmental origin and underlying causation(s) have been elusive. Models of the genetic basis of variation in handedness have been proposed that fit different features of the observed resemblance between relatives, but none has been decisively tested or a corresponding causative locus identified. In this study, we applied data from well-characterised individuals studied at the London Twin Research Unit. Analysis of genome-wide SNP data from 3940 twins failed to identify any locus associated with handedness at a genome-wide level of significance. The most straightforward interpretation of our analyses is that they exclude the simplest formulations of the ‘right-shift' model of Annett and the ‘dextral/chance' model of McManus, although more complex modifications of those models are still compatible with our observations. For polygenic effects, our study is inadequately powered to reliably detect alleles with effect sizes corresponding to an odds ratio of 1.2, but should have good power to detect effects at an odds ratio of 2 or more. PMID:24065183

Evidence Accumulator or Decision Threshold – Which Cortical Mechanism are We Observing?

PubMed Central

Simen, Patrick

2012-01-01

Most psychological models of perceptual decision making are of the accumulation-to-threshold variety. The neural basis of accumulation in parietal and prefrontal cortex is therefore a topic of great interest in neuroscience. In contrast, threshold mechanisms have received less attention, and their neural basis has usually been sought in subcortical structures. Here I analyze a model of a decision threshold that can be implemented in the same cortical areas as evidence accumulators, and whose behavior bears on two open questions in decision neuroscience: (1) When ramping activity is observed in a brain region during decision making, does it reflect evidence accumulation? (2) Are changes in speed-accuracy tradeoffs and response biases more likely to be achieved by changes in thresholds, or in accumulation rates and starting points? The analysis suggests that task-modulated ramping activity, by itself, is weak evidence that a brain area mediates evidence accumulation as opposed to threshold readout; and that signs of modulated accumulation are as likely to indicate threshold adaptation as adaptation of starting points and accumulation rates. These conclusions imply that how thresholds are modeled can dramatically impact accumulator-based interpretations of this data. PMID:22737136

Thresholds for conservation and management: structured decision making as a conceptual framework

USGS Publications Warehouse

Nichols, James D.; Eaton, Mitchell J.; Martin, Julien; Edited by Guntenspergen, Glenn R.

2014-01-01

changes in system dynamics. They are frequently incorporated into ecological models used to project system responses to management actions. Utility thresholds are components of management objectives and are values of state or performance variables at which small changes yield substantial changes in the value of the management outcome. Decision thresholds are values of system state variables at which small changes prompt changes in management actions in order to reach specified management objectives. Decision thresholds are derived from the other components of the decision process.We advocate a structured decision making (SDM) approach within which the following components are identified: objectives (possibly including utility thresholds), potential actions, models (possibly including ecological thresholds), monitoring program, and a solution algorithm (which produces decision thresholds). Adaptive resource management (ARM) is described as a special case of SDM developed for recurrent decision problems that are characterized by uncertainty. We believe that SDM, in general, and ARM, in particular, provide good approaches to conservation and management. Use of SDM and ARM also clarifies the distinct roles of ecological thresholds, utility thresholds, and decision thresholds in informed decision processes.

Genome-wide association study of resistance to ear rot by Fusarium verticillioides in a tropical field maize and popcorn core collection

USDA-ARS?s Scientific Manuscript database

Fusarium ear rot (caused by Fusarium verticillioides) is one of the most prevalent diseases of maize worldwide, and has one of the greatest negative economic impacts on this cereal crop globally. Fusarium ear rot is a highly complex trait, under polygenic control with minor effects per gene and low ...

76 FR 15968 - Notice of Availability of the Draft Environmental Impact Statement and Public Hearing Notice for...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-03-22

... to generate electric power and would capture carbon dioxide (CO 2 ) for use in enhanced oil recovery... cooperative agreement. The polygen plant would be built on a 600 acre oil field site in Ector County, Texas, north of the abandoned oil town of Penwell. Summit would design and construct the plant to capture...

Signatures of negative selection in the genetic architecture of human complex traits.

PubMed

Zeng, Jian; de Vlaming, Ronald; Wu, Yang; Robinson, Matthew R; Lloyd-Jones, Luke R; Yengo, Loic; Yap, Chloe X; Xue, Angli; Sidorenko, Julia; McRae, Allan F; Powell, Joseph E; Montgomery, Grant W; Metspalu, Andres; Esko, Tonu; Gibson, Greg; Wray, Naomi R; Visscher, Peter M; Yang, Jian

2018-05-01

We develop a Bayesian mixed linear model that simultaneously estimates single-nucleotide polymorphism (SNP)-based heritability, polygenicity (proportion of SNPs with nonzero effects), and the relationship between SNP effect size and minor allele frequency for complex traits in conventionally unrelated individuals using genome-wide SNP data. We apply the method to 28 complex traits in the UK Biobank data (N = 126,752) and show that on average, 6% of SNPs have nonzero effects, which in total explain 22% of phenotypic variance. We detect significant (P < 0.05/28) signatures of natural selection in the genetic architecture of 23 traits, including reproductive, cardiovascular, and anthropometric traits, as well as educational attainment. The significant estimates of the relationship between effect size and minor allele frequency in complex traits are consistent with a model of negative (or purifying) selection, as confirmed by forward simulation. We conclude that negative selection acts pervasively on the genetic variants associated with human complex traits.

Rare and low-frequency coding variants alter human adult height.

PubMed

Marouli, Eirini; Graff, Mariaelisa; Medina-Gomez, Carolina; Lo, Ken Sin; Wood, Andrew R; Kjaer, Troels R; Fine, Rebecca S; Lu, Yingchang; Schurmann, Claudia; Highland, Heather M; Rüeger, Sina; Thorleifsson, Gudmar; Justice, Anne E; Lamparter, David; Stirrups, Kathleen E; Turcot, Valérie; Young, Kristin L; Winkler, Thomas W; Esko, Tõnu; Karaderi, Tugce; Locke, Adam E; Masca, Nicholas G D; Ng, Maggie C Y; Mudgal, Poorva; Rivas, Manuel A; Vedantam, Sailaja; Mahajan, Anubha; Guo, Xiuqing; Abecasis, Goncalo; Aben, Katja K; Adair, Linda S; Alam, Dewan S; Albrecht, Eva; Allin, Kristine H; Allison, Matthew; Amouyel, Philippe; Appel, Emil V; Arveiler, Dominique; Asselbergs, Folkert W; Auer, Paul L; Balkau, Beverley; Banas, Bernhard; Bang, Lia E; Benn, Marianne; Bergmann, Sven; Bielak, Lawrence F; Blüher, Matthias; Boeing, Heiner; Boerwinkle, Eric; Böger, Carsten A; Bonnycastle, Lori L; Bork-Jensen, Jette; Bots, Michiel L; Bottinger, Erwin P; Bowden, Donald W; Brandslund, Ivan; Breen, Gerome; Brilliant, Murray H; Broer, Linda; Burt, Amber A; Butterworth, Adam S; Carey, David J; Caulfield, Mark J; Chambers, John C; Chasman, Daniel I; Chen, Yii-Der Ida; Chowdhury, Rajiv; Christensen, Cramer; Chu, Audrey Y; Cocca, Massimiliano; Collins, Francis S; Cook, James P; Corley, Janie; Galbany, Jordi Corominas; Cox, Amanda J; Cuellar-Partida, Gabriel; Danesh, John; Davies, Gail; de Bakker, Paul I W; de Borst, Gert J; de Denus, Simon; de Groot, Mark C H; de Mutsert, Renée; Deary, Ian J; Dedoussis, George; Demerath, Ellen W; den Hollander, Anneke I; Dennis, Joe G; Di Angelantonio, Emanuele; Drenos, Fotios; Du, Mengmeng; Dunning, Alison M; Easton, Douglas F; Ebeling, Tapani; Edwards, Todd L; Ellinor, Patrick T; Elliott, Paul; Evangelou, Evangelos; Farmaki, Aliki-Eleni; Faul, Jessica D; Feitosa, Mary F; Feng, Shuang; Ferrannini, Ele; Ferrario, Marco M; Ferrieres, Jean; Florez, Jose C; Ford, Ian; Fornage, Myriam; Franks, Paul W; Frikke-Schmidt, Ruth; Galesloot, Tessel E; Gan, Wei; Gandin, Ilaria; Gasparini, Paolo; Giedraitis, Vilmantas; Giri, Ayush; Girotto, Giorgia; Gordon, Scott D; Gordon-Larsen, Penny; Gorski, Mathias; Grarup, Niels; Grove, Megan L; Gudnason, Vilmundur; Gustafsson, Stefan; Hansen, Torben; Harris, Kathleen Mullan; Harris, Tamara B; Hattersley, Andrew T; Hayward, Caroline; He, Liang; Heid, Iris M; Heikkilä, Kauko; Helgeland, Øyvind; Hernesniemi, Jussi; Hewitt, Alex W; Hocking, Lynne J; Hollensted, Mette; Holmen, Oddgeir L; Hovingh, G Kees; Howson, Joanna M M; Hoyng, Carel B; Huang, Paul L; Hveem, Kristian; Ikram, M Arfan; Ingelsson, Erik; Jackson, Anne U; Jansson, Jan-Håkan; Jarvik, Gail P; Jensen, Gorm B; Jhun, Min A; Jia, Yucheng; Jiang, Xuejuan; Johansson, Stefan; Jørgensen, Marit E; Jørgensen, Torben; Jousilahti, Pekka; Jukema, J Wouter; Kahali, Bratati; Kahn, René S; Kähönen, Mika; Kamstrup, Pia R; Kanoni, Stavroula; Kaprio, Jaakko; Karaleftheri, Maria; Kardia, Sharon L R; Karpe, Fredrik; Kee, Frank; Keeman, Renske; Kiemeney, Lambertus A; Kitajima, Hidetoshi; Kluivers, Kirsten B; Kocher, Thomas; Komulainen, Pirjo; Kontto, Jukka; Kooner, Jaspal S; Kooperberg, Charles; Kovacs, Peter; Kriebel, Jennifer; Kuivaniemi, Helena; Küry, Sébastien; Kuusisto, Johanna; La Bianca, Martina; Laakso, Markku; Lakka, Timo A; Lange, Ethan M; Lange, Leslie A; Langefeld, Carl D; Langenberg, Claudia; Larson, Eric B; Lee, I-Te; Lehtimäki, Terho; Lewis, Cora E; Li, Huaixing; Li, Jin; Li-Gao, Ruifang; Lin, Honghuang; Lin, Li-An; Lin, Xu; Lind, Lars; Lindström, Jaana; Linneberg, Allan; Liu, Yeheng; Liu, Yongmei; Lophatananon, Artitaya; Luan, Jian'an; Lubitz, Steven A; Lyytikäinen, Leo-Pekka; Mackey, David A; Madden, Pamela A F; Manning, Alisa K; Männistö, Satu; Marenne, Gaëlle; Marten, Jonathan; Martin, Nicholas G; Mazul, Angela L; Meidtner, Karina; Metspalu, Andres; Mitchell, Paul; Mohlke, Karen L; Mook-Kanamori, Dennis O; Morgan, Anna; Morris, Andrew D; Morris, Andrew P; Müller-Nurasyid, Martina; Munroe, Patricia B; Nalls, Mike A; Nauck, Matthias; Nelson, Christopher P; Neville, Matt; Nielsen, Sune F; Nikus, Kjell; Njølstad, Pål R; Nordestgaard, Børge G; Ntalla, Ioanna; O'Connel, Jeffrey R; Oksa, Heikki; Loohuis, Loes M Olde; Ophoff, Roel A; Owen, Katharine R; Packard, Chris J; Padmanabhan, Sandosh; Palmer, Colin N A; Pasterkamp, Gerard; Patel, Aniruddh P; Pattie, Alison; Pedersen, Oluf; Peissig, Peggy L; Peloso, Gina M; Pennell, Craig E; Perola, Markus; Perry, James A; Perry, John R B; Person, Thomas N; Pirie, Ailith; Polasek, Ozren; Posthuma, Danielle; Raitakari, Olli T; Rasheed, Asif; Rauramaa, Rainer; Reilly, Dermot F; Reiner, Alex P; Renström, Frida; Ridker, Paul M; Rioux, John D; Robertson, Neil; Robino, Antonietta; Rolandsson, Olov; Rudan, Igor; Ruth, Katherine S; Saleheen, Danish; Salomaa, Veikko; Samani, Nilesh J; Sandow, Kevin; Sapkota, Yadav; Sattar, Naveed; Schmidt, Marjanka K; Schreiner, Pamela J; Schulze, Matthias B; Scott, Robert A; Segura-Lepe, Marcelo P; Shah, Svati; Sim, Xueling; Sivapalaratnam, Suthesh; Small, Kerrin S; Smith, Albert Vernon; Smith, Jennifer A; Southam, Lorraine; Spector, Timothy D; Speliotes, Elizabeth K; Starr, John M; Steinthorsdottir, Valgerdur; Stringham, Heather M; Stumvoll, Michael; Surendran, Praveen; 't Hart, Leen M; Tansey, Katherine E; Tardif, Jean-Claude; Taylor, Kent D; Teumer, Alexander; Thompson, Deborah J; Thorsteinsdottir, Unnur; Thuesen, Betina H; Tönjes, Anke; Tromp, Gerard; Trompet, Stella; Tsafantakis, Emmanouil; Tuomilehto, Jaakko; Tybjaerg-Hansen, Anne; Tyrer, Jonathan P; Uher, Rudolf; Uitterlinden, André G; Ulivi, Sheila; van der Laan, Sander W; Van Der Leij, Andries R; van Duijn, Cornelia M; van Schoor, Natasja M; van Setten, Jessica; Varbo, Anette; Varga, Tibor V; Varma, Rohit; Edwards, Digna R Velez; Vermeulen, Sita H; Vestergaard, Henrik; Vitart, Veronique; Vogt, Thomas F; Vozzi, Diego; Walker, Mark; Wang, Feijie; Wang, Carol A; Wang, Shuai; Wang, Yiqin; Wareham, Nicholas J; Warren, Helen R; Wessel, Jennifer; Willems, Sara M; Wilson, James G; Witte, Daniel R; Woods, Michael O; Wu, Ying; Yaghootkar, Hanieh; Yao, Jie; Yao, Pang; Yerges-Armstrong, Laura M; Young, Robin; Zeggini, Eleftheria; Zhan, Xiaowei; Zhang, Weihua; Zhao, Jing Hua; Zhao, Wei; Zhao, Wei; Zheng, He; Zhou, Wei; Rotter, Jerome I; Boehnke, Michael; Kathiresan, Sekar; McCarthy, Mark I; Willer, Cristen J; Stefansson, Kari; Borecki, Ingrid B; Liu, Dajiang J; North, Kari E; Heard-Costa, Nancy L; Pers, Tune H; Lindgren, Cecilia M; Oxvig, Claus; Kutalik, Zoltán; Rivadeneira, Fernando; Loos, Ruth J F; Frayling, Timothy M; Hirschhorn, Joel N; Deloukas, Panos; Lettre, Guillaume

2017-02-09

Height is a highly heritable, classic polygenic trait with approximately 700 common associated variants identified through genome-wide association studies so far. Here, we report 83 height-associated coding variants with lower minor-allele frequencies (in the range of 0.1-4.8%) and effects of up to 2 centimetres per allele (such as those in IHH, STC2, AR and CRISPLD2), greater than ten times the average effect of common variants. In functional follow-up studies, rare height-increasing alleles of STC2 (giving an increase of 1-2 centimetres per allele) compromised proteolytic inhibition of PAPP-A and increased cleavage of IGFBP-4 in vitro, resulting in higher bioavailability of insulin-like growth factors. These 83 height-associated variants overlap genes that are mutated in monogenic growth disorders and highlight new biological candidates (such as ADAMTS3, IL11RA and NOX4) and pathways (such as proteoglycan and glycosaminoglycan synthesis) involved in growth. Our results demonstrate that sufficiently large sample sizes can uncover rare and low-frequency variants of moderate-to-large effect associated with polygenic human phenotypes, and that these variants implicate relevant genes and pathways.

Nationwide Genomic Study in Denmark Reveals Remarkable Population Homogeneity

PubMed Central

Athanasiadis, Georgios; Cheng, Jade Y.; Vilhjálmsson, Bjarni J.; Jørgensen, Frank G.; Als, Thomas D.; Le Hellard, Stephanie; Espeseth, Thomas; Sullivan, Patrick F.; Hultman, Christina M.; Kjærgaard, Peter C.; Schierup, Mikkel H.; Mailund, Thomas

2016-01-01

Denmark has played a substantial role in the history of Northern Europe. Through a nationwide scientific outreach initiative, we collected genetic and anthropometrical data from ∼800 high school students and used them to elucidate the genetic makeup of the Danish population, as well as to assess polygenic predictions of phenotypic traits in adolescents. We observed remarkable homogeneity across different geographic regions, although we could still detect weak signals of genetic structure reflecting the history of the country. Denmark presented genomic affinity with primarily neighboring countries with overall resemblance of decreasing weight from Britain, Sweden, Norway, Germany, and France. A Polish admixture signal was detected in Zealand and Funen, and our date estimates coincided with historical evidence of Wend settlements in the south of Denmark. We also observed considerably diverse demographic histories among Scandinavian countries, with Denmark having the smallest current effective population size compared to Norway and Sweden. Finally, we found that polygenic prediction of self-reported adolescent height in the population was remarkably accurate (R2 = 0.639 ± 0.015). The high homogeneity of the Danish population could render population structure a lesser concern for the upcoming large-scale gene-mapping studies in the country. PMID:27535931

Artificial selection for a secondary sexual character in males of Drosophila silvestris from Hawaii

PubMed Central

Carson, Hampton L.; Teramoto, Linden T.

1984-01-01

Drosophila silvestris is endemic to the rain forests of Hawaii Island. In populations from the northeast side, the male foreleg tibia bears about 100 long cilia; these are used as a brush to stimulate the female during courtship. Cyclical family selection for high and low cilia number was carried out on progeny of lines started from single wild isofemales collected at a single site. Significant response in both directions was obtained; in the third generation the lines differed by a mean of 25 cilia. Despite much effort to save them, both lines died out without further advance; the low cilia number line died after five and the high cilia number line died after nine generations. The data are compatible with the view that the cilia character is polygenic and is maintained in nature by a stabilizing sexual selection that also favors a polygenic heterozygous state. Although selection in these experiments resulted in dysgenesis, such a result is not inevitable. Disorganization and reorganization of such a genetic system following a population bottleneck might be important as a predisposing condition for the emergence of a specifically novel and possibly isolating mode of courtship. PMID:16593479

Genetic basis of hybrid male sterility among three closely related species of Drosophila.

PubMed

Mishra, Paras Kumar; Singh, B N

2005-05-01

The genetic basis of hybrid male sterility among three closely related species, Drosophila bipectinata, D. parabipectinata and D. malerkotliana has been investigated by using backcross analysis methods. The role of Y chromosome, major hybrid sterility (MHS) genes (genetic factors) and cytoplasm (non-genetic factor) have been studied in the hybrids of these three species. In the species pair, bipectinata--parabipectinata, Y chromosome introgression of parabipectinata in the genomic background of bipectinata and the reciprocal Y chromosome introgression were unsuccessful as all males in second backcross generation were sterile. Neither MHS genes nor cytoplasm was found important for sterility. This suggests the involvement of X-Y, X-autosomes or polygenic interactions in hybrid male sterility. In bipectinata--malerkotliana and parabipectinata--malerkotliana species pairs, Y chromosome substitution in reciprocal crosses did not affect male fertility. Backcross analyses also show no involvement of MHS genes or cytoplasm in hybrid male sterility in these two species pairs. Therefore, X- autosome interaction or polygenic interaction is supposed to be involved in hybrid male sterility in these two species pairs. These findings also provide evidence that even in closely related species, genetic interactions underlying hybrid male sterility may vary.

Partitioning the variability of fasting plasma glucose levels in pedigrees. Genetic and environmental factors.

PubMed

Boehnke, M; Moll, P P; Kottke, B A; Weidman, W H

1987-04-01

Fasting plasma glucose measurements made in 1972-1977 on normoglycemic individuals in three-generation Caucasian pedigrees from Rochester, Minnesota were analyzed. The authors determined the contributions of polygenic loci and environmental factors to fasting plasma glucose variability in these pedigrees. To that end, fasting plasma glucose measurements were normalized by an inverse normal scores transformation and then regressed separately for males and females on measured concomitants including age, body mass index (weight/height2), season of measurement, sex hormone use, and diuretic use. The authors found that 27.7% of the variability in normalized fasting plasma glucose in these pedigrees is explained by these measured concomitants. Subsequent variance components analysis suggested that unmeasured polygenic loci and unmeasured shared environmental factors together account for at least an additional 36.7% of the variability in normalized fasting plasma glucose, with genes alone accounting for at least 27.3%. These results are consistent with the known familiality of diabetes, for which fasting plasma glucose level is an important predictor. Further, these familial factors provide an explanation for at least half the variability in normalized fasting plasma glucose which remains after regression on known concomitants.

Construction of an Exome-Wide Risk Score for Schizophrenia Based on a Weighted Burden Test.

PubMed

Curtis, David

2018-01-01

Polygenic risk scores obtained as a weighted sum of associated variants can be used to explore association in additional data sets and to assign risk scores to individuals. The methods used to derive polygenic risk scores from common SNPs are not suitable for variants detected in whole exome sequencing studies. Rare variants, which may have major effects, are seen too infrequently to judge whether they are associated and may not be shared between training and test subjects. A method is proposed whereby variants are weighted according to their frequency, their annotations and the genes they affect. A weighted sum across all variants provides an individual risk score. Scores constructed in this way are used in a weighted burden test and are shown to be significantly different between schizophrenia cases and controls using a five-way cross-validation procedure. This approach represents a first attempt to summarise exome sequence variation into a summary risk score, which could be combined with risk scores from common variants and from environmental factors. It is hoped that the method could be developed further. © 2017 John Wiley & Sons Ltd/University College London.

A Threshold Model of Social Support, Adjustment, and Distress after Breast Cancer Treatment

ERIC Educational Resources Information Center

Mallinckrodt, Brent; Armer, Jane M.; Heppner, P. Paul

2012-01-01

This study examined a threshold model that proposes that social support exhibits a curvilinear association with adjustment and distress, such that support in excess of a critical threshold level has decreasing incremental benefits. Women diagnosed with a first occurrence of breast cancer (N = 154) completed survey measures of perceived support…

Prediction of insufficient serum vitamin D status in older women: a validated model.

PubMed

Merlijn, T; Swart, K M A; Lips, P; Heymans, M W; Sohl, E; Van Schoor, N M; Netelenbos, C J; Elders, P J M

2018-05-28

We developed an externally validated simple prediction model to predict serum 25(OH)D levels < 30, < 40, < 50 and 60 nmol/L in older women with risk factors for fractures. The benefit of the model reduces when a higher 25(OH)D threshold is chosen. Vitamin D deficiency is associated with increased fracture risk in older persons. General supplementation of all older women with vitamin D could cause medicalization and costs. We developed a clinical model to identify insufficient serum 25-hydroxyvitamin D (25(OH)D) status in older women at risk for fractures. In a sample of 2689 women ≥ 65 years selected from general practices, with at least one risk factor for fractures, a questionnaire was administered and serum 25(OH)D was measured. Multivariable logistic regression models with backward selection were developed to select predictors for insufficient serum 25(OH)D status, using separate thresholds 30, 40, 50 and 60 nmol/L. Internal and external model validations were performed. Predictors in the models were as follows: age, BMI, vitamin D supplementation, multivitamin supplementation, calcium supplementation, daily use of margarine, fatty fish ≥ 2×/week, ≥ 1 hours/day outdoors in summer, season of blood sampling, the use of a walking aid and smoking. The AUC was 0.77 for the model using a 30 nmol/L threshold and decreased in the models with higher thresholds to 0.72 for 60 nmol/L. We demonstrate that the model can help to distinguish patients with or without insufficient serum 25(OH)D levels at thresholds of 30 and 40 nmol/L, but not when a threshold of 50 nmol/L is demanded. This externally validated model can predict the presence of vitamin D insufficiency in women at risk for fractures. The potential clinical benefit of this tool is highly dependent of the chosen 25(OH)D threshold and decreases when a higher threshold is used.

Genetics and the making of Homo sapiens.

PubMed

Carroll, Sean B

2003-04-24

Understanding the genetic basis of the physical and behavioural traits that distinguish humans from other primates presents one of the great new challenges in biology. Of the millions of base-pair differences between humans and chimpanzees, which particular changes contributed to the evolution of human features after the separation of the Pan and Homo lineages 5-7 million years ago? How can we identify the 'smoking guns' of human genetic evolution from neutral ticks of the molecular evolutionary clock? The magnitude and rate of morphological evolution in hominids suggests that many independent and incremental developmental changes have occurred that, on the basis of recent findings in model animals, are expected to be polygenic and regulatory in nature. Comparative genomics, population genetics, gene-expression analyses and medical genetics have begun to make complementary inroads into the complex genetic architecture of human evolution.

A sampling algorithm for segregation analysis

PubMed Central

Tier, Bruce; Henshall, John

2001-01-01

Methods for detecting Quantitative Trait Loci (QTL) without markers have generally used iterative peeling algorithms for determining genotype probabilities. These algorithms have considerable shortcomings in complex pedigrees. A Monte Carlo Markov chain (MCMC) method which samples the pedigree of the whole population jointly is described. Simultaneous sampling of the pedigree was achieved by sampling descent graphs using the Metropolis-Hastings algorithm. A descent graph describes the inheritance state of each allele and provides pedigrees guaranteed to be consistent with Mendelian sampling. Sampling descent graphs overcomes most, if not all, of the limitations incurred by iterative peeling algorithms. The algorithm was able to find the QTL in most of the simulated populations. However, when the QTL was not modeled or found then its effect was ascribed to the polygenic component. No QTL were detected when they were not simulated. PMID:11742631

Effects of pump recycling technique on stimulated Brillouin scattering threshold: a theoretical model.

PubMed

Al-Asadi, H A; Al-Mansoori, M H; Ajiya, M; Hitam, S; Saripan, M I; Mahdi, M A

2010-10-11

We develop a theoretical model that can be used to predict stimulated Brillouin scattering (SBS) threshold in optical fibers that arises through the effect of Brillouin pump recycling technique. Obtained simulation results from our model are in close agreement with our experimental results. The developed model utilizes single mode optical fiber of different lengths as the Brillouin gain media. For 5-km long single mode fiber, the calculated threshold power for SBS is about 16 mW for conventional technique. This value is reduced to about 8 mW when the residual Brillouin pump is recycled at the end of the fiber. The decrement of SBS threshold is due to longer interaction lengths between Brillouin pump and Stokes wave.

Comparison between intensity- duration thresholds and cumulative rainfall thresholds for the forecasting of landslide

NASA Astrophysics Data System (ADS)

Lagomarsino, Daniela; Rosi, Ascanio; Rossi, Guglielmo; Segoni, Samuele; Catani, Filippo

2014-05-01

This work makes a quantitative comparison between the results of landslide forecasting obtained using two different rainfall threshold models, one using intensity-duration thresholds and the other based on cumulative rainfall thresholds in an area of northern Tuscany of 116 km2. The first methodology identifies rainfall intensity-duration thresholds by means a software called MaCumBA (Massive CUMulative Brisk Analyzer) that analyzes rain-gauge records, extracts the intensities (I) and durations (D) of the rainstorms associated with the initiation of landslides, plots these values on a diagram, and identifies thresholds that define the lower bounds of the I-D values. A back analysis using data from past events can be used to identify the threshold conditions associated with the least amount of false alarms. The second method (SIGMA) is based on the hypothesis that anomalous or extreme values of rainfall are responsible for landslide triggering: the statistical distribution of the rainfall series is analyzed, and multiples of the standard deviation (σ) are used as thresholds to discriminate between ordinary and extraordinary rainfall events. The name of the model, SIGMA, reflects the central role of the standard deviations in the proposed methodology. The definition of intensity-duration rainfall thresholds requires the combined use of rainfall measurements and an inventory of dated landslides, whereas SIGMA model can be implemented using only rainfall data. These two methodologies were applied in an area of 116 km2 where a database of 1200 landslides was available for the period 2000-2012. The results obtained are compared and discussed. Although several examples of visual comparisons between different intensity-duration rainfall thresholds are reported in the international literature, a quantitative comparison between thresholds obtained in the same area using different techniques and approaches is a relatively undebated research topic.

Characterizing Decision-Analysis Performances of Risk Prediction Models Using ADAPT Curves.

PubMed

Lee, Wen-Chung; Wu, Yun-Chun

2016-01-01

The area under the receiver operating characteristic curve is a widely used index to characterize the performance of diagnostic tests and prediction models. However, the index does not explicitly acknowledge the utilities of risk predictions. Moreover, for most clinical settings, what counts is whether a prediction model can guide therapeutic decisions in a way that improves patient outcomes, rather than to simply update probabilities.Based on decision theory, the authors propose an alternative index, the "average deviation about the probability threshold" (ADAPT).An ADAPT curve (a plot of ADAPT value against the probability threshold) neatly characterizes the decision-analysis performances of a risk prediction model.Several prediction models can be compared for their ADAPT values at a chosen probability threshold, for a range of plausible threshold values, or for the whole ADAPT curves. This should greatly facilitate the selection of diagnostic tests and prediction models.

Identifying optimal threshold statistics for elimination of hookworm using a stochastic simulation model.

PubMed

Truscott, James E; Werkman, Marleen; Wright, James E; Farrell, Sam H; Sarkar, Rajiv; Ásbjörnsdóttir, Kristjana; Anderson, Roy M

2017-06-30

There is an increased focus on whether mass drug administration (MDA) programmes alone can interrupt the transmission of soil-transmitted helminths (STH). Mathematical models can be used to model these interventions and are increasingly being implemented to inform investigators about expected trial outcome and the choice of optimum study design. One key factor is the choice of threshold for detecting elimination. However, there are currently no thresholds defined for STH regarding breaking transmission. We develop a simulation of an elimination study, based on the DeWorm3 project, using an individual-based stochastic disease transmission model in conjunction with models of MDA, sampling, diagnostics and the construction of study clusters. The simulation is then used to analyse the relationship between the study end-point elimination threshold and whether elimination is achieved in the long term within the model. We analyse the quality of a range of statistics in terms of the positive predictive values (PPV) and how they depend on a range of covariates, including threshold values, baseline prevalence, measurement time point and how clusters are constructed. End-point infection prevalence performs well in discriminating between villages that achieve interruption of transmission and those that do not, although the quality of the threshold is sensitive to baseline prevalence and threshold value. Optimal post-treatment prevalence threshold value for determining elimination is in the range 2% or less when the baseline prevalence range is broad. For multiple clusters of communities, both the probability of elimination and the ability of thresholds to detect it are strongly dependent on the size of the cluster and the size distribution of the constituent communities. Number of communities in a cluster is a key indicator of probability of elimination and PPV. Extending the time, post-study endpoint, at which the threshold statistic is measured improves PPV value in discriminating between eliminating clusters and those that bounce back. The probability of elimination and PPV are very sensitive to baseline prevalence for individual communities. However, most studies and programmes are constructed on the basis of clusters. Since elimination occurs within smaller population sub-units, the construction of clusters introduces new sensitivities for elimination threshold values to cluster size and the underlying population structure. Study simulation offers an opportunity to investigate key sources of sensitivity for elimination studies and programme designs in advance and to tailor interventions to prevailing local or national conditions.

A generalised individual-based algorithm for modelling the evolution of quantitative herbicide resistance in arable weed populations.

PubMed

Liu, Chun; Bridges, Melissa E; Kaundun, Shiv S; Glasgow, Les; Owen, Micheal Dk; Neve, Paul

2017-02-01

Simulation models are useful tools for predicting and comparing the risk of herbicide resistance in weed populations under different management strategies. Most existing models assume a monogenic mechanism governing herbicide resistance evolution. However, growing evidence suggests that herbicide resistance is often inherited in a polygenic or quantitative fashion. Therefore, we constructed a generalised modelling framework to simulate the evolution of quantitative herbicide resistance in summer annual weeds. Real-field management parameters based on Amaranthus tuberculatus (Moq.) Sauer (syn. rudis) control with glyphosate and mesotrione in Midwestern US maize-soybean agroecosystems demonstrated that the model can represent evolved herbicide resistance in realistic timescales. Sensitivity analyses showed that genetic and management parameters were impactful on the rate of quantitative herbicide resistance evolution, whilst biological parameters such as emergence and seed bank mortality were less important. The simulation model provides a robust and widely applicable framework for predicting the evolution of quantitative herbicide resistance in summer annual weed populations. The sensitivity analyses identified weed characteristics that would favour herbicide resistance evolution, including high annual fecundity, large resistance phenotypic variance and pre-existing herbicide resistance. Implications for herbicide resistance management and potential use of the model are discussed. © 2016 Society of Chemical Industry. © 2016 Society of Chemical Industry.

Predicting the threshold of pulse-train electrical stimuli using a stochastic auditory nerve model: the effects of stimulus noise.

PubMed

Xu, Yifang; Collins, Leslie M

2004-04-01

The incorporation of low levels of noise into an electrical stimulus has been shown to improve auditory thresholds in some human subjects (Zeng et al., 2000). In this paper, thresholds for noise-modulated pulse-train stimuli are predicted utilizing a stochastic neural-behavioral model of ensemble fiber responses to bi-phasic stimuli. The neural refractory effect is described using a Markov model for a noise-free pulse-train stimulus and a closed-form solution for the steady-state neural response is provided. For noise-modulated pulse-train stimuli, a recursive method using the conditional probability is utilized to track the neural responses to each successive pulse. A neural spike count rule has been presented for both threshold and intensity discrimination under the assumption that auditory perception occurs via integration over a relatively long time period (Bruce et al., 1999). An alternative approach originates from the hypothesis of the multilook model (Viemeister and Wakefield, 1991), which argues that auditory perception is based on several shorter time integrations and may suggest an NofM model for prediction of pulse-train threshold. This motivates analyzing the neural response to each individual pulse within a pulse train, which is considered to be the brief look. A logarithmic rule is hypothesized for pulse-train threshold. Predictions from the multilook model are shown to match trends in psychophysical data for noise-free stimuli that are not always matched by the long-time integration rule. Theoretical predictions indicate that threshold decreases as noise variance increases. Theoretical models of the neural response to pulse-train stimuli not only reduce calculational overhead but also facilitate utilization of signal detection theory and are easily extended to multichannel psychophysical tasks.

A New Integrated Threshold Selection Methodology for Spatial Forecast Verification of Extreme Events

NASA Astrophysics Data System (ADS)

Kholodovsky, V.

2017-12-01

Extreme weather and climate events such as heavy precipitation, heat waves and strong winds can cause extensive damage to the society in terms of human lives and financial losses. As climate changes, it is important to understand how extreme weather events may change as a result. Climate and statistical models are often independently used to model those phenomena. To better assess performance of the climate models, a variety of spatial forecast verification methods have been developed. However, spatial verification metrics that are widely used in comparing mean states, in most cases, do not have an adequate theoretical justification to benchmark extreme weather events. We proposed a new integrated threshold selection methodology for spatial forecast verification of extreme events that couples existing pattern recognition indices with high threshold choices. This integrated approach has three main steps: 1) dimension reduction; 2) geometric domain mapping; and 3) thresholds clustering. We apply this approach to an observed precipitation dataset over CONUS. The results are evaluated by displaying threshold distribution seasonally, monthly and annually. The method offers user the flexibility of selecting a high threshold that is linked to desired geometrical properties. The proposed high threshold methodology could either complement existing spatial verification methods, where threshold selection is arbitrary, or be directly applicable in extreme value theory.

Estimating economic thresholds for pest control: an alternative procedure.

PubMed

Ramirez, O A; Saunders, J L

1999-04-01

An alternative methodology to determine profit maximizing economic thresholds is developed and illustrated. An optimization problem based on the main biological and economic relations involved in determining a profit maximizing economic threshold is first advanced. From it, a more manageable model of 2 nonsimultaneous reduced-from equations is derived, which represents a simpler but conceptually and statistically sound alternative. The model recognizes that yields and pest control costs are a function of the economic threshold used. Higher (less strict) economic thresholds can result in lower yields and, therefore, a lower gross income from the sale of the product, but could also be less costly to maintain. The highest possible profits will be obtained by using the economic threshold that results in a maximum difference between gross income and pest control cost functions.

The threshold of a stochastic delayed SIR epidemic model with temporary immunity

NASA Astrophysics Data System (ADS)

Liu, Qun; Chen, Qingmei; Jiang, Daqing

2016-05-01

This paper is concerned with the asymptotic properties of a stochastic delayed SIR epidemic model with temporary immunity. Sufficient conditions for extinction and persistence in the mean of the epidemic are established. The threshold between persistence in the mean and extinction of the epidemic is obtained. Compared with the corresponding deterministic model, the threshold affected by the white noise is smaller than the basic reproduction number R0 of the deterministic system.

The Dubna-Mainz-Taipei Dynamical Model for πN Scattering and π Electromagnetic Production

NASA Astrophysics Data System (ADS)

Yang, Shin Nan

Some of the featured results of the Dubna-Mainz-Taipei (DMT) dynamical model for πN scattering and π0 electromagnetic production are summarized. These include results for threshold π0 production, deformation of Δ(1232),and the extracted properties of higher resonances below 2 GeV. The excellent agreement of DMT model's predictions with threshold π0 production data, including the recent precision measurements from MAMI establishes results of DMT model as a benchmark for experimentalists and theorists in dealing with threshold pion production.

Neutral Theory: From Complex Population History to Natural Selection and Sociocultural Phenomena in Human Populations.

PubMed

Austerlitz, Frédéric; Heyer, Evelyne

2018-06-01

Here, we present a synthetic view on how Kimura's Neutral theory has helped us gaining insight on the different evolutionary forces that shape human evolution. We put this perspective in the frame of recent emerging challenges: the use of whole genome data for reconstructing population histories, natural selection on complex polygenic traits, and integrating cultural processes in human evolution.

Recommendations to report and interpret HLA genetic findings in coeliac disease.

PubMed

Núñez, Concepción; Garrote, José Antonio; Arranz, Eduardo; Bilbao, José Ramón; Fernández Bañares, Fernando; Jiménez, Juana; Perucho, Teresa; Ruiz Casares, Eva; Sánchez-Valverde, Félix; Serrano, Nacho

2018-05-03

Coeliac disease (CD) is a chronic autoimmune enteropathy triggered by gluten and related prolamines in genetically predisposed individuals. Although CD is a polygenic disease, there is a strong association with genes of the human leukocyte antigen (HLA) region. Most patients present the HLA-DQ2 heterodimer, specifically the DQ2.5 isoform, which is present in around 90-96% of patients of European ancestry.

[Diabetes and predictive medicine--parallax of the present time].

PubMed

Rybka, J

2010-04-01

Predictive genetics uses genetic testing to estimate the risk in asymptomatic persons. Since in the case of multifactorial diseases predictive genetic analysis deals with findings which allow wider interpretation, it has a higher predictive value in expressly qualified diseases (monogenous) with high penetration compared to multifactorial (polygenous) diseases with high participation of environmental factors. In most "civilisation" (multifactorial) diseases including diabetes, heredity and environmental factors do not play two separate, independent roles. Instead, their interactions play a principal role. The new classification of diabetes is based on the implementation of not only ethiopathogenetic, but also genetic research. Diabetes mellitus type 1 (DM1T) is a polygenous multifactorial disease with the genetic component carrying about one half of the risk, the non-genetic one the other half. The study of the autoimmune nature of DM1T in connection with genetic analysis is going to bring about new insights in DM1T prediction. The author presents new pieces of knowledge on molecular genetics concerning certain specific types of diabetes. Issues relating to heredity in diabetes mellitus type 2 (DM2T) are even more complex. The disease has a polygenous nature, and the phenotype of a patient with DM2T, in addition to environmental factors, involves at least three, perhaps even tens of different genetic variations. At present, results at the genom-wide level appear to be most promising. The current concept of prediabetes is a realistic foundation for our prediction and prevention of DM2T. A multifactorial, multimarker approach based on our understanding of new pathophysiological factors of DM2T, tries to outline a "map" of prediabetes physiology, and if these tests are combined with sophisticated methods of genetic forecasting of DM2T, this may represent a significant step in our methodology of diabetes prediction. So far however, predictive genetics is limited by the interpretation of genetic predisposition and individualisation of the level of risk. There is no doubt that interpretation calls for co-operation with clinicians, while results of genetic analyses should presently be not uncritically overestimated. Predictive medicine, however, unquestionably fulfills the preventive focus of modern medicine, and genetic analysis is a perspective diagnostic method.

Development and Current Status of the “Cambridge” Loudness Models

PubMed Central

2014-01-01

This article reviews the evolution of a series of models of loudness developed in Cambridge, UK. The first model, applicable to stationary sounds, was based on modifications of the model developed by Zwicker, including the introduction of a filter to allow for the effects of transfer of sound through the outer and middle ear prior to the calculation of an excitation pattern, and changes in the way that the excitation pattern was calculated. Later, modifications were introduced to the assumed middle-ear transfer function and to the way that specific loudness was calculated from excitation level. These modifications led to a finite calculated loudness at absolute threshold, which made it possible to predict accurately the absolute thresholds of broadband and narrowband sounds, based on the assumption that the absolute threshold corresponds to a fixed small loudness. The model was also modified to give predictions of partial loudness—the loudness of one sound in the presence of another. This allowed predictions of masked thresholds based on the assumption that the masked threshold corresponds to a fixed small partial loudness. Versions of the model for time-varying sounds were developed, which allowed prediction of the masked threshold of any sound in a background of any other sound. More recent extensions incorporate binaural processing to account for the summation of loudness across ears. In parallel, versions of the model for predicting loudness for hearing-impaired ears have been developed and have been applied to the development of methods for fitting multichannel compression hearing aids. PMID:25315375

Setting conservation management thresholds using a novel participatory modeling approach.

PubMed

Addison, P F E; de Bie, K; Rumpff, L

2015-10-01

We devised a participatory modeling approach for setting management thresholds that show when management intervention is required to address undesirable ecosystem changes. This approach was designed to be used when management thresholds: must be set for environmental indicators in the face of multiple competing objectives; need to incorporate scientific understanding and value judgments; and will be set by participants with limited modeling experience. We applied our approach to a case study where management thresholds were set for a mat-forming brown alga, Hormosira banksii, in a protected area management context. Participants, including management staff and scientists, were involved in a workshop to test the approach, and set management thresholds to address the threat of trampling by visitors to an intertidal rocky reef. The approach involved trading off the environmental objective, to maintain the condition of intertidal reef communities, with social and economic objectives to ensure management intervention was cost-effective. Ecological scenarios, developed using scenario planning, were a key feature that provided the foundation for where to set management thresholds. The scenarios developed represented declines in percent cover of H. banksii that may occur under increased threatening processes. Participants defined 4 discrete management alternatives to address the threat of trampling and estimated the effect of these alternatives on the objectives under each ecological scenario. A weighted additive model was used to aggregate participants' consequence estimates. Model outputs (decision scores) clearly expressed uncertainty, which can be considered by decision makers and used to inform where to set management thresholds. This approach encourages a proactive form of conservation, where management thresholds and associated actions are defined a priori for ecological indicators, rather than reacting to unexpected ecosystem changes in the future. © 2015 The Authors Conservation Biology published by Wiley Periodicals, Inc. on behalf of Society for Conservation Biology.

Study on the threshold of a stochastic SIR epidemic model and its extensions

NASA Astrophysics Data System (ADS)

Zhao, Dianli

2016-09-01

This paper provides a simple but effective method for estimating the threshold of a class of the stochastic epidemic models by use of the nonnegative semimartingale convergence theorem. Firstly, the threshold R0SIR is obtained for the stochastic SIR model with a saturated incidence rate, whose value is below 1 or above 1 will completely determine the disease to go extinct or prevail for any size of the white noise. Besides, when R0SIR > 1 , the system is proved to be convergent in time mean. Then, the threshold of the stochastic SIVS models with or without saturated incidence rate are also established by the same method. Comparing with the previously-known literatures, the related results are improved, and the method is simpler than before.

Position Estimation for Switched Reluctance Motor Based on the Single Threshold Angle

NASA Astrophysics Data System (ADS)

Zhang, Lei; Li, Pang; Yu, Yue

2017-05-01

This paper presents a position estimate model of switched reluctance motor based on the single threshold angle. In view of the relationship of between the inductance and rotor position, the position is estimated by comparing the real-time dynamic flux linkage with the threshold angle position flux linkage (7.5° threshold angle, 12/8SRM). The sensorless model is built by Maltab/Simulink, the simulation are implemented under the steady state and transient state different condition, and verified its validity and feasibility of the method..

Optimum polygenic profile to resist exertional rhabdomyolysis during a marathon

PubMed Central

Valero, Marjorie; Salinero, Juan José; Lara, Beatriz; Gallo-Salazar, César; Areces, Francisco

2017-01-01

Purpose Exertional rhabdomyolysis can occur in individuals performing various types of exercise but it is unclear why some individuals develop this condition while others do not. Previous investigations have determined the role of several single nucleotide polymorphisms (SNPs) to explain inter-individual variability of serum creatine kinase (CK) concentrations after exertional muscle damage. However, there has been no research about the interrelationship among these SNPs. The purpose of this investigation was to analyze seven SNPs that are candidates for explaining individual variations of CK response after a marathon competition (ACE = 287bp Ins/Del, ACTN3 = p.R577X, CKMM = NcoI, IGF2 = C13790G, IL6 = 174G>C, MLCK = C37885A, TNFα = 308G>A). Methods Using Williams and Folland’s model, we determined the total genotype score from the accumulated combination of these seven SNPs for marathoners with a low CK response (n = 36; serum CK <400 U·L-1) vs. marathoners with a high CK response (n = 31; serum CK ≥400 U·L-1). Results At the end of the race, low CK responders had lower serum CK (290±65 vs. 733±405 U·L-1; P<0.01) and myoglobin concentrations (443±328 vs. 1009±971 ng·mL-1, P<0.01) than high CK responders. Although the groups were similar in age, anthropometric characteristics, running experience and training habits, total genotype score was higher in low CK responders than in high CK responders (5.2±1.4 vs. 4.4±1.7 point, P = 0.02). Conclusion Marathoners with a lower CK response after the race had a more favorable polygenic profile than runners with high serum CK concentrations. This might suggest a significant role of genetic polymorphisms in the levels of exertional muscle damage and rhabdomyolysis. Yet other SNPs, in addition to exercise training, might also play a role in the values of CK after damaging exercise. PMID:28257486

Genetic contributions to variation in general cognitive function: a meta-analysis of genome-wide association studies in the CHARGE consortium (N=53 949)

PubMed Central

Davies, G; Armstrong, N; Bis, J C; Bressler, J; Chouraki, V; Giddaluru, S; Hofer, E; Ibrahim-Verbaas, C A; Kirin, M; Lahti, J; van der Lee, S J; Le Hellard, S; Liu, T; Marioni, R E; Oldmeadow, C; Postmus, I; Smith, A V; Smith, J A; Thalamuthu, A; Thomson, R; Vitart, V; Wang, J; Yu, L; Zgaga, L; Zhao, W; Boxall, R; Harris, S E; Hill, W D; Liewald, D C; Luciano, M; Adams, H; Ames, D; Amin, N; Amouyel, P; Assareh, A A; Au, R; Becker, J T; Beiser, A; Berr, C; Bertram, L; Boerwinkle, E; Buckley, B M; Campbell, H; Corley, J; De Jager, P L; Dufouil, C; Eriksson, J G; Espeseth, T; Faul, J D; Ford, I; Scotland, Generation; Gottesman, R F; Griswold, M E; Gudnason, V; Harris, T B; Heiss, G; Hofman, A; Holliday, E G; Huffman, J; Kardia, S L R; Kochan, N; Knopman, D S; Kwok, J B; Lambert, J-C; Lee, T; Li, G; Li, S-C; Loitfelder, M; Lopez, O L; Lundervold, A J; Lundqvist, A; Mather, K A; Mirza, S S; Nyberg, L; Oostra, B A; Palotie, A; Papenberg, G; Pattie, A; Petrovic, K; Polasek, O; Psaty, B M; Redmond, P; Reppermund, S; Rotter, J I; Schmidt, H; Schuur, M; Schofield, P W; Scott, R J; Steen, V M; Stott, D J; van Swieten, J C; Taylor, K D; Trollor, J; Trompet, S; Uitterlinden, A G; Weinstein, G; Widen, E; Windham, B G; Jukema, J W; Wright, A F; Wright, M J; Yang, Q; Amieva, H; Attia, J R; Bennett, D A; Brodaty, H; de Craen, A J M; Hayward, C; Ikram, M A; Lindenberger, U; Nilsson, L-G; Porteous, D J; Räikkönen, K; Reinvang, I; Rudan, I; Sachdev, P S; Schmidt, R; Schofield, P R; Srikanth, V; Starr, J M; Turner, S T; Weir, D R; Wilson, J F; van Duijn, C; Launer, L; Fitzpatrick, A L; Seshadri, S; Mosley, T H; Deary, I J

2015-01-01

General cognitive function is substantially heritable across the human life course from adolescence to old age. We investigated the genetic contribution to variation in this important, health- and well-being-related trait in middle-aged and older adults. We conducted a meta-analysis of genome-wide association studies of 31 cohorts (N=53 949) in which the participants had undertaken multiple, diverse cognitive tests. A general cognitive function phenotype was tested for, and created in each cohort by principal component analysis. We report 13 genome-wide significant single-nucleotide polymorphism (SNP) associations in three genomic regions, 6q16.1, 14q12 and 19q13.32 (best SNP and closest gene, respectively: rs10457441, P=3.93 × 10−9, MIR2113; rs17522122, P=2.55 × 10−8, AKAP6; rs10119, P=5.67 × 10−9, APOE/TOMM40). We report one gene-based significant association with the HMGN1 gene located on chromosome 21 (P=1 × 10−6). These genes have previously been associated with neuropsychiatric phenotypes. Meta-analysis results are consistent with a polygenic model of inheritance. To estimate SNP-based heritability, the genome-wide complex trait analysis procedure was applied to two large cohorts, the Atherosclerosis Risk in Communities Study (N=6617) and the Health and Retirement Study (N=5976). The proportion of phenotypic variation accounted for by all genotyped common SNPs was 29% (s.e.=5%) and 28% (s.e.=7%), respectively. Using polygenic prediction analysis, ~1.2% of the variance in general cognitive function was predicted in the Generation Scotland cohort (N=5487; P=1.5 × 10−17). In hypothesis-driven tests, there was significant association between general cognitive function and four genes previously associated with Alzheimer's disease: TOMM40, APOE, ABCG1 and MEF2C. PMID:25644384

Validation of a polygenic risk score for dementia in black and white individuals

PubMed Central

Marden, Jessica R; Walter, Stefan; Tchetgen Tchetgen, Eric J; Kawachi, Ichiro; Glymour, M Maria

2014-01-01

Objective To determine whether a polygenic risk score for Alzheimer's disease (AD) predicts dementia probability and memory functioning in non-Hispanic black (NHB) and non-Hispanic white (NHW) participants from a sample not used in previous genome-wide association studies. Methods Non-Hispanic white and NHB Health and Retirement Study (HRS) participants provided genetic information and either a composite memory score (n = 10,401) or a dementia probability score (n = 7690). Dementia probability score was estimated for participants' age 65+ from 2006 to 2010, while memory score was available for participants age 50+. We calculated AD genetic risk scores (AD-GRS) based on 10 polymorphisms confirmed to predict AD, weighting alleles by beta coefficients reported in AlzGene meta-analyses. We used pooled logistic regression to estimate the association of the AD-GRS with dementia probability and generalized linear models to estimate its effect on memory score. Results Each 0.10 unit change in the AD-GRS was associated with larger relative effects on dementia among NHW aged 65+ (OR = 2.22; 95% CI: 1.79, 2.74; P < 0.001) than NHB (OR=1.33; 95% CI: 1.00, 1.77; P = 0.047), although additive effect estimates were similar. Each 0.10 unit change in the AD-GRS was associated with a −0.07 (95% CI: −0.09, −0.05; P < 0.001) SD difference in memory score among NHW aged 50+, but no significant differences among NHB (β = −0.01; 95% CI: −0.04, 0.01; P = 0.546). [Correction added on 29 July 2014, after first online publication: confidence intervalshave been amended.] The estimated effect of the GRS was significantly smaller among NHB than NHW (P < 0.05) for both outcomes. Conclusion This analysis provides evidence for differential relative effects of the GRS on dementia probability and memory score among NHW and NHB in a new, national data set. PMID:25328845

Circulating ghrelin level is higher in HNF1A-MODY and GCK-MODY than in polygenic forms of diabetes mellitus.

PubMed

Nowak, Natalia; Hohendorff, Jerzy; Solecka, Iwona; Szopa, Magdalena; Skupien, Jan; Kiec-Wilk, Beata; Mlynarski, Wojciech; Malecki, Maciej T

2015-12-01

Ghrelin is a hormone that regulates appetite. It is likely to be involved in the pathophysiology of varying forms of diabetes. In animal studies, the ghrelin expression was regulated by the hepatocyte nuclear factor 1 alpha (HNF1A). Mutations of the HNF1A gene cause maturity onset diabetes of the young (MODY). We aimed to assess the circulating ghrelin levels in HNF1A-MODY and in other types of diabetes and to evaluate its association with HNF1A mutation status. Our cohort included 46 diabetic HNF1A gene mutation carriers, 55 type 2 diabetes (T2DM) subjects, 42 type 1 diabetes (T1DM) patients, and 31 glucokinase (GCK) gene mutation carriers with diabetes as well as 51 healthy controls. Plasma ghrelin concentration was measured using the immunoenzymatic assay with polyclonal antibody against the C-terminal fragment of its acylated and desacylated forms. Ghrelin concentrations were 0.75 ± 0.32, 0.70 ± 0.21, 0.50 ± 0.20, and 0.40 ± 0.16 ng/ml in patients with HNF1A-MODY, GCK-MODY, T1DM, and T2DM, respectively. The ghrelin levels were higher in HNF1A-MODY and GCK-MODY than in T1DM and T2DM (p < 0.001 for all comparisons) but lower than in non-diabetic controls (1.02 ± 0.29 ng/ml, p < 0.001 for both comparisons). In the multivariate linear model, the differences between both MODY groups and common diabetes types remained significant. Analysis by a HNF1A mutation type indicated that ghrelin concentration is similar in patients with different types of sequence differences. Plasma ghrelin level is higher in HNF1A-MODY and GCK-MODY than in the common polygenic forms of diabetes.

Optimum polygenic profile to resist exertional rhabdomyolysis during a marathon.

PubMed

Del Coso, Juan; Valero, Marjorie; Salinero, Juan José; Lara, Beatriz; Gallo-Salazar, César; Areces, Francisco

2017-01-01

Exertional rhabdomyolysis can occur in individuals performing various types of exercise but it is unclear why some individuals develop this condition while others do not. Previous investigations have determined the role of several single nucleotide polymorphisms (SNPs) to explain inter-individual variability of serum creatine kinase (CK) concentrations after exertional muscle damage. However, there has been no research about the interrelationship among these SNPs. The purpose of this investigation was to analyze seven SNPs that are candidates for explaining individual variations of CK response after a marathon competition (ACE = 287bp Ins/Del, ACTN3 = p.R577X, CKMM = NcoI, IGF2 = C13790G, IL6 = 174G>C, MLCK = C37885A, TNFα = 308G>A). Using Williams and Folland's model, we determined the total genotype score from the accumulated combination of these seven SNPs for marathoners with a low CK response (n = 36; serum CK <400 U·L-1) vs. marathoners with a high CK response (n = 31; serum CK ≥400 U·L-1). At the end of the race, low CK responders had lower serum CK (290±65 vs. 733±405 U·L-1; P<0.01) and myoglobin concentrations (443±328 vs. 1009±971 ng·mL-1, P<0.01) than high CK responders. Although the groups were similar in age, anthropometric characteristics, running experience and training habits, total genotype score was higher in low CK responders than in high CK responders (5.2±1.4 vs. 4.4±1.7 point, P = 0.02). Marathoners with a lower CK response after the race had a more favorable polygenic profile than runners with high serum CK concentrations. This might suggest a significant role of genetic polymorphisms in the levels of exertional muscle damage and rhabdomyolysis. Yet other SNPs, in addition to exercise training, might also play a role in the values of CK after damaging exercise.

Schizophrenia and subsequent neighborhood deprivation: revisiting the social drift hypothesis using population, twin and molecular genetic data.

PubMed

Sariaslan, A; Fazel, S; D'Onofrio, B M; Långström, N; Larsson, H; Bergen, S E; Kuja-Halkola, R; Lichtenstein, P

2016-05-03

Neighborhood influences in the etiology of schizophrenia have been emphasized in a number of systematic reviews, but causality remains uncertain. To test the social drift hypothesis, we used three complementary genetically informed Swedish cohorts. First, we used nationwide Swedish data on approximately 760 000 full- and half-sibling pairs born between 1951 and 1974 and quantitative genetic models to study genetic and environmental influences on the overlap between schizophrenia in young adulthood and subsequent residence in socioeconomically deprived neighborhoods. Schizophrenia diagnoses were ascertained using the National Patient Registry. Second, we tested the overlap between childhood psychotic experiences and neighborhood deprivation in early adulthood in the longitudinal Twin Study of Child and Adolescent Development (TCHAD; n=2960). Third, we investigated to what extent polygenic risk scores for schizophrenia predicted residence in deprived neighborhoods during late adulthood using the TwinGene sample (n=6796). Sibling data suggested that living in deprived neighborhoods was substantially heritable; 65% (95% confidence interval (95% CI): 60-71%) of the variance was attributed to genetic influences. Although the correlation between schizophrenia and neighborhood deprivation was moderate in magnitude (r=0.22; 95% CI: 0.20-0.24), it was entirely explained by genetic influences. We replicated these findings in the TCHAD sample. Moreover, the association between polygenic risk for schizophrenia and neighborhood deprivation was statistically significant (R(2)=0.15%, P=0.002). Our findings are primarily consistent with a genetic selection interpretation where genetic liability for schizophrenia also predicts subsequent residence in socioeconomically deprived neighborhoods. Previous studies may have overemphasized the relative importance of environmental influences in the social drift of schizophrenia patients. Clinical and policy interventions will therefore benefit from the future identification of potentially causal pathways between different dimensions of cognitive functions and socioeconomic trajectories derived from studies adopting family-based research designs.

Spontaneous Trigeminal Allodynia in Rats: A Model of Primary Headache

PubMed Central

Oshinsky, Michael L.; Sanghvi, Menka M.; Maxwell, Christina R.; Gonzalez, Dorian; Spangenberg, Rebecca J.; Cooper, Marnie; Silberstein, Stephen D.

2014-01-01

Animal models are essential for studying the pathophysiology of headache disorders and as a screening tool for new therapies. Most animal models modify a normal animal in an attempt to mimic migraine symptoms. They require manipulation to activate the trigeminal nerve or dural nociceptors. At best, they are models of secondary headache. No existing model can address the fundamental question: How is a primary headache spontaneously initiated? In the process of obtaining baseline periorbital von Frey thresholds in a wild-type Sprague-Dawley rat, we discovered a rat with spontaneous episodic trigeminal allodynia (manifested by episodically changing periorbital pain threshold). Subsequent mating showed that the trait is inherited. Animals with spontaneous trigeminal allodynia allow us to study the pathophysiology of primary recurrent headache disorders. To validate this as a model for migraine, we tested the effects of clinically proven acute and preventive migraine treatments on spontaneous changes in rat periorbital sensitivity. Sumatriptan, ketorolac, and dihydroergotamine temporarily reversed the low periorbital pain thresholds. Thirty days of chronic valproic acid treatment prevented spontaneous changes in trigeminal allodynia. After discontinuation, the rats returned to their baseline of spontaneous episodic threshold changes. We also tested the effects of known chemical human migraine triggers. On days when the rats did not have allodynia and showed normal periorbital von Frey thresholds, glycerol trinitrate and calcitonin gene related peptide induced significant decreases in the periorbital pain threshold. This model can be used as a predictive model for drug development and for studies of putative biomarkers for headache diagnosis and treatment. PMID:22963523

Analytical expression for Risken-Nummedal-Graham-Haken instability threshold in quantum cascade lasers.

PubMed

Vukovic, N; Radovanovic, J; Milanovic, V; Boiko, D L

2016-11-14

We have obtained a closed-form expression for the threshold of Risken-Nummedal-Graham-Haken (RNGH) multimode instability in a Fabry-Pérot (FP) cavity quantum cascade laser (QCL). This simple analytical expression is a versatile tool that can easily be applied in practical situations which require analysis of QCL dynamic behavior and estimation of its RNGH multimode instability threshold. Our model for a FP cavity laser accounts for the carrier coherence grating and carrier population grating as well as their relaxation due to carrier diffusion. In the model, the RNGH instability threshold is analyzed using a second-order bi-orthogonal perturbation theory and we confirm our analytical solution by a comparison with the numerical simulations. In particular, the model predicts a low RNGH instability threshold in QCLs. This agrees very well with experimental data available in the literature.

Modelling the impact of altered axonal morphometry on the response of regenerative nervous tissue to electrical stimulation through macro-sieve electrodes.

PubMed

Zellmer, Erik R; MacEwan, Matthew R; Moran, Daniel W

2018-04-01

Regenerated peripheral nervous tissue possesses different morphometric properties compared to undisrupted nerve. It is poorly understood how these morphometric differences alter the response of the regenerated nerve to electrical stimulation. In this work, we use computational modeling to explore the electrophysiological response of regenerated and undisrupted nerve axons to electrical stimulation delivered by macro-sieve electrodes (MSEs). A 3D finite element model of a peripheral nerve segment populated with mammalian myelinated axons and implanted with a macro-sieve electrode has been developed. Fiber diameters and morphometric characteristics representative of undisrupted or regenerated peripheral nervous tissue were assigned to core conductor models to simulate the two tissue types. Simulations were carried out to quantify differences in thresholds and chronaxie between undisrupted and regenerated fiber populations. The model was also used to determine the influence of axonal caliber on recruitment thresholds for the two tissue types. Model accuracy was assessed through comparisons with in vivo recruitment data from chronically implanted MSEs. Recruitment thresholds of individual regenerated fibers with diameters  >2 µm were found to be lower compared to same caliber undisrupted fibers at electrode to fiber distances of less than about 90-140 µm but roughly equal or higher for larger distances. Caliber redistributions observed in regenerated nerve resulted in an overall increase in average recruitment thresholds and chronaxie during whole nerve stimulation. Modeling results also suggest that large diameter undisrupted fibers located close to a longitudinally restricted current source such as the MSE have higher average recruitment thresholds compared to small diameter fibers. In contrast, large diameter regenerated nerve fibers located in close proximity of MSE sites have, on average, lower recruitment thresholds compared to small fibers. Utilizing regenerated fiber morphometry and caliber distributions resulted in accurate predictions of in vivo recruitment data. Our work uses computational modeling to show how morphometric differences between regenerated and undisrupted tissue results in recruitment threshold discrepancies, quantifies these differences, and illustrates how large undisrupted nerve fibers close to longitudinally restricted current sources have higher recruitment thresholds compared to adjacently positioned smaller fibers while the opposite is true for large regenerated fibers.

Modelling the impact of altered axonal morphometry on the response of regenerative nervous tissue to electrical stimulation through macro-sieve electrodes

NASA Astrophysics Data System (ADS)

Zellmer, Erik R.; MacEwan, Matthew R.; Moran, Daniel W.

2018-04-01

Objective. Regenerated peripheral nervous tissue possesses different morphometric properties compared to undisrupted nerve. It is poorly understood how these morphometric differences alter the response of the regenerated nerve to electrical stimulation. In this work, we use computational modeling to explore the electrophysiological response of regenerated and undisrupted nerve axons to electrical stimulation delivered by macro-sieve electrodes (MSEs). Approach. A 3D finite element model of a peripheral nerve segment populated with mammalian myelinated axons and implanted with a macro-sieve electrode has been developed. Fiber diameters and morphometric characteristics representative of undisrupted or regenerated peripheral nervous tissue were assigned to core conductor models to simulate the two tissue types. Simulations were carried out to quantify differences in thresholds and chronaxie between undisrupted and regenerated fiber populations. The model was also used to determine the influence of axonal caliber on recruitment thresholds for the two tissue types. Model accuracy was assessed through comparisons with in vivo recruitment data from chronically implanted MSEs. Main results. Recruitment thresholds of individual regenerated fibers with diameters  >2 µm were found to be lower compared to same caliber undisrupted fibers at electrode to fiber distances of less than about 90-140 µm but roughly equal or higher for larger distances. Caliber redistributions observed in regenerated nerve resulted in an overall increase in average recruitment thresholds and chronaxie during whole nerve stimulation. Modeling results also suggest that large diameter undisrupted fibers located close to a longitudinally restricted current source such as the MSE have higher average recruitment thresholds compared to small diameter fibers. In contrast, large diameter regenerated nerve fibers located in close proximity of MSE sites have, on average, lower recruitment thresholds compared to small fibers. Utilizing regenerated fiber morphometry and caliber distributions resulted in accurate predictions of in vivo recruitment data. Significance. Our work uses computational modeling to show how morphometric differences between regenerated and undisrupted tissue results in recruitment threshold discrepancies, quantifies these differences, and illustrates how large undisrupted nerve fibers close to longitudinally restricted current sources have higher recruitment thresholds compared to adjacently positioned smaller fibers while the opposite is true for large regenerated fibers.

Modelling of surface-water temperature for the estimation of the Czech fishery productivity under the climate change

NASA Astrophysics Data System (ADS)

Svobodová, Eva; Trnka, Miroslav; Kopp, Radovan; Mareš, Jan; Dubrovský, Martin; Spurný, Petr; Žalud, Zděněk

2015-04-01

Freshwater fish production is significantly correlated with water temperature which is expected to increase under the climate change. This study is dealing with the estimation of the change of water temperature in productive ponds and its impact on the fishery in the Czech Republic. Calculation of surface-water temperature which was based on three-day mean of the air temperature was developed and tested in several ponds in three main fish production areas. Output of surface-water temperature model was compared with measured data and showed that the lower range of model accuracy is surface-water temperature 3°C, under this temperature threshold the model loses its predictive competence. In the expecting of surface-water temperature above the temperature 3°C the model has proved the well consistence between observed and modelled surface-water temperature (R 0.79 - 0.96). Verified model was applied in the conditions of climate change determined by the pattern scaling method, in which standardised scenarios were derived from five global circulation models MPEH5, CSMK3, IPCM4, GFCM21 and HADGEM. Results were evaluated with regard to thresholds which characterise the fish species requirements on water temperature. Used thresholds involved the upper temperature threshold for fish survival and the tolerable number of days in continual period with mentioned threshold surface-water temperature. Target fish species were Common carp (Cyprinus carpio), Maraene whitefish (Coregonus maraena), Northern whitefish (Coregonus peled) and Rainbow trout (Oncorhynchus mykis). Results indicated the limitation of the Czech fish-farming in terms of i) the increase of the length of continual periods with surface-water temperature above the threshold appropriate to given fish species toleration, ii) the increase of the number of continual periods with surface-water temperature above the threshold, both appropriate to given fish species toleration, and iii) the increase of overall number of days within the continual period with temperature above the threshold tolerated by given fish species. ACKNOWLEDGEMENTS: This study was funded by project "Building up a multidisciplinary scientific team focused on drought" No. CZ.1.07/2.3.00/20.0248.

Predictive performance of rainfall thresholds for shallow landslides in Switzerland from gridded daily data

NASA Astrophysics Data System (ADS)

Leonarduzzi, Elena; Molnar, Peter; McArdell, Brian W.

2017-08-01

A high-resolution gridded daily precipitation data set was combined with a landslide inventory containing over 2000 events in the period 1972-2012 to analyze rainfall thresholds which lead to landsliding in Switzerland. We colocated triggering rainfall to landslides, developed distributions of triggering and nontriggering rainfall event properties, and determined rainfall thresholds and intensity-duration ID curves and validated their performance. The best predictive performance was obtained by the intensity-duration ID threshold curve, followed by peak daily intensity Imax and mean event intensity Imean. Event duration by itself had very low predictive power. A single country-wide threshold of Imax = 28 mm/d was extended into space by regionalization based on surface erodibility and local climate (mean daily precipitation). It was found that wetter local climate and lower erodibility led to significantly higher rainfall thresholds required to trigger landslides. However, we showed that the improvement in model performance due to regionalization was marginal and much lower than what can be achieved by having a high-quality landslide database. Reference cases in which the landslide locations and timing were randomized and the landslide sample size was reduced showed the sensitivity of the Imax rainfall threshold model. Jack-knife and cross-validation experiments demonstrated that the model was robust. The results reported here highlight the potential of using rainfall ID threshold curves and rainfall threshold values for predicting the occurrence of landslides on a country or regional scale with possible applications in landslide warning systems, even with daily data.

Network meta-analysis of diagnostic test accuracy studies identifies and ranks the optimal diagnostic tests and thresholds for health care policy and decision-making.

PubMed

Owen, Rhiannon K; Cooper, Nicola J; Quinn, Terence J; Lees, Rosalind; Sutton, Alex J

2018-07-01

Network meta-analyses (NMA) have extensively been used to compare the effectiveness of multiple interventions for health care policy and decision-making. However, methods for evaluating the performance of multiple diagnostic tests are less established. In a decision-making context, we are often interested in comparing and ranking the performance of multiple diagnostic tests, at varying levels of test thresholds, in one simultaneous analysis. Motivated by an example of cognitive impairment diagnosis following stroke, we synthesized data from 13 studies assessing the efficiency of two diagnostic tests: Mini-Mental State Examination (MMSE) and Montreal Cognitive Assessment (MoCA), at two test thresholds: MMSE <25/30 and <27/30, and MoCA <22/30 and <26/30. Using Markov chain Monte Carlo (MCMC) methods, we fitted a bivariate network meta-analysis model incorporating constraints on increasing test threshold, and accounting for the correlations between multiple test accuracy measures from the same study. We developed and successfully fitted a model comparing multiple tests/threshold combinations while imposing threshold constraints. Using this model, we found that MoCA at threshold <26/30 appeared to have the best true positive rate, whereas MMSE at threshold <25/30 appeared to have the best true negative rate. The combined analysis of multiple tests at multiple thresholds allowed for more rigorous comparisons between competing diagnostics tests for decision making. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

Bayesian methods for estimating GEBVs of threshold traits

PubMed Central

Wang, C-L; Ding, X-D; Wang, J-Y; Liu, J-F; Fu, W-X; Zhang, Z; Yin, Z-J; Zhang, Q

2013-01-01

Estimation of genomic breeding values is the key step in genomic selection (GS). Many methods have been proposed for continuous traits, but methods for threshold traits are still scarce. Here we introduced threshold model to the framework of GS, and specifically, we extended the three Bayesian methods BayesA, BayesB and BayesCπ on the basis of threshold model for estimating genomic breeding values of threshold traits, and the extended methods are correspondingly termed BayesTA, BayesTB and BayesTCπ. Computing procedures of the three BayesT methods using Markov Chain Monte Carlo algorithm were derived. A simulation study was performed to investigate the benefit of the presented methods in accuracy with the genomic estimated breeding values (GEBVs) for threshold traits. Factors affecting the performance of the three BayesT methods were addressed. As expected, the three BayesT methods generally performed better than the corresponding normal Bayesian methods, in particular when the number of phenotypic categories was small. In the standard scenario (number of categories=2, incidence=30%, number of quantitative trait loci=50, h2=0.3), the accuracies were improved by 30.4%, 2.4%, and 5.7% points, respectively. In most scenarios, BayesTB and BayesTCπ generated similar accuracies and both performed better than BayesTA. In conclusion, our work proved that threshold model fits well for predicting GEBVs of threshold traits, and BayesTCπ is supposed to be the method of choice for GS of threshold traits. PMID:23149458

Structured decision making as a conceptual framework to identify thresholds for conservation and management

USGS Publications Warehouse

Martin, J.; Runge, M.C.; Nichols, J.D.; Lubow, B.C.; Kendall, W.L.

2009-01-01

Thresholds and their relevance to conservation have become a major topic of discussion in the ecological literature. Unfortunately, in many cases the lack of a clear conceptual framework for thinking about thresholds may have led to confusion in attempts to apply the concept of thresholds to conservation decisions. Here, we advocate a framework for thinking about thresholds in terms of a structured decision making process. The purpose of this framework is to promote a logical and transparent process for making informed decisions for conservation. Specification of such a framework leads naturally to consideration of definitions and roles of different kinds of thresholds in the process. We distinguish among three categories of thresholds. Ecological thresholds are values of system state variables at which small changes bring about substantial changes in system dynamics. Utility thresholds are components of management objectives (determined by human values) and are values of state or performance variables at which small changes yield substantial changes in the value of the management outcome. Decision thresholds are values of system state variables at which small changes prompt changes in management actions in order to reach specified management objectives. The approach that we present focuses directly on the objectives of management, with an aim to providing decisions that are optimal with respect to those objectives. This approach clearly distinguishes the components of the decision process that are inherently subjective (management objectives, potential management actions) from those that are more objective (system models, estimates of system state). Optimization based on these components then leads to decision matrices specifying optimal actions to be taken at various values of system state variables. Values of state variables separating different actions in such matrices are viewed as decision thresholds. Utility thresholds are included in the objectives component, and ecological thresholds may be embedded in models projecting consequences of management actions. Decision thresholds are determined by the above-listed components of a structured decision process. These components may themselves vary over time, inducing variation in the decision thresholds inherited from them. These dynamic decision thresholds can then be determined using adaptive management. We provide numerical examples (that are based on patch occupancy models) of structured decision processes that include all three kinds of thresholds. ?? 2009 by the Ecological Society of America.

Development of an anaerobic threshold (HRLT, HRVT) estimation equation using the heart rate threshold (HRT) during the treadmill incremental exercise test

PubMed Central

Ham, Joo-ho; Park, Hun-Young; Kim, Youn-ho; Bae, Sang-kon; Ko, Byung-hoon

2017-01-01

[Purpose] The purpose of this study was to develop a regression model to estimate the heart rate at the lactate threshold (HRLT) and the heart rate at the ventilatory threshold (HRVT) using the heart rate threshold (HRT), and to test the validity of the regression model. [Methods] We performed a graded exercise test with a treadmill in 220 normal individuals (men: 112, women: 108) aged 20–59 years. HRT, HRLT, and HRVT were measured in all subjects. A regression model was developed to estimate HRLT and HRVT using HRT with 70% of the data (men: 79, women: 76) through randomization (7:3), with the Bernoulli trial. The validity of the regression model developed with the remaining 30% of the data (men: 33, women: 32) was also examined. [Results] Based on the regression coefficient, we found that the independent variable HRT was a significant variable in all regression models. The adjusted R2 of the developed regression models averaged about 70%, and the standard error of estimation of the validity test results was 11 bpm, which is similar to that of the developed model. [Conclusion] These results suggest that HRT is a useful parameter for predicting HRLT and HRVT. PMID:29036765

Development of an anaerobic threshold (HRLT, HRVT) estimation equation using the heart rate threshold (HRT) during the treadmill incremental exercise test.

PubMed

Ham, Joo-Ho; Park, Hun-Young; Kim, Youn-Ho; Bae, Sang-Kon; Ko, Byung-Hoon; Nam, Sang-Seok

2017-09-30

The purpose of this study was to develop a regression model to estimate the heart rate at the lactate threshold (HRLT) and the heart rate at the ventilatory threshold (HRVT) using the heart rate threshold (HRT), and to test the validity of the regression model. We performed a graded exercise test with a treadmill in 220 normal individuals (men: 112, women: 108) aged 20-59 years. HRT, HRLT, and HRVT were measured in all subjects. A regression model was developed to estimate HRLT and HRVT using HRT with 70% of the data (men: 79, women: 76) through randomization (7:3), with the Bernoulli trial. The validity of the regression model developed with the remaining 30% of the data (men: 33, women: 32) was also examined. Based on the regression coefficient, we found that the independent variable HRT was a significant variable in all regression models. The adjusted R2 of the developed regression models averaged about 70%, and the standard error of estimation of the validity test results was 11 bpm, which is similar to that of the developed model. These results suggest that HRT is a useful parameter for predicting HRLT and HRVT. ©2017 The Korean Society for Exercise Nutrition

Octave-Band Thresholds for Modeled Reverberant Fields

NASA Technical Reports Server (NTRS)

Begault, Durand R.; Wenzel, Elizabeth M.; Tran, Laura L.; Anderson, Mark R.; Trejo, Leonard J. (Technical Monitor)

1998-01-01

Auditory thresholds for 10 subjects were obtained for speech stimuli reverberation. The reverberation was produced and manipulated by 3-D audio modeling based on an actual room. The independent variables were octave-band-filtering (bypassed, 0.25 - 2.0 kHz Fc) and reverberation time (0.2- 1.1 sec). An ANOVA revealed significant effects (threshold range: -19 to -35 dB re 60 dB SRL).

A Meta-Assembly of Selection Signatures in Cattle

PubMed Central

Randhawa, Imtiaz A. S.; Khatkar, Mehar S.; Thomson, Peter C.; Raadsma, Herman W.

2016-01-01

Since domestication, significant genetic improvement has been achieved for many traits of commercial importance in cattle, including adaptation, appearance and production. In response to such intense selection pressures, the bovine genome has undergone changes at the underlying regions of functional genetic variants, which are termed “selection signatures”. This article reviews 64 recent (2009–2015) investigations testing genomic diversity for departure from neutrality in worldwide cattle populations. In particular, we constructed a meta-assembly of 16,158 selection signatures for individual breeds and their archetype groups (European, African, Zebu and composite) from 56 genome-wide scans representing 70,743 animals of 90 pure and crossbred cattle breeds. Meta-selection-scores (MSS) were computed by combining published results at every given locus, within a sliding window span. MSS were adjusted for common samples across studies and were weighted for significance thresholds across and within studies. Published selection signatures show extensive coverage across the bovine genome, however, the meta-assembly provides a consensus profile of 263 genomic regions of which 141 were unique (113 were breed-specific) and 122 were shared across cattle archetypes. The most prominent peaks of MSS represent regions under selection across multiple populations and harboured genes of known major effects (coat color, polledness and muscle hypertrophy) and genes known to influence polygenic traits (stature, adaptation, feed efficiency, immunity, behaviour, reproduction, beef and dairy production). As the first meta-assembly of selection signatures, it offers novel insights about the hotspots of selective sweeps in the bovine genome, and this method could equally be applied to other species. PMID:27045296

Dual processing model of medical decision-making.

PubMed

Djulbegovic, Benjamin; Hozo, Iztok; Beckstead, Jason; Tsalatsanis, Athanasios; Pauker, Stephen G

2012-09-03

Dual processing theory of human cognition postulates that reasoning and decision-making can be described as a function of both an intuitive, experiential, affective system (system I) and/or an analytical, deliberative (system II) processing system. To date no formal descriptive model of medical decision-making based on dual processing theory has been developed. Here we postulate such a model and apply it to a common clinical situation: whether treatment should be administered to the patient who may or may not have a disease. We developed a mathematical model in which we linked a recently proposed descriptive psychological model of cognition with the threshold model of medical decision-making and show how this approach can be used to better understand decision-making at the bedside and explain the widespread variation in treatments observed in clinical practice. We show that physician's beliefs about whether to treat at higher (lower) probability levels compared to the prescriptive therapeutic thresholds obtained via system II processing is moderated by system I and the ratio of benefit and harms as evaluated by both system I and II. Under some conditions, the system I decision maker's threshold may dramatically drop below the expected utility threshold derived by system II. This can explain the overtreatment often seen in the contemporary practice. The opposite can also occur as in the situations where empirical evidence is considered unreliable, or when cognitive processes of decision-makers are biased through recent experience: the threshold will increase relative to the normative threshold value derived via system II using expected utility threshold. This inclination for the higher diagnostic certainty may, in turn, explain undertreatment that is also documented in the current medical practice. We have developed the first dual processing model of medical decision-making that has potential to enrich the current medical decision-making field, which is still to the large extent dominated by expected utility theory. The model also provides a platform for reconciling two groups of competing dual processing theories (parallel competitive with default-interventionalist theories).

Flood and landslide warning based on rainfall thresholds and soil moisture indexes: the HEWS (Hydrohazards Early Warning System) for Sicily

NASA Astrophysics Data System (ADS)

Brigandì, Giuseppina; Tito Aronica, Giuseppe; Bonaccorso, Brunella; Gueli, Roberto; Basile, Giuseppe

2017-09-01

The main focus of the paper is to present a flood and landslide early warning system, named HEWS (Hydrohazards Early Warning System), specifically developed for the Civil Protection Department of Sicily, based on the combined use of rainfall thresholds, soil moisture modelling and quantitative precipitation forecast (QPF). The warning system is referred to 9 different Alert Zones in which Sicily has been divided into and based on a threshold system of three different increasing critical levels: ordinary, moderate and high. In this system, for early flood warning, a Soil Moisture Accounting (SMA) model provides daily soil moisture conditions, which allow to select a specific set of three rainfall thresholds, one for each critical level considered, to be used for issue the alert bulletin. Wetness indexes, representative of the soil moisture conditions of a catchment, are calculated using a simple, spatially-lumped rainfall-streamflow model, based on the SCS-CN method, and on the unit hydrograph approach, that require daily observed and/or predicted rainfall, and temperature data as input. For the calibration of this model daily continuous time series of rainfall, streamflow and air temperature data are used. An event based lumped rainfall-runoff model has been, instead, used for the derivation of the rainfall thresholds for each catchment in Sicily characterised by an area larger than 50 km2. In particular, a Kinematic Instantaneous Unit Hydrograph based lumped rainfall-runoff model with the SCS-CN routine for net rainfall was developed for this purpose. For rainfall-induced shallow landslide warning, empirical rainfall thresholds provided by Gariano et al. (2015) have been included in the system. They were derived on an empirical basis starting from a catalogue of 265 shallow landslides in Sicily in the period 2002-2012. Finally, Delft-FEWS operational forecasting platform has been applied to link input data, SMA model and rainfall threshold models to produce warning on a daily basis for the entire region.

Epidemic threshold of the susceptible-infected-susceptible model on complex networks

NASA Astrophysics Data System (ADS)

Lee, Hyun Keun; Shim, Pyoung-Seop; Noh, Jae Dong

2013-06-01

We demonstrate that the susceptible-infected-susceptible (SIS) model on complex networks can have an inactive Griffiths phase characterized by a slow relaxation dynamics. It contrasts with the mean-field theoretical prediction that the SIS model on complex networks is active at any nonzero infection rate. The dynamic fluctuation of infected nodes, ignored in the mean field approach, is responsible for the inactive phase. It is proposed that the question whether the epidemic threshold of the SIS model on complex networks is zero or not can be resolved by the percolation threshold in a model where nodes are occupied in degree-descending order. Our arguments are supported by the numerical studies on scale-free network models.

The dynamics of learning about a climate threshold

NASA Astrophysics Data System (ADS)

Keller, Klaus; McInerney, David

2008-02-01

Anthropogenic greenhouse gas emissions may trigger threshold responses of the climate system. One relevant example of such a potential threshold response is a shutdown of the North Atlantic meridional overturning circulation (MOC). Numerous studies have analyzed the problem of early MOC change detection (i.e., detection before the forcing has committed the system to a threshold response). Here we analyze the early MOC prediction problem. To this end, we virtually deploy an MOC observation system into a simple model that mimics potential future MOC responses and analyze the timing of confident detection and prediction. Our analysis suggests that a confident prediction of a potential threshold response can require century time scales, considerably longer that the time required for confident detection. The signal enabling early prediction of an approaching MOC threshold in our model study is associated with the rate at which the MOC intensity decreases for a given forcing. A faster MOC weakening implies a higher MOC sensitivity to forcing. An MOC sensitivity exceeding a critical level results in a threshold response. Determining whether an observed MOC trend in our model differs in a statistically significant way from an unforced scenario (the detection problem) imposes lower requirements on an observation system than the determination whether the MOC will shut down in the future (the prediction problem). As a result, the virtual observation systems designed in our model for early detection of MOC changes might well fail at the task of early and confident prediction. Transferring this conclusion to the real world requires a considerably refined MOC model, as well as a more complete consideration of relevant observational constraints.

Threshold Effects Beyond the Standard Model

NASA Astrophysics Data System (ADS)

Taylor, T. R.

In this contribution to the Festschrift celebrating Gabriele Veneziano on his 65th birthday, I discuss the threshold effects of extra dimensions and their applications to physics beyond the standard model, focusing on superstring theory.

Model Fit and Item Factor Analysis: Overfactoring, Underfactoring, and a Program to Guide Interpretation.

PubMed

Clark, D Angus; Bowles, Ryan P

2018-04-23

In exploratory item factor analysis (IFA), researchers may use model fit statistics and commonly invoked fit thresholds to help determine the dimensionality of an assessment. However, these indices and thresholds may mislead as they were developed in a confirmatory framework for models with continuous, not categorical, indicators. The present study used Monte Carlo simulation methods to investigate the ability of popular model fit statistics (chi-square, root mean square error of approximation, the comparative fit index, and the Tucker-Lewis index) and their standard cutoff values to detect the optimal number of latent dimensions underlying sets of dichotomous items. Models were fit to data generated from three-factor population structures that varied in factor loading magnitude, factor intercorrelation magnitude, number of indicators, and whether cross loadings or minor factors were included. The effectiveness of the thresholds varied across fit statistics, and was conditional on many features of the underlying model. Together, results suggest that conventional fit thresholds offer questionable utility in the context of IFA.

Analysis of Critical Mass in Threshold Model of Diffusion

NASA Astrophysics Data System (ADS)

Kim, Jeehong; Hur, Wonchang; Kang, Suk-Ho

2012-04-01

Why does diffusion sometimes show cascade phenomena but at other times is impeded? In addressing this question, we considered a threshold model of diffusion, focusing on the formation of a critical mass, which enables diffusion to be self-sustaining. Performing an agent-based simulation, we found that the diffusion model produces only two outcomes: Almost perfect adoption or relatively few adoptions. In order to explain the difference, we considered the various properties of network structures and found that the manner in which thresholds are arrayed over a network is the most critical factor determining the size of a cascade. On the basis of the results, we derived a threshold arrangement method effective for generation of a critical mass and calculated the size required for perfect adoption.

Threshold flux-controlled memristor model and its equivalent circuit implementation

NASA Astrophysics Data System (ADS)

Wu, Hua-Gan; Bao, Bo-Cheng; Chen, Mo

2014-11-01

Modeling a memristor is an effective way to explore the memristor properties due to the fact that the memristor devices are still not commercially available for common researchers. In this paper, a physical memristive device is assumed to exist whose ionic drift direction is perpendicular to the direction of the applied voltage, upon which, corresponding to the HP charge-controlled memristor model, a novel threshold flux-controlled memristor model with a window function is proposed. The fingerprints of the proposed model are analyzed. Especially, a practical equivalent circuit of the proposed model is realized, from which the corresponding experimental fingerprints are captured. The equivalent circuit of the threshold memristor model is appropriate for various memristors based breadboard experiments.

Large-Scale Interaction Effects Reveal Missing Heritability in Schizophrenia, Bipolar Disorder and Posttraumatic Stress Disorder

DTIC Science & Technology

2017-04-11

polymorphisms (SNPs) reached genome-wide significance. In contrast, when SNPs were selected in groups ( containing up to thousands each) and the collective...the underlying genetic factors has been challen- ging because of high polygenicity, necessitating large sample sizes in meta-analyses.4 Possible ways...partners simultaneously considered beyond SNP pairs by using the regularized inference of high -dimensional interactions within large SNP groups. Over

Quantitative Trait Loci (QTL) that Underlie SCN Resistance in the Soybean [Glycine max (L.) Merr.] ‘PI438489B’ by ‘Hamilton’ Recombinant Inbred Line Population

USDA-ARS?s Scientific Manuscript database

Soybean cyst nematode caused by Heterodera glycines is the most devastating pest in soybean [Glycine max (L.) Merr.]. Resistance to SCN is complex, polygenic, race-cultivar specific, and controlled by several QTL. Our objective was to identify and map QTL for SCN resistance to races 3 and 5 using a ...

Effects of autozygosity and schizophrenia polygenic risk on cognitive and brain developmental trajectories.

PubMed

Córdova-Palomera, Aldo; Kaufmann, Tobias; Bettella, Francesco; Wang, Yunpeng; Doan, Nhat Trung; van der Meer, Dennis; Alnæs, Dag; Rokicki, Jaroslav; Moberget, Torgeir; Sønderby, Ida Elken; Andreassen, Ole A; Westlye, Lars T

2018-04-27

Cognitive and brain development are determined by dynamic interactions between genes and environment across the lifespan. Aside from marker-by-marker analyses of polymorphisms, biologically meaningful features of the whole genome (derived from the combined effect of individual markers) have been postulated to inform on human phenotypes including cognitive traits and their underlying biological substrate. Here, estimates of inbreeding and genetic susceptibility for schizophrenia calculated from genome-wide data-runs of homozygosity (ROH) and schizophrenia polygenic risk score (PGRS)-are analyzed in relation to cognitive abilities (n = 4183) and brain structure (n = 516) in a general-population sample of European-ancestry participants aged 8-22, from the Philadelphia Neurodevelopmental Cohort. The findings suggest that a higher ROH burden and higher schizophrenia PGRS are associated with higher intelligence. Cognition-ROH and cognition-PGRS associations obtained in this cohort may, respectively, evidence that assortative mating influences intelligence, and that individuals with high schizophrenia genetic risk who do not transition to disease status are cognitively resilient. Neuroanatomical data showed that the effects of schizophrenia PGRS on cognition could be modulated by brain structure, although larger imaging datasets are needed to accurately disentangle the underlying neural mechanisms linking IQ with both inbreeding and the genetic burden for schizophrenia.

Genetic diversity of disease-associated loci in Turkish population.

PubMed

Karaca, Sefayet; Cesuroglu, Tomris; Karaca, Mehmet; Erge, Sema; Polimanti, Renato

2015-04-01

Many consortia and international projects have investigated the human genetic variation of a large number of ethno-geographic groups. However, populations with peculiar genetic features, such as the Turkish population, are still absent in publically available datasets. To explore the genetic predisposition to health-related traits of the Turkish population, we analyzed 34 genes associated with different health-related traits (for example, lipid metabolism, cardio-vascular diseases, hormone metabolism, cellular detoxification, aging and energy metabolism). We observed relevant differences between the Turkish population and populations with non-European ancestries (that is, Africa and East Asia) in some of the investigated genes (that is, AGT, APOE, CYP1B1, GNB3, IL10, IL6, LIPC and PON1). As most complex traits are highly polygenic, we developed polygenic scores associated with different health-related traits to explore the genetic diversity of the Turkish population with respect to other human groups. This approach showed significant differences between the Turkish population and populations with non-European ancestries, as well as between Turkish and Northern European individuals. This last finding is in agreement with the genetic structure of European and Middle East populations, and may also agree with epidemiological evidences about the health disparities of Turkish communities in Northern European countries.

Chronic gastroesophageal reflux disease shares genetic background with esophageal adenocarcinoma and Barrett's esophagus

PubMed Central

Gharahkhani, Puya; Tung, Joyce; Hinds, David; Mishra, Aniket; Vaughan, Thomas L.; Whiteman, David C.; MacGregor, Stuart

2016-01-01

Esophageal adenocarcinoma (EA) is a rapidly fatal cancer with rising incidence in the developed world. Most EAs arise in a metaplastic epithelium, Barrett's esophagus (BE), which is associated with greatly increased risk of EA. One of the key risk factors for both BE and EA is chronic gastroesophageal reflux disease (GERD). This study used the linkage disequilibrium (LD) score regression and genomic profile risk scoring approaches to investigate the contribution of multiple common single-nucleotide polymorphisms (SNPs) to the risk of GERD, and the extent of genetic overlap between GERD and BE or EA. Using LD score regression, we estimated an overall phenotypic variance of 7% (95% CI 3–11%) for GERD explained by all the genotyped SNPs. A genetic correlation of 77% (s.e. = 24%, P = 0.0012) between GERD and BE and 88% between GERD and EA (s.e. = 25%, P = 0.0004) was estimated using the LD score regression approach. Results from the genomic profile risk scoring approach, as a robustness check, were broadly similar to those from the LD score regression. This study provides the first evidence for a polygenic basis for GERD and supports for a polygenic overlap between GERD and BE, and GERD and EA. PMID:26704365

Parent and peer influences on emerging adult substance use disorder: A genetically informed study

PubMed Central

Bountress, Kaitlin; Chassin, Laurie; Lemery-Chalfant, Kathryn

2017-01-01

The present study utilizes longitudinal data from a high-risk community sample to examine the unique effects of genetic risk, parental knowledge about the daily activities of adolescents, and peer substance use on emerging adult substance use disorders (SUDs). These effects are examined over and above a polygenic risk score. In addition, this polygenic risk score is used to examine gene–environment correlation and interaction. The results show that during older adolescence, higher adolescent genetic risk for SUDs predicts less parental knowledge, but this relation is nonsignificant in younger adolescence. Parental knowledge (using mother report) mediates the effects of parental alcohol use disorder (AUD) and adolescent genetic risk on risk for SUD, and peer substance use mediates the effect of parent AUD on offspring SUD. Finally, there are significant gene–environment interactions such that, for those at the highest levels of genetic risk, less parental knowledge and more peer substance use confers greater risk for SUDs. However, for those at medium and low genetic risk, these effects are attenuated. These findings suggest that the evocative effects of adolescent genetic risk on parenting increase with age across adolescence. They also suggest that some of the most important environmental risk factors for SUDs exert effects that vary across level of genetic propensity. PMID:26753847

Recent advancements to study flowering time in almond and other Prunus species

PubMed Central

Sánchez-Pérez, Raquel; Del Cueto, Jorge; Dicenta, Federico; Martínez-Gómez, Pedro

2014-01-01

Flowering time is an important agronomic trait in almond since it is decisive to avoid the late frosts that affect production in early flowering cultivars. Evaluation of this complex trait is a long process because of the prolonged juvenile period of trees and the influence of environmental conditions affecting gene expression year by year. Consequently, flowering time has to be studied for several years to have statistical significant results. This trait is the result of the interaction between chilling and heat requirements. Flowering time is a polygenic trait with high heritability, although a major gene Late blooming (Lb) was described in “Tardy Nonpareil.” Molecular studies at DNA level confirmed this polygenic nature identifying several genome regions (Quantitative Trait Loci, QTL) involved. Studies about regulation of gene expression are scarcer although several transcription factors have been described as responsible for flowering time. From the metabolomic point of view, the integrated analysis of the mechanisms of accumulation of cyanogenic glucosides and flowering regulation through transcription factors open new possibilities in the analysis of this complex trait in almond and in other Prunus species (apricot, cherry, peach, plum). New opportunities are arising from the integration of recent advancements including phenotypic, genetic, genomic, transcriptomic, and metabolomics studies from the beginning of dormancy until flowering. PMID:25071812

DOE Office of Scientific and Technical Information (OSTI.GOV)

Comings, D.E.; Wu, S.; Chiu, C.

Polymorphisms of three different dopaminergic genes, dopamine D{sub 2} receptor (DRD2), dopamine {beta}-hydroxylase (D{beta}H), and dopamine transporter (DAT1), were examined in Tourette syndrome (TS) probands, their relatives, and controls. Each gene individually showed a significant correlation with various behavioral variables in these subjects. The additive and subtractive effects of the three genes were examined by genotyping all three genes in the same set of subjects. For 9 of 20 TS associated comorbid behaviors there was a significant linear association between the degree of loading for markers of three genes and the mean behavior scores. The behavior variables showing the significantmore » associations were, in order, attention deficit hyperactivity disorder (ADHD), stuttering, oppositional defiant, tics, conduct, obsessive-compulsive, mania, alcohol abuse, and general anxiety - behaviors that constitute the most overt clinical aspects of TS. For 16 of the 20 behavior scores there was a linear progressive decrease in the mean score with progressively lesser loading for the three gene markers. These results suggest that TS, ADHD, stuttering, oppositional defiant and conduct disorder, and other behaviors associated with TS, are polygenic, due in part to these three dopaminergic genes, and that the genetics of other polygenic psychiatric disorders may be deciphered using this technique. 144 refs., 2 figs., 13 tabs.« less

Incorporating genomics into breast and prostate cancer screening: assessing the implications

PubMed Central

Chowdhury, Susmita; Dent, Tom; Pashayan, Nora; Hall, Alison; Lyratzopoulos, Georgios; Hallowell, Nina; Hall, Per; Pharoah, Paul; Burton, Hilary

2013-01-01

Individual risk prediction and stratification based on polygenic profiling may be useful in disease prevention. Risk-stratified population screening based on multiple factors including a polygenic risk profile has the potential to be more efficient than age-stratified screening. In this article, we summarize the implications of personalized screening for breast and prostate cancers. We report the opinions of multidisciplinary international experts who have explored the scientific, ethical, and logistical aspects of stratified screening. We have identified (i) the need to recognize the benefits and harms of personalized screening as compared with existing screening methods, (ii) that the use of genetic data highlights complex ethical issues including discrimination against high-risk individuals by insurers and employers and patient autonomy in relation to genetic testing of minors, (iii) the need for transparency and clear communication about risk scores, about harms and benefits, and about reasons for inclusion and exclusion from the risk-based screening process, and (iv) the need to develop new professional competences and to assess cost-effectiveness and acceptability of stratified screening programs before implementation. We conclude that health professionals and stakeholders need to consider the implications of incorporating genetic information in intervention strategies for health-care planning in the future. Genet Med 2013:15(6):423–432 PMID:23412607

Detecting gene subnetworks under selection in biological pathways.

PubMed

Gouy, Alexandre; Daub, Joséphine T; Excoffier, Laurent

2017-09-19

Advances in high throughput sequencing technologies have created a gap between data production and functional data analysis. Indeed, phenotypes result from interactions between numerous genes, but traditional methods treat loci independently, missing important knowledge brought by network-level emerging properties. Therefore, detecting selection acting on multiple genes affecting the evolution of complex traits remains challenging. In this context, gene network analysis provides a powerful framework to study the evolution of adaptive traits and facilitates the interpretation of genome-wide data. We developed a method to analyse gene networks that is suitable to evidence polygenic selection. The general idea is to search biological pathways for subnetworks of genes that directly interact with each other and that present unusual evolutionary features. Subnetwork search is a typical combinatorial optimization problem that we solve using a simulated annealing approach. We have applied our methodology to find signals of adaptation to high-altitude in human populations. We show that this adaptation has a clear polygenic basis and is influenced by many genetic components. Our approach, implemented in the R package signet, improves on gene-level classical tests for selection by identifying both new candidate genes and new biological processes involved in adaptation to altitude. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

Collective interaction effects associated with mammalian behavioral traits reveal genetic factors connecting fear and hemostasis.

PubMed

Woo, Hyung Jun; Reifman, Jaques

2018-06-05

Investigation of the genetic architectures that influence the behavioral traits of animals can provide important insights into human neuropsychiatric phenotypes. These traits, however, are often highly polygenic, with individual loci contributing only small effects to the overall association. The polygenicity makes it challenging to explain, for example, the widely observed comorbidity between stress and cardiac disease. We present an algorithm for inferring the collective association of a large number of interacting gene variants with a quantitative trait. Using simulated data, we demonstrate that by taking into account the non-uniform distribution of genotypes within a cohort, we can achieve greater power than regression-based methods for high-dimensional inference. We analyzed genome-wide data sets of outbred mice and pet dogs, and found neurobiological pathways whose associations with behavioral traits arose primarily from interaction effects: γ-carboxylated coagulation factors and downstream neuronal signaling were highly associated with conditioned fear, consistent with our previous finding in human post-traumatic stress disorder (PTSD) data. Prepulse inhibition in mice was associated with serotonin transporter and platelet homeostasis, and noise-induced fear in dogs with hemostasis. Our findings suggest a novel explanation for the observed comorbidity between PTSD/anxiety and cardiovascular diseases: key coagulation factors modulating hemostasis also regulate synaptic plasticity affecting the learning and extinction of fear.

Genetics of canid skeletal variation: Size and shape of the pelvis

PubMed Central

Carrier, David R.; Chase, Kevin; Lark, Karl G.

2005-01-01

The mammalian skeleton presents an ideal system in which to study the genetic architecture of a set of related polygenic traits and the skeleton of the domestic dog (Canis familiaris) is arguably the best system in which to address the relationship between genes and anatomy. We have analyzed the genetic basis for skeletal variation in a population of >450 Portuguese Water Dogs. At this stage of this ongoing project, we have identified >40 putative quantitative trait loci (QTLs) for heritable skeletal phenotypes located on 22 different chromosomes, including the “X.” A striking aspect of these is the regulation of suites of traits representing bones located in different parts of the skeleton but related by function. Here we illustrate this by describing genetic variation in postcranial morphology. Two suites of traits are involved. One regulates the size of the pelvis relative to dimensions of the limb bones. The other regulates the shape of the pelvis. Both are examples of trade-offs that may be prototypical of different breeds. For the size of the pelvis relative to limb bones, we describe four QTLs located on autosome CFA 12, 30, 31, and X. For pelvic shape we describe QTLs on autosome CFA 2, 3, 22, and 36. The relation of these polygenic systems to musculoskeletal function is discussed. PMID:16339381

Genetics of canid skeletal variation: size and shape of the pelvis.

PubMed

Carrier, David R; Chase, Kevin; Lark, Karl G

2005-12-01

The mammalian skeleton presents an ideal system in which to study the genetic architecture of a set of related polygenic traits and the skeleton of the domestic dog (Canis familiaris) is arguably the best system in which to address the relationship between genes and anatomy. We have analyzed the genetic basis for skeletal variation in a population of >450 Portuguese Water Dogs. At this stage of this ongoing project, we have identified >40 putative quantitative trait loci (QTLs) for heritable skeletal phenotypes located on 22 different chromosomes, including the "X." A striking aspect of these is the regulation of suites of traits representing bones located in different parts of the skeleton but related by function. Here we illustrate this by describing genetic variation in postcranial morphology. Two suites of traits are involved. One regulates the size of the pelvis relative to dimensions of the limb bones. The other regulates the shape of the pelvis. Both are examples of trade-offs that may be prototypical of different breeds. For the size of the pelvis relative to limb bones, we describe four QTLs located on autosome CFA 12, 30, 31, and X. For pelvic shape we describe QTLs on autosome CFA 2, 3, 22, and 36. The relation of these polygenic systems to musculoskeletal function is discussed.

An avoidance behavior model for migrating whale populations

NASA Astrophysics Data System (ADS)

Buck, John R.; Tyack, Peter L.

2003-04-01

A new model is presented for the avoidance behavior of migrating marine mammals in the presence of a noise stimulus. This model assumes that each whale will adjust its movement pattern near a sound source to maintain its exposure below its own individually specific maximum received sound-pressure level, called its avoidance threshold. The probability distribution function (PDF) of this avoidance threshold across individuals characterizes the migrating population. The avoidance threshold PDF may be estimated by comparing the distribution of migrating whales during playback and control conditions at their closest point of approach to the sound source. The proposed model was applied to the January 1998 experiment which placed a single acoustic source from the U.S. Navy SURTASS-LFA system in the migration corridor of grey whales off the California coast. This analysis found that the median avoidance threshold for this migrating grey whale population was 135 dB, with 90% confidence that the median threshold was within +/-3 dB of this value. This value is less than the 141 dB value for 50% avoidance obtained when the 1984 ``Probability of Avoidance'' model of Malme et al.'s was applied to the same data. [Work supported by ONR.

Transverse tripolar stimulation of peripheral nerve: a modelling study of spatial selectivity.

PubMed

Deurloo, K E; Holsheimer, J; Boom, H B

1998-01-01

Various anode-cathode configurations in a nerve cuff are modelled to predict their spatial selectivity characteristics for functional nerve stimulation. A 3D volume conductor model of a monofascicular nerve is used for the computation of stimulation-induced field potentials, whereas a cable model of myelinated nerve fibre is used for the calculation of the excitation thresholds of fibres. As well as the usual configurations (monopole, bipole, longitudinal tripole, 'steering' anode), a transverse tripolar configuration (central cathode) is examined. It is found that the transverse tripole is the only configuration giving convex recruitment contours and therefore maximises activation selectivity for a small (cylindrical) bundle of fibres in the periphery of a monofascicular nerve trunk. As the electrode configuration is changed to achieve greater selectivity, the threshold current increases. Therefore threshold currents for fibre excitation with a transverse tripole are relatively high. Inverse recruitment is less extreme than for the other configurations. The influences of several geometrical parameters and model conductivities of the transverse tripole on selectivity and threshold current are analysed. In chronic implantation, when electrodes are encapsulated by a layer of fibrous tissue, threshold currents are low, whereas the shape of the recruitment contours in transverse tripolar stimulation does not change.

The consequences of ignoring measurement invariance for path coefficients in structural equation models

PubMed Central

Guenole, Nigel; Brown, Anna

2014-01-01

We report a Monte Carlo study examining the effects of two strategies for handling measurement non-invariance – modeling and ignoring non-invariant items – on structural regression coefficients between latent variables measured with item response theory models for categorical indicators. These strategies were examined across four levels and three types of non-invariance – non-invariant loadings, non-invariant thresholds, and combined non-invariance on loadings and thresholds – in simple, partial, mediated and moderated regression models where the non-invariant latent variable occupied predictor, mediator, and criterion positions in the structural regression models. When non-invariance is ignored in the latent predictor, the focal group regression parameters are biased in the opposite direction to the difference in loadings and thresholds relative to the referent group (i.e., lower loadings and thresholds for the focal group lead to overestimated regression parameters). With criterion non-invariance, the focal group regression parameters are biased in the same direction as the difference in loadings and thresholds relative to the referent group. While unacceptable levels of parameter bias were confined to the focal group, bias occurred at considerably lower levels of ignored non-invariance than was previously recognized in referent and focal groups. PMID:25278911

Otoliths - Accelerometer and seismometer; Implications in Vestibular Evoked Myogenic Potential (VEMP).

PubMed

Grant, Wally; Curthoys, Ian

2017-09-01

Vestibular otolithic organs are recognized as transducers of head acceleration and they function as such up to their corner frequency or undamped natural frequency. It is well recognized that these organs respond to frequencies above their corner frequency up to the 2-3 kHz range (Curthoys et al., 2016). A mechanics model for the transduction of these organs is developed that predicts the response below the undamped natural frequency as an accelerometer and above that frequency as a seismometer. The model is converted to a transfer function using hair cell bundle deflection. Measured threshold acceleration stimuli are used along with threshold deflections for threshold transfer function values. These are compared to model predicted values, both below and above their undamped natural frequency. Threshold deflection values are adjusted to match the model transfer function. The resulting threshold deflection values were well within in measure threshold bundle deflection ranges. Vestibular Evoked Myogenic Potentials (VEMPs) today routinely uses stimulus frequencies of 500 and 1000 Hz, and otoliths have been established incontrovertibly by clinical and neural evidence as the stimulus source. The mechanism for stimulus at these frequencies above the undamped natural frequency of otoliths is presented where otoliths are utilizing a seismometer mode of response for VEMP transduction. Copyright © 2017 Elsevier B.V. All rights reserved.

Cascades in the Threshold Model for varying system sizes

NASA Astrophysics Data System (ADS)

Karampourniotis, Panagiotis; Sreenivasan, Sameet; Szymanski, Boleslaw; Korniss, Gyorgy

2015-03-01

A classical model in opinion dynamics is the Threshold Model (TM) aiming to model the spread of a new opinion based on the social drive of peer pressure. Under the TM a node adopts a new opinion only when the fraction of its first neighbors possessing that opinion exceeds a pre-assigned threshold. Cascades in the TM depend on multiple parameters, such as the number and selection strategy of the initially active nodes (initiators), and the threshold distribution of the nodes. For a uniform threshold in the network there is a critical fraction of initiators for which a transition from small to large cascades occurs, which for ER graphs is largerly independent of the system size. Here, we study the spread contribution of each newly assigned initiator under the TM for different initiator selection strategies for synthetic graphs of various sizes. We observe that for ER graphs when large cascades occur, the spread contribution of the added initiator on the transition point is independent of the system size, while the contribution of the rest of the initiators converges to zero at infinite system size. This property is used for the identification of large transitions for various threshold distributions. Supported in part by ARL NS-CTA, ARO, ONR, and DARPA.

Modeling of ablation threshold dependence on pulse duration for dielectrics with ultrashort pulsed laser

NASA Astrophysics Data System (ADS)

Sun, Mingying; Zhu, Jianqiang; Lin, Zunqi

2017-01-01

We present a numerical model of plasma formation in ultrafast laser ablation on the dielectrics surface. Ablation threshold dependence on pulse duration is predicted with the model and the numerical results for water agrees well with the experimental data for pulse duration from 140 fs to 10 ps. Influences of parameters and approximations of photo- and avalanche-ionization on the ablation threshold prediction are analyzed in detail for various pulse lengths. The calculated ablation threshold is strongly dependent on electron collision time for all the pulse durations. The complete photoionization model is preferred for pulses shorter than 1 ps rather than the multiphoton ionization approximations. The transition time of inverse bremsstrahlung absorption needs to be considered when pulses are shorter than 5 ps and it can also ensure the avalanche ionization (AI) coefficient consistent with that in multiple rate equations (MREs) for pulses shorter than 300 fs. The threshold electron density for AI is only crucial for longer pulses. It is reasonable to ignore the recombination loss for pulses shorter than 100 fs. In addition to thermal transport and hydrodynamics, neglecting the threshold density for AI and recombination could also contribute to the disagreements between the numerical and the experimental results for longer pulses.

Patterns of motor recruitment can be determined using surface EMG.

PubMed

Wakeling, James M

2009-04-01

Previous studies have reported how different populations of motor units (MUs) can be recruited during dynamic and locomotor tasks. It was hypothesised that the higher-threshold units would contribute higher-frequency components to the sEMG spectra due to their faster conduction velocities, and thus recruitment patterns that increase the proportion of high-threshold units active would lead to higher-frequency elements in the sEMG spectra. This idea was tested by using a model of varying recruitment coupled to a three-layer volume conductor model to generate a series of sEMG signals. The recruitment varied from (A) orderly recruitment where the lowest-threshold MUs were initially activated and higher-threshold MUs were sequentially recruited as the contraction progressed, (B) a recurrent inhibition model that started with orderly recruitment, but as the higher-threshold units were activated they inhibited the lower-threshold MUs (C) nine models with intermediate properties that were graded between these two extremes. The sEMG was processed using wavelet analysis and the spectral properties quantified by their mean frequency, and an angle theta that was determined from the principal components of the spectra. Recruitment strategies that resulted in a greater proportion of faster MUs being active had a significantly lower theta and higher mean frequency.

Random sex determination: When developmental noise tips the sex balance.

PubMed

Perrin, Nicolas

2016-12-01

Sex-determining factors are usually assumed to be either genetic or environmental. The present paper aims at drawing attention to the potential contribution of developmental noise, an important but often-neglected component of phenotypic variance. Mutual inhibitions between male and female pathways make sex a bistable equilibrium, such that random fluctuations in the expression of genes at the top of the cascade are sufficient to drive individual development toward one or the other stable state. Evolutionary modeling shows that stochastic sex determinants should resist elimination by genetic or environmental sex determinants under ecologically meaningful settings. On the empirical side, many sex-determination systems traditionally considered as environmental or polygenic actually provide evidence for large components of stochasticity. In reviewing the field, I argue that sex-determination systems should be considered within a three-ends continuum, rather than the classical two-ends continuum. © 2016 WILEY Periodicals, Inc.

Genomic estimation of complex traits reveals ancient maize adaptation to temperate North America.

PubMed

Swarts, Kelly; Gutaker, Rafal M; Benz, Bruce; Blake, Michael; Bukowski, Robert; Holland, James; Kruse-Peeples, Melissa; Lepak, Nicholas; Prim, Lynda; Romay, M Cinta; Ross-Ibarra, Jeffrey; Sanchez-Gonzalez, Jose de Jesus; Schmidt, Chris; Schuenemann, Verena J; Krause, Johannes; Matson, R G; Weigel, Detlef; Buckler, Edward S; Burbano, Hernán A

2017-08-04

By 4000 years ago, people had introduced maize to the southwestern United States; full agriculture was established quickly in the lowland deserts but delayed in the temperate highlands for 2000 years. We test if the earliest upland maize was adapted for early flowering, a characteristic of modern temperate maize. We sequenced fifteen 1900-year-old maize cobs from Turkey Pen Shelter in the temperate Southwest. Indirectly validated genomic models predicted that Turkey Pen maize was marginally adapted with respect to flowering, as well as short, tillering, and segregating for yellow kernel color. Temperate adaptation drove modern population differentiation and was selected in situ from ancient standing variation. Validated prediction of polygenic traits improves our understanding of ancient phenotypes and the dynamics of environmental adaptation. Copyright © 2017 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.

Insights into DDT Resistance from the Drosophila melanogaster Genetic Reference Panel

PubMed Central

Schmidt, Joshua M.; Battlay, Paul; Gledhill-Smith, Rebecca S.; Good, Robert T.; Lumb, Chris; Fournier-Level, Alexandre; Robin, Charles

2017-01-01

Insecticide resistance is considered a classic model of microevolution, where a strong selective agent is applied to a large natural population, resulting in a change in frequency of alleles that confer resistance. While many insecticide resistance variants have been characterized at the gene level, they are typically single genes of large effect identified in highly resistant pest species. In contrast, multiple variants have been implicated in DDT resistance in Drosophila melanogaster; however, only the Cyp6g1 locus has previously been shown to be relevant to field populations. Here we use genome-wide association studies (GWAS) to identify DDT-associated polygenes and use selective sweep analyses to assess their adaptive significance. We identify and verify two candidate DDT resistance loci. A largely uncharacterized gene, CG10737, has a function in muscles that ameliorates the effects of DDT, while a putative detoxifying P450, Cyp6w1, shows compelling evidence of positive selection. PMID:28935691

Neuroendocrine regulation of somatic growth in fishes.

PubMed

Dai, XiangYan; Zhang, Wei; Zhuo, ZiJian; He, JiangYan; Yin, Zhan

2015-02-01

Growth is a polygenic trait that is under the influence of multiple physiological pathways regulating energy metabolism and muscle growth. Among the possible growth-regulating pathways in vertebrates, components of the somatotropic axis are thought to have the greatest influence. There is growing body of literature focusing on the somatotropic axis and its role regulating growth in fish. This includes research into growth hormone, upstream hypothalamic hormones, insulin-like growth factors, and downstream signaling molecules. Many of these signals have both somatic effects stimulating the growth of tissues and metabolic effects that play a role in nutrient metabolism. Signals of other endocrine axes exhibit profound effects on the function of the somatotropic axis in vivo. In this review we highlight recent advances in our understanding of the teleost fish endocrine somatotropic axis, including emerging research using genetic modified models. These studies have revealed new aspects and challenges associated with regulation of the important steps of somatic growth.

Deciphering the evolution of herbicide resistance in weeds.

PubMed

Délye, Christophe; Jasieniuk, Marie; Le Corre, Valérie

2013-11-01

Resistance to herbicides in arable weeds is increasing rapidly worldwide and threatening global food security. Resistance has now been reported to all major herbicide modes of action despite the development of resistance management strategies in the 1990s. We review here recent advances in understanding the genetic bases and evolutionary drivers of herbicide resistance that highlight the complex nature of selection for this adaptive trait. Whereas early studied cases of resistance were highly herbicide-specific and largely under monogenic control, cases of greatest concern today generally involve resistance to multiple modes of action, are under polygenic control, and are derived from pre-existing stress response pathways. Although 'omics' approaches should enable unraveling the genetic bases of complex resistances, the appearance, selection, and spread of herbicide resistance in weed populations can only be fully elucidated by focusing on evolutionary dynamics and implementing integrative modeling efforts. Copyright © 2013 Elsevier Ltd. All rights reserved.

Animal model of cochlear third window in the scala vestibuli or scala tympani.

PubMed

Attias, Joseph; Preis, Michal; Shemesh, Rafi; Hadar, Tuvia; Nageris, Ben I

2010-08-01

The auditory impact of a cochlear third window differs by its location in the scala vestibuli or scala tympani. Pathologic third window has been investigated primarily in the vestibular apparatus of animals and humans. Dehiscence of the superior semicircular canal is the clinical model. Fat sand rats (n = 11) have a unique inner-ear anatomy that allows easy surgical access. A window was drilled in the bony labyrinth over the scala vestibuli in 1 group (12 ears) and over the scala tympani in another (7 ears) while preserving the membranous labyrinth. Auditory brain stem responses to high- and low-frequency stimuli delivered by air and bone conduction were recorded before and after the procedure. Scala vestibuli group: preoperative air-conduction thresholds to clicks and tone-bursts averaged 8.3 and 9.6 dB, respectively, and bone-conduction thresholds, 4.6 and 3.3 dB, respectively; after fenestration, air-conduction thresholds averaged 40.4 and 41.8 dB, respectively, and bone-conduction thresholds, -1 and 5.6 dB, respectively. Scala tympani group: preoperative air-conduction thresholds to clicks and tone-bursts averaged 8.6 dB each, and bone-conduction thresholds, 7.9 dB and 7.1 dB, respectively; after fenestration, air-conduction thresholds averaged 11.4 and 9.3 dB, respectively, and bone-conduction thresholds, 9.3 and 4.2 dB, respectively. The changes in air- (p = 0.0001) and bone-conduction (p = 0.04) thresholds were statistically significant only in the scala vestibuli group. The presence of a cochlear third window over the scala vestibuli, but not over the scala tympani, causes a significant increase in air-conduction auditory thresholds. These results agree with the theoretic model and clinical findings and contribute to our understanding of vestibular dehiscence.

A Genome-Wide Association Study for Clinical Mastitis in First Parity US Holstein Cows Using Single-Step Approach and Genomic Matrix Re-Weighting Procedure

PubMed Central

Tiezzi, Francesco; Parker-Gaddis, Kristen L.; Cole, John B.; Clay, John S.; Maltecca, Christian

2015-01-01

Clinical mastitis (CM) is one of the health disorders with large impacts on dairy farming profitability and animal welfare. The objective of this study was to perform a genome-wide association study (GWAS) for CM in first-lactation Holstein. Producer-recorded mastitis event information for 103,585 first-lactation cows were used, together with genotype information on 1,361 bulls from the Illumina BovineSNP50 BeadChip. Single-step genomic-BLUP methodology was used to incorporate genomic data into a threshold-liability model. Association analysis confirmed that CM follows a highly polygenic mode of inheritance. However, 10-adjacent-SNP windows showed that regions on chromosomes 2, 14 and 20 have impacts on genetic variation for CM. Some of the genes located on chromosome 14 (LY6K, LY6D, LYNX1, LYPD2, SLURP1, PSCA) are part of the lymphocyte-antigen-6 complex (LY6) known for its neutrophil regulation function linked to the major histocompatibility complex. Other genes on chromosome 2 were also involved in regulating immune response (IFIH1, LY75, and DPP4), or are themselves regulated in the presence of specific pathogens (ITGB6, NR4A2). Other genes annotated on chromosome 20 are involved in mammary gland metabolism (GHR, OXCT1), antibody production and phagocytosis of bacterial cells (C6, C7, C9, C1QTNF3), tumor suppression (DAB2), involution of mammary epithelium (OSMR) and cytokine regulation (PRLR). DAVID enrichment analysis revealed 5 KEGG pathways. The JAK-STAT signaling pathway (cell proliferation and apoptosis) and the ‘Cytokine-cytokine receptor interaction’ (cytokine and interleukines response to infectious agents) are co-regulated and linked to the ‘ABC transporters’ pathway also found here. Gene network analysis performed using GeneMania revealed a co-expression network where 665 interactions existed among 145 of the genes reported above. Clinical mastitis is a complex trait and the different genes regulating immune response are known to be pathogen-specific. Despite the lack of information in this study, candidate QTL for CM were identified in the US Holstein population. PMID:25658712

A flexible cure rate model with dependent censoring and a known cure threshold.

PubMed

Bernhardt, Paul W

2016-11-10

We propose a flexible cure rate model that accommodates different censoring distributions for the cured and uncured groups and also allows for some individuals to be observed as cured when their survival time exceeds a known threshold. We model the survival times for the uncured group using an accelerated failure time model with errors distributed according to the seminonparametric distribution, potentially truncated at a known threshold. We suggest a straightforward extension of the usual expectation-maximization algorithm approach for obtaining estimates in cure rate models to accommodate the cure threshold and dependent censoring. We additionally suggest a likelihood ratio test for testing for the presence of dependent censoring in the proposed cure rate model. We show through numerical studies that our model has desirable properties and leads to approximately unbiased parameter estimates in a variety of scenarios. To demonstrate how our method performs in practice, we analyze data from a bone marrow transplantation study and a liver transplant study. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Poverty dynamics, poverty thresholds and mortality: An age-stage Markovian model

PubMed Central

Rehkopf, David; Tuljapurkar, Shripad; Horvitz, Carol C.

2018-01-01

Recent studies have examined the risk of poverty throughout the life course, but few have considered how transitioning in and out of poverty shape the dynamic heterogeneity and mortality disparities of a cohort at each age. Here we use state-by-age modeling to capture individual heterogeneity in crossing one of three different poverty thresholds (defined as 1×, 2× or 3× the “official” poverty threshold) at each age. We examine age-specific state structure, the remaining life expectancy, its variance, and cohort simulations for those above and below each threshold. Survival and transitioning probabilities are statistically estimated by regression analyses of data from the Health and Retirement Survey RAND data-set, and the National Longitudinal Survey of Youth. Using the results of these regression analyses, we parameterize discrete state, discrete age matrix models. We found that individuals above all three thresholds have higher annual survival than those in poverty, especially for mid-ages to about age 80. The advantage is greatest when we classify individuals based on 1× the “official” poverty threshold. The greatest discrepancy in average remaining life expectancy and its variance between those above and in poverty occurs at mid-ages for all three thresholds. And fewer individuals are in poverty between ages 40-60 for all three thresholds. Our findings are consistent with results based on other data sets, but also suggest that dynamic heterogeneity in poverty and the transience of the poverty state is associated with income-related mortality disparities (less transience, especially of those above poverty, more disparities). This paper applies the approach of age-by-stage matrix models to human demography and individual poverty dynamics. In so doing we extend the literature on individual poverty dynamics across the life course. PMID:29768416

A threshold-based weather model for predicting stripe rust infection in winter wheat

USDA-ARS?s Scientific Manuscript database

Wheat stripe rust (WSR) (caused by Puccinia striiformis sp. tritici) is a major threat in most wheat growing regions worldwide, with potential to inflict regular yield losses when environmental conditions are favorable. We propose a threshold-based disease-forecasting model using a stepwise modeling...

Limit sets for natural extensions of Schelling’s segregation model

NASA Astrophysics Data System (ADS)

Singh, Abhinav; Vainchtein, Dmitri; Weiss, Howard

2011-07-01

Thomas Schelling developed an influential demographic model that illustrated how, even with relatively mild assumptions on each individual's nearest neighbor preferences, an integrated city would likely unravel to a segregated city, even if all individuals prefer integration. Individuals in Schelling's model cities are divided into two groups of equal number and each individual is "happy" or "unhappy" when the number of similar neighbors cross a simple threshold. In this manuscript we consider natural extensions of Schelling's original model to allow the two groups have different sizes and to allow different notions of happiness of an individual. We observe that differences in aggregation patterns of majority and minority groups are highly sensitive to the happiness threshold; for low threshold, the differences are small, and when the threshold is raised, striking new patterns emerge. We also observe that when individuals strongly prefer to live in integrated neighborhoods, the final states exhibit a new tessellated-like structure.

Vehicle lift-off modelling and a new rollover detection criterion

NASA Astrophysics Data System (ADS)

Mashadi, Behrooz; Mostaghimi, Hamid

2017-05-01

The modelling and development of a general criterion for the prediction of rollover threshold is the main purpose of this work. Vehicle dynamics models after the wheels lift-off and when the vehicle moves on the two wheels are derived and the governing equations are used to develop the rollover threshold. These models include the properties of the suspension and steering systems. In order to study the stability of motion, the steady-state solutions of the equations of motion are carried out. Based on the stability analyses, a new relation is obtained for the rollover threshold in terms of measurable response parameters. The presented criterion predicts the best time for the prevention of the vehicle rollover by applying a correcting moment. It is shown that the introduced threshold of vehicle rollover is a proper state of vehicle motion that is best for stabilising the vehicle with a low energy requirement.

Algorithmic detectability threshold of the stochastic block model

NASA Astrophysics Data System (ADS)

Kawamoto, Tatsuro

2018-03-01

The assumption that the values of model parameters are known or correctly learned, i.e., the Nishimori condition, is one of the requirements for the detectability analysis of the stochastic block model in statistical inference. In practice, however, there is no example demonstrating that we can know the model parameters beforehand, and there is no guarantee that the model parameters can be learned accurately. In this study, we consider the expectation-maximization (EM) algorithm with belief propagation (BP) and derive its algorithmic detectability threshold. Our analysis is not restricted to the community structure but includes general modular structures. Because the algorithm cannot always learn the planted model parameters correctly, the algorithmic detectability threshold is qualitatively different from the one with the Nishimori condition.

Computer simulation of fibrillation threshold measurements and electrophysiologic testing procedures

NASA Technical Reports Server (NTRS)

Grumbach, M. P.; Saxberg, B. E.; Cohen, R. J.

1987-01-01

A finite element model of cardiac conduction was used to simulate two experimental protocols: 1) fibrillation threshold measurements and 2) clinical electrophysiologic (EP) testing procedures. The model consisted of a cylindrical lattice whose properties were determined by four parameters: element length, conduction velocity, mean refractory period, and standard deviation of refractory periods. Different stimulation patterns were applied to the lattice under a given set of lattice parameter values and the response of the model was observed through a simulated electrocardiogram. The studies confirm that the model can account for observations made in experimental fibrillation threshold measurements and in clinical EP testing protocols.

On the thresholds in modeling of high flows via artificial neural networks - A bootstrapping analysis

NASA Astrophysics Data System (ADS)

Panagoulia, D.; Trichakis, I.

2012-04-01

Considering the growing interest in simulating hydrological phenomena with artificial neural networks (ANNs), it is useful to figure out the potential and limits of these models. In this study, the main objective is to examine how to improve the ability of an ANN model to simulate extreme values of flow utilizing a priori knowledge of threshold values. A three-layer feedforward ANN was trained by using the back propagation algorithm and the logistic function as activation function. By using the thresholds, the flow was partitioned in low (x < μ), medium (μ ≤ x ≤ μ + 2σ) and high (x > μ + 2σ) values. The employed ANN model was trained for high flow partition and all flow data too. The developed methodology was implemented over a mountainous river catchment (the Mesochora catchment in northwestern Greece). The ANN model received as inputs pseudo-precipitation (rain plus melt) and previous observed flow data. After the training was completed the bootstrapping methodology was applied to calculate the ANN confidence intervals (CIs) for a 95% nominal coverage. The calculated CIs included only the uncertainty, which comes from the calibration procedure. The results showed that an ANN model trained specifically for high flows, with a priori knowledge of the thresholds, can simulate these extreme values much better (RMSE is 31.4% less) than an ANN model trained with all data of the available time series and using a posteriori threshold values. On the other hand the width of CIs increases by 54.9% with a simultaneous increase by 64.4% of the actual coverage for the high flows (a priori partition). The narrower CIs of the high flows trained with all data may be attributed to the smoothing effect produced from the use of the full data sets. Overall, the results suggest that an ANN model trained with a priori knowledge of the threshold values has an increased ability in simulating extreme values compared with an ANN model trained with all the data and a posteriori knowledge of the thresholds.

[The analysis of threshold effect using Empower Stats software].

PubMed

Lin, Lin; Chen, Chang-zhong; Yu, Xiao-dan

2013-11-01

In many studies about biomedical research factors influence on the outcome variable, it has no influence or has a positive effect within a certain range. Exceeding a certain threshold value, the size of the effect and/or orientation will change, which called threshold effect. Whether there are threshold effects in the analysis of factors (x) on the outcome variable (y), it can be observed through a smooth curve fitting to see whether there is a piecewise linear relationship. And then using segmented regression model, LRT test and Bootstrap resampling method to analyze the threshold effect. Empower Stats software developed by American X & Y Solutions Inc has a threshold effect analysis module. You can input the threshold value at a given threshold segmentation simulated data. You may not input the threshold, but determined the optimal threshold analog data by the software automatically, and calculated the threshold confidence intervals.

Level crossings and excess times due to a superposition of uncorrelated exponential pulses

NASA Astrophysics Data System (ADS)

Theodorsen, A.; Garcia, O. E.

2018-01-01

A well-known stochastic model for intermittent fluctuations in physical systems is investigated. The model is given by a superposition of uncorrelated exponential pulses, and the degree of pulse overlap is interpreted as an intermittency parameter. Expressions for excess time statistics, that is, the rate of level crossings above a given threshold and the average time spent above the threshold, are derived from the joint distribution of the process and its derivative. Limits of both high and low intermittency are investigated and compared to previously known results. In the case of a strongly intermittent process, the distribution of times spent above threshold is obtained analytically. This expression is verified numerically, and the distribution of times above threshold is explored for other intermittency regimes. The numerical simulations compare favorably to known results for the distribution of times above the mean threshold for an Ornstein-Uhlenbeck process. This contribution generalizes the excess time statistics for the stochastic model, which find applications in a wide diversity of natural and technological systems.

Network-level reproduction number and extinction threshold for vector-borne diseases.

PubMed

Xue, Ling; Scoglio, Caterina

2015-06-01

The basic reproduction number of deterministic models is an essential quantity to predict whether an epidemic will spread or not. Thresholds for disease extinction contribute crucial knowledge of disease control, elimination, and mitigation of infectious diseases. Relationships between basic reproduction numbers of two deterministic network-based ordinary differential equation vector-host models, and extinction thresholds of corresponding stochastic continuous-time Markov chain models are derived under some assumptions. Numerical simulation results for malaria and Rift Valley fever transmission on heterogeneous networks are in agreement with analytical results without any assumptions, reinforcing that the relationships may always exist and proposing a mathematical problem for proving existence of the relationships in general. Moreover, numerical simulations show that the basic reproduction number does not monotonically increase or decrease with the extinction threshold. Consistent trends of extinction probability observed through numerical simulations provide novel insights into mitigation strategies to increase the disease extinction probability. Research findings may improve understandings of thresholds for disease persistence in order to control vector-borne diseases.

Effects of noise and confidence thresholds in nominal and metric Axelrod dynamics of social influence

NASA Astrophysics Data System (ADS)

de Sanctis, Luca; Galla, Tobias

2009-04-01

We study the effects of bounded confidence thresholds and of interaction and external noise on Axelrod’s model of social influence. Our study is based on a combination of numerical simulations and an integration of the mean-field master equation describing the system in the thermodynamic limit. We find that interaction thresholds affect the system only quantitatively, but that they do not alter the basic phase structure. The known crossover between an ordered and a disordered state in finite systems subject to external noise persists in models with general confidence threshold. Interaction noise here facilitates the dynamics and reduces relaxation times. We also study Axelrod systems with metric features and point out similarities and differences compared to models with nominal features.

Comparison of singlet oxygen threshold dose for PDT.

PubMed

Zhu, Timothy C; Liu, Baochang; Kim, Michele M; McMillan, Dayton; Liang, Xing; Finlay, Jarod C; Busch, Theresa M

2014-02-01

Macroscopic modeling of singlet oxygen ( 1 O 2 ) is of particular interest because it is the major cytotoxic agent causing biological effects for type II photosensitizers during PDT. We have developed a macroscopic model to calculate reacted singlet oxygen concentration ([1O2] rx for PDT. An in-vivo RIF tumor mouse model is used to correlate the necrosis depth to the calculation based on explicit PDT dosimetry of light fluence distribution, tissue optical properties, and photosensitizer concentrations. Inputs to the model include 4 photosensitizer specific photochemical parameters along with the apparent singlet oxygen threshold concentration. Photosensitizer specific model parameters are determined for several type II photosensitizers (Photofrin, BPD, and HPPH). The singlet oxygen threshold concentration is approximately 0.41 - 0.56 mM for all three photosensitizers studied, assuming that the fraction of singlet oxygen generated that interacts with the cell is ( f = 1). In comparison, value derived from other in-vivo mice studies is 0.4 mM for mTHPC. However, the singlet oxygen threshold doses were reported to be 7.9 and 12.1 mM for a multicell in-vitro EMT6/Ro spheroid model for mTHPC and Photofrin PDT, respectively. The sensitivity of threshold singlet oxygen dose for our experiment is examined. The possible influence of vascular vs. apoptotic cell killing mechanism on the singlet oxygen threshold dose is discussed using the BPD with different drug-light intervals 3 hrs vs. 15 min. The observed discrepancies between different experiments warrant further investigation to explain the cause of the difference.

Comparison of singlet oxygen threshold dose for PDT

PubMed Central

Zhu, Timothy C; Liu, Baochang; Kim, Michele M.; McMillan, Dayton; Liang, Xing; Finlay, Jarod C.; Busch, Theresa M.

2015-01-01

Macroscopic modeling of singlet oxygen (1O2) is of particular interest because it is the major cytotoxic agent causing biological effects for type II photosensitizers during PDT. We have developed a macroscopic model to calculate reacted singlet oxygen concentration ([1O2]rx for PDT. An in-vivo RIF tumor mouse model is used to correlate the necrosis depth to the calculation based on explicit PDT dosimetry of light fluence distribution, tissue optical properties, and photosensitizer concentrations. Inputs to the model include 4 photosensitizer specific photochemical parameters along with the apparent singlet oxygen threshold concentration. Photosensitizer specific model parameters are determined for several type II photosensitizers (Photofrin, BPD, and HPPH). The singlet oxygen threshold concentration is approximately 0.41 – 0.56 mM for all three photosensitizers studied, assuming that the fraction of singlet oxygen generated that interacts with the cell is (f = 1). In comparison, value derived from other in-vivo mice studies is 0.4 mM for mTHPC. However, the singlet oxygen threshold doses were reported to be 7.9 and 12.1 mM for a multicell in-vitro EMT6/Ro spheroid model for mTHPC and Photofrin PDT, respectively. The sensitivity of threshold singlet oxygen dose for our experiment is examined. The possible influence of vascular vs. apoptotic cell killing mechanism on the singlet oxygen threshold dose is discussed using the BPD with different drug-light intervals 3 hrs vs. 15 min. The observed discrepancies between different experiments warrant further investigation to explain the cause of the difference. PMID:25999651

Association of daily asthma emergency department visits and hospital admissions with ambient air pollutants among the pediatric Medicaid population in Detroit: time-series and time-stratified case-crossover analyses with threshold effects.

PubMed

Li, Shi; Batterman, Stuart; Wasilevich, Elizabeth; Wahl, Robert; Wirth, Julie; Su, Feng-Chiao; Mukherjee, Bhramar

2011-11-01

Asthma morbidity has been associated with ambient air pollutants in time-series and case-crossover studies. In such study designs, threshold effects of air pollutants on asthma outcomes have been relatively unexplored, which are of potential interest for exploring concentration-response relationships. This study analyzes daily data on the asthma morbidity experienced by the pediatric Medicaid population (ages 2-18 years) of Detroit, Michigan and concentrations of pollutants fine particles (PM2.5), CO, NO2 and SO2 for the 2004-2006 period, using both time-series and case-crossover designs. We use a simple, testable and readily implementable profile likelihood-based approach to estimate threshold parameters in both designs. Evidence of significant increases in daily acute asthma events was found for SO2 and PM2.5, and a significant threshold effect was estimated for PM2.5 at 13 and 11 μg m(-3) using generalized additive models and conditional logistic regression models, respectively. Stronger effect sizes above the threshold were typically noted compared to standard linear relationship, e.g., in the time series analysis, an interquartile range increase (9.2 μg m(-3)) in PM2.5 (5-day-moving average) had a risk ratio of 1.030 (95% CI: 1.001, 1.061) in the generalized additive models, and 1.066 (95% CI: 1.031, 1.102) in the threshold generalized additive models. The corresponding estimates for the case-crossover design were 1.039 (95% CI: 1.013, 1.066) in the conditional logistic regression, and 1.054 (95% CI: 1.023, 1.086) in the threshold conditional logistic regression. This study indicates that the associations of SO2 and PM2.5 concentrations with asthma emergency department visits and hospitalizations, as well as the estimated PM2.5 threshold were fairly consistent across time-series and case-crossover analyses, and suggests that effect estimates based on linear models (without thresholds) may underestimate the true risk. Copyright © 2011 Elsevier Inc. All rights reserved.

Do we need a dynamic snow depth threshold when comparing hydrological models with remote sensing products in mountain catchments?

NASA Astrophysics Data System (ADS)

Engel, Michael; Bertoldi, Giacomo; Notarnicola, Claudia; Comiti, Francesco

2017-04-01

To assess the performance of simulated snow cover of hydrological models, it is common practice to compare simulated data with observed ones derived from satellite images such as MODIS. However, technical and methodological limitations such as data availability of MODIS products, its spatial resolution or difficulties in finding appropriate parameterisations of the model need to be solved previously. Another important assumption usually made is the threshold of minimum simulated snow depth, generally set to 10 mm of snow depth, to respect the MODIS detection thresholds for snow cover. But is such a constant threshold appropriate for complex alpine terrain? How important is the impact of different snow depth thresholds on the spatial and temporal distribution of the pixel-based overall accuracy (OA)? To address this aspect, we compared the snow covered area (SCA) simulated by the GEOtop 2.0 snow model to the daily composite 250 m EURAC MODIS SCA in the upper Saldur basin (61 km2, Eastern Italian Alps) during the period October 2011 - October 2013. Initially, we calibrated the snow model against snow depths and snow water equivalents at point scale, taken from measurements at different meteorological stations. We applied different snow depth thresholds (0 mm, 10 mm, 50 mm, and 100 mm) to obtain the simulated snow cover and assessed the changes in OA both in time (during the entire evaluation period, accumulation and melting season) and space (entire catchment and specific areas of topographic characteristics such as elevation, slope, aspect, landcover, and roughness). Results show remarkable spatial and temporal differences in OA with respect to different snow depth thresholds. Inaccuracies of simulated and observed SCA during the accumulation season September to November 2012 were located in areas with north-west aspect, slopes of 30° or little elevation differences at sub-pixel scale (-0.25 to 0 m). We obtained best agreements with MODIS SCA for a snow depth threshold of 100 mm, leading to increased OA (> 0.8) in 13‰ of the catchment area. SCA agreement in January 2012 and 2013 was slightly limited by MODIS sensor detection due to shading effects and low illumination in areas exposed north-west to north. On the contrary, during the melting season in April 2013 and after the September 2013 snowfall event seemed to depend more on parameterisation than on snow depth thresholds. In contrast, inaccuracies during the melting season March to June 2013 could hardly be attributed to topographic characteristics and different snow depth thresholds but rather on model parameterisation. We identified specific conditions (p.e. specific snowfall events in autumn 2012 and spring 2013) when either MODIS data or the hydrological model was less accurate, thus justifying the need for improvements of precision in the snow cover detection algorithms or in the model's process description. In consequence, our study observations could support future snow cover evaluations in mountain areas, where spatially and temporally dynamic snow depth thresholds are transferred from the catchment scale to the regional scale. Keywords: snow cover, snow modelling, MODIS, snow depth sensitivity, alpine catchment

The Impact of Heterogeneous Thresholds on Social Contagion with Multiple Initiators

PubMed Central

Karampourniotis, Panagiotis D.; Sreenivasan, Sameet; Szymanski, Boleslaw K.; Korniss, Gyorgy

2015-01-01

The threshold model is a simple but classic model of contagion spreading in complex social systems. To capture the complex nature of social influencing we investigate numerically and analytically the transition in the behavior of threshold-limited cascades in the presence of multiple initiators as the distribution of thresholds is varied between the two extreme cases of identical thresholds and a uniform distribution. We accomplish this by employing a truncated normal distribution of the nodes’ thresholds and observe a non-monotonic change in the cascade size as we vary the standard deviation. Further, for a sufficiently large spread in the threshold distribution, the tipping-point behavior of the social influencing process disappears and is replaced by a smooth crossover governed by the size of initiator set. We demonstrate that for a given size of the initiator set, there is a specific variance of the threshold distribution for which an opinion spreads optimally. Furthermore, in the case of synthetic graphs we show that the spread asymptotically becomes independent of the system size, and that global cascades can arise just by the addition of a single node to the initiator set. PMID:26571486

Information and redundancy: key concepts in understanding the genetic control of health and intelligence.

PubMed

Morris, J A

1999-08-01

A model is proposed in which information from the environment is analysed by complex biological decision-making systems which are highly redundant. A correct response is intelligent behaviour which preserves health; incorrect responses lead to disease. Mutations in genes which code for the redundant systems will accumulate in the genome and impair decision-making. The number of mutant genes will depend upon a balance between the new mutation rate per generation and systems of elimination based on synergistic interaction in redundant systems. This leads to a polygenic pattern of inheritance for intelligence and the common diseases. The model also gives a simple explanation for some of the hitherto puzzling aspects of work on the genetic basis of intelligence including the recorded rise in IQ this century. There is a prediction that health, intelligence and socio-economic position will be correlated generating a health differential in the social hierarchy. Furthermore, highly competitive societies will place those least able to cope in the harshest environment and this will impair health overall. The model points to a need for population monitoring of somatic mutation in order to preserve the health and intelligence of future generations.

Towards a unifying basis of auditory thresholds: binaural summation.

PubMed

Heil, Peter

2014-04-01

Absolute auditory threshold decreases with increasing sound duration, a phenomenon explainable by the assumptions that the sound evokes neural events whose probabilities of occurrence are proportional to the sound's amplitude raised to an exponent of about 3 and that a constant number of events are required for threshold (Heil and Neubauer, Proc Natl Acad Sci USA 100:6151-6156, 2003). Based on this probabilistic model and on the assumption of perfect binaural summation, an equation is derived here that provides an explicit expression of the binaural threshold as a function of the two monaural thresholds, irrespective of whether they are equal or unequal, and of the exponent in the model. For exponents >0, the predicted binaural advantage is largest when the two monaural thresholds are equal and decreases towards zero as the monaural threshold difference increases. This equation is tested and the exponent derived by comparing binaural thresholds with those predicted on the basis of the two monaural thresholds for different values of the exponent. The thresholds, measured in a large sample of human subjects with equal and unequal monaural thresholds and for stimuli with different temporal envelopes, are compatible only with an exponent close to 3. An exponent of 3 predicts a binaural advantage of 2 dB when the two ears are equally sensitive. Thus, listening with two (equally sensitive) ears rather than one has the same effect on absolute threshold as doubling duration. The data suggest that perfect binaural summation occurs at threshold and that peripheral neural signals are governed by an exponent close to 3. They might also shed new light on mechanisms underlying binaural summation of loudness.

[Genetics of congenital heart diseases].

PubMed

Bonnet, Damien

2017-06-01

Developmental genetics of congenital heart diseases has evolved from analysis of serial slices in embryos towards molecular genetics of cardiac morphogenesis with a dynamic view of cardiac development. Genetics of congenital heart diseases has also changed from formal genetic analysis of familial recurrences or population-based analysis to screening for mutations in candidates genes identified in animal models. Close cooperation between molecular embryologists, pathologists involved in heart development and pediatric cardiologists is crucial for further increase of knowledge in the field of cardiac morphogenesis and genetics of cardiac defects. The genetic model for congenital heart disease has to be revised to favor a polygenic origin rather than a monogenic one. The main mechanism is altered genic dosage that can account for heart diseases in chromosomal anomalies as well as in point mutations in syndromic and isolated congenital heart diseases. The use of big data grouping information from cardiac development, interactions between genes and proteins, epigenetic factors such as chromatin remodeling or DNA methylation is the current source for improving our knowledge in the field and to give clues for future therapies. Copyright © 2017 Elsevier Masson SAS. All rights reserved.

Genetic heterogeneity of skin microvasculature

PubMed Central

Liu, Fang; Smith, Jason; Zhang, Zhen; Cole, Richard; Herron, Bruce J

2010-01-01

Angiogenesis, the formation of new blood vessels from existing vasculature, is a complex process that is essential for normal embryonic development. Current models for experimental evaluation of angiogenesis often use tissue from large vessels like the aorta and umbilical vein, which are phenotypically distinct from microvasculature. We demonstrate that the utilization of skin to measure microvascular angiogenesis in embryonic and adult tissues is an efficient way to quantify microvasculature angiogenesis. We validate this approach and demonstrate its added value by showing significant differences in angiogenesis in monogenic and polygenic mouse models. We discovered that the pattern of angiogenic response among inbred mouse strains in this ex vivo assay differ from the strain distributions of previous in vivo angiogenesis assays. The difference between the ex vivo and in vivo assays may be related to systemic factors present in whole animals. Expression analysis of cultured skin biopsies from strains of mice with opposing angiogenic response were performed to identify pathways that contribute to differential angiogenic response. Increased expression of negative regulators of angiogenesis in C57Bl/6J mice was associated with lower growth rates. PMID:20170648

Genomic relationships based on X chromosome markers and accuracy of genomic predictions with and without X chromosome markers

PubMed Central

2014-01-01

Background Although the X chromosome is the second largest bovine chromosome, markers on the X chromosome are not used for genomic prediction in some countries and populations. In this study, we presented a method for computing genomic relationships using X chromosome markers, investigated the accuracy of imputation from a low density (7K) to the 54K SNP (single nucleotide polymorphism) panel, and compared the accuracy of genomic prediction with and without using X chromosome markers. Methods The impact of considering X chromosome markers on prediction accuracy was assessed using data from Nordic Holstein bulls and different sets of SNPs: (a) the 54K SNPs for reference and test animals, (b) SNPs imputed from the 7K to the 54K SNP panel for test animals, (c) SNPs imputed from the 7K to the 54K panel for half of the reference animals, and (d) the 7K SNP panel for all animals. Beagle and Findhap were used for imputation. GBLUP (genomic best linear unbiased prediction) models with or without X chromosome markers and with or without a residual polygenic effect were used to predict genomic breeding values for 15 traits. Results Averaged over the two imputation datasets, correlation coefficients between imputed and true genotypes for autosomal markers, pseudo-autosomal markers, and X-specific markers were 0.971, 0.831 and 0.935 when using Findhap, and 0.983, 0.856 and 0.937 when using Beagle. Estimated reliabilities of genomic predictions based on the imputed datasets using Findhap or Beagle were very close to those using the real 54K data. Genomic prediction using all markers gave slightly higher reliabilities than predictions without X chromosome markers. Based on our data which included only bulls, using a G matrix that accounted for sex-linked relationships did not improve prediction, compared with a G matrix that did not account for sex-linked relationships. A model that included a polygenic effect did not recover the loss of prediction accuracy from exclusion of X chromosome markers. Conclusions The results from this study suggest that markers on the X chromosome contribute to accuracy of genomic predictions and should be used for routine genomic evaluation. PMID:25080199

Uncovering state-dependent relationships in shallow lakes using Bayesian latent variable regression.

PubMed

Vitense, Kelsey; Hanson, Mark A; Herwig, Brian R; Zimmer, Kyle D; Fieberg, John

2018-03-01

Ecosystems sometimes undergo dramatic shifts between contrasting regimes. Shallow lakes, for instance, can transition between two alternative stable states: a clear state dominated by submerged aquatic vegetation and a turbid state dominated by phytoplankton. Theoretical models suggest that critical nutrient thresholds differentiate three lake types: highly resilient clear lakes, lakes that may switch between clear and turbid states following perturbations, and highly resilient turbid lakes. For effective and efficient management of shallow lakes and other systems, managers need tools to identify critical thresholds and state-dependent relationships between driving variables and key system features. Using shallow lakes as a model system for which alternative stable states have been demonstrated, we developed an integrated framework using Bayesian latent variable regression (BLR) to classify lake states, identify critical total phosphorus (TP) thresholds, and estimate steady state relationships between TP and chlorophyll a (chl a) using cross-sectional data. We evaluated the method using data simulated from a stochastic differential equation model and compared its performance to k-means clustering with regression (KMR). We also applied the framework to data comprising 130 shallow lakes. For simulated data sets, BLR had high state classification rates (median/mean accuracy >97%) and accurately estimated TP thresholds and state-dependent TP-chl a relationships. Classification and estimation improved with increasing sample size and decreasing noise levels. Compared to KMR, BLR had higher classification rates and better approximated the TP-chl a steady state relationships and TP thresholds. We fit the BLR model to three different years of empirical shallow lake data, and managers can use the estimated bifurcation diagrams to prioritize lakes for management according to their proximity to thresholds and chance of successful rehabilitation. Our model improves upon previous methods for shallow lakes because it allows classification and regression to occur simultaneously and inform one another, directly estimates TP thresholds and the uncertainty associated with thresholds and state classifications, and enables meaningful constraints to be built into models. The BLR framework is broadly applicable to other ecosystems known to exhibit alternative stable states in which regression can be used to establish relationships between driving variables and state variables. © 2017 by the Ecological Society of America.

Modeling Randomness in Judging Rating Scales with a Random-Effects Rating Scale Model

ERIC Educational Resources Information Center

Wang, Wen-Chung; Wilson, Mark; Shih, Ching-Lin

2006-01-01

This study presents the random-effects rating scale model (RE-RSM) which takes into account randomness in the thresholds over persons by treating them as random-effects and adding a random variable for each threshold in the rating scale model (RSM) (Andrich, 1978). The RE-RSM turns out to be a special case of the multidimensional random…

Structure, Function, and Applications of the Georgetown-Einstein (GE) Breast Cancer Simulation Model.

PubMed

Schechter, Clyde B; Near, Aimee M; Jayasekera, Jinani; Chandler, Young; Mandelblatt, Jeanne S

2018-04-01

The Georgetown University-Albert Einstein College of Medicine breast cancer simulation model (Model GE) has evolved over time in structure and function to reflect advances in knowledge about breast cancer, improvements in early detection and treatment technology, and progress in computing resources. This article describes the model and provides examples of model applications. The model is a discrete events microsimulation of single-life histories of women from multiple birth cohorts. Events are simulated in the absence of screening and treatment, and interventions are then applied to assess their impact on population breast cancer trends. The model accommodates differences in natural history associated with estrogen receptor (ER) and human epidermal growth factor receptor 2 (HER2) biomarkers, as well as conventional breast cancer risk factors. The approach for simulating breast cancer natural history is phenomenological, relying on dates, stage, and age of clinical and screen detection for a tumor molecular subtype without explicitly modeling tumor growth. The inputs to the model are regularly updated to reflect current practice. Numerous technical modifications, including the use of object-oriented programming (C++), and more efficient algorithms, along with hardware advances, have increased program efficiency permitting simulations of large samples. The model results consistently match key temporal trends in US breast cancer incidence and mortality. The model has been used in collaboration with other CISNET models to assess cancer control policies and will be applied to evaluate clinical trial design, recurrence risk, and polygenic risk-based screening.

Spike-Threshold Adaptation Predicted by Membrane Potential Dynamics In Vivo

PubMed Central

Fontaine, Bertrand; Peña, José Luis; Brette, Romain

2014-01-01

Neurons encode information in sequences of spikes, which are triggered when their membrane potential crosses a threshold. In vivo, the spiking threshold displays large variability suggesting that threshold dynamics have a profound influence on how the combined input of a neuron is encoded in the spiking. Threshold variability could be explained by adaptation to the membrane potential. However, it could also be the case that most threshold variability reflects noise and processes other than threshold adaptation. Here, we investigated threshold variation in auditory neurons responses recorded in vivo in barn owls. We found that spike threshold is quantitatively predicted by a model in which the threshold adapts, tracking the membrane potential at a short timescale. As a result, in these neurons, slow voltage fluctuations do not contribute to spiking because they are filtered by threshold adaptation. More importantly, these neurons can only respond to input spikes arriving together on a millisecond timescale. These results demonstrate that fast adaptation to the membrane potential captures spike threshold variability in vivo. PMID:24722397

Effect of microgravity on visual contrast threshold during STS Shuttle missions: Visual Function Tester-Model 2 (VFT-2)

NASA Technical Reports Server (NTRS)

Oneal, Melvin R.; Task, H. Lee; Genco, Louis V.

1992-01-01

Viewgraphs on effect of microgravity on visual contrast threshold during STS shuttle missions are presented. The purpose, methods, and results are discussed. The visual function tester model 2 is used.

An analytical prediction of the oscillation and extinction thresholds of a clarinet

NASA Astrophysics Data System (ADS)

Dalmont, Jean-Pierre; Gilbert, Joël; Kergomard, Jean; Ollivier, Sébastien

2005-11-01

This paper investigates the dynamic range of the clarinet from the oscillation threshold to the extinction at high pressure level. The use of an elementary model for the reed-mouthpiece valve effect combined with a simplified model of the pipe assuming frequency independent losses (Raman's model) allows an analytical calculation of the oscillations and their stability analysis. The different thresholds are shown to depend on parameters related to embouchure parameters and to the absorption coefficient in the pipe. Their values determine the dynamic range of the fundamental oscillations and the bifurcation scheme at the extinction.

Visible lesion thresholds and model predictions for Q-switched 1318-nm and 1540-nm laser exposures to porcine skin

NASA Astrophysics Data System (ADS)

Zohner, Justin J.; Schuster, Kurt J.; Chavey, Lucas J.; Stolarski, David J.; Kumru, Semih S.; Rockwell, Benjamin A.; Thomas, Robert J.; Cain, Clarence P.

2006-02-01

Skin damage thresholds were measured and compared with theoretical predictions using a skin thermal model for near-IR laser pulses at 1318 nm and 1540 nm. For the 1318-nm data, a Q-switched, 50-ns pulse with a spot size of 5 mm was applied to porcine skin and the damage thresholds were determined at 1 hour and 24 hours postexposure using Probit analysis. The same analysis was conducted for a Q-switched, 30-ns pulse at 1540 nm with a spot size of 5 mm. The Yucatan mini-pig was used as the skin model for human skin due to its similarity to pigmented human skin. The ED 50 for these skin exposures at 24 hours postexposure was 10.5 J/cm2 for the 1318-nm exposures, and 6.1 J/cm2 for the 1540-nm exposures. These results were compared to thermal model predictions. We show that the thermal model fails to account for the ED 50 values observed. A brief discussion of the possible causes of this discrepancy is presented. These thresholds are also compared with previously published skin minimum visible lesion (MVL) thresholds and with the ANSI Standard's MPE for 1318-nm lasers at 50 ns and 1540-nm lasers at 30 ns.

Influence of arousal threshold and depth of sleep on respiratory stability in man: analysis using a mathematical model.

PubMed

Longobardo, G S; Evangelisti, C J; Cherniack, N S

2009-12-01

We examined the effect of arousals (shifts from sleep to wakefulness) on breathing during sleep using a mathematical model. The model consisted of a description of the fluid dynamics and mechanical properties of the upper airways and lungs, as well as a controller sensitive to arterial and brain changes in CO(2), changes in arterial oxygen, and a neural input, alertness. The body was divided into multiple gas store compartments connected by the circulation. Cardiac output was constant, and cerebral blood flows were sensitive to changes in O(2) and CO(2) levels. Arousal was considered to occur instantaneously when afferent respiratory chemical and neural stimulation reached a threshold value, while sleep occurred when stimulation fell below that value. In the case of rigid and nearly incompressible upper airways, lowering arousal threshold decreased the stability of breathing and led to the occurrence of repeated apnoeas. In more compressible upper airways, to maintain stability, increasing arousal thresholds and decreasing elasticity were linked approximately linearly, until at low elastances arousal thresholds had no effect on stability. Increased controller gain promoted instability. The architecture of apnoeas during unstable sleep changed with the arousal threshold and decreases in elasticity. With rigid airways, apnoeas were central. With lower elastances, apnoeas were mixed even with higher arousal thresholds. With very low elastances and still higher arousal thresholds, sleep consisted totally of obstructed apnoeas. Cycle lengths shortened as the sleep architecture changed from mixed apnoeas to total obstruction. Deeper sleep also tended to promote instability by increasing plant gain. These instabilities could be countered by arousal threshold increases which were tied to deeper sleep or accumulated aroused time, or by decreased controller gains.

Dual processing model of medical decision-making

PubMed Central

2012-01-01

Background Dual processing theory of human cognition postulates that reasoning and decision-making can be described as a function of both an intuitive, experiential, affective system (system I) and/or an analytical, deliberative (system II) processing system. To date no formal descriptive model of medical decision-making based on dual processing theory has been developed. Here we postulate such a model and apply it to a common clinical situation: whether treatment should be administered to the patient who may or may not have a disease. Methods We developed a mathematical model in which we linked a recently proposed descriptive psychological model of cognition with the threshold model of medical decision-making and show how this approach can be used to better understand decision-making at the bedside and explain the widespread variation in treatments observed in clinical practice. Results We show that physician’s beliefs about whether to treat at higher (lower) probability levels compared to the prescriptive therapeutic thresholds obtained via system II processing is moderated by system I and the ratio of benefit and harms as evaluated by both system I and II. Under some conditions, the system I decision maker’s threshold may dramatically drop below the expected utility threshold derived by system II. This can explain the overtreatment often seen in the contemporary practice. The opposite can also occur as in the situations where empirical evidence is considered unreliable, or when cognitive processes of decision-makers are biased through recent experience: the threshold will increase relative to the normative threshold value derived via system II using expected utility threshold. This inclination for the higher diagnostic certainty may, in turn, explain undertreatment that is also documented in the current medical practice. Conclusions We have developed the first dual processing model of medical decision-making that has potential to enrich the current medical decision-making field, which is still to the large extent dominated by expected utility theory. The model also provides a platform for reconciling two groups of competing dual processing theories (parallel competitive with default-interventionalist theories). PMID:22943520

Cross-validation analysis for genetic evaluation models for ranking in endurance horses.

PubMed

García-Ballesteros, S; Varona, L; Valera, M; Gutiérrez, J P; Cervantes, I

2018-01-01

Ranking trait was used as a selection criterion for competition horses to estimate racing performance. In the literature the most common approaches to estimate breeding values are the linear or threshold statistical models. However, recent studies have shown that a Thurstonian approach was able to fix the race effect (competitive level of the horses that participate in the same race), thus suggesting a better prediction accuracy of breeding values for ranking trait. The aim of this study was to compare the predictability of linear, threshold and Thurstonian approaches for genetic evaluation of ranking in endurance horses. For this purpose, eight genetic models were used for each approach with different combinations of random effects: rider, rider-horse interaction and environmental permanent effect. All genetic models included gender, age and race as systematic effects. The database that was used contained 4065 ranking records from 966 horses and that for the pedigree contained 8733 animals (47% Arabian horses), with an estimated heritability around 0.10 for the ranking trait. The prediction ability of the models for racing performance was evaluated using a cross-validation approach. The average correlation between real and predicted performances across genetic models was around 0.25 for threshold, 0.58 for linear and 0.60 for Thurstonian approaches. Although no significant differences were found between models within approaches, the best genetic model included: the rider and rider-horse random effects for threshold, only rider and environmental permanent effects for linear approach and all random effects for Thurstonian approach. The absolute correlations of predicted breeding values among models were higher between threshold and Thurstonian: 0.90, 0.91 and 0.88 for all animals, top 20% and top 5% best animals. For rank correlations these figures were 0.85, 0.84 and 0.86. The lower values were those between linear and threshold approaches (0.65, 0.62 and 0.51). In conclusion, the Thurstonian approach is recommended for the routine genetic evaluations for ranking in endurance horses.

Evaluation of a new model of aeolian transport in the presence of vegetation

USGS Publications Warehouse

Li, Junran; Okin, Gregory S.; Herrick, Jeffrey E.; Belnap, Jayne; Miller, Mark E.; Vest, Kimberly; Draut, Amy E.

2013-01-01

Aeolian transport is an important characteristic of many arid and semiarid regions worldwide that affects dust emission and ecosystem processes. The purpose of this paper is to evaluate a recent model of aeolian transport in the presence of vegetation. This approach differs from previous models by accounting for how vegetation affects the distribution of shear velocity on the surface rather than merely calculating the average effect of vegetation on surface shear velocity or simply using empirical relationships. Vegetation, soil, and meteorological data at 65 field sites with measurements of horizontal aeolian flux were collected from the Western United States. Measured fluxes were tested against modeled values to evaluate model performance, to obtain a set of optimum model parameters, and to estimate the uncertainty in these parameters. The same field data were used to model horizontal aeolian flux using three other schemes. Our results show that the model can predict horizontal aeolian flux with an approximate relative error of 2.1 and that further empirical corrections can reduce the approximate relative error to 1.0. The level of error is within what would be expected given uncertainties in threshold shear velocity and wind speed at our sites. The model outperforms the alternative schemes both in terms of approximate relative error and the number of sites at which threshold shear velocity was exceeded. These results lend support to an understanding of the physics of aeolian transport in which (1) vegetation's impact on transport is dependent upon the distribution of vegetation rather than merely its average lateral cover and (2) vegetation impacts surface shear stress locally by depressing it in the immediate lee of plants rather than by changing the bulk surface's threshold shear velocity. Our results also suggest that threshold shear velocity is exceeded more than might be estimated by single measurements of threshold shear stress and roughness length commonly associated with vegetated surfaces, highlighting the variation of threshold shear velocity with space and time in real landscapes.

Calculation of femtosecond pulse laser induced damage threshold for broadband antireflective microstructure arrays.

PubMed

Jing, Xufeng; Shao, Jianda; Zhang, Junchao; Jin, Yunxia; He, Hongbo; Fan, Zhengxiu

2009-12-21

In order to more exactly predict femtosecond pulse laser induced damage threshold, an accurate theoretical model taking into account photoionization, avalanche ionization and decay of electrons is proposed by comparing respectively several combined ionization models with the published experimental measurements. In addition, the transmittance property and the near-field distribution of the 'moth eye' broadband antireflective microstructure directly patterned into the substrate material as a function of the surface structure period and groove depth are performed by a rigorous Fourier model method. It is found that the near-field distribution is strongly dependent on the periodicity of surface structure for TE polarization, but for TM wave it is insensitive to the period. What's more, the femtosecond pulse laser damage threshold of the surface microstructure on the pulse duration taking into account the local maximum electric field enhancement was calculated using the proposed relatively accurate theoretical ionization model. For the longer incident wavelength of 1064 nm, the weak linear damage threshold on the pulse duration is shown, but there is a surprising oscillation peak of breakdown threshold as a function of the pulse duration for the shorter incident wavelength of 532 nm.

Modelling the effects of cutting off infected branches and replanting on fire-blight transmission using Filippov systems.

PubMed

Chen, Can; Li, Chentong; Kang, Yanmei

2018-02-14

Fire blight is one of the most devastating plant diseases in the world. This paper proposes a Filippov fire-blight model incorporating cutting off infected branches and replanting susceptible trees. The Filippov-type model is formulated by considering that no control strategy is taken if the number of infected trees is less than an infected threshold level I c ; further, we cut off infected branches once the number of infected trees exceeds I c ; meanwhile, we replant trees if the number of susceptible trees is less than a susceptible threshold level S c . The global dynamical behaviour of the Filippov system is investigated. It is shown that model solutions ultimately converge to the positive equilibrium that lies in the region above I c , or below I c , or on I=I c , as we vary the susceptible and infected threshold values S c and I c . Our results indicate that proper combinations of the susceptible and infected threshold values based on the threshold policy can lead the number of infected trees to an acceptable level, when complete eradication is not economically desirable. Copyright © 2017 Elsevier Ltd. All rights reserved.

Effects of moisture content on wind erosion thresholds of biochar

NASA Astrophysics Data System (ADS)

Silva, F. C.; Borrego, C.; Keizer, J. J.; Amorim, J. H.; Verheijen, F. G. A.

2015-12-01

Biochar, i.e. pyrolysed biomass, as a soil conditioner is gaining increasing attention in research and industry, with guidelines and certifications being developed for biochar production, storage and handling, as well as for application to soils. Adding water to biochar aims to reduce its susceptibility to become air-borne during and after the application to soils, thereby preventing, amongst others, human health issues from inhalation. The Bagnold model has previously been modified to explain the threshold friction velocity of coal particles at different moisture contents, by adding an adhesive effect. However, it is unknown if this model also works for biochar particles. We measured the threshold friction velocities of a range of biochar particles (woody feedstock) under a range of moisture contents by using a wind tunnel, and tested the performance of the modified Bagnold model. Results showed that the threshold friction velocity can be significantly increased by keeping the gravimetric moisture content at or above 15% to promote adhesive effects between the small particles. For the specific biochar of this study, the modified Bagnold model accurately estimated threshold friction velocities of biochar particles up to moisture contents of 10%.

Clinical multiple sclerosis occurs at one end of a spectrum of CNS pathology: a modified threshold liability model leads to new ways of thinking about the cause of clinical multiple sclerosis.

PubMed

Haegert, David G

2005-01-01

Multiple sclerosis (MS) is a complex trait, the causes of which are elusive. A threshold liability model influences thinking about the causes of this disorder. According to this model, a population has a normal distribution of genetic liability to MS. In addition, a threshold exists, so that MS begins when an individual's liability exceeds the MS threshold; environmental and other causative factors may increase or decrease an individual's MS liability. It is argued here, however, that this model is misleading, as it is based on the incorrect assumption that MS is a disorder that one either has or does not have. This paper hypothesizes, instead, that patients with a diagnosis of MS share identical CNS pathology, termed MS pathology, with some individuals who have a diagnosis of possible MS and with some apparently healthy individuals, who may never have a diagnosis of MS. In order to accommodate this hypothesis, the current threshold liability model is modified as follows. (1) In addition to a normal distribution of MS liability within a population, a spectrum of MS pathology occurs in some who have a high MS liability. (2) A clinical MS threshold exists at a point on this liability distribution, where the burden and distribution of MS pathology permits a diagnosis of clinical MS. (3) Additional thresholds exist that correspond to a lower MS liability and a lesser burden of MS pathology than occur at the clinical MS threshold. This modified threshold model leads to the postulate that causes act at various time points to increase MS liability and induce MS pathology. The accumulation of MS pathology sometimes leads to a diagnosis of clinical MS. One implication of this model is that the MS pathology in clinical MS and in some with possible MS differs only in the extent but not in the type of CNS injury. Thus, it may be possible to obtain insight into the causative environmental factors that increase MS liability and induce MS pathology by focusing on patients who have clinical MS; some environmental factors that induce new lesions in patients with clinical MS may be identical to those that induce MS pathology in genetically susceptible individuals who do not have clinical MS. Identification of these causative factors has importance, as specific treatment may prevent the accumulation of MS pathology that leads to the significant CNS damage associated with clinical MS.

Stable Extraction of Threshold Voltage Using Transconductance Change Method for CMOS Modeling, Simulation and Characterization

NASA Astrophysics Data System (ADS)

Choi, Woo Young; Woo, Dong-Soo; Choi, Byung Yong; Lee, Jong Duk; Park, Byung-Gook

2004-04-01

We proposed a stable extraction algorithm for threshold voltage using transconductance change method by optimizing node interval. With the algorithm, noise-free gm2 (=dgm/dVGS) profiles can be extracted within one-percent error, which leads to more physically-meaningful threshold voltage calculation by the transconductance change method. The extracted threshold voltage predicts the gate-to-source voltage at which the surface potential is within kT/q of φs=2φf+VSB. Our algorithm makes the transconductance change method more practical by overcoming noise problem. This threshold voltage extraction algorithm yields the threshold roll-off behavior of nanoscale metal oxide semiconductor field effect transistor (MOSFETs) accurately and makes it possible to calculate the surface potential φs at any other point on the drain-to-source current (IDS) versus gate-to-source voltage (VGS) curve. It will provide us with a useful analysis tool in the field of device modeling, simulation and characterization.

Estimating Alarm Thresholds for Process Monitoring Data under Different Assumptions about the Data Generating Mechanism

DOE PAGES

Burr, Tom; Hamada, Michael S.; Howell, John; ...

2013-01-01

Process monitoring (PM) for nuclear safeguards sometimes requires estimation of thresholds corresponding to small false alarm rates. Threshold estimation dates to the 1920s with the Shewhart control chart; however, because possible new roles for PM are being evaluated in nuclear safeguards, it is timely to consider modern model selection options in the context of threshold estimation. One of the possible new PM roles involves PM residuals, where a residual is defined as residual = data − prediction. This paper reviews alarm threshold estimation, introduces model selection options, and considers a range of assumptions regarding the data-generating mechanism for PM residuals.more » Two PM examples from nuclear safeguards are included to motivate the need for alarm threshold estimation. The first example involves mixtures of probability distributions that arise in solution monitoring, which is a common type of PM. The second example involves periodic partial cleanout of in-process inventory, leading to challenging structure in the time series of PM residuals.« less

Threshold concepts in finance: conceptualizing the curriculum

NASA Astrophysics Data System (ADS)

Hoadley, Susan; Tickle, Leonie; Wood, Leigh N.; Kyng, Tim

2015-08-01

Graduates with well-developed capabilities in finance are invaluable to our society and in increasing demand. Universities face the challenge of designing finance programmes to develop these capabilities and the essential knowledge that underpins them. Our research responds to this challenge by identifying threshold concepts that are central to the mastery of finance and by exploring their potential for informing curriculum design and pedagogical practices to improve student outcomes. In this paper, we report the results of an online survey of finance academics at multiple institutions in Australia, Canada, New Zealand, South Africa and the United Kingdom. The outcomes of our research are recommendations for threshold concepts in finance endorsed by quantitative evidence, as well as a model of the finance curriculum incorporating finance, modelling and statistics threshold concepts. In addition, we draw conclusions about the application of threshold concept theory supported by both quantitative and qualitative evidence. Our methodology and findings have general relevance to the application of threshold concept theory as a means to investigate and inform curriculum design and delivery in higher education.

Self-dual random-plaquette gauge model and the quantum toric code

NASA Astrophysics Data System (ADS)

Takeda, Koujin; Nishimori, Hidetoshi

2004-05-01

We study the four-dimensional Z2 random-plaquette lattice gauge theory as a model of topological quantum memory, the toric code in particular. In this model, the procedure of quantum error correction works properly in the ordered (Higgs) phase, and phase boundary between the ordered (Higgs) and disordered (confinement) phases gives the accuracy threshold of error correction. Using self-duality of the model in conjunction with the replica method, we show that this model has exactly the same mathematical structure as that of the two-dimensional random-bond Ising model, which has been studied very extensively. This observation enables us to derive a conjecture on the exact location of the multicritical point (accuracy threshold) of the model, pc=0.889972…, and leads to several nontrivial results including bounds on the accuracy threshold in three dimensions.

The threshold of a stochastic SIQS epidemic model

NASA Astrophysics Data System (ADS)

Zhang, Xiao-Bing; Huo, Hai-Feng; Xiang, Hong; Shi, Qihong; Li, Dungang

2017-09-01

In this paper, we present the threshold of a stochastic SIQS epidemic model which determines the extinction and persistence of the disease. Furthermore, we find that noise can suppress the disease outbreak. Numerical simulations are also carried out to confirm the analytical results.

Genetic parameters for direct and maternal calving ease in Walloon dairy cattle based on linear and threshold models.

PubMed

Vanderick, S; Troch, T; Gillon, A; Glorieux, G; Gengler, N

2014-12-01

Calving ease scores from Holstein dairy cattle in the Walloon Region of Belgium were analysed using univariate linear and threshold animal models. Variance components and derived genetic parameters were estimated from a data set including 33,155 calving records. Included in the models were season, herd and sex of calf × age of dam classes × group of calvings interaction as fixed effects, herd × year of calving, maternal permanent environment and animal direct and maternal additive genetic as random effects. Models were fitted with the genetic correlation between direct and maternal additive genetic effects either estimated or constrained to zero. Direct heritability for calving ease was approximately 8% with linear models and approximately 12% with threshold models. Maternal heritabilities were approximately 2 and 4%, respectively. Genetic correlation between direct and maternal additive effects was found to be not significantly different from zero. Models were compared in terms of goodness of fit and predictive ability. Criteria of comparison such as mean squared error, correlation between observed and predicted calving ease scores as well as between estimated breeding values were estimated from 85,118 calving records. The results provided few differences between linear and threshold models even though correlations between estimated breeding values from subsets of data for sires with progeny from linear model were 17 and 23% greater for direct and maternal genetic effects, respectively, than from threshold model. For the purpose of genetic evaluation for calving ease in Walloon Holstein dairy cattle, the linear animal model without covariance between direct and maternal additive effects was found to be the best choice. © 2014 Blackwell Verlag GmbH.

Optimization of artificial neural network models through genetic algorithms for surface ozone concentration forecasting.

PubMed

Pires, J C M; Gonçalves, B; Azevedo, F G; Carneiro, A P; Rego, N; Assembleia, A J B; Lima, J F B; Silva, P A; Alves, C; Martins, F G

2012-09-01

This study proposes three methodologies to define artificial neural network models through genetic algorithms (GAs) to predict the next-day hourly average surface ozone (O(3)) concentrations. GAs were applied to define the activation function in hidden layer and the number of hidden neurons. Two of the methodologies define threshold models, which assume that the behaviour of the dependent variable (O(3) concentrations) changes when it enters in a different regime (two and four regimes were considered in this study). The change from one regime to another depends on a specific value (threshold value) of an explanatory variable (threshold variable), which is also defined by GAs. The predictor variables were the hourly average concentrations of carbon monoxide (CO), nitrogen oxide, nitrogen dioxide (NO(2)), and O(3) (recorded in the previous day at an urban site with traffic influence) and also meteorological data (hourly averages of temperature, solar radiation, relative humidity and wind speed). The study was performed for the period from May to August 2004. Several models were achieved and only the best model of each methodology was analysed. In threshold models, the variables selected by GAs to define the O(3) regimes were temperature, CO and NO(2) concentrations, due to their importance in O(3) chemistry in an urban atmosphere. In the prediction of O(3) concentrations, the threshold model that considers two regimes was the one that fitted the data most efficiently.

Computational methods using genome-wide association studies to predict radiotherapy complications and to identify correlative molecular processes

NASA Astrophysics Data System (ADS)

Oh, Jung Hun; Kerns, Sarah; Ostrer, Harry; Powell, Simon N.; Rosenstein, Barry; Deasy, Joseph O.

2017-02-01

The biological cause of clinically observed variability of normal tissue damage following radiotherapy is poorly understood. We hypothesized that machine/statistical learning methods using single nucleotide polymorphism (SNP)-based genome-wide association studies (GWAS) would identify groups of patients of differing complication risk, and furthermore could be used to identify key biological sources of variability. We developed a novel learning algorithm, called pre-conditioned random forest regression (PRFR), to construct polygenic risk models using hundreds of SNPs, thereby capturing genomic features that confer small differential risk. Predictive models were trained and validated on a cohort of 368 prostate cancer patients for two post-radiotherapy clinical endpoints: late rectal bleeding and erectile dysfunction. The proposed method results in better predictive performance compared with existing computational methods. Gene ontology enrichment analysis and protein-protein interaction network analysis are used to identify key biological processes and proteins that were plausible based on other published studies. In conclusion, we confirm that novel machine learning methods can produce large predictive models (hundreds of SNPs), yielding clinically useful risk stratification models, as well as identifying important underlying biological processes in the radiation damage and tissue repair process. The methods are generally applicable to GWAS data and are not specific to radiotherapy endpoints.

Relationships between host viremia and vector susceptibility for arboviruses.

PubMed

Lord, Cynthia C; Rutledge, C Roxanne; Tabachnick, Walter J

2006-05-01

Using a threshold model where a minimum level of host viremia is necessary to infect vectors affects our assessment of the relative importance of different host species in the transmission and spread of these pathogens. Other models may be more accurate descriptions of the relationship between host viremia and vector infection. Under the threshold model, the intensity and duration of the viremia above the threshold level is critical in determining the potential numbers of infected mosquitoes. A probabilistic model relating host viremia to the probability distribution of virions in the mosquito bloodmeal shows that the threshold model will underestimate the significance of hosts with low viremias. A probabilistic model that includes avian mortality shows that the maximum number of mosquitoes is infected by feeding on hosts whose viremia peaks just below the lethal level. The relationship between host viremia and vector infection is complex, and there is little experimental information to determine the most accurate model for different arthropod-vector-host systems. Until there is more information, the ability to distinguish the relative importance of different hosts in infecting vectors will remain problematic. Relying on assumptions with little support may result in erroneous conclusions about the importance of different hosts.

Relationships Between Host Viremia and Vector Susceptibility for Arboviruses

PubMed Central

Lord, Cynthia C.; Rutledge, C. Roxanne; Tabachnick, Walter J.

2010-01-01

Using a threshold model where a minimum level of host viremia is necessary to infect vectors affects our assessment of the relative importance of different host species in the transmission and spread of these pathogens. Other models may be more accurate descriptions of the relationship between host viremia and vector infection. Under the threshold model, the intensity and duration of the viremia above the threshold level is critical in determining the potential numbers of infected mosquitoes. A probabilistic model relating host viremia to the probability distribution of virions in the mosquito bloodmeal shows that the threshold model will underestimate the significance of hosts with low viremias. A probabilistic model that includes avian mortality shows that the maximum number of mosquitoes is infected by feeding on hosts whose viremia peaks just below the lethal level. The relationship between host viremia and vector infection is complex, and there is little experimental information to determine the most accurate model for different arthropod–vector–host systems. Until there is more information, the ability to distinguish the relative importance of different hosts in infecting vectors will remain problematic. Relying on assumptions with little support may result in erroneous conclusions about the importance of different hosts. PMID:16739425

Understanding the trends in HIV and hepatitis C prevalence amongst injecting drug users in different settings--implications for intervention impact.

PubMed

Vickerman, Peter; Martin, Natasha K; Hickman, Matthew

2012-06-01

A recent systematic review observed that HIV prevalence amongst injectors is negligible (<1%) below a threshold HCV prevalence of 30%, but thereafter increases with HCV prevalence. We explore whether a model can reproduce these trends, what determines different epidemiological profiles and how this affects intervention impact. An HIV/HCV transmission model was developed. Univariate sensitivity analyses determined whether the model projected a HCV prevalence threshold below which HIV is negligible, and how different behavioural and epidemiological factors affect the threshold. Multivariate uncertainty analyses considered whether the model could reproduce the observed breadth of HIV/HCV epidemics, how specific behavioural patterns produce different epidemic profiles, and how this affects an intervention's impact (reduces injecting risk by 30%). The model projected a HCV prevalence threshold, which varied depending on the heterogeneity in risk, mixing, and injecting duration in a setting. Multivariate uncertainty analyses showed the model could produce the same range of observed HIV/HCV epidemics. Variability in injecting transmission risk, degree of heterogeneity and injecting duration mainly determined different epidemic profiles. The intervention resulted in 50%/28% reduction in HIV incidence/prevalence and 37%/10% reduction in HCV incidence/prevalence over five years. For either infection, greater impact occurred in settings with lower prevalence of that infection and higher prevalence of the other infection. There are threshold levels of HCV prevalence below which HIV risk is negligible but these thresholds are likely to vary by setting. A setting's HIV and HCV prevalence may give insights into IDU risk behaviour and intervention impact. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

Cognitive and Neural Bases of Skilled Performance.

DTIC Science & Technology

1987-10-04

advantage is that this method is not computationally demanding, and model -specific analyses such as high -precision source localization with realistic...and a two- < " high -threshold model satisfy theoretical and pragmatic independence. Discrimination and bias measures from these two models comparing...recognition memory of patients with dementing diseases, amnesics, and normal controls. We found the two- high -threshold model to be more sensitive Lloyd

An in vitro Corneal Model with a Laser Damage Threshold at 2 Micrometers That is Similar to That in the Rabbit

DTIC Science & Technology

2007-11-01

Proceedings 3. DATES COVERED (From - To) June 2007- November 2007 4. TITLE AND SUBTITLE An In Vitro Corneal Model with a Laser Damage Threshold at 2...2-µm wavelength output of a thulium fiber laser with 4 mm beam diameter for 0.25 seconds in a thermally controlled environment and then assayed for...data in the literature. 15. SUBJECT TERMS corneal organotypic culture, laser , threshold, thermography, Probit 16. SECURITY CLASSIFICATION OF

Optical Associative Memory Model With Threshold Modification Using Complementary Vector

NASA Astrophysics Data System (ADS)

Bian, Shaoping; Xu, Kebin; Hong, Jing

1989-02-01

A new criterion to evaluate the similarity between two vectors in associative memory is presented. According to it, an experimental research about optical associative memory model with threshold modification using complementary vector is carried out. This model is capable of eliminating the posibility to recall erroneously. Therefore the accuracy of reading out is improved.