Multivariate genetic architecture of the Anolis dewlap reveals both shared and sex-specific features of a sexually dimorphic ornament.

PubMed

Cox, R M; Costello, R A; Camber, B E; McGlothlin, J W

2017-07-01

Darwin viewed the ornamentation of females as an indirect consequence of sexual selection on males and the transmission of male phenotypes to females via the 'laws of inheritance'. Although a number of studies have supported this view by demonstrating substantial between-sex genetic covariance for ornament expression, the majority of this work has focused on avian plumage. Moreover, few studies have considered the genetic basis of ornaments from a multivariate perspective, which may be crucial for understanding the evolution of sex differences in general, and of complex ornaments in particular. Here, we provide a multivariate, quantitative-genetic analysis of a sexually dimorphic ornament that has figured prominently in studies of sexual selection: the brightly coloured dewlap of Anolis lizards. Using data from a paternal half-sibling breeding experiment in brown anoles (Anolis sagrei), we show that multiple aspects of dewlap size and colour exhibit significant heritability and a genetic variance-covariance structure (G) that is broadly similar in males (G m ) and females (G f ). Whereas sexually monomorphic aspects of the dewlap, such as hue, exhibit significant between-sex genetic correlations (r mf ), sexually dimorphic features, such as area and brightness, exhibit reduced r mf values that do not differ from zero. Using a modified random skewers analysis, we show that the between-sex genetic variance-covariance matrix (B) should not strongly constrain the independent responses of males and females to sexually antagonistic selection. Our microevolutionary analysis is in broad agreement with macroevolutionary perspectives indicating considerable scope for the independent evolution of coloration and ornamentation in males and females. © 2017 European Society For Evolutionary Biology. Journal of Evolutionary Biology © 2017 European Society For Evolutionary Biology.

Common Aetiology for Diverse Language Skills in 4 1/2-Year-Old Twins

ERIC Educational Resources Information Center

Hayiou-Thomas, Marianna E.; Kovas, Yulia; Harlaar, Nicole; Plomin, Robert; Bishop, Dorothy V. M.; Dale, Philip S.

2006-01-01

Multivariate genetic analysis was used to examine the genetic and environmental aetiology of the interrelationships of diverse linguistic skills. This study used data from a large sample of 4 1/2-year-old twins who were tested on measures assessing articulation, phonology, grammar, vocabulary, and verbal memory. Phenotypic analysis suggested two…

Evaluation of genetic diversity among soybean (Glycine max) genotypes using univariate and multivariate analysis.

PubMed

Oliveira, M M; Sousa, L B; Reis, M C; Silva Junior, E G; Cardoso, D B O; Hamawaki, O T; Nogueira, A P O

2017-05-31

The genetic diversity study has paramount importance in breeding programs; hence, it allows selection and choice of the parental genetic divergence, which have the agronomic traits desired by the breeder. This study aimed to characterize the genetic divergence between 24 soybean genotypes through their agronomic traits, using multivariate clustering methods to select the potential genitors for the promising hybrid combinations. Six agronomic traits evaluated were number of days to flowering and maturity, plant height at flowering and maturity, insertion height of the first pod, and yield. The genetic divergence evaluated by multivariate analysis that esteemed first the Mahalanobis' generalized distance (D 2 ), then the clustering using Tocher's optimization methods, and then the unweighted pair group method with arithmetic average (UPGMA). Tocher's optimization method and the UPGMA agreed with the groups' constitution between each other, the formation of eight distinct groups according Tocher's method and seven distinct groups using UPGMA. The trait number of days for flowering (45.66%) was the most efficient to explain dissimilarity between genotypes, and must be one of the main traits considered by the breeder in the moment of genitors choice in soybean-breeding programs. The genetic variability allowed the identification of dissimilar genotypes and with superior performances. The hybridizations UFU 18 x UFUS CARAJÁS, UFU 15 x UFU 13, and UFU 13 x UFUS CARAJÁS are promising to obtain superior segregating populations, which enable the development of more productive genotypes.

Genetic and Environmental Influences on Female Sexual Orientation, Childhood Gender Typicality and Adult Gender Identity

PubMed Central

Burri, Andrea; Cherkas, Lynn; Spector, Timothy; Rahman, Qazi

2011-01-01

Background Human sexual orientation is influenced by genetic and non-shared environmental factors as are two important psychological correlates – childhood gender typicality (CGT) and adult gender identity (AGI). However, researchers have been unable to resolve the genetic and non-genetic components that contribute to the covariation between these traits, particularly in women. Methodology/Principal Findings Here we performed a multivariate genetic analysis in a large sample of British female twins (N = 4,426) who completed a questionnaire assessing sexual attraction, CGT and AGI. Univariate genetic models indicated modest genetic influences on sexual attraction (25%), AGI (11%) and CGT (31%). For the multivariate analyses, a common pathway model best fitted the data. Conclusions/Significance This indicated that a single latent variable influenced by a genetic component and common non-shared environmental component explained the association between the three traits but there was substantial measurement error. These findings highlight common developmental factors affecting differences in sexual orientation. PMID:21760939

"Generalist Genes" and Mathematics in 7-Year-Old Twins

ERIC Educational Resources Information Center

Kovas, Y.; Harlaar, N.; Petrill, S. A.; Plomin, R.

2005-01-01

Mathematics performance at 7 years as assessed by teachers using UK national curriculum criteria has been found to be highly heritable. For almost 3000 pairs of 7-year-old same-sex twins, we used multivariate genetic analysis to investigate the extent to which these genetic effects on mathematics performance overlap with genetic effects on reading…

Applications of modern statistical methods to analysis of data in physical science

NASA Astrophysics Data System (ADS)

Wicker, James Eric

Modern methods of statistical and computational analysis offer solutions to dilemmas confronting researchers in physical science. Although the ideas behind modern statistical and computational analysis methods were originally introduced in the 1970's, most scientists still rely on methods written during the early era of computing. These researchers, who analyze increasingly voluminous and multivariate data sets, need modern analysis methods to extract the best results from their studies. The first section of this work showcases applications of modern linear regression. Since the 1960's, many researchers in spectroscopy have used classical stepwise regression techniques to derive molecular constants. However, problems with thresholds of entry and exit for model variables plagues this analysis method. Other criticisms of this kind of stepwise procedure include its inefficient searching method, the order in which variables enter or leave the model and problems with overfitting data. We implement an information scoring technique that overcomes the assumptions inherent in the stepwise regression process to calculate molecular model parameters. We believe that this kind of information based model evaluation can be applied to more general analysis situations in physical science. The second section proposes new methods of multivariate cluster analysis. The K-means algorithm and the EM algorithm, introduced in the 1960's and 1970's respectively, formed the basis of multivariate cluster analysis methodology for many years. However, several shortcomings of these methods include strong dependence on initial seed values and inaccurate results when the data seriously depart from hypersphericity. We propose new cluster analysis methods based on genetic algorithms that overcomes the strong dependence on initial seed values. In addition, we propose a generalization of the Genetic K-means algorithm which can accurately identify clusters with complex hyperellipsoidal covariance structures. We then use this new algorithm in a genetic algorithm based Expectation-Maximization process that can accurately calculate parameters describing complex clusters in a mixture model routine. Using the accuracy of this GEM algorithm, we assign information scores to cluster calculations in order to best identify the number of mixture components in a multivariate data set. We will showcase how these algorithms can be used to process multivariate data from astronomical observations.

Shell shape variation of queen conch Strombus gigas (Mesograstropoda: Strombidae) from Southwest Caribbean.

PubMed

Márquez, Edna Judith; Restrepo-Escobar, Natalia; Montoya-Herrera, Francisco Luis

2016-12-01

The endangered species Strombus gigas is a marine gastropod of significant economic importance through the Greater Caribbean region. In contrast to phenotypic plasticity, the role of genetics on shell variations in S. gigas has not been addressed so far, despite its importance in evolution, management and conservation of this species. This work used geometric morphometrics to investigate the phenotypic variation of 219 shells of S. gigas from eight sites of the Colombian Southwest Caribbean. Differences in mean size between sexes and among sites were contrasted by analysis of variance. Allometry was tested by multivariate regression and the hypothesis of common slope was contrasted by covariance multivariate analysis. Differences in the shell shape among sites were analyzed by principal component analysis. Sexual size dimorphism was not significant, whereas sexual shape dimorphism was significant and variable across sites. Differences in the shell shape among sites were concordant with genetic differences based on microsatellite data, supporting its genetic background. Besides, differences in the shell shape between populations genetically similar suggest a role of phenotypic plasticity in the morphometric variation of the shell shape. These outcomes evidence the role of genetic background and phenotypic plasticity in the shell shape of S. gigas. Thus, geometric morphometrics of shell shape may constitute a complementary tool to explore the genetic diversity of this species.

Multivariate Genetic Correlates of the Auditory Paired Stimuli-Based P2 Event-Related Potential in the Psychosis Dimension From the BSNIP Study.

PubMed

Mokhtari, Mohammadreza; Narayanan, Balaji; Hamm, Jordan P; Soh, Pauline; Calhoun, Vince D; Ruaño, Gualberto; Kocherla, Mohan; Windemuth, Andreas; Clementz, Brett A; Tamminga, Carol A; Sweeney, John A; Keshavan, Matcheri S; Pearlson, Godfrey D

2016-05-01

The complex molecular etiology of psychosis in schizophrenia (SZ) and psychotic bipolar disorder (PBP) is not well defined, presumably due to their multifactorial genetic architecture. Neurobiological correlates of psychosis can be identified through genetic associations of intermediate phenotypes such as event-related potential (ERP) from auditory paired stimulus processing (APSP). Various ERP components of APSP are heritable and aberrant in SZ, PBP and their relatives, but their multivariate genetic factors are less explored. We investigated the multivariate polygenic association of ERP from 64-sensor auditory paired stimulus data in 149 SZ, 209 PBP probands, and 99 healthy individuals from the multisite Bipolar-Schizophrenia Network on Intermediate Phenotypes study. Multivariate association of 64-channel APSP waveforms with a subset of 16 999 single nucleotide polymorphisms (SNPs) (reduced from 1 million SNP array) was examined using parallel independent component analysis (Para-ICA). Biological pathways associated with the genes were assessed using enrichment-based analysis tools. Para-ICA identified 2 ERP components, of which one was significantly correlated with a genetic network comprising multiple linearly coupled gene variants that explained ~4% of the ERP phenotype variance. Enrichment analysis revealed epidermal growth factor, endocannabinoid signaling, glutamatergic synapse and maltohexaose transport associated with P2 component of the N1-P2 ERP waveform. This ERP component also showed deficits in SZ and PBP. Aberrant P2 component in psychosis was associated with gene networks regulating several fundamental biologic functions, either general or specific to nervous system development. The pathways and processes underlying the gene clusters play a crucial role in brain function, plausibly implicated in psychosis. © The Author 2015. Published by Oxford University Press on behalf of the Maryland Psychiatric Research Center. All rights reserved. For permissions, please email: journals.permissions@oup.com.

Genome-Wide Association Analysis of Adaptation Using Environmentally Predicted Traits.

PubMed

van Heerwaarden, Joost; van Zanten, Martijn; Kruijer, Willem

2015-10-01

Current methods for studying the genetic basis of adaptation evaluate genetic associations with ecologically relevant traits or single environmental variables, under the implicit assumption that natural selection imposes correlations between phenotypes, environments and genotypes. In practice, observed trait and environmental data are manifestations of unknown selective forces and are only indirectly associated with adaptive genetic variation. In theory, improved estimation of these forces could enable more powerful detection of loci under selection. Here we present an approach in which we approximate adaptive variation by modeling phenotypes as a function of the environment and using the predicted trait in multivariate and univariate genome-wide association analysis (GWAS). Based on computer simulations and published flowering time data from the model plant Arabidopsis thaliana, we find that environmentally predicted traits lead to higher recovery of functional loci in multivariate GWAS and are more strongly correlated to allele frequencies at adaptive loci than individual environmental variables. Our results provide an example of the use of environmental data to obtain independent and meaningful information on adaptive genetic variation.

Partial least squares correspondence analysis: A framework to simultaneously analyze behavioral and genetic data.

PubMed

Beaton, Derek; Dunlop, Joseph; Abdi, Hervé

2016-12-01

For nearly a century, detecting the genetic contributions to cognitive and behavioral phenomena has been a core interest for psychological research. Recently, this interest has been reinvigorated by the availability of genotyping technologies (e.g., microarrays) that provide new genetic data, such as single nucleotide polymorphisms (SNPs). These SNPs-which represent pairs of nucleotide letters (e.g., AA, AG, or GG) found at specific positions on human chromosomes-are best considered as categorical variables, but this coding scheme can make difficult the multivariate analysis of their relationships with behavioral measurements, because most multivariate techniques developed for the analysis between sets of variables are designed for quantitative variables. To palliate this problem, we present a generalization of partial least squares-a technique used to extract the information common to 2 different data tables measured on the same observations-called partial least squares correspondence analysis-that is specifically tailored for the analysis of categorical and mixed ("heterogeneous") data types. Here, we formally define and illustrate-in a tutorial format-how partial least squares correspondence analysis extends to various types of data and design problems that are particularly relevant for psychological research that include genetic data. We illustrate partial least squares correspondence analysis with genetic, behavioral, and neuroimaging data from the Alzheimer's Disease Neuroimaging Initiative. R code is available on the Comprehensive R Archive Network and via the authors' websites. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Selection Indices and Multivariate Analysis Show Similar Results in the Evaluation of Growth and Carcass Traits in Beef Cattle

PubMed Central

Brito Lopes, Fernando; da Silva, Marcelo Corrêa; Magnabosco, Cláudio Ulhôa; Goncalves Narciso, Marcelo; Sainz, Roberto Daniel

2016-01-01

This research evaluated a multivariate approach as an alternative tool for the purpose of selection regarding expected progeny differences (EPDs). Data were fitted using a multi-trait model and consisted of growth traits (birth weight and weights at 120, 210, 365 and 450 days of age) and carcass traits (longissimus muscle area (LMA), back-fat thickness (BF), and rump fat thickness (RF)), registered over 21 years in extensive breeding systems of Polled Nellore cattle in Brazil. Multivariate analyses were performed using standardized (zero mean and unit variance) EPDs. The k mean method revealed that the best fit of data occurred using three clusters (k = 3) (P < 0.001). Estimates of genetic correlation among growth and carcass traits and the estimates of heritability were moderate to high, suggesting that a correlated response approach is suitable for practical decision making. Estimates of correlation between selection indices and the multivariate index (LD1) were moderate to high, ranging from 0.48 to 0.97. This reveals that both types of indices give similar results and that the multivariate approach is reliable for the purpose of selection. The alternative tool seems very handy when economic weights are not available or in cases where more rapid identification of the best animals is desired. Interestingly, multivariate analysis allowed forecasting information based on the relationships among breeding values (EPDs). Also, it enabled fine discrimination, rapid data summarization after genetic evaluation, and permitted accounting for maternal ability and the genetic direct potential of the animals. In addition, we recommend the use of longissimus muscle area and subcutaneous fat thickness as selection criteria, to allow estimation of breeding values before the first mating season in order to accelerate the response to individual selection. PMID:26789008

Selection Indices and Multivariate Analysis Show Similar Results in the Evaluation of Growth and Carcass Traits in Beef Cattle.

PubMed

Brito Lopes, Fernando; da Silva, Marcelo Corrêa; Magnabosco, Cláudio Ulhôa; Goncalves Narciso, Marcelo; Sainz, Roberto Daniel

2016-01-01

This research evaluated a multivariate approach as an alternative tool for the purpose of selection regarding expected progeny differences (EPDs). Data were fitted using a multi-trait model and consisted of growth traits (birth weight and weights at 120, 210, 365 and 450 days of age) and carcass traits (longissimus muscle area (LMA), back-fat thickness (BF), and rump fat thickness (RF)), registered over 21 years in extensive breeding systems of Polled Nellore cattle in Brazil. Multivariate analyses were performed using standardized (zero mean and unit variance) EPDs. The k mean method revealed that the best fit of data occurred using three clusters (k = 3) (P < 0.001). Estimates of genetic correlation among growth and carcass traits and the estimates of heritability were moderate to high, suggesting that a correlated response approach is suitable for practical decision making. Estimates of correlation between selection indices and the multivariate index (LD1) were moderate to high, ranging from 0.48 to 0.97. This reveals that both types of indices give similar results and that the multivariate approach is reliable for the purpose of selection. The alternative tool seems very handy when economic weights are not available or in cases where more rapid identification of the best animals is desired. Interestingly, multivariate analysis allowed forecasting information based on the relationships among breeding values (EPDs). Also, it enabled fine discrimination, rapid data summarization after genetic evaluation, and permitted accounting for maternal ability and the genetic direct potential of the animals. In addition, we recommend the use of longissimus muscle area and subcutaneous fat thickness as selection criteria, to allow estimation of breeding values before the first mating season in order to accelerate the response to individual selection.

Motivations for genetic testing for lung cancer risk among young smokers.

PubMed

O'Neill, Suzanne C; Lipkus, Isaac M; Sanderson, Saskia C; Shepperd, James; Docherty, Sharron; McBride, Colleen M

2013-11-01

To examine why young people might want to undergo genetic susceptibility testing for lung cancer despite knowing that tested gene variants are associated with small increases in disease risk. The authors used a mixed-method approach to evaluate motives for and against genetic testing and the association between these motivations and testing intentions in 128 college students who smoke. Exploratory factor analysis yielded four reliable factors: Test Scepticism, Test Optimism, Knowledge Enhancement and Smoking Optimism. Test Optimism and Knowledge Enhancement correlated positively with intentions to test in bivariate and multivariate analyses (ps<0.001). Test Scepticism correlated negatively with testing intentions in multivariate analyses (p<0.05). Open-ended questions assessing testing motivations generally replicated themes of the quantitative survey. In addition to learning about health risks, young people may be motivated to seek genetic testing for reasons, such as gaining knowledge about new genetic technologies more broadly.

A multivariate twin study of early literacy in Japanese Kana

PubMed Central

Fujisawa, Keiko K.; Wadsworth, Sally J.; Kakihana, Shinichiro; Olson, Richard K.; DeFries, John C.; Byrne, Brian; Ando, Juko

2013-01-01

This first Japanese twin study of early literacy development investigated the extent to which genetic and environmental factors influence individual differences in prereading skills in 238 pairs of twins at 42 months of age. Twin pairs were individually tested on measures of phonological awareness, kana letter name/sound knowledge, receptive vocabulary, visual perception, nonword repetition, and digit span. Results obtained from univariate behavioral-genetic analyses yielded little evidence for genetic influences, but substantial shared-environmental influences, for all measures. Phenotypic confirmatory factor analysis suggested three correlated factors: phonological awareness, letter name/sound knowledge, and general prereading skills. Multivariate behavioral genetic analyses confirmed relatively small genetic and substantial shared environmental influences on the factors. The correlations among the three factors were mostly attributable to shared environment. Thus, shared environmental influences play an important role in the early reading development of Japanese children. PMID:23997545

Multivariate approach in popcorn genotypes using the Ward-MLM strategy: morpho-agronomic analysis and incidence of Fusarium spp.

PubMed

Kurosawa, R N F; do Amaral Junior, A T; Silva, F H L; Dos Santos, A; Vivas, M; Kamphorst, S H; Pena, G F

2017-02-08

The multivariate analyses are useful tools to estimate the genetic variability between accessions. In the breeding programs, the Ward-Modified Location Model (MLM) multivariate method has been a powerful strategy to quantify variability using quantitative and qualitative variables simultaneously. The present study was proposed in view of the dearth of information about popcorn breeding programs under a multivariate approach using the Ward-MLM methodology. The objective of this study was thus to estimate the genetic diversity among 37 genotypes of popcorn aiming to identify divergent groups associated with morpho-agronomic traits and traits related to resistance to Fusarium spp. To this end, 7 qualitative and 17 quantitative variables were analyzed. The experiment was conducted in 2014, at Universidade Estadual do Norte Fluminense, located in Campos dos Goytacazes, RJ, Brazil. The Ward-MLM strategy allowed the identification of four groups as follows: Group I with 10 genotypes, Group II with 11 genotypes, Group III with 9 genotypes, and Group IV with 7 genotypes. Group IV was distant in relation to the other groups, while groups I, II, and III were near. The crosses between genotypes from the other groups with those of group IV allow an exploitation of heterosis. The Ward-MLM strategy provided an appropriate grouping of genotypes; ear weight, ear diameter, and grain yield were the traits that most contributed to the analysis of genetic diversity.

A Unified Framework for Association Analysis with Multiple Related Phenotypes

PubMed Central

Stephens, Matthew

2013-01-01

We consider the problem of assessing associations between multiple related outcome variables, and a single explanatory variable of interest. This problem arises in many settings, including genetic association studies, where the explanatory variable is genotype at a genetic variant. We outline a framework for conducting this type of analysis, based on Bayesian model comparison and model averaging for multivariate regressions. This framework unifies several common approaches to this problem, and includes both standard univariate and standard multivariate association tests as special cases. The framework also unifies the problems of testing for associations and explaining associations – that is, identifying which outcome variables are associated with genotype. This provides an alternative to the usual, but conceptually unsatisfying, approach of resorting to univariate tests when explaining and interpreting significant multivariate findings. The method is computationally tractable genome-wide for modest numbers of phenotypes (e.g. 5–10), and can be applied to summary data, without access to raw genotype and phenotype data. We illustrate the methods on both simulated examples, and to a genome-wide association study of blood lipid traits where we identify 18 potential novel genetic associations that were not identified by univariate analyses of the same data. PMID:23861737

Genetic Structure of Bluefin Tuna in the Mediterranean Sea Correlates with Environmental Variables

PubMed Central

Riccioni, Giulia; Stagioni, Marco; Landi, Monica; Ferrara, Giorgia; Barbujani, Guido; Tinti, Fausto

2013-01-01

Background Atlantic Bluefin Tuna (ABFT) shows complex demography and ecological variation in the Mediterranean Sea. Genetic surveys have detected significant, although weak, signals of population structuring; catch series analyses and tagging programs identified complex ABFT spatial dynamics and migration patterns. Here, we tested the hypothesis that the genetic structure of the ABFT in the Mediterranean is correlated with mean surface temperature and salinity. Methodology We used six samples collected from Western and Central Mediterranean integrated with a new sample collected from the recently identified easternmost reproductive area of Levantine Sea. To assess population structure in the Mediterranean we used a multidisciplinary framework combining classical population genetics, spatial and Bayesian clustering methods and a multivariate approach based on factor analysis. Conclusions FST analysis and Bayesian clustering methods detected several subpopulations in the Mediterranean, a result also supported by multivariate analyses. In addition, we identified significant correlations of genetic diversity with mean salinity and surface temperature values revealing that ABFT is genetically structured along two environmental gradients. These results suggest that a preference for some spawning habitat conditions could contribute to shape ABFT genetic structuring in the Mediterranean. However, further studies should be performed to assess to what extent ABFT spawning behaviour in the Mediterranean Sea can be affected by environmental variation. PMID:24260341

A flexible model for multivariate interval-censored survival times with complex correlation structure.

PubMed

Falcaro, Milena; Pickles, Andrew

2007-02-10

We focus on the analysis of multivariate survival times with highly structured interdependency and subject to interval censoring. Such data are common in developmental genetics and genetic epidemiology. We propose a flexible mixed probit model that deals naturally with complex but uninformative censoring. The recorded ages of onset are treated as possibly censored ordinal outcomes with the interval censoring mechanism seen as arising from a coarsened measurement of a continuous variable observed as falling between subject-specific thresholds. This bypasses the requirement for the failure times to be observed as falling into non-overlapping intervals. The assumption of a normal age-of-onset distribution of the standard probit model is relaxed by embedding within it a multivariate Box-Cox transformation whose parameters are jointly estimated with the other parameters of the model. Complex decompositions of the underlying multivariate normal covariance matrix of the transformed ages of onset become possible. The new methodology is here applied to a multivariate study of the ages of first use of tobacco and first consumption of alcohol without parental permission in twins. The proposed model allows estimation of the genetic and environmental effects that are shared by both of these risk behaviours as well as those that are specific. 2006 John Wiley & Sons, Ltd.

Learning abilities and disabilities: generalist genes in early adolescence.

PubMed

Davis, Oliver S P; Haworth, Claire M A; Plomin, Robert

2009-01-01

The new view of cognitive neuropsychology that considers not just case studies of rare severe disorders but also common disorders, as well as normal variation and quantitative traits, is more amenable to recent advances in molecular genetics, such as genome-wide association studies, and advances in quantitative genetics, such as multivariate genetic analysis. A surprising finding emerging from multivariate quantitative genetic studies across diverse learning abilities is that most genetic influences are shared: they are "generalist", rather than "specialist". We exploited widespread access to inexpensive and fast Internet connections in the United Kingdom to assess over 5000 pairs of 12-year-old twins from the Twins Early Development Study (TEDS) on four distinct batteries: reading, mathematics, general cognitive ability (g) and, for the first time, language. Genetic correlations remain high among all of the measured abilities, with language as highly correlated genetically with g as reading and mathematics. Despite developmental upheaval, generalist genes remain important into early adolescence, suggesting optimal strategies for molecular genetic studies seeking to identify the genes of small effect that influence learning abilities and disabilities.

The genetic basis for cognitive ability, memory, and depression symptomatology in middle-aged and elderly chinese twins.

PubMed

Xu, Chunsheng; Sun, Jianping; Ji, Fuling; Tian, Xiaocao; Duan, Haiping; Zhai, Yaoming; Wang, Shaojie; Pang, Zengchang; Zhang, Dongfeng; Zhao, Zhongtang; Li, Shuxia; Hjelmborg, Jacob V B; Christensen, Kaare; Tan, Qihua

2015-02-01

The genetic influences on aging-related phenotypes, including cognition and depression, have been well confirmed in the Western populations. We performed the first twin-based analysis on cognitive performance, memory and depression status in middle-aged and elderly Chinese twins, representing the world's largest and most rapidly aging population. The sample consisted of 384 twin pairs with a median age of 50 years. Cognitive function was measured using the Montreal Cognitive Assessment (MoCA) scale; memory was assessed using the revised Wechsler Adult Intelligence scale; depression symptomatology was evaluated by the self-reported 30-item Geriatric Depression (GDS-30)scale. Both univariate and multivariate twin models were fitted to the three phenotypes with full and nested models and compared to select the best fitting models. Univariate analysis showed moderate-to-high genetic influences with heritability 0.44 for cognition and 0.56 for memory. Multivariate analysis by the reduced Cholesky model estimated significant genetic (rG = 0.69) and unique environmental (rE = 0.25) correlation between cognitive ability and memory. The model also estimated weak but significant inverse genetic correlation for depression with cognition (-0.31) and memory (-0.28). No significant unique environmental correlation was found for depression with other two phenotypes. In conclusion, there can be a common genetic architecture for cognitive ability and memory that weakly correlates with depression symptomatology, but in the opposite direction.

Ten-year experiences on initial genetic examination in childhood acute lymphoblastic leukaemia in Hungary (1993-2002). Technical approaches and clinical implementation.

PubMed

Olah, Eva; Balogh, Erzsebet; Pajor, Laszlo; Jakab, Zsuzsanna

2011-03-01

A nationwide study was started in 1993 to provide genetic diagnosis for all newly diagnosed childhood ALL cases in Hungary using cytogenetic examination, DNA-index determination, FISH (aneuploidy, ABL/BCR, TEL/AML1) and molecular genetic tests (ABL/BCR, MLL/AF4, TEL/AML1). Aim of the study was to assess the usefulness of different genetic methods, to study the frequency of various aberrations and their prognostic significance. Results were synthesized for genetic subgrouping of patients. To assess the prognostic value of genetic aberrations overall and event-free survival of genetic subgroups were compared using Kaplan-Meier method. Prognostic role of aberrations was investigated by multivariate analysis (Cox's regression) as well in comparison with other factors (age, sex, major congenital abnormalities, initial WBC, therapy, immunophenotype). Five hundred eighty-eight ALL cases were diagnosed between 1993-2002. Cytogenetic examination was performed in 537 (91%) (success rate 73%), DNA-index in 265 (45%), FISH in 74 (13%), TEL/AML1 RT-PCR in 219 (37%) cases producing genetic diagnosis in 457 patients (78%). Proportion of subgroups with good prognosis in prae-B-cell ALL was lower than expected: hyperdiploidB 18% (73/400), TEL/AML1+ 9% (36/400). Univariate analysis showed significantly better 5-year EFS in TEL/AML1+ (82%) and hyperdiploidB cases (78%) than in tetraploid (44%) or pseudodiploid (52%) subgroups. By multivariate analysis main negative prognostic factors were: congenital abnormalities, high WBC, delay in therapy, specific translocations. Complementary use of each of genetic methods used is necessary for reliable genetic diagnosis according to the algorithm presented. Specific genetic alterations proved to be of prognostic significance.

Multivariate analysis of the cotton seed ionome reveals integrated genetic signatures of abiotic stress-response

USDA-ARS?s Scientific Manuscript database

To mitigate the effects of heat and drought stress, an understanding of the genetic control of physiological responses to these environmental conditions is needed. To this end, we evaluated an upland cotton (Gossypium hirsutum L.) mapping population under water-limited and well-watered conditions in...

Genome-Wide Association Analysis of Adaptation Using Environmentally Predicted Traits

PubMed Central

van Zanten, Martijn

2015-01-01

Current methods for studying the genetic basis of adaptation evaluate genetic associations with ecologically relevant traits or single environmental variables, under the implicit assumption that natural selection imposes correlations between phenotypes, environments and genotypes. In practice, observed trait and environmental data are manifestations of unknown selective forces and are only indirectly associated with adaptive genetic variation. In theory, improved estimation of these forces could enable more powerful detection of loci under selection. Here we present an approach in which we approximate adaptive variation by modeling phenotypes as a function of the environment and using the predicted trait in multivariate and univariate genome-wide association analysis (GWAS). Based on computer simulations and published flowering time data from the model plant Arabidopsis thaliana, we find that environmentally predicted traits lead to higher recovery of functional loci in multivariate GWAS and are more strongly correlated to allele frequencies at adaptive loci than individual environmental variables. Our results provide an example of the use of environmental data to obtain independent and meaningful information on adaptive genetic variation. PMID:26496492

Meta-analysis of quantitative pleiotropic traits for next-generation sequencing with multivariate functional linear models

PubMed Central

Chiu, Chi-yang; Jung, Jeesun; Chen, Wei; Weeks, Daniel E; Ren, Haobo; Boehnke, Michael; Amos, Christopher I; Liu, Aiyi; Mills, James L; Ting Lee, Mei-ling; Xiong, Momiao; Fan, Ruzong

2017-01-01

To analyze next-generation sequencing data, multivariate functional linear models are developed for a meta-analysis of multiple studies to connect genetic variant data to multiple quantitative traits adjusting for covariates. The goal is to take the advantage of both meta-analysis and pleiotropic analysis in order to improve power and to carry out a unified association analysis of multiple studies and multiple traits of complex disorders. Three types of approximate F -distributions based on Pillai–Bartlett trace, Hotelling–Lawley trace, and Wilks's Lambda are introduced to test for association between multiple quantitative traits and multiple genetic variants. Simulation analysis is performed to evaluate false-positive rates and power of the proposed tests. The proposed methods are applied to analyze lipid traits in eight European cohorts. It is shown that it is more advantageous to perform multivariate analysis than univariate analysis in general, and it is more advantageous to perform meta-analysis of multiple studies instead of analyzing the individual studies separately. The proposed models require individual observations. The value of the current paper can be seen at least for two reasons: (a) the proposed methods can be applied to studies that have individual genotype data; (b) the proposed methods can be used as a criterion for future work that uses summary statistics to build test statistics to meta-analyze the data. PMID:28000696

Meta-analysis of quantitative pleiotropic traits for next-generation sequencing with multivariate functional linear models.

PubMed

Chiu, Chi-Yang; Jung, Jeesun; Chen, Wei; Weeks, Daniel E; Ren, Haobo; Boehnke, Michael; Amos, Christopher I; Liu, Aiyi; Mills, James L; Ting Lee, Mei-Ling; Xiong, Momiao; Fan, Ruzong

2017-02-01

To analyze next-generation sequencing data, multivariate functional linear models are developed for a meta-analysis of multiple studies to connect genetic variant data to multiple quantitative traits adjusting for covariates. The goal is to take the advantage of both meta-analysis and pleiotropic analysis in order to improve power and to carry out a unified association analysis of multiple studies and multiple traits of complex disorders. Three types of approximate F -distributions based on Pillai-Bartlett trace, Hotelling-Lawley trace, and Wilks's Lambda are introduced to test for association between multiple quantitative traits and multiple genetic variants. Simulation analysis is performed to evaluate false-positive rates and power of the proposed tests. The proposed methods are applied to analyze lipid traits in eight European cohorts. It is shown that it is more advantageous to perform multivariate analysis than univariate analysis in general, and it is more advantageous to perform meta-analysis of multiple studies instead of analyzing the individual studies separately. The proposed models require individual observations. The value of the current paper can be seen at least for two reasons: (a) the proposed methods can be applied to studies that have individual genotype data; (b) the proposed methods can be used as a criterion for future work that uses summary statistics to build test statistics to meta-analyze the data.

Multivariate random regression analysis for body weight and main morphological traits in genetically improved farmed tilapia (Oreochromis niloticus).

PubMed

He, Jie; Zhao, Yunfeng; Zhao, Jingli; Gao, Jin; Han, Dandan; Xu, Pao; Yang, Runqing

2017-11-02

Because of their high economic importance, growth traits in fish are under continuous improvement. For growth traits that are recorded at multiple time-points in life, the use of univariate and multivariate animal models is limited because of the variable and irregular timing of these measures. Thus, the univariate random regression model (RRM) was introduced for the genetic analysis of dynamic growth traits in fish breeding. We used a multivariate random regression model (MRRM) to analyze genetic changes in growth traits recorded at multiple time-point of genetically-improved farmed tilapia. Legendre polynomials of different orders were applied to characterize the influences of fixed and random effects on growth trajectories. The final MRRM was determined by optimizing the univariate RRM for the analyzed traits separately via penalizing adaptively the likelihood statistical criterion, which is superior to both the Akaike information criterion and the Bayesian information criterion. In the selected MRRM, the additive genetic effects were modeled by Legendre polynomials of three orders for body weight (BWE) and body length (BL) and of two orders for body depth (BD). By using the covariance functions of the MRRM, estimated heritabilities were between 0.086 and 0.628 for BWE, 0.155 and 0.556 for BL, and 0.056 and 0.607 for BD. Only heritabilities for BD measured from 60 to 140 days of age were consistently higher than those estimated by the univariate RRM. All genetic correlations between growth time-points exceeded 0.5 for either single or pairwise time-points. Moreover, correlations between early and late growth time-points were lower. Thus, for phenotypes that are measured repeatedly in aquaculture, an MRRM can enhance the efficiency of the comprehensive selection for BWE and the main morphological traits.

Inherited behavioral susceptibility to adiposity in infancy: a multivariate genetic analysis of appetite and weight in the Gemini birth cohort.

PubMed

Llewellyn, Clare H; van Jaarsveld, Cornelia H M; Plomin, Robert; Fisher, Abigail; Wardle, Jane

2012-03-01

The behavioral susceptibility model proposes that inherited differences in traits such as appetite confer differential risk of weight gain and contribute to the heritability of weight. Evidence that the FTO gene may influence weight partly through its effects on appetite supports this model, but testing the behavioral pathways for multiple genes with very small effects is not feasible. Twin analyses make it possible to get a broad-based estimate of the extent of shared genetic influence between appetite and weight. The objective was to use multivariate twin analyses to test the hypothesis that associations between appetite and weight are underpinned by shared genetic effects. Data were from Gemini, a population-based birth cohort of twins (n = 4804) born in 2007. Infant weights at 3 mo were taken from the records of health professionals. Appetite was assessed at 3 mo for the milk-feeding period by using the Baby Eating Behaviour Questionnaire (BEBQ), a parent-reported measure of appetite [enjoyment of food, food responsiveness, slowness in eating (SE), satiety responsiveness (SR), and appetite size (AS)]. Multivariate quantitative genetic modeling was used to test for shared genetic influences. Significant correlations were found between all BEBQ traits and weight. Significant shared genetic influence was identified for weight with SE, SR, and AS; genetic correlations were between 0.22 and 0.37. Shared genetic effects explained 41-45% of these phenotypic associations. Differences in weight in infancy may be due partly to genetically determined differences in appetitive traits that confer differential susceptibility to obesogenic environments.

Multivariate analysis of molecular and morphological diversity in fig (Ficus carica L.)

USDA-ARS?s Scientific Manuscript database

Genetic polymorphism across 15 microsatellite loci among 194 fig accessions including Common, Smyrna, San Pedro, and Caprifig were analyzed using a cluster analysis (CA) and the principal components analysis (PCA). The collection was moderately variable with observed number of alleles per locus rang...

Effect of environment and genotype on commercial maize hybrids using LC/MS-based metabolomics.

PubMed

Baniasadi, Hamid; Vlahakis, Chris; Hazebroek, Jan; Zhong, Cathy; Asiago, Vincent

2014-02-12

We recently applied gas chromatography coupled to time-of-flight mass spectrometry (GC/TOF-MS) and multivariate statistical analysis to measure biological variation of many metabolites due to environment and genotype in forage and grain samples collected from 50 genetically diverse nongenetically modified (non-GM) DuPont Pioneer commercial maize hybrids grown at six North American locations. In the present study, the metabolome coverage was extended using a core subset of these grain and forage samples employing ultra high pressure liquid chromatography (uHPLC) mass spectrometry (LC/MS). A total of 286 and 857 metabolites were detected in grain and forage samples, respectively, using LC/MS. Multivariate statistical analysis was utilized to compare and correlate the metabolite profiles. Environment had a greater effect on the metabolome than genetic background. The results of this study support and extend previously published insights into the environmental and genetic associated perturbations to the metabolome that are not associated with transgenic modification.

A Multivariate Twin Study of the DSM-IV Criteria for Antisocial Personality Disorder

PubMed Central

Kendler, Kenneth S.; Aggen, Steven H.; Patrick, Christopher J.

2012-01-01

BACKGROUND Many assessment instruments for psychopathy are multidimensional, suggesting that distinguishable factors are needed to effectively capture variation in this personality domain. However, no prior study has examined the factor structure of the DSM-IV criteria for antisocial personality disorder (ASPD). METHODS Self-report questionnaire items reflecting all A criteria for DSM-IV ASPD were available from 4,291 twins (including both members of 1,647 pairs) from the Virginia Adult Study of Psychiatric and Substance Use Disorders. Exploratory factor analysis and twin model fitting were performed using, respectively, Mplus and Mx. RESULTS Phenotypic factor analysis produced evidence for 2 correlated factors: aggressive-disregard and disinhibition. The best-fitting multivariate twin model included two genetic and one unique environmental common factor, along with criteria-specific genetic and environmental effects. The two genetic factors closely resembled the phenotypic factors and varied in their prediction of a range of relevant criterion variables. Scores on the genetic aggressive-disregard factor score were more strongly associated with risk for conduct disorder, early and heavy alcohol use, and low educational status, whereas scores on the genetic disinhibition factor score were more strongly associated with younger age, novelty seeking, and major depression. CONCLUSION From a genetic perspective, the DSM-IV criteria for ASPD do not reflect a single dimension of liability but rather are influenced by two dimensions of genetic risk reflecting aggressive-disregard and disinhibition. The phenotypic structure of the ASPD criteria results largely from genetic and not from environmental influences. PMID:21762879

FGWAS: Functional genome wide association analysis.

PubMed

Huang, Chao; Thompson, Paul; Wang, Yalin; Yu, Yang; Zhang, Jingwen; Kong, Dehan; Colen, Rivka R; Knickmeyer, Rebecca C; Zhu, Hongtu

2017-10-01

Functional phenotypes (e.g., subcortical surface representation), which commonly arise in imaging genetic studies, have been used to detect putative genes for complexly inherited neuropsychiatric and neurodegenerative disorders. However, existing statistical methods largely ignore the functional features (e.g., functional smoothness and correlation). The aim of this paper is to develop a functional genome-wide association analysis (FGWAS) framework to efficiently carry out whole-genome analyses of functional phenotypes. FGWAS consists of three components: a multivariate varying coefficient model, a global sure independence screening procedure, and a test procedure. Compared with the standard multivariate regression model, the multivariate varying coefficient model explicitly models the functional features of functional phenotypes through the integration of smooth coefficient functions and functional principal component analysis. Statistically, compared with existing methods for genome-wide association studies (GWAS), FGWAS can substantially boost the detection power for discovering important genetic variants influencing brain structure and function. Simulation studies show that FGWAS outperforms existing GWAS methods for searching sparse signals in an extremely large search space, while controlling for the family-wise error rate. We have successfully applied FGWAS to large-scale analysis of data from the Alzheimer's Disease Neuroimaging Initiative for 708 subjects, 30,000 vertices on the left and right hippocampal surfaces, and 501,584 SNPs. Copyright © 2017 Elsevier Inc. All rights reserved.

Genetic structure of Quechua-speakers of the Central Andes and geographic patterns of gene frequencies in South Amerindian populations.

PubMed

Luiselli, D; Simoni, L; Tarazona-Santos, E; Pastor, S; Pettener, D

2000-09-01

A sample of 141 Quechua-speaking individuals of the population of Tayacaja, in the Peruvian Central Andes, was typed for the following 16 genetic systems: ABO, Rh, MNSs, P, Duffy, AcP1, EsD, GLOI, PGM1, AK, 6-PGD, Hp, Gc, Pi, C3, and Bf. The genetic structure of the population was analyzed in relation to the allele frequencies available for other South Amerindian populations, using a combination of multivariate and multivariable techniques. Spatial autocorrelation analysis was performed independently for 13 alleles to identify patterns of gene flow in South America as a whole and in more specific geographic regions. We found a longitudinal cline for the AcP1*a and EsD*1 alleles which we interpreted as the result of an ancient longitudinal expansion of a putative ancestral population of modern Amerindians. Monmonnier's algorithm, used to identify areas of sharp genetic discontinuity, suggested a clear east-west differentiation of native South American populations, which was confirmed by analysis of the distribution of genetic distances. We suggest that this pattern of genetic structures is the consequence of the independent peopling of western and eastern South America or to low levels of gene flow between these regions, related to different environmental and demographic histories. Copyright 2000 Wiley-Liss, Inc.

metaCCA: summary statistics-based multivariate meta-analysis of genome-wide association studies using canonical correlation analysis.

PubMed

Cichonska, Anna; Rousu, Juho; Marttinen, Pekka; Kangas, Antti J; Soininen, Pasi; Lehtimäki, Terho; Raitakari, Olli T; Järvelin, Marjo-Riitta; Salomaa, Veikko; Ala-Korpela, Mika; Ripatti, Samuli; Pirinen, Matti

2016-07-01

A dominant approach to genetic association studies is to perform univariate tests between genotype-phenotype pairs. However, analyzing related traits together increases statistical power, and certain complex associations become detectable only when several variants are tested jointly. Currently, modest sample sizes of individual cohorts, and restricted availability of individual-level genotype-phenotype data across the cohorts limit conducting multivariate tests. We introduce metaCCA, a computational framework for summary statistics-based analysis of a single or multiple studies that allows multivariate representation of both genotype and phenotype. It extends the statistical technique of canonical correlation analysis to the setting where original individual-level records are not available, and employs a covariance shrinkage algorithm to achieve robustness.Multivariate meta-analysis of two Finnish studies of nuclear magnetic resonance metabolomics by metaCCA, using standard univariate output from the program SNPTEST, shows an excellent agreement with the pooled individual-level analysis of original data. Motivated by strong multivariate signals in the lipid genes tested, we envision that multivariate association testing using metaCCA has a great potential to provide novel insights from already published summary statistics from high-throughput phenotyping technologies. Code is available at https://github.com/aalto-ics-kepaco anna.cichonska@helsinki.fi or matti.pirinen@helsinki.fi Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press.

metaCCA: summary statistics-based multivariate meta-analysis of genome-wide association studies using canonical correlation analysis

PubMed Central

Cichonska, Anna; Rousu, Juho; Marttinen, Pekka; Kangas, Antti J.; Soininen, Pasi; Lehtimäki, Terho; Raitakari, Olli T.; Järvelin, Marjo-Riitta; Salomaa, Veikko; Ala-Korpela, Mika; Ripatti, Samuli; Pirinen, Matti

2016-01-01

Motivation: A dominant approach to genetic association studies is to perform univariate tests between genotype-phenotype pairs. However, analyzing related traits together increases statistical power, and certain complex associations become detectable only when several variants are tested jointly. Currently, modest sample sizes of individual cohorts, and restricted availability of individual-level genotype-phenotype data across the cohorts limit conducting multivariate tests. Results: We introduce metaCCA, a computational framework for summary statistics-based analysis of a single or multiple studies that allows multivariate representation of both genotype and phenotype. It extends the statistical technique of canonical correlation analysis to the setting where original individual-level records are not available, and employs a covariance shrinkage algorithm to achieve robustness. Multivariate meta-analysis of two Finnish studies of nuclear magnetic resonance metabolomics by metaCCA, using standard univariate output from the program SNPTEST, shows an excellent agreement with the pooled individual-level analysis of original data. Motivated by strong multivariate signals in the lipid genes tested, we envision that multivariate association testing using metaCCA has a great potential to provide novel insights from already published summary statistics from high-throughput phenotyping technologies. Availability and implementation: Code is available at https://github.com/aalto-ics-kepaco Contacts: anna.cichonska@helsinki.fi or matti.pirinen@helsinki.fi Supplementary information: Supplementary data are available at Bioinformatics online. PMID:27153689

Apolipoprotein E Polymorphism and Left Ventricular Failure in Beta-Thalassemia: A Multivariate Meta-Analysis.

PubMed

Dimou, Niki L; Pantavou, Katerina G; Bagos, Pantelis G

2017-09-01

Apolipoprotein E (ApoE) is potentially a genetic risk factor for the development of left ventricular failure (LVF), the main cause of death in beta-thalassemia homozygotes. In the present study, we synthesize the results of independent studies examining the effect of ApoE on LVF development in thalassemic patients through a meta-analytic approach. However, all studies report more than one outcome, as patients are classified into three groups according to the severity of the symptoms and the genetic polymorphism. Thus, a multivariate meta-analytic method that addresses simultaneously multiple exposures and multiple comparison groups was developed. Four individual studies were included in the meta-analysis involving 613 beta-thalassemic patients and 664 controls. The proposed method that takes into account the correlation of log odds ratios (log(ORs)), revealed a statistically significant overall association (P-value  =  0.009), mainly attributed to the contrast of E4 versus E3 allele for patients with evidence (OR: 2.32, 95% CI: 1.19, 4.53) or patients with clinical and echocardiographic findings (OR: 3.34, 95% CI: 1.78, 6.26) of LVF. This study suggests that E4 is a genetic risk factor for LVF in beta-thalassemia major. The presented multivariate approach can be applied in several fields of research. © 2017 John Wiley & Sons Ltd/University College London.

A multivariate twin study of the DSM-IV criteria for antisocial personality disorder.

PubMed

Kendler, Kenneth S; Aggen, Steven H; Patrick, Christopher J

2012-02-01

Many assessment instruments for psychopathy are multidimensional, suggesting that distinguishable factors are needed to effectively capture variation in this personality domain. However, no prior study has examined the factor structure of the DSM-IV criteria for antisocial personality disorder (ASPD). Self-report questionnaire items reflecting all A criteria for DSM-IV ASPD were available from 4291 twins (including both members of 1647 pairs) from the Virginia Adult Study of Psychiatric and Substance Use Disorders. Exploratory factor analysis and twin model fitting were performed using, respectively, Mplus and Mx. Phenotypic factor analysis produced evidence for two correlated factors: aggressive-disregard and disinhibition. The best-fitting multivariate twin model included two genetic and one unique environmental common factor, along with criteria-specific genetic and environmental effects. The two genetic factors closely resembled the phenotypic factors and varied in their prediction of a range of relevant criterion variables. Scores on the genetic aggressive-disregard factor score were more strongly associated with risk for conduct disorder, early and heavy alcohol use, and low educational status, whereas scores on the genetic disinhibition factor score were more strongly associated with younger age, novelty seeking, and major depression. From a genetic perspective, the DSM-IV criteria for ASPD do not reflect a single dimension of liability but rather are influenced by two dimensions of genetic risk reflecting aggressive-disregard and disinhibition. The phenotypic structure of the ASPD criteria results largely from genetic and not from environmental influences. Copyright © 2012 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

Bioinformatics Identification of Modules of Transcription Factor Binding Sites in Alzheimer's Disease-Related Genes by In Silico Promoter Analysis and Microarrays

PubMed Central

Augustin, Regina; Lichtenthaler, Stefan F.; Greeff, Michael; Hansen, Jens; Wurst, Wolfgang; Trümbach, Dietrich

2011-01-01

The molecular mechanisms and genetic risk factors underlying Alzheimer's disease (AD) pathogenesis are only partly understood. To identify new factors, which may contribute to AD, different approaches are taken including proteomics, genetics, and functional genomics. Here, we used a bioinformatics approach and found that distinct AD-related genes share modules of transcription factor binding sites, suggesting a transcriptional coregulation. To detect additional coregulated genes, which may potentially contribute to AD, we established a new bioinformatics workflow with known multivariate methods like support vector machines, biclustering, and predicted transcription factor binding site modules by using in silico analysis and over 400 expression arrays from human and mouse. Two significant modules are composed of three transcription factor families: CTCF, SP1F, and EGRF/ZBPF, which are conserved between human and mouse APP promoter sequences. The specific combination of in silico promoter and multivariate analysis can identify regulation mechanisms of genes involved in multifactorial diseases. PMID:21559189

Use of Multivariate Linkage Analysis for Dissection of a Complex Cognitive Trait

PubMed Central

Marlow, Angela J.; Fisher, Simon E.; Francks, Clyde; MacPhie, I. Laurence; Cherny, Stacey S.; Richardson, Alex J.; Talcott, Joel B.; Stein, John F.; Monaco, Anthony P.; Cardon, Lon R.

2003-01-01

Replication of linkage results for complex traits has been exceedingly difficult, owing in part to the inability to measure the precise underlying phenotype, small sample sizes, genetic heterogeneity, and statistical methods employed in analysis. Often, in any particular study, multiple correlated traits have been collected, yet these have been analyzed independently or, at most, in bivariate analyses. Theoretical arguments suggest that full multivariate analysis of all available traits should offer more power to detect linkage; however, this has not yet been evaluated on a genomewide scale. Here, we conduct multivariate genomewide analyses of quantitative-trait loci that influence reading- and language-related measures in families affected with developmental dyslexia. The results of these analyses are substantially clearer than those of previous univariate analyses of the same data set, helping to resolve a number of key issues. These outcomes highlight the relevance of multivariate analysis for complex disorders for dissection of linkage results in correlated traits. The approach employed here may aid positional cloning of susceptibility genes in a wide spectrum of complex traits. PMID:12587094

Multivariate Analysis of the Cotton Seed Ionome Reveals a Shared Genetic Architecture

PubMed Central

Pauli, Duke; Ziegler, Greg; Ren, Min; Jenks, Matthew A.; Hunsaker, Douglas J.; Zhang, Min; Baxter, Ivan; Gore, Michael A.

2018-01-01

To mitigate the effects of heat and drought stress, a better understanding of the genetic control of physiological responses to these environmental conditions is needed. To this end, we evaluated an upland cotton (Gossypium hirsutum L.) mapping population under water-limited and well-watered conditions in a hot, arid environment. The elemental concentrations (ionome) of seed samples from the population were profiled in addition to those of soil samples taken from throughout the field site to better model environmental variation. The elements profiled in seeds exhibited moderate to high heritabilities, as well as strong phenotypic and genotypic correlations between elements that were not altered by the imposed irrigation regimes. Quantitative trait loci (QTL) mapping results from a Bayesian classification method identified multiple genomic regions where QTL for individual elements colocalized, suggesting that genetic control of the ionome is highly interrelated. To more fully explore this genetic architecture, multivariate QTL mapping was implemented among groups of biochemically related elements. This analysis revealed both additional and pleiotropic QTL responsible for coordinated control of phenotypic variation for elemental accumulation. Machine learning algorithms that utilized only ionomic data predicted the irrigation regime under which genotypes were evaluated with very high accuracy. Taken together, these results demonstrate the extent to which the seed ionome is genetically interrelated and predictive of plant physiological responses to adverse environmental conditions. PMID:29437829

Recent applications of multivariate data analysis methods in the authentication of rice and the most analyzed parameters: A review.

PubMed

Maione, Camila; Barbosa, Rommel Melgaço

2018-01-24

Rice is one of the most important staple foods around the world. Authentication of rice is one of the most addressed concerns in the present literature, which includes recognition of its geographical origin and variety, certification of organic rice and many other issues. Good results have been achieved by multivariate data analysis and data mining techniques when combined with specific parameters for ascertaining authenticity and many other useful characteristics of rice, such as quality, yield and others. This paper brings a review of the recent research projects on discrimination and authentication of rice using multivariate data analysis and data mining techniques. We found that data obtained from image processing, molecular and atomic spectroscopy, elemental fingerprinting, genetic markers, molecular content and others are promising sources of information regarding geographical origin, variety and other aspects of rice, being widely used combined with multivariate data analysis techniques. Principal component analysis and linear discriminant analysis are the preferred methods, but several other data classification techniques such as support vector machines, artificial neural networks and others are also frequently present in some studies and show high performance for discrimination of rice.

GenAlEx 6.5: genetic analysis in Excel. Population genetic software for teaching and research--an update.

PubMed

Peakall, Rod; Smouse, Peter E

2012-10-01

GenAlEx: Genetic Analysis in Excel is a cross-platform package for population genetic analyses that runs within Microsoft Excel. GenAlEx offers analysis of diploid codominant, haploid and binary genetic loci and DNA sequences. Both frequency-based (F-statistics, heterozygosity, HWE, population assignment, relatedness) and distance-based (AMOVA, PCoA, Mantel tests, multivariate spatial autocorrelation) analyses are provided. New features include calculation of new estimators of population structure: G'(ST), G''(ST), Jost's D(est) and F'(ST) through AMOVA, Shannon Information analysis, linkage disequilibrium analysis for biallelic data and novel heterogeneity tests for spatial autocorrelation analysis. Export to more than 30 other data formats is provided. Teaching tutorials and expanded step-by-step output options are included. The comprehensive guide has been fully revised. GenAlEx is written in VBA and provided as a Microsoft Excel Add-in (compatible with Excel 2003, 2007, 2010 on PC; Excel 2004, 2011 on Macintosh). GenAlEx, and supporting documentation and tutorials are freely available at: http://biology.anu.edu.au/GenAlEx. rod.peakall@anu.edu.au.

Application of Multivariate Statistical Analysis to Biomarkers in Se-Turkey Crude Oils

NASA Astrophysics Data System (ADS)

Gürgey, K.; Canbolat, S.

2017-11-01

Twenty-four crude oil samples were collected from the 24 oil fields distributed in different districts of SE-Turkey. API and Sulphur content (%), Stable Carbon Isotope, Gas Chromatography (GC), and Gas Chromatography-Mass Spectrometry (GC-MS) data were used to construct a geochemical data matrix. The aim of this study is to examine the genetic grouping or correlations in the crude oil samples, hence the number of source rocks present in the SE-Turkey. To achieve these aims, two of the multivariate statistical analysis techniques (Principle Component Analysis [PCA] and Cluster Analysis were applied to data matrix of 24 samples and 8 source specific biomarker variables/parameters. The results showed that there are 3 genetically different oil groups: Batman-Nusaybin Oils, Adıyaman-Kozluk Oils and Diyarbakir Oils, in addition to a one mixed group. These groupings imply that at least, three different source rocks are present in South-Eastern (SE) Turkey. Grouping of the crude oil samples appears to be consistent with the geographic locations of the oils fields, subsurface stratigraphy as well as geology of the area.

On measures of association among genetic variables

PubMed Central

Gianola, Daniel; Manfredi, Eduardo; Simianer, Henner

2012-01-01

Summary Systems involving many variables are important in population and quantitative genetics, for example, in multi-trait prediction of breeding values and in exploration of multi-locus associations. We studied departures of the joint distribution of sets of genetic variables from independence. New measures of association based on notions of statistical distance between distributions are presented. These are more general than correlations, which are pairwise measures, and lack a clear interpretation beyond the bivariate normal distribution. Our measures are based on logarithmic (Kullback-Leibler) and on relative ‘distances’ between distributions. Indexes of association are developed and illustrated for quantitative genetics settings in which the joint distribution of the variables is either multivariate normal or multivariate-t, and we show how the indexes can be used to study linkage disequilibrium in a two-locus system with multiple alleles and present applications to systems of correlated beta distributions. Two multivariate beta and multivariate beta-binomial processes are examined, and new distributions are introduced: the GMS-Sarmanov multivariate beta and its beta-binomial counterpart. PMID:22742500

Genetic Overlap Between Schizophrenia and Developmental Psychopathology: Longitudinal and Multivariate Polygenic Risk Prediction of Common Psychiatric Traits During Development.

PubMed

Nivard, Michel G; Gage, Suzanne H; Hottenga, Jouke J; van Beijsterveldt, Catharina E M; Abdellaoui, Abdel; Bartels, Meike; Baselmans, Bart M L; Ligthart, Lannie; Pourcain, Beate St; Boomsma, Dorret I; Munafò, Marcus R; Middeldorp, Christel M

2017-10-21

Several nonpsychotic psychiatric disorders in childhood and adolescence can precede the onset of schizophrenia, but the etiology of this relationship remains unclear. We investigated to what extent the association between schizophrenia and psychiatric disorders in childhood is explained by correlated genetic risk factors. Polygenic risk scores (PRS), reflecting an individual's genetic risk for schizophrenia, were constructed for 2588 children from the Netherlands Twin Register (NTR) and 6127 from the Avon Longitudinal Study of Parents And Children (ALSPAC). The associations between schizophrenia PRS and measures of anxiety, depression, attention deficit hyperactivity disorder (ADHD), and oppositional defiant disorder/conduct disorder (ODD/CD) were estimated at age 7, 10, 12/13, and 15 years in the 2 cohorts. Results were then meta-analyzed, and a meta-regression analysis was performed to test differences in effects sizes over, age and disorders. Schizophrenia PRS were associated with childhood and adolescent psychopathology. Meta-regression analysis showed differences in the associations over disorders, with the strongest association with childhood and adolescent depression and a weaker association for ODD/CD at age 7. The associations increased with age and this increase was steepest for ADHD and ODD/CD. Genetic correlations varied between 0.10 and 0.25. By optimally using longitudinal data across diagnoses in a multivariate meta-analysis this study sheds light on the development of childhood disorders into severe adult psychiatric disorders. The results are consistent with a common genetic etiology of schizophrenia and developmental psychopathology as well as with a stronger shared genetic etiology between schizophrenia and adolescent onset psychopathology. © The Author 2017. Published by Oxford University Press on behalf of the Maryland Psychiatric Research Center. All rights reserved. For permissions, please email: journals.permissions@oup.com

Multivariate studies on the genetics of dermal ridges.

PubMed

Rostron, J

1977-10-01

In order to investigate the inheritance of the series of ten ridgecounts, factor analysis was used to reduce the dimensionability to two. These two factors are inherited more or less independently and the heritability of the first is 0.97.

A Quantitative Comparison of the Similarity between Genes and Geography in Worldwide Human Populations

PubMed Central

Wang, Chaolong; Zöllner, Sebastian; Rosenberg, Noah A.

2012-01-01

Multivariate statistical techniques such as principal components analysis (PCA) and multidimensional scaling (MDS) have been widely used to summarize the structure of human genetic variation, often in easily visualized two-dimensional maps. Many recent studies have reported similarity between geographic maps of population locations and MDS or PCA maps of genetic variation inferred from single-nucleotide polymorphisms (SNPs). However, this similarity has been evident primarily in a qualitative sense; and, because different multivariate techniques and marker sets have been used in different studies, it has not been possible to formally compare genetic variation datasets in terms of their levels of similarity with geography. In this study, using genome-wide SNP data from 128 populations worldwide, we perform a systematic analysis to quantitatively evaluate the similarity of genes and geography in different geographic regions. For each of a series of regions, we apply a Procrustes analysis approach to find an optimal transformation that maximizes the similarity between PCA maps of genetic variation and geographic maps of population locations. We consider examples in Europe, Sub-Saharan Africa, Asia, East Asia, and Central/South Asia, as well as in a worldwide sample, finding that significant similarity between genes and geography exists in general at different geographic levels. The similarity is highest in our examples for Asia and, once highly distinctive populations have been removed, Sub-Saharan Africa. Our results provide a quantitative assessment of the geographic structure of human genetic variation worldwide, supporting the view that geography plays a strong role in giving rise to human population structure. PMID:22927824

A quantitative comparison of the similarity between genes and geography in worldwide human populations.

PubMed

Wang, Chaolong; Zöllner, Sebastian; Rosenberg, Noah A

2012-08-01

Multivariate statistical techniques such as principal components analysis (PCA) and multidimensional scaling (MDS) have been widely used to summarize the structure of human genetic variation, often in easily visualized two-dimensional maps. Many recent studies have reported similarity between geographic maps of population locations and MDS or PCA maps of genetic variation inferred from single-nucleotide polymorphisms (SNPs). However, this similarity has been evident primarily in a qualitative sense; and, because different multivariate techniques and marker sets have been used in different studies, it has not been possible to formally compare genetic variation datasets in terms of their levels of similarity with geography. In this study, using genome-wide SNP data from 128 populations worldwide, we perform a systematic analysis to quantitatively evaluate the similarity of genes and geography in different geographic regions. For each of a series of regions, we apply a Procrustes analysis approach to find an optimal transformation that maximizes the similarity between PCA maps of genetic variation and geographic maps of population locations. We consider examples in Europe, Sub-Saharan Africa, Asia, East Asia, and Central/South Asia, as well as in a worldwide sample, finding that significant similarity between genes and geography exists in general at different geographic levels. The similarity is highest in our examples for Asia and, once highly distinctive populations have been removed, Sub-Saharan Africa. Our results provide a quantitative assessment of the geographic structure of human genetic variation worldwide, supporting the view that geography plays a strong role in giving rise to human population structure.

Heritability of somatotype components: a multivariate analysis.

PubMed

Peeters, M W; Thomis, M A; Loos, R J F; Derom, C A; Fagard, R; Claessens, A L; Vlietinck, R F; Beunen, G P

2007-08-01

To study the genetic and environmental determination of variation in Heath-Carter somatotype (ST) components (endomorphy, mesomorphy and ectomorphy). Multivariate path analysis on twin data. Eight hundred and three members of 424 adult Flemish twin pairs (18-34 years of age). The results indicate the significance of sex differences and the significance of the covariation between the three ST components. After age-regression, variation of the population in ST components and their covariation is explained by additive genetic sources of variance (A), shared (familial) environment (C) and unique environment (E). In men, additive genetic sources of variance explain 28.0% (CI 8.7-50.8%), 86.3% (71.6-90.2%) and 66.5% (37.4-85.1%) for endomorphy, mesomorphy and ectomorphy, respectively. For women, corresponding values are 32.3% (8.9-55.6%), 82.0% (67.7-87.7%) and 70.1% (48.9-81.8%). For all components in men and women, more than 70% of the total variation was explained by sources of variance shared between the three components, emphasising the importance of analysing the ST in a multivariate way. The findings suggest that the high heritabilities for mesomorphy and ectomorphy reported in earlier twin studies in adolescence are maintained in adulthood. For endomorphy, which represents a relative measure of subcutaneous adipose tissue, however, the results suggest heritability may be considerably lower than most values reported in earlier studies on adolescent twins. The heritability is also lower than values reported for, for example, body mass index (BMI), which next to the weight of organs and adipose tissue also includes muscle and bone tissue. Considering the differences in heritability between musculoskeletal robustness (mesomorphy) and subcutaneous adipose tissue (endomorphy) it may be questioned whether studying the genetics of BMI will eventually lead to a better understanding of the genetics of fatness, obesity and overweight.

Assessing Multivariate Constraints to Evolution across Ten Long-Term Avian Studies

PubMed Central

Teplitsky, Celine; Tarka, Maja; Møller, Anders P.; Nakagawa, Shinichi; Balbontín, Javier; Burke, Terry A.; Doutrelant, Claire; Gregoire, Arnaud; Hansson, Bengt; Hasselquist, Dennis; Gustafsson, Lars; de Lope, Florentino; Marzal, Alfonso; Mills, James A.; Wheelwright, Nathaniel T.; Yarrall, John W.; Charmantier, Anne

2014-01-01

Background In a rapidly changing world, it is of fundamental importance to understand processes constraining or facilitating adaptation through microevolution. As different traits of an organism covary, genetic correlations are expected to affect evolutionary trajectories. However, only limited empirical data are available. Methodology/Principal Findings We investigate the extent to which multivariate constraints affect the rate of adaptation, focusing on four morphological traits often shown to harbour large amounts of genetic variance and considered to be subject to limited evolutionary constraints. Our data set includes unique long-term data for seven bird species and a total of 10 populations. We estimate population-specific matrices of genetic correlations and multivariate selection coefficients to predict evolutionary responses to selection. Using Bayesian methods that facilitate the propagation of errors in estimates, we compare (1) the rate of adaptation based on predicted response to selection when including genetic correlations with predictions from models where these genetic correlations were set to zero and (2) the multivariate evolvability in the direction of current selection to the average evolvability in random directions of the phenotypic space. We show that genetic correlations on average decrease the predicted rate of adaptation by 28%. Multivariate evolvability in the direction of current selection was systematically lower than average evolvability in random directions of space. These significant reductions in the rate of adaptation and reduced evolvability were due to a general nonalignment of selection and genetic variance, notably orthogonality of directional selection with the size axis along which most (60%) of the genetic variance is found. Conclusions These results suggest that genetic correlations can impose significant constraints on the evolution of avian morphology in wild populations. This could have important impacts on evolutionary dynamics and hence population persistence in the face of rapid environmental change. PMID:24608111

Applying Multivariate Discrete Distributions to Genetically Informative Count Data.

PubMed

Kirkpatrick, Robert M; Neale, Michael C

2016-03-01

We present a novel method of conducting biometric analysis of twin data when the phenotypes are integer-valued counts, which often show an L-shaped distribution. Monte Carlo simulation is used to compare five likelihood-based approaches to modeling: our multivariate discrete method, when its distributional assumptions are correct, when they are incorrect, and three other methods in common use. With data simulated from a skewed discrete distribution, recovery of twin correlations and proportions of additive genetic and common environment variance was generally poor for the Normal, Lognormal and Ordinal models, but good for the two discrete models. Sex-separate applications to substance-use data from twins in the Minnesota Twin Family Study showed superior performance of two discrete models. The new methods are implemented using R and OpenMx and are freely available.

Constrained evolution of the sex comb in Drosophila simulans.

PubMed

Maraqa, M S; Griffin, R; Sharma, M D; Wilson, A J; Hunt, J; Hosken, D J; House, C M

2017-02-01

Male fitness is dependent on sexual traits that influence mate acquisition (precopulatory sexual selection) and paternity (post-copulatory sexual selection), and although many studies have documented the form of selection in one or the other of these arenas, fewer have done it for both. Nonetheless, it appears that the dominant form of sexual selection is directional, although theoretically, populations should converge on peaks in the fitness surface, where selection is stabilizing. Many factors, however, can prevent populations from reaching adaptive peaks. Genetic constraints can be important if they prevent the development of highest fitness phenotypes, as can the direction of selection if it reverses across episodes of selection. In this study, we examine the evidence that these processes influence the evolution of the multivariate sex comb morphology of male Drosophila simulans. To do this, we conduct a quantitative genetic study together with a multivariate selection analysis to infer how the genetic architecture and selection interact. We find abundant genetic variance and covariance in elements of the sex comb. However, there was little evidence for directional selection in either arena. Significant nonlinear selection was detected prior to copulation when males were mated to nonvirgin females, and post-copulation during sperm offence (again with males mated to nonvirgins). Thus, contrary to our predictions, the evolution of the D. simulans sex comb is limited neither by genetic constraints nor by antagonistic selection between pre- and post-copulatory arenas, but nonlinear selection on the multivariate phenotype may prevent sex combs from evolving to reach some fitness maximizing optima. © 2016 The Authors. Journal of Evolutionary Biology © 2016 European Society For Evolutionary Biology.

G/SPLINES: A hybrid of Friedman's Multivariate Adaptive Regression Splines (MARS) algorithm with Holland's genetic algorithm

NASA Technical Reports Server (NTRS)

Rogers, David

1991-01-01

G/SPLINES are a hybrid of Friedman's Multivariable Adaptive Regression Splines (MARS) algorithm with Holland's Genetic Algorithm. In this hybrid, the incremental search is replaced by a genetic search. The G/SPLINE algorithm exhibits performance comparable to that of the MARS algorithm, requires fewer least squares computations, and allows significantly larger problems to be considered.

GenAlEx 6.5: genetic analysis in Excel. Population genetic software for teaching and research—an update

PubMed Central

Peakall, Rod; Smouse, Peter E.

2012-01-01

Summary: GenAlEx: Genetic Analysis in Excel is a cross-platform package for population genetic analyses that runs within Microsoft Excel. GenAlEx offers analysis of diploid codominant, haploid and binary genetic loci and DNA sequences. Both frequency-based (F-statistics, heterozygosity, HWE, population assignment, relatedness) and distance-based (AMOVA, PCoA, Mantel tests, multivariate spatial autocorrelation) analyses are provided. New features include calculation of new estimators of population structure: G′ST, G′′ST, Jost’s Dest and F′ST through AMOVA, Shannon Information analysis, linkage disequilibrium analysis for biallelic data and novel heterogeneity tests for spatial autocorrelation analysis. Export to more than 30 other data formats is provided. Teaching tutorials and expanded step-by-step output options are included. The comprehensive guide has been fully revised. Availability and implementation: GenAlEx is written in VBA and provided as a Microsoft Excel Add-in (compatible with Excel 2003, 2007, 2010 on PC; Excel 2004, 2011 on Macintosh). GenAlEx, and supporting documentation and tutorials are freely available at: http://biology.anu.edu.au/GenAlEx. Contact: rod.peakall@anu.edu.au PMID:22820204

Sparse multivariate factor analysis regression models and its applications to integrative genomics analysis.

PubMed

Zhou, Yan; Wang, Pei; Wang, Xianlong; Zhu, Ji; Song, Peter X-K

2017-01-01

The multivariate regression model is a useful tool to explore complex associations between two kinds of molecular markers, which enables the understanding of the biological pathways underlying disease etiology. For a set of correlated response variables, accounting for such dependency can increase statistical power. Motivated by integrative genomic data analyses, we propose a new methodology-sparse multivariate factor analysis regression model (smFARM), in which correlations of response variables are assumed to follow a factor analysis model with latent factors. This proposed method not only allows us to address the challenge that the number of association parameters is larger than the sample size, but also to adjust for unobserved genetic and/or nongenetic factors that potentially conceal the underlying response-predictor associations. The proposed smFARM is implemented by the EM algorithm and the blockwise coordinate descent algorithm. The proposed methodology is evaluated and compared to the existing methods through extensive simulation studies. Our results show that accounting for latent factors through the proposed smFARM can improve sensitivity of signal detection and accuracy of sparse association map estimation. We illustrate smFARM by two integrative genomics analysis examples, a breast cancer dataset, and an ovarian cancer dataset, to assess the relationship between DNA copy numbers and gene expression arrays to understand genetic regulatory patterns relevant to the disease. We identify two trans-hub regions: one in cytoband 17q12 whose amplification influences the RNA expression levels of important breast cancer genes, and the other in cytoband 9q21.32-33, which is associated with chemoresistance in ovarian cancer. © 2016 WILEY PERIODICALS, INC.

Multivariate selection and intersexual genetic constraints in a wild bird population.

PubMed

Poissant, J; Morrissey, M B; Gosler, A G; Slate, J; Sheldon, B C

2016-10-01

When selection differs between the sexes for traits that are genetically correlated between the sexes, there is potential for the effect of selection in one sex to be altered by indirect selection in the other sex, a situation commonly referred to as intralocus sexual conflict (ISC). While potentially common, ISC has rarely been studied in wild populations. Here, we studied ISC over a set of morphological traits (wing length, tarsus length, bill depth and bill length) in a wild population of great tits (Parus major) from Wytham Woods, UK. Specifically, we quantified the microevolutionary impacts of ISC by combining intra- and intersex additive genetic (co)variances and sex-specific selection estimates in a multivariate framework. Large genetic correlations between homologous male and female traits combined with evidence for sex-specific multivariate survival selection suggested that ISC could play an appreciable role in the evolution of this population. Together, multivariate sex-specific selection and additive genetic (co)variance for the traits considered accounted for additive genetic variance in fitness that was uncorrelated between the sexes (cross-sex genetic correlation = -0.003, 95% CI = -0.83, 0.83). Gender load, defined as the reduction in a population's rate of adaptation due to sex-specific effects, was estimated at 50% (95% CI = 13%, 86%). This study provides novel insights into the evolution of sexual dimorphism in wild populations and illustrates how quantitative genetics and selection analyses can be combined in a multivariate framework to quantify the microevolutionary impacts of ISC. © 2016 European Society For Evolutionary Biology. Journal of Evolutionary Biology © 2016 European Society For Evolutionary Biology.

Restricted maximum likelihood estimation of genetic principal components and smoothed covariance matrices

PubMed Central

Meyer, Karin; Kirkpatrick, Mark

2005-01-01

Principal component analysis is a widely used 'dimension reduction' technique, albeit generally at a phenotypic level. It is shown that we can estimate genetic principal components directly through a simple reparameterisation of the usual linear, mixed model. This is applicable to any analysis fitting multiple, correlated genetic effects, whether effects for individual traits or sets of random regression coefficients to model trajectories. Depending on the magnitude of genetic correlation, a subset of the principal component generally suffices to capture the bulk of genetic variation. Corresponding estimates of genetic covariance matrices are more parsimonious, have reduced rank and are smoothed, with the number of parameters required to model the dispersion structure reduced from k(k + 1)/2 to m(2k - m + 1)/2 for k effects and m principal components. Estimation of these parameters, the largest eigenvalues and pertaining eigenvectors of the genetic covariance matrix, via restricted maximum likelihood using derivatives of the likelihood, is described. It is shown that reduced rank estimation can reduce computational requirements of multivariate analyses substantially. An application to the analysis of eight traits recorded via live ultrasound scanning of beef cattle is given. PMID:15588566

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

Generalist genes and the Internet generation: etiology of learning abilities by web testing at age 10.

PubMed

Davis, O S P; Kovas, Y; Harlaar, N; Busfield, P; McMillan, A; Frances, J; Petrill, S A; Dale, P S; Plomin, R

2008-06-01

A key translational issue for neuroscience is to understand how genes affect individual differences in brain function. Although it is reasonable to suppose that genetic effects on specific learning abilities, such as reading and mathematics, as well as general cognitive ability (g), will overlap very little, the counterintuitive finding emerging from multivariate genetic studies is that the same genes affect these diverse learning abilities: a Generalist Genes hypothesis. To conclusively test this hypothesis, we exploited the widespread access to inexpensive and fast Internet connections in the UK to assess 2541 pairs of 10-year-old twins for reading, mathematics and g, using a web-based test battery. Heritabilities were 0.38 for reading, 0.49 for mathematics and 0.44 for g. Multivariate genetic analysis showed substantial genetic correlations between learning abilities: 0.57 between reading and mathematics, 0.61 between reading and g, and 0.75 between mathematics and g, providing strong support for the Generalist Genes hypothesis. If genetic effects on cognition are so general, the effects of these genes on the brain are also likely to be general. In this way, generalist genes may prove invaluable in integrating top-down and bottom-up approaches to the systems biology of the brain.

Functional Regression Models for Epistasis Analysis of Multiple Quantitative Traits.

PubMed

Zhang, Futao; Xie, Dan; Liang, Meimei; Xiong, Momiao

2016-04-01

To date, most genetic analyses of phenotypes have focused on analyzing single traits or analyzing each phenotype independently. However, joint epistasis analysis of multiple complementary traits will increase statistical power and improve our understanding of the complicated genetic structure of the complex diseases. Despite their importance in uncovering the genetic structure of complex traits, the statistical methods for identifying epistasis in multiple phenotypes remains fundamentally unexplored. To fill this gap, we formulate a test for interaction between two genes in multiple quantitative trait analysis as a multiple functional regression (MFRG) in which the genotype functions (genetic variant profiles) are defined as a function of the genomic position of the genetic variants. We use large-scale simulations to calculate Type I error rates for testing interaction between two genes with multiple phenotypes and to compare the power with multivariate pairwise interaction analysis and single trait interaction analysis by a single variate functional regression model. To further evaluate performance, the MFRG for epistasis analysis is applied to five phenotypes of exome sequence data from the NHLBI's Exome Sequencing Project (ESP) to detect pleiotropic epistasis. A total of 267 pairs of genes that formed a genetic interaction network showed significant evidence of epistasis influencing five traits. The results demonstrate that the joint interaction analysis of multiple phenotypes has a much higher power to detect interaction than the interaction analysis of a single trait and may open a new direction to fully uncovering the genetic structure of multiple phenotypes.

Dominance Genetic Variance for Traits Under Directional Selection in Drosophila serrata

PubMed Central

Sztepanacz, Jacqueline L.; Blows, Mark W.

2015-01-01

In contrast to our growing understanding of patterns of additive genetic variance in single- and multi-trait combinations, the relative contribution of nonadditive genetic variance, particularly dominance variance, to multivariate phenotypes is largely unknown. While mechanisms for the evolution of dominance genetic variance have been, and to some degree remain, subject to debate, the pervasiveness of dominance is widely recognized and may play a key role in several evolutionary processes. Theoretical and empirical evidence suggests that the contribution of dominance variance to phenotypic variance may increase with the correlation between a trait and fitness; however, direct tests of this hypothesis are few. Using a multigenerational breeding design in an unmanipulated population of Drosophila serrata, we estimated additive and dominance genetic covariance matrices for multivariate wing-shape phenotypes, together with a comprehensive measure of fitness, to determine whether there is an association between directional selection and dominance variance. Fitness, a trait unequivocally under directional selection, had no detectable additive genetic variance, but significant dominance genetic variance contributing 32% of the phenotypic variance. For single and multivariate morphological traits, however, no relationship was observed between trait–fitness correlations and dominance variance. A similar proportion of additive and dominance variance was found to contribute to phenotypic variance for single traits, and double the amount of additive compared to dominance variance was found for the multivariate trait combination under directional selection. These data suggest that for many fitness components a positive association between directional selection and dominance genetic variance may not be expected. PMID:25783700

Evaluating the role of admixture in cancer therapy via in vitro drug response and multivariate genome-wide associations

PubMed Central

Jack, John; Havener, Tammy M; McLeod, Howard L; Motsinger-Reif, Alison A; Foster, Matthew

2015-01-01

Aim: We investigate the role of ethnicity and admixture in drug response across a broad group of chemotherapeutic drugs. Also, we generate hypotheses on the genetic variants driving differential drug response through multivariate genome-wide association studies. Methods: Immortalized lymphoblastoid cell lines from 589 individuals (Hispanic or non-Hispanic/Caucasian) were used to investigate dose-response for 28 chemotherapeutic compounds. Univariate and multivariate statistical models were used to elucidate associations between genetic variants and differential drug response as well as the role of ethnicity in drug potency and efficacy. Results & Conclusion: For many drugs, the variability in drug response appears to correlate with self-reported race and estimates of genetic ancestry. Additionally, multivariate genome-wide association analyses offered interesting hypotheses governing these differential responses. PMID:26314407

Diversity in phenotypic and nutritional traits in vegetable amaranth (Amaranthus tricolor), a nutritionally underutilised crop.

PubMed

Shukla, Sudhir; Bhargava, Atul; Chatterjee, Avijeet; Pandey, Avinash Chandra; Mishra, Brij K

2010-01-15

Assessment of genetic diversity in a crop-breeding programme helps in the identification of diverse parental combinations to create segregating progenies with maximum genetic variability and facilitates introgression of desirable genes from diverse germplasm into the available genetic base. In the present study, 39 strains of vegetable amaranth (Amaranthus tricolor) were evaluated for eight morphological and seven quality traits for two test seasons to study the extent of genetic divergence among the strains. Multivariate analysis showed that the first four principal components contributed 67.55% of the variability. Cluster analysis grouped the strains into six clusters that displayed a wide range of diversity for most of the traits. Cluster analysis has proved to be an effective method in grouping strains that may facilitate effective management and utilisation in crop-breeding programmes. The diverse strains falling in different clusters were identified, which can be utilised in different hybridisation programmes to develop high-foliage-yielding varieties rich in nutritional components. Copyright (c) 2009 Society of Chemical Industry.

Mapping the Schizophrenia Genes by Neuroimaging: The Opportunities and the Challenges

PubMed Central

2018-01-01

Schizophrenia (SZ) is a heritable brain disease originating from a complex interaction of genetic and environmental factors. The genes underpinning the neurobiology of SZ are largely unknown but recent data suggest strong evidence for genetic variations, such as single nucleotide polymorphisms, making the brain vulnerable to the risk of SZ. Structural and functional brain mapping of these genetic variations are essential for the development of agents and tools for better diagnosis, treatment and prevention of SZ. Addressing this, neuroimaging methods in combination with genetic analysis have been increasingly used for almost 20 years. So-called imaging genetics, the opportunities of this approach along with its limitations for SZ research will be outlined in this invited paper. While the problems such as reproducibility, genetic effect size, specificity and sensitivity exist, opportunities such as multivariate analysis, development of multisite consortia for large-scale data collection, emergence of non-candidate gene (hypothesis-free) approach of neuroimaging genetics are likely to contribute to a rapid progress for gene discovery besides to gene validation studies that are related to SZ. PMID:29324666

Simultaneous Analysis of the Behavioural Phenotype, Physical Factors, and Parenting Stress in People with Cornelia De Lange Syndrome

ERIC Educational Resources Information Center

Wulffaert, J.; van Berckelaer-Onnes, I.; Kroonenberg, P.; Scholte, E.; Bhuiyan, Z.; Hennekam, R.

2009-01-01

Background: Studies into the phenotype of rare genetic syndromes largely rely on bivariate analysis. The aim of this study was to describe the phenotype of Cornelia de Lange syndrome (CdLS) in depth by examining a large number of variables with varying measurement levels. Virtually the only suitable multivariate technique for this is categorical…

Dominance genetic variance for traits under directional selection in Drosophila serrata.

PubMed

Sztepanacz, Jacqueline L; Blows, Mark W

2015-05-01

In contrast to our growing understanding of patterns of additive genetic variance in single- and multi-trait combinations, the relative contribution of nonadditive genetic variance, particularly dominance variance, to multivariate phenotypes is largely unknown. While mechanisms for the evolution of dominance genetic variance have been, and to some degree remain, subject to debate, the pervasiveness of dominance is widely recognized and may play a key role in several evolutionary processes. Theoretical and empirical evidence suggests that the contribution of dominance variance to phenotypic variance may increase with the correlation between a trait and fitness; however, direct tests of this hypothesis are few. Using a multigenerational breeding design in an unmanipulated population of Drosophila serrata, we estimated additive and dominance genetic covariance matrices for multivariate wing-shape phenotypes, together with a comprehensive measure of fitness, to determine whether there is an association between directional selection and dominance variance. Fitness, a trait unequivocally under directional selection, had no detectable additive genetic variance, but significant dominance genetic variance contributing 32% of the phenotypic variance. For single and multivariate morphological traits, however, no relationship was observed between trait-fitness correlations and dominance variance. A similar proportion of additive and dominance variance was found to contribute to phenotypic variance for single traits, and double the amount of additive compared to dominance variance was found for the multivariate trait combination under directional selection. These data suggest that for many fitness components a positive association between directional selection and dominance genetic variance may not be expected. Copyright © 2015 by the Genetics Society of America.

Genetic polymorphisms and the risk of stroke after cardiac surgery.

PubMed

Grocott, Hilary P; White, William D; Morris, Richard W; Podgoreanu, Mihai V; Mathew, Joseph P; Nielsen, Dahlia M; Schwinn, Debra A; Newman, Mark F

2005-09-01

Stroke represents a significant cause of morbidity and mortality after cardiac surgery. Although the risk of stroke varies according to both patient and procedural factors, the impact of genetic variants on stroke risk is not well understood. Therefore, we tested the hypothesis that specific genetic polymorphisms are associated with an increased risk of stroke after cardiac surgery. Patients undergoing cardiac surgery utilizing cardiopulmonary bypass surgery were studied. DNA was isolated from preoperative blood and analyzed for 26 different single-nucleotide polymorphisms. Multivariable logistic regression modeling was used to determine the association of clinical and genetic characteristics with stroke. Permutation analysis was used to adjust for multiple comparisons inherent in genetic association studies. A total of 1635 patients experiencing 28 strokes (1.7%) were included in the final genetic model. The combination of the 2 minor alleles of C-reactive protein (CRP; 3'UTR 1846C/T) and interleukin-6 (IL-6; -174G/C) polymorphisms, occurring in 583 (35.7%) patients, was significantly associated with stroke (odds ratio, 3.3; 95% CI, 1.4 to 8.1; P=0.0023). In a multivariable logistic model adjusting for age, the CRP and IL-6 single-nucleotide polymorphism combination remained significantly associated with stroke (P=0.0020). We demonstrate that common genetic variants of CRP (3'UTR 1846C/T) and IL-6 (-174G/C) are significantly associated with the risk of stroke after cardiac surgery, suggesting a pivotal role of inflammation in post-cardiac surgery stroke.

A novel structure-aware sparse learning algorithm for brain imaging genetics.

PubMed

Du, Lei; Jingwen, Yan; Kim, Sungeun; Risacher, Shannon L; Huang, Heng; Inlow, Mark; Moore, Jason H; Saykin, Andrew J; Shen, Li

2014-01-01

Brain imaging genetics is an emergent research field where the association between genetic variations such as single nucleotide polymorphisms (SNPs) and neuroimaging quantitative traits (QTs) is evaluated. Sparse canonical correlation analysis (SCCA) is a bi-multivariate analysis method that has the potential to reveal complex multi-SNP-multi-QT associations. Most existing SCCA algorithms are designed using the soft threshold strategy, which assumes that the features in the data are independent from each other. This independence assumption usually does not hold in imaging genetic data, and thus inevitably limits the capability of yielding optimal solutions. We propose a novel structure-aware SCCA (denoted as S2CCA) algorithm to not only eliminate the independence assumption for the input data, but also incorporate group-like structure in the model. Empirical comparison with a widely used SCCA implementation, on both simulated and real imaging genetic data, demonstrated that S2CCA could yield improved prediction performance and biologically meaningful findings.

‘Generalist genes’ and mathematics in 7-year-old twins

PubMed Central

Kovas, Y.; Harlaar, N.; Petrill, S. A.; Plomin, R.

2009-01-01

Mathematics performance at 7 years as assessed by teachers using UK national curriculum criteria has been found to be highly heritable. For almost 3000 pairs of 7-year-old same-sex twins, we used multivariate genetic analysis to investigate the extent to which these genetic effects on mathematics performance overlap with genetic effects on reading and general intelligence (g) as predicted by the ‘generalist genes’ hypothesis. We found substantial genetic overlap between mathematics and reading (genetic correlation=0.74) and between mathematics and g (0.67). These findings support the ‘generalist genes’ hypothesis that most of the genes that contribute to individual differences in mathematics are the same genes that affect reading and g. Nonetheless, the genetic correlations are less than unity and about a third of the genetic variance on mathematics is independent of reading and g, suggesting that there are also some genes whose effects are specific to mathematics. PMID:19319204

MAOA, MTHFR, and TNF-β genes polymorphisms and personality traits in the pathogenesis of migraine.

PubMed

Ishii, Masakazu; Shimizu, Shunichi; Sakairi, Yuki; Nagamine, Ayumu; Naito, Yuika; Hosaka, Yukiko; Naito, Yuko; Kurihara, Tatsuya; Onaya, Tomomi; Oyamada, Hideto; Imagawa, Atsuko; Shida, Kenji; Takahashi, Johji; Oguchi, Katsuji; Masuda, Yutaka; Hara, Hajime; Usami, Shino; Kiuchi, Yuji

2012-04-01

Migraine is a multifactorial disease with various factors, such as genetic polymorphisms and personality traits, but the contribution of those factors is not clear. To clarify the pathogenesis of migraine, the contributions of genetic polymorphisms and personality traits were simultaneously investigated using multivariate analysis. Ninety-one migraine patients and 119 non-headache healthy volunteers were enrolled. The 12 gene polymorphisms analysis and NEO-FFI personality test were performed. At first, the univariate analysis was performed to extract the contributing factors to pathogenesis of migraine. We then extracted the factors that independently contributed to the pathogenesis of migraine using multivariate stepwise logistic regression analysis. Using the multivariate analysis, three gene polymorphisms including monoamine oxidase A (MAOA) T941G, methylenetetrahydrofolate reductase (MTHFR) C677T, and tumor necrosis factor beta (TNF-β) G252Α, and the neuroticism and conscientiousness scores in NEO-FFI were selected as significant factors that independently contributed to the pathogenesis of migraine. Their odds ratios were 1.099 (per point of neuroticism score), 1.080 (per point of conscientiousness score), 2.272 (T and T/T or T/G vs G and G/G genotype of MAOA), 1.939 (C/T or T/T vs C/C genotype of MTHFR), and 2.748 (G/A or A/A vs G/G genotype of TNF-β), respectively. We suggested that multiple factors, such as gene polymorphisms and personality traits, contribute to the pathogenesis of migraine. The contribution of polymorphisms, such as MAOA T941G, MTHFR C677T, and TNF-β G252A, were more important than personality traits in the pathogenesis of migraine, a multifactorial disorder.

Biodemographic Modeling of the Links Between Fertility Motivation and Fertility Outcomes in the NLSY79

PubMed Central

MILLER, WARREN B.; BARD, DAVID E.; PASTA, DAVID J.; RODGERS, JOSEPH LEE

2010-01-01

In spite of long-held beliefs that traits related to reproductive success tend to become fixed by evolution with little or no genetic variation, there is now considerable evidence that the natural variation of fertility within populations is genetically influenced and that a portion of that influence is related to the motivational precursors to fertility. We conduct a two-stage analysis to examine these inferences in a time-ordered multivariate context. First, using data from the National Longitudinal Survey of Youth, 1979, and LISREL analysis, we develop a structural equation model in which five hypothesized motivational precursors to fertility, measured in 1979–1982, predict both a child-timing and a child-number outcome, measured in 2002. Second, having chosen two time-ordered sequences of six variables from the SEM to represent our phenotypic models, we use Mx to conduct both univariate and multivariate behavioral genetic analyses with the selected variables. Our results indicate that one or more genes acting within a gene network have additive effects that operate through child-number desires to affect both the timing of the next child born and the final number of children born, that one or more genes acting through a separate network may have additive effects operating through gender role attitudes to produce downstream effects on the two fertility outcomes, and that no genetic variance is associated with either child-timing intentions or educational intentions. PMID:20608103

Structural equation models based on multivariate diversity assessment of diploid and tetraploid hulled wheat species

USDA-ARS?s Scientific Manuscript database

Hulled wheats are largely untapped genetic resources with >10,000 years of genetic memory and diversity that can be used for wheat quality improvement, development of healthy products, and adaptation to climate change. Multivariate diversity was assessed in the diploid Triticum monococcum L. var mon...

Heritability of somatotype components from early adolescence into young adulthood: a multivariate analysis on a longitudinal twin study.

PubMed

Peeters, M W; Thomis, M A; Claessens, A L; Loos, R J F; Maes, H H M; Lysens, R; Vanden Eynde, B; Vlietinck, R; Beunen, G

2003-01-01

Several studies with different designs have attempted to estimate the heritability of somatotype components. However they often ignore the covariation between the three components as well as possible sex and age effects. Shared environmental factors are not always controlled for. This study explores the pattern of genetic and environmental determination of the variation in Heath-Carter somatotype components from early adolescence into young adulthood. Data from the Leuven Longitudinal Twin Study, a longitudinal sample of Belgian same-aged twins followed from 10 to 18 years (n = 105 pairs, equally divided over five zygosity groups), is entered into a multivariate path analysis. Thus the covariation between the somatotype components is taken into account, gender heterogeneity can be tested, common environmental influences can be distinguished from genetic effects and age effects are controlled for. Heritability estimates from 10 to 18 years range from 0.21 to 0.88, 0.46 to 0.76 and 0.16 to 0.73 for endomorphy, mesomorphy and ectomorphy in boys. In girls, heritability estimates range from 0.76 to 0.89, 0.36 to 0.57 and 0.57 to 0.76 for the respective somatotype components. Sex differences are significant from 14 years onwards. More than half of the variance in all somatotype components for both sexes at all time points is explained by factors the three components have in common. The finding of substantial genetic influence on the variability of somatotype components is further supported. The need to consider somatotype as a whole is stressed as well as the need for sex- and perhaps age-specific analyses. Further multivariate analyses are needed to confirm the present findings.

Multivariate analysis of maize disease resistances suggests a pleiotropic genetic basis and implicates a glutathione S-transferase gene

USDA-ARS?s Scientific Manuscript database

Plants are attacked by pathogens representing diverse taxonomic groups, such that genes providing multiple disease resistance (MDR) would likely be under positive selection pressure. We examined the novel proposition that naturally occurring allelic variants may confer MDR. To do so, we applied a ...

Comparative artificial neural network and partial least squares models for analysis of Metronidazole, Diloxanide, Spiramycin and Cliquinol in pharmaceutical preparations.

PubMed

Elkhoudary, Mahmoud M; Abdel Salam, Randa A; Hadad, Ghada M

2014-09-15

Metronidazole (MNZ) is a widely used antibacterial and amoebicide drug. Therefore, it is important to develop a rapid and specific analytical method for the determination of MNZ in mixture with Spiramycin (SPY), Diloxanide (DIX) and Cliquinol (CLQ) in pharmaceutical preparations. This work describes simple, sensitive and reliable six multivariate calibration methods, namely linear and nonlinear artificial neural networks preceded by genetic algorithm (GA-ANN) and principle component analysis (PCA-ANN) as well as partial least squares (PLS) either alone or preceded by genetic algorithm (GA-PLS) for UV spectrophotometric determination of MNZ, SPY, DIX and CLQ in pharmaceutical preparations with no interference of pharmaceutical additives. The results manifest the problem of nonlinearity and how models like ANN can handle it. Analytical performance of these methods was statistically validated with respect to linearity, accuracy, precision and specificity. The developed methods indicate the ability of the previously mentioned multivariate calibration models to handle and solve UV spectra of the four components' mixtures using easy and widely used UV spectrophotometer. Copyright © 2014 Elsevier B.V. All rights reserved.

Comparative multivariate analysis of biometric traits of West African Dwarf and Red Sokoto goats.

PubMed

Yakubu, Abdulmojeed; Salako, Adebowale E; Imumorin, Ikhide G

2011-03-01

The population structure of 302 randomly selected West African Dwarf (WAD) and Red Sokoto (RS) goats was examined using multivariate morphometric analyses. This was to make the case for conservation, rational management and genetic improvement of these two most important Nigerian goat breeds. Fifteen morphometric measurements were made on each individual animal. RS goats were superior (P<0.05) to the WAD for the body size and skeletal proportions investigated. The phenotypic variability between the two breeds was revealed by their mutual responses in the principal components. While four principal components were extracted for WAD goats, three components were obtained for their RS counterparts with variation in the loading traits of each component for each breed. The Mahalanobis distance of 72.28 indicated a high degree of spatial racial separation in morphology between the genotypes. The Ward's option of the cluster analysis consolidated the morphometric distinctness of the two breeds. Application of selective breeding to genetic improvement would benefit from the detected phenotypic differentiation. Other implications for management and conservation of the goats are highlighted.

Comparative artificial neural network and partial least squares models for analysis of Metronidazole, Diloxanide, Spiramycin and Cliquinol in pharmaceutical preparations

NASA Astrophysics Data System (ADS)

Elkhoudary, Mahmoud M.; Abdel Salam, Randa A.; Hadad, Ghada M.

2014-09-01

Metronidazole (MNZ) is a widely used antibacterial and amoebicide drug. Therefore, it is important to develop a rapid and specific analytical method for the determination of MNZ in mixture with Spiramycin (SPY), Diloxanide (DIX) and Cliquinol (CLQ) in pharmaceutical preparations. This work describes simple, sensitive and reliable six multivariate calibration methods, namely linear and nonlinear artificial neural networks preceded by genetic algorithm (GA-ANN) and principle component analysis (PCA-ANN) as well as partial least squares (PLS) either alone or preceded by genetic algorithm (GA-PLS) for UV spectrophotometric determination of MNZ, SPY, DIX and CLQ in pharmaceutical preparations with no interference of pharmaceutical additives. The results manifest the problem of nonlinearity and how models like ANN can handle it. Analytical performance of these methods was statistically validated with respect to linearity, accuracy, precision and specificity. The developed methods indicate the ability of the previously mentioned multivariate calibration models to handle and solve UV spectra of the four components’ mixtures using easy and widely used UV spectrophotometer.

Stability indicating methods for the analysis of cefprozil in the presence of its alkaline induced degradation product

NASA Astrophysics Data System (ADS)

Attia, Khalid A. M.; Nassar, Mohammed W. I.; El-Zeiny, Mohamed B.; Serag, Ahmed

2016-04-01

Three simple, specific, accurate and precise spectrophotometric methods were developed for the determination of cefprozil (CZ) in the presence of its alkaline induced degradation product (DCZ). The first method was the bivariate method, while the two other multivariate methods were partial least squares (PLS) and spectral residual augmented classical least squares (SRACLS). The multivariate methods were applied with and without variable selection procedure (genetic algorithm GA). These methods were tested by analyzing laboratory prepared mixtures of the above drug with its alkaline induced degradation product and they were applied to its commercial pharmaceutical products.

Population genetic structure in a social landscape: barley in a traditional Ethiopian agricultural system

PubMed Central

Samberg, Leah H; Fishman, Lila; Allendorf, Fred W

2013-01-01

Conservation strategies are increasingly driven by our understanding of the processes and patterns of gene flow across complex landscapes. The expansion of population genetic approaches into traditional agricultural systems requires understanding how social factors contribute to that landscape, and thus to gene flow. This study incorporates extensive farmer interviews and population genetic analysis of barley landraces (Hordeum vulgare) to build a holistic picture of farmer-mediated geneflow in an ancient, traditional agricultural system in the highlands of Ethiopia. We analyze barley samples at 14 microsatellite loci across sites at varying elevations and locations across a contiguous mountain range, and across farmer-identified barley types and management strategies. Genetic structure is analyzed using population-based and individual-based methods, including measures of population differentiation and genetic distance, multivariate Principal Coordinate Analysis, and Bayesian assignment tests. Phenotypic analysis links genetic patterns to traits identified by farmers. We find that differential farmer management strategies lead to markedly different patterns of population structure across elevation classes and barley types. The extent to which farmer seed management appears as a stronger determinant of spatial structure than the physical landscape highlights the need for incorporation of social, landscape, and genetic data for the design of conservation strategies in human-influenced landscapes. PMID:24478796

Analysis of algae growth mechanism and water bloom prediction under the effect of multi-affecting factor.

PubMed

Wang, Li; Wang, Xiaoyi; Jin, Xuebo; Xu, Jiping; Zhang, Huiyan; Yu, Jiabin; Sun, Qian; Gao, Chong; Wang, Lingbin

2017-03-01

The formation process of algae is described inaccurately and water blooms are predicted with a low precision by current methods. In this paper, chemical mechanism of algae growth is analyzed, and a correlation analysis of chlorophyll-a and algal density is conducted by chemical measurement. Taking into account the influence of multi-factors on algae growth and water blooms, the comprehensive prediction method combined with multivariate time series and intelligent model is put forward in this paper. Firstly, through the process of photosynthesis, the main factors that affect the reproduction of the algae are analyzed. A compensation prediction method of multivariate time series analysis based on neural network and Support Vector Machine has been put forward which is combined with Kernel Principal Component Analysis to deal with dimension reduction of the influence factors of blooms. Then, Genetic Algorithm is applied to improve the generalization ability of the BP network and Least Squares Support Vector Machine. Experimental results show that this method could better compensate the prediction model of multivariate time series analysis which is an effective way to improve the description accuracy of algae growth and prediction precision of water blooms.

Determination of thiamine HCl and pyridoxine HCl in pharmaceutical preparations using UV-visible spectrophotometry and genetic algorithm based multivariate calibration methods.

PubMed

Ozdemir, Durmus; Dinc, Erdal

2004-07-01

Simultaneous determination of binary mixtures pyridoxine hydrochloride and thiamine hydrochloride in a vitamin combination using UV-visible spectrophotometry and classical least squares (CLS) and three newly developed genetic algorithm (GA) based multivariate calibration methods was demonstrated. The three genetic multivariate calibration methods are Genetic Classical Least Squares (GCLS), Genetic Inverse Least Squares (GILS) and Genetic Regression (GR). The sample data set contains the UV-visible spectra of 30 synthetic mixtures (8 to 40 microg/ml) of these vitamins and 10 tablets containing 250 mg from each vitamin. The spectra cover the range from 200 to 330 nm in 0.1 nm intervals. Several calibration models were built with the four methods for the two components. Overall, the standard error of calibration (SEC) and the standard error of prediction (SEP) for the synthetic data were in the range of <0.01 and 0.43 microg/ml for all the four methods. The SEP values for the tablets were in the range of 2.91 and 11.51 mg/tablets. A comparison of genetic algorithm selected wavelengths for each component using GR method was also included.

Landscape genetics of leaf-toed geckos in the tropical dry forest of northern Mexico.

PubMed

Blair, Christopher; Jiménez Arcos, Victor H; Mendez de la Cruz, Fausto R; Murphy, Robert W

2013-01-01

Habitat fragmentation due to both natural and anthropogenic forces continues to threaten the evolution and maintenance of biological diversity. This is of particular concern in tropical regions that are experiencing elevated rates of habitat loss. Although less well-studied than tropical rain forests, tropical dry forests (TDF) contain an enormous diversity of species and continue to be threatened by anthropogenic activities including grazing and agriculture. However, little is known about the processes that shape genetic connectivity in species inhabiting TDF ecosystems. We adopt a landscape genetic approach to understanding functional connectivity for leaf-toed geckos (Phyllodactylus tuberculosus) at multiple sites near the northernmost limit of this ecosystem at Alamos, Sonora, Mexico. Traditional analyses of population genetics are combined with multivariate GIS-based landscape analyses to test hypotheses on the potential drivers of spatial genetic variation. Moderate levels of within-population diversity and substantial levels of population differentiation are revealed by FST and Dest. Analyses using structure suggest the occurrence of from 2 to 9 genetic clusters depending on the model used. Landscape genetic analysis suggests that forest cover, stream connectivity, undisturbed habitat, slope, and minimum temperature of the coldest period explain more genetic variation than do simple Euclidean distances. Additional landscape genetic studies throughout TDF habitat are required to understand species-specific responses to landscape and climate change and to identify common drivers. We urge researchers interested in using multivariate distance methods to test for, and report, significant correlations among predictor matrices that can impact results, particularly when adopting least-cost path approaches. Further investigation into the use of information theoretic approaches for model selection is also warranted.

Racial Differences in Circulating Natriuretic Peptide Levels: The Atherosclerosis Risk in Communities Study

PubMed Central

Gupta, Deepak K; Claggett, Brian; Wells, Quinn; Cheng, Susan; Li, Man; Maruthur, Nisa; Selvin, Elizabeth; Coresh, Josef; Konety, Suma; Butler, Kenneth R; Mosley, Thomas; Boerwinkle, Eric; Hoogeveen, Ron; Ballantyne, Christie M; Solomon, Scott D

2015-01-01

Background Natriuretic peptides promote natriuresis, diuresis, and vasodilation. Experimental deficiency of natriuretic peptides leads to hypertension (HTN) and cardiac hypertrophy, conditions more common among African Americans. Hospital-based studies suggest that African Americans may have reduced circulating natriuretic peptides, as compared to Caucasians, but definitive data from community-based cohorts are lacking. Methods and Results We examined plasma N-terminal pro B-type natriuretic peptide (NTproBNP) levels according to race in 9137 Atherosclerosis Risk in Communities (ARIC) Study participants (22% African American) without prevalent cardiovascular disease at visit 4 (1996–1998). Multivariable linear and logistic regression analyses were performed adjusting for clinical covariates. Among African Americans, percent European ancestry was determined from genetic ancestry informative markers and then examined in relation to NTproBNP levels in multivariable linear regression analysis. NTproBNP levels were significantly lower in African Americans (median, 43 pg/mL; interquartile range [IQR], 18, 88) than Caucasians (median, 68 pg/mL; IQR, 36, 124; P<0.0001). In multivariable models, adjusted log NTproBNP levels were 40% lower (95% confidence interval [CI], −43, −36) in African Americans, compared to Caucasians, which was consistent across subgroups of age, gender, HTN, diabetes, insulin resistance, and obesity. African-American race was also significantly associated with having nondetectable NTproBNP (adjusted OR, 5.74; 95% CI, 4.22, 7.80). In multivariable analyses in African Americans, a 10% increase in genetic European ancestry was associated with a 7% (95% CI, 1, 13) increase in adjusted log NTproBNP. Conclusions African Americans have lower levels of plasma NTproBNP than Caucasians, which may be partially owing to genetic variation. Low natriuretic peptide levels in African Americans may contribute to the greater risk for HTN and its sequalae in this population. PMID:25999400

Environmental effects on the structure of the G-matrix.

PubMed

Wood, Corlett W; Brodie, Edmund D

2015-11-01

Genetic correlations between traits determine the multivariate response to selection in the short term, and thereby play a causal role in evolutionary change. Although individual studies have documented environmentally induced changes in genetic correlations, the nature and extent of environmental effects on multivariate genetic architecture across species and environments remain largely uncharacterized. We reviewed the literature for estimates of the genetic variance-covariance (G) matrix in multiple environments, and compared differences in G between environments to the divergence in G between conspecific populations (measured in a common garden). We found that the predicted evolutionary trajectory differed as strongly between environments as it did between populations. Between-environment differences in the underlying structure of G (total genetic variance and the relative magnitude and orientation of genetic correlations) were equal to or greater than between-population differences. Neither environmental novelty, nor the difference in mean phenotype predicted these differences in G. Our results suggest that environmental effects on multivariate genetic architecture may be comparable to the divergence that accumulates over dozens or hundreds of generations between populations. We outline avenues of future research to address the limitations of existing data and characterize the extent to which lability in genetic correlations shapes evolution in changing environments. © 2015 The Author(s). Evolution © 2015 The Society for the Study of Evolution.

Multicollinearity in spatial genetics: separating the wheat from the chaff using commonality analyses.

PubMed

Prunier, J G; Colyn, M; Legendre, X; Nimon, K F; Flamand, M C

2015-01-01

Direct gradient analyses in spatial genetics provide unique opportunities to describe the inherent complexity of genetic variation in wildlife species and are the object of many methodological developments. However, multicollinearity among explanatory variables is a systemic issue in multivariate regression analyses and is likely to cause serious difficulties in properly interpreting results of direct gradient analyses, with the risk of erroneous conclusions, misdirected research and inefficient or counterproductive conservation measures. Using simulated data sets along with linear and logistic regressions on distance matrices, we illustrate how commonality analysis (CA), a detailed variance-partitioning procedure that was recently introduced in the field of ecology, can be used to deal with nonindependence among spatial predictors. By decomposing model fit indices into unique and common (or shared) variance components, CA allows identifying the location and magnitude of multicollinearity, revealing spurious correlations and thus thoroughly improving the interpretation of multivariate regressions. Despite a few inherent limitations, especially in the case of resistance model optimization, this review highlights the great potential of CA to account for complex multicollinearity patterns in spatial genetics and identifies future applications and lines of research. We strongly urge spatial geneticists to systematically investigate commonalities when performing direct gradient analyses. © 2014 John Wiley & Sons Ltd.

Transforming growth factor-β and toll-like receptor-4 polymorphisms are not associated with fibrosis in haemochromatosis

PubMed Central

Wood, Marnie J; Powell, Lawrie W; Dixon, Jeannette L; Subramaniam, V Nathan; Ramm, Grant A

2013-01-01

AIM: To investigate the role of genetic polymorphisms in the progression of hepatic fibrosis in hereditary haemochromatosis. METHODS: A cohort of 245 well-characterised C282Y homozygous patients with haemochromatosis was studied, with all subjects having liver biopsy data and DNA available for testing. This study assessed the association of eight single nucleotide polymorphisms (SNPs) in a total of six genes including toll-like receptor 4 (TLR4), transforming growth factor-beta (TGF-β), oxoguanine DNA glycosylase, monocyte chemoattractant protein 1, chemokine C-C motif receptor 2 and interleukin-10 with liver disease severity. Genotyping was performed using high resolution melt analysis and sequencing. The results were analysed in relation to the stage of hepatic fibrosis in multivariate analysis incorporating other cofactors including alcohol consumption and hepatic iron concentration. RESULTS: There were significant associations between the cofactors of male gender (P = 0.0001), increasing age (P = 0.006), alcohol consumption (P = 0.0001), steatosis (P = 0.03), hepatic iron concentration (P < 0.0001) and the presence of hepatic fibrosis. Of the candidate gene polymorphisms studied, none showed a significant association with hepatic fibrosis in univariate or multivariate analysis incorporating cofactors. We also specifically studied patients with hepatic iron loading above threshold levels for cirrhosis and compared the genetic polymorphisms between those with no fibrosis vs cirrhosis however there was no significant effect from any of the candidate genes studied. Importantly, in this large, well characterised cohort of patients there was no association between SNPs for TGF-β or TLR4 and the presence of fibrosis, cirrhosis or increasing fibrosis stage in multivariate analysis. CONCLUSION: In our large, well characterised group of haemochromatosis subjects we did not demonstrate any relationship between candidate gene polymorphisms and hepatic fibrosis or cirrhosis. PMID:24409064

Transforming growth factor-β and toll-like receptor-4 polymorphisms are not associated with fibrosis in haemochromatosis.

PubMed

Wood, Marnie J; Powell, Lawrie W; Dixon, Jeannette L; Subramaniam, V Nathan; Ramm, Grant A

2013-12-28

To investigate the role of genetic polymorphisms in the progression of hepatic fibrosis in hereditary haemochromatosis. A cohort of 245 well-characterised C282Y homozygous patients with haemochromatosis was studied, with all subjects having liver biopsy data and DNA available for testing. This study assessed the association of eight single nucleotide polymorphisms (SNPs) in a total of six genes including toll-like receptor 4 (TLR4), transforming growth factor-beta (TGF-β), oxoguanine DNA glycosylase, monocyte chemoattractant protein 1, chemokine C-C motif receptor 2 and interleukin-10 with liver disease severity. Genotyping was performed using high resolution melt analysis and sequencing. The results were analysed in relation to the stage of hepatic fibrosis in multivariate analysis incorporating other cofactors including alcohol consumption and hepatic iron concentration. There were significant associations between the cofactors of male gender (P = 0.0001), increasing age (P = 0.006), alcohol consumption (P = 0.0001), steatosis (P = 0.03), hepatic iron concentration (P < 0.0001) and the presence of hepatic fibrosis. Of the candidate gene polymorphisms studied, none showed a significant association with hepatic fibrosis in univariate or multivariate analysis incorporating cofactors. We also specifically studied patients with hepatic iron loading above threshold levels for cirrhosis and compared the genetic polymorphisms between those with no fibrosis vs cirrhosis however there was no significant effect from any of the candidate genes studied. Importantly, in this large, well characterised cohort of patients there was no association between SNPs for TGF-β or TLR4 and the presence of fibrosis, cirrhosis or increasing fibrosis stage in multivariate analysis. In our large, well characterised group of haemochromatosis subjects we did not demonstrate any relationship between candidate gene polymorphisms and hepatic fibrosis or cirrhosis.

Multivariate diallel analysis allows multiple gains in segregating populations for agronomic traits in Jatropha.

PubMed

Teodoro, P E; Rodrigues, E V; Peixoto, L A; Silva, L A; Laviola, B G; Bhering, L L

2017-03-22

Jatropha is research target worldwide aimed at large-scale oil production for biodiesel and bio-kerosene. Its production potential is among 1200 and 1500 kg/ha of oil after the 4th year. This study aimed to estimate combining ability of Jatropha genotypes by multivariate diallel analysis to select parents and crosses that allow gains in important agronomic traits. We performed crosses in diallel complete genetic design (3 x 3) arranged in blocks with five replications and three plants per plot. The following traits were evaluated: plant height, stem diameter, canopy projection between rows, canopy projection on the line, number of branches, mass of hundred grains, and grain yield. Data were submitted to univariate and multivariate diallel analysis. Genotypes 107 and 190 can be used in crosses for establishing a base population of Jatropha, since it has favorable alleles for increasing the mass of hundred grains and grain yield and reducing the plant height. The cross 190 x 107 is the most promising to perform the selection of superior genotypes for the simultaneous breeding of these traits.

East Greenland and Barents Sea polar bears (Ursus maritimus): adaptive variation between two populations using skull morphometrics as an indicator of environmental and genetic differences.

PubMed

Pertoldi, Cino; Sonne, Christian; Wiig, Øystein; Baagøe, Hans J; Loeschcke, Volker; Bechshøft, Thea Østergaard

2012-06-01

A morphometric study was conducted on four skull traits of 37 male and 18 female adult East Greenland polar bears (Ursus maritimus) collected 1892-1968, and on 54 male and 44 female adult Barents Sea polar bears collected 1950-1969. The aim was to compare differences in size and shape of the bear skulls using a multivariate approach, characterizing the variation between the two populations using morphometric traits as an indicator of environmental and genetic differences. Mixture analysis testing for geographic differentiation within each population revealed three clusters for Barents Sea males and three clusters for Barents Sea females. East Greenland consisted of one female and one male cluster. A principal component analysis (PCA) conducted on the clusters defined by the mixture analysis, showed that East Greenland and Barents Sea polar bear populations overlapped to a large degree, especially with regards to females. Multivariate analyses of variance (MANOVA) showed no significant differences in morphometric means between the two populations, but differences were detected between clusters from each respective geographic locality. To estimate the importance of genetics and environment in the morphometric differences between the bears, a PCA was performed on the covariance matrix derived from the skull measurements. Skull trait size (PC1) explained approx. 80% of the morphometric variation, whereas shape (PC2) defined approx. 15%, indicating some genetic differentiation. Hence, both environmental and genetic factors seem to have contributed to the observed skull differences between the two populations. Overall, results indicate that many Barents Sea polar bears are morphometrically similar to the East Greenland ones, suggesting an exchange of individuals between the two populations. Furthermore, a subpopulation structure in the Barents Sea population was also indicated from the present analyses, which should be considered with regards to future management decisions. © 2012 The Authors.

Genetic Factors of Individual Differences in Decision Making in Economic Behavior: A Japanese Twin Study using the Allais Problem.

PubMed

Shikishima, Chizuru; Hiraishi, Kai; Yamagata, Shinji; Ando, Juko; Okada, Mitsuhiro

2015-01-01

Why does decision making differ among individuals? People sometimes make seemingly inconsistent decisions with lower expected (monetary) utility even when objective information of probabilities and reward are provided. It is noteworthy, however, that a certain proportion of people do not provide anomalous responses, choosing the alternatives with higher expected utility, thus appearing to be more "rational." We investigated the genetic and environmental influences on these types of individual differences in decision making using a classical Allais problem task. Participants were 1,199 Japanese adult twins aged 20-47. Univariate genetic analysis revealed that approximately a third of the Allais problem response variance was explained by genetic factors and the rest by environmental factors unique to individuals and measurement error. The environmental factor shared between families did not contribute to the variance. Subsequent multivariate genetic analysis clarified that decision making using the expected utility theory was associated with general intelligence and that the association was largely mediated by the same genetic factor. We approach the mechanism underlying two types of "rational" decision making from the perspective of genetic correlations with cognitive abilities.

Genetic and Environmental Influences on Systemic Markers of Inflammation in Middle-Aged Male Twins

PubMed Central

Su, Shaoyong; Snieder, Harold; Miller, Andrew H.; Ritchie, James; Bremner, J. Douglas; Goldberg, Jack; Dai, Jun; Jones, Linda; Murrah, Nancy V.; Zhao, Jinying; Vaccarino, Viola

2008-01-01

Objectives The aims of this study were to determine the relative influence of genetic and environmental contributions to inflammatory biomarkers, and to what extent correlations among these markers are due to genetic or environmental factors. Methods We performed univariate and multivariate genetic analyses of four inflammatory markers: interleukin-6 (IL-6), soluble IL-6 receptor (sIL-6R), C-reactive protein (CRP), and fibrinogen, in 166 (88 monozygotic and 78 dizygotic) middle-aged male twin pairs. Results The mean age (±SD) of the twins was 54 (±2.93) years. Heritability was substantial for CRP (0.61, 95% CI: 0.47–0.72) and moderate to fair for IL-6 (0.31, 0.13–0.46), sIL-6R (0.49, 0.30–0.76) and fibrinogen (0.52, 0.34–0.65). IL-6, CRP and fibrinogen showed significant correlations, but not with sIL-6R. Multivariate genetic analysis found that these correlations could be best explained by a common pathway model, where the common factor explained 27%, 73% and 25% of the variance of IL-6, CRP and fibrinogen, respectively. About 46% (95% CI: 21–64%) of the correlations among the three inflammatory markers could be explained by the genetic factors. After adjusting for covariates known to influence inflammation levels, heritability estimates were slightly decreased but the overall results remained similar. Conclusions A significant part of the variation in inflammatory marker levels is due to genetic influences. Furthermore, almost 50% of the shared variance among these biomarkers is due to a common genetic factor which likely plays a key role in the regulation of inflammation. PMID:18243214

Using sperm morphometry and multivariate analysis to differentiate species of gray Mazama

PubMed Central

Duarte, José Maurício Barbanti

2016-01-01

There is genetic evidence that the two species of Brazilian gray Mazama, Mazama gouazoubira and Mazama nemorivaga, belong to different genera. This study identified significant differences that separated them into distinct groups, based on characteristics of the spermatozoa and ejaculate of both species. The characteristics that most clearly differentiated between the species were ejaculate colour, white for M. gouazoubira and reddish for M. nemorivaga, and sperm head dimensions. Multivariate analysis of sperm head dimension and format data accurately discriminated three groups for species with total percentage of misclassified of 0.71. The individual analysis, by animal, and the multivariate analysis have also discriminated correctly all five animals (total percentage of misclassified of 13.95%), and the canonical plot has shown three different clusters: Cluster 1, including individuals of M. nemorivaga; Cluster 2, including two individuals of M. gouazoubira; and Cluster 3, including a single individual of M. gouazoubira. The results obtained in this work corroborate the hypothesis of the formation of new genera and species for gray Mazama. Moreover, the easily applied method described herein can be used as an auxiliary tool to identify sibling species of other taxonomic groups. PMID:28018612

External validity of a hierarchical dimensional model of child and adolescent psychopathology: Tests using confirmatory factor analyses and multivariate behavior genetic analyses.

PubMed

Waldman, Irwin D; Poore, Holly E; van Hulle, Carol; Rathouz, Paul J; Lahey, Benjamin B

2016-11-01

Several recent studies of the hierarchical phenotypic structure of psychopathology have identified a General psychopathology factor in addition to the more expected specific Externalizing and Internalizing dimensions in both youth and adult samples and some have found relevant unique external correlates of this General factor. We used data from 1,568 twin pairs (599 MZ & 969 DZ) age 9 to 17 to test hypotheses for the underlying structure of youth psychopathology and the external validity of the higher-order factors. Psychopathology symptoms were assessed via structured interviews of caretakers and youth. We conducted phenotypic analyses of competing structural models using Confirmatory Factor Analysis and used Structural Equation Modeling and multivariate behavior genetic analyses to understand the etiology of the higher-order factors and their external validity. We found that both a General factor and specific Externalizing and Internalizing dimensions are necessary for characterizing youth psychopathology at both the phenotypic and etiologic levels, and that the 3 higher-order factors differed substantially in the magnitudes of their underlying genetic and environmental influences. Phenotypically, the specific Externalizing and Internalizing dimensions were slightly negatively correlated when a General factor was included, which reflected a significant inverse correlation between the nonshared environmental (but not genetic) influences on Internalizing and Externalizing. We estimated heritability of the general factor of psychopathology for the first time. Its moderate heritability suggests that it is not merely an artifact of measurement error but a valid construct. The General, Externalizing, and Internalizing factors differed in their relations with 3 external validity criteria: mother's smoking during pregnancy, parent's harsh discipline, and the youth's association with delinquent peers. Multivariate behavior genetic analyses supported the external validity of the 3 higher-order factors by suggesting that the General, Externalizing, and Internalizing factors were correlated with peer delinquency and parent's harsh discipline for different etiologic reasons. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Genetic and environmental contributions to the associations between intraindividual variability in reaction time and cognitive function.

PubMed

Finkel, Deborah; Pedersen, Nancy L

2014-01-01

Intraindividual variability (IIV) in reaction time has been related to cognitive decline, but questions remain about the nature of this relationship. Mean and range in movement and decision time for simple reaction time were available from 241 individuals aged 51-86 years at the fifth testing wave of the Swedish Adoption/Twin Study of Aging. Cognitive performance on four factors was also available: verbal, spatial, memory, and speed. Analyses indicated that range in reaction time could be used as an indicator of IIV. Heritability estimates were 35% for mean reaction and 20% for range in reaction. Multivariate analysis indicated that the genetic variance on the memory, speed, and spatial factors is shared with genetic variance for mean or range in reaction time. IIV shares significant genetic variance with fluid ability in late adulthood, over and above and genetic variance shared with mean reaction time.

Neural-genetic synthesis for state-space controllers based on linear quadratic regulator design for eigenstructure assignment.

PubMed

da Fonseca Neto, João Viana; Abreu, Ivanildo Silva; da Silva, Fábio Nogueira

2010-04-01

Toward the synthesis of state-space controllers, a neural-genetic model based on the linear quadratic regulator design for the eigenstructure assignment of multivariable dynamic systems is presented. The neural-genetic model represents a fusion of a genetic algorithm and a recurrent neural network (RNN) to perform the selection of the weighting matrices and the algebraic Riccati equation solution, respectively. A fourth-order electric circuit model is used to evaluate the convergence of the computational intelligence paradigms and the control design method performance. The genetic search convergence evaluation is performed in terms of the fitness function statistics and the RNN convergence, which is evaluated by landscapes of the energy and norm, as a function of the parameter deviations. The control problem solution is evaluated in the time and frequency domains by the impulse response, singular values, and modal analysis.

Genetic variation and structure in remnant population of critically endangered Melicope zahlbruckneri

USGS Publications Warehouse

Raji, J. A.; Atkinson, Carter T.

2016-01-01

The distribution and amount of genetic variation within and between populations of plant species are important for their adaptability to future habitat changes and also critical for their restoration and overall management. This study was initiated to assess the genetic status of the remnant population of Melicope zahlbruckneri–a critically endangered species in Hawaii, and determine the extent of genetic variation and diversity in order to propose valuable conservation approaches. Estimated genetic structure of individuals based on molecular marker allele frequencies identified genetic groups with low overall differentiation but identified the most genetically diverse individuals within the population. Analysis of Amplified Fragment Length Polymorphic (AFLP) marker loci in the population based on Bayesian model and multivariate statistics classified the population into four subgroups. We inferred a mixed species population structure based on Bayesian clustering and frequency of unique alleles. The percentage of Polymorphic Fragment (PPF) ranged from 18.8 to 64.6% for all marker loci with an average of 54.9% within the population. Inclusion of all surviving M. zahlbruckneri trees in future restorative planting at new sites are suggested, and approaches for longer term maintenance of genetic variability are discussed. To our knowledge, this study represents the first report of molecular genetic analysis of the remaining population of M. zahlbruckneri and also illustrates the importance of genetic variability for conservation of a small endangered population.

A Statistical Approach for Testing Cross-Phenotype Effects of Rare Variants

PubMed Central

Broadaway, K. Alaine; Cutler, David J.; Duncan, Richard; Moore, Jacob L.; Ware, Erin B.; Jhun, Min A.; Bielak, Lawrence F.; Zhao, Wei; Smith, Jennifer A.; Peyser, Patricia A.; Kardia, Sharon L.R.; Ghosh, Debashis; Epstein, Michael P.

2016-01-01

Increasing empirical evidence suggests that many genetic variants influence multiple distinct phenotypes. When cross-phenotype effects exist, multivariate association methods that consider pleiotropy are often more powerful than univariate methods that model each phenotype separately. Although several statistical approaches exist for testing cross-phenotype effects for common variants, there is a lack of similar tests for gene-based analysis of rare variants. In order to fill this important gap, we introduce a statistical method for cross-phenotype analysis of rare variants using a nonparametric distance-covariance approach that compares similarity in multivariate phenotypes to similarity in rare-variant genotypes across a gene. The approach can accommodate both binary and continuous phenotypes and further can adjust for covariates. Our approach yields a closed-form test whose significance can be evaluated analytically, thereby improving computational efficiency and permitting application on a genome-wide scale. We use simulated data to demonstrate that our method, which we refer to as the Gene Association with Multiple Traits (GAMuT) test, provides increased power over competing approaches. We also illustrate our approach using exome-chip data from the Genetic Epidemiology Network of Arteriopathy. PMID:26942286

Online health communication about human genetics: perceptions and preferences of internet users.

PubMed

Bernhardt, Jay M; McClain, Jacqueline; Parrott, Roxanne L

2004-12-01

Unprecedented advancements in human genetics research necessitate keeping the public abreast of new information, applications, and implications and the Internet represents an important method of communicating with the public. Our research used cross-sectional self-report survey data collected from a diverse convenience sample of 780 Internet users in two states. Multivariate regression analysis explored the relationships between experiences, perceptions, and preferences for online health and genetics communication. Online health information seeking was associated with previous genetic information seeking, comfort with online genetic communication, perceived risk for genetic abnormality, being female, and having more education. Comfort with online genetics communication was associated with a preference for online genetic information, previous online health and off-line genetics information seeking, having a healthy lifestyle, believing in the positive impact of human genetics research, and being female. Perceiving online health information to be accurate was associated with preferring the Internet for genetics communication, being older, less educated, and perceiving Internet use as anonymous. Preferring online genetics communication to other communication channels was associated with perceiving online health information as accurate, being comfortable receiving online genetics information, having lower intrinsic religiosity, and being male. The implications of findings for Web-based health message design are discussed.

Female choice for male cuticular hydrocarbon profile in decorated crickets is not based on similarity to their own profile.

PubMed

Steiger, S; Capodeanu-Nägler, A; Gershman, S N; Weddle, C B; Rapkin, J; Sakaluk, S K; Hunt, J

2015-12-01

Indirect genetic benefits derived from female mate choice comprise additive (good genes) and nonadditive genetic benefits (genetic compatibility). Although good genes can be revealed by condition-dependent display traits, the mechanism by which compatibility alleles are detected is unclear because evaluation of the genetic similarity of a prospective mate requires the female to assess the genotype of the male and compare it to her own. Cuticular hydrocarbons (CHCs), lipids coating the exoskeleton of most insects, influence female mate choice in a number of species and offer a way for females to assess genetic similarity of prospective mates. Here, we determine whether female mate choice in decorated crickets is based on male CHCs and whether it is influenced by females' own CHC profiles. We used multivariate selection analysis to estimate the strength and form of selection acting on male CHCs through female mate choice, and employed different measures of multivariate dissimilarity to determine whether a female's preference for male CHCs is based on similarity to her own CHC profile. Female mating preferences were significantly influenced by CHC profiles of males. Male CHC attractiveness was not, however, contingent on the CHC profile of the choosing female, as certain male CHC phenotypes were equally attractive to most females, evidenced by significant linear and stabilizing selection gradients. These results suggest that additive genetic benefits, rather than nonadditive genetic benefits, accrue to female mate choice, in support of earlier work showing that CHC expression of males, but not females, is condition dependent. © 2015 European Society For Evolutionary Biology. Journal of Evolutionary Biology © 2015 European Society For Evolutionary Biology.

Personality disorder traits, family environment, and alcohol misuse: a multivariate behavioural genetic analysis.

PubMed

Jang, K L; Vernon, P A; Livesley, W J

2000-06-01

This study seeks to estimate the extent to which a common genetic and environmental basis is shared between (i) traits delineating specific aspects of antisocial personality and alcohol misuse, and (ii) childhood family environments, traits delineating broad domains of personality pathology and alcohol misuse. Postal survey data were collected from monozygotic and dizygotic twin pairs. Twin pairs were recruited from Vancouver, British Columbia and London, Ontario, Canada using newspaper advertisements, media stories and twin clubs. Data obtained from 324 monozygotic and 335 dizygotic twin pairs were used to estimate the extent to which traits delineating specific antisocial personality traits and alcohol misuse shared a common genetic and environmental aetiology. Data from 81 monozygotic and 74 dizygotic twin pairs were used to estimate the degree to which traits delineating personality pathology, childhood family environment and alcohol misuse shared a common aetiology. Current alcohol misuse and personality pathology were measured using scales contained in the self-report Dimensional Assessment of Personality Pathology. Perceptions of childhood family environment were measured using the self-report Family Environment Scale. Multivariate genetic analyses showed that a subset of traits delineating components of antisocial personality (i.e. grandiosity, attention-seeking, failure to adopt social norms, interpersonal violence and juvenile antisocial behaviours) are influenced by genetic factors in common to alcohol misuse. Genetically based perceptions of childhood family environment had little relationship with alcohol misuse. Heritable personality factors that influence the perception of childhood family environment play only a small role in the liability to alcohol misuse. Instead, liability to alcohol misuse is related to genetic factors common a specific subset of antisocial personality traits describing conduct problems, narcissistic and stimulus-seeking behaviour.

Learning Abilities and Disabilities: Generalist Genes, Specialist Environments.

PubMed

Kovas, Yulia; Plomin, Robert

2007-10-01

Twin studies comparing identical and fraternal twins consistently show substantial genetic influence on individual differences in learning abilities such as reading and mathematics, as well as in other cognitive abilities such as spatial ability and memory. Multivariate genetic research has shown that the same set of genes is largely responsible for genetic influence on these diverse cognitive areas. We call these "generalist genes." What differentiates these abilities is largely the environment, especially nonshared environments that make children growing up in the same family different from one another. These multivariate genetic findings of generalist genes and specialist environments have far-reaching implications for diagnosis and treatment of learning disabilities and for understanding the brain mechanisms that mediate these effects.

Genetic parameters for growth characteristics of free-range chickens under univariate random regression models.

PubMed

Rovadoscki, Gregori A; Petrini, Juliana; Ramirez-Diaz, Johanna; Pertile, Simone F N; Pertille, Fábio; Salvian, Mayara; Iung, Laiza H S; Rodriguez, Mary Ana P; Zampar, Aline; Gaya, Leila G; Carvalho, Rachel S B; Coelho, Antonio A D; Savino, Vicente J M; Coutinho, Luiz L; Mourão, Gerson B

2016-09-01

Repeated measures from the same individual have been analyzed by using repeatability and finite dimension models under univariate or multivariate analyses. However, in the last decade, the use of random regression models for genetic studies with longitudinal data have become more common. Thus, the aim of this research was to estimate genetic parameters for body weight of four experimental chicken lines by using univariate random regression models. Body weight data from hatching to 84 days of age (n = 34,730) from four experimental free-range chicken lines (7P, Caipirão da ESALQ, Caipirinha da ESALQ and Carijó Barbado) were used. The analysis model included the fixed effects of contemporary group (gender and rearing system), fixed regression coefficients for age at measurement, and random regression coefficients for permanent environmental effects and additive genetic effects. Heterogeneous variances for residual effects were considered, and one residual variance was assigned for each of six subclasses of age at measurement. Random regression curves were modeled by using Legendre polynomials of the second and third orders, with the best model chosen based on the Akaike Information Criterion, Bayesian Information Criterion, and restricted maximum likelihood. Multivariate analyses under the same animal mixed model were also performed for the validation of the random regression models. The Legendre polynomials of second order were better for describing the growth curves of the lines studied. Moderate to high heritabilities (h(2) = 0.15 to 0.98) were estimated for body weight between one and 84 days of age, suggesting that selection for body weight at all ages can be used as a selection criteria. Genetic correlations among body weight records obtained through multivariate analyses ranged from 0.18 to 0.96, 0.12 to 0.89, 0.06 to 0.96, and 0.28 to 0.96 in 7P, Caipirão da ESALQ, Caipirinha da ESALQ, and Carijó Barbado chicken lines, respectively. Results indicate that genetic gain for body weight can be achieved by selection. Also, selection for body weight at 42 days of age can be maintained as a selection criterion. © 2016 Poultry Science Association Inc.

[A survey of willingness about genetic counseling and tests in patients of epithelial ovarian cancer].

PubMed

Li, L; Qiu, L; Wu, M

2017-11-21

Objective: To analyze patients' tendency towards genetics counseling and tests based on a prospective cohort study on hereditary ovarian cancer. Methods: From February 2017 to June 2017, among 220 cases of epithelial ovarian cancer in Peking Union Medical College Hospital, we collected epidemiological, pathological and tendency towards genetics counseling and tests via medical records and questionnaire.All patients would get education about hereditary ovarian cancer by pamphlets and WeChat.If they would receive further counseling, a face to face interview and tests will be given. Results: Among all 220 patients, 10 (4.5%) denied further counseling.For 210 patients receiving genetic counseling, 170 (81%) accepted genetic tests.In multivariate analysis, risk factors relevant to acceptance of genetic tests included: being charged by physicians of gynecologic oncology for diagnosis and treatment, receiving counseling in genetic counseling clinics, and having family history of breast cancer.For patients denying genetic tests, there were many subjective reasons, among which, "still not understanding genetic tests" (25%) and "unable bear following expensive targeting medicine" . Conclusions: High proportion patients of epithelial ovarian cancer would accept genetic counseling and tests.Genetic counseling clinics for gynecologic oncology would further improve genetic tests for patients.

Fast Genome-Wide QTL Association Mapping on Pedigree and Population Data.

PubMed

Zhou, Hua; Blangero, John; Dyer, Thomas D; Chan, Kei-Hang K; Lange, Kenneth; Sobel, Eric M

2017-04-01

Since most analysis software for genome-wide association studies (GWAS) currently exploit only unrelated individuals, there is a need for efficient applications that can handle general pedigree data or mixtures of both population and pedigree data. Even datasets thought to consist of only unrelated individuals may include cryptic relationships that can lead to false positives if not discovered and controlled for. In addition, family designs possess compelling advantages. They are better equipped to detect rare variants, control for population stratification, and facilitate the study of parent-of-origin effects. Pedigrees selected for extreme trait values often segregate a single gene with strong effect. Finally, many pedigrees are available as an important legacy from the era of linkage analysis. Unfortunately, pedigree likelihoods are notoriously hard to compute. In this paper, we reexamine the computational bottlenecks and implement ultra-fast pedigree-based GWAS analysis. Kinship coefficients can either be based on explicitly provided pedigrees or automatically estimated from dense markers. Our strategy (a) works for random sample data, pedigree data, or a mix of both; (b) entails no loss of power; (c) allows for any number of covariate adjustments, including correction for population stratification; (d) allows for testing SNPs under additive, dominant, and recessive models; and (e) accommodates both univariate and multivariate quantitative traits. On a typical personal computer (six CPU cores at 2.67 GHz), analyzing a univariate HDL (high-density lipoprotein) trait from the San Antonio Family Heart Study (935,392 SNPs on 1,388 individuals in 124 pedigrees) takes less than 2 min and 1.5 GB of memory. Complete multivariate QTL analysis of the three time-points of the longitudinal HDL multivariate trait takes less than 5 min and 1.5 GB of memory. The algorithm is implemented as the Ped-GWAS Analysis (Option 29) in the Mendel statistical genetics package, which is freely available for Macintosh, Linux, and Windows platforms from http://genetics.ucla.edu/software/mendel. © 2016 WILEY PERIODICALS, INC.

Smoothing of the bivariate LOD score for non-normal quantitative traits.

PubMed

Buil, Alfonso; Dyer, Thomas D; Almasy, Laura; Blangero, John

2005-12-30

Variance component analysis provides an efficient method for performing linkage analysis for quantitative traits. However, type I error of variance components-based likelihood ratio testing may be affected when phenotypic data are non-normally distributed (especially with high values of kurtosis). This results in inflated LOD scores when the normality assumption does not hold. Even though different solutions have been proposed to deal with this problem with univariate phenotypes, little work has been done in the multivariate case. We present an empirical approach to adjust the inflated LOD scores obtained from a bivariate phenotype that violates the assumption of normality. Using the Collaborative Study on the Genetics of Alcoholism data available for the Genetic Analysis Workshop 14, we show how bivariate linkage analysis with leptokurtotic traits gives an inflated type I error. We perform a novel correction that achieves acceptable levels of type I error.

Random forests on Hadoop for genome-wide association studies of multivariate neuroimaging phenotypes

PubMed Central

2013-01-01

Motivation Multivariate quantitative traits arise naturally in recent neuroimaging genetics studies, in which both structural and functional variability of the human brain is measured non-invasively through techniques such as magnetic resonance imaging (MRI). There is growing interest in detecting genetic variants associated with such multivariate traits, especially in genome-wide studies. Random forests (RFs) classifiers, which are ensembles of decision trees, are amongst the best performing machine learning algorithms and have been successfully employed for the prioritisation of genetic variants in case-control studies. RFs can also be applied to produce gene rankings in association studies with multivariate quantitative traits, and to estimate genetic similarities measures that are predictive of the trait. However, in studies involving hundreds of thousands of SNPs and high-dimensional traits, a very large ensemble of trees must be inferred from the data in order to obtain reliable rankings, which makes the application of these algorithms computationally prohibitive. Results We have developed a parallel version of the RF algorithm for regression and genetic similarity learning tasks in large-scale population genetic association studies involving multivariate traits, called PaRFR (Parallel Random Forest Regression). Our implementation takes advantage of the MapReduce programming model and is deployed on Hadoop, an open-source software framework that supports data-intensive distributed applications. Notable speed-ups are obtained by introducing a distance-based criterion for node splitting in the tree estimation process. PaRFR has been applied to a genome-wide association study on Alzheimer's disease (AD) in which the quantitative trait consists of a high-dimensional neuroimaging phenotype describing longitudinal changes in the human brain structure. PaRFR provides a ranking of SNPs associated to this trait, and produces pair-wise measures of genetic proximity that can be directly compared to pair-wise measures of phenotypic proximity. Several known AD-related variants have been identified, including APOE4 and TOMM40. We also present experimental evidence supporting the hypothesis of a linear relationship between the number of top-ranked mutated states, or frequent mutation patterns, and an indicator of disease severity. Availability The Java codes are freely available at http://www2.imperial.ac.uk/~gmontana. PMID:24564704

Random forests on Hadoop for genome-wide association studies of multivariate neuroimaging phenotypes.

PubMed

Wang, Yue; Goh, Wilson; Wong, Limsoon; Montana, Giovanni

2013-01-01

Multivariate quantitative traits arise naturally in recent neuroimaging genetics studies, in which both structural and functional variability of the human brain is measured non-invasively through techniques such as magnetic resonance imaging (MRI). There is growing interest in detecting genetic variants associated with such multivariate traits, especially in genome-wide studies. Random forests (RFs) classifiers, which are ensembles of decision trees, are amongst the best performing machine learning algorithms and have been successfully employed for the prioritisation of genetic variants in case-control studies. RFs can also be applied to produce gene rankings in association studies with multivariate quantitative traits, and to estimate genetic similarities measures that are predictive of the trait. However, in studies involving hundreds of thousands of SNPs and high-dimensional traits, a very large ensemble of trees must be inferred from the data in order to obtain reliable rankings, which makes the application of these algorithms computationally prohibitive. We have developed a parallel version of the RF algorithm for regression and genetic similarity learning tasks in large-scale population genetic association studies involving multivariate traits, called PaRFR (Parallel Random Forest Regression). Our implementation takes advantage of the MapReduce programming model and is deployed on Hadoop, an open-source software framework that supports data-intensive distributed applications. Notable speed-ups are obtained by introducing a distance-based criterion for node splitting in the tree estimation process. PaRFR has been applied to a genome-wide association study on Alzheimer's disease (AD) in which the quantitative trait consists of a high-dimensional neuroimaging phenotype describing longitudinal changes in the human brain structure. PaRFR provides a ranking of SNPs associated to this trait, and produces pair-wise measures of genetic proximity that can be directly compared to pair-wise measures of phenotypic proximity. Several known AD-related variants have been identified, including APOE4 and TOMM40. We also present experimental evidence supporting the hypothesis of a linear relationship between the number of top-ranked mutated states, or frequent mutation patterns, and an indicator of disease severity. The Java codes are freely available at http://www2.imperial.ac.uk/~gmontana.

Integration of genome and phenotypic scanning gives evidence of genetic structure in Mesoamerican common bean (Phaseolus vulgaris L.) landraces from the southwest of Europe.

PubMed

Santalla, M; De Ron, A M; De La Fuente, M

2010-05-01

Southwestern Europe has been considered as a secondary centre of genetic diversity for the common bean. The dispersal of domesticated materials from their centres of origin provides an experimental system that reveals how human selection during cultivation and adaptation to novel environments affects the genetic composition. In this paper, our goal was to elucidate how distinct events could modify the structure and level of genetic diversity in the common bean. The genome-wide genetic composition was analysed at 42 microsatellite loci in individuals of 22 landraces of domesticated common bean from the Mesoamerican gene pool. The accessions were also characterised for phaseolin seed protein and for nine allozyme polymorphisms and phenotypic traits. One of this study's important findings was the complementary information obtained from all the polymorphisms examined. Most of the markers found to be potentially under the influence of selection were located in the proximity of previously mapped genes and quantitative trait loci (QTLs) related to important agronomic traits, which indicates that population genomics approaches are very efficient in detecting QTLs. As it was revealed by outlier simple sequence repeats, loci analysis with STRUCTURE software and multivariate analysis of phenotypic data, the landraces were grouped into three clusters according to seed size and shape, vegetative growth habit and genetic resistance. A total of 151 alleles were detected with an average of 4 alleles per locus and an average polymorphism information content of 0.31. Using a model-based approach, on the basis of neutral markers implemented in the software STRUCTURE, three clusters were inferred, which were in good agreement with multivariate analysis. Geographic and genetic distances were congruent with the exception of a few putative hybrids identified in this study, suggesting a predominant effect of isolation by distance. Genomic scans using both markers linked to genes affected by selection (outlier) and neutral markers showed advantages relative to other approaches, since they help to create a more complete picture of how adaptation to environmental conditions has sculpted the common bean genomes in southern Europe. The use of outlier loci also gives a clue about what selective forces gave rise to the actual phenotypes of the analysed landraces.

Effect of religion on the attitude of primiparous women toward genetic testing.

PubMed

Usta, Ihab M; Nassar, Anwar H; Abu-Musa, Antoine A; Hannoun, Antoine

2010-03-01

Factors that influence a pregnant woman's decision to accept or decline genetic tests are largely undefined. The objective of this study was to determine the acceptance rate of prenatal diagnostic testing in Lebanon according to religion. Prenatal charts were reviewed to obtain information about prenatal genetic testing. Women were divided according to their religion and were compared regarding the acceptance of triple screen test (TST) or amniocentesis (AMN) and reasons for declining such tests. Differences between groups were examined using the student's t-test, chi(2)-test and multivariate analysis (age >or= 35 years, religion, education and class). The religious distribution was 73.8% Moslems, 14.0% Christians and 11.2% Druze. Utilization of TST, AMN, and either (TST/AMN) was 61.2%, 7.6% and 67.0%, respectively. Uptake of TST/AMN was highest in Christians and lowest in Moslems and that of AMN higher in Christians >or= 35 years compared with Moslems. On multivariate analysis, none of the factors studied significantly affected the utilization of TST or TST/AMN except for age >or= 35 years which was associated with a borderline decrease in the utilization of TST Odds Ratio (OR) 0.485 (95% CI 0.21-1.12). The utilization of AMN significantly increased with age >or= 35 years OR 7.19 (95% CI 2.65-19.56) and lower education. Religion does not seem to affect utilization of prenatal diagnostic tests in Lebanon. Copyright (c) 2010 John Wiley & Sons, Ltd.

Genetic variants associated with physical and mental characteristics of the elite athletes in the Polish population.

PubMed

Peplonska, B; Adamczyk, J G; Siewierski, M; Safranow, K; Maruszak, A; Sozanski, H; Gajewski, A K; Zekanowski, C

2017-08-01

The aim of the study was to assess whether selected genetic variants are associated with elite athlete performance in a group of 413 elite athletes and 451 sedentary controls. Polymorphisms in ACE, ACTN3, AGT, NRF-2, PGC1A, PPARG, and TFAM implicated in physical performance traits were analyzed. Additionally, polymorphisms in CHRNB3 and FAAH coding for proteins modulating activity of brain's emotion centers were included. The results of univariate analyses indicated that the elite athletic performance is associated with four polymorphisms: ACE (rs4341, P = 0.0095), NRF-2 (rs12594956, P = 0.011), TFAM (rs2306604, P = 0.049), and FAAH (rs324420, P = 0.0041). The multivariate analysis adjusted for age and gender confirmed this association. The higher number of ACE D alleles (P = 0.0021) and the presence of NRF-2 rs12594956 A allele (P = 0.0067) are positive predictors, whereas TFAM rs2306604 GG genotype (P = 0.031) and FAAH rs324420 AA genotype (P = 0.0084) negatively affect the elite athletic performance. The CHRNB3 variant (rs4950, G allele) is significantly more frequent in the endurance athletes compared with the power ones (P = 0.025). Multivariate analysis demonstrated that the presence of rs4950 G allele contributes to endurance performance (P = 0.0047). Our results suggest that genetic inheritance of psychological traits should be taken into consideration while trying to decipher a genetic profile of top athletic performance. © 2016 The Authors. Scandinavian Journal of Medicine & Science in Sports published by John Wiley & Sons Ltd.

Multivariate analysis and extraction of parameters in resistive RAMs using the Quantum Point Contact model

NASA Astrophysics Data System (ADS)

Roldán, J. B.; Miranda, E.; González-Cordero, G.; García-Fernández, P.; Romero-Zaliz, R.; González-Rodelas, P.; Aguilera, A. M.; González, M. B.; Jiménez-Molinos, F.

2018-01-01

A multivariate analysis of the parameters that characterize the reset process in Resistive Random Access Memory (RRAM) has been performed. The different correlations obtained can help to shed light on the current components that contribute in the Low Resistance State (LRS) of the technology considered. In addition, a screening method for the Quantum Point Contact (QPC) current component is presented. For this purpose, the second derivative of the current has been obtained using a novel numerical method which allows determining the QPC model parameters. Once the procedure is completed, a whole Resistive Switching (RS) series of thousands of curves is studied by means of a genetic algorithm. The extracted QPC parameter distributions are characterized in depth to get information about the filamentary pathways associated with LRS in the low voltage conduction regime.

Integrating Genetic, Neuropsychological and Neuroimaging Data to Model Early-Onset Obsessive Compulsive Disorder Severity

PubMed Central

Mas, Sergi; Gassó, Patricia; Morer, Astrid; Calvo, Anna; Bargalló, Nuria; Lafuente, Amalia; Lázaro, Luisa

2016-01-01

We propose an integrative approach that combines structural magnetic resonance imaging data (MRI), diffusion tensor imaging data (DTI), neuropsychological data, and genetic data to predict early-onset obsessive compulsive disorder (OCD) severity. From a cohort of 87 patients, 56 with complete information were used in the present analysis. First, we performed a multivariate genetic association analysis of OCD severity with 266 genetic polymorphisms. This association analysis was used to select and prioritize the SNPs that would be included in the model. Second, we split the sample into a training set (N = 38) and a validation set (N = 18). Third, entropy-based measures of information gain were used for feature selection with the training subset. Fourth, the selected features were fed into two supervised methods of class prediction based on machine learning, using the leave-one-out procedure with the training set. Finally, the resulting model was validated with the validation set. Nine variables were used for the creation of the OCD severity predictor, including six genetic polymorphisms and three variables from the neuropsychological data. The developed model classified child and adolescent patients with OCD by disease severity with an accuracy of 0.90 in the testing set and 0.70 in the validation sample. Above its clinical applicability, the combination of particular neuropsychological, neuroimaging, and genetic characteristics could enhance our understanding of the neurobiological basis of the disorder. PMID:27093171

Imaging genetics in attention-deficit/hyperactivity disorder and related neurodevelopmental domains: state of the art.

PubMed

Vilor-Tejedor, Natàlia; Cáceres, Alejandro; Pujol, Jesús; Sunyer, Jordi; González, Juan R

2017-12-01

Joint analysis of genetic and neuroimaging data, known as Imaging Genetics (IG), offers an opportunity to deepen our knowledge of the biological mechanisms of neurodevelopmental domains. There has been exponential growth in the literature on IG studies, which challenges the standardization of analysis methods in this field. In this review we give a complete up-to-date account of IG studies on attention deficit hyperactivity disorder (ADHD) and related neurodevelopmental domains, which serves as a reference catalog for researchers working on this neurological disorder. We searched MEDLINE/Pubmed and identified 37 articles on IG of ADHD that met our eligibility criteria. We carefully cataloged these articles according to imaging technique, genes and brain region, and summarized the main results and characteristics of each study. We found that IG studies on ADHD generally focus on dopaminergic genes and the structure of basal ganglia using structural Magnetic Resonance Imaging (MRI). We found little research involving multiple genetic factors and brain regions because of the scarce use of multivariate strategies in data analysis. IG of ADHD and related neurodevelopmental domains is still in its early stages, and a lack of replicated findings is one of the most pressing challenges in the field.

Potential of SNP markers for the characterization of Brazilian cassava germplasm.

PubMed

de Oliveira, Eder Jorge; Ferreira, Cláudia Fortes; da Silva Santos, Vanderlei; de Jesus, Onildo Nunes; Oliveira, Gilmara Alvarenga Fachardo; da Silva, Maiane Suzarte

2014-06-01

High-throughput markers, such as SNPs, along with different methodologies were used to evaluate the applicability of the Bayesian approach and the multivariate analysis in structuring the genetic diversity in cassavas. The objective of the present work was to evaluate the diversity and genetic structure of the largest cassava germplasm bank in Brazil. Complementary methodological approaches such as discriminant analysis of principal components (DAPC), Bayesian analysis and molecular analysis of variance (AMOVA) were used to understand the structure and diversity of 1,280 accessions genotyped using 402 single nucleotide polymorphism markers. The genetic diversity (0.327) and the average observed heterozygosity (0.322) were high considering the bi-allelic markers. In terms of population, the presence of a complex genetic structure was observed indicating the formation of 30 clusters by DAPC and 34 clusters by Bayesian analysis. Both methodologies presented difficulties and controversies in terms of the allocation of some accessions to specific clusters. However, the clusters suggested by the DAPC analysis seemed to be more consistent for presenting higher probability of allocation of the accessions within the clusters. Prior information related to breeding patterns and geographic origins of the accessions were not sufficient for providing clear differentiation between the clusters according to the AMOVA analysis. In contrast, the F ST was maximized when considering the clusters suggested by the Bayesian and DAPC analyses. The high frequency of germplasm exchange between producers and the subsequent alteration of the name of the same material may be one of the causes of the low association between genetic diversity and geographic origin. The results of this study may benefit cassava germplasm conservation programs, and contribute to the maximization of genetic gains in breeding programs.

Racial differences in circulating natriuretic peptide levels: the atherosclerosis risk in communities study.

PubMed

Gupta, Deepak K; Claggett, Brian; Wells, Quinn; Cheng, Susan; Li, Man; Maruthur, Nisa; Selvin, Elizabeth; Coresh, Josef; Konety, Suma; Butler, Kenneth R; Mosley, Thomas; Boerwinkle, Eric; Hoogeveen, Ron; Ballantyne, Christie M; Solomon, Scott D

2015-05-21

Natriuretic peptides promote natriuresis, diuresis, and vasodilation. Experimental deficiency of natriuretic peptides leads to hypertension (HTN) and cardiac hypertrophy, conditions more common among African Americans. Hospital-based studies suggest that African Americans may have reduced circulating natriuretic peptides, as compared to Caucasians, but definitive data from community-based cohorts are lacking. We examined plasma N-terminal pro B-type natriuretic peptide (NTproBNP) levels according to race in 9137 Atherosclerosis Risk in Communities (ARIC) Study participants (22% African American) without prevalent cardiovascular disease at visit 4 (1996-1998). Multivariable linear and logistic regression analyses were performed adjusting for clinical covariates. Among African Americans, percent European ancestry was determined from genetic ancestry informative markers and then examined in relation to NTproBNP levels in multivariable linear regression analysis. NTproBNP levels were significantly lower in African Americans (median, 43 pg/mL; interquartile range [IQR], 18, 88) than Caucasians (median, 68 pg/mL; IQR, 36, 124; P<0.0001). In multivariable models, adjusted log NTproBNP levels were 40% lower (95% confidence interval [CI], -43, -36) in African Americans, compared to Caucasians, which was consistent across subgroups of age, gender, HTN, diabetes, insulin resistance, and obesity. African-American race was also significantly associated with having nondetectable NTproBNP (adjusted OR, 5.74; 95% CI, 4.22, 7.80). In multivariable analyses in African Americans, a 10% increase in genetic European ancestry was associated with a 7% (95% CI, 1, 13) increase in adjusted log NTproBNP. African Americans have lower levels of plasma NTproBNP than Caucasians, which may be partially owing to genetic variation. Low natriuretic peptide levels in African Americans may contribute to the greater risk for HTN and its sequalae in this population. © 2015 The Authors. Published on behalf of the American Heart Association, Inc., by Wiley Blackwell.

Learning Abilities and Disabilities: Generalist Genes, Specialist Environments

PubMed Central

Kovas, Yulia; Plomin, Robert

2007-01-01

Twin studies comparing identical and fraternal twins consistently show substantial genetic influence on individual differences in learning abilities such as reading and mathematics, as well as in other cognitive abilities such as spatial ability and memory. Multivariate genetic research has shown that the same set of genes is largely responsible for genetic influence on these diverse cognitive areas. We call these “generalist genes.” What differentiates these abilities is largely the environment, especially nonshared environments that make children growing up in the same family different from one another. These multivariate genetic findings of generalist genes and specialist environments have far-reaching implications for diagnosis and treatment of learning disabilities and for understanding the brain mechanisms that mediate these effects. PMID:20351764

TNFRSF10C copy number variation is associated with metastatic colorectal cancer

PubMed Central

Tanenbaum, Daniel G.; Hall, William A.; Colbert, Lauren E.; Bastien, Amanda J.; Brat, Daniel J.; Kong, Jun; Kim, Sungjin; Dwivedi, Bhakti; Kowalski, Jeanne; Landry, Jerome C.

2016-01-01

Background Genetic markers for distant metastatic disease in patients with colorectal cancer (CRC) are not well defined. Identification of genetic alterations associated with metastatic CRC could help to guide systemic and local treatment strategies. We evaluated the association of tumor necrosis factor receptor superfamily member 10C (TNFRSF10C) copy number variation (CNV) with distant metastatic disease in patients with CRC using The Cancer Genome Atlas (TCGA). Methods Genetic sequencing data and clinical characteristics were obtained from TCGA for all available patients with CRC. There were 515 CRC patient samples with CNV and clinical outcome data, including a subset of 144 rectal adenocarcinoma patient samples. Using the TCGA CRC dataset, CNV of TNFRSF10C was evaluated for association with distant metastatic disease (M1 vs. M0). Multivariate logistic regression analysis with odds ratio (OR) using a 95% confidence interval (CI) was performed adjusting for age, T stage, N stage, adjuvant chemotherapy, gender, microsatellite instability (MSI), location, and surgical margin status. Results TNFRSF10C CNV in patients with CRC was associated with distant metastatic disease [OR 4.81 (95% CI, 2.13–10.85) P<0.001] and positive lymph nodes [OR 18.83 (95% CI, 8.42–42.09)]; P<0.001) but not MSI (OR P=0.799). On multivariate analysis, after adjusting for pathologic T stage, N stage, adjuvant chemotherapy, gender, and MSI, TNFRSF10C CNV remained significantly associated with distant metastatic disease (OR P=0.018). Subset analysis revealed that TNFRSF10C CNV was also significantly associated with distant metastatic disease in patients with rectal adenocarcinoma (OR P=0.016). Conclusions TNFRSF10C CNV in patients with CRC is associated with distant metastatic disease. With further validation, such genetic profiles could be used clinically to support optimal systemic treatment strategies versus more aggressive local therapies in patients with CRC, including radiation therapy for rectal adenocarcinoma. PMID:27284460

Identifying Pleiotropic Genes in Genome-Wide Association Studies for Multivariate Phenotypes with Mixed Measurement Scales

PubMed Central

Williams, L. Keoki; Buu, Anne

2017-01-01

We propose a multivariate genome-wide association test for mixed continuous, binary, and ordinal phenotypes. A latent response model is used to estimate the correlation between phenotypes with different measurement scales so that the empirical distribution of the Fisher’s combination statistic under the null hypothesis is estimated efficiently. The simulation study shows that our proposed correlation estimation methods have high levels of accuracy. More importantly, our approach conservatively estimates the variance of the test statistic so that the type I error rate is controlled. The simulation also shows that the proposed test maintains the power at the level very close to that of the ideal analysis based on known latent phenotypes while controlling the type I error. In contrast, conventional approaches–dichotomizing all observed phenotypes or treating them as continuous variables–could either reduce the power or employ a linear regression model unfit for the data. Furthermore, the statistical analysis on the database of the Study of Addiction: Genetics and Environment (SAGE) demonstrates that conducting a multivariate test on multiple phenotypes can increase the power of identifying markers that may not be, otherwise, chosen using marginal tests. The proposed method also offers a new approach to analyzing the Fagerström Test for Nicotine Dependence as multivariate phenotypes in genome-wide association studies. PMID:28081206

Linkage Analysis of a Model Quantitative Trait in Humans: Finger Ridge Count Shows Significant Multivariate Linkage to 5q14.1

PubMed Central

Medland, Sarah E; Loesch, Danuta Z; Mdzewski, Bogdan; Zhu, Gu; Montgomery, Grant W; Martin, Nicholas G

2007-01-01

The finger ridge count (a measure of pattern size) is one of the most heritable complex traits studied in humans and has been considered a model human polygenic trait in quantitative genetic analysis. Here, we report the results of the first genome-wide linkage scan for finger ridge count in a sample of 2,114 offspring from 922 nuclear families. Both univariate linkage to the absolute ridge count (a sum of all the ridge counts on all ten fingers), and multivariate linkage analyses of the counts on individual fingers, were conducted. The multivariate analyses yielded significant linkage to 5q14.1 (Logarithm of odds [LOD] = 3.34, pointwise-empirical p-value = 0.00025) that was predominantly driven by linkage to the ring, index, and middle fingers. The strongest univariate linkage was to 1q42.2 (LOD = 2.04, point-wise p-value = 0.002, genome-wide p-value = 0.29). In summary, the combination of univariate and multivariate results was more informative than simple univariate analyses alone. Patterns of quantitative trait loci factor loadings consistent with developmental fields were observed, and the simple pleiotropic model underlying the absolute ridge count was not sufficient to characterize the interrelationships between the ridge counts of individual fingers. PMID:17907812

Heritability of Nociception IV: Neuropathic pain assays are genetically distinct across methods of peripheral nerve injury

PubMed Central

Young, Erin E.; Costigan, Michael; Herbert, Teri A.; Lariviere, William R.

2013-01-01

Prior genetic correlation analysis of 22 heritable behavioral measures of nociception and hypersensitivity in the mouse identified five genetically distinct pain types. In the present study, we reanalyzed that dataset and included the results of an additional nine assays of nociception and hypersensitivity to: 1) replicate the previously identified five pain types; 2) test whether any of the newly added pain assays represent novel genetically distinct pain types; 3) test the level of genetic relatedness among nine commonly employed neuropathic pain assays. Multivariate analysis of pairwise correlations between assays shows that the newly added zymosan-induced heat hypersensitivity assay does not conform to the two previously identified groups of heat hypersensitivity assays and cyclophosphamide-induced cystitis, the first organ-specific visceral pain model examined, is genetically distinct from other inflammatory assays. The four included mechanical hypersensitivity assays are genetically distinct, and do not comprise a single pain type as previously reported. Among the nine neuropathic pain assays including autotomy, chemotherapy, nerve ligation and spared nerve injury assays, at least four genetically distinct types of neuropathic sensory abnormalities were identified, corresponding to differences in nerve injury method. In addition, two itch assays and Comt genotype were compared to the expanded set of nociception and hypersensitivity assays. Comt genotype was strongly related only to spontaneous inflammatory nociception assays. These results indicate the priority for continued investigation of genetic mechanisms in several assays newly identified to represent genetically distinct pain types. PMID:24071598

Gene-set and multivariate genome-wide association analysis of oppositional defiant behavior subtypes in attention-deficit/hyperactivity disorder.

PubMed

Aebi, Marcel; van Donkelaar, Marjolein M J; Poelmans, Geert; Buitelaar, Jan K; Sonuga-Barke, Edmund J S; Stringaris, Argyris; Consortium, Image; Faraone, Stephen V; Franke, Barbara; Steinhausen, Hans-Christoph; van Hulzen, Kimm J E

2016-07-01

Oppositional defiant disorder (ODD) is a frequent psychiatric disorder seen in children and adolescents with attention-deficit-hyperactivity disorder (ADHD). ODD is also a common antecedent to both affective disorders and aggressive behaviors. Although the heritability of ODD has been estimated to be around 0.60, there has been little research into the molecular genetics of ODD. The present study examined the association of irritable and defiant/vindictive dimensions and categorical subtypes of ODD (based on latent class analyses) with previously described specific polymorphisms (DRD4 exon3 VNTR, 5-HTTLPR, and seven OXTR SNPs) as well as with dopamine, serotonin, and oxytocin genes and pathways in a clinical sample of children and adolescents with ADHD. In addition, we performed a multivariate genome-wide association study (GWAS) of the aforementioned ODD dimensions and subtypes. Apart from adjusting the analyses for age and sex, we controlled for "parental ability to cope with disruptive behavior." None of the hypothesis-driven analyses revealed a significant association with ODD dimensions and subtypes. Inadequate parenting behavior was significantly associated with all ODD dimensions and subtypes, most strongly with defiant/vindictive behaviors. In addition, the GWAS did not result in genome-wide significant findings but bioinformatics and literature analyses revealed that the proteins encoded by 28 of the 53 top-ranked genes functionally interact in a molecular landscape centered around Beta-catenin signaling and involved in the regulation of neurite outgrowth. Our findings provide new insights into the molecular basis of ODD and inform future genetic studies of oppositional behavior. © 2015 The Authors. American Journal of Medical Genetics Part B: Neuropsychiatric Genetics Published by Wiley Periodicals, Inc. © 2015 The Authors. American Journal of Medical Genetics Part B: Neuropsychiatric Genetics Published by Wiley Periodicals, Inc.

Common genetic factors among sexual orientation, gender nonconformity, and number of sex partners in female twins: implications for the evolution of homosexuality.

PubMed

Burri, Andrea; Spector, Tim; Rahman, Qazi

2015-04-01

Homosexuality is a stable population-level trait in humans that lowers direct fitness and yet is substantially heritable, resulting in a so-called Darwinian "paradox." Evolutionary models have proposed that polymorphic genes influencing homosexuality confer a reproductive benefit to heterosexual carriers, thus offsetting the fitness costs associated with persistent homosexuality. This benefit may consist of a "sex typicality" intermediate phenotype. However, there are few empirical tests of this hypothesis using genetically informative data in humans. This study aimed to test the hypothesis that common genetic factors can explain the association between measures of sex typicality, mating success, and homosexuality in a Western (British) sample of female twins. Here, we used data from 996 female twins (498 twin pairs) comprising 242 full dizygotic pairs and 256 full monozygotic pairs (mean age 56.8) and 1,555 individuals whose co-twin did not participate. Measures of sexual orientation, sex typicality (recalled childhood gender nonconformity), and mating success (number of lifetime sexual partners) were completed. Variables were subject to multivariate variance component analysis. We found that masculine women are more likely to be nonheterosexual, report more sexual partners, and, when heterosexual, also report more sexual partners. Multivariate twin modeling showed that common genetic factors explained the relationship between sexual orientation, sex typicality, and mating success through a shared latent factor. Our findings suggest that genetic factors responsible for nonheterosexuality are shared with genetic factors responsible for the number of lifetime sexual partners via a latent sex typicality phenotype in human females. These results may have implications for evolutionary models of homosexuality but are limited by potential mediating variables (such as personality traits) and measurement issues. © 2015 International Society for Sexual Medicine.

MTHFR, TS and XRCC1 genetic variants may affect survival in patients with myelodysplastic syndromes treated with supportive care or azacitidine.

PubMed

Visani, G; Loscocco, F; Ruzzo, A; Galimberti, S; Graziano, F; Voso, M T; Giacomini, E; Finelli, C; Ciabatti, E; Fabiani, E; Barulli, S; Volpe, A; Magro, D; Piccaluga, P; Fuligni, F; Vignetti, M; Fazi, P; Piciocchi, A; Gabucci, E; Rocchi, M; Magnani, M; Isidori, A

2017-12-05

We evaluated the impact of genomic polymorphisms in folate-metabolizing, DNA synthesis and DNA repair enzymes on the clinical outcome of 108 patients with myelodysplastic syndromes (MDS) receiving best supportive care (BSC) or azacitidine. A statistically significant association between methylenetetrahydrofolate reductase (MTHFR) 677T/T, thymidylate synthase (TS) 5'-untranslated region (UTR) 3RG, TS 3'-UTR -6 bp/-6 bp, XRCC1 399G/G genotypes and short survival was found in patients receiving BSC by multivariate analysis (P<0.001; P=0.026; P=0.058; P=0.024). MTHFR 677T/T, TS 3'-UTR -6 bp/-6 bp and XRCC1 399G/G genotypes were associated with short survival in patients receiving azacitidine by multivariate analysis (P<0.001; P=0.004; P=0.002). We then performed an exploratory analysis to evaluate the effect of the simultaneous presence of multiple adverse variant genotypes. Interestingly, patients with ⩾1 adverse genetic variants had a short survival, independently from their International Prognostic Scoring System (IPSS) and therapy received. To our knowledge, this is the first study showing that polymorphisms in folate-metabolizing pathway, DNA synthesis and DNA repair genes could influence survival of MDS patients.The Pharmacogenomics Journal advance online publication, 5 December 2017; doi:10.1038/tpj.2017.48.

Clinical, biomarker, and genetic predictors of specific types of atrial fibrillation in a community-based cohort: data of the PREVEND study.

PubMed

Hobbelt, Anne H; Siland, Joylene E; Geelhoed, Bastiaan; Van Der Harst, Pim; Hillege, Hans L; Van Gelder, Isabelle C; Rienstra, Michiel

2017-02-01

Atrial fibrillation (AF) may present variously in time, and AF may progress from self-terminating to non-self-terminating AF, and is associated with impaired prognosis. However, predictors of AF types are largely unexplored. We investigate the clinical, biomarker, and genetic predictors of development of specific types of AF in a community-based cohort. We included 8042 individuals (319 with incident AF) of the PREVEND study. Types of AF were compared, and multivariate multinomial regression analysis determined associations with specific types of AF. Mean age was 48.5 ± 12.4 years and 50% were men. The types of incident AF were ascertained based on electrocardiograms; 103(32%) were classified as AF without 2-year recurrence, 158(50%) as self-terminating AF, and 58(18%) as non-self-terminating AF. With multivariate multinomial logistic regression analysis, advancing age (P< 0.001 for all three types) was associated with all AF types, male sex was associated with AF without 2-year recurrence and self-terminating AF (P= 0.031 and P= 0.008, respectively). Increasing body mass index and MR-proANP were associated with both self-terminating (P= 0.009 and P< 0.001) and non-self-terminating AF (P= 0.003 and P< 0.001). The only predictor associated with solely self-terminating AF is prescribed anti-hypertensive treatment (P= 0.019). The following predictors were associated with non-self-terminating AF; lower heart rate (P= 0.018), lipid-lowering treatment prescribed (P= 0.009), and eGFR <60 mL/min/1.73 m2 (P= 0.006). Three known AF-genetic variants (rs6666258, rs6817105, and rs10821415) were associated with self-terminating AF. We found clinical, biomarker and genetic predictors of specific types of incident AF in a community-based cohort. The genetic background seems to play a more important role than modifiable risk factors in self-terminating AF.

Further blood genetic studies on Amazonian diversity--data from four Indian groups.

PubMed

Callegari-Jacques, S M; Salzano, F M; Weimer, T A; Hutz, M H; Black, F L; Santos, S E; Guerreiro, J F; Mestriner, M A; Pandey, J P

1994-01-01

Information related to 31 protein genetic systems was obtained for 307 individuals affiliated with the Cinta Larga, Karitiana, Surui and Kararaô Indians of northern Brazil. In terms of genetic distances the Cinta Larga showed more similarities with the Karitiana (both are Tupi-speaking tribes), while at a more distant level the Surui clustered with the Kararaô. The latter, a Cayapo subgroup, showed a completely different genetic constitution from the other subgroups of this same tribe. Both the Kararaô and Karitiana are small, remnant populations, and their gene pools have presumably been severely affected by random and founder effects. These results were incorporated with those of 25 other Amazonian Indian tribes, and analysis by two multivariate techniques confirmed a previously observed geographical dichotomy, suggesting either that the Amazon river constitutes a barrier to north-south gene flow or that latitudinally different past migrations entered the region from the west.

Impact of US Brown Swiss genetics on milk quality from low-input herds in Switzerland: interactions with grazing intake and pasture type.

PubMed

Stergiadis, S; Bieber, A; Franceschin, E; Isensee, A; Eyre, M D; Maurer, V; Chatzidimitriou, E; Cozzi, G; Bapst, B; Stewart, G; Gordon, A; Butler, G

2015-05-15

This study investigated the effect of, and interactions between, contrasting crossbreed genetics (US Brown Swiss [BS] × Improved Braunvieh [BV] × Original Braunvieh [OB]) and feeding regimes (especially grazing intake and pasture type) on milk fatty acid (FA) profiles. Concentrations of total polyunsaturated FAs, total omega-3 FAs and trans palmitoleic, vaccenic, α-linolenic, eicosapentaenoic and docosapentaenoic acids were higher in cows with a low proportion of BS genetics. Highest concentrations of the nutritionally desirable FAs, trans palmitoleic, vaccenic and eicosapentaenoic acids were found for cows with a low proportion of BS genetics (0-24% and/or 25-49%) on high grazing intake (75-100% of dry matter intake) diets. Multivariate analysis indicated that the proportion of OB genetics is a positive driver for nutritionally desirable monounsaturated and polyunsaturated FAs while BS genetics proportion was positive driver for total and undesirable individual saturated FAs. Significant genetics × feeding regime interactions were also detected for a range of FAs. Copyright © 2014 Elsevier Ltd. All rights reserved.

The ABCs of Math: A Genetic Analysis of Mathematics and Its Links With Reading Ability and General Cognitive Ability

PubMed Central

Hart, Sara A.; Petrill, Stephen A.; Thompson, Lee A.; Plomin, Robert

2009-01-01

The goal of this first major report from the Western Reserve Reading Project Math component is to explore the etiology of the relationship among tester-administered measures of mathematics ability, reading ability, and general cognitive ability. Data are available on 314 pairs of monozygotic and same-sex dizygotic twins analyzed across 5 waves of assessment. Univariate analyses provide a range of estimates of genetic (h2 = .00 –.63) and shared (c2 = .15–.52) environmental influences across math calculation, fluency, and problem solving measures. Multivariate analyses indicate genetic overlap between math problem solving with general cognitive ability and reading decoding, whereas math fluency shares significant genetic overlap with reading fluency and general cognitive ability. Further, math fluency has unique genetic influences. In general, math ability has shared environmental overlap with general cognitive ability and decoding. These results indicate that aspects of math that include problem solving have different genetic and environmental influences than math calculation. Moreover, math fluency, a timed measure of calculation, is the only measured math ability with unique genetic influences. PMID:20157630

Physical exercise counteracts genetic susceptibility to depression.

PubMed

Haslacher, Helmuth; Michlmayr, Matthias; Batmyagmar, Delgerdalai; Perkmann, Thomas; Ponocny-Seliger, Elisabeth; Scheichenberger, Vanessa; Pilger, Alexander; Dal-Bianco, Peter; Lehrner, Johann; Pezawas, Lukas; Wagner, Oswald; Winker, Robert

2015-01-01

Depression is a highly prevalent disorder in elderly individuals. A genetic variant (rs6265) of the brain-derived neurotrophic factor (BDNF) impacting on emotion processing is known to increase the risk for depression. We aim to investigate whether intensive endurance sports might attenuate this genetic susceptibility in a cohort of elderly marathon athletes. Fifty-five athletes and 58 controls were included. rs6265 of the BDNF gene was genotyped by the TaqMan method. Depressive symptoms were assessed by standardized self-rating tests (BDI = Beck Depression Inventory, GDS = Geriatric Depression Scale). In multivariable analysis of BDI and GDS scores, the interaction between group (athletes vs. controls) and genotypes ([C];[C] vs. [C];[T] + [T];[T]) was found to be statistically significant (BDI: p = 0.027, GDS: p = 0.013). Among [C];[C] carriers, merely controls had an increased relative risk of 3.537 (95% CI = 1.276-9.802) of achieving a subclinical depression score ≥10 on the BDI. There was no such effect in carriers of the [T] allele. In a multivariable binary logistic regression, genetic information, group (athletes/controls), but no information on rs6265 allele carrier status presented as a significant predictor of BDI scores ≥10. Physical exercise positively affects BDNF effects on mood. Since 66Met BDNF secretion is impaired, this effect seems to be much stronger in [C];[C] homozygous individuals expressing the 66Val variant. This confirms that genetic susceptibility to depressive symptoms can indeed be influenced by endurance sports in elderly people. © 2015 S. Karger AG, Basel.

Progressive erosion of genetic and epigenetic variation in callus-derived cocoa (Theobroma cacao) plants.

PubMed

Rodríguez López, Carlos M; Wetten, Andrew C; Wilkinson, Michael J

2010-06-01

*Relatively little is known about the timing of genetic and epigenetic forms of somaclonal variation arising from callus growth. We surveyed for both types of change in cocoa (Theobroma cacao) plants regenerated from calli of various ages, and also between tissues from the source trees. *For genetic change, we used 15 single sequence repeat (SSR) markers from four source trees and from 233 regenerated plants. For epigenetic change, we used 386 methylation-sensitive amplified polymorphism (MSAP) markers on leaf and explant (staminode) DNA from two source trees and on leaf DNA from 114 regenerants. *Genetic variation within source trees was limited to one slippage mutation in one leaf. Regenerants were far more variable, with 35% exhibiting at least one mutation. Genetic variation initially accumulated with culture age but subsequently declined. MSAP (epigenetic) profiles diverged between leaf and staminode samples from source trees. Multivariate analysis revealed that leaves from regenerants occupied intermediate eigenspace between leaves and staminodes of source plants but became progressively more similar to source tree leaves with culture age. *Statistical analysis confirmed this rather counterintuitive finding that leaves of 'late regenerants' exhibited significantly less genetic and epigenetic divergence from source leaves than those exposed to short periods of callus growth.

Estimation of Genetic Parameters from Longitudinal Records of Body Weight of Berkshire Pigs

PubMed Central

Lee, Dong-Hee; Do, Chang-Hee

2012-01-01

Direct and maternal genetic heritabilities and their correlations with body weight at 5 stages in the life span of purebred Berkshire pigs, from birth to harvest, were estimated to scrutinize body weight development with the records for 5,088 purebred Berkshire pigs in a Korean farm, using the REML based on an animal model. Body weights were measured at birth (Birth), at weaning (Weaning: mean 22.9 d), at the beginning of a performance test (On: mean 72.7 d), at the end of a performance test (Off: mean 152.4 d), and at harvest (Finish: mean 174.3 d). Ordinary polynomials and Legendre with order 1, 2, and 3 were adopted to adjust body weight with age in the multivariate animal models. Legendre with order 3 fitted best concerning prediction error deviation (PED) and yielded the lowest AIC for multivariate analysis of longitudinal body weights. Direct genetic correlations between body weight at Birth and body weight at Weaning, On, Off, and Finish were 0.48, 0.36, 0.10, and 0.10, respectively. The estimated maternal genetic correlations of body weight at Finish with body weight at Birth, Weaning, On, and Off were 0.39, 0.49, 0.65, and 0.90, respectively. Direct genetic heritabilities progressively increased from birth to harvest and were 0.09, 0.11, 0.20, 0.31, and 0.43 for body weight at Birth, Weaning, On, Off, and Finish, respectively. Maternal genetic heritabilities generally decreased and were 0.26, 0.34, 0.15, 0.10, and 0.10 for body weight at Birth, Weaning, On, Off, and Finish, respectively. As pigs age, maternal genetic effects on growth are reduced and pigs begin to rely more on the expression of their own genes. Although maternal genetic effects on body weight may not be large, they are sustained through life. PMID:25049624

Heritable influences on behavioural problems from early childhood to mid-adolescence: evidence for genetic stability and innovation.

PubMed

Lewis, G J; Plomin, R

2015-07-01

Although behavioural problems (e.g., anxiety, conduct, hyperactivity, peer problems) are known to be heritable both in early childhood and in adolescence, limited work has examined prediction across these ages, and none using a genetically informative sample. We examined, first, whether parental ratings of behavioural problems (indexed by the Strengths and Difficulties questionnaire) at ages 4, 7, 9, 12, and 16 years were stable across these ages. Second, we examined the extent to which stability reflected genetic or environmental effects through multivariate quantitative genetic analysis on data from a large (n > 3000) population (UK) sample of monozygotic and dizygotic twins. Behavioural problems in early childhood (age 4 years) showed significant associations with the corresponding behavioural problem at all subsequent ages. Moreover, stable genetic influences were observed across ages, indicating that biological bases underlying behavioural problems in adolescence are underpinned by genetic influences expressed as early as age 4 years. However, genetic and environmental innovations were also observed at each age. These observations indicate that genetic factors are important for understanding stable individual differences in behavioural problems across childhood and adolescence, although novel genetic influences also facilitate change in such behaviours.

Candidate genetic pathways for attention-deficit/hyperactivity disorder (ADHD) show association to hyperactive/impulsive symptoms in children with ADHD.

PubMed

Bralten, Janita; Franke, Barbara; Waldman, Irwin; Rommelse, Nanda; Hartman, Catharina; Asherson, Philip; Banaschewski, Tobias; Ebstein, Richard P; Gill, Michael; Miranda, Ana; Oades, Robert D; Roeyers, Herbert; Rothenberger, Aribert; Sergeant, Joseph A; Oosterlaan, Jaap; Sonuga-Barke, Edmund; Steinhausen, Hans-Christoph; Faraone, Stephen V; Buitelaar, Jan K; Arias-Vásquez, Alejandro

2013-11-01

Because multiple genes with small effect sizes are assumed to play a role in attention-deficit/hyperactivity disorder (ADHD) etiology, considering multiple variants within the same analysis likely increases the total explained phenotypic variance, thereby boosting the power of genetic studies. This study investigated whether pathway-based analysis could bring scientists closer to unraveling the biology of ADHD. The pathway was described as a predefined gene selection based on a well-established database or literature data. Common genetic variants in pathways involved in dopamine/norepinephrine and serotonin neurotransmission and genes involved in neuritic outgrowth were investigated in cases from the International Multicentre ADHD Genetics (IMAGE) study. Multivariable analysis was performed to combine the effects of single genetic variants within the pathway genes. Phenotypes were DSM-IV symptom counts for inattention and hyperactivity/impulsivity (n = 871) and symptom severity measured with the Conners Parent (n = 930) and Teacher (n = 916) Rating Scales. Summing genetic effects of common genetic variants within the pathways showed a significant association with hyperactive/impulsive symptoms ((p)empirical = .007) but not with inattentive symptoms ((p)empirical = .73). Analysis of parent-rated Conners hyperactive/impulsive symptom scores validated this result ((p)empirical = .0018). Teacher-rated Conners scores were not associated. Post hoc analyses showed a significant contribution of all pathways to the hyperactive/impulsive symptom domain (dopamine/norepinephrine, (p)empirical = .0004; serotonin, (p)empirical = .0149; neuritic outgrowth, (p)empirical = .0452). The present analysis shows an association between common variants in 3 genetic pathways and the hyperactive/impulsive component of ADHD. This study demonstrates that pathway-based association analyses, using quantitative measurements of ADHD symptom domains, can increase the power of genetic analyses to identify biological risk factors involved in this disorder. Copyright © 2013 American Academy of Child and Adolescent Psychiatry. Published by Elsevier Inc. All rights reserved.

GENETIC AND ENVIRONMENTAL CONTRIBUTIONS TO THE CO-OCCURRENCE OF DEPRESSIVE PERSONALITY DISORDER AND DSM-IV PERSONALITY DISORDERS

PubMed Central

Ørstavik, Ragnhild E.; Kendler, Kenneth S.; Røysamb, Espen; Czajkowski, Nikolai; Tambs, Kristian; Reichborn-Kjennerud, Ted

2012-01-01

One of the main controversies with regard to depressive personality disorder (DPD) concerns the co-occurrence with the established DSM-IV personality disorders (PDs). The main aim of this study was to examine to what extent DPD and the DSM-IV PDs share genetic and environmental risk factors, using multivariate twin modeling. The DSM-IV Structured Interview for Personality was applied to 2,794 young adult twins. Paranoid PD from Cluster A, borderline PD from Cluster B, and all three PDs from Cluster C were independently and significantly associated with DPD in multiple regression analysis. The genetic correlations between DPD and the other PDs were strong (.53–.83), while the environmental correlations were moderate (.36–.40). Close to 50% of the total variance in DPD was disorder specific. However, only 5% was due to disorder-specific genetic factors, indicating that a substantial part of the genetic vulnerability to DPD also increases the vulnerability to other PDs. PMID:22686231

Genetic and environmental contributions to the co-occurrence of depressive personality disorder and DSM-IV personality disorders.

PubMed

Ørstavik, Ragnhild E; Kendler, Kenneth S; Røysamb, Espen; Czajkowski, Nikolai; Tambs, Kristian; Reichborn-Kjennerud, Ted

2012-06-01

One of the main controversies with regard to depressive personality disorder (DPD) concerns the co-occurrence with the established DSM-IV personality disorders (PDs). The main aim of this study was to examine to what extent DPD and the DSM-IV PDs share genetic and environmental risk factors, using multivariate twin modeling. The DSM-IV Structured Interview for Personality was applied to 2,794 young adult twins. Paranoid PD from Cluster A, borderline PD from Cluster B, and all three PDs from Cluster C were independently and significantly associated with DPD in multiple regression analysis. The genetic correlations between DPD and the other PDs were strong (.53-.83), while the environmental correlations were moderate (.36-.40). Close to 50% of the total variance in DPD was disorder specific. However, only 5% was due to disorder-specific genetic factors, indicating that a substantial part of the genetic vulnerability to DPD also increases the vulnerability to other PDs.

Rate of evolutionary change in cranial morphology of the marsupial genus Monodelphis is constrained by the availability of additive genetic variation

PubMed Central

Porto, Arthur; Sebastião, Harley; Pavan, Silvia Eliza; VandeBerg, John L.; Marroig, Gabriel; Cheverud, James M.

2015-01-01

We tested the hypothesis that the rate of marsupial cranial evolution is dependent on the distribution of genetic variation in multivariate space. To do so, we carried out a genetic analysis of cranial morphological variation in laboratory strains of Monodelphis domestica and used estimates of genetic covariation to analyze the morphological diversification of the Monodelphis brevicaudata species group. We found that within-species genetic variation is concentrated in only a few axes of the morphospace and that this strong genetic covariation influenced the rate of morphological diversification of the brevicaudata group, with between-species divergence occurring fastest when occurring along the genetic line of least resistance. Accounting for the geometric distribution of genetic variation also increased our ability to detect the selective regimen underlying species diversification, with several instances of selection only being detected when genetic covariances were taken into account. Therefore, this work directly links patterns of genetic covariation among traits to macroevolutionary patterns of morphological divergence. Our findings also suggest that the limited distribution of Monodelphis species in morphospace is the result of a complex interplay between the limited dimensionality of available genetic variation and strong stabilizing selection along two major axes of genetic variation. PMID:25818173

Inferring Population Genetic Structure in Widely and Continuously Distributed Carnivores: The Stone Marten (Martes foina) as a Case Study

PubMed Central

Vergara, María; Basto, Mafalda P.; Madeira, María José; Gómez-Moliner, Benjamín J.; Santos-Reis, Margarida; Fernandes, Carlos; Ruiz-González, Aritz

2015-01-01

The stone marten is a widely distributed mustelid in the Palaearctic region that exhibits variable habitat preferences in different parts of its range. The species is a Holocene immigrant from southwest Asia which, according to fossil remains, followed the expansion of the Neolithic farming cultures into Europe and possibly colonized the Iberian Peninsula during the Early Neolithic (ca. 7,000 years BP). However, the population genetic structure and historical biogeography of this generalist carnivore remains essentially unknown. In this study we have combined mitochondrial DNA (mtDNA) sequencing (621 bp) and microsatellite genotyping (23 polymorphic markers) to infer the population genetic structure of the stone marten within the Iberian Peninsula. The mtDNA data revealed low haplotype and nucleotide diversities and a lack of phylogeographic structure, most likely due to a recent colonization of the Iberian Peninsula by a few mtDNA lineages during the Early Neolithic. The microsatellite data set was analysed with a) spatial and non-spatial Bayesian individual-based clustering (IBC) approaches (STRUCTURE, TESS, BAPS and GENELAND), and b) multivariate methods [discriminant analysis of principal components (DAPC) and spatial principal component analysis (sPCA)]. Additionally, because isolation by distance (IBD) is a common spatial genetic pattern in mobile and continuously distributed species and it may represent a challenge to the performance of the above methods, the microsatellite data set was tested for its presence. Overall, the genetic structure of the stone marten in the Iberian Peninsula was characterized by a NE-SW spatial pattern of IBD, and this may explain the observed disagreement between clustering solutions obtained by the different IBC methods. However, there was significant indication for contemporary genetic structuring, albeit weak, into at least three different subpopulations. The detected subdivision could be attributed to the influence of the rivers Ebro, Tagus and Guadiana, suggesting that main watercourses in the Iberian Peninsula may act as semi-permeable barriers to gene flow in stone martens. To our knowledge, this is the first phylogeographic and population genetic study of the species at a broad regional scale. We also wanted to make the case for the importance and benefits of using and comparing multiple different clustering and multivariate methods in spatial genetic analyses of mobile and continuously distributed species. PMID:26222680

Inferring Population Genetic Structure in Widely and Continuously Distributed Carnivores: The Stone Marten (Martes foina) as a Case Study.

PubMed

Vergara, María; Basto, Mafalda P; Madeira, María José; Gómez-Moliner, Benjamín J; Santos-Reis, Margarida; Fernandes, Carlos; Ruiz-González, Aritz

2015-01-01

The stone marten is a widely distributed mustelid in the Palaearctic region that exhibits variable habitat preferences in different parts of its range. The species is a Holocene immigrant from southwest Asia which, according to fossil remains, followed the expansion of the Neolithic farming cultures into Europe and possibly colonized the Iberian Peninsula during the Early Neolithic (ca. 7,000 years BP). However, the population genetic structure and historical biogeography of this generalist carnivore remains essentially unknown. In this study we have combined mitochondrial DNA (mtDNA) sequencing (621 bp) and microsatellite genotyping (23 polymorphic markers) to infer the population genetic structure of the stone marten within the Iberian Peninsula. The mtDNA data revealed low haplotype and nucleotide diversities and a lack of phylogeographic structure, most likely due to a recent colonization of the Iberian Peninsula by a few mtDNA lineages during the Early Neolithic. The microsatellite data set was analysed with a) spatial and non-spatial Bayesian individual-based clustering (IBC) approaches (STRUCTURE, TESS, BAPS and GENELAND), and b) multivariate methods [discriminant analysis of principal components (DAPC) and spatial principal component analysis (sPCA)]. Additionally, because isolation by distance (IBD) is a common spatial genetic pattern in mobile and continuously distributed species and it may represent a challenge to the performance of the above methods, the microsatellite data set was tested for its presence. Overall, the genetic structure of the stone marten in the Iberian Peninsula was characterized by a NE-SW spatial pattern of IBD, and this may explain the observed disagreement between clustering solutions obtained by the different IBC methods. However, there was significant indication for contemporary genetic structuring, albeit weak, into at least three different subpopulations. The detected subdivision could be attributed to the influence of the rivers Ebro, Tagus and Guadiana, suggesting that main watercourses in the Iberian Peninsula may act as semi-permeable barriers to gene flow in stone martens. To our knowledge, this is the first phylogeographic and population genetic study of the species at a broad regional scale. We also wanted to make the case for the importance and benefits of using and comparing multiple different clustering and multivariate methods in spatial genetic analyses of mobile and continuously distributed species.

Genetic analysis of Holstein cattle populations in Brazil and the United States.

PubMed

Costa, C N; Blake, R W; Pollak, E J; Oltenacu, P A; Quaas, R L; Searle, S R

2000-12-01

Genetic relationships between Brazilian and US Holstein cattle populations were studied using first-lactation records of 305-d mature equivalent (ME) yields of milk and fat of daughters of 705 sires in Brazil and 701 sires in the United States, 358 of which had progeny in both countries. Components of(co)variance and genetic parameters were estimated from all data and from within herd-year standard deviation for milk (HYSD) data files using bivariate and multivariate sire models and DFREML procedures distinguishing the two countries. Sire (residual) variances from all data for milk yield were 51 to 59% (58 to 101%) as large in Brazil as those obtained from half-sisters in the average US herd. Corresponding proportions of the US variance in fat yield that were found in Brazil were 30 to 41% for the sire component of variance and 48 to 80% for the residual. Heritabilities for milk and fat yields from multivariate analysis of all the data were 0.25 and 0.22 in Brazil, and 0.34 and 0.35 in the United States. Genetic correlations between milk and fat were 0.79 in Brazil and 0.62 in the United States. Genetic correlations between countries were 0.85 for milk, 0.88 for fat, 0.55 for milk in Brazil and fat in the US, and 0.67 for fat in Brazil and milk in the United States. Correlated responses in Brazil from sire selection based on the US information increased with average HYSD in Brazil. Largest daughter yield response was predicted from information from half-sisters in low HYSD US herds (0.75 kg/kg for milk; 0.63 kg/kg for fat), which was 14% to 17% greater than estimates from all US herds because the scaling effects were less severe from heterogeneous variances. Unequal daughter response from unequal genetic (co)variances under restrictive Brazilian conditions is evidence for the interaction of genotype and environment. The smaller and variable yield expectations of daughters of US sires in Brazilian environments suggest the need for specific genetic improvement strategies in Brazilian Holstein herds. A US data file restricting daughter information to low HYSD US environments would be a wise choice for across-country evaluation. Procedures to incorporate such foreign evaluations should be explored to improve the accuracy of genetic evaluations for the Brazilian Holstein population.

A functional U-statistic method for association analysis of sequencing data.

PubMed

Jadhav, Sneha; Tong, Xiaoran; Lu, Qing

2017-11-01

Although sequencing studies hold great promise for uncovering novel variants predisposing to human diseases, the high dimensionality of the sequencing data brings tremendous challenges to data analysis. Moreover, for many complex diseases (e.g., psychiatric disorders) multiple related phenotypes are collected. These phenotypes can be different measurements of an underlying disease, or measurements characterizing multiple related diseases for studying common genetic mechanism. Although jointly analyzing these phenotypes could potentially increase the power of identifying disease-associated genes, the different types of phenotypes pose challenges for association analysis. To address these challenges, we propose a nonparametric method, functional U-statistic method (FU), for multivariate analysis of sequencing data. It first constructs smooth functions from individuals' sequencing data, and then tests the association of these functions with multiple phenotypes by using a U-statistic. The method provides a general framework for analyzing various types of phenotypes (e.g., binary and continuous phenotypes) with unknown distributions. Fitting the genetic variants within a gene using a smoothing function also allows us to capture complexities of gene structure (e.g., linkage disequilibrium, LD), which could potentially increase the power of association analysis. Through simulations, we compared our method to the multivariate outcome score test (MOST), and found that our test attained better performance than MOST. In a real data application, we apply our method to the sequencing data from Minnesota Twin Study (MTS) and found potential associations of several nicotine receptor subunit (CHRN) genes, including CHRNB3, associated with nicotine dependence and/or alcohol dependence. © 2017 WILEY PERIODICALS, INC.

Proton Nuclear Magnetic Resonance-Spectroscopic Discrimination of Wines Reflects Genetic Homology of Several Different Grape (V. vinifera L.) Cultivars.

PubMed

Hu, Boran; Yue, Yaqing; Zhu, Yong; Wen, Wen; Zhang, Fengmin; Hardie, Jim W

2015-01-01

Proton nuclear magnetic resonance spectroscopy coupled multivariate analysis (1H NMR-PCA/PLS-DA) is an important tool for the discrimination of wine products. Although 1H NMR has been shown to discriminate wines of different cultivars, a grape genetic component of the discrimination has been inferred only from discrimination of cultivars of undefined genetic homology and in the presence of many confounding environmental factors. We aimed to confirm the influence of grape genotypes in the absence of those factors. We applied 1H NMR-PCA/PLS-DA and hierarchical cluster analysis (HCA) to wines from five, variously genetically-related grapevine (V. vinifera) cultivars; all grown similarly on the same site and vinified similarly. We also compared the semi-quantitative profiles of the discriminant metabolites of each cultivar with previously reported chemical analyses. The cultivars were clearly distinguishable and there was a general correlation between their grouping and their genetic homology as revealed by recent genomic studies. Between cultivars, the relative amounts of several of the cultivar-related discriminant metabolites conformed closely with reported chemical analyses. Differences in grape-derived metabolites associated with genetic differences alone are a major source of 1H NMR-based discrimination of wines and 1H NMR has the capacity to discriminate between very closely related cultivars. The study confirms that genetic variation among grape cultivars alone can account for the discrimination of wine by 1H NMR-PCA/PLS and indicates that 1H NMR spectra of wine of single grape cultivars may in future be used in tandem with hierarchical cluster analysis to elucidate genetic lineages and metabolomic relations of grapevine cultivars. In the absence of genetic information, for example, where predecessor varieties are no longer extant, this may be a particularly useful approach.

Accounting for Sampling Error in Genetic Eigenvalues Using Random Matrix Theory.

PubMed

Sztepanacz, Jacqueline L; Blows, Mark W

2017-07-01

The distribution of genetic variance in multivariate phenotypes is characterized by the empirical spectral distribution of the eigenvalues of the genetic covariance matrix. Empirical estimates of genetic eigenvalues from random effects linear models are known to be overdispersed by sampling error, where large eigenvalues are biased upward, and small eigenvalues are biased downward. The overdispersion of the leading eigenvalues of sample covariance matrices have been demonstrated to conform to the Tracy-Widom (TW) distribution. Here we show that genetic eigenvalues estimated using restricted maximum likelihood (REML) in a multivariate random effects model with an unconstrained genetic covariance structure will also conform to the TW distribution after empirical scaling and centering. However, where estimation procedures using either REML or MCMC impose boundary constraints, the resulting genetic eigenvalues tend not be TW distributed. We show how using confidence intervals from sampling distributions of genetic eigenvalues without reference to the TW distribution is insufficient protection against mistaking sampling error as genetic variance, particularly when eigenvalues are small. By scaling such sampling distributions to the appropriate TW distribution, the critical value of the TW statistic can be used to determine if the magnitude of a genetic eigenvalue exceeds the sampling error for each eigenvalue in the spectral distribution of a given genetic covariance matrix. Copyright © 2017 by the Genetics Society of America.

Meta-analysis of gene-level associations for rare variants based on single-variant statistics.

PubMed

Hu, Yi-Juan; Berndt, Sonja I; Gustafsson, Stefan; Ganna, Andrea; Hirschhorn, Joel; North, Kari E; Ingelsson, Erik; Lin, Dan-Yu

2013-08-08

Meta-analysis of genome-wide association studies (GWASs) has led to the discoveries of many common variants associated with complex human diseases. There is a growing recognition that identifying "causal" rare variants also requires large-scale meta-analysis. The fact that association tests with rare variants are performed at the gene level rather than at the variant level poses unprecedented challenges in the meta-analysis. First, different studies may adopt different gene-level tests, so the results are not compatible. Second, gene-level tests require multivariate statistics (i.e., components of the test statistic and their covariance matrix), which are difficult to obtain. To overcome these challenges, we propose to perform gene-level tests for rare variants by combining the results of single-variant analysis (i.e., p values of association tests and effect estimates) from participating studies. This simple strategy is possible because of an insight that multivariate statistics can be recovered from single-variant statistics, together with the correlation matrix of the single-variant test statistics, which can be estimated from one of the participating studies or from a publicly available database. We show both theoretically and numerically that the proposed meta-analysis approach provides accurate control of the type I error and is as powerful as joint analysis of individual participant data. This approach accommodates any disease phenotype and any study design and produces all commonly used gene-level tests. An application to the GWAS summary results of the Genetic Investigation of ANthropometric Traits (GIANT) consortium reveals rare and low-frequency variants associated with human height. The relevant software is freely available. Copyright © 2013 The American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.

Comparative genetic analysis of trichome-less and normal pod genotypes of Mucuna pruriens (Fabaceae).

PubMed

Dhawan, S S; Rai, G K; Darokar, M P; Lal, R K; Misra, H O; Khanuja, S P S

2011-09-15

Velvet bean (Mucuna pruriens) seeds contain the catecholic amino acid L-DoPA (L-3,4-dihydroxyphenylalanine), which is a neurotransmitter precursor and used for the treatment of Parkinson's disease and mental disorders. The great demand for L-DoPA is largely met by the pharmaceutical industry through extraction of the compound from wild populations of this plant; commercial exploitation of this compound is hampered because of its limited availability. The trichomes present on the pods can cause severe itching, blisters and dermatitis, discouraging cultivation. We screened genetic stocks of velvet bean for the trichome-less trait, along with high seed yield and L-DoPA content. The highest yielding trichome-less elite strain was selected and indentified on the basis of a PCR-based DNA fingerprinting method (RAPD), using deca-nucleotide primers. A genetic similarity index matrix was obtained through multivariant analysis using Nei and Li's coefficient. The similarity coefficients were used to generate a tree for cluster analysis using the UPGMA method. Analysis of amplification spectra of 408 bands obtained with 56 primers allowed us to distinguish a trichome-less elite strain of M. pruriens.

Multivariate Feature Selection of Image Descriptors Data for Breast Cancer with Computer-Assisted Diagnosis

PubMed Central

Galván-Tejada, Carlos E.; Zanella-Calzada, Laura A.; Galván-Tejada, Jorge I.; Celaya-Padilla, José M.; Gamboa-Rosales, Hamurabi; Garza-Veloz, Idalia; Martinez-Fierro, Margarita L.

2017-01-01

Breast cancer is an important global health problem, and the most common type of cancer among women. Late diagnosis significantly decreases the survival rate of the patient; however, using mammography for early detection has been demonstrated to be a very important tool increasing the survival rate. The purpose of this paper is to obtain a multivariate model to classify benign and malignant tumor lesions using a computer-assisted diagnosis with a genetic algorithm in training and test datasets from mammography image features. A multivariate search was conducted to obtain predictive models with different approaches, in order to compare and validate results. The multivariate models were constructed using: Random Forest, Nearest centroid, and K-Nearest Neighbor (K-NN) strategies as cost function in a genetic algorithm applied to the features in the BCDR public databases. Results suggest that the two texture descriptor features obtained in the multivariate model have a similar or better prediction capability to classify the data outcome compared with the multivariate model composed of all the features, according to their fitness value. This model can help to reduce the workload of radiologists and present a second opinion in the classification of tumor lesions. PMID:28216571

Multivariate Feature Selection of Image Descriptors Data for Breast Cancer with Computer-Assisted Diagnosis.

PubMed

Galván-Tejada, Carlos E; Zanella-Calzada, Laura A; Galván-Tejada, Jorge I; Celaya-Padilla, José M; Gamboa-Rosales, Hamurabi; Garza-Veloz, Idalia; Martinez-Fierro, Margarita L

2017-02-14

Breast cancer is an important global health problem, and the most common type of cancer among women. Late diagnosis significantly decreases the survival rate of the patient; however, using mammography for early detection has been demonstrated to be a very important tool increasing the survival rate. The purpose of this paper is to obtain a multivariate model to classify benign and malignant tumor lesions using a computer-assisted diagnosis with a genetic algorithm in training and test datasets from mammography image features. A multivariate search was conducted to obtain predictive models with different approaches, in order to compare and validate results. The multivariate models were constructed using: Random Forest, Nearest centroid, and K-Nearest Neighbor (K-NN) strategies as cost function in a genetic algorithm applied to the features in the BCDR public databases. Results suggest that the two texture descriptor features obtained in the multivariate model have a similar or better prediction capability to classify the data outcome compared with the multivariate model composed of all the features, according to their fitness value. This model can help to reduce the workload of radiologists and present a second opinion in the classification of tumor lesions.

Phenotypic and Genetic Variations in Obligate Parthenogenetic Populations of Eriosoma lanigerum Hausmann (Hemiptera: Aphididae).

PubMed

Ruiz-Montoya, L; Zúñiga, G; Cisneros, R; Salinas-Moreno, Y; Peña-Martínez, R; Machkour-M'Rabet, S

2015-12-01

The study of phenotypic and genetic variation of obligate parthenogenetic organisms contributes to an understanding of evolution in the absence of genetic variation produced by sexual reproduction. Eriosoma lanigerum Hausmann undergoes obligate parthenogenesis in Mexico City, Mexico, due to the unavailability of the host plants required for sexual reproduction. We analysed the phenotypic and genetic variation of E. lanigerum in relation to the dry and wet season and plant phenology. Aphids were collected on two occasions per season on a secondary host plant, Pyracantha koidzumii, at five different sites in the southern area of Mexico City, Mexico. Thirteen morphological characteristics were measured from 147 to 276 individuals per site and per season. A multivariate analysis of variance was performed to test the effect of the season, site and their interaction on morphological traits. Morphological variation was summarised using a principal component analysis. Genetic variation was described using six enzymatic loci, four of which were polymorphic. Our study showed that the site and season has a significant effect on morphological trait variation. The largest aphids were recorded during cold temperatures with low relative humidity and when the plant was at the end of the fruiting period. The mean genetic diversity was low (mean H e =  .161), and populations were genetically structured by season and site. Morphological and genetic variations appear to be associated with environmental factors that directly affect aphid development and/or indirectly by host plant phenology.

Understanding of multigene test results among males undergoing germline testing for inherited prostate cancer: Implications for genetic counseling.

PubMed

Giri, Veda N; Obeid, Elias; Hegarty, Sarah E; Gross, Laura; Bealin, Lisa; Hyatt, Colette; Fang, Carolyn Y; Leader, Amy

2018-04-14

Genetic testing (GT) for prostate cancer (PCA) is rising, with limited insights regarding genetic counseling (GC) needs of males. Genetic Evaluation of Men (GEM) is a prospective multigene testing study for inherited PCA. Men undergoing GC were surveyed on knowledge of cancer risk and genetics (CRG) and understanding of personal GT results to identify GC needs. GEM participants with or high-risk for PCA were recruited. Pre-test GC was in-person, with video and handout, or via telehealth. Post-test disclosure was in-person, by phone, or via telehealth. Clinical and family history data were obtained from participant surveys and medical records. Participants completed measures of knowledge of CRG, literacy, and numeracy pre-test and post-test. Understanding of personal genetic results was assessed post-test. Factors associated with knowledge of CRG and understanding of personal genetic results were examined using multivariable linear regression or McNemar's test. Among 109 men who completed pre- and post-GT surveys, multivariable analysis revealed family history meeting hereditary cancer syndrome (HCS) criteria was significantly predictive of higher baseline knowledge (P = 0.040). Of 101 men who responded definitively regarding understanding of results, 13 incorrectly reported their result (McNemar's P < 0.001). Factors significantly associated with discordance between reported and actual results included having a variant of uncertain significance (VUS) (P < 0.001) and undergoing GC via pre-test video and post-test phone disclosure (P = 0.015). While meeting criteria for HCS was associated with higher knowledge of CRG, understanding of personal GT results was lacking among a subset of males with VUS. A more exploratory finding was lack of understanding of results among men who underwent GC utilizing video and phone. Studies optimizing GC strategies for males undergoing multigene testing for inherited PCA are warranted. © 2018 Wiley Periodicals, Inc.

Generalist Genes and Learning Disabilities: A Multivariate Genetic Analysis of Low Performance in Reading, Mathematics, Language and General Cognitive Ability in a Sample of 8000 12-Year-Old Twins

ERIC Educational Resources Information Center

Haworth, Claire M. A.; Kovas, Yulia; Harlaar, Nicole; Hayiou-Thomas, Marianna E.; Petrill, Stephen A.; Dale, Philip S.; Plomin, Robert

2009-01-01

Background: Our previous investigation found that the same genes influence poor reading and mathematics performance in 10-year-olds. Here we assess whether this finding extends to language and general cognitive disabilities, as well as replicating the earlier finding for reading and mathematics in an older and larger sample. Methods: Using a…

New evidence for involvement of ESR1 gene in susceptibility to Chinese migraine.

PubMed

An, Xingkai; Fang, Jie; Lin, Qing; Lu, Congxia; Ma, Qilin; Qu, Hongli

2017-01-01

Migraine is a common and disabling nervous system disease with a significant genetic predisposition. The sex hormones play an important role in the pathogenesis of migraine. However, the conclusions of the previous genetic relation studies are conflicting. The aim of this study is to determine whether variants in genes involved in estrogen receptor and estrogen hormone metabolism are related to Chinese migraine. By employing a case-control approach, 8 SNPs in the ESR1, ESR2, and CYP19A1 genes are studied in a cohort of 494 migraine cases and 533 controls. In addition, genotyping is performed using Sequenom MALDI-TOF mass spectrometry iPLEX platform. Univariate and multivariate analyses are carried out by logistic regression. The corresponding haplotypes are studied with the Haploview software and gene-gene interaction is assessed using the Generalized Multifactor Dimensionality Reduction (GMDR) analysis. There are significant differences in allelic distributions for rs2234693 and rs9340799 in ESR1 gene between patients with migraine and control subjects. Univariate logistic analysis shows that rs2234693 and rs9340799 are risk factors for migraine, but multivariate analysis reveals that only rs2234693 is significant associated with migraine. In the subgroup analysis, rs2234693 in ESR1 gene is found associated with menstrually related migraine. Further haplotypic analysis shows that rs2234693-rs9340799 TA haplotype serves as risk haplotype for migraine. The GMDR analysis identifies rs2234693 in ESR1 alone to be a crucial candidate in migraine susceptibility. This study is in agreement with the previous studies that variants in the ESR1 gene are associated with migraine suggesting that it plays a role in the migraine process.

Plasma urate concentration and risk of coronary heart disease: a Mendelian randomisation analysis.

PubMed

White, Jon; Sofat, Reecha; Hemani, Gibran; Shah, Tina; Engmann, Jorgen; Dale, Caroline; Shah, Sonia; Kruger, Felix A; Giambartolomei, Claudia; Swerdlow, Daniel I; Palmer, Tom; McLachlan, Stela; Langenberg, Claudia; Zabaneh, Delilah; Lovering, Ruth; Cavadino, Alana; Jefferis, Barbara; Finan, Chris; Wong, Andrew; Amuzu, Antoinette; Ong, Ken; Gaunt, Tom R; Warren, Helen; Davies, Teri-Louise; Drenos, Fotios; Cooper, Jackie; Ebrahim, Shah; Lawlor, Debbie A; Talmud, Philippa J; Humphries, Steve E; Power, Christine; Hypponen, Elina; Richards, Marcus; Hardy, Rebecca; Kuh, Diana; Wareham, Nicholas; Ben-Shlomo, Yoav; Day, Ian N; Whincup, Peter; Morris, Richard; Strachan, Mark W J; Price, Jacqueline; Kumari, Meena; Kivimaki, Mika; Plagnol, Vincent; Whittaker, John C; Smith, George Davey; Dudbridge, Frank; Casas, Juan P; Holmes, Michael V; Hingorani, Aroon D

2016-04-01

Increased circulating plasma urate concentration is associated with an increased risk of coronary heart disease, but the extent of any causative effect of urate on risk of coronary heart disease is still unclear. In this study, we aimed to clarify any causal role of urate on coronary heart disease risk using Mendelian randomisation analysis. We first did a fixed-effects meta-analysis of the observational association of plasma urate and risk of coronary heart disease. We then used a conventional Mendelian randomisation approach to investigate the causal relevance using a genetic instrument based on 31 urate-associated single nucleotide polymorphisms (SNPs). To account for potential pleiotropic associations of certain SNPs with risk factors other than urate, we additionally did both a multivariable Mendelian randomisation analysis, in which the genetic associations of SNPs with systolic and diastolic blood pressure, HDL cholesterol, and triglycerides were included as covariates, and an Egger Mendelian randomisation (MR-Egger) analysis to estimate a causal effect accounting for unmeasured pleiotropy. In the meta-analysis of 17 prospective observational studies (166 486 individuals; 9784 coronary heart disease events) a 1 SD higher urate concentration was associated with an odds ratio (OR) for coronary heart disease of 1·07 (95% CI 1·04-1·10). The corresponding OR estimates from the conventional, multivariable adjusted, and Egger Mendelian randomisation analysis (58 studies; 198 598 individuals; 65 877 events) were 1·18 (95% CI 1·08-1·29), 1·10 (1·00-1·22), and 1·05 (0·92-1·20), respectively, per 1 SD increment in plasma urate. Conventional and multivariate Mendelian randomisation analysis implicates a causal role for urate in the development of coronary heart disease, but these estimates might be inflated by hidden pleiotropy. Egger Mendelian randomisation analysis, which accounts for pleiotropy but has less statistical power, suggests there might be no causal effect. These results might help investigators to determine the priority of trials of urate lowering for the prevention of coronary heart disease compared with other potential interventions. UK National Institute for Health Research, British Heart Foundation, and UK Medical Research Council. Copyright © 2016 White et al. Open Access article distributed under the terms of CC BY. Published by Elsevier Ltd.. All rights reserved.

Plasma urate concentration and risk of coronary heart disease: a Mendelian randomisation analysis

PubMed Central

White, Jon; Sofat, Reecha; Hemani, Gibran; Shah, Tina; Engmann, Jorgen; Dale, Caroline; Shah, Sonia; Kruger, Felix A; Giambartolomei, Claudia; Swerdlow, Daniel I; Palmer, Tom; McLachlan, Stela; Langenberg, Claudia; Zabaneh, Delilah; Lovering, Ruth; Cavadino, Alana; Jefferis, Barbara; Finan, Chris; Wong, Andrew; Amuzu, Antoinette; Ong, Ken; Gaunt, Tom R; Warren, Helen; Davies, Teri-Louise; Drenos, Fotios; Cooper, Jackie; Ebrahim, Shah; Lawlor, Debbie A; Talmud, Philippa J; Humphries, Steve E; Power, Christine; Hypponen, Elina; Richards, Marcus; Hardy, Rebecca; Kuh, Diana; Wareham, Nicholas; Ben-Shlomo, Yoav; Day, Ian N; Whincup, Peter; Morris, Richard; Strachan, Mark W J; Price, Jacqueline; Kumari, Meena; Kivimaki, Mika; Plagnol, Vincent; Whittaker, John C; Smith, George Davey; Dudbridge, Frank; Casas, Juan P; Holmes, Michael V; Hingorani, Aroon D

2016-01-01

Summary Background Increased circulating plasma urate concentration is associated with an increased risk of coronary heart disease, but the extent of any causative effect of urate on risk of coronary heart disease is still unclear. In this study, we aimed to clarify any causal role of urate on coronary heart disease risk using Mendelian randomisation analysis. Methods We first did a fixed-effects meta-analysis of the observational association of plasma urate and risk of coronary heart disease. We then used a conventional Mendelian randomisation approach to investigate the causal relevance using a genetic instrument based on 31 urate-associated single nucleotide polymorphisms (SNPs). To account for potential pleiotropic associations of certain SNPs with risk factors other than urate, we additionally did both a multivariable Mendelian randomisation analysis, in which the genetic associations of SNPs with systolic and diastolic blood pressure, HDL cholesterol, and triglycerides were included as covariates, and an Egger Mendelian randomisation (MR-Egger) analysis to estimate a causal effect accounting for unmeasured pleiotropy. Findings In the meta-analysis of 17 prospective observational studies (166 486 individuals; 9784 coronary heart disease events) a 1 SD higher urate concentration was associated with an odds ratio (OR) for coronary heart disease of 1·07 (95% CI 1·04–1·10). The corresponding OR estimates from the conventional, multivariable adjusted, and Egger Mendelian randomisation analysis (58 studies; 198 598 individuals; 65 877 events) were 1·18 (95% CI 1·08–1·29), 1·10 (1·00–1·22), and 1·05 (0·92–1·20), respectively, per 1 SD increment in plasma urate. Interpretation Conventional and multivariate Mendelian randomisation analysis implicates a causal role for urate in the development of coronary heart disease, but these estimates might be inflated by hidden pleiotropy. Egger Mendelian randomisation analysis, which accounts for pleiotropy but has less statistical power, suggests there might be no causal effect. These results might help investigators to determine the priority of trials of urate lowering for the prevention of coronary heart disease compared with other potential interventions. Funding UK National Institute for Health Research, British Heart Foundation, and UK Medical Research Council. PMID:26781229

Genetic Variation in Complement Component 2 of the Classical Complement Pathway is Associated with Increased Mortality and Infection: A Study of 627 Trauma Patients

PubMed Central

Morris, John A.; Francois, Cedric; Olson, Paul K.; Cotton, Bryan A.; Summar, Marshall; Jenkins, Judith M.; Norris, Patrick R.; Moore, Jason H.; Williams, Anna E.; McNew, Brent S.; Canter, Jeffrey A.

2009-01-01

Trauma is a disease of inflammation. Complement Component 2 (C2) is a protease involved in activation of complement through the classical pathway and has been implicated in a variety of chronic inflammatory diseases. We hypothesized that genetic variation in C2 (E318D) identifies a high-risk subgroup of trauma patients reflecting increased mortality and infection (Ventilator associated pneumonia: VAP). Consequently, genetic variation in C2 may stratify patient risk and illuminate underlying mechanisms for therapeutic intervention. Methods DNA samples from 702 trauma patients were genotyped for C2 E318D and linked with covariates (age: mean 42.8 years, gender: 74% male, ethnicity: 80% Caucasian, mechanism: 84% blunt, ISS: mean 25.0, admission lactate: mean 3.13 mEq/L) and outcomes: mortality 9.9% and VAP: 18.5%. VAP was defined by quantitative bronchoalveolar lavage (>104). Multivariate regression determined the relationship of genotype and covariates to risk of death and VAP. However, patients with ISS ≥ 45 were excluded from the multivariate analysis, as magnitude of injury overwhelms genetics and covariates in determining outcome. Results 52 patients (8.3%) had the high-risk heterozygous genotype, associated with a significant increase in mortality and VAP. Conclusion In 702 trauma patients, 8.3% had a high-risk genetic variation in C2 associated with increased mortality (OR=2.65) and infection (OR=2.00). This variation: 1) Identifies a previously unknown high risk group for infection and mortality; 2) Can be determined on admission; 3) May provide opportunity for early therapeutic intervention; and 4) Requires validation in a distinct cohort of patients. PMID:19430225

Variation in clinical phenotype of human infection among genetic groups of Blastomyces dermatitidis

USGS Publications Warehouse

Meece, Jennifer K.; Anderson, Jennifer L.; Gruszka, Sarah; Sloss, Brian L.; Sullivan, Bradley; Reed, Kurt D.

2013-01-01

Background. Blastomyces dermatitidis, the etiologic agent of blastomycosis, has 2 genetic groups and shows varied clinical presentation, ranging from silent infections to fulminant respiratory disease and dissemination. The objective of this study was to determine whether clinical phenotype and outcomes vary based on the infecting organism's genetic group.Methods. We used microsatellites to genotype 227 clinical isolates of B. dermatitidis from Wisconsin patients. For each isolate, corresponding clinical disease characteristics and patient demographic information were abstracted from electronic health records and Wisconsin Division of Health reportable disease forms and questionnaires.Results. In univariate analysis, group 1 isolates were more likely to be associated with pulmonary-only infections (P < .0001) and constitutional symptoms such as fever (P < .0001). In contrast, group 2 isolates were more likely to be associated with disseminated disease (P < .0001), older patient age (P < .0001), and comorbidities (P = .0019). In multivariate analysis, disease onset to diagnosis of >1 month (P < .0001), older age at diagnosis (P < .0001), and current smoking status (P = .0001) remained predictors for group 2 infections.Conclusions. This study identified previously unknown associations between clinical phenotype of human infection and genetic groups of B. dermatitidis and provides a framework for further investigations of the genetic basis for virulence in B. dermatitidis.

The effects of socioeconomic status, clinical factors, and genetic ancestry on pulmonary tuberculosis disease in northeastern Mexico.

PubMed

Young, Bonnie N; Rendón, Adrian; Rosas-Taraco, Adrian; Baker, Jack; Healy, Meghan; Gross, Jessica M; Long, Jeffrey; Burgos, Marcos; Hunley, Keith L

2014-01-01

Diverse socioeconomic and clinical factors influence susceptibility to tuberculosis (TB) disease in Mexico. The role of genetic factors, particularly those that differ between the parental groups that admixed in Mexico, is unclear. The objectives of this study are to identify the socioeconomic and clinical predictors of the transition from latent TB infection (LTBI) to pulmonary TB disease in an urban population in northeastern Mexico, and to examine whether genetic ancestry plays an independent role in this transition. We recruited 97 pulmonary TB disease patients and 97 LTBI individuals from a public hospital in Monterrey, Nuevo León. Socioeconomic and clinical variables were collected from interviews and medical records, and genetic ancestry was estimated for a subset of 142 study participants from 291,917 single nucleotide polymorphisms (SNPs). We examined crude associations between the variables and TB disease status. Significant predictors from crude association tests were analyzed using multivariable logistic regression. We also compared genetic ancestry between LTBI individuals and TB disease patients at 1,314 SNPs in 273 genes from the TB biosystem in the NCBI BioSystems database. In crude association tests, 12 socioeconomic and clinical variables were associated with TB disease. Multivariable logistic regression analyses indicated that marital status, diabetes, and smoking were independently associated with TB status. Genetic ancestry was not associated with TB disease in either crude or multivariable analyses. Separate analyses showed that LTBI individuals recruited from hospital staff had significantly higher European genetic ancestry than LTBI individuals recruited from the clinics and waiting rooms. Genetic ancestry differed between individuals with LTBI and TB disease at SNPs located in two genes in the TB biosystem. These results indicate that Monterrey may be structured with respect to genetic ancestry, and that genetic differences in TB susceptibility in parental populations may contribute to variation in disease susceptibility in the region.

The Effects of Socioeconomic Status, Clinical Factors, and Genetic Ancestry on Pulmonary Tuberculosis Disease in Northeastern Mexico

PubMed Central

Young, Bonnie N.; Rendón, Adrian; Rosas-Taraco, Adrian; Baker, Jack; Healy, Meghan; Gross, Jessica M.; Long, Jeffrey; Burgos, Marcos; Hunley, Keith L.

2014-01-01

Diverse socioeconomic and clinical factors influence susceptibility to tuberculosis (TB) disease in Mexico. The role of genetic factors, particularly those that differ between the parental groups that admixed in Mexico, is unclear. The objectives of this study are to identify the socioeconomic and clinical predictors of the transition from latent TB infection (LTBI) to pulmonary TB disease in an urban population in northeastern Mexico, and to examine whether genetic ancestry plays an independent role in this transition. We recruited 97 pulmonary TB disease patients and 97 LTBI individuals from a public hospital in Monterrey, Nuevo León. Socioeconomic and clinical variables were collected from interviews and medical records, and genetic ancestry was estimated for a subset of 142 study participants from 291,917 single nucleotide polymorphisms (SNPs). We examined crude associations between the variables and TB disease status. Significant predictors from crude association tests were analyzed using multivariable logistic regression. We also compared genetic ancestry between LTBI individuals and TB disease patients at 1,314 SNPs in 273 genes from the TB biosystem in the NCBI BioSystems database. In crude association tests, 12 socioeconomic and clinical variables were associated with TB disease. Multivariable logistic regression analyses indicated that marital status, diabetes, and smoking were independently associated with TB status. Genetic ancestry was not associated with TB disease in either crude or multivariable analyses. Separate analyses showed that LTBI individuals recruited from hospital staff had significantly higher European genetic ancestry than LTBI individuals recruited from the clinics and waiting rooms. Genetic ancestry differed between individuals with LTBI and TB disease at SNPs located in two genes in the TB biosystem. These results indicate that Monterrey may be structured with respect to genetic ancestry, and that genetic differences in TB susceptibility in parental populations may contribute to variation in disease susceptibility in the region. PMID:24728409

Willingness to donate blood samples for genetic research: a survey from a community in Singapore.

PubMed

Wong, M L; Chia, K S; Yam, W M; Teodoro, G R; Lau, K W

2004-01-01

Studies on the public's willingness to donate blood specimens for genetic research are few and are conducted mainly among Western countries. Little is known about the Asian community's willingness to participate in genetic research. A community-based survey was conducted on 548 adult Singaporeans to examine their willingness to donate blood samples for genetic research and its associated factors. The response rate was 70.3%. About 49.3% (95% CI, 45.1-53.5%) were willing to donate blood for genetic research. In the multivariable Cox regression analysis, willingness was significantly associated with belief in the benefits of genetic research; intention to participate in government studies; having no fear of pain, blood, injections, and needles; and non-concern about the loss of confidentiality. Reasons against donating blood were fear of pain, blood, injections, and needles (38.1%); no self-benefits (24.8%); fear of finding out about having a disease (22.3%); fear of discrimination (18.7%); and concerns about weakness (15.1%) and weight gain (9.4%). Public education programs to promote participation in genetic research should stress its benefits and address people's fears and concerns.

An efficient genome-wide association test for multivariate phenotypes based on the Fisher combination function.

PubMed

Yang, James J; Li, Jia; Williams, L Keoki; Buu, Anne

2016-01-05

In genome-wide association studies (GWAS) for complex diseases, the association between a SNP and each phenotype is usually weak. Combining multiple related phenotypic traits can increase the power of gene search and thus is a practically important area that requires methodology work. This study provides a comprehensive review of existing methods for conducting GWAS on complex diseases with multiple phenotypes including the multivariate analysis of variance (MANOVA), the principal component analysis (PCA), the generalizing estimating equations (GEE), the trait-based association test involving the extended Simes procedure (TATES), and the classical Fisher combination test. We propose a new method that relaxes the unrealistic independence assumption of the classical Fisher combination test and is computationally efficient. To demonstrate applications of the proposed method, we also present the results of statistical analysis on the Study of Addiction: Genetics and Environment (SAGE) data. Our simulation study shows that the proposed method has higher power than existing methods while controlling for the type I error rate. The GEE and the classical Fisher combination test, on the other hand, do not control the type I error rate and thus are not recommended. In general, the power of the competing methods decreases as the correlation between phenotypes increases. All the methods tend to have lower power when the multivariate phenotypes come from long tailed distributions. The real data analysis also demonstrates that the proposed method allows us to compare the marginal results with the multivariate results and specify which SNPs are specific to a particular phenotype or contribute to the common construct. The proposed method outperforms existing methods in most settings and also has great applications in GWAS on complex diseases with multiple phenotypes such as the substance abuse disorders.

Multivariate pattern analysis reveals subtle brain anomalies relevant to the cognitive phenotype in neurofibromatosis type 1.

PubMed

Duarte, João V; Ribeiro, Maria J; Violante, Inês R; Cunha, Gil; Silva, Eduardo; Castelo-Branco, Miguel

2014-01-01

Neurofibromatosis Type 1 (NF1) is a common genetic condition associated with cognitive dysfunction. However, the pathophysiology of the NF1 cognitive deficits is not well understood. Abnormal brain structure, including increased total brain volume, white matter (WM) and grey matter (GM) abnormalities have been reported in the NF1 brain. These previous studies employed univariate model-driven methods preventing detection of subtle and spatially distributed differences in brain anatomy. Multivariate pattern analysis allows the combination of information from multiple spatial locations yielding a discriminative power beyond that of single voxels. Here we investigated for the first time subtle anomalies in the NF1 brain, using a multivariate data-driven classification approach. We used support vector machines (SVM) to classify whole-brain GM and WM segments of structural T1 -weighted MRI scans from 39 participants with NF1 and 60 non-affected individuals, divided in children/adolescents and adults groups. We also employed voxel-based morphometry (VBM) as a univariate gold standard to study brain structural differences. SVM classifiers correctly classified 94% of cases (sensitivity 92%; specificity 96%) revealing the existence of brain structural anomalies that discriminate NF1 individuals from controls. Accordingly, VBM analysis revealed structural differences in agreement with the SVM weight maps representing the most relevant brain regions for group discrimination. These included the hippocampus, basal ganglia, thalamus, and visual cortex. This multivariate data-driven analysis thus identified subtle anomalies in brain structure in the absence of visible pathology. Our results provide further insight into the neuroanatomical correlates of known features of the cognitive phenotype of NF1. Copyright © 2012 Wiley Periodicals, Inc.

Firefly algorithm versus genetic algorithm as powerful variable selection tools and their effect on different multivariate calibration models in spectroscopy: A comparative study

NASA Astrophysics Data System (ADS)

Attia, Khalid A. M.; Nassar, Mohammed W. I.; El-Zeiny, Mohamed B.; Serag, Ahmed

2017-01-01

For the first time, a new variable selection method based on swarm intelligence namely firefly algorithm is coupled with three different multivariate calibration models namely, concentration residual augmented classical least squares, artificial neural network and support vector regression in UV spectral data. A comparative study between the firefly algorithm and the well-known genetic algorithm was developed. The discussion revealed the superiority of using this new powerful algorithm over the well-known genetic algorithm. Moreover, different statistical tests were performed and no significant differences were found between all the models regarding their predictabilities. This ensures that simpler and faster models were obtained without any deterioration of the quality of the calibration.

Genetic dissimilarity of putative gamma-ray-induced 'Preciosa-AAAB-Pome type' banana (Musa sp) mutants based on multivariate statistical analysis.

PubMed

Pestana, R K N; Amorim, E P; Ferreira, C F; Amorim, V B O; Oliveira, L S; Ledo, C A S; Silva, S O

2011-10-25

Bananas are among the most important fruit crops worldwide, being cultivated in more than 120 countries, mainly by small-scale producers. However, short-stature high-yielding bananas presenting good agronomic characteristics are hard to find. Consequently, wind continues to damage a great number of plantations each year, leading to lodging of plants and bunch loss. Development of new cultivars through conventional genetic breeding methods is hindered by female sterility and the low number of seeds. Mutation induction seems to have great potential for the development of new cultivars. We evaluated genetic dissimilarity among putative 'Preciosa' banana mutants generated by gamma-ray irradiation, using morphoagronomic characteristics and ISSR markers. The genetic distances between the putative 'Preciosa' mutants varied from 0.21 to 0.66, with a cophenetic correlation coefficient of 0.8064. We found good variability after irradiation of 'Preciosa' bananas; this procedure could be useful for banana breeding programs aimed at developing short-stature varieties with good agronomic characteristics.

Trabecular bone microarchitecture analysis, a way for an early detection of genetic dwarfism? Case study of a dwarf mother's offspring.

PubMed

Colombo, Antony; Hoogland, Menno; Coqueugniot, Hélène; Dutour, Olivier; Waters-Rist, Andrea

2018-03-01

A 66 year-old woman with a disproportionate dwarfism and who bore seven children was discovered at the Middenbeemster archaeological site (The Netherlands). Three are perinates and show no macroscopic or radiological evidence for a FGFR3 mutation causing hypo-or achondroplasia. This mutation induces dysfunction of the growth cartilage, leading to abnormalities in the development of trabecular bone. Because the mutation is autosomal dominant, these perinates have a 50% risk of having been affected. This study determines whether trabecular bone microarchitecture (TBMA) analysis is useful for detecting genetic dwarfism. Proximal metaphyses of humeri were μCT-scanned with a resolution of 7-12 μm. Three volumes of interest were segmented from each bone with TIVMI© software. The TBMA was quantified in BoneJ© using six parameters on which a multivariate analysis was then performed. Two of the Middenbeemster perinates show a quantitatively different TBMA organization. These results and the family's medical history suggest a diagnosis of genetic dwarfism for this two perinates. This study provides evidence to support the efficacy of μCT for diagnosing early-stage bone disease. Copyright © 2017 Elsevier Inc. All rights reserved.

Analysis of positive control STR experiments reveals that results obtained for FGA, D3S1358, and D13S317 condition the success rate of the analysis of routine reference samples.

PubMed

Murigneux, Valentine; Dufour, Anne-Béatrice; Lobry, Jean R; Pène, Laurent

2014-07-01

About 120,000 reference samples are analyzed each year in the Forensic Laboratory of Lyon. A total of 1640 positive control experiments used to validate and optimize the analytical method in the routine process were submitted to a multivariate exploratory data analysis approach with the aim of better understanding the underlying sources of variability. The peak heights of the 16 genetic markers targeted by the AmpFℓSTR(®) Identifiler(®) STR kit were used as variables of interest. Six different 3130xl genetic analyzers located in the same controlled environment were involved. Two major sources of variability were found: (i) the DNA load of the sample modulates all peak heights in a similar way so that the 16 markers are highly correlated, (ii) the genetic analyzer used with a locus-specific response for peak height and a better sensitivity for the most recently acquired. Three markers (FGA, D3S1358, and D13S317) were found to be of special interest to predict the success rate observed in the routine process. © 2014 American Academy of Forensic Sciences.

Assessment of genetic diversity of Tunisian orange, Citrus sinensis (L.) Osbeck using microsatellite (SSR) markers.

PubMed

Mahjbi, A; Oueslati, A; Baraket, G; Salhi-Hannachi, A; Zehdi Azouzi, S

2016-05-20

Citrus are one of the most cultivated crops in the world. Economically, they are very important fruit trees in Tunisia. Little is known about the genetic diversity of the Tunisian Citrus germplasm. Exploring this diversity is a prerequisite for the identification and characterization of the local germplasm to circumvent and controlling genetic erosion caused by biotic and abiotic stress to aid its conservation and use. In the present study, we explored the genetic diversity of 20 Tunisian orange cultivars [Citrus sinensis (L.) Osbeck] and established their relationships by using seven simple sequence repeat (SSR) loci. In total, 37 alleles and 44 genotypes were scored. The sizes of alleles ranged from 90 to 280 bp. The number of alleles per locus was from 4 to 7, with an average of 5.28. Polymorphic information content value changed from 0.599 to 0.769 with an average of 0.675. Analysis of the genotypes revealed a heterozygote deficiency across all the genotypes. The observed heterozygosity varied from 0 to 1 (average of 0.671). Cluster analysis showed that three groups could be distinguished and the polymorphism occurred independently of the geographical origin of the studied orange cultivars. The detected SSR genotypes allowed the establishment of an identification key with a discriminating power of 100%. Multivariate analysis and the neighbor-joining phylogenetic tree indicated a narrow genetic base for the orange cultivars. The usefulness of SSR markers for orange fingerprinting and evaluation of the genetic diversity in the Tunisian germplasm are discussed in this paper.

Prevalence, heritability and genetic correlations of congenital sensorineural deafness and pigmentation phenotypes in the Border Collie.

PubMed

De Risio, Luisa; Lewis, Tom; Freeman, Julia; de Stefani, Alberta; Matiasek, Lara; Blott, Sarah

2011-06-01

The objectives of this study were to estimate prevalence, heritability and genetic correlations of congenital sensorineural deafness (CSD) and pigmentation phenotypes in the Border Collie. Entire litters of Border Collies that presented to the Animal Health Trust (1994-2008) for assessment of hearing status by brain stem auditory evoked response (BAER) at 4-10 weeks of age were included. Heritability and genetic correlations were estimated using residual maximum likelihood (REML). Of 4143 puppies that met the inclusion criteria, 97.6% had normal hearing status, 2.0% were unilaterally deaf and 0.4% were bilaterally deaf. Heritability of deafness as a trichotomous trait (normal/unilaterally deaf/bilaterally deaf) was estimated at 0.42 using multivariate analysis. Genetic correlations of deafness with iris colour and merle coat colour were 0.58 and 0.26, respectively. These results indicate that there is a significant genetic effect on CSD in Border Collies and that some of the genes determining deafness also influence pigmentation phenotypes. Copyright © 2010 Elsevier Ltd. All rights reserved.

Identifying pleiotropic genes in genome-wide association studies from related subjects using the linear mixed model and Fisher combination function.

PubMed

Yang, James J; Williams, L Keoki; Buu, Anne

2017-08-24

A multivariate genome-wide association test is proposed for analyzing data on multivariate quantitative phenotypes collected from related subjects. The proposed method is a two-step approach. The first step models the association between the genotype and marginal phenotype using a linear mixed model. The second step uses the correlation between residuals of the linear mixed model to estimate the null distribution of the Fisher combination test statistic. The simulation results show that the proposed method controls the type I error rate and is more powerful than the marginal tests across different population structures (admixed or non-admixed) and relatedness (related or independent). The statistical analysis on the database of the Study of Addiction: Genetics and Environment (SAGE) demonstrates that applying the multivariate association test may facilitate identification of the pleiotropic genes contributing to the risk for alcohol dependence commonly expressed by four correlated phenotypes. This study proposes a multivariate method for identifying pleiotropic genes while adjusting for cryptic relatedness and population structure between subjects. The two-step approach is not only powerful but also computationally efficient even when the number of subjects and the number of phenotypes are both very large.

Genetic risk score and cardiovascular mortality in a southern european population with coronary artery disease.

PubMed

Pereira, Andreia; Mendonca, Maria Isabel; Sousa, Ana Célia; Borges, Sofia; Freitas, Sónia; Henriques, Eva; Rodrigues, Mariana; Freitas, Ana Isabel; Guerra, Graça; Ornelas, Ilídio; Pereira, Décio; Brehm, António; Palma Dos Reis, Roberto

2017-06-01

Several genetic risk scores (GRS) have been associated with cardiovascular disease; their role, however, in survival from proven coronary artery disease (CAD) have yielded conflicting results. The objective of this study was to evaluate long-term cardiovascular mortality according to the genetic risk score in a Southern European population with CAD. A cohort of 1464 CAD patients with angiographic proven CAD were followed up prospectively for up to 58.3 (interquartile range: 25.8-88.1) months. Genotyping of 32 single-nucleotide polymorphisms previously associated with CAD was performed using oligonucleotides probes marked with fluorescence for each allele. GRS was constructed according to the additive model assuming codominance and categorised using the median (=26). Cox Regression analysis was performed to determine independent multivariate predictors of cardiovascular mortality. Kaplan-Meier survival curves compared high vs low GRS using log-rank test. C-index was done for our population, as a measure of discrimination in survival analysis model. During a mean follow-up of 58.3 months, 156 patients (10.7%) died, 107 (7.3%) of CV causes. High GRS (≥26) was associated with reduced cardiovascular survival. Survival analysis with Cox regression model adjusted for 8 variables showed that high GRS, dyslipidemia, diabetes and 3-vessel disease were independent risk factors for cardiovascular mortality (HR=1.53, P=.037; HR=3.64, P=.012; HR=1.75, P=.004; HR=2.97, P<.0001, respectively). At the end of follow-up, the estimated survival probability was 70.8% for high GRS and 80.8% for low GRS (Log-rank test 5.6; P=.018). C-Index of 0.71 was found when GRS was added to a multivariate survival model of diabetes, dyslipidemia, smoking, hypertension and 3 vessel disease, stable angina and dual antiplatelet therapy. Besides the classical risk factors management, this work highlights the relevance of the genetic profile in survival from CAD. It is expected that new therapies will be dirsected to gene targets with proven value in cardiovascular survival. © 2017 John Wiley & Sons Ltd.

Radiogenomics to characterize regional genetic heterogeneity in glioblastoma

PubMed Central

Hu, Leland S.; Ning, Shuluo; Eschbacher, Jennifer M.; Baxter, Leslie C.; Gaw, Nathan; Ranjbar, Sara; Plasencia, Jonathan; Dueck, Amylou C.; Peng, Sen; Smith, Kris A.; Nakaji, Peter; Karis, John P.; Quarles, C. Chad; Wu, Teresa; Loftus, Joseph C.; Jenkins, Robert B.; Sicotte, Hugues; Kollmeyer, Thomas M.; O'Neill, Brian P.; Elmquist, William; Hoxworth, Joseph M.; Frakes, David; Sarkaria, Jann; Swanson, Kristin R.; Tran, Nhan L.; Li, Jing; Mitchell, J. Ross

2017-01-01

Background Glioblastoma (GBM) exhibits profound intratumoral genetic heterogeneity. Each tumor comprises multiple genetically distinct clonal populations with different therapeutic sensitivities. This has implications for targeted therapy and genetically informed paradigms. Contrast-enhanced (CE)-MRI and conventional sampling techniques have failed to resolve this heterogeneity, particularly for nonenhancing tumor populations. This study explores the feasibility of using multiparametric MRI and texture analysis to characterize regional genetic heterogeneity throughout MRI-enhancing and nonenhancing tumor segments. Methods We collected multiple image-guided biopsies from primary GBM patients throughout regions of enhancement (ENH) and nonenhancing parenchyma (so called brain-around-tumor, [BAT]). For each biopsy, we analyzed DNA copy number variants for core GBM driver genes reported by The Cancer Genome Atlas. We co-registered biopsy locations with MRI and texture maps to correlate regional genetic status with spatially matched imaging measurements. We also built multivariate predictive decision-tree models for each GBM driver gene and validated accuracies using leave-one-out-cross-validation (LOOCV). Results We collected 48 biopsies (13 tumors) and identified significant imaging correlations (univariate analysis) for 6 driver genes: EGFR, PDGFRA, PTEN, CDKN2A, RB1, and TP53. Predictive model accuracies (on LOOCV) varied by driver gene of interest. Highest accuracies were observed for PDGFRA (77.1%), EGFR (75%), CDKN2A (87.5%), and RB1 (87.5%), while lowest accuracy was observed in TP53 (37.5%). Models for 4 driver genes (EGFR, RB1, CDKN2A, and PTEN) showed higher accuracy in BAT samples (n = 16) compared with those from ENH segments (n = 32). Conclusion MRI and texture analysis can help characterize regional genetic heterogeneity, which offers potential diagnostic value under the paradigm of individualized oncology. PMID:27502248

Multivariate genetic determinants of EEG oscillations in schizophrenia and psychotic bipolar disorder from the BSNIP study

PubMed Central

Narayanan, B; Soh, P; Calhoun, V D; Ruaño, G; Kocherla, M; Windemuth, A; Clementz, B A; Tamminga, C A; Sweeney, J A; Keshavan, M S; Pearlson, G D

2015-01-01

Schizophrenia (SZ) and psychotic bipolar disorder (PBP) are disabling psychiatric illnesses with complex and unclear etiologies. Electroencephalogram (EEG) oscillatory abnormalities in SZ and PBP probands are heritable and expressed in their relatives, but the neurobiology and genetic factors mediating these abnormalities in the psychosis dimension of either disorder are less explored. We examined the polygenic architecture of eyes-open resting state EEG frequency activity (intrinsic frequency) from 64 channels in 105 SZ, 145 PBP probands and 56 healthy controls (HCs) from the multisite BSNIP (Bipolar-Schizophrenia Network on Intermediate Phenotypes) study. One million single-nucleotide polymorphisms (SNPs) were derived from DNA. We assessed eight data-driven EEG frequency activity derived from group-independent component analysis (ICA) in conjunction with a reduced subset of 10 422 SNPs through novel multivariate association using parallel ICA (para-ICA). Genes contributing to the association were examined collectively using pathway analysis tools. Para-ICA extracted five frequency and nine SNP components, of which theta and delta activities were significantly correlated with two different gene components, comprising genes participating extensively in brain development, neurogenesis and synaptogenesis. Delta and theta abnormality was present in both SZ and PBP, while theta differed between the two disorders. Theta abnormalities were also mediated by gene clusters involved in glutamic acid pathways, cadherin and synaptic contact-based cell adhesion processes. Our data suggest plausible multifactorial genetic networks, including novel and several previously identified (DISC1) candidate risk genes, mediating low frequency delta and theta abnormalities in psychoses. The gene clusters were enriched for biological properties affecting neural circuitry and involved in brain function and/or development. PMID:26101851

Application of neural networks with novel independent component analysis methodologies to a Prussian blue modified glassy carbon electrode array.

PubMed

Wang, Liang; Yang, Die; Fang, Cheng; Chen, Zuliang; Lesniewski, Peter J; Mallavarapu, Megharaj; Naidu, Ravendra

2015-01-01

Sodium potassium absorption ratio (SPAR) is an important measure of agricultural water quality, wherein four exchangeable cations (K(+), Na(+), Ca(2+) and Mg(2+)) should be simultaneously determined. An ISE-array is suitable for this application because its simplicity, rapid response characteristics and lower cost. However, cross-interferences caused by the poor selectivity of ISEs need to be overcome using multivariate chemometric methods. In this paper, a solid contact ISE array, based on a Prussian blue modified glassy carbon electrode (PB-GCE), was applied with a novel chemometric strategy. One of the most popular independent component analysis (ICA) methods, the fast fixed-point algorithm for ICA (fastICA), was implemented by the genetic algorithm (geneticICA) to avoid the local maxima problem commonly observed with fastICA. This geneticICA can be implemented as a data preprocessing method to improve the prediction accuracy of the Back-propagation neural network (BPNN). The ISE array system was validated using 20 real irrigation water samples from South Australia, and acceptable prediction accuracies were obtained. Copyright © 2014 Elsevier B.V. All rights reserved.

Quantitative analysis of production traits in saltwater crocodiles (Crocodylus porosus): II. age at slaughter.

PubMed

Isberg, S R; Thomson, P C; Nicholas, F W; Barker, S G; Moran, C

2005-12-01

Crocodile morphometric (head, snout-vent and total length) measurements were recorded at three stages during the production chain: hatching, inventory [average age (+/-SE) is 265.1 +/- 0.4 days] and slaughter (average age is 1037.8 +/- 0.4 days). Crocodile skins are used for the manufacture of exclusive leather products, with the most common-sized skin sold having 35-45 cm in belly width. One of the breeding objectives for inclusion into a multitrait genetic improvement programme for saltwater crocodiles is the time taken for a juvenile to reach this size or age at slaughter. A multivariate restricted maximum likelihood analysis provided (co)variance components for estimating the first published genetic parameter estimates for these traits. Heritability (+/-SE) estimates for the traits hatchling snout-vent length, inventory head length and age at slaughter were 0.60 (0.15), 0.59 (0.12) and 0.40 (0.10) respectively. There were strong negative genetic (-0.81 +/- 0.08) and phenotypic (-0.82 +/- 0.02) correlations between age at slaughter and inventory head length.

A DNA fingerprinting procedure for ultra high-throughput genetic analysis of insects.

PubMed

Schlipalius, D I; Waldron, J; Carroll, B J; Collins, P J; Ebert, P R

2001-12-01

Existing procedures for the generation of polymorphic DNA markers are not optimal for insect studies in which the organisms are often tiny and background molecular information is often non-existent. We have used a new high throughput DNA marker generation protocol called randomly amplified DNA fingerprints (RAF) to analyse the genetic variability in three separate strains of the stored grain pest, Rhyzopertha dominica. This protocol is quick, robust and reliable even though it requires minimal sample preparation, minute amounts of DNA and no prior molecular analysis of the organism. Arbitrarily selected oligonucleotide primers routinely produced approximately 50 scoreable polymorphic DNA markers, between individuals of three independent field isolates of R. dominica. Multivariate cluster analysis using forty-nine arbitrarily selected polymorphisms generated from a single primer reliably separated individuals into three clades corresponding to their geographical origin. The resulting clades were quite distinct, with an average genetic difference of 37.5 +/- 6.0% between clades and of 21.0 +/- 7.1% between individuals within clades. As a prelude to future gene mapping efforts, we have also assessed the performance of RAF under conditions commonly used in gene mapping. In this analysis, fingerprints from pooled DNA samples accurately and reproducibly reflected RAF profiles obtained from individual DNA samples that had been combined to create the bulked samples.

Genetic parameters for body condition score, body weight, milk yield, and fertility estimated using random regression models.

PubMed

Berry, D P; Buckley, F; Dillon, P; Evans, R D; Rath, M; Veerkamp, R F

2003-11-01

Genetic (co)variances between body condition score (BCS), body weight (BW), milk yield, and fertility were estimated using a random regression animal model extended to multivariate analysis. The data analyzed included 81,313 BCS observations, 91,937 BW observations, and 100,458 milk test-day yields from 8725 multiparous Holstein-Friesian cows. A cubic random regression was sufficient to model the changing genetic variances for BCS, BW, and milk across different days in milk. The genetic correlations between BCS and fertility changed little over the lactation; genetic correlations between BCS and interval to first service and between BCS and pregnancy rate to first service varied from -0.47 to -0.31, and from 0.15 to 0.38, respectively. This suggests that maximum genetic gain in fertility from indirect selection on BCS should be based on measurements taken in midlactation when the genetic variance for BCS is largest. Selection for increased BW resulted in shorter intervals to first service, but more services and poorer pregnancy rates; genetic correlations between BW and pregnancy rate to first service varied from -0.52 to -0.45. Genetic selection for higher lactation milk yield alone through selection on increased milk yield in early lactation is likely to have a more deleterious effect on genetic merit for fertility than selection on higher milk yield in late lactation.

Psychosocial and Clinical Factors Associated with Family Communication of Cancer Genetic Test Results Among Women Diagnosed with Breast Cancer at a Young Age

PubMed Central

Elrick, Ashley; Ashida, Sato; Ivanovich, Jennifer; Lyons, Sarah; Biesecker, Barbara B.; Goodman, Melody S.; Kaphingst, Kimberly A.

2016-01-01

Genetic test results have medical implications beyond the patient that extend to biological family members. We examined psychosocial and clinical factors associated with communication of genetic test results within families. Women (N=1080) diagnosed with breast cancer at age 40 or younger completed an online survey; 920 women that reported prior cancer genetic testing were included in analysis. We examined the proportion of immediate family members to whom they communicated genetic test results, and built multivariable regression models to examine clinical and psychosocial variables associated with the proportion score. Participants were most likely to communicate test results to their mother (83%) and least likely to their son (45%). Participants who carried a BRCA mutation (OR=1.34; 95% CI = 1.06, 1.70), had higher interest in genomic information (OR=1.55; 95% CI = 1.26, 1.91) and lower genetic worry (OR=0.91; 95% CI = 0.86, 0.96) communicated genetic test results to a greater proportion of their immediate family members. Participants with a BRCA1/2 mutation shared their genetic test results with more male family members (OR=1.72; 95% CI = 1.02, 2.89). Our findings suggest that patients with high worry about genetic risks, low interest in genomic information, or receive a negative genetic test result will likely need additional support to encourage family communication. PMID:27422778

The Covariation of Antisocial Behavior and Substance Use in Adolescence: A Behavioral Genetic Perspective

ERIC Educational Resources Information Center

McAdams, Tom; Rowe, Richard; Rijsdijk, Fruhling; Maughan, Barbara; Eley, Thalia C.

2012-01-01

Multivariate genetic studies have revealed genetic correlations between antisocial behavior (ASB) and substance use (SU). However, ASB is heterogeneous, and it remains unclear whether all forms are similarly related to SU. The present study examines links between cannabis use, alcohol consumption, and aggressive and delinquent forms of ASB using a…

Genetics, the Big Five, and the Tendency to Be Self-Employed

ERIC Educational Resources Information Center

Shane, Scott; Nicolaou, Nicos; Cherkas, Lynn; Spector, Tim D.

2010-01-01

We applied multivariate genetics techniques to a sample of 3,412 monozygotic and dizygotic twins from the United Kingdom and 1,300 monozygotic and dizygotic twins from the United States to examine whether genetic factors account for part of the covariance between the Big Five personality characteristics and the tendency to be an entrepreneur. We…

Associations among facial masculinity, physical strength, fluctuating asymmetry and attractiveness in young men and women.

PubMed

Van Dongen, Stefan

2014-01-01

Studies of the process of human mate selection and attractiveness have assumed that selection favours morphological features that correlate with (genetic) quality. Degree of masculinity/femininity and fluctuating asymmetry (FA) may signal (genetic) quality, but what information they harboured and how they relate to fitness is still debated. To study strength of associations between facial masculinity/femininity, facial FA, attractiveness and physical strength in humans. Two-hundred young males and females were studied by measuring facial asymmetry and masculinity on the basis of frontal photographs. Attractiveness was determined on the basis of scores given by an anonymous panel, and physical strength using hand grip strength. Patterns differed markedly between males and females and analysis method used (univariate vs multivariate). Overall, no associations between FA and attractiveness, masculinity and physical strength were found. In females, but not males, masculinity and attractiveness correlated negatively and masculinity and physical strength correlated positively. Further research into the differences between males and females in associations between facial morphology, attractiveness and physical strength is clearly needed. The use of a multivariate approach can increase our understanding of which regions of the face harbour specific information of hormone levels and perhaps behavioural traits.

Environmental heterogeneity explains the genetic structure of Continental and Mediterranean populations of Fraxinus angustifolia Vahl.

PubMed

Temunović, Martina; Franjić, Jozo; Satovic, Zlatko; Grgurev, Marin; Frascaria-Lacoste, Nathalie; Fernández-Manjarrés, Juan F

2012-01-01

Tree species with wide distributions often exhibit different levels of genetic structuring correlated to their environment. However, understanding how environmental heterogeneity influences genetic variation is difficult because the effects of gene flow, drift and selection are confounded. We investigated the genetic variation and its ecological correlates in a wind-pollinated Mediterranean tree species, Fraxinus angustifolia Vahl, within a recognised glacial refugium in Croatia. We sampled 11 populations from environmentally divergent habitats within the Continental and Mediterranean biogeographical regions. We combined genetic data analyses based on nuclear microsatellite loci, multivariate statistics on environmental data and ecological niche modelling (ENM). We identified a geographic structure with a high genetic diversity and low differentiation in the Continental region, which contrasted with the significantly lower genetic diversity and higher population divergence in the Mediterranean region. The positive and significant correlation between environmental and genetic distances after controlling for geographic distance suggests an important influence of ecological divergence of the sites in shaping genetic variation. The ENM provided support for niche differentiation between the populations from the Continental and Mediterranean regions, suggesting that contemporary populations may represent two divergent ecotypes. Ecotype differentiation was also supported by multivariate environmental and genetic distance analyses. Our results suggest that despite extensive gene flow in continental areas, long-term stability of heterogeneous environments have likely promoted genetic divergence of ashes in this region and can explain the present-day genetic variation patterns of these ancient populations.

Environmental Heterogeneity Explains the Genetic Structure of Continental and Mediterranean Populations of Fraxinus angustifolia Vahl

PubMed Central

Temunović, Martina; Franjić, Jozo; Satovic, Zlatko; Grgurev, Marin; Frascaria-Lacoste, Nathalie; Fernández-Manjarrés, Juan F.

2012-01-01

Tree species with wide distributions often exhibit different levels of genetic structuring correlated to their environment. However, understanding how environmental heterogeneity influences genetic variation is difficult because the effects of gene flow, drift and selection are confounded. We investigated the genetic variation and its ecological correlates in a wind-pollinated Mediterranean tree species, Fraxinus angustifolia Vahl, within a recognised glacial refugium in Croatia. We sampled 11 populations from environmentally divergent habitats within the Continental and Mediterranean biogeographical regions. We combined genetic data analyses based on nuclear microsatellite loci, multivariate statistics on environmental data and ecological niche modelling (ENM). We identified a geographic structure with a high genetic diversity and low differentiation in the Continental region, which contrasted with the significantly lower genetic diversity and higher population divergence in the Mediterranean region. The positive and significant correlation between environmental and genetic distances after controlling for geographic distance suggests an important influence of ecological divergence of the sites in shaping genetic variation. The ENM provided support for niche differentiation between the populations from the Continental and Mediterranean regions, suggesting that contemporary populations may represent two divergent ecotypes. Ecotype differentiation was also supported by multivariate environmental and genetic distance analyses. Our results suggest that despite extensive gene flow in continental areas, long-term stability of heterogeneous environments have likely promoted genetic divergence of ashes in this region and can explain the present-day genetic variation patterns of these ancient populations. PMID:22905171

Parent Beliefs about the Causes of Learning and Developmental Problems among Children with Autism Spectrum Disorder: Results from a National Survey

PubMed Central

Lindly, Olivia J.; Sinche, Brianna

2017-01-01

This study aimed to assess variation in parent beliefs about causes of learning and developmental problems in U.S. children with autism spectrum disorder, using data from a nationally-representative survey. Results showed that beliefs about a genetic/hereditary cause of learning/developmental problems were most common, but nearly as many parents believed in exposure causes. 40% of parents had no definite causal beliefs. On multivariate analysis, parents who were non-white, publicly-insured or poor were more likely than other parents to endorse exposure causes, or less likely to endorse genetic causes, compared to other parents. Further research should assess how these beliefs modify health care quality or services utilization. PMID:27611353

Firefly algorithm versus genetic algorithm as powerful variable selection tools and their effect on different multivariate calibration models in spectroscopy: A comparative study.

PubMed

Attia, Khalid A M; Nassar, Mohammed W I; El-Zeiny, Mohamed B; Serag, Ahmed

2017-01-05

For the first time, a new variable selection method based on swarm intelligence namely firefly algorithm is coupled with three different multivariate calibration models namely, concentration residual augmented classical least squares, artificial neural network and support vector regression in UV spectral data. A comparative study between the firefly algorithm and the well-known genetic algorithm was developed. The discussion revealed the superiority of using this new powerful algorithm over the well-known genetic algorithm. Moreover, different statistical tests were performed and no significant differences were found between all the models regarding their predictabilities. This ensures that simpler and faster models were obtained without any deterioration of the quality of the calibration. Copyright © 2016 Elsevier B.V. All rights reserved.

Quantitative genetic analysis of the body composition and blood pressure association in two ethnically diverse populations.

PubMed

Ghosh, Sudipta; Dosaev, Tasbulat; Prakash, Jai; Livshits, Gregory

2017-04-01

The major aim of this study was to conduct comparative quantitative-genetic analysis of the body composition (BCP) and somatotype (STP) variation, as well as their correlations with blood pressure (BP) in two ethnically, culturally and geographically different populations: Santhal, indigenous ethnic group from India and Chuvash, indigenous population from Russia. Correspondently two pedigree-based samples were collected from 1,262 Santhal and1,558 Chuvash individuals, respectively. At the first stage of the study, descriptive statistics and a series of univariate regression analyses were calculated. Finally, multiple and multivariate regression (MMR) analyses, with BP measurements as dependent variables and age, sex, BCP and STP as independent variables were carried out in each sample separately. The significant and independent covariates of BP were identified and used for re-examination in pedigree-based variance decomposition analysis. Despite clear and significant differences between the populations in BCP/STP, both Santhal and Chuvash were found to be predominantly mesomorphic irrespective of their sex. According to MMR analyses variation of BP significantly depended on age and mesomorphic component in both samples, and in addition on sex, ectomorphy and fat mass index in Santhal and on fat free mass index in Chuvash samples, respectively. Additive genetic component contributes to a substantial proportion of blood pressure and body composition variance. Variance component analysis in addition to above mentioned results suggests that additive genetic factors influence BP and BCP/STP associations significantly. © 2017 Wiley Periodicals, Inc.

Proton Nuclear Magnetic Resonance-Spectroscopic Discrimination of Wines Reflects Genetic Homology of Several Different Grape (V. vinifera L.) Cultivars

PubMed Central

Zhu, Yong; Wen, Wen; Zhang, Fengmin; Hardie, Jim W.

2015-01-01

Background and Aims Proton nuclear magnetic resonance spectroscopy coupled multivariate analysis (1H NMR-PCA/PLS-DA) is an important tool for the discrimination of wine products. Although 1H NMR has been shown to discriminate wines of different cultivars, a grape genetic component of the discrimination has been inferred only from discrimination of cultivars of undefined genetic homology and in the presence of many confounding environmental factors. We aimed to confirm the influence of grape genotypes in the absence of those factors. Methods and Results We applied 1H NMR-PCA/PLS-DA and hierarchical cluster analysis (HCA) to wines from five, variously genetically-related grapevine (V. vinifera) cultivars; all grown similarly on the same site and vinified similarly. We also compared the semi-quantitative profiles of the discriminant metabolites of each cultivar with previously reported chemical analyses. The cultivars were clearly distinguishable and there was a general correlation between their grouping and their genetic homology as revealed by recent genomic studies. Between cultivars, the relative amounts of several of the cultivar-related discriminant metabolites conformed closely with reported chemical analyses. Conclusions Differences in grape-derived metabolites associated with genetic differences alone are a major source of 1H NMR-based discrimination of wines and 1H NMR has the capacity to discriminate between very closely related cultivars. Significance of the Study The study confirms that genetic variation among grape cultivars alone can account for the discrimination of wine by 1H NMR-PCA/PLS and indicates that 1H NMR spectra of wine of single grape cultivars may in future be used in tandem with hierarchical cluster analysis to elucidate genetic lineages and metabolomic relations of grapevine cultivars. In the absence of genetic information, for example, where predecessor varieties are no longer extant, this may be a particularly useful approach. PMID:26658757

Exploration of the Genetic Organization of Morphological Modularity on the Mouse Mandible Using a Set of Interspecific Recombinant Congenic Strains Between C57BL/6 and Mice of the Mus spretus Species

PubMed Central

Burgio, Gaëtan; Baylac, Michel; Heyer, Evelyne; Montagutelli, Xavier

2012-01-01

Morphological integration and modularity within semi-autonomous modules are essential mechanisms for the evolution of morphological traits. However, the genetic makeup responsible for the control of variational modularity is still relatively unknown. In our study, we tested the hypothesis that the genetic variation for mandible shape clustered into two morphogenetic components: the alveolar group and the ascending ramus. We used the mouse as a model system to investigate genetics determinants of mandible shape. To do this, we used a combination of geometric morphometric tools and a set of 18 interspecific recombinant congenic strains (IRCS) derived from the distantly related species, Mus spretus SEG/Pas and Mus musculus C57BL/6. Quantitative trait loci (QTL) analysis comparing mandible morphometry between the C57BL/6 and the IRCSs identified 42 putative SEG/Pas segments responsible for the genetic variation. The magnitude of the QTL effects was dependent on the proportion of SEG/Pas genome inherited. Using a multivariate correlation coefficient adapted for modularity assessment and a two-block partial least squares analysis to explore the morphological integration, we found that these QTL clustered into two well-integrated morphogenetic groups, corresponding to the ascending ramus and the alveolar region. Together, these results provide evidence that the mouse mandible is subjected to genetic coordination in a modular manner. PMID:23050236

Applications of time-of-flight secondary ion mass spectrometry (TOF-SIMS) and X-ray photoelectron spectroscopy (XPS) to study interactions of genetically engineered proteins with noble metal films

NASA Astrophysics Data System (ADS)

Suzuki, Noriaki

Genetically engineered proteins for inorganics (GEPIs) belong to a new class of polypeptides that are designed to have specific affinities to inorganic materials. A "gold binding protein (GBP)" was chosen as a model protein for GEPIs to study the molecular origins of binding specificity to gold using Time-of-flight secondary ion mass spectrometry (TOF-SIMS) and X-ray photoelectron spectroscopy (XPS). TOF-SIMS, a surface-sensitive analytical instrument with extremely high mass resolutions, provides information on specific amino acid-surface interactions. We used "principal component analysis (PCA)" to analyze the data. We also introduced a new multivariate technique, "hierarchical cluster analysis (HCA)" to organize the data into meaningful structures by measuring a degree of "similarity" and "dissimilarity" of the data. This report discusses a combined use of PCA and HCA to elucidate the binding specificity of GBP to Au. Based on the knowledge gained from TOF-SIMS measurements, we further investigated the nature of the interaction between selected amino acids and noble metal surfaces by using X-ray photoelectron spectroscopy (XPS). We developed a unique capability to introduce water vapor during the adsorption of a single amino acid and applied this method to study the intrinsic nature of sidechain/Au interactions. To further apply this unique research protocol, we characterized another type of GEPI, "quartz binding protein (QBP)," to identify the possible binding sites. This thesis research aims to provide experimental protocols for analyzing short peptide-substrate interface from complex spectroscopic data by using multivariate analysis techniques.

Who is afraid of math? Two sources of genetic variance for mathematical anxiety.

PubMed

Wang, Zhe; Hart, Sara Ann; Kovas, Yulia; Lukowski, Sarah; Soden, Brooke; Thompson, Lee A; Plomin, Robert; McLoughlin, Grainne; Bartlett, Christopher W; Lyons, Ian M; Petrill, Stephen A

2014-09-01

Emerging work suggests that academic achievement may be influenced by the management of affect as well as through efficient information processing of task demands. In particular, mathematical anxiety has attracted recent attention because of its damaging psychological effects and potential associations with mathematical problem solving and achievement. This study investigated the genetic and environmental factors contributing to the observed differences in the anxiety people feel when confronted with mathematical tasks. In addition, the genetic and environmental mechanisms that link mathematical anxiety with math cognition and general anxiety were also explored. Univariate and multivariate quantitative genetic models were conducted in a sample of 514 12-year-old twin siblings. Genetic factors accounted for roughly 40% of the variation in mathematical anxiety, with the remaining being accounted for by child-specific environmental factors. Multivariate genetic analyses suggested that mathematical anxiety was influenced by the genetic and nonfamilial environmental risk factors associated with general anxiety and additional independent genetic influences associated with math-based problem solving. The development of mathematical anxiety may involve not only exposure to negative experiences with mathematics, but also likely involves genetic risks related to both anxiety and math cognition. These results suggest that integrating cognitive and affective domains may be particularly important for mathematics and may extend to other areas of academic achievement. © 2014 The Authors. Journal of Child Psychology and Psychiatry. © 2014 Association for Child and Adolescent Mental Health.

Who’s Afraid of Math? Two Sources of Genetic Variance for Mathematical Anxiety

PubMed Central

Wang, Zhe; Hart, Sara Ann; Kovas, Yulia; Lukowski, Sarah; Soden, Brooke; Thompson, Lee A.; Plomin, Robert; McLoughlin, Grainne; Bartlett, Christopher W.; Lyons, Ian M.; Petrill, Stephen A.

2015-01-01

Background Emerging work suggests that academic achievement may be influenced by the management of affect as well as through efficient information processing of task demands. In particular, mathematical anxiety has attracted recent attention because of its damaging psychological effects and potential associations with mathematical problem-solving and achievement. The present study investigated the genetic and environmental factors contributing to the observed differences in the anxiety people feel when confronted with mathematical tasks. In addition, the genetic and environmental mechanisms that link mathematical anxiety with math cognition and general anxiety were also explored. Methods Univariate and multivariate quantitative genetic models were conducted in a sample of 514 12-year-old twin siblings. Results Genetic factors accounted for roughly 40% of the variation in mathematical anxiety, with the remaining being accounted for by child-specific environmental factors. Multivariate genetic analyses suggested that mathematical anxiety was influenced by the genetic and non-familial environmental risk factors associated with general anxiety and additional independent genetic influences associated with math-based problem solving. Conclusions The development of mathematical anxiety may involve not only exposure to negative experiences with mathematics, but also likely involves genetic risks related to both anxiety and math cognition. These results suggest that integrating cognitive and affective domains may be particularly important for mathematics, and may extend to other areas of academic achievement. PMID:24611799

Quantitative Genetic Architecture at Latitudinal Range Boundaries: Reduced Variation but Higher Trait Independence.

PubMed

Paccard, Antoine; Van Buskirk, Josh; Willi, Yvonne

2016-05-01

Species distribution limits are hypothesized to be caused by small population size and limited genetic variation in ecologically relevant traits, but earlier studies have not evaluated genetic variation in multivariate phenotypes. We asked whether populations at the latitudinal edges of the distribution have altered quantitative genetic architecture of ecologically relevant traits compared with midlatitude populations. We calculated measures of evolutionary potential in nine Arabidopsis lyrata populations spanning the latitudinal range of the species in eastern and midwestern North America. Environments at the latitudinal extremes have reduced water availability, and therefore plants were assessed under wet and dry treatments. We estimated genetic variance-covariance (G-) matrices for 10 traits related to size, development, and water balance. Populations at southern and northern distribution edges had reduced levels of genetic variation across traits, but their G-matrices were more spherical; G-matrix orientation was unrelated to latitude. As a consequence, the predicted short-term response to selection was at least as strong in edge populations as in central populations. These results are consistent with genetic drift eroding variation and reducing the effectiveness of correlational selection at distribution margins. We conclude that genetic variation of isolated traits poorly predicts the capacity to evolve in response to multivariate selection and that the response to selection may frequently be greater than expected at species distribution margins because of genetic drift.

Tryptophan hydroxylase type 2 variants modulate severity and outcome of addictive behaviors in Parkinson's disease.

PubMed

Cilia, Roberto; Benfante, Roberta; Asselta, Rosanna; Marabini, Laura; Cereda, Emanuele; Siri, Chiara; Pezzoli, Gianni; Goldwurm, Stefano; Fornasari, Diego

2016-08-01

Impulse control disorders and compulsive medication intake may occur in a minority of patients with Parkinson's disease (PD). We hypothesize that genetic polymorphisms associated with addiction in the general population may increase the risk for addictive behaviors also in PD. Sixteen polymorphisms in candidate genes belonging to five neurotransmitter systems (dopaminergic, catecholaminergic, serotonergic, glutamatergic, opioidergic) and the BDNF were screened in 154 PD patients with addictive behaviors and 288 PD control subjects. Multivariate analysis investigated clinical and genetic predictors of outcome (remission vs. persistence/relapse) after 1 year and at the last follow-up (5.1 ± 2.5 years). Addictive behaviors were associated with tryptophan hydroxylase type 2 (TPH2) and dopamine transporter gene variants. A subsequent analysis within the group of cases showed a robust association between TPH2 genotype and the severity of addictive behaviors, which survived Bonferroni correction for multiple testing. At multivariate analysis, TPH2 genotype resulted the strongest predictor of no remission at the last follow-up (OR[95%CI], 7.4[3.27-16.78] and 13.2[3.89-44.98] in heterozygous and homozygous carriers, respectively, p < 0.001). The extent of medication dose reduction was not a predictor. TPH2 haplotype analysis confirmed the association with more severe symptoms and lower remission rates in the short- and the long-term (p < 0.005 for all analyses). The serotonergic system is likely to be involved in the pathophysiology of addictive behaviors in PD, modulating the severity of symptoms and the rate of remission at follow-up. If confirmed in larger independent cohorts, TPH2 genotype may become a useful biomarker for the identification of at-risk individuals. Copyright © 2016 Elsevier Ltd. All rights reserved.

Rapid and Simultaneous Prediction of Eight Diesel Quality Parameters through ATR-FTIR Analysis.

PubMed

Nespeca, Maurilio Gustavo; Hatanaka, Rafael Rodrigues; Flumignan, Danilo Luiz; de Oliveira, José Eduardo

2018-01-01

Quality assessment of diesel fuel is highly necessary for society, but the costs and time spent are very high while using standard methods. Therefore, this study aimed to develop an analytical method capable of simultaneously determining eight diesel quality parameters (density; flash point; total sulfur content; distillation temperatures at 10% (T10), 50% (T50), and 85% (T85) recovery; cetane index; and biodiesel content) through attenuated total reflection Fourier transform infrared (ATR-FTIR) spectroscopy and the multivariate regression method, partial least square (PLS). For this purpose, the quality parameters of 409 samples were determined using standard methods, and their spectra were acquired in ranges of 4000-650 cm -1 . The use of the multivariate filters, generalized least squares weighting (GLSW) and orthogonal signal correction (OSC), was evaluated to improve the signal-to-noise ratio of the models. Likewise, four variable selection approaches were tested: manual exclusion, forward interval PLS (FiPLS), backward interval PLS (BiPLS), and genetic algorithm (GA). The multivariate filters and variables selection algorithms generated more fitted and accurate PLS models. According to the validation, the FTIR/PLS models presented accuracy comparable to the reference methods and, therefore, the proposed method can be applied in the diesel routine monitoring to significantly reduce costs and analysis time.

Rapid and Simultaneous Prediction of Eight Diesel Quality Parameters through ATR-FTIR Analysis

PubMed Central

Hatanaka, Rafael Rodrigues; Flumignan, Danilo Luiz; de Oliveira, José Eduardo

2018-01-01

Quality assessment of diesel fuel is highly necessary for society, but the costs and time spent are very high while using standard methods. Therefore, this study aimed to develop an analytical method capable of simultaneously determining eight diesel quality parameters (density; flash point; total sulfur content; distillation temperatures at 10% (T10), 50% (T50), and 85% (T85) recovery; cetane index; and biodiesel content) through attenuated total reflection Fourier transform infrared (ATR-FTIR) spectroscopy and the multivariate regression method, partial least square (PLS). For this purpose, the quality parameters of 409 samples were determined using standard methods, and their spectra were acquired in ranges of 4000–650 cm−1. The use of the multivariate filters, generalized least squares weighting (GLSW) and orthogonal signal correction (OSC), was evaluated to improve the signal-to-noise ratio of the models. Likewise, four variable selection approaches were tested: manual exclusion, forward interval PLS (FiPLS), backward interval PLS (BiPLS), and genetic algorithm (GA). The multivariate filters and variables selection algorithms generated more fitted and accurate PLS models. According to the validation, the FTIR/PLS models presented accuracy comparable to the reference methods and, therefore, the proposed method can be applied in the diesel routine monitoring to significantly reduce costs and analysis time. PMID:29629209

Investigation of Association Between Hip Osteoarthritis Susceptibility Loci and Radiographic Proximal Femur Shape

PubMed Central

Thiagarajah, Shankar; Wilkinson, J. Mark; Panoutsopoulou, Kalliope; Day‐Williams, Aaron G.; Cootes, Timothy F.; Wallis, Gillian A.; Loughlin, John; Arden, Nigel; Birrell, Fraser; Carr, Andrew; Chapman, Kay; Deloukas, Panos; Doherty, Michael; McCaskie, Andrew; Ollier, William E. R.; Rai, Ashok; Ralston, Stuart H.; Spector, Timothy D.; Valdes, Ana M.; Wallis, Gillian A.; Mark Wilkinson, J.; Zeggini, Eleftheria

2015-01-01

Objective To test whether previously reported hip morphology or osteoarthritis (OA) susceptibility loci are associated with proximal femur shape as represented by statistical shape model (SSM) modes and as univariate or multivariate quantitative traits. Methods We used pelvic radiographs and genotype data from 929 subjects with unilateral hip OA who had been recruited previously for the Arthritis Research UK Osteoarthritis Genetics Consortium genome‐wide association study. We built 3 SSMs capturing the shape variation of the OA‐unaffected proximal femur in the entire mixed‐sex cohort and for male/female‐stratified cohorts. We selected 41 candidate single‐nucleotide polymorphisms (SNPs) previously reported as being associated with hip morphology (for replication analysis) or OA (for discovery analysis) and for which genotype data were available. We performed 2 types of analysis for genotype–phenotype associations between these SNPs and the modes of the SSMs: 1) a univariate analysis using individual SSM modes and 2) a multivariate analysis using combinations of SSM modes. Results The univariate analysis identified association between rs4836732 (within the ASTN2 gene) and mode 5 of the female SSM (P = 0.0016) and between rs6976 (within the GLT8D1 gene) and mode 7 of the mixed‐sex SSM (P = 0.0003). The multivariate analysis identified association between rs5009270 (near the IFRD1 gene) and a combination of modes 3, 4, and 9 of the mixed‐sex SSM (P = 0.0004). Evidence of associations remained significant following adjustment for multiple testing. All 3 SNPs had previously been associated with hip OA. Conclusion These de novo findings suggest that rs4836732, rs6976, and rs5009270 may contribute to hip OA susceptibility by altering proximal femur shape. PMID:25939412

A multivariate analysis of genetic variation in the advertisement call of the gray treefrog, Hyla versicolor.

PubMed

Welch, Allison M; Smith, Michael J; Gerhardt, H Carl

2014-06-01

Genetic variation in sexual displays is crucial for an evolutionary response to sexual selection, but can be eroded by strong selection. Identifying the magnitude and sources of additive genetic variance underlying sexually selected traits is thus an important issue in evolutionary biology. We conducted a quantitative genetics experiment with gray treefrogs (Hyla versicolor) to investigate genetic variances and covariances among features of the male advertisement call. Two energetically expensive traits showed significant genetic variation: call duration, expressed as number of pulses per call, and call rate, represented by its inverse, call period. These two properties also showed significant genetic covariance, consistent with an energetic constraint to call production. Combining the genetic variance-covariance matrix with previous estimates of directional sexual selection imposed by female preferences predicts a limited increase in call duration but no change in call rate despite significant selection on both traits. In addition to constraints imposed by the genetic covariance structure, an evolutionary response to sexual selection may also be limited by high energetic costs of long-duration calls and by preferences that act most strongly against very short-duration calls. Meanwhile, the persistence of these preferences could be explained by costs of mating with males with especially unattractive calls. © 2014 The Author(s). Evolution © 2014 The Society for the Study of Evolution.

Population structure of the Korean gizzard shad, Konosirus punctatus (Clupeiformes, Clupeidae) using multivariate morphometric analysis

NASA Astrophysics Data System (ADS)

Myoung, Se Hun; Kim, Jin-Koo

2016-03-01

The gizzard shad, Konosirus punctatus, is one of the most important fish species in Korea, China, Japan and Taiwan, and therefore the implementation of an appropriate population structure analysis is both necessary and fitting. In order to clarify the current distribution range for the two lineages of the Korean gizzard shad (Myoung and Kim 2014), we conducted a multivariate morphometric analysis by locality and lineage. We analyzed 17 morphometric and 5 meristic characters of 173 individuals, which were sampled from eight localities in the East Sea, the Yellow Sea and the Korean Strait. Unlike population genetics studies, the canonical discriminant analysis (CDA) results showed that the two morphotypes were clearly segregated by the center value "0" of CAN1, of which morphotype A occurred from the Yellow Sea to the western Korean Strait with negative values, and morphotype B occurred from the East Sea to the eastern Korean Strait with positive values even though there exists an admixture zone in the eastern Korean Strait. Further studies using more sensitive markers such as microsatellite DNA are required in order to define the true relationship between the two lineages.

Genetic association of impulsivity in young adults: a multivariate study

PubMed Central

Khadka, S; Narayanan, B; Meda, S A; Gelernter, J; Han, S; Sawyer, B; Aslanzadeh, F; Stevens, M C; Hawkins, K A; Anticevic, A; Potenza, M N; Pearlson, G D

2014-01-01

Impulsivity is a heritable, multifaceted construct with clinically relevant links to multiple psychopathologies. We assessed impulsivity in young adult (N~2100) participants in a longitudinal study, using self-report questionnaires and computer-based behavioral tasks. Analysis was restricted to the subset (N=426) who underwent genotyping. Multivariate association between impulsivity measures and single-nucleotide polymorphism data was implemented using parallel independent component analysis (Para-ICA). Pathways associated with multiple genes in components that correlated significantly with impulsivity phenotypes were then identified using a pathway enrichment analysis. Para-ICA revealed two significantly correlated genotype–phenotype component pairs. One impulsivity component included the reward responsiveness subscale and behavioral inhibition scale of the Behavioral-Inhibition System/Behavioral-Activation System scale, and the second impulsivity component included the non-planning subscale of the Barratt Impulsiveness Scale and the Experiential Discounting Task. Pathway analysis identified processes related to neurogenesis, nervous system signal generation/amplification, neurotransmission and immune response. We identified various genes and gene regulatory pathways associated with empirically derived impulsivity components. Our study suggests that gene networks implicated previously in brain development, neurotransmission and immune response are related to impulsive tendencies and behaviors. PMID:25268255

Patients' understanding of and responses to multiplex genetic susceptibility test results.

PubMed

Kaphingst, Kimberly A; McBride, Colleen M; Wade, Christopher; Alford, Sharon Hensley; Reid, Robert; Larson, Eric; Baxevanis, Andreas D; Brody, Lawrence C

2012-07-01

Examination of patients' responses to direct-to-consumer genetic susceptibility tests is needed to inform clinical practice. This study examined patients' recall and interpretation of, and responses to, genetic susceptibility test results provided directly by mail. This observational study had three prospective assessments (before testing, 10 days after receiving results, and 3 months later). Participants were 199 patients aged 25-40 years who received free genetic susceptibility testing for eight common health conditions. More than 80% of the patients correctly recalled their results for the eight health conditions. Patients were unlikely to interpret genetic results as deterministic of health outcomes (mean = 6.0, s.d. = 0.8 on a scale of 1-7, 1 indicating strongly deterministic). In multivariate analysis, patients with the least deterministic interpretations were white (P = 0.0098), more educated (P = 0.0093), and least confused by results (P = 0.001). Only 1% talked about their results with a provider. Findings suggest that most patients will correctly recall their results and will not interpret genetics as the sole cause of diseases. The subset of those confused by results could benefit from consultation with a health-care provider, which could emphasize that health habits currently are the best predictors of risk. Providers could leverage patients' interest in genetic tests to encourage behavior changes to reduce disease risk.

Multivariate analysis in a genetic divergence study of Psidium guajava.

PubMed

Nogueira, A M; Ferreira, M F S; Guilhen, J H S; Ferreira, A

2014-12-18

The family Myrtaceae is widespread in the Atlantic Forest and is well-represented in the Espírito Santo State in Brazil. In the genus Psidium of this family, guava (Psidium guajava L.) is the most economically important species. Guava is widely cultivated in tropical and subtropical countries; however, the widespread cultivation of only a small number of guava tree cultivars may cause the genetic vulnerability of this crop, making the search for promising genotypes in natural populations important for breeding programs and conservation. In this study, the genetic diversity of 66 guava trees sampled in the southern region of Espírito Santo and in Caparaó, MG, Brazil were evaluated. A total of 28 morphological descriptors (11 quantitative and 17 multicategorical) and 18 microsatellite markers were used. Principal component, discriminant and cluster analyses, descriptive analyses, and genetic diversity analyses using simple sequence repeats were performed. Discrimination of accessions using molecular markers resulted in clustering of genotypes of the same origin, which was not observed using morphological data. Genetic diversity was detected between and within the localities evaluated, regardless of the methodology used. Genetic differentiation among the populations using morphological and molecular data indicated the importance of the study area for species conservation, genetic erosion estimation, and exploitation in breeding programs.

Shared additive genetic influences on DSM-IV criteria for alcohol dependence in subjects of European ancestry.

PubMed

Palmer, Rohan H C; McGeary, John E; Heath, Andrew C; Keller, Matthew C; Brick, Leslie A; Knopik, Valerie S

2015-12-01

Genetic studies of alcohol dependence (AD) have identified several candidate loci and genes, but most observed effects are small and difficult to reproduce. A plausible explanation for inconsistent findings may be a violation of the assumption that genetic factors contributing to each of the seven DSM-IV criteria point to a single underlying dimension of risk. Given that recent twin studies suggest that the genetic architecture of AD is complex and probably involves multiple discrete genetic factors, the current study employed common single nucleotide polymorphisms in two multivariate genetic models to examine the assumption that the genetic risk underlying DSM-IV AD is unitary. AD symptoms and genome-wide single nucleotide polymorphism (SNP) data from 2596 individuals of European descent from the Study of Addiction: Genetics and Environment were analyzed using genomic-relatedness-matrix restricted maximum likelihood. DSM-IV AD symptom covariance was described using two multivariate genetic factor models. Common SNPs explained 30% (standard error=0.136, P=0.012) of the variance in AD diagnosis. Additive genetic effects varied across AD symptoms. The common pathway model approach suggested that symptoms could be described by a single latent variable that had a SNP heritability of 31% (0.130, P=0.008). Similarly, the exploratory genetic factor model approach suggested that the genetic variance/covariance across symptoms could be represented by a single genetic factor that accounted for at least 60% of the genetic variance in any one symptom. Additive genetic effects on DSM-IV alcohol dependence criteria overlap. The assumption of common genetic effects across alcohol dependence symptoms appears to be a valid assumption. © 2015 Society for the Study of Addiction.

The Genetic and Environmental Etiology of the Association between Vocabulary and Syntax in First Grade

ERIC Educational Resources Information Center

Mimeau, Catherine; Dionne, Ginette; Feng, Bei; Brendgen, Mara; Vitaro, Frank; Tremblay, Richard E.; Boivin, Michel

2018-01-01

This twin study examined the genetic and environmental etiology of vocabulary, syntax, and their association in first graders. French-speaking same-sex twins (n = 555) completed two vocabulary tests, and two scores of syntax were calculated from their spontaneous speech at 7 years of age. Multivariate latent factor genetic analyses showed that…

Particle analysis using laser ablation mass spectroscopy

DOEpatents

Parker, Eric P.; Rosenthal, Stephen E.; Trahan, Michael W.; Wagner, John S.

2003-09-09

The present invention provides a method of quickly identifying bioaerosols by class, even if the subject bioaerosol has not been previously encountered. The method begins by collecting laser ablation mass spectra from known particles. The spectra are correlated with the known particles, including the species of particle and the classification (e.g., bacteria). The spectra can then be used to train a neural network, for example using genetic algorithm-based training, to recognize each spectra and to recognize characteristics of the classifications. The spectra can also be used in a multivariate patch algorithm. Laser ablation mass specta from unknown particles can be presented as inputs to the trained neural net for identification as to classification. The description below first describes suitable intelligent algorithms and multivariate patch algorithms, then presents an example of the present invention including results.

A Multivariate Genome-Wide Association Analysis of 10 LDL Subfractions, and Their Response to Statin Treatment, in 1868 Caucasians

PubMed Central

Shim, Heejung; Chasman, Daniel I.; Smith, Joshua D.; Mora, Samia; Ridker, Paul M.; Nickerson, Deborah A.; Krauss, Ronald M.; Stephens, Matthew

2015-01-01

We conducted a genome-wide association analysis of 7 subfractions of low density lipoproteins (LDLs) and 3 subfractions of intermediate density lipoproteins (IDLs) measured by gradient gel electrophoresis, and their response to statin treatment, in 1868 individuals of European ancestry from the Pharmacogenomics and Risk of Cardiovascular Disease study. Our analyses identified four previously-implicated loci (SORT1, APOE, LPA, and CETP) as containing variants that are very strongly associated with lipoprotein subfractions (log10Bayes Factor > 15). Subsequent conditional analyses suggest that three of these (APOE, LPA and CETP) likely harbor multiple independently associated SNPs. Further, while different variants typically showed different characteristic patterns of association with combinations of subfractions, the two SNPs in CETP show strikingly similar patterns - both in our original data and in a replication cohort - consistent with a common underlying molecular mechanism. Notably, the CETP variants are very strongly associated with LDL subfractions, despite showing no association with total LDLs in our study, illustrating the potential value of the more detailed phenotypic measurements. In contrast with these strong subfraction associations, genetic association analysis of subfraction response to statins showed much weaker signals (none exceeding log10Bayes Factor of 6). However, two SNPs (in APOE and LPA) previously-reported to be associated with LDL statin response do show some modest evidence for association in our data, and the subfraction response proles at the LPA SNP are consistent with the LPA association, with response likely being due primarily to resistance of Lp(a) particles to statin therapy. An additional important feature of our analysis is that, unlike most previous analyses of multiple related phenotypes, we analyzed the subfractions jointly, rather than one at a time. Comparisons of our multivariate analyses with standard univariate analyses demonstrate that multivariate analyses can substantially increase power to detect associations. Software implementing our multivariate analysis methods is available at http://stephenslab.uchicago.edu/software.html. PMID:25898129

Biometrics from the carbon isotope ratio analysis of amino acids in human hair.

PubMed

Jackson, Glen P; An, Yan; Konstantynova, Kateryna I; Rashaid, Ayat H B

2015-01-01

This study compares and contrasts the ability to classify individuals into different grouping factors through either bulk isotope ratio analysis or amino-acid-specific isotope ratio analysis of human hair. Using LC-IRMS, we measured the isotope ratios of 14 amino acids in hair proteins independently, and leucine/isoleucine as a co-eluting pair, to provide 15 variables for classification. Multivariate analysis confirmed that the essential amino acids and non-essential amino acids were mostly independent variables in the classification rules, thereby enabling the separation of dietary factors of isotope intake from intrinsic or phenotypic factors of isotope fractionation. Multivariate analysis revealed at least two potential sources of non-dietary factors influencing the carbon isotope ratio values of the amino acids in human hair: body mass index (BMI) and age. These results provide evidence that compound-specific isotope ratio analysis has the potential to go beyond region-of-origin or geospatial movements of individuals-obtainable through bulk isotope measurements-to the provision of physical and characteristic traits about the individuals, such as age and BMI. Further development and refinement, for example to genetic, metabolic, disease and hormonal factors could ultimately be of great assistance in forensic and clinical casework. Copyright © 2014 Forensic Science Society. Published by Elsevier Ireland Ltd. All rights reserved.

The relationship of quantitative nuclear morphology to molecular genetic alterations in the adenoma-carcinoma sequence of the large bowel.

PubMed Central

Mulder, J. W.; Offerhaus, G. J.; de Feyter, E. P.; Floyd, J. J.; Kern, S. E.; Vogelstein, B.; Hamilton, S. R.

1992-01-01

The relationship of abnormal nuclear morphology to molecular genetic alterations that are important in colorectal tumorigenesis is unknown. Therefore, Feulgen-stained isolated nuclei from 22 adenomas and 42 carcinomas that had been analyzed for ras gene mutations and allelic deletions on chromosomes 5q, 18q, and 17p were characterized by computerized image analysis. Both nuclear area and the nuclear shape factor representing irregularity correlated with adenoma-carcinoma progression (r = 0.57 and r = 0.52, P < 0.0001), whereas standard nuclear texture, a parameter of chromatin homogeneity, was inversely correlated with progression (r = -0.80, P < 0.0001). The nuclear parameters were strongly interrelated (P < 0.0005). In multivariate analysis, the nuclear parameters were predominantly associated with adenoma-carcinoma progression (P < or = 0.0001) and were not influenced significantly by the individual molecular genetic alterations. Nuclear texture, however, was inversely correlated with fractional allelic loss, a global measure of genetic changes, in carcinomas (r = -0.39, P = 0.011). The findings indicate that nuclear morphology in colorectal neoplasms is strongly related to tumor progression. Nuclear morphology and biologic behavior appear to be influenced by accumulated alterations in cancer-associated genes. Images Figure 1 PMID:1357973

Gene‐set and multivariate genome‐wide association analysis of oppositional defiant behavior subtypes in attention‐deficit/hyperactivity disorder

PubMed Central

van Donkelaar, Marjolein M. J.; Poelmans, Geert; Buitelaar, Jan K.; Sonuga‐Barke, Edmund J. S.; Stringaris, Argyris; consortium, IMAGE; Faraone, Stephen V.; Franke, Barbara; Steinhausen, Hans‐Christoph; van Hulzen, Kimm J. E.

2015-01-01

Oppositional defiant disorder (ODD) is a frequent psychiatric disorder seen in children and adolescents with attention‐deficit‐hyperactivity disorder (ADHD). ODD is also a common antecedent to both affective disorders and aggressive behaviors. Although the heritability of ODD has been estimated to be around 0.60, there has been little research into the molecular genetics of ODD. The present study examined the association of irritable and defiant/vindictive dimensions and categorical subtypes of ODD (based on latent class analyses) with previously described specific polymorphisms (DRD4 exon3 VNTR, 5‐HTTLPR, and seven OXTR SNPs) as well as with dopamine, serotonin, and oxytocin genes and pathways in a clinical sample of children and adolescents with ADHD. In addition, we performed a multivariate genome‐wide association study (GWAS) of the aforementioned ODD dimensions and subtypes. Apart from adjusting the analyses for age and sex, we controlled for “parental ability to cope with disruptive behavior.” None of the hypothesis‐driven analyses revealed a significant association with ODD dimensions and subtypes. Inadequate parenting behavior was significantly associated with all ODD dimensions and subtypes, most strongly with defiant/vindictive behaviors. In addition, the GWAS did not result in genome‐wide significant findings but bioinformatics and literature analyses revealed that the proteins encoded by 28 of the 53 top‐ranked genes functionally interact in a molecular landscape centered around Beta‐catenin signaling and involved in the regulation of neurite outgrowth. Our findings provide new insights into the molecular basis of ODD and inform future genetic studies of oppositional behavior. © 2015 The Authors. American Journal of Medical Genetics Part B: Neuropsychiatric Genetics Published by Wiley Periodicals, Inc. PMID:26184070

Genetic differentiation in life history traits and thermal stress performance across a heterogeneous dune landscape in Arabidopsis lyrata.

PubMed

Wos, Guillaume; Willi, Yvonne

2018-05-26

Over very short spatial scales, the habitat of a species can differ in multiple abiotic and biotic factors. These factors may impose natural selection on several traits and can cause genetic differentiation within a population. We studied multivariate genetic differentiation in a plant species of a sand dune landscape by linking environmental variation with differences in genotypic trait values and gene expression levels to find traits and candidate genes of microgeographical adaptation. Maternal seed families of Arabidopsis lyrata were collected in Saugatuck Dunes State Park, Michigan, USA, and environmental parameters were recorded at each collection site. Offspring plants were raised in climate chambers and exposed to one of three temperature treatments: regular occurrence of frost, heat, or constant control conditions. Several traits were assessed: plant growth, time to flowering, and frost and heat resistance. The strongest trait-environment association was between a fast switch to sexual reproduction and weaker growth under frost, and growing in the open, away from trees. The second strongest association was between the trait combination of small plant size and early flowering under control conditions combined with large size under frost, and the combination of environmental conditions of growing close to trees, at low vegetation cover, on dune bottoms. Gene expression analysis by RNA-seq revealed candidate genes involved in multivariate trait differentiation. The results support the hypothesis that in natural populations, many environmental factors impose selection, and that they affect multiple traits, with the relative direction of trait change being complex. The results highlight that heterogeneity in the selection environment over small spatial scales is a main driver of the maintenance of adaptive genetic variation within populations.

Accuracies of univariate and multivariate genomic prediction models in African cassava.

PubMed

Okeke, Uche Godfrey; Akdemir, Deniz; Rabbi, Ismail; Kulakow, Peter; Jannink, Jean-Luc

2017-12-04

Genomic selection (GS) promises to accelerate genetic gain in plant breeding programs especially for crop species such as cassava that have long breeding cycles. Practically, to implement GS in cassava breeding, it is necessary to evaluate different GS models and to develop suitable models for an optimized breeding pipeline. In this paper, we compared (1) prediction accuracies from a single-trait (uT) and a multi-trait (MT) mixed model for a single-environment genetic evaluation (Scenario 1), and (2) accuracies from a compound symmetric multi-environment model (uE) parameterized as a univariate multi-kernel model to a multivariate (ME) multi-environment mixed model that accounts for genotype-by-environment interaction for multi-environment genetic evaluation (Scenario 2). For these analyses, we used 16 years of public cassava breeding data for six target cassava traits and a fivefold cross-validation scheme with 10-repeat cycles to assess model prediction accuracies. In Scenario 1, the MT models had higher prediction accuracies than the uT models for all traits and locations analyzed, which amounted to on average a 40% improved prediction accuracy. For Scenario 2, we observed that the ME model had on average (across all locations and traits) a 12% improved prediction accuracy compared to the uE model. We recommend the use of multivariate mixed models (MT and ME) for cassava genetic evaluation. These models may be useful for other plant species.

A methodology for multivariate phenotype-based genome-wide association studies to mine pleiotropic genes.

PubMed

Park, Sung Hee; Lee, Ji Young; Kim, Sangsoo

2011-01-01

Current Genome-Wide Association Studies (GWAS) are performed in a single trait framework without considering genetic correlations between important disease traits. Hence, the GWAS have limitations in discovering genetic risk factors affecting pleiotropic effects. This work reports a novel data mining approach to discover patterns of multiple phenotypic associations over 52 anthropometric and biochemical traits in KARE and a new analytical scheme for GWAS of multivariate phenotypes defined by the discovered patterns. This methodology applied to the GWAS for multivariate phenotype highLDLhighTG derived from the predicted patterns of the phenotypic associations. The patterns of the phenotypic associations were informative to draw relations between plasma lipid levels with bone mineral density and a cluster of common traits (Obesity, hypertension, insulin resistance) related to Metabolic Syndrome (MS). A total of 15 SNPs in six genes (PAK7, C20orf103, NRIP1, BCL2, TRPM3, and NAV1) were identified for significant associations with highLDLhighTG. Noteworthy findings were that the significant associations included a mis-sense mutation (PAK7:R335P), a frame shift mutation (C20orf103) and SNPs in splicing sites (TRPM3). The six genes corresponded to rat and mouse quantitative trait loci (QTLs) that had shown associations with the common traits such as the well characterized MS and even tumor susceptibility. Our findings suggest that the six genes may play important roles in the pleiotropic effects on lipid metabolism and the MS, which increase the risk of Type 2 Diabetes and cardiovascular disease. The use of the multivariate phenotypes can be advantageous in identifying genetic risk factors, accounting for the pleiotropic effects when the multivariate phenotypes have a common etiological pathway.

Probability of Positive Genetic Testing Results in Patients with Family History of Primary Hyperparathyroidism.

PubMed

El Lakis, Mustapha; Nockel, Pavel; Gaitanidis, Apostolos; Guan, Bin; Agarwal, Sunita; Welch, James; Simonds, William F; Weinstein, Lee; Marx, Stephen; Nilubol, Naris; Patel, Dhaval; Merkel, Roxanne; Tirosh, Amit; Kebebew, Electron

2018-05-01

Approximately 10% of patients with primary hyperparathyroidism (PHPT) have hereditary disease. Hereditary PHPT may be syndromic (MEN1, 2, and 4 and hyperparathyroidism-jaw tumor syndrome) or non-syndromic (familial isolated PHPT). There are limited data on the probability of testing positive for genetic mutation based on clinical presentation. The aim of this study was to determine potential associations between clinical and biochemical features and mutation in susceptibility genes for PHPT in patients with a family history of PHPT. A retrospective analysis of 657 patients who had an initial parathyroidectomy for PHPT at a tertiary referral center. Logistic regression analyses were performed in 205 patients with a family history of PHPT to identify factors associated with a positive genetic test. Of 657 patients, 205 (31.2%) had a family history of PHPT. Of those 205 patients, 123 (60%) had a germline mutation detected (91 MEN1, 14 CDC73, and 18 GCM2). In univariate analysis, younger age (45 years and younger), male sex, multigland disease, and parathyroid carcinoma were associated with positive germline mutation; biochemical cure after an initial parathyroidectomy was less frequent in patients with familial PHPT (96.2% vs 89.2%; p = 0.005). In multivariable analysis, age 45 years and younger, male sex, and multigland disease were independent factors associated with positive genetic testing. In addition to a family history of PHPT, male sex, age 45 years and younger, and presence of multigland disease, should prompt physicians to offer the opportunity for genetic counseling and testing, as it could influence the management of patients with PHPT. Published by Elsevier Inc.

Molecular genetic and morphological analyses of the African wild dog (Lycaon pictus).

PubMed

Girman, D J; Kat, P W; Mills, M G; Ginsberg, J R; Borner, M; Wilson, V; Fanshawe, J H; Fitzgibbon, C; Lau, L M; Wayne, R K

1993-01-01

African wild dog populations have declined precipitously during the last 100 years in eastern Africa. The possible causes of this decline include a reduction in prey abundance and habitat; disease; and loss of genetic variability accompanied by inbreeding depression. We examined the levels of genetic variability and distinctiveness among populations of African wild dogs using mitochondrial DNA (mtDNA) restriction site and sequence analyses and multivariate analysis of cranial and dental measurements. Our results indicate that the genetic variability of eastern African wild dog populations is comparable to that of southern Africa and similar to levels of variability found in other large canids. Southern and eastern populations of wild dogs show about 1% divergence in mtDNA sequence and form two monophyletic assemblages containing three mtDNA genotypes each. No genotypes are shared between the two regions. With one exception, all wild dogs examined from zoos had southern African genotypes. Morphological analysis supports the distinction of eastern and southern African wild dog populations, and we suggest they should be considered separate subspecies. An eastern African wild dog breeding program should be initiated to ensure preservation of the eastern African form and to slow the loss of genetic variability that, while not yet apparent, will inevitably occur if wild populations continue to decline. Finally, we examined the phylogenetic relationships of wild dogs to other wolf-like canids through analysis of 736 base pairs (bp) of cytochrome b sequence and showed wild dogs to belong to a phylogenetically distinct lineage of the wolf-like canids.

Detecting hybridization between Iranian wild wolf (Canis lupus pallipes) and free-ranging domestic dog (Canis familiaris) by analysis of microsatellite markers.

PubMed

Khosravi, Rasoul; Rezaei, Hamid Reza; Kaboli, Mohammad

2013-01-01

The genetic threat due to hybridization with free-ranging dogs is one major concern in wolf conservation. The identification of hybrids and extent of hybridization is important in the conservation and management of wolf populations. Genetic variation was analyzed at 15 unlinked loci in 28 dogs, 28 wolves, four known hybrids, two black wolves, and one dog with abnormal traits in Iran. Pritchard's model, multivariate ordination by principal component analysis and neighbor joining clustering were used for population clustering and individual assignment. Analysis of genetic variation showed that genetic variability is high in both wolf and dog populations in Iran. Values of H(E) in dog and wolf samples ranged from 0.75-0.92 and 0.77-0.92, respectively. The results of AMOVA showed that the two groups of dog and wolf were significantly different (F(ST) = 0.05 and R(ST) = 0.36; P < 0.001). In each of the three methods, wolf and dog samples were separated into two distinct clusters. Two dark wolves were assigned to the wolf cluster. Also these models detected D32 (dog with abnormal traits) and some other samples, which were assigned to more than one cluster and could be a hybrid. This study is the beginning of a genetic study in wolf populations in Iran, and our results reveal that as in other countries, hybridization between wolves and dogs is sporadic in Iran and can be a threat to wolf populations if human perturbations increase.

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

Association of genetic and phenotypic variability with geography and climate in three southern California oaks.

PubMed

Riordan, Erin C; Gugger, Paul F; Ortego, Joaquín; Smith, Carrie; Gaddis, Keith; Thompson, Pam; Sork, Victoria L

2016-01-01

Geography and climate shape the distribution of organisms, their genotypes, and their phenotypes. To understand historical and future evolutionary and ecological responses to climate, we compared the association of geography and climate of three oak species (Quercus engelmannii, Quercus berberidifolia, and Quercus cornelius-mulleri) in an environmentally heterogeneous region of southern California at three organizational levels: regional species distributions, genetic variation, and phenotypic variation. We identified climatic variables influencing regional distribution patterns using species distribution models (SDMs), and then tested whether those individual variables are important in shaping genetic (microsatellite) and phenotypic (leaf morphology) variation. We estimated the relative contributions of geography and climate using multivariate redundancy analyses (RDA) with variance partitioning. The modeled distribution of each species was influenced by climate differently. Our analysis of genetic variation using RDA identified small but significant associations between genetic variation with climate and geography in Q. engelmannii and Q. cornelius-mulleri, but not in Q. berberidifolia, and climate explained more of the variation. Our analysis of phenotypic variation in Q. engelmannii indicated that climate had more impact than geography, but not in Q. berberidifolia. Throughout our analyses, we did not find a consistent pattern in effects of individual climatic variables. Our comparative analysis illustrates that climate influences tree response at all organizational levels, but the important climate factors vary depending on the level and on the species. Because of these species-specific and level-specific responses, today's sympatric species are unlikely to have similar distributions in the future. © 2016 Botanical Society of America.

Genetic parameters for different growth scales in GIFT strain of Nile tilapia (Oreochromis niloticus).

PubMed

He, J; Gao, H; Xu, P; Yang, R

2015-12-01

Body weight, length, width and depth at two growth stages were observed for a total of 5015 individuals of GIFT strain, along with a pedigree including 5588 individuals from 104 sires and 162 dams was collected. Multivariate animal models and a random regression model were used to genetically analyse absolute and relative growth scales of these growth traits. In absolute growth scale, the observed growth traits had moderate heritabilities ranging from 0.321 to 0.576, while pairwise ratios between body length, width and depth were lowly inherited and maximum heritability was only 0.146 for length/depth. All genetic correlations were above 0.5 between pairwise growth traits and genetic correlation between length/width and length/depth varied between both growth stages. Based on those estimates, selection index of multiple traits of interest can be formulated in future breeding program to improve genetically body weight and morphology of the GIFT strain. In relative growth scale, heritabilities in relative growths of body length, width and depth to body weight were 0.257, 0.412 and 0.066, respectively, while genetic correlations among these allometry scalings were above 0.8. Genetic analysis for joint allometries of body weight to body length, width and depth will contribute to genetically regulate the growth rate between body shape and body weight. © 2015 Blackwell Verlag GmbH.

Genetic history of the population of Corsica (western Mediterranean) as inferred from autosomal STR analysis.

PubMed

Tofanelli, Sergio; Taglioli, Luca; Varesi, Laurent; Paoli, Giorgio

2004-04-01

To genetically reconstruct the demographic history of the human population of Corsica (western Mediterranean), we analyzed the variability at eight autosomal STR loci (FES, VWA, CSF1PO, TH01, F13A1, TPOX, CD4, and D3S1358) in a sample of 179 native blood donors from 4 out of the 5 administrative districts. The main line of genetic discontinuity inferred from the spatial distribution of STR variability overlapped the linguistic and geographic boundaries. In the innermost areas (Corte district) several estimators had larger stochastic effects on allele frequencies. Genetic distance measures underlying different evolutionary models all pointed to a higher variability within Corsicans than within the rest of the Mediterranean reference populations. All Corsican subsamples showed the highest distance with a pooled sample from central Sardinia, thus making recent gene flow between the two neighboring islands unlikely. Hierarchical AMOVA and distance-based multivariate genetic spaces stressed the closeness of Tuscan and Corsican frequency distributions, which could reflect peopling events with different time depths. Anyway, estimated separation times well support the linguistic hypothesis that Neolithic/Chalcolithic events have been far more important than Paleolithic or historical processes in the shaping of present Corsican variability.

Quantitative genetics of age at reproduction in wild swans: Support for antagonistic pleiotropy models of senescence

PubMed Central

Charmantier, Anne; Perrins, Christopher; McCleery, Robin H.; Sheldon, Ben C.

2006-01-01

Why do individuals stop reproducing after a certain age, and how is this age determined? The antagonistic pleiotropy theory for the evolution of senescence predicts that increased early-life performance should be accompanied by earlier (or faster) senescence. Hence, an individual that has started to breed early should also lose its reproductive capacities early. We investigate here the relationship between age at first reproduction (AFR) and age at last reproduction (ALR) in a free-ranging mute swan (Cygnus olor) population monitored for 36 years. Using multivariate analyses on the longitudinal data, we show that both traits are strongly selected in opposite directions. Analysis of the phenotypic covariance between these characters shows that individuals vary in their inherent quality, such that some individuals have earlier AFR and later ALR than expected. Quantitative genetic pedigree analyses show that both traits possess additive genetic variance but also that AFR and ALR are positively genetically correlated. Hence, although both traits display heritable variation and are under opposing directional selection, their evolution is constrained by a strong evolutionary tradeoff. These results are consistent with the theory that increased early-life performance comes with faster senescence because of genetic tradeoffs. PMID:16618935

Psychosocial and Clinical Factors Associated with Family Communication of Cancer Genetic Test Results among Women Diagnosed with Breast Cancer at a Young Age.

PubMed

Elrick, Ashley; Ashida, Sato; Ivanovich, Jennifer; Lyons, Sarah; Biesecker, Barbara B; Goodman, Melody S; Kaphingst, Kimberly A

2017-02-01

Genetic test results have medical implications beyond the patient that extend to biological family members. We examined psychosocial and clinical factors associated with communication of genetic test results within families. Women (N = 1080) diagnosed with breast cancer at age 40 or younger completed an online survey; 920 women that reported prior cancer genetic testing were included in analysis. We examined the proportion of immediate family members to whom they communicated genetic test results, and built multivariable regression models to examine clinical and psychosocial variables associated with the proportion score. Participants were most likely to communicate test results to their mother (83 %) and least likely to their son (45 %). Participants who carried a BRCA mutation (OR = 1.34; 95 % CI = 1.06, 1.70), had higher interest in genomic information (OR = 1.55; 95 % CI = 1.26, 1.91) and lower genetic worry (OR = 0.91; 95 % CI = 0.86, 0.96) communicated genetic test results to a greater proportion of their immediate family members. Participants with a BRCA1/2 mutation shared their genetic test results with more male family members (OR = 1.72; 95 % CI = 1.02, 2.89). Our findings suggest that patients with high worry about genetic risks, low interest in genomic information, or receive a negative genetic test result will likely need additional support to encourage family communication.

Metabolomic Fingerprinting of Romaneschi Globe Artichokes by NMR Spectroscopy and Multivariate Data Analysis.

PubMed

de Falco, Bruna; Incerti, Guido; Pepe, Rosa; Amato, Mariana; Lanzotti, Virginia

2016-09-01

Globe artichoke (Cynara cardunculus L. var. scolymus L. Fiori) and cardoon (Cynara cardunculus L. var. altilis DC) are sources of nutraceuticals and bioactive compounds. To apply a NMR metabolomic fingerprinting approach to Cynara cardunculus heads to obtain simultaneous identification and quantitation of the major classes of organic compounds. The edible part of 14 Globe artichoke populations, belonging to the Romaneschi varietal group, were extracted to obtain apolar and polar organic extracts. The analysis was also extended to one species of cultivated cardoon for comparison. The (1) H-NMR of the extracts allowed simultaneous identification of the bioactive metabolites whose quantitation have been obtained by spectral integration followed by principal component analysis (PCA). Apolar organic extracts were mainly based on highly unsaturated long chain lipids. Polar organic extracts contained organic acids, amino acids, sugars (mainly inulin), caffeoyl derivatives (mainly cynarin), flavonoids, and terpenes. The level of nutraceuticals was found to be highest in the Italian landraces Bianco di Pertosa zia E and Natalina while cardoon showed the lowest content of all metabolites thus confirming the genetic distance between artichokes and cardoon. Metabolomic approach coupling NMR spectroscopy with multivariate data analysis allowed for a detailed metabolite profile of artichoke and cardoon varieties to be obtained. Relevant differences in the relative content of the metabolites were observed for the species analysed. This work is the first application of (1) H-NMR with multivariate statistics to provide a metabolomic fingerprinting of Cynara scolymus. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Efficient inference for genetic association studies with multiple outcomes.

PubMed

Ruffieux, Helene; Davison, Anthony C; Hager, Jorg; Irincheeva, Irina

2017-10-01

Combined inference for heterogeneous high-dimensional data is critical in modern biology, where clinical and various kinds of molecular data may be available from a single study. Classical genetic association studies regress a single clinical outcome on many genetic variants one by one, but there is an increasing demand for joint analysis of many molecular outcomes and genetic variants in order to unravel functional interactions. Unfortunately, most existing approaches to joint modeling are either too simplistic to be powerful or are impracticable for computational reasons. Inspired by Richardson and others (2010, Bayesian Statistics 9), we consider a sparse multivariate regression model that allows simultaneous selection of predictors and associated responses. As Markov chain Monte Carlo (MCMC) inference on such models can be prohibitively slow when the number of genetic variants exceeds a few thousand, we propose a variational inference approach which produces posterior information very close to that of MCMC inference, at a much reduced computational cost. Extensive numerical experiments show that our approach outperforms popular variable selection methods and tailored Bayesian procedures, dealing within hours with problems involving hundreds of thousands of genetic variants and tens to hundreds of clinical or molecular outcomes. © The Author 2017. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

A threshold model of content knowledge transfer for socioscientific argumentation

NASA Astrophysics Data System (ADS)

Sadler, Troy D.; Fowler, Samantha R.

2006-11-01

This study explores how individuals make use of scientific content knowledge for socioscientific argumentation. More specifically, this mixed-methods study investigates how learners apply genetics content knowledge as they justify claims relative to genetic engineering. Interviews are conducted with 45 participants, representing three distinct groups: high school students with variable genetics knowledge, college nonscience majors with little genetics knowledge, and college science majors with advanced genetics knowledge. During the interviews, participants advance positions concerning three scenarios dealing with gene therapy and cloning. Arguments are assessed in terms of the number of justifications offered as well as justification quality, based on a five-point rubric. Multivariate analysis of variance results indicate that college science majors outperformed the other groups in terms of justification quality and frequency. Argumentation does not differ among nonscience majors or high school students. Follow-up qualitative analyses of interview responses suggest that all three groups tend to focus on similar, sociomoral themes as they negotiate socially complex, genetic engineering issues, but that the science majors frequently reference specific science content knowledge in the justification of their claims. Results support the Threshold Model of Content Knowledge Transfer, which proposes two knowledge thresholds around which argumentation quality can reasonably be expected to increase. Research and educational implications of these findings are discussed.

The Genetic Association Between Neocortical Volume and General Cognitive Ability Is Driven by Global Surface Area Rather Than Thickness.

PubMed

Vuoksimaa, Eero; Panizzon, Matthew S; Chen, Chi-Hua; Fiecas, Mark; Eyler, Lisa T; Fennema-Notestine, Christine; Hagler, Donald J; Fischl, Bruce; Franz, Carol E; Jak, Amy; Lyons, Michael J; Neale, Michael C; Rinker, Daniel A; Thompson, Wesley K; Tsuang, Ming T; Dale, Anders M; Kremen, William S

2015-08-01

Total gray matter volume is associated with general cognitive ability (GCA), an association mediated by genetic factors. It is expectable that total neocortical volume should be similarly associated with GCA. Neocortical volume is the product of thickness and surface area, but global thickness and surface area are unrelated phenotypically and genetically in humans. The nature of the genetic association between GCA and either of these 2 cortical dimensions has not been examined. Humans possess greater cognitive capacity than other species, and surface area increases appear to be the primary driver of the increased size of the human cortex. Thus, we expected neocortical surface area to be more strongly associated with cognition than thickness. Using multivariate genetic analysis in 515 middle-aged twins, we demonstrated that both the phenotypic and genetic associations between neocortical volume and GCA are driven primarily by surface area rather than thickness. Results were generally similar for each of 4 specific cognitive abilities that comprised the GCA measure. Our results suggest that emphasis on neocortical surface area, rather than thickness, could be more fruitful for elucidating neocortical-GCA associations and identifying specific genes underlying those associations. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Genetic diversity among 16 genotypes of Coffea arabica in the Brazilian cerrado.

PubMed

Machado, C M S; Pimentel, N S; Golynsk, A; Ferreira, A; Vieira, H D; Partelli, F L

2017-09-21

For the selection of coffee plants that have favorable characteristics, it is necessary to evaluate variables related to production. Knowledge of the genetic divergence of arabica coffee is of extreme importance, as this knowledge can be associated with plant breeding programs in order to combine genetic divergence with good productive performance. The objective of this study was to evaluate the genetic divergence among 16 genotypes of Coffea arabica with the purpose of identifying the most dissimilar genotypes for the establishment of breeding programs and adaptation to the Brazilian cerrado. The genetic divergence was evaluated using multivariate procedures, the analysis of the average grouping unweighted pair group method with arithmetic mean (UPGMA) and main components in 2013 and 2014. Eight characters were evaluated in an experiment conducted in Morrinhos, Goiás. The presence of genetic divergence among the 16 C. arabica genotypes under cerrado conditions was recorded. The formation of UPGMA groups for the evaluated characteristics was pertinent due to the number of genotypes. The first three major components accounted for 81.77% of the total variance. The genotype H-419-3-4-4-13(C-241) of low size was the most divergent, followed by Catucaí 2 SL and Catiguá MG2, according to the main components.

Characterization of the Genetic Diversity of Acid Lime (Citrus aurantifolia (Christm.) Swingle) Cultivars of Eastern Nepal Using Inter-Simple Sequence Repeat Markers.

PubMed

Munankarmi, Nabin Narayan; Rana, Neesha; Bhattarai, Tribikram; Shrestha, Ram Lal; Joshi, Bal Krishna; Baral, Bikash; Shrestha, Sangita

2018-06-12

Acid lime ( Citrus aurantifolia (Christm.) Swingle) is an important fruit crop, which has high commercial value and is cultivated in 60 out of the 77 districts representing all geographical landscapes of Nepal. A lack of improved high-yielding varieties, infestation with various diseases, and pests, as well as poor management practices might have contributed to its extremely reduced productivity, which necessitates a reliable understanding of genetic diversity in existing cultivars. Hereby, we aim to characterize the genetic diversity of acid lime cultivars cultivated at three different agro-ecological gradients of eastern Nepal, employing PCR-based inter-simple sequence repeat (ISSR) markers. Altogether, 21 polymorphic ISSR markers were used to assess the genetic diversity in 60 acid lime cultivars sampled from different geographical locations. Analysis of binary data matrix was performed on the basis of bands obtained, and principal coordinate analysis and phenogram construction were performed using different computer algorithms. ISSR profiling yielded 234 amplicons, of which 87.18% were polymorphic. The number of amplified fragments ranged from 7⁻18, with amplicon size ranging from ca. 250⁻3200 bp. The Numerical Taxonomy and Multivariate System (NTSYS)-based cluster analysis using the unweighted pair group method of arithmetic averages (UPGMA) algorithm and Dice similarity coefficient separated 60 cultivars into two major and three minor clusters. Genetic diversity analysis using Popgene ver. 1.32 revealed the highest percentage of polymorphic bands (PPB), Nei’s genetic diversity (H), and Shannon’s information index (I) for the Terai zone (PPB = 69.66%; H = 0.215; I = 0.325), and the lowest of all three for the high hill zone (PPB = 55.13%; H = 0.173; I = 0.262). Thus, our data indicate that the ISSR marker has been successfully employed for evaluating the genetic diversity of Nepalese acid lime cultivars and has furnished valuable information on intrinsic genetic diversity and the relationship between cultivars that might be useful in acid lime breeding and conservation programs in Nepal.

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.

A genetic variant in SLC28A3, rs56350726, is associated with progression to castration-resistant prostate cancer in a Korean population with metastatic prostate cancer.

PubMed

Jo, Jung Ku; Oh, Jong Jin; Kim, Yong Tae; Moon, Hong Sang; Choi, Hong Yong; Park, Seunghyun; Ho, Jin-Nyoung; Yoon, Sungroh; Park, Hae Young; Byun, Seok-Soo

2017-11-14

Genetic variation which related with progression to castration-resistant prostate cancer (CRPC) during androgen-deprivation therapy (ADT) has not been elucidated in patients with metastatic prostate cancer (mPCa). Therefore, we assessed the association between genetic variats in mPCa and progession to CRPC. Analysis of exome genotypes revealed that 42 SNPs were significantly associated with mPCa. The top five polymorphisms were statistically significantly associated with metastatic disease. In addition, one of these SNPs, rs56350726, was significantly associated with time to CRPC in Kaplan-Meier analysis (Log-rank test, p = 0.011). In multivariable Cox regression, rs56350726 was strongly associated with progression to CRPC (HR = 4.172 95% CI = 1.223-14.239, p = 0.023). We assessed genetic variation among 1000 patients with PCa with or without metastasis, using 242,221 single nucleotide polymorphisms (SNPs) on the custom HumanExome BeadChip v1.0 (Illuminam Inc.). We analyzed the time to CRPC in 110 of the 1000 patients who were treated with ADT. Genetic data were analyzed using unconditional logistic regression and odds ratios calculated as estimates of relative risk of metastasis. We identified SNPs associated with metastasis and analyzed the relationship between these SNPs and time to CRPC in mPCa. Based on a genetic variation, the five top SNPs were observed to associate with mPCa. And one (SLC28A3, rs56350726) of five SNP was found the association with the progression to CRPC in patients with mPCa.

Polarization in Raman spectroscopy helps explain bone brittleness in genetic mouse models

NASA Astrophysics Data System (ADS)

Makowski, Alexander J.; Pence, Isaac J.; Uppuganti, Sasidhar; Zein-Sabatto, Ahbid; Huszagh, Meredith C.; Mahadevan-Jansen, Anita; Nyman, Jeffry S.

2014-11-01

Raman spectroscopy (RS) has been extensively used to characterize bone composition. However, the link between bone biomechanics and RS measures is not well established. Here, we leveraged the sensitivity of RS polarization to organization, thereby assessing whether RS can explain differences in bone toughness in genetic mouse models for which traditional RS peak ratios are not informative. In the selected mutant mice-activating transcription factor 4 (ATF4) or matrix metalloproteinase 9 (MMP9) knock-outs-toughness is reduced but differences in bone strength do not exist between knock-out and corresponding wild-type controls. To incorporate differences in the RS of bone occurring at peak shoulders, a multivariate approach was used. Full spectrum principal components analysis of two paired, orthogonal bone orientations (relative to laser polarization) improved genotype classification and correlation to bone toughness when compared to traditional peak ratios. When applied to femurs from wild-type mice at 8 and 20 weeks of age, the principal components of orthogonal bone orientations improved age classification but not the explanation of the maturation-related increase in strength. Overall, increasing polarization information by collecting spectra from two bone orientations improves the ability of multivariate RS to explain variance in bone toughness, likely due to polarization sensitivity to organizational changes in both mineral and collagen.

Assessing admixture by multivariate analyses of phenotypic differentiation in the Algerian goat livestock.

PubMed

Ouchene-Khelifi, Nadjet-Amina; Ouchene, Nassim; Maftah, Abderrahman; Da Silva, Anne Blondeau; Lafri, Mohamed

2015-10-01

In Algeria, goat research has been largely neglected, in spite of the economic importance of this domestic species for rural livelihoods. Goat farming is traditional and cross-breeding practices are current. The phenotypic variability of the four main native breeds (Arabia, Makatia, M'zabite and Kabyle), and of two exotic breeds (Alpine and Saanen), was investigated for the first time, using multivariate discriminant analysis. A total of 892 females were sampled in a large area, including the cradle of the native breeds, and phenotyped with 23 quantitative measures and 10 qualitative traits. Our results suggested that cross-breeding practices have ever led to critical consequences, particularly for Makatia and M'zabite. The information reported in this study has to be carefully considered in order to establish governmental plan able to prevent the genetic dilution of the Algerian goat livestock.

Classification of pumpkin seed oils according to their species and genetic variety by attenuated total reflection Fourier-transform infrared spectroscopy.

PubMed

Saucedo-Hernández, Yanelis; Lerma-García, María Jesús; Herrero-Martínez, José Manuel; Ramis-Ramos, Guillermo; Jorge-Rodríguez, Elisa; Simí-Alfonso, Ernesto F

2011-04-27

Attenuated total reflection Fourier-transform infrared spectroscopy (ATR-FTIR), followed by multivariate treatment of the spectral data, was used to classify seed oils of the genus Cucurbita (pumpkins) according to their species as C. maxima, C. pepo, and C. moschata. Also, C. moschata seed oils were classified according to their genetic variety as RG, Inivit C-88, and Inivit C-2000. Up to 23 wavelength regions were selected on the spectra, each region corresponding to a peak or shoulder. The normalized absorbance peak areas within these regions were used as predictors. Using linear discriminant analysis (LDA), an excellent resolution among all categories concerning both Cucurbita species and C. moschata varieties was achieved. The proposed method was straightforward and quick and can be easily implemented. Quality control of pumpkin seed oils is important because Cucurbita species and genetic variety are both related to the pharmaceutical properties of the oils.

Phenotypic and genetic structure of traits delineating personality disorder.

PubMed

Livesley, W J; Jang, K L; Vernon, P A

1998-10-01

The evidence suggests that personality traits are hierarchically organized with more specific or lower-order traits combining to form more generalized higher-order traits. Agreement exists across studies regarding the lower-order traits that delineate personality disorder but not the higher-order traits. This study seeks to identify the higher-order structure of personality disorder by examining the phenotypic and genetic structures underlying lower-order traits. Eighteen lower-order traits were assessed using the Dimensional Assessment of Personality Disorder-Basic Questionnaire in samples of 656 personality disordered patients, 939 general population subjects, and a volunteer sample of 686 twin pairs. Principal components analysis yielded 4 components, labeled Emotional Dysregulation, Dissocial Behavior, Inhibitedness, and Compulsivity, that were similar across the 3 samples. Multivariate genetic analyses also yielded 4 genetic and environmental factors that were remarkably similar to the phenotypic factors. Analysis of the residual heritability of the lower-order traits when the effects of the higher-order factors were removed revealed a substantial residual heritable component for 12 of the 18 traits. The results support the following conclusions. First, the stable structure of traits across clinical and nonclinical samples is consistent with dimensional representations of personality disorders. Second, the higher-order traits of personality disorder strongly resemble dimensions of normal personality. This implies that a dimensional classification should be compatible with normative personality. Third, the residual heritability of the lower-order traits suggests that the personality phenotypes are based on a large number of specific genetic components.

Generalist genes and learning disabilities: a multivariate genetic analysis of low performance in reading, mathematics, language and general cognitive ability in a sample of 8000 12-year-old twins.

PubMed

Haworth, Claire M A; Kovas, Yulia; Harlaar, Nicole; Hayiou-Thomas, Marianna E; Petrill, Stephen A; Dale, Philip S; Plomin, Robert

2009-10-01

Our previous investigation found that the same genes influence poor reading and mathematics performance in 10-year-olds. Here we assess whether this finding extends to language and general cognitive disabilities, as well as replicating the earlier finding for reading and mathematics in an older and larger sample. Using a representative sample of 4000 pairs of 12-year-old twins from the UK Twins Early Development Study, we investigated the genetic and environmental overlap between internet-based batteries of language and general cognitive ability tests in addition to tests of reading and mathematics for the bottom 15% of the distribution using DeFries-Fulker extremes analysis. We compared these results to those for the entire distribution. All four traits were highly correlated at the low extreme (average group phenotypic correlation = .58). and in the entire distribution (average phenotypic correlation = .59). Genetic correlations for the low extreme were consistently high (average = .67), and non-shared environmental correlations were modest (average = .23). These results are similar to those seen across the entire distribution (.68 and .23, respectively). The 'Generalist Genes Hypothesis' holds for language and general cognitive disabilities, as well as reading and mathematics disabilities. Genetic correlations were high, indicating a strong degree of overlap in genetic influences on these diverse traits. In contrast, non-shared environmental influences were largely specific to each trait, causing phenotypic differentiation of traits.

Testing the adaptive plasticity of Iris pumila leaf traits to natural light conditions using phenotypic selection analysis

NASA Astrophysics Data System (ADS)

Tucić, Branka; Tomić, Vladimir; Avramov, Stevan; Pemac, Danijela

1998-12-01

A multivariate selection analysis has been used to test the adaptiveness of several Iris pumila leaf traits that display plasticity to natural light conditions. Siblings of a synthetic population comprising 31 families of two populations from contrasting light habitats were grown at an open dune site and in the understory of a Pinus nigra stand in order to score variation in phenotypic expression of six leaf traits: number of senescent leaves, number of live leaves, leaf length, leaf width, leaf angle, and specific leaf area. The ambient light conditions affected the values of all traits studied except for specific leaf area. In accordance to ecophysiological expectations for an adaptive response to light, both leaf length and width were significantly greater while the angle between sequential leaves was significantly smaller in the woodland understory than at the exposed dune site. The relationship between leaf traits and vegetative fitness (total leaf area) differed across light habitats as predicted by functional hypotheses. The standardized linear selection gradient ( β') for leaf length and width were positive in sign in both environments, but their magnitude for leaf length was higher in the shade than under full sunlight. Since plasticity of leaf length in the woodland shade has been recognized as adaptive, fitness cost of producing plastic change in leaf length was assessed. In both of the available methods used, the two-step and the multivariate regression procedures, a rather high negative association between the fitness value and the plasticity of leaf length was obtained, indicating a cost of plasticity. The selection gradient for leaf angle was weak and significant only in the woodland understory. Genetic correlations between trait expressions in contrasting light environments were negative in sign and low in magnitude, implying a significant genetic variation for plasticity in these leaf traits. Furthermore, leaf length and leaf width were found to be genetically positively coupled, which indicates that there is a potential for these two traits to evolve toward their optimal phenotypic values even faster than would be expected if they were genetically independent.

Horabagrus melanosoma: a junior synonym of Horabagrus brachysoma (Teleostei: Horabagridae).

PubMed

Ali, Anvar; Katwate, Unmesh; Philip, Siby; Dhaneesh, K V; Bijukumar, A; Raghavan, Rajeev; Dahanukar, Neelesh

2014-11-06

Horabagrus melanosoma was described from West Venpala in the lower reaches of the Manimala River, in the state of Kerala, India. It was distinguished from its nearest congener, H. brachysoma based on a combination of characters including darker body colour, shorter pelvic fin and greater number of anal fin rays. Examination of the type material revealed significant morphometric and meristic discrepancies with the original description. Based on multivariate morphometric, and genetic analysis of topotypical specimens, we propose that H. melanosoma should be treated as a junior synonym of H. brachysoma.

Single nucleotide polymorphisms in the mitochondrial displacement loop and outcome of esophageal squamous cell carcinoma.

PubMed

Zhang, Ruixing; Wang, Rui; Zhang, Fengbin; Wu, Chensi; Fan, Haiyan; Li, Yan; Wang, Cuiju; Guo, Zhanjun

2010-11-26

Accumulation of single nucleotide polymorphisms (SNPs) in the displacement loop (D-loop) of mitochondrial DNA (mtDNA) has been described for different types of cancers and might be associated with cancer risk and disease outcome. We used a population-based series of esophageal squamous cell carcinoma (ESCC) patients for investigating the prediction power of SNPs in mitochondrial D-loop. The D-loop region of mtDNA was sequenced for 60 ESCC patients recorded in the Fourth Hospital of Hebei Medical University between 2003 and 2004. The 5 year survival curve were calculated with the Kaplan-Meier method and compared by the log-rank test at each SNP site, a multivariate survival analysis was also performed with the Cox proportional hazards method. The SNP sites of nucleotides 16274G/A, 16278C/T and 16399A/G were identified for prediction of post-operational survival by the log-rank test. In an overall multivariate analysis, the 16278 and 16399 alleles were identified as independent predictors of ESCC outcome. The length of survival of patients with the minor allele 16278T genotype was significantly shorter than that of patients with 16278C at the 16278 site (relative risk, 3.001; 95% CI, 1.029 - 8.756; p = 0.044). The length of survival of patients with the minor allele 16399G genotype was significantly shorter than that of patients with the more frequent allele 16399A at the 16399 site in ESCC patients (relative risk, 3.483; 95% CI, 1.068 - 11.359; p = 0.039). Genetic polymorphisms in the D-loop are independent prognostic markers for patients with ESCC. Accordingly, the analysis of genetic polymorphisms in the mitochondrial D-loop can help identify patient subgroups at high risk of a poor disease outcome.

Detection of gene-environment interactions in the presence of linkage disequilibrium and noise by using genetic risk scores with internal weights from elastic net regression.

PubMed

Hüls, Anke; Ickstadt, Katja; Schikowski, Tamara; Krämer, Ursula

2017-06-12

For the analysis of gene-environment (GxE) interactions commonly single nucleotide polymorphisms (SNPs) are used to characterize genetic susceptibility, an approach that mostly lacks power and has poor reproducibility. One promising approach to overcome this problem might be the use of weighted genetic risk scores (GRS), which are defined as weighted sums of risk alleles of gene variants. The gold-standard is to use external weights from published meta-analyses. In this study, we used internal weights from the marginal genetic effects of the SNPs estimated by a multivariate elastic net regression and thereby provided a method that can be used if there are no external weights available. We conducted a simulation study for the detection of GxE interactions and compared power and type I error of single SNPs analyses with Bonferroni correction and corresponding analysis with unweighted and our weighted GRS approach in scenarios with six risk SNPs and an increasing number of highly correlated (up to 210) and noise SNPs (up to 840). Applying weighted GRS increased the power enormously in comparison to the common single SNPs approach (e.g. 94.2% vs. 35.4%, respectively, to detect a weak interaction with an OR ≈ 1.04 for six uncorrelated risk SNPs and n = 700 with a well-controlled type I error). Furthermore, weighted GRS outperformed the unweighted GRS, in particular in the presence of SNPs without any effect on the phenotype (e.g. 90.1% vs. 43.9%, respectively, when 20 noise SNPs were added to the six risk SNPs). This outperforming of the weighted GRS was confirmed in a real data application on lung inflammation in the SALIA cohort (n = 402). However, in scenarios with a high number of noise SNPs (>200 vs. 6 risk SNPs), larger sample sizes are needed to avoid an increased type I error, whereas a high number of correlated SNPs can be handled even in small samples (e.g. n = 400). In conclusion, weighted GRS with weights from the marginal genetic effects of the SNPs estimated by a multivariate elastic net regression were shown to be a powerful tool to detect gene-environment interactions in scenarios of high Linkage disequilibrium and noise.

Radiogenomics to characterize regional genetic heterogeneity in glioblastoma.

PubMed

Hu, Leland S; Ning, Shuluo; Eschbacher, Jennifer M; Baxter, Leslie C; Gaw, Nathan; Ranjbar, Sara; Plasencia, Jonathan; Dueck, Amylou C; Peng, Sen; Smith, Kris A; Nakaji, Peter; Karis, John P; Quarles, C Chad; Wu, Teresa; Loftus, Joseph C; Jenkins, Robert B; Sicotte, Hugues; Kollmeyer, Thomas M; O'Neill, Brian P; Elmquist, William; Hoxworth, Joseph M; Frakes, David; Sarkaria, Jann; Swanson, Kristin R; Tran, Nhan L; Li, Jing; Mitchell, J Ross

2017-01-01

Glioblastoma (GBM) exhibits profound intratumoral genetic heterogeneity. Each tumor comprises multiple genetically distinct clonal populations with different therapeutic sensitivities. This has implications for targeted therapy and genetically informed paradigms. Contrast-enhanced (CE)-MRI and conventional sampling techniques have failed to resolve this heterogeneity, particularly for nonenhancing tumor populations. This study explores the feasibility of using multiparametric MRI and texture analysis to characterize regional genetic heterogeneity throughout MRI-enhancing and nonenhancing tumor segments. We collected multiple image-guided biopsies from primary GBM patients throughout regions of enhancement (ENH) and nonenhancing parenchyma (so called brain-around-tumor, [BAT]). For each biopsy, we analyzed DNA copy number variants for core GBM driver genes reported by The Cancer Genome Atlas. We co-registered biopsy locations with MRI and texture maps to correlate regional genetic status with spatially matched imaging measurements. We also built multivariate predictive decision-tree models for each GBM driver gene and validated accuracies using leave-one-out-cross-validation (LOOCV). We collected 48 biopsies (13 tumors) and identified significant imaging correlations (univariate analysis) for 6 driver genes: EGFR, PDGFRA, PTEN, CDKN2A, RB1, and TP53. Predictive model accuracies (on LOOCV) varied by driver gene of interest. Highest accuracies were observed for PDGFRA (77.1%), EGFR (75%), CDKN2A (87.5%), and RB1 (87.5%), while lowest accuracy was observed in TP53 (37.5%). Models for 4 driver genes (EGFR, RB1, CDKN2A, and PTEN) showed higher accuracy in BAT samples (n = 16) compared with those from ENH segments (n = 32). MRI and texture analysis can help characterize regional genetic heterogeneity, which offers potential diagnostic value under the paradigm of individualized oncology. © The Author(s) 2016. Published by Oxford University Press on behalf of the Society for Neuro-Oncology. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Descriptor selection for banana accessions based on univariate and multivariate analysis.

PubMed

Brandão, L P; Souza, C P F; Pereira, V M; Silva, S O; Santos-Serejo, J A; Ledo, C A S; Amorim, E P

2013-05-14

Our objective was to establish a minimum number of morphological descriptors for the characterization of banana germplasm and evaluate the efficiency of removal of redundant characters, based on univariate and multivariate statistical analyses. Phenotypic characterization was made of 77 accessions from Bahia, Brazil, using 92 descriptors. The selection of the descriptors was carried out by principal components analysis (quantitative) and by entropy (multi-category). Efficiency of elimination was analyzed by a comparative study between the clusters formed, taking into consideration all 92 descriptors and smaller groups. The selected descriptors were analyzed with the Ward-MLM procedure and a combined matrix formed by the Gower algorithm. We were able to reduce the number of descriptors used for characterizing the banana germplasm (42%). The correlation between the matrices considering the 92 descriptors and the selected ones was 0.82, showing that the reduction in the number of descriptors did not influence estimation of genetic variability between the banana accessions. We conclude that removing these descriptors caused no loss of information, considering the groups formed from pre-established criteria, including subgroup/subspecies.

Influence of shifting cultivation practices on soil-plant-beetle interactions.

PubMed

Ibrahim, Kalibulla Syed; Momin, Marcy D; Lalrotluanga, R; Rosangliana, David; Ghatak, Souvik; Zothansanga, R; Kumar, Nachimuthu Senthil; Gurusubramanian, Guruswami

2016-08-01

Shifting cultivation (jhum) is a major land use practice in Mizoram. It was considered as an eco-friendly and efficient method when the cycle duration was long (15-30 years), but it poses the problem of land degradation and threat to ecology when shortened (4-5 years) due to increased intensification of farming systems. Studying beetle community structure is very helpful in understanding how shifting cultivation affects the biodiversity features compared to natural forest system. The present study examines the beetle species diversity and estimates the effects of shifting cultivation practices on the beetle assemblages in relation to change in tree species composition and soil nutrients. Scarabaeidae and Carabidae were observed to be the dominant families in the land use systems studied. Shifting cultivation practice significantly (P < 0.05) affected the beetle and tree species diversity as well as the soil nutrients as shown by univariate (one-way analysis of variance (ANOVA), correlation and regression, diversity indices) and multivariate (cluster analysis, principal component analysis (PCA), detrended correspondence analysis (DCA), canonical variate analysis (CVA), permutational multivariate analysis of variance (PERMANOVA), permutational multivariate analysis of dispersion (PERMDISP)) statistical analyses. Besides changing the tree species composition and affecting the soil fertility, shifting cultivation provides less suitable habitat conditions for the beetle species. Bioindicator analysis categorized the beetle species into forest specialists, anthropogenic specialists (shifting cultivation habitat specialist), and habitat generalists. Molecular analysis of bioindicator beetle species was done using mitochondrial cytochrome oxidase subunit I (COI) marker to validate the beetle species and describe genetic variation among them in relation to heterogeneity, transition/transversion bias, codon usage bias, evolutionary distance, and substitution pattern. The present study revealed the fact that shifting cultivation practice significantly affects the beetle species in terms of biodiversity pattern as well as evolutionary features. Spatiotemporal assessment of soil-plant-beetle interactions in shifting cultivation system and their influence in land degradation and ecology will be helpful in making biodiversity conservation decisions in the near future.

Dissecting maize diversity in lowland South America: genetic structure and geographic distribution models.

PubMed

Bracco, Mariana; Cascales, Jimena; Hernández, Julián Cámara; Poggio, Lidia; Gottlieb, Alexandra M; Lia, Verónica V

2016-08-26

Maize landraces from South America have traditionally been assigned to two main categories: Andean and Tropical Lowland germplasm. However, the genetic structure and affiliations of the lowland gene pools have been difficult to assess due to limited sampling and the lack of comparative analysis. Here, we examined SSR and Adh2 sequence variation in a diverse sample of maize landraces from lowland middle South America, and performed a comprehensive integrative analysis of population structure and diversity including already published data of archaeological and extant specimens from the Americas. Geographic distribution models were used to explore the relationship between environmental factors and the observed genetic structure. Bayesian and multivariate analyses of population structure showed the existence of two previously overlooked lowland gene pools associated with Guaraní indigenous communities of middle South America. The singularity of this germplasm was also evidenced by the frequency distribution of microsatellite repeat motifs of the Adh2 locus and the distinct spatial pattern inferred from geographic distribution models. Our results challenge the prevailing view that lowland middle South America is just a contact zone between Andean and Tropical Lowland germplasm and highlight the occurrence of a unique, locally adapted gene pool. This information is relevant for the conservation and utilization of maize genetic resources, as well as for a better understanding of environment-genotype associations.

Testing for biases in selection on avian reproductive traits and partitioning direct and indirect selection using quantitative genetic models.

PubMed

Reed, Thomas E; Gienapp, Phillip; Visser, Marcel E

2016-10-01

Key life history traits such as breeding time and clutch size are frequently both heritable and under directional selection, yet many studies fail to document microevolutionary responses. One general explanation is that selection estimates are biased by the omission of correlated traits that have causal effects on fitness, but few valid tests of this exist. Here, we show, using a quantitative genetic framework and six decades of life-history data on two free-living populations of great tits Parus major, that selection estimates for egg-laying date and clutch size are relatively unbiased. Predicted responses to selection based on the Robertson-Price Identity were similar to those based on the multivariate breeder's equation (MVBE), indicating that unmeasured covarying traits were not missing from the analysis. Changing patterns of phenotypic selection on these traits (for laying date, linked to climate change) therefore reflect changing selection on breeding values, and genetic constraints appear not to limit their independent evolution. Quantitative genetic analysis of correlational data from pedigreed populations can be a valuable complement to experimental approaches to help identify whether apparent associations between traits and fitness are biased by missing traits, and to parse the roles of direct versus indirect selection across a range of environments. © 2016 The Author(s). Evolution © 2016 The Society for the Study of Evolution.

Discrete mixture modeling to address genetic heterogeneity in time-to-event regression

PubMed Central

Eng, Kevin H.; Hanlon, Bret M.

2014-01-01

Motivation: Time-to-event regression models are a critical tool for associating survival time outcomes with molecular data. Despite mounting evidence that genetic subgroups of the same clinical disease exist, little attention has been given to exploring how this heterogeneity affects time-to-event model building and how to accommodate it. Methods able to diagnose and model heterogeneity should be valuable additions to the biomarker discovery toolset. Results: We propose a mixture of survival functions that classifies subjects with similar relationships to a time-to-event response. This model incorporates multivariate regression and model selection and can be fit with an expectation maximization algorithm, we call Cox-assisted clustering. We illustrate a likely manifestation of genetic heterogeneity and demonstrate how it may affect survival models with little warning. An application to gene expression in ovarian cancer DNA repair pathways illustrates how the model may be used to learn new genetic subsets for risk stratification. We explore the implications of this model for censored observations and the effect on genomic predictors and diagnostic analysis. Availability and implementation: R implementation of CAC using standard packages is available at https://gist.github.com/programeng/8620b85146b14b6edf8f Data used in the analysis are publicly available. Contact: kevin.eng@roswellpark.org Supplementary information: Supplementary data are available at Bioinformatics online. PMID:24532723

Kinship and Leprosy in the Contacts of Leprosy Patients: Cohort at the Souza Araújo Outpatient Clinic, Rio de Janeiro, RJ, 1987–2010

PubMed Central

dos Santos, Daiane Santos; Duppre, Nadia Cristina; Nery, José Augusto da Costa; Sarno, Euzenir Nunes; Hacker, Mariana Andréa

2013-01-01

A broad variety of factors have been associated with leprosy among contacts, including socioeconomic, epidemiological, and genetic characteristics. Data from 7,174 contacts of leprosy patients from a leprosy outpatient clinic in Rio de Janeiro, Brazil, 1987–2010, were analyzed to investigate the effects of kinship, individual, and contextual factors on leprosy. Multivariate analyses were performed using a robust estimation method. In the prevalence analysis, close kinship (sibling OR = 2.75, offspring OR = 2.00, and other relatives OR = 1.70), socioeconomic factors, and the duration of exposure to the bacillus were associated to leprosy. In the incidence analysis, significant risks were found for all categories of kinship (parents RR = 10.93, spouse, boyfriend/girlfriend, and bride/groom RR = 7.53, sibling RR = 7.03, offspring RR = 5.34, and other relatives RR = 3.71). Once the treatment of the index case was initiated, other factors lost their significance, and the index case bacteriological index and BCG (Bacillus Calmette-Guérin vaccine) protection had a greater impact. Our findings suggested that both genetic susceptibility and physical exposure play an important role in the epidemiology of leprosy, but it was not possible establishing the role of genetic factor. Analyses of other factors related to the genotype of individuals, such as genetic polymorphisms, are needed. PMID:23690793

Mapping eQTL Networks with Mixed Graphical Markov Models

PubMed Central

Tur, Inma; Roverato, Alberto; Castelo, Robert

2014-01-01

Expression quantitative trait loci (eQTL) mapping constitutes a challenging problem due to, among other reasons, the high-dimensional multivariate nature of gene-expression traits. Next to the expression heterogeneity produced by confounding factors and other sources of unwanted variation, indirect effects spread throughout genes as a result of genetic, molecular, and environmental perturbations. From a multivariate perspective one would like to adjust for the effect of all of these factors to end up with a network of direct associations connecting the path from genotype to phenotype. In this article we approach this challenge with mixed graphical Markov models, higher-order conditional independences, and q-order correlation graphs. These models show that additive genetic effects propagate through the network as function of gene–gene correlations. Our estimation of the eQTL network underlying a well-studied yeast data set leads to a sparse structure with more direct genetic and regulatory associations that enable a straightforward comparison of the genetic control of gene expression across chromosomes. Interestingly, it also reveals that eQTLs explain most of the expression variability of network hub genes. PMID:25271303

Individual and family characteristics associated with BRCA1/2 genetic testing in high-risk families.

PubMed

Katapodi, Maria C; Northouse, Laurel L; Milliron, Kara J; Liu, Guipeng; Merajver, Sofia D

2013-06-01

Little is known about family members' interrelated decisions to seek genetic testing for breast cancer susceptibility. The specific aims of this cross-sectional, descriptive, cohort study were (i) to examine whether individual and family characteristics have a direct effect on women's decisions to use genetic testing for hereditary susceptibility to breast cancer and (ii) to explore whether family characteristics moderate the relationships between individual characteristics and the decision to use genetic testing. Participants were women (>18 years old) who (i) received genetic testing for hereditary breast cancer and who agreed to invite one of their female relatives into the study and (ii) female relatives who had NOT obtained genetic testing and were identified by pedigree analysis as having >10% chances of hereditary susceptibility to breast cancer. The final sample consisted of 168 English-speaking, family dyads who completed self-administered, mailed surveys with validated instruments. Multivariate conditional logistic regression analyses showed that the proposed model explained 62% of the variance in genetic testing. The factors most significantly associated with genetic testing were having a personal history of cancer; perceiving genetic testing to have more benefits than barriers; having greater family hardiness; and perceiving fewer negative consequences associated with a breast cancer diagnosis. No significant interaction effects were observed. Findings suggest that both individual and family characteristics are associated with the decision to obtain genetic testing for hereditary breast cancer; hence, there is a need for interventions that foster a supportive family environment for patients and their high-risk relatives. Copyright © 2012 John Wiley & Sons, Ltd.

Genetic factors contribute to bleeding after cardiac surgery.

PubMed

Welsby, I J; Podgoreanu, M V; Phillips-Bute, B; Mathew, J P; Smith, P K; Newman, M F; Schwinn, D A; Stafford-Smith, M

2005-06-01

Postoperative bleeding remains a common, serious problem for cardiac surgery patients, with striking inter-patient variability poorly explained by clinical, procedural, and biological markers. We tested the hypothesis that genetic polymorphisms of coagulation proteins and platelet glycoproteins are associated with bleeding after cardiac surgery. Seven hundred and eighty patients undergoing aortocoronary surgery with cardiopulmonary bypass were studied. Clinical covariates previously associated with bleeding were recorded and DNA isolated from preoperative blood. Matrix Assisted Laser Desorption/Ionization, Time-Of-Flight (MALDI-TOF) mass spectroscopy or polymerase chain reaction were used for genotype analysis. Multivariable linear regression modeling, including all genetic main effects and two-way gene-gene interactions, related clinical and genetic predictors to bleeding from the thorax and mediastinum. Nineteen candidate polymorphisms were assessed; seven [GPIaIIa-52C>T and 807C>T, GPIb alpha 524C>T, tissue factor-603A>G, prothrombin 20210G>A, tissue factor pathway inhibitor-399C>T, and angiotensin converting enzyme (ACE) deletion/insertion] demonstrate significant association with bleeding (P < 0.01). Adding genetic to clinical predictors results improves the model, doubling overall ability to predict bleeding (P < 0.01). We identified seven genetic polymorphisms associated with bleeding after cardiac surgery. Genetic factors appear primarily independent of, and explain at least as much variation in bleeding as clinical covariates; combining genetic and clinical factors double our ability to predict bleeding after cardiac surgery. Accounting for genotype may be necessary when stratifying risk of bleeding after cardiac surgery.

Distribution, genetic and cardiovascular determinants of FVIII:c - Data from the population-based Gutenberg Health Study.

PubMed

Hermanns, M Iris; Grossmann, Vera; Spronk, Henri M H; Schulz, Andreas; Jünger, Claus; Laubert-Reh, Dagmar; Mazur, Johanna; Gori, Tommaso; Zeller, Tanja; Pfeiffer, Norbert; Beutel, Manfred; Blankenberg, Stefan; Münzel, Thomas; Lackner, Karl J; Ten Cate-Hoek, Arina J; Ten Cate, Hugo; Wild, Philipp S

2015-01-01

Elevated levels of c are associated with risk for both venous and arterial thromboembolism. However, no population-based study on the sex-specific distribution and reference ranges of plasma c and its cardiovascular determinants is available. c was analyzed in a randomly selected sample of 2533 males and 2440 females from the Gutenberg Health Study in Germany. Multivariable regression analyses for c were performed under adjustment for genetic determinants, cardiovascular risk factors and cardiovascular disease. Females (126.6% (95% CI: 125.2/128)) showed higher c levels than males (121.2% (119.8/122.7)). c levels increased with age in both sexes (ß per decade: 5.67% (4.22/7.13) male, 6.15% (4.72/7.57) female; p<0.001). Sex-specific reference limits and categories indicating the grade of deviation from the reference were calculated, and nomograms for c were created. c was approximately 25% higher in individuals with non-O blood type. Adjusted for sex and age, ABO-blood group accounted for 18.3% of c variation. In multivariable analysis, c was notably positively associated with diabetes mellitus, obesity, hypertension and dyslipidemia and negatively with current smoking. In a fully adjusted multivariable model, the strongest associations observed were of elevated c with diabetes and peripheral artery disease in both sexes and with obesity in males. Effects of SNPs in the vWF, STAB2 and SCARA5 gene were stronger in females than in males. The use of nomograms for valuation of c might be useful to identify high-risk cohorts for thromboembolism. Additionally, the prospective evaluation of c as a risk predictor becomes feasible. Copyright © 2015. Published by Elsevier Ireland Ltd.

Transmission clustering among newly diagnosed HIV patients in Chicago, 2008 to 2011: using phylogenetics to expand knowledge of regional HIV transmission patterns

PubMed Central

Lubelchek, Ronald J.; Hoehnen, Sarah C.; Hotton, Anna L.; Kincaid, Stacey L.; Barker, David E.; French, Audrey L.

2014-01-01

Introduction HIV transmission cluster analyses can inform HIV prevention efforts. We describe the first such assessment for transmission clustering among HIV patients in Chicago. Methods We performed transmission cluster analyses using HIV pol sequences from newly diagnosed patients presenting to Chicago’s largest HIV clinic between 2008 and 2011. We compared sequences via progressive pairwise alignment, using neighbor joining to construct an un-rooted phylogenetic tree. We defined clusters as >2 sequences among which each sequence had at least one partner within a genetic distance of ≤ 1.5%. We used multivariable regression to examine factors associated with clustering and used geospatial analysis to assess geographic proximity of phylogenetically clustered patients. Results We compared sequences from 920 patients; median age 35 years; 75% male; 67% Black, 23% Hispanic; 8% had a Rapid Plasma Reagin (RPR) titer ≥ 1:16 concurrent with their HIV diagnosis. We had HIV transmission risk data for 54%; 43% identified as men who have sex with men (MSM). Phylogenetic analysis demonstrated 123 patients (13%) grouped into 26 clusters, the largest having 20 members. In multivariable regression, age < 25, Black race, MSM status, male gender, higher HIV viral load, and RPR ≥ 1:16 associated with clustering. We did not observe geographic grouping of genetically clustered patients. Discussion Our results demonstrate high rates of HIV transmission clustering, without local geographic foci, among young Black MSM in Chicago. Applied prospectively, phylogenetic analyses could guide prevention efforts and help break the cycle of transmission. PMID:25321182

Genetic variants in PNPLA3 and risk of non-alcoholic fatty liver disease in a Han Chinese population.

PubMed

Peng, Xian-E; Wu, Yun-Li; Lin, Shao-Wei; Lu, Qing-Qing; Hu, Zhi-Jian; Lin, Xu

2012-01-01

We investigated the possible association between genetic variants in the Patatin like phospholipase-3 (PNPLA3) gene and nonalcoholic fatty liver disease (NAFLD) in a Han Chinese population. We evaluated twelve tagging single-nucleotide polymorphisms (tSNPs) of the PNPLA3 gene in a frequency matched case-control study from Fuzhou city of China (553 cases, 553 controls). In the multivariate logistic regression analysis, the rs738409 GG or GC, and rs139051 TT genotypes were found to be associated with increased risk of NAFLD, and a significant trend of increased risk with increasing numbers of risk genotype was observed in the cumulative effect analysis of these single nucleotide polymorphisms. Furthermore, haplotype association analysis showed that, compared with the most common haplotype, the CAAGAATGCGTG and CGAAGGTGTCCG haplotypes conferred a statistically significant increased risk for NAFLD, while the CGGGAACCCGCG haplotype decreased the risk of NAFLD. Moreover, rs738409 C>G appeared to have a multiplicative joint effect with tea drinking (P<0.005) and an additive joint effect with obesity (Interaction contrast ratio (ICR) = 2.31, 95% CI: 0.7-8.86), hypertriglyceridemia (ICR = 3.07, 95% CI: 0.98-5.09) or hypertension (ICR = 1.74, 95% CI: 0.52-3.12). Our data suggests that PNPLA3 genetic polymorphisms might influence the susceptibility to NAFLD development independently or jointly in Han Chinese.

Estimating Information Processing in a Memory System: The Utility of Meta-analytic Methods for Genetics.

PubMed

Yildizoglu, Tugce; Weislogel, Jan-Marek; Mohammad, Farhan; Chan, Edwin S-Y; Assam, Pryseley N; Claridge-Chang, Adam

2015-12-01

Genetic studies in Drosophila reveal that olfactory memory relies on a brain structure called the mushroom body. The mainstream view is that each of the three lobes of the mushroom body play specialized roles in short-term aversive olfactory memory, but a number of studies have made divergent conclusions based on their varying experimental findings. Like many fields, neurogenetics uses null hypothesis significance testing for data analysis. Critics of significance testing claim that this method promotes discrepancies by using arbitrary thresholds (α) to apply reject/accept dichotomies to continuous data, which is not reflective of the biological reality of quantitative phenotypes. We explored using estimation statistics, an alternative data analysis framework, to examine published fly short-term memory data. Systematic review was used to identify behavioral experiments examining the physiological basis of olfactory memory and meta-analytic approaches were applied to assess the role of lobular specialization. Multivariate meta-regression models revealed that short-term memory lobular specialization is not supported by the data; it identified the cellular extent of a transgenic driver as the major predictor of its effect on short-term memory. These findings demonstrate that effect sizes, meta-analysis, meta-regression, hierarchical models and estimation methods in general can be successfully harnessed to identify knowledge gaps, synthesize divergent results, accommodate heterogeneous experimental design and quantify genetic mechanisms.

Motor impulsivity during childhood and adolescence: a longitudinal biometric analysis of the go/no-go task in 9- to 18-year-old twins.

PubMed

Bezdjian, Serena; Tuvblad, Catherine; Wang, Pan; Raine, Adrian; Baker, Laura A

2014-11-01

In the present study, we investigated genetic and environmental effects on motor impulsivity from childhood to late adolescence using a longitudinal sample of twins from ages 9 to 18 years. Motor impulsivity was assessed using errors of commission (no-go errors) in a visual go/no-go task at 4 time points: ages 9-10, 11-13, 14-15, and 16-18 years. Significant genetic and nonshared environmental effects on motor impulsivity were found at each of the 4 waves of assessment with genetic factors explaining 22%-41% of the variance within each of the 4 waves. Phenotypically, children's average performance improved across age (i.e., fewer no-go errors during later assessments). Multivariate biometric analyses revealed that common genetic factors influenced 12%-40% of the variance in motor impulsivity across development, whereas nonshared environmental factors common to all time points contributed to 2%-52% of the variance. Nonshared environmental influences specific to each time point also significantly influenced motor impulsivity. Overall, results demonstrated that although genetic factors were critical to motor impulsivity across development, both common and specific nonshared environmental factors played a strong role in the development of motor impulsivity across age. (PsycINFO Database Record (c) 2014 APA, all rights reserved).

SNP by SNP by environment interaction network of alcoholism.

PubMed

Zollanvari, Amin; Alterovitz, Gil

2017-03-14

Alcoholism has a strong genetic component. Twin studies have demonstrated the heritability of a large proportion of phenotypic variance of alcoholism ranging from 50-80%. The search for genetic variants associated with this complex behavior has epitomized sequence-based studies for nearly a decade. The limited success of genome-wide association studies (GWAS), possibly precipitated by the polygenic nature of complex traits and behaviors, however, has demonstrated the need for novel, multivariate models capable of quantitatively capturing interactions between a host of genetic variants and their association with non-genetic factors. In this regard, capturing the network of SNP by SNP or SNP by environment interactions has recently gained much interest. Here, we assessed 3,776 individuals to construct a network capable of detecting and quantifying the interactions within and between plausible genetic and environmental factors of alcoholism. In this regard, we propose the use of first-order dependence tree of maximum weight as a potential statistical learning technique to delineate the pattern of dependencies underpinning such a complex trait. Using a predictive based analysis, we further rank the genes, demographic factors, biological pathways, and the interactions represented by our SNP [Formula: see text]SNP[Formula: see text]E network. The proposed framework is quite general and can be potentially applied to the study of other complex traits.

Characterization of clinical and genetic risk factors associated with dyslipidemia after kidney transplantation.

PubMed

Numakura, Kazuyuki; Kagaya, Hideaki; Yamamoto, Ryohei; Komine, Naoki; Saito, Mitsuru; Hiroshi, Tsuruta; Akihama, Susumu; Inoue, Takamitsu; Narita, Shintaro; Tsuchiya, Norihiko; Habuchi, Tomonori; Niioka, Takenori; Miura, Masatomo; Satoh, Shigeru

2015-01-01

We determined the prevalence of dyslipidemia in a Japanese cohort of renal allograft recipients and investigated clinical and genetic characteristics associated with having the disease. In total, 126 patients that received renal allograft transplants between February 2002 and August 2011 were studied, of which 44 recipients (34.9%) were diagnosed with dyslipidemia at 1 year after transplantation. Three clinical factors were associated with a risk of having dyslipidemia: a higher prevalence of disease observed among female than male patients (P = 0.021) and treatment with high mycophenolate mofetil (P = 0.012) and prednisolone (P = 0.023) doses per body weight at 28 days after transplantation. The genetic association between dyslipidemia and 60 previously described genetic polymorphisms in 38 putative disease-associated genes was analyzed. The frequency of dyslipidemia was significantly higher in patients with the glucocorticoid receptor (NR3C1) Bcl1 G allele than in those with the CC genotype (P = 0.001). A multivariate analysis revealed that the NR3C1 Bcl1 G allele was a significant risk factor for the prevalence of dyslipidemia (odds ratio = 4.6; 95% confidence interval = 1.8-12.2). These findings may aid in predicting a patient's risk of developing dyslipidemia.

The genetic and environmental aetiology of spatial, mathematics and general anxiety

PubMed Central

Malanchini, Margherita; Rimfeld, Kaili; Shakeshaft, Nicholas G.; Rodic, Maja; Schofield, Kerry; Selzam, Saskia; Dale, Philip S.; Petrill, Stephen A.; Kovas, Yulia

2017-01-01

Individuals differ in their level of general anxiety as well as in their level of anxiety towards specific activities, such as mathematics and spatial tasks. Both specific anxieties correlate moderately with general anxiety, but the aetiology of their association remains unexplored. Moreover, the factor structure of spatial anxiety is to date unknown. The present study investigated the factor structure of spatial anxiety, its aetiology, and the origins of its association with general and mathematics anxiety in a sample of 1,464 19-21-year-old twin pairs from the UK representative Twins Early Development Study. Participants reported their general, mathematics and spatial anxiety as part of an online battery of tests. We found that spatial anxiety is a multifactorial construct, including two components: navigation anxiety and rotation/visualization anxiety. All anxiety measures were moderately heritable (30% to 41%), and non-shared environmental factors explained the remaining variance. Multivariate genetic analysis showed that, although some genetic and environmental factors contributed to all anxiety measures, a substantial portion of genetic and non-shared environmental influences were specific to each anxiety construct. This suggests that anxiety is a multifactorial construct phenotypically and aetiologically, highlighting the importance of studying anxiety within specific contexts. PMID:28220830

Multigenic Control of Measles Vaccine Immunity Mediated by Polymorphisms in Measles Receptor, Innate Pathway, and Cytokine Genes

PubMed Central

Kennedy, Richard B.; Ovsyannikova, Inna G.; Haralambieva, Iana H.; O’Byrne, Megan; Jacobson, Robert M.; Pankratz, V. Shane; Poland, Gregory A.

2012-01-01

Measles infection and vaccine response are complex biological processes that involve both viral and host genetic factors. We have previously investigated the influence of genetic polymorphisms on vaccine immune response, including measles vaccines, and have shown that polymorphisms in HLA, cytokine, cytokine receptor, and innate immune response genes are associated with variation in vaccine response but do not account for all of the inter-individual variance seen in vaccinated populations. In the current study we report the findings of a multigenic analysis of measles vaccine immunity, indicating a role for the measles virus receptor CD46, innate pattern-recognition receptors (DDX58, TLR2, 4, 5,7 and 8) and intracellular signaling intermediates (MAP3K7, NFKBIA), and key antiviral molecules (VISA, OAS2, MX1, PKR) as well as cytokines (IFNA1, IL4, IL6, IL8, IL12B) and cytokine receptor genes (IL2RB, IL6R, IL8RA) in the genetic control of both humoral and cellular immune responses. This multivariate approach provided additional insights into the genetic control of measles vaccine responses over and above the information gained by our previous univariate SNP association analyses. PMID:22265947

Genetic divergence of the common bean (Phaseolus vulgaris L.) group Carioca using morpho-agronomic traits by multivariate analysis.

PubMed

Gonçalves Ceolin, Ana Cristina; Gonçalves-Vidigal, Maria Celeste; Soares Vidigal Filho, Pedro; Vinícius Kvitschal, Marcus; Gonela, Adriana; Alberto Scapim, Carlos

2007-03-01

The objective of this study was to evaluate the genetic divergence among the common bean group Carioca by the Tocher method (based on Mahalanobis distance) and graphic dispersion of canonic variables, aiming to identify populations with wide genetic variability. Eighteen genotypes were evaluated in four seasons using a randomized block design with four replications. The mean weight of 100 seeds, in three experiments, and the mean number of pods per plant, in one experiment, were the most important characteristics for the genetic divergence, representing more than 46% of the total variation in the first canonic variable. The first two canonic variables were sufficient to explain about 88.23% of the total variation observed in the average of the four environments. The results showed that CNFC 8008 and CNFC 8009 genotypes presented the best yield averages in all the experiments. While Pérola, Princesa and CNFC 8005 cultivars were the most dissimilar for morpho-agronomic traits. Therefore, the combinations of PérolaxCNFC 8008, CNFC 8005xCNFC 8009, PérolaxCNFC 8009, PrincesaxCNFC 8008 and PrincesaxCNFC 8009 were indicated for interpopulational breeding.

The genetic and environmental aetiology of spatial, mathematics and general anxiety.

PubMed

Malanchini, Margherita; Rimfeld, Kaili; Shakeshaft, Nicholas G; Rodic, Maja; Schofield, Kerry; Selzam, Saskia; Dale, Philip S; Petrill, Stephen A; Kovas, Yulia

2017-02-21

Individuals differ in their level of general anxiety as well as in their level of anxiety towards specific activities, such as mathematics and spatial tasks. Both specific anxieties correlate moderately with general anxiety, but the aetiology of their association remains unexplored. Moreover, the factor structure of spatial anxiety is to date unknown. The present study investigated the factor structure of spatial anxiety, its aetiology, and the origins of its association with general and mathematics anxiety in a sample of 1,464 19-21-year-old twin pairs from the UK representative Twins Early Development Study. Participants reported their general, mathematics and spatial anxiety as part of an online battery of tests. We found that spatial anxiety is a multifactorial construct, including two components: navigation anxiety and rotation/visualization anxiety. All anxiety measures were moderately heritable (30% to 41%), and non-shared environmental factors explained the remaining variance. Multivariate genetic analysis showed that, although some genetic and environmental factors contributed to all anxiety measures, a substantial portion of genetic and non-shared environmental influences were specific to each anxiety construct. This suggests that anxiety is a multifactorial construct phenotypically and aetiologically, highlighting the importance of studying anxiety within specific contexts.

Unaffected family members report improvements in daily routine sun-protection 2 years following melanoma genetic testing

PubMed Central

Aspinwall, Lisa G.; Taber, Jennifer M.; Kohlmann, Wendy; Leaf, Samantha L.; Leachman, Sancy A.

2014-01-01

Purpose Reducing ultraviolet radiation (UVR) exposure may decrease melanoma risk in the hereditary melanoma setting. It is unknown whether genetic counseling and test reporting of CDKN2A/p16 mutation status promote long-term compliance with photoprotection recommendations, especially in unaffected mutation carriers. Methods This study evaluated changes 2 years following melanoma genetic testing in self-reported practice of sun-protection (sunscreen, photoprotective clothing, UVR avoidance) among 37 members of two CDKN2A/p16 kindreds (10 unaffected carriers, 11 affected carriers, 16 unaffected noncarriers; response rate=64.9% of eligible participants). Results Multivariate profile analysis indicated that all 3 participant groups reported increased daily routine practice of sun-protection 2 years following melanoma genetic testing (p<.02), with 96.9% reporting that at least 1 sun-protection behavior was part of their daily routine, up from 78.1% at baseline (p<.015). Unaffected carriers (p<.024) and unaffected noncarriers (p<.027) reported significantly more frequent use of photoprotective clothing. Affected carriers maintained adherence to all sun-protection behaviors. Reported sunburns in the past 6 months decreased significantly (p<.018). Conclusion Members of high-risk families reported increased daily routine sun-protection and decreased sunburns 2 years following melanoma genetic testing, with no net decline in sun-protection following negative test results. Thus, genetic testing and counseling may motivate sustained improvements in prevention behaviors. PMID:24763292

Imaging genetics of schizophrenia in the post-GWAS era.

PubMed

Arslan, Ayla

2018-01-03

Imaging genetics is a research methodology studying the effect of genetic variation on brain structure, function, behavior, and risk for psychopathology. Since the early 2000s, imaging genetics has been increasingly used in the research of schizophrenia (SZ). SZ is a severe mental disorder with no precise knowledge of its underlying neurobiology, however, new genetic and neurobiological data generate a climate for new avenues. The accumulating data of genome wide association studies (GWAS) continuously decode SZ risk genes. Global neuroimaging consortia produce collections of brain phenotypes from tens of thousands of people. In this context, imaging genetics will be strategically important both for the validation and discovery of SZ related findings. Thus, the study of GWAS supported risk variants as candidate genes to validate by neuroimaging is one trend. The study of epigenetic differences in relation to variations of brain phenotypes and the study of large scale multivariate analysis of genome wide and brain wide associations are other trends. While these studies hold a big potential for understanding the neurobiology of SZ, the problem of reproducibility appears as a major challenge, which requires standardizations in study designs and compensations of methodological limitations such as sensitivity and specificity. On the other hand, advancements of neuroimaging, optical and electron microscopy along with the use of genetically encoded fluorescent probes and robust statistical approaches will not only catalyze integrative methodologies but also will help better design the imaging genetics studies. In this invited paper, I will discuss the current perspective of imaging genetics and emerging opportunities of SZ research. Copyright © 2017 Elsevier Inc. All rights reserved.

A mixed model for the relationship between climate and human cranial form.

PubMed

Katz, David C; Grote, Mark N; Weaver, Timothy D

2016-08-01

We expand upon a multivariate mixed model from quantitative genetics in order to estimate the magnitude of climate effects in a global sample of recent human crania. In humans, genetic distances are correlated with distances based on cranial form, suggesting that population structure influences both genetic and quantitative trait variation. Studies controlling for this structure have demonstrated significant underlying associations of cranial distances with ecological distances derived from climate variables. However, to assess the biological importance of an ecological predictor, estimates of effect size and uncertainty in the original units of measurement are clearly preferable to significance claims based on units of distance. Unfortunately, the magnitudes of ecological effects are difficult to obtain with distance-based methods, while models that produce estimates of effect size generally do not scale to high-dimensional data like cranial shape and form. Using recent innovations that extend quantitative genetics mixed models to highly multivariate observations, we estimate morphological effects associated with a climate predictor for a subset of the Howells craniometric dataset. Several measurements, particularly those associated with cranial vault breadth, show a substantial linear association with climate, and the multivariate model incorporating a climate predictor is preferred in model comparison. Previous studies demonstrated the existence of a relationship between climate and cranial form. The mixed model quantifies this relationship concretely. Evolutionary questions that require population structure and phylogeny to be disentangled from potential drivers of selection may be particularly well addressed by mixed models. Am J Phys Anthropol 160:593-603, 2016. © 2015 Wiley Periodicals, Inc. © 2015 Wiley Periodicals, Inc.

Phenotypic variation and covariation indicate high evolvability of acoustic communication in crickets.

PubMed

Blankers, T; Lübke, A K; Hennig, R M

2015-09-01

Studying the genetic architecture of sexual traits provides insight into the rate and direction at which traits can respond to selection. Traits associated with few loci and limited genetic and phenotypic constraints tend to evolve at high rates typically observed for secondary sexual characters. Here, we examined the genetic architecture of song traits and female song preferences in the field crickets Gryllus rubens and Gryllus texensis. Song and preference data were collected from both species and interspecific F1 and F2 hybrids. We first analysed phenotypic variation to examine interspecific differentiation and trait distributions in parental and hybrid generations. Then, the relative contribution of additive and additive-dominance variation was estimated. Finally, phenotypic variance-covariance (P) matrices were estimated to evaluate the multivariate phenotype available for selection. Song traits and preferences had unimodal trait distributions, and hybrid offspring were intermediate with respect to the parents. We uncovered additive and dominance variation in song traits and preferences. For two song traits, we found evidence for X-linked inheritance. On the one hand, the observed genetic architecture does not suggest rapid divergence, although sex linkage may have allowed for somewhat higher evolutionary rates. On the other hand, P matrices revealed that multivariate variation in song traits aligned with major dimensions in song preferences, suggesting a strong selection response. We also found strong covariance between the main traits that are sexually selected and traits that are not directly selected by females, providing an explanation for the striking multivariate divergence in male calling songs despite limited divergence in female preferences. © 2015 European Society For Evolutionary Biology.

A molecular analysis of the patterns of genetic diversity in local chickens from western Algeria in comparison with commercial lines and wild jungle fowls.

PubMed

Mahammi, F Z; Gaouar, S B S; Laloë, D; Faugeras, R; Tabet-Aoul, N; Rognon, X; Tixier-Boichard, M; Saidi-Mehtar, N

2016-02-01

The objectives of this study were to characterize the genetic variability of village chickens from three agro-ecological regions of western Algeria: coastal (CT), inland plains (IP) and highlands (HL), to reveal any underlying population structure, and to evaluate potential genetic introgression from commercial lines into local populations. A set of 233 chickens was genotyped with a panel of 23 microsatellite markers. Geographical coordinates were individually recorded. Eight reference populations were included in the study to investigate potential gene flow: four highly selected commercial pure lines and four lines of French slow-growing chickens. Two populations of wild red jungle fowls were also genotyped to compare the range of diversity between domestic and wild fowls. A genetic diversity analysis was conducted both within and between populations. Multivariate redundancy analyses were performed to assess the relative influence of geographical location among Algerian ecotypes. The results showed a high genetic variability within the Algerian population, with 184 alleles and a mean number of 8.09 alleles per locus. The values of heterozygosity (He and Ho) ranged from 0.55 to 0.62 in Algerian ecotypes and were smaller than values found in Jungle fowl populations and higher than values found in commercial populations. Although the structuring analysis of genotypes did not reveal clear subpopulations within Algerian ecotypes, the supervised approach using geographical data showed a significant (p < 0.01) differentiation between the three ecotypes which was mainly due to altitude. Thus, the genetic diversity of Algerian ecotypes may be under the influence of two factors with contradictory effects: the geographical location and climatic conditions may induce some differentiation, whereas the high level of exchanges and gene flow may suppress it. Evidence of gene flow between commercial and Algerian local populations was observed, which may be due to unrecorded crossing with commercial chickens. Chicken ecotypes from western Algeria are characterized by a high genetic diversity and must be safeguarded as an important reservoir of genetic diversity. © 2015 Blackwell Verlag GmbH.

Patient and Genetic Counselor Perceptions of In-person versus Telephone Genetic Counseling for Hereditary Breast/Ovarian Cancer

PubMed Central

Jacobs, Aryana S.; Schwartz, Marc D.; Valdimarsdottir, Heiddis; Nusbaum, Rachel H.; Hooker, Gillian W.; DeMarco, Tiffani A.; Heinzmann, Jessica E.; McKinnon, Wendy; McCormick, Shelley R.; Davis, Claire; Forman, Andrea D.; Lebensohn, Alexandra Perez; Dalton, Emily; Tully, Diana Moglia; Graves, Kristi D.; Similuk, Morgan; Kelly, Scott; Peshkin, Beth N.

2016-01-01

Telephone genetic counseling (TC) for high-risk women interested in BRCA1/2 testing has been shown to yield positive outcomes comparable to usual care (UC; in-person) genetic counseling. However, little is known about how genetic counselors perceive the delivery of these alternate forms of genetic counseling. As part of a randomized trial of TC versus UC, genetic counselors completed a 5-item genetic counselor process questionnaire (GCQ) assessing key elements of pre-test sessions (information delivery, emotional support, addressing questions and concerns, tailoring of session, and facilitation of decision- making) with the 479 female participants (TC, N=236; UC, N=243). The GCQ scores did not differ for TC vs. UC sessions (t (477) = 0.11, p = 0.910). However, multivariate analysis showed that participant race/ethnicity significantly predicted genetic counselor perceptions (β = 0.172, p<0.001) in that the GCQ scores were lower for minorities in TC and UC. Exploratory analyses suggested that GCQ scores may be associated with patient preference for UC versus TC (t (79) = 2.21, p=0.030). Additionally, we found that genetic counselor ratings of session effectiveness were generally concordant with patient perceptions of the session. These data indicate that genetic counselors perceive that key components of TC can be delivered as effectively as UC, and that these elements may contribute to specific aspects of patient satisfaction. However, undefined process differences may be present which account for lower counselor perceptions about the effectiveness of their sessions with minority women (i.e., those other than non-Hispanic Whites). We discuss other potential clinical and research implications of our findings. PMID:26969308

Concurrent risk-reduction surgery in patients with increased lifetime risk for breast and ovarian cancer: an analysis of the National Surgical Quality Improvement Program (NSQIP) database.

PubMed

Elmi, Maryam; Azin, Arash; Elnahas, Ahmad; McCready, David R; Cil, Tulin D

2018-05-14

Patients with genetic susceptibility to breast and ovarian cancer are eligible for risk-reduction surgery. Surgical morbidity of risk-reduction mastectomy (RRM) with concurrent bilateral salpingo-oophorectomy (BSO) is unknown. Outcomes in these patients were compared to patients undergoing RRM without BSO using a large multi-institutional database. A retrospective cohort analysis was conducted using the American College of Surgeon's National Surgical Quality Improvement Program (NSQIP) 2007-2016 datasets, comparing postoperative morbidity between patients undergoing RRM with patients undergoing RRM with concurrent BSO. Patients with genetic susceptibility to breast/ovarian cancer undergoing risk-reduction surgery were identified. The primary outcome was 30-day postoperative major morbidity. Secondary outcomes included surgical site infections, reoperations, readmissions, length of stay, and venous thromboembolic events. A multivariate analysis was performed to determine predictors of postoperative morbidity and the adjusted effect of concurrent BSO on morbidity. Of the 5470 patients undergoing RRM, 149 (2.7%) underwent concurrent BSO. The overall rate of major morbidity and postoperative infections was 4.5% and 4.6%, respectively. There was no significant difference in the rate of postoperative major morbidity (4.5% vs 4.7%, p = 0.91) or any of the secondary outcomes between patients undergoing RRM without BSO vs. those undergoing RRM with concurrent BSO. Multivariable analysis showed Body Mass Index (OR 1.05; p < 0.001) and smoking (OR 1.78; p = 0.003) to be the only predictors associated with major morbidity. Neither immediate breast reconstruction (OR 1.02; p = 0.93) nor concurrent BSO (OR 0.94; p = 0.89) were associated with increased postoperative major morbidity. This study demonstrated that RRM with concurrent BSO was not associated with significant additional morbidity when compared to RRM without BSO. Therefore, this joint approach may be considered for select patients at risk for both breast and ovarian cancer.

Process analysis of recycled thermoplasts from consumer electronics by laser-induced plasma spectroscopy.

PubMed

Fink, Herbert; Panne, Ulrich; Niessner, Reinhard

2002-09-01

An experimental setup for direct elemental analysis of recycled thermoplasts from consumer electronics by laser-induced plasma spectroscopy (LIPS, or laser-induced breakdown spectroscopy, LIBS) was realized. The combination of a echelle spectrograph, featuring a high resolution with a broad spectral coverage, with multivariate methods, such as PLS, PCR, and variable subset selection via a genetic algorithm, resulted in considerable improvements in selectivity and sensitivity for this complex matrix. With a normalization to carbon as internal standard, the limits of detection were in the ppm range. A preliminary pattern recognition study points to the possibility of polymer recognition via the line-rich echelle spectra. Several experiments at an extruder within a recycling plant demonstrated successfully the capability of LIPS for different kinds of routine on-line process analysis.

Genetic variation in Southern USA rice genotypes for seedling salinity tolerance

PubMed Central

De Leon, Teresa B.; Linscombe, Steven; Gregorio, Glenn; Subudhi, Prasanta K.

2015-01-01

The success of a rice breeding program in developing salt tolerant varieties depends on genetic variation and the salt stress response of adapted and donor rice germplasm. In this study, we used a combination of morphological and physiological traits in multivariate analyses to elucidate the phenotypic and genetic variation in salinity tolerance of 30 Southern USA rice genotypes, along with 19 donor genotypes with varying degree of tolerance. Significant genotypic variation and correlations were found among the salt injury score (SIS), ion leakage, chlorophyll reduction, shoot length reduction, shoot K+ concentration, and shoot Na+/K+ ratio. Using these parameters, the combined methods of cluster analysis and discriminant analysis validated the salinity response of known genotypes and classified most of the USA varieties into sensitive groups, except for three and seven varieties placed in the tolerant and moderately tolerant groups, respectively. Discriminant function and MANOVA delineated the differences in tolerance and suggested no differences between sensitive and highly sensitive (HS) groups. DNA profiling using simple sequence repeat markers showed narrow genetic diversity among USA genotypes. However, the overall genetic clustering was mostly due to subspecies and grain type differentiation and not by varietal grouping based on salinity tolerance. Among the donor genotypes, Nona Bokra, Pokkali, and its derived breeding lines remained the donors of choice for improving salinity tolerance during the seedling stage. However, due to undesirable agronomic attributes and photosensitivity of these donors, alternative genotypes such as TCCP266, Geumgangbyeo, and R609 are recommended as useful and novel sources of salinity tolerance for USA rice breeding programs. PMID:26074937

Landscape genomics in Atlantic salmon (Salmo salar): searching for gene-environment interactions driving local adaptation.

PubMed

Vincent, Bourret; Dionne, Mélanie; Kent, Matthew P; Lien, Sigbjørn; Bernatchez, Louis

2013-12-01

A growing number of studies are examining the factors driving historical and contemporary evolution in wild populations. By combining surveys of genomic variation with a comprehensive assessment of environmental parameters, such studies can increase our understanding of the genomic and geographical extent of local adaptation in wild populations. We used a large-scale landscape genomics approach to examine adaptive and neutral differentiation across 54 North American populations of Atlantic salmon representing seven previously defined genetically distinct regional groups. Over 5500 genome-wide single nucleotide polymorphisms were genotyped in 641 individuals and 28 bulk assays of 25 pooled individuals each. Genome scans, linkage map, and 49 environmental variables were combined to conduct an innovative landscape genomic analysis. Our results provide valuable insight into the links between environmental variation and both neutral and potentially adaptive genetic divergence. In particular, we identified markers potentially under divergent selection, as well as associated selective environmental factors and biological functions with the observed adaptive divergence. Multivariate landscape genetic analysis revealed strong associations of both genetic and environmental structures. We found an enrichment of growth-related functions among outlier markers. Climate (temperature-precipitation) and geological characteristics were significantly associated with both potentially adaptive and neutral genetic divergence and should be considered as candidate loci involved in adaptation at the regional scale in Atlantic salmon. Hence, this study significantly contributes to the improvement of tools used in modern conservation and management schemes of Atlantic salmon wild populations. © 2013 The Author(s). Evolution © 2013 The Society for the Study of Evolution.

Behavioral Actions of Alcohol: Phenotypic Relations from Multivariate Analysis of Mutant Mouse Data

PubMed Central

Blednov, Yuri A.; Mayfield, R. Dayne; Belknap, John; Harris, R. Adron

2012-01-01

Behavioral studies of genetically diverse mice have proven powerful for determining relationships between phenotypes and have been widely used in alcohol research. Most of these studies rely on naturally occurring genetic polymorphisms among inbred strains and selected lines. Another approach is to introduce variation by engineering single gene mutations in mice. We have tested 37 different mutant mice and their wild type controls for a variety (31) of behaviors and have mined this dataset by K-means clustering and analysis of correlations. We found a correlation between a stress-related response (activity in a novel environment) and alcohol consumption and preference for saccharin. We confirmed several relationships detected in earlier genetic studies including positive correlation of alcohol consumption with saccharin consumption, and negative correlations with conditioned taste aversion and alcohol withdrawal severity. Introduction of single gene mutations either eliminated or greatly diminished these correlations. The three tests of alcohol consumption used (continuous two bottle choice, and two limited access tests: Drinking In the Dark and Sustained High Alcohol Consumption) share a relationship with saccharin consumption, but differ from each other in their correlation networks. We suggest that alcohol consumption is controlled by multiple physiological systems where single gene mutations can disrupt the networks of such systems. PMID:22405477

Liver transplantation for lethal genetic syndromes: a novel model of personalized genomic medicine.

PubMed

Petrowsky, Henrik; Brunicardi, F Charles; Leow, Voon Meng; Venick, Robert S; Agopian, Vatche; Kaldas, Fady M; Zarrinpar, Ali; Markovic, Daniela; McDiarmid, Sue V; Hong, Johnny C; Farmer, Douglas G; Hiatt, Jonathan R; Busuttil, Ronald W

2013-04-01

Our aim was to analyze our single-center experience with orthotopic liver transplantation for metabolic lethal genetic syndromes in children and adults. From 1984 to 2012, all pediatric (younger than 18 years) and adult (18 years and older) patients who underwent orthotopic liver transplantation for lethal genetic disorders were identified. Data on diagnostic pathways and specific outcomes were analyzed for both groups. Outcomes measures included recurrence rate as well as graft and patient survival. Metabolic lethal genetic syndrome was the primary indication for orthotopic liver transplantation in 152 of 4,564 patients (3.3%) at University of California, Los Angeles during the study period (74 pediatric patients and 78 adults). Genetic testing was performed in only 12% of the 152 patients and in 39% of patients after 2006. Two patients (1.3%) experienced a recurrence of the genetic disease. Overall 5- and 20-year survival rates were 89% and 77% for children and 73% and 50% for adults. Survival of pediatric patients was superior to adults (log-rank p < 0.009). Multivariate analysis identified age (hazard ratio = 2.18), preoperative life support (hazard ratio = 2.68), and earlier transplantation (hazard ratio = 3.41) as independent predictors of reduced survival. Orthotopic liver transplantation achieved excellent long-term survival in pediatric and adult patients with lethal genetic syndromes and represents a model of personalized genomic medicine by providing gene therapy through solid organ transplantation. Copyright © 2013 American College of Surgeons. Published by Elsevier Inc. All rights reserved.

6C.04: INTEGRATED SNP ANALYSIS AND METABOLOMIC PROFILES OF METABOLIC SYNDROME.

PubMed

Marrachelli, V; Monleon, D; Morales, J M; Rentero, P; Martínez, F; Chaves, F J; Martin-Escudero, J C; Redon, J

2015-06-01

Metabolic syndrome (MS) has become a health and financial burden worldwide. Susceptibility of genetically determined metabotype of MS has not yet been investigated. We aimed to identify a distinctive metabolic profile of blood serum which might correlates to the early detection of the development of MS associated to genetic polymorphism. We applied high resolution NMR spectroscopy to profile blood serum from patients without MS (n = 945) or with (n = 291). Principal component analysis (PCA) and projection to latent structures for discriminant analysis (PLS-DA) were applied to NMR spectral datasets. Results were cross-validated using the Venetian Blinds approach. Additionally, five SNPs previously associated with MS were genotyped with SNPlex and tested for associations between the metabolic profiles and the genetic variants. Statistical analysis was performed using in-house MATLAB scripts and the PLS Toolbox statistical multivariate analysis library. Our analysis provided a PLS-DA Metabolic Syndrome discrimination model based on NMR metabolic profile (AUC = 0.86) with 84% of sensitivity and 72% specificity. The model identified 11 metabolites differentially regulated in patients with MS. Among others, fatty acids, glucose, alanine, hydroxyisovalerate, acetone, trimethylamine, 2-phenylpropionate, isobutyrate and valine, significantly contributed to the model. The combined analysis of metabolomics and SNP data revealed an association between the metabolic profile of MS and genes polymorphism involved in the adiposity regulation and fatty acids metabolism: rs2272903_TT (TFAP2B), rs3803_TT (GATA2), rs174589_CC (FADS2) and rs174577_AA (FADS2). In addition, individuals with the rs2272903-TT genotype seem to develop MS earlier than general population. Our study provides new insights on the metabolic alterations associated with a MS high-risk genotype. These results could help in future development of risk assessment and predictive models for subclinical cardiovascular disease.

Childhood adiposity and risk of type 1 diabetes: A Mendelian randomization study

PubMed Central

Todd, John A.

2017-01-01

Background The incidence of type 1 diabetes (T1D) is increasing globally. One hypothesis is that increasing childhood obesity rates may explain part of this increase, but, as T1D is rare, intervention studies are challenging to perform. The aim of this study was to assess this hypothesis with a Mendelian randomization approach that uses genetic variants as instrumental variables to test for causal associations. Methods and findings We created a genetic instrument of 23 single nucleotide polymorphisms (SNPs) associated with childhood adiposity in children aged 2–10 years. Summary-level association results for these 23 SNPs with childhood-onset (<17 years) T1D were extracted from a meta-analysis of genome-wide association study with 5,913 T1D cases and 8,828 reference samples. Using inverse-variance weighted Mendelian randomization analysis, we found support for an effect of childhood adiposity on T1D risk (odds ratio 1.32, 95% CI 1.06–1.64 per standard deviation score in body mass index [SDS-BMI]). A sensitivity analysis provided evidence of horizontal pleiotropy bias (p = 0.04) diluting the estimates towards the null. We therefore applied Egger regression and multivariable Mendelian randomization methods to control for this type of bias and found evidence in support of a role of childhood adiposity in T1D (odds ratio in Egger regression, 2.76, 95% CI 1.40–5.44). Limitations of our study include that underlying genes and their mechanisms for most of the genetic variants included in the score are not known. Mendelian randomization requires large sample sizes, and power was limited to provide precise estimates. This research has been conducted using data from the Early Growth Genetics (EGG) Consortium, the Genetic Investigation of Anthropometric Traits (GIANT) Consortium, the Tobacco and Genetics (TAG) Consortium, and the Social Science Genetic Association Consortium (SSGAC), as well as meta-analysis results from a T1D genome-wide association study. Conclusions This study provides genetic support for a link between childhood adiposity and T1D risk. Together with evidence from observational studies, our findings further emphasize the importance of measures to reduce the global epidemic of childhood obesity and encourage mechanistic studies. PMID:28763444

Integrative analysis of gene expression and copy number alterations using canonical correlation analysis.

PubMed

Soneson, Charlotte; Lilljebjörn, Henrik; Fioretos, Thoas; Fontes, Magnus

2010-04-15

With the rapid development of new genetic measurement methods, several types of genetic alterations can be quantified in a high-throughput manner. While the initial focus has been on investigating each data set separately, there is an increasing interest in studying the correlation structure between two or more data sets. Multivariate methods based on Canonical Correlation Analysis (CCA) have been proposed for integrating paired genetic data sets. The high dimensionality of microarray data imposes computational difficulties, which have been addressed for instance by studying the covariance structure of the data, or by reducing the number of variables prior to applying the CCA. In this work, we propose a new method for analyzing high-dimensional paired genetic data sets, which mainly emphasizes the correlation structure and still permits efficient application to very large data sets. The method is implemented by translating a regularized CCA to its dual form, where the computational complexity depends mainly on the number of samples instead of the number of variables. The optimal regularization parameters are chosen by cross-validation. We apply the regularized dual CCA, as well as a classical CCA preceded by a dimension-reducing Principal Components Analysis (PCA), to a paired data set of gene expression changes and copy number alterations in leukemia. Using the correlation-maximizing methods, regularized dual CCA and PCA+CCA, we show that without pre-selection of known disease-relevant genes, and without using information about clinical class membership, an exploratory analysis singles out two patient groups, corresponding to well-known leukemia subtypes. Furthermore, the variables showing the highest relevance to the extracted features agree with previous biological knowledge concerning copy number alterations and gene expression changes in these subtypes. Finally, the correlation-maximizing methods are shown to yield results which are more biologically interpretable than those resulting from a covariance-maximizing method, and provide different insight compared to when each variable set is studied separately using PCA. We conclude that regularized dual CCA as well as PCA+CCA are useful methods for exploratory analysis of paired genetic data sets, and can be efficiently implemented also when the number of variables is very large.

The Developmental Association between Eating Disorders Symptoms and Symptoms of Depression and Anxiety in Juvenile Twin Girls

ERIC Educational Resources Information Center

Silberg, Judy L.; Bulik, Cynthia M.

2005-01-01

Objective: We investigated the role of genetic and environmental factors in the developmental association among symptoms of eating disorders, depression, and anxiety syndromes in 8-13-year-old and 14-17-year-old twin girls. Methods: Multivariate genetic models were fitted to child-reported longitudinal symptom data gathered from clinical interview…

Evolutionary rates for multivariate traits: the role of selection and genetic variation

PubMed Central

Pitchers, William; Wolf, Jason B.; Tregenza, Tom; Hunt, John; Dworkin, Ian

2014-01-01

A fundamental question in evolutionary biology is the relative importance of selection and genetic architecture in determining evolutionary rates. Adaptive evolution can be described by the multivariate breeders' equation (), which predicts evolutionary change for a suite of phenotypic traits () as a product of directional selection acting on them (β) and the genetic variance–covariance matrix for those traits (G). Despite being empirically challenging to estimate, there are enough published estimates of G and β to allow for synthesis of general patterns across species. We use published estimates to test the hypotheses that there are systematic differences in the rate of evolution among trait types, and that these differences are, in part, due to genetic architecture. We find some evidence that sexually selected traits exhibit faster rates of evolution compared with life-history or morphological traits. This difference does not appear to be related to stronger selection on sexually selected traits. Using numerous proposed approaches to quantifying the shape, size and structure of G, we examine how these parameters relate to one another, and how they vary among taxonomic and trait groupings. Despite considerable variation, they do not explain the observed differences in evolutionary rates. PMID:25002697

Multivariate Cholesky models of human female fertility patterns in the NLSY.

PubMed

Rodgers, Joseph Lee; Bard, David E; Miller, Warren B

2007-03-01

Substantial evidence now exists that variables measuring or correlated with human fertility outcomes have a heritable component. In this study, we define a series of age-sequenced fertility variables, and fit multivariate models to account for underlying shared genetic and environmental sources of variance. We make predictions based on a theory developed by Udry [(1996) Biosocial models of low-fertility societies. In: Casterline, JB, Lee RD, Foote KA (eds) Fertility in the United States: new patterns, new theories. The Population Council, New York] suggesting that biological/genetic motivations can be more easily realized and measured in settings in which fertility choices are available. Udry's theory, along with principles from molecular genetics and certain tenets of life history theory, allow us to make specific predictions about biometrical patterns across age. Consistent with predictions, our results suggest that there are different sources of genetic influence on fertility variance at early compared to later ages, but that there is only one source of shared environmental influence that occurs at early ages. These patterns are suggestive of the types of gene-gene and gene-environment interactions for which we must account to better understand individual differences in fertility outcomes.

Observational and Genetic Associations of Resting Heart Rate With Aortic Valve Calcium.

PubMed

Whelton, Seamus P; Mauer, Andreas C; Pencina, Karol M; Massaro, Joseph M; D'Agostino, Ralph B; Fox, Caroline S; Hoffmann, Udo; Michos, Erin D; Peloso, Gina M; Dufresne, Line; Engert, James C; Kathiresan, Sekar; Budoff, Matthew; Post, Wendy S; Thanassoulis, George; O'Donnell, Christopher J

2018-05-15

It is unknown if lifelong exposure to increased hemodynamic stress from an elevated resting heart rate (HR) may contribute to aortic valve calcium (AVC). We performed multivariate regression analyses using data from 1,266 Framingham Heart Study (FHS) Offspring cohort participants and 6,764 Multi-Ethnic Study of Atherosclerosis (MESA) participants. We constructed a genetic risk score (GRS) for HR using summary-level data in the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) AVC Consortium to investigate if there was evidence in favor of a causal relation. AVC was present in 39% of FHS Offspring cohort participants and in 13% of MESA cohort participants. In multivariate adjusted models, participants in the highest resting HR quartiles had significantly greater prevalence of AVC, with a prevalence ratio of 1.19 (95% confidence interval [CI] 0.99 to 1.44) for the FHS Offspring cohort and 1.32 (95% CI 1.12 to 1.63) for the MESA cohort, compared with those in the lowest quartile. There was a similar increase in the prevalence of AVC per standard deviation increase in resting HR in both FHS Offspring (prevalence ratio 1.08, 95% CI 1.01 to 1.15) and MESA (1.10, 95% CI 1.03 to 1.17). In contrast with these observational findings, a HR associated GRS was not significantly associated with AVC. Although our observational analysis indicates that a higher resting HR is associated with AVC, our genetic results do not support a causal relation. Unmeasured environmental and/or lifestyle factors associated with both increased resting HR and AVC that are not fully explained by covariates in our observational models may account for the association between resting HR and AVC. Copyright © 2018. Published by Elsevier Inc.

Pathway-Targeted Pharmacogenomics of CYP1A2 in Human Liver

PubMed Central

Klein, Kathrin; Winter, Stefan; Turpeinen, Miia; Schwab, Matthias; Zanger, Ulrich M.

2010-01-01

The human drug metabolizing cytochrome P450 (CYP) 1A2, is one of the major P450 isoforms contributing by about 5–20% to the hepatic P450 pool and catalyzing oxidative biotransformation of up to 10% of clinically relevant drugs including clozapine and caffeine. CYP1A2 activity is interindividually highly variable and although twin studies have suggested a high heritability, underlying genetic factors are still unknown. Here we adopted a pathway-oriented approach using a large human liver bank (n = 150) to elucidate whether variants in candidate genes of constitutive, ligand-inducible, and pathophysiological inhibitory regulatory pathways may explain different hepatic CYP1A2 phenotypes. Samples were phenotyped for phenacetin O-deethylase activity, and the expression of CYP1A2 protein and mRNA was determined. CYP1A2 expression and function was increased in smokers and decreased in patients with inflammation and cholestasis. Of 169 SNPs in 17 candidate genes including the CYP1A locus, 136 non-redundant SNPs with minor allele frequency >5% were analyzed by univariate and multivariate methods. A total of 13 strong significant associations were identified, of which 10 SNPs in the ARNT, AhRR, HNF1α, IL1β, SRC-1, and VDR genes showed consistent changes for at least two phenotypes by univariate analysis. Multivariate linear modeling indicated that the polymorphisms and non-genetic factors together explained 42, 38, and 33% of CYP1A2 variation at activity, protein and mRNA levels, respectively. In conclusion, we identified novel trans-associations between regulatory genes and hepatic CYP1A2 function and expression, but additional genetic factors must be assumed to explain the full extent of CYP1A2 heritability. PMID:21918647

Drug-related genetic polymorphisms affecting severe chemotherapy-induced neutropenia in breast cancer patients

PubMed Central

Tsuji, Daiki; Ikeda, Midori; Yamamoto, Keisuke; Nakamori, Harumi; Kim, Yong-Il; Kawasaki, Yohei; Otake, Aki; Yokoi, Mari; Inoue, Kazuyuki; Hirai, Keita; Nakamichi, Hidenori; Tokou, Umi; Shiokawa, Mitsuru; Itoh, Kunihiko

2016-01-01

Abstract Chemotherapy-induced neutropenia (CIN) is one of the major adverse events that necessitate chemotherapy dose reduction. This study aimed to evaluate the association between grade 4 neutropenia and genetic polymorphisms in breast cancer patients. In this genetic polymorphism association study, peripheral blood samples from 100 consecutive breast cancer outpatients, between August 2012 and September 2014, treated with doxorubicin and cyclophosphamide (AC) combination chemotherapy were genotyped for polymorphisms in adenosine triphosphate-binding cassette subfamily B member 1 (ABCB1), cytochrome P450 (CYP) enzyme-coding genes (CYP2B6 and CYP3A5), glutathione S-transferase (GST), and excision repair cross-complementing 1 (ERCC1). Associations between grade 4 neutropenia and genotypes as well as risk factors were examined using multivariate logistic regression. From 100 patients, 32.0% had grade 4 neutropenia. Multivariate logistic regression analysis revealed that ERCC1 118C > T (odds ratio [OR], 3.43; 95% confidence interval [CI], 1.22–9.69; P = 0.020), CYP2B6∗6 (OR, 4.51; 95% CI, 1.21–16.95; P = 0.025), body mass index (BMI) (OR, 6.94; 95% CI, 1.15–41.67; P = 0.035), and baseline white blood cell (WBC) count (OR, 2.99; 95% CI, 1.06–8.40; P = 0.038) were significant predictors of grade 4 neutropenia. ERCC1 and CYP2B6 gene polymorphisms were associated with the extent of grade 4 neutropenia in patients receiving AC chemotherapy. In addition to previously known risk factors, BMI and WBC counts, ERCC1 and CYP2B6 gene polymorphisms were also identified as independent strong predictors of grade 4 neutropenia. PMID:27858847

Chemometrics Methods for Specificity, Authenticity and Traceability Analysis of Olive Oils: Principles, Classifications and Applications.

PubMed

Messai, Habib; Farman, Muhammad; Sarraj-Laabidi, Abir; Hammami-Semmar, Asma; Semmar, Nabil

2016-11-17

Olive oils (OOs) show high chemical variability due to several factors of genetic, environmental and anthropic types. Genetic and environmental factors are responsible for natural compositions and polymorphic diversification resulting in different varietal patterns and phenotypes. Anthropic factors, however, are at the origin of different blends' preparation leading to normative, labelled or adulterated commercial products. Control of complex OO samples requires their (i) characterization by specific markers; (ii) authentication by fingerprint patterns; and (iii) monitoring by traceability analysis. These quality control and management aims require the use of several multivariate statistical tools: specificity highlighting requires ordination methods; authentication checking calls for classification and pattern recognition methods; traceability analysis implies the use of network-based approaches able to separate or extract mixed information and memorized signals from complex matrices. This chapter presents a review of different chemometrics methods applied for the control of OO variability from metabolic and physical-chemical measured characteristics. The different chemometrics methods are illustrated by different study cases on monovarietal and blended OO originated from different countries. Chemometrics tools offer multiple ways for quantitative evaluations and qualitative control of complex chemical variability of OO in relation to several intrinsic and extrinsic factors.

Genetic variation of germination cold tolerance in Japanese rice germplasm

PubMed Central

Bosetti, Fátima; Montebelli, Camila; Novembre, Ana Dionísia L.C.; Chamma, Helena Pescarin; Pinheiro, José Baldin

2012-01-01

Low temperatures at the initial stages of rice development prevent fast germination and seedling establishment and may cause significant productivity losses. In order to develop rice cultivars exhibiting cold tolerance, it is necessary to investigate genetic resources, providing basic knowledge to allow the introduction of genes involved in low temperature germination ability from accessions into elite cultivars. Japanese rice accessions were evaluated at the germination under two conditions: 13°C for 28 days (cold stress) and 28°C for seven days (optimal temperature). The traits studied were coleoptile and radicle length under optimal temperature, coleoptile and radicle length under cold and percentage of the reduction in coleptile and radicle length due to low temperature. Among the accessions studied, genetic variation for traits related to germination under low temperatures was observed and accessions exhibiting adequate performance for all investigated traits were identified. The use of multivariate analysis allowed the identification of the genotypes displaying cold tolerance by smaller reductions in coleoptile and radicle lenght in the presence of cold and high vigour, by higher coleoptile and radicle growth under cold. PMID:23226080

Genetic variation of germination cold tolerance in Japanese rice germplasm.

PubMed

Bosetti, Fátima; Montebelli, Camila; Novembre, Ana Dionísia L C; Chamma, Helena Pescarin; Pinheiro, José Baldin

2012-09-01

Low temperatures at the initial stages of rice development prevent fast germination and seedling establishment and may cause significant productivity losses. In order to develop rice cultivars exhibiting cold tolerance, it is necessary to investigate genetic resources, providing basic knowledge to allow the introduction of genes involved in low temperature germination ability from accessions into elite cultivars. Japanese rice accessions were evaluated at the germination under two conditions: 13°C for 28 days (cold stress) and 28°C for seven days (optimal temperature). The traits studied were coleoptile and radicle length under optimal temperature, coleoptile and radicle length under cold and percentage of the reduction in coleptile and radicle length due to low temperature. Among the accessions studied, genetic variation for traits related to germination under low temperatures was observed and accessions exhibiting adequate performance for all investigated traits were identified. The use of multivariate analysis allowed the identification of the genotypes displaying cold tolerance by smaller reductions in coleoptile and radicle lenght in the presence of cold and high vigour, by higher coleoptile and radicle growth under cold.

Morphoagronomic and molecular profiling of Capsicum spp from southwest Mato Grosso, Brazil.

PubMed

Campos, A L; Marostega, T N; Cabral, N S S; Araújo, K L; Serafim, M E; Seabra-Júnior, S; Sudré, C P; Rodrigues, R; Neves, L G

2016-07-15

The genus Capsicum ranks as the second most exported vegetable in Brazil, which is also considered to be a center of diversity for this genus. The aim of this study was to rescue genetic variability in the genus Capsicum in the southwest region of Mato Grosso, and to characterize and estimate the genetic diversity of accessions based on morphoagronomic descriptors and inter-simple sequence repeat molecular markers. Data were obtained following the criteria of the International Plant Genetic Resources Institute, renamed Bioversity International for Capsicum. Data were analyzed using different multivariate statistical techniques. An array of binary data was used to analyze molecular data, and the arithmetic complement of the Jaccard index was used to estimate the genetic dissimilarity among accessions. Six well-defined groups were formed based on the morphological characterization. The most divergent accessions were 142 and 126, with 125 and 126 being the most similar. The groups formed following agronomic characterization differed from those formed by morphological characterization, and there was a need to subdivide the groups for better distinction of accessions. Based on molecular analysis, accessions were divided into two groups, and there was also a need to subdivide the groups. Based on joint analysis (morphological + agronomic + molecular), six groups were formed with no duplicates. For all groups, the cophenetic correlation coefficient was higher than 0.8. These results provide useful information for the better management of the work collection. All correlations between the combined distance matrix were significant by the Mantel test.

Additive genetic variation in the craniofacial skeleton of baboons (genus Papio) and its relationship to body and cranial size.

PubMed

Joganic, Jessica L; Willmore, Katherine E; Richtsmeier, Joan T; Weiss, Kenneth M; Mahaney, Michael C; Rogers, Jeffrey; Cheverud, James M

2018-02-01

Determining the genetic architecture of quantitative traits and genetic correlations among them is important for understanding morphological evolution patterns. We address two questions regarding papionin evolution: (1) what effect do body and cranial size, age, and sex have on phenotypic (V P ) and additive genetic (V A ) variation in baboon crania, and (2) how might additive genetic correlations between craniofacial traits and body mass affect morphological evolution? We use a large captive pedigreed baboon sample to estimate quantitative genetic parameters for craniofacial dimensions (EIDs). Our models include nested combinations of the covariates listed above. We also simulate the correlated response of a given EID due to selection on body mass alone. Covariates account for 1.2-91% of craniofacial V P . EID V A decreases across models as more covariates are included. The median genetic correlation estimate between each EID and body mass is 0.33. Analysis of the multivariate response to selection reveals that observed patterns of craniofacial variation in extant baboons cannot be attributed solely to correlated response to selection on body mass, particularly in males. Because a relatively large proportion of EID V A is shared with body mass variation, different methods of correcting for allometry by statistically controlling for size can alter residual V P patterns. This may conflate direct selection effects on craniofacial variation with those resulting from a correlated response to body mass selection. This shared genetic variation may partially explain how selection for increased body mass in two different papionin lineages produced remarkably similar craniofacial phenotypes. © 2017 Wiley Periodicals, Inc.

Investigating genetic diversity and habitat dynamics in Plantago brutia (Plantaginaceae), implications for the management of narrow endemics in Mediterranean mountain pastures.

PubMed

De Vita, A; Bernardo, L; Gargano, D; Palermo, A M; Peruzzi, L; Musacchio, A

2009-11-01

Many factors have contributed to the richness of narrow endemics in the Mediterranean, including long-lasting human impact on pristine landscapes. The abandonment of traditional land-use practices is causing forest recovery throughout the Mediterranean mountains, by increasing reduction and fragmentation of open habitats. We investigated the population genetic structure and habitat dynamics of Plantago brutia Ten., a narrow endemic in mountain pastures of S Italy. Some plants were cultivated in the botanical garden to explore the species' breeding system. Genetic diversity was evaluated based on inter-simple sequence repeat (ISSR) polymorphisms in 150 individuals from most of known stands. Recent dynamics in the species habitat were checked over a 14-year period. Flower phenology, stigma receptivity and experimental pollinations revealed protogyny and self-incompatibility. With the exception of very small and isolated populations, high genetic diversity was found at the species and population level. amova revealed weak differentiation among populations, and the Mantel test suggested absence of isolation-by-distance. Multivariate analysis of population and genetic data distinguished the populations based on genetic richness, size and isolation. Landscape analyses confirmed recent reduction and isolation of potentially suitable habitats. Low selfing, recent isolation and probable seed exchange may have preserved P. brutia populations from higher loss of genetic diversity. Nonetheless, data related to very small populations suggest that this species may suffer further fragmentation and isolation. To preserve most of the species' genetic richness, future management efforts should consider the large and isolated populations recognised in our analyses.

CD44 Gene Polymorphisms in Breast Cancer Risk and Prognosis: A Study in North Indian Population

PubMed Central

Tulsyan, Sonam; Agarwal, Gaurav; Lal, Punita; Agrawal, Sushma; Mittal, Rama Devi; Mittal, Balraj

2013-01-01

Background Cell surface biomarker CD44 plays an important role in breast cancer cell growth, differentiation, invasion, angiogenesis and tumour metastasis. Therefore, we aimed to investigate the role of CD44 gene polymorphisms in breast cancer risk and prognosis in North Indian population. Materials & Methods A total of 258 breast cancer patients and 241 healthy controls were included in the case-control study for risk prediction. According to RECIST, 114 patients who received neo-adjuvant chemotherapy were recruited for the evaluation of breast cancer prognosis. We examined the association of tagging SNP (rs353639) of Hapmap Gujrati Indians in Houston (GIH population) in CD44 gene along with a significant reported SNP (rs13347) in Chinese population by genotyping using Taqman allelic discrimination assays. Statistical analysis was done using SPSS software, version 17. In-silico analysis for prediction of functional effects was done using F-SNP and FAST-SNP. Results No significant association of both the genetic variants of the CD44 gene polymorphisms was found with breast cancer risk. On performing univariate analysis with clinicopathological characteristics and treatment response, we found significant association of genotype (CT+TT) of rs13347 polymorphism with earlier age of onset (P = 0.029, OR = 0.037). However, significance was lost in multivariate analysis. For rs353639 polymorphism, significant association was seen with clinical tumour size, both at the genotypic (AC+CC) (P = 0.039, OR = 3.02) as well as the allelic (C) (P = 0.042, OR = 2.87) levels. On performing multivariate analysis, increased significance of variant genotype (P = 0.017, OR = 4.29) and allele (P = 0.025, OR = 3.34) of rs353639 was found with clinical tumour size. In-silico analysis using F-SNP, showed altered transcriptional regulation for rs353639 polymorphism. Conclusions These findings suggest that CD44 rs353639 genetic variants may have significant effect in breast cancer prognosis. However, both the polymorphisms- rs13347 and rs353639 had no effect on breast cancer susceptibility. PMID:23940692

ECOPASS - a multivariate model used as an index of growth performance of poplar clones

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

Ceulemans, R.; Impens, I.

The model (ECOlogical PASSport) reported was constructed by principal component analysis from a combination of biochemical, anatomical/morphological and ecophysiological gas exchange parameters measured on 5 fast growing poplar clones. Productivity data were 10 selected trees in 3 plantations in Belgium and given as m.a.i.(b.a.). The model is shown to be able to reflect not only genetic origin and the relative effects of the different parameters of the clones, but also their production potential. Multiple regression analysis of the 4 principal components showed a high cumulative correlation (96%) between the 3 components related to ecophysiological, biochemical and morphological parameters, and productivity;more » the ecophysiological component alone correlated 85% with productivity.« less

Evolving attractive faces using morphing technology and a genetic algorithm: a new approach to determining ideal facial aesthetics.

PubMed

Wong, Brian J F; Karimi, Koohyar; Devcic, Zlatko; McLaren, Christine E; Chen, Wen-Pin

2008-06-01

The objectives of this study were to: 1) determine if a genetic algorithm in combination with morphing software can be used to evolve more attractive faces; and 2) evaluate whether this approach can be used as a tool to define or identify the attributes of the ideal attractive face. Basic research study incorporating focus group evaluations. Digital images were acquired of 250 female volunteers (18-25 y). Randomly selected images were used to produce a parent generation (P) of 30 synthetic faces using morphing software. Then, a focus group of 17 trained volunteers (18-25 y) scored each face on an attractiveness scale ranging from 1 (unattractive) to 10 (attractive). A genetic algorithm was used to select 30 new pairs from the parent generation, and these were morphed using software to produce a new first generation (F1) of faces. The F1 faces were scored by the focus group, and the process was repeated for a total of four iterations of the algorithm. The algorithm mimics natural selection by using the attractiveness score as the selection pressure; the more attractive faces are more likely to morph. All five generations (P-F4) were then scored by three focus groups: a) surgeons (n = 12), b) cos-metology students (n = 44), and c) undergraduate students (n = 44). Morphometric measurements were made of 33 specific features on each of the 150 synthetic faces, and correlated with attractiveness scores using univariate and multivariate analysis. The average facial attractiveness scores increased with each generation and were 3.66 (+0.60), 4.59 (+/-0.73), 5.50 (+/-0.62), 6.23 (+/-0.31), and 6.39 (+/-0.24) for P and F1-F4 generations, respectively. Histograms of attractiveness score distributions show a significant shift in the skew of each curve toward more attractive faces with each generation. Univariate analysis identified nasal width, eyebrow arch height, and lip thickness as being significantly correlated with attractiveness scores. Multivariate analysis identified a similar collection of morphometric measures. No correlation with more commonly accepted measures such as the length facial thirds or fifths were identified. When images are examined as a montage (by generation), clear distinct trends are identified: oval shaped faces, distinct arched eyebrows, and full lips predominate. Faces evolve to approximate the guidelines suggested by classical canons. F3 and F4 generation faces look profoundly similar. The statistical and qualitative analysis indicates that the algorithm and methodology succeeds in generating successively more attractive faces. The use of genetic algorithms in combination with a morphing software and traditional focus-group derived attractiveness scores can be used to evolve attractive synthetic faces. We have demonstrated that the evolution of attractive faces can be mimicked in software. Genetic algorithms and morphing provide a robust alternative to traditional approaches rooted in comparing attractiveness scores with a series of morphometric measurements in human subjects.

Renal cell carcinoma associated with transcription factor E3 expression and Xp11.2 translocation: incidence, characteristics, and prognosis.

PubMed

Klatte, Tobias; Streubel, Berthold; Wrba, Friedrich; Remzi, Mesut; Krammer, Barbara; de Martino, Michela; Waldert, Matthias; Marberger, Michael; Susani, Martin; Haitel, Andrea

2012-05-01

We studied the characteristics and prognosis of renal cell carcinoma (RCC) associated with Xp11.2 translocation and transcription factor E3 (TFE3) expression and determined the need for genetic analysis in routine diagnostics. Of 848 consecutive cases, 75 showed microscopic features suggestive of Xp11.2 translocation RCC or occurred in patients 40 years or younger. Of these cases, 17 (23%) showed strong nuclear TFE3 immunostaining, which was associated with more advanced tumors and inverse prognosis in univariate (P = .032) but not multivariate (P = .404) analysis. With fluorescence in situ hybridization and polymerase chain reaction, only 2 cases showed alterations of the X chromosome and the ASPL-TFE3 gene fusion, respectively. In our laboratory, the predictive value of TFE3 expression for the Xp11.2 translocation was 12%. Strong nuclear TFE3 expression is associated with metastatic spread and a poor prognosis. In our laboratory, TFE3 is not diagnostic for Xp11.2 translocation RCC. Diagnosis of Xp11.2 translocation RCC may be made only genetically.

Analysis of association of clinical aspects and IL1B tagSNPs with severe preeclampsia.

PubMed

Leme Galvão, Larissa Paes; Menezes, Filipe Emanuel; Mendonca, Caio; Barreto, Ikaro; Alvim-Pereira, Claudia; Alvim-Pereira, Fabiano; Gurgel, Ricardo

2016-01-01

This study investigates the association between IL1B genotypes using a tag SNP (single polymorphism) approach, maternal and environmental factors in Brazilian women with severe preeclampsia. A case-control study with a total of 456 patients (169 preeclamptic women and 287 controls) was conducted in the two reference maternity hospitals of Sergipe state, Northeast Brazil. A questionnaire was administered and DNA was extracted to genotype the population for four tag SNPs of the IL1Beta: rs 1143643, rs 1143633, rs 1143634 and rs 1143630. Haplotype association analysis and p-values were calculated using the THESIAS test. Odds ratio (OR) estimation, confidence interval (CI) and multivariate logistic regression were performed. High pregestational body mass index (pre-BMI), first gestation, cesarean section, more than six medical visits, low level of consciousness on admission and TC and TT genotype in rs1143630 of IL1Beta showed association with the preeclamptic group in univariate analysis. After multivariate logistic regression pre-BMI, first gestation and low level of consciousness on admission remained associated. We identified an association between clinical variables and preeclampsia. Univariate analysis suggested that inflammatory process-related genes, such as IL1B, may be involved and should be targeted in further studies. The identification of the genetic background involved in preeclampsia host response modulation is mandatory in order to understand the preeclampsia process.

Saponin Profile of Wild Asparagus Species.

PubMed

Jaramillo-Carmona, Sara; Rodriguez-Arcos, Rocío; Jiménez-Araujo, Ana; López, Sergio; Gil, Juan; Moreno, Roberto; Guillén-Bejarano, Rafael

2017-03-01

The aim of this work was to study the saponin profiles from spears of different wild asparagus species in the context of its genetic diversity aside from geographical seed origin. They included Asparagus pseudoscaber Grecescu, Asparagus maritimus (L.) Mill., Asparagus brachiphyllus Turcz., Asparagus prostrates Dumort., and Asparagus officinalis L. The saponin analysis by LC-MS has shown that saponin profile from wild asparagus is similar to that previously described for triguero asparagus from Huétor-Tájar landrace (triguero HT), which had not ever been reported in the edible part of asparagus. All the samples, except A. officinalis, were characterized for having saponins distinct to protodioscin and the total saponin contents were 10-fold higher than those described for commercial hybrids of green asparagus. In particular, A. maritimus from different origins were rich in saponins previously found in triguero HT. These findings supported previous suggestion, based on genetic analysis, about A. maritimus being the origin of triguero HT. Multivariate statistics including principal component analysis and hierarchical clustering analysis were used to define both similarities and differences among samples. The results showed that the greatest variance of the tested wild asparagus could be attributed to differences in the concentration of particular saponins and this knowledge could be a tool for identifying similar species. © 2017 Institute of Food Technologists®.

Genetic diversity of a large set of horse breeds raised in France assessed by microsatellite polymorphism

PubMed Central

2009-01-01

The genetic diversity and structure of horses raised in France were investigated using 11 microsatellite markers and 1679 animals belonging to 34 breeds. Between-breed differences explained about ten per cent of the total genetic diversity (Fst = 0.099). Values of expected heterozygosity ranged from 0.43 to 0.79 depending on the breed. According to genetic relationships, multivariate and structure analyses, breeds could be classified into four genetic differentiated groups: warm-blooded, draught, Nordic and pony breeds. Using complementary maximisation of diversity and aggregate diversity approaches, we conclude that particular efforts should be made to conserve five local breeds, namely the Boulonnais, Landais, Merens, Poitevin and Pottok breeds. PMID:19284689

Genetic and environmental determinants of violence risk in psychotic disorders: a multivariate quantitative genetic study of 1.8 million Swedish twins and siblings.

PubMed

Sariaslan, A; Larsson, H; Fazel, S

2016-09-01

Patients diagnosed with psychotic disorders (for example, schizophrenia and bipolar disorder) have elevated risks of committing violent acts, particularly if they are comorbid with substance misuse. Despite recent insights from quantitative and molecular genetic studies demonstrating considerable pleiotropy in the genetic architecture of these phenotypes, there is currently a lack of large-scale studies that have specifically examined the aetiological links between psychotic disorders and violence. Using a sample of all Swedish individuals born between 1958 and 1989 (n=3 332 101), we identified a total of 923 259 twin-sibling pairs. Patients were identified using the National Patient Register using validated algorithms based on International Classification of Diseases (ICD) 8-10. Univariate quantitative genetic models revealed that all phenotypes (schizophrenia, bipolar disorder, substance misuse, and violent crime) were highly heritable (h(2)=53-71%). Multivariate models further revealed that schizophrenia was a stronger predictor of violence (r=0.32; 95% confidence interval: 0.30-0.33) than bipolar disorder (r=0.23; 0.21-0.25), and large proportions (51-67%) of these phenotypic correlations were explained by genetic factors shared between each disorder, substance misuse, and violence. Importantly, we found that genetic influences that were unrelated to substance misuse explained approximately a fifth (21%; 20-22%) of the correlation with violent criminality in bipolar disorder but none of the same correlation in schizophrenia (Pbipolar disorder<0.001; Pschizophrenia=0.55). These findings highlight the problems of not disentangling common and unique sources of covariance across genetically similar phenotypes as the latter sources may include aetiologically important clues. Clinically, these findings underline the importance of assessing risk of different phenotypes together and integrating interventions for psychiatric disorders, substance misuse, and violence.

Cytochrome P450 (CYP2D6) genotype is associated with elevated systolic blood pressure in preterm infants after discharge from the neonatal intensive care unit.

PubMed

Dagle, John M; Fisher, Tyler J; Haynes, Susan E; Berends, Susan K; Brophy, Patrick D; Morriss, Frank H; Murray, Jeffrey C

2011-07-01

To determine genetic and clinical risk factors associated with elevated systolic blood pressure (ESBP) in preterm infants after discharge from the neonatal intensive care unit (NICU). A convenience cohort of infants born at <32 weeks gestational age was followed after NICU discharge. We retrospectively identified a subgroup of subjects with ESBP (systolic blood pressure [SBP] >90th percentile for term infants). Genetic testing identified alleles associated with ESBP. Multivariate logistic regression analysis was performed for the outcome ESBP, with clinical characteristics and genotype as independent variables. Predictors of ESBP were cytochrome P450, family 2, subfamily D, polypeptide 6 (CYP2D6) (rs28360521) CC genotype (OR, 2.92; 95% CI, 1.48-5.79), adjusted for outpatient oxygen therapy (OR, 4.53; 95% CI, 2.23-8.81) and history of urinary tract infection (OR, 4.68; 95% CI, 1.47-14.86). Maximum SBP was modeled by multivariate linear regression analysis: maximum SBP=84.8 mm Hg + 6.8 mm Hg if cytochrome P450, family 2, subfamily D, polypeptide 6 (CYP2D6) CC genotype + 6.8 mm Hg if discharged on supplemental oxygen + 4.4 mm Hg if received inpatient glucocorticoids (P=.0002). ESBP is common in preterm infants with residual lung disease after discharge from the NICU. This study defines clinical factors associated with ESBP, identifies a candidate gene for further testing, and supports the recommendation to monitor blood pressure before age 3 years, as is suggested for term infants. Copyright © 2011 Mosby, Inc. All rights reserved.

Artificial neural network, genetic algorithm, and logistic regression applications for predicting renal colic in emergency settings.

PubMed

Eken, Cenker; Bilge, Ugur; Kartal, Mutlu; Eray, Oktay

2009-06-03

Logistic regression is the most common statistical model for processing multivariate data in the medical literature. Artificial intelligence models like an artificial neural network (ANN) and genetic algorithm (GA) may also be useful to interpret medical data. The purpose of this study was to perform artificial intelligence models on a medical data sheet and compare to logistic regression. ANN, GA, and logistic regression analysis were carried out on a data sheet of a previously published article regarding patients presenting to an emergency department with flank pain suspicious for renal colic. The study population was composed of 227 patients: 176 patients had a diagnosis of urinary stone, while 51 ultimately had no calculus. The GA found two decision rules in predicting urinary stones. Rule 1 consisted of being male, pain not spreading to back, and no fever. In rule 2, pelvicaliceal dilatation on bedside ultrasonography replaced no fever. ANN, GA rule 1, GA rule 2, and logistic regression had a sensitivity of 94.9, 67.6, 56.8, and 95.5%, a specificity of 78.4, 76.47, 86.3, and 47.1%, a positive likelihood ratio of 4.4, 2.9, 4.1, and 1.8, and a negative likelihood ratio of 0.06, 0.42, 0.5, and 0.09, respectively. The area under the curve was found to be 0.867, 0.720, 0.715, and 0.713 for all applications, respectively. Data mining techniques such as ANN and GA can be used for predicting renal colic in emergency settings and to constitute clinical decision rules. They may be an alternative to conventional multivariate analysis applications used in biostatistics.

Bayesian inference on risk differences: an application to multivariate meta-analysis of adverse events in clinical trials.

PubMed

Chen, Yong; Luo, Sheng; Chu, Haitao; Wei, Peng

2013-05-01

Multivariate meta-analysis is useful in combining evidence from independent studies which involve several comparisons among groups based on a single outcome. For binary outcomes, the commonly used statistical models for multivariate meta-analysis are multivariate generalized linear mixed effects models which assume risks, after some transformation, follow a multivariate normal distribution with possible correlations. In this article, we consider an alternative model for multivariate meta-analysis where the risks are modeled by the multivariate beta distribution proposed by Sarmanov (1966). This model have several attractive features compared to the conventional multivariate generalized linear mixed effects models, including simplicity of likelihood function, no need to specify a link function, and has a closed-form expression of distribution functions for study-specific risk differences. We investigate the finite sample performance of this model by simulation studies and illustrate its use with an application to multivariate meta-analysis of adverse events of tricyclic antidepressants treatment in clinical trials.

Neuroanatomical morphometric characterization of sex differences in youth using statistical learning.

PubMed

Sepehrband, Farshid; Lynch, Kirsten M; Cabeen, Ryan P; Gonzalez-Zacarias, Clio; Zhao, Lu; D'Arcy, Mike; Kesselman, Carl; Herting, Megan M; Dinov, Ivo D; Toga, Arthur W; Clark, Kristi A

2018-05-15

Exploring neuroanatomical sex differences using a multivariate statistical learning approach can yield insights that cannot be derived with univariate analysis. While gross differences in total brain volume are well-established, uncovering the more subtle, regional sex-related differences in neuroanatomy requires a multivariate approach that can accurately model spatial complexity as well as the interactions between neuroanatomical features. Here, we developed a multivariate statistical learning model using a support vector machine (SVM) classifier to predict sex from MRI-derived regional neuroanatomical features from a single-site study of 967 healthy youth from the Philadelphia Neurodevelopmental Cohort (PNC). Then, we validated the multivariate model on an independent dataset of 682 healthy youth from the multi-site Pediatric Imaging, Neurocognition and Genetics (PING) cohort study. The trained model exhibited an 83% cross-validated prediction accuracy, and correctly predicted the sex of 77% of the subjects from the independent multi-site dataset. Results showed that cortical thickness of the middle occipital lobes and the angular gyri are major predictors of sex. Results also demonstrated the inferential benefits of going beyond classical regression approaches to capture the interactions among brain features in order to better characterize sex differences in male and female youths. We also identified specific cortical morphological measures and parcellation techniques, such as cortical thickness as derived from the Destrieux atlas, that are better able to discriminate between males and females in comparison to other brain atlases (Desikan-Killiany, Brodmann and subcortical atlases). Copyright © 2018 Elsevier Inc. All rights reserved.

The Etiology of Variation in Language Skills Changes with Development: A Longitudinal Twin Study of Language from 2 to 12 Years

ERIC Educational Resources Information Center

Hayiou-Thomas, Marianna E.; Dale, Philip S.; Plomin, Robert

2012-01-01

The present study is the first long-term longitudinal examination of the etiology of individual differences in language from early childhood through to adolescence. We applied a multivariate latent factor genetic model to longitudinal data from the Twins Early Development Study in order to (a) compare the magnitude of genetic and environmental…

Population characteristics of DNA fingerprints in humpback whales (Megaptera novaeangliae).

PubMed

Baker, C S; Gilbert, D A; Weinrich, M T; Lambertsen, R; Calambokidis, J; McArdle, B; Chambers, G K; O'Brien, S J

1993-01-01

Humpback whales exhibit a remarkable social organization that is characterized by seasonal long-distance migration (> 10,000 km/year) between summer feeding grounds in high latitudes and winter calving and breeding grounds in tropical or near-tropical waters. All populations are currently considered endangered as a result of intensive commercial exploitation during the last 200 years. Using three hypervariable minisatellite DNA probes (33.15, 3'HVR, and M13) originally developed for studies of human genetic variation, we examined genetic variation within and among three regional subpopulations of humpback whales from the North Pacific and one from the North Atlantic oceans. Analysis of DNA extracted from skin tissues collected by biopsy darting from free-ranging whales revealed considerable variation in each subpopulation. The extent of this variation argues against a recent history of inbreeding among humpback whales as a result of nineteenth- and twentieth-century hunting. A canonical variate analysis suggested a relationship between scaled genetic distance, based on similarities of DNA fingerprints, and geographic distance (i.e., longitude of regional subpopulation). Significant categorical differences were found between the two oceanic populations using a multivariate analysis of variance (MANOVA) with a modification of the Mantel nonparametric permutation test. The relationship between DNA fingerprint similarities and geographic distance suggests that nuclear gene flow between regional subpopulations within the North Pacific is restricted by relatively low rates of migratory interchange between breeding grounds or assortative mating on common wintering grounds.

Genetic Variants in PNPLA3 and Risk of Non-Alcoholic Fatty Liver Disease in a Han Chinese Population

PubMed Central

Lin, Shao-Wei; Lu, Qing-Qing; Hu, Zhi-Jian; Lin, Xu

2012-01-01

We investigated the possible association between genetic variants in the Patatin like phospholipase-3 (PNPLA3) gene and nonalcoholic fatty liver disease (NAFLD) in a Han Chinese population. We evaluated twelve tagging single-nucleotide polymorphisms (tSNPs) of the PNPLA3 gene in a frequency matched case–control study from Fuzhou city of China (553 cases, 553 controls). In the multivariate logistic regression analysis, the rs738409 GG or GC, and rs139051 TT genotypes were found to be associated with increased risk of NAFLD, and a significant trend of increased risk with increasing numbers of risk genotype was observed in the cumulative effect analysis of these single nucleotide polymorphisms. Furthermore, haplotype association analysis showed that, compared with the most common haplotype, the CAAGAATGCGTG and CGAAGGTGTCCG haplotypes conferred a statistically significant increased risk for NAFLD, while the CGGGAACCCGCG haplotype decreased the risk of NAFLD. Moreover, rs738409 C>G appeared to have a multiplicative joint effect with tea drinking (P<0.005) and an additive joint effect with obesity (Interaction contrast ratio (ICR) = 2.31, 95% CI: 0.7–8.86), hypertriglyceridemia (ICR = 3.07, 95% CI: 0.98–5.09) or hypertension (ICR = 1.74, 95% CI: 0.52–3.12). Our data suggests that PNPLA3 genetic polymorphisms might influence the susceptibility to NAFLD development independently or jointly in Han Chinese. PMID:23226254

Principal variance component analysis of crop composition data: a case study on herbicide-tolerant cotton.

PubMed

Harrison, Jay M; Howard, Delia; Malven, Marianne; Halls, Steven C; Culler, Angela H; Harrigan, George G; Wolfinger, Russell D

2013-07-03

Compositional studies on genetically modified (GM) and non-GM crops have consistently demonstrated that their respective levels of key nutrients and antinutrients are remarkably similar and that other factors such as germplasm and environment contribute more to compositional variability than transgenic breeding. We propose that graphical and statistical approaches that can provide meaningful evaluations of the relative impact of different factors to compositional variability may offer advantages over traditional frequentist testing. A case study on the novel application of principal variance component analysis (PVCA) in a compositional assessment of herbicide-tolerant GM cotton is presented. Results of the traditional analysis of variance approach confirmed the compositional equivalence of the GM and non-GM cotton. The multivariate approach of PVCA provided further information on the impact of location and germplasm on compositional variability relative to GM.

Paternal alcoholism and offspring ADHD problems: a children of twins design.

PubMed

Knopik, Valerie S; Jacob, Theodore; Haber, Jon Randolph; Swenson, Lance P; Howell, Donelle N

2009-02-01

A recent Children-of-Female-Twin design suggests that the association between maternal alcohol use disorder and offspring ADHD is due to a combination of genetic and environmental factors, such as prenatal nicotine exposure. We present here a complementary analysis using a Children-of-Male-Twin design examining the association between paternal alcoholism and offspring attention deficit hyperactivity problems (ADHP). Children-of-twins design: offspring were classified into 4 groups of varying genetic and environmental risk based on father and co-twin's alcohol dependence status. Univariate results are suggestive of a genetic association between paternal alcohol dependence and broadly defined offspring ADHP. Specifically, offspring of male twins with a history of DSM-III-R alcohol dependence, as well as offspring of non-alcohol dependent monozygotic twins whose co-twin was alcohol dependent, were significantly more likely to exhibit ADHP than control offspring. However, multivariate models show maternal variables independently predicting increased risk for offspring ADHP and significantly decreased support for a genetic mechanism of parent-to-child transmission. In support of earlier work, maternal variables (i.e., maternal ADHD and prenatal exposure) were strongly associated with child ADHP; however, the role of paternal alcohol dependence influences was not definitive. While genetic transmission may be important, the association between paternal alcohol dependence and child ADHP is more likely to be indirect and a result of several pathways.

PATERNAL ALCOHOLISM AND OFFSPRING ADHD PROBLEMS: A CHILDREN OF TWINS DESIGN

PubMed Central

Knopik, Valerie S.; Jacob, Theodore; Haber, Jon Randolph; Swenson, Lance P.; Howell, Donelle N.

2013-01-01

Objective A recent Children-of-Female-Twin design suggests that the association between maternal alcohol use disorder and offspring ADHD is due to a combination of genetic and environmental factors, such as prenatal nicotine exposure. We present here a complementary analysis using a Children-of-Male-Twin design examining the association between paternal alcoholism and offspring attention deficit hyperactivity problems (ADHP). Methods Children-of-twins design: offspring were classified into 4 groups of varying genetic and environmental risk based on father and co-twin’s alcohol dependence status. Results Univariate results are suggestive of a genetic association between paternal alcohol dependence and broadly defined offspring ADHP. Specifically, offspring of male twins with a history of DSM-III-R alcohol dependence, as well as offspring of non-alcohol dependent monozygotic twins whose cotwin was alcohol dependent, were significantly more likely to exhibit ADHP than control offspring. However, multivariate models show maternal variables independently predicting increased risk for offspring ADHP and significantly decreased support for a genetic mechanism of parent-to-child transmission. Conclusions In support of earlier work, maternal variables (i.e., maternal ADHD and prenatal exposure) were strongly associated with child ADHP; however, the role of paternal alcohol dependence influences was not definitive. While genetic transmission may be important, the association between paternal alcohol dependence and child ADHP is more likely to be indirect and a result of several pathways. PMID:19210180

The five-factor model of personality and borderline personality disorder: a genetic analysis of comorbidity.

PubMed

Distel, Marijn A; Trull, Timothy J; Willemsen, Gonneke; Vink, Jacqueline M; Derom, Catherine A; Lynskey, Michael; Martin, Nicholas G; Boomsma, Dorret I

2009-12-15

Recently, the nature of personality disorders and their relationship with normal personality traits has received extensive attention. The five-factor model (FFM) of personality, consisting of the personality traits neuroticism, extraversion, openness to experience, agreeableness, and conscientiousness, is one of the proposed models to conceptualize personality disorders as maladaptive variants of continuously distributed personality traits. The present study examined the phenotypic and genetic association between borderline personality and FFM personality traits. Data were available for 4403 monozygotic twins, 4425 dizygotic twins, and 1661 siblings from 6140 Dutch, Belgian, and Australian families. Broad-sense heritability estimates for neuroticism, agreeableness, conscientiousness, extraversion, openness to experience, and borderline personality were 43%, 36%, 43%, 47%, 54%, and 45%, respectively. Phenotypic correlations between borderline personality and the FFM personality traits ranged from .06 for openness to experience to .68 for neuroticism. Multiple regression analyses showed that a combination of high neuroticism and low agreeableness best predicted borderline personality. Multivariate genetic analyses showed the genetic factors that influence individual differences in neuroticism, agreeableness, conscientiousness, and extraversion account for all genetic liability to borderline personality. Unique environmental effects on borderline personality, however, were not completely shared with those for the FFM traits (33% is unique to borderline personality). Borderline personality shares all genetic variation with neuroticism, agreeableness, conscientiousness, and extraversion. The unique environmental influences specific to borderline personality may cause individuals with a specific pattern of personality traits to cross a threshold and develop borderline personality.

Multivariate data analysis methods for the interpretation of microbial flow cytometric data.

PubMed

Davey, Hazel M; Davey, Christopher L

2011-01-01

Flow cytometry is an important technique in cell biology and immunology and has been applied by many groups to the analysis of microorganisms. This has been made possible by developments in hardware that is now sensitive enough to be used routinely for analysis of microbes. However, in contrast to advances in the technology that underpin flow cytometry, there has not been concomitant progress in the software tools required to analyse, display and disseminate the data and manual analysis, of individual samples remains a limiting aspect of the technology. We present two new data sets that illustrate common applications of flow cytometry in microbiology and demonstrate the application of manual data analysis, automated visualisation (including the first description of a new piece of software we are developing to facilitate this), genetic programming, principal components analysis and artificial neural nets to these data. The data analysis methods described here are equally applicable to flow cytometric applications with other cell types.

Evidence-based provisional clinical classification criteria for autoinflammatory periodic fevers.

PubMed

Federici, Silvia; Sormani, Maria Pia; Ozen, Seza; Lachmann, Helen J; Amaryan, Gayane; Woo, Patricia; Koné-Paut, Isabelle; Dewarrat, Natacha; Cantarini, Luca; Insalaco, Antonella; Uziel, Yosef; Rigante, Donato; Quartier, Pierre; Demirkaya, Erkan; Herlin, Troels; Meini, Antonella; Fabio, Giovanna; Kallinich, Tilmann; Martino, Silvana; Butbul, Aviel Yonatan; Olivieri, Alma; Kuemmerle-Deschner, Jasmin; Neven, Benedicte; Simon, Anna; Ozdogan, Huri; Touitou, Isabelle; Frenkel, Joost; Hofer, Michael; Martini, Alberto; Ruperto, Nicolino; Gattorno, Marco

2015-05-01

The objective of this work was to develop and validate a set of clinical criteria for the classification of patients affected by periodic fevers. Patients with inherited periodic fevers (familial Mediterranean fever (FMF); mevalonate kinase deficiency (MKD); tumour necrosis factor receptor-associated periodic fever syndrome (TRAPS); cryopyrin-associated periodic syndromes (CAPS)) enrolled in the Eurofever Registry up until March 2013 were evaluated. Patients with periodic fever, aphthosis, pharyngitis and adenitis (PFAPA) syndrome were used as negative controls. For each genetic disease, patients were considered to be 'gold standard' on the basis of the presence of a confirmatory genetic analysis. Clinical criteria were formulated on the basis of univariate and multivariate analysis in an initial group of patients (training set) and validated in an independent set of patients (validation set). A total of 1215 consecutive patients with periodic fevers were identified, and 518 gold standard patients (291 FMF, 74 MKD, 86 TRAPS, 67 CAPS) and 199 patients with PFAPA as disease controls were evaluated. The univariate and multivariate analyses identified a number of clinical variables that correlated independently with each disease, and four provisional classification scores were created. Cut-off values of the classification scores were chosen using receiver operating characteristic curve analysis as those giving the highest sensitivity and specificity. The classification scores were then tested in an independent set of patients (validation set) with an area under the curve of 0.98 for FMF, 0.95 for TRAPS, 0.96 for MKD, and 0.99 for CAPS. In conclusion, evidence-based provisional clinical criteria with high sensitivity and specificity for the clinical classification of patients with inherited periodic fevers have been developed. 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 relationship between genetic profiling, clinicopathological factors and survival in patients undergoing surgery for node-negative colorectal cancer: 10-year follow-up.

PubMed

Powell, Arfon G M T; Ferguson, Jenny; Al-Mulla, Fahd; Orange, Clare; McMillan, Donald C; Horgan, Paul G; Edwards, Joanne; Going, James J

2013-12-01

The introduction of the bowel cancer screening programme has resulted in increasing numbers of patients being diagnosed with node-negative disease. Unfortunately, approximately 30 % will develop recurrence following surgery. Given the toxicity associated with adjuvant chemotherapy, it is important to identify high-risk patients who may benefit from adjuvant therapy. This study aims to identify which clinicopathological factors and genetic profiling markers predict outcome in node-negative disease. Forty-nine microsatellite stable (MSS) patients undergoing curative resection between 1991 and 1993 were included. Local immune response was assessed by Klintrup criteria and vascular invasion status assessed through Miller's elastin staining. Comparative genomic hybridisation (CGH) on a range of loci provided data on allelic imbalance. Analysis of survival included clinicopathological and CGH data in a multivariate (Cox) model. On binary logistical regression analysis, 4p deletion was independently associated with low Klintrup score (HR 0.16; 95 % CI (0.03-0.96); P = 0.045), venous invasion (HR 4.19; 95 % CI (1.08-16.29); P = 0.039) and higher Dukes' stage (HR 6.43; 95 % CI (1.22-33.97); P = 0.028). Minimum follow-up was 109 months and there were 24 cancer deaths. On multivariate analysis, high Klintrup score (HR 0.33; 95 % CI (0.12-0.93); P = 0.036), 4p- (HR 4.01; 95 % CI (1.58-10.21); P = 0.004) and 5q- (HR 3.81; 95 % CI (1.54-9.47); P = 0.004) were significantly associated with survival. 4p-, 5q- and low Klintrup score were independently associated with poor cancer-specific survival in node-negative MSS colorectal cancer. Confirmatory work in a larger cohort is needed to determine whether these markers may be used to identify patients who may benefit from adjuvant chemotherapy.

Meta-analysis identifies gene-by-environment interactions as demonstrated in a study of 4,965 mice.

PubMed

Kang, Eun Yong; Han, Buhm; Furlotte, Nicholas; Joo, Jong Wha J; Shih, Diana; Davis, Richard C; Lusis, Aldons J; Eskin, Eleazar

2014-01-01

Identifying environmentally-specific genetic effects is a key challenge in understanding the structure of complex traits. Model organisms play a crucial role in the identification of such gene-by-environment interactions, as a result of the unique ability to observe genetically similar individuals across multiple distinct environments. Many model organism studies examine the same traits but under varying environmental conditions. For example, knock-out or diet-controlled studies are often used to examine cholesterol in mice. These studies, when examined in aggregate, provide an opportunity to identify genomic loci exhibiting environmentally-dependent effects. However, the straightforward application of traditional methodologies to aggregate separate studies suffers from several problems. First, environmental conditions are often variable and do not fit the standard univariate model for interactions. Additionally, applying a multivariate model results in increased degrees of freedom and low statistical power. In this paper, we jointly analyze multiple studies with varying environmental conditions using a meta-analytic approach based on a random effects model to identify loci involved in gene-by-environment interactions. Our approach is motivated by the observation that methods for discovering gene-by-environment interactions are closely related to random effects models for meta-analysis. We show that interactions can be interpreted as heterogeneity and can be detected without utilizing the traditional uni- or multi-variate approaches for discovery of gene-by-environment interactions. We apply our new method to combine 17 mouse studies containing in aggregate 4,965 distinct animals. We identify 26 significant loci involved in High-density lipoprotein (HDL) cholesterol, many of which are consistent with previous findings. Several of these loci show significant evidence of involvement in gene-by-environment interactions. An additional advantage of our meta-analysis approach is that our combined study has significantly higher power and improved resolution compared to any single study thus explaining the large number of loci discovered in the combined study.

Meta-Analysis Identifies Gene-by-Environment Interactions as Demonstrated in a Study of 4,965 Mice

PubMed Central

Joo, Jong Wha J.; Shih, Diana; Davis, Richard C.; Lusis, Aldons J.; Eskin, Eleazar

2014-01-01

Identifying environmentally-specific genetic effects is a key challenge in understanding the structure of complex traits. Model organisms play a crucial role in the identification of such gene-by-environment interactions, as a result of the unique ability to observe genetically similar individuals across multiple distinct environments. Many model organism studies examine the same traits but under varying environmental conditions. For example, knock-out or diet-controlled studies are often used to examine cholesterol in mice. These studies, when examined in aggregate, provide an opportunity to identify genomic loci exhibiting environmentally-dependent effects. However, the straightforward application of traditional methodologies to aggregate separate studies suffers from several problems. First, environmental conditions are often variable and do not fit the standard univariate model for interactions. Additionally, applying a multivariate model results in increased degrees of freedom and low statistical power. In this paper, we jointly analyze multiple studies with varying environmental conditions using a meta-analytic approach based on a random effects model to identify loci involved in gene-by-environment interactions. Our approach is motivated by the observation that methods for discovering gene-by-environment interactions are closely related to random effects models for meta-analysis. We show that interactions can be interpreted as heterogeneity and can be detected without utilizing the traditional uni- or multi-variate approaches for discovery of gene-by-environment interactions. We apply our new method to combine 17 mouse studies containing in aggregate 4,965 distinct animals. We identify 26 significant loci involved in High-density lipoprotein (HDL) cholesterol, many of which are consistent with previous findings. Several of these loci show significant evidence of involvement in gene-by-environment interactions. An additional advantage of our meta-analysis approach is that our combined study has significantly higher power and improved resolution compared to any single study thus explaining the large number of loci discovered in the combined study. PMID:24415945

Characterization of Clinical and Genetic Risk Factors Associated with Dyslipidemia after Kidney Transplantation

PubMed Central

Numakura, Kazuyuki; Kagaya, Hideaki; Yamamoto, Ryohei; Komine, Naoki; Saito, Mitsuru; Hiroshi, Tsuruta; Akihama, Susumu; Narita, Shintaro; Tsuchiya, Norihiko; Habuchi, Tomonori; Niioka, Takenori; Miura, Masatomo; Satoh, Shigeru

2015-01-01

We determined the prevalence of dyslipidemia in a Japanese cohort of renal allograft recipients and investigated clinical and genetic characteristics associated with having the disease. In total, 126 patients that received renal allograft transplants between February 2002 and August 2011 were studied, of which 44 recipients (34.9%) were diagnosed with dyslipidemia at 1 year after transplantation. Three clinical factors were associated with a risk of having dyslipidemia: a higher prevalence of disease observed among female than male patients (P = 0.021) and treatment with high mycophenolate mofetil (P = 0.012) and prednisolone (P = 0.023) doses per body weight at 28 days after transplantation. The genetic association between dyslipidemia and 60 previously described genetic polymorphisms in 38 putative disease-associated genes was analyzed. The frequency of dyslipidemia was significantly higher in patients with the glucocorticoid receptor (NR3C1) Bcl1 G allele than in those with the CC genotype (P = 0.001). A multivariate analysis revealed that the NR3C1 Bcl1 G allele was a significant risk factor for the prevalence of dyslipidemia (odds ratio = 4.6; 95% confidence interval = 1.8–12.2). These findings may aid in predicting a patient's risk of developing dyslipidemia. PMID:25944971

Attitudes and anticipated reactions to genetic testing for cancer among patients in Mexico City.

PubMed

Romero-Hidalgo, Sandra; Urraca, Nora; Parra, Dionisio; Villa, Antonio R; Lisker, Rubén; Carnevale, Alessandra

2009-08-01

The aim of this study was to investigate the attitudes toward cancer predictive genetic testing in a group of non-high-risk women and men and to analyze the factors that may influence their intention to use these tests. We studied a sample of 859 outpatient women and men attending the four tertiary care hospitals of the ISSSTE (Institute of Social Security and Services for Government Employees) in Mexico City. Subjects between the ages of 30 and 74 years with no present or past history of cancer were asked to answer a questionnaire through face-to-face interview. Two different questionnaires were designed, one for women and the other for men, regarding genetic testing of a high-risk gene for breast and prostate cancer, respectively. Descriptive statistics and univariate comparisons were carried out using chi-square test, Wilcoxon's signed rank test, and Friedman test. Multivariate analysis was performed using logistic regression technique. Results showed that the majority of women attended clinics for regular check-ups and for performing screening tests to detect breast cancer, and men did not follow this pattern regarding prostate cancer. Women were more motivated to get genetic testing, more aware about its benefits, and more concerned about having cancer than men.

Cryptic or pseudocryptic: can morphological methods inform copepod taxonomy? An analysis of publications and a case study of the Eurytemora affinis species complex

PubMed Central

Lajus, Dmitry; Sukhikh, Natalia; Alekseev, Victor

2015-01-01

Interest in cryptic species has increased significantly with current progress in genetic methods. The large number of cryptic species suggests that the resolution of traditional morphological techniques may be insufficient for taxonomical research. However, some species now considered to be cryptic may, in fact, be designated pseudocryptic after close morphological examination. Thus the “cryptic or pseudocryptic” dilemma speaks to the resolution of morphological analysis and its utility for identifying species. We address this dilemma first by systematically reviewing data published from 1980 to 2013 on cryptic species of Copepoda and then by performing an in-depth morphological study of the former Eurytemora affinis complex of cryptic species. Analyzing the published data showed that, in 5 of 24 revisions eligible for systematic review, cryptic species assignment was based solely on the genetic variation of forms without detailed morphological analysis to confirm the assignment. Therefore, some newly described cryptic species might be designated pseudocryptic under more detailed morphological analysis as happened with Eurytemora affinis complex. Recent genetic analyses of the complex found high levels of heterogeneity without morphological differences; it is argued to be cryptic. However, next detailed morphological analyses allowed to describe a number of valid species. Our study, using deep statistical analyses usually not applied for new species describing, of this species complex confirmed considerable differences between former cryptic species. In particular, fluctuating asymmetry (FA), the random variation of left and right structures, was significantly different between forms and provided independent information about their status. Our work showed that multivariate statistical approaches, such as principal component analysis, can be powerful techniques for the morphological discrimination of cryptic taxons. Despite increasing cryptic species designations, morphological techniques have great potential in determining copepod taxonomy. PMID:26120427

Overlapping Genetic and Child-Specific Nonshared Environmental Influences on Listening Comprehension, Reading Motivation, and Reading Comprehension

PubMed Central

Schenker, Victoria J.; Petrill, Stephen A.

2015-01-01

This study investigated the genetic and environmental influences on observed associations between listening comprehension, reading motivation, and reading comprehension. Univariate and multivariate quantitative genetic models were conducted in a sample of 284 pairs of twins at a mean age of 9.81 years. Genetic and nonshared environmental factors accounted for statistically significant variance in listening and reading comprehension, and nonshared environmental factors accounted for variance in reading motivation. Furthermore, listening comprehension demonstrated unique genetic and nonshared environmental influences but also had overlapping genetic influences with reading comprehension. Reading motivation and reading comprehension each had unique and overlapping nonshared environmental contributions. Therefore, listening comprehension appears to be related to reading primarily due to genetic factors whereas motivation appears to affect reading via child-specific, nonshared environmental effects. PMID:26321677

Overlapping genetic and child-specific nonshared environmental influences on listening comprehension, reading motivation, and reading comprehension.

PubMed

Schenker, Victoria J; Petrill, Stephen A

2015-01-01

This study investigated the genetic and environmental influences on observed associations between listening comprehension, reading motivation, and reading comprehension. Univariate and multivariate quantitative genetic models were conducted in a sample of 284 pairs of twins at a mean age of 9.81 years. Genetic and nonshared environmental factors accounted for statistically significant variance in listening and reading comprehension, and nonshared environmental factors accounted for variance in reading motivation. Furthermore, listening comprehension demonstrated unique genetic and nonshared environmental influences but also had overlapping genetic influences with reading comprehension. Reading motivation and reading comprehension each had unique and overlapping nonshared environmental contributions. Therefore, listening comprehension appears to be related to reading primarily due to genetic factors whereas motivation appears to affect reading via child-specific, nonshared environmental effects. Copyright © 2015 Elsevier Inc. All rights reserved.

Using parallel factor analysis modeling (PARAFAC) and self-organizing maps to track senescence-induced patterns in leaf litter leachate

NASA Astrophysics Data System (ADS)

Wheeler, K. I.; Levia, D. F., Jr.; Hudson, J. E.

2017-12-01

As trees undergo autumnal processes such as resorption, senescence, and leaf abscission, the dissolved organic matter (DOM) contribution of leaf litter leachate to streams changes. However, little research has investigated how the fluorescent DOM (FDOM) changes throughout the autumn and how this differs inter- and intraspecifically. Two of the major impacts of global climate change on forested ecosystems include altering phenology and causing forest community species and subspecies composition restructuring. We examined changes in FDOM in leachate from American beech (Fagus grandifolia Ehrh.) leaves in Maryland, Rhode Island, Vermont, and North Carolina and yellow poplar (Liriodendron tulipifera L.) leaves from Maryland throughout three different phenophases: green, senescing, and freshly abscissed. Beech leaves from Maryland and Rhode Island have previously been identified as belonging to the same distinct genetic cluster and beech trees from Vermont and the study site in North Carolina from the other. FDOM in samples was characterized using excitation-emission matrices (EEMs) and a six-component parallel factor analysis (PARAFAC) model was created to identify components. Self-organizing maps (SOMs) were used to visualize variation and patterns in the PARAFAC component proportions of the leachate samples. Phenophase and species had the greatest influence on determining where a sample mapped on the SOM when compared to genetic clusters and geographic origin. Throughout senescence, FDOM from all the trees transitioned from more protein-like components to more humic-like ones. Percent greenness of the sampled leaves and the proportion of the tyrosine-like component 1 were found to significantly differ between the two genetic beech clusters. This suggests possible differences in photosynthesis and resorption between the two genetic clusters of beech. The use of SOMs to visualize differences in patterns of senescence between the different species and genetic populations proved to be useful in ways that other multivariate analysis techniques lack.

Recipient’s Genetic R702W NOD2 Variant Is Associated with an Increased Risk of Bacterial Infections after Orthotopic Liver Transplantation

PubMed Central

van Hoek, Bart; van den Berg, Arie P.; Porte, Robert J.; Blokzijl, Hans; Coenraad, Minneke J.; Hepkema, Bouke G.; Schaapherder, Alexander F.; Ringers, Jan; Weersma, Rinse K.; Verspaget, Hein W.

2013-01-01

Introduction Orthotopic liver transplantation (OLT) is accompanied by a significant postoperative infection risk. Immunosuppression to prevent rejection increases the susceptibility to infections, mainly by impairing the adaptive immune system. Genetic polymorphisms in the lectin complement pathway of the donor have recently been identified as important risk determinants of clinically significant bacterial infection (CSI) after OLT. Another genetic factor involved in innate immunity is NOD2, which was reported to be associated with increased risk of spontaneous bacterial peritonitis in cirrhotic patients. Methods We assessed association of three genetic NOD2 variants (R702W, G908R and 3020insC) with increased risk of CSI after OLT. 288 OLT recipient-donor pairs from two tertiary referral centers were genotyped for the three NOD2 variants. The probability of CSI in relation to NOD2 gene variants was determined with cumulative incidence curves and log-rank analysis. Results The R702W NOD2 variant in the recipient was associated with CSI after OLT. Eight out of 15 (53.3%) individuals with a mutated genotype compared to 80/273 (29.3%) with wild type genotype developed CSI (p=0.027, univariate cox regression), illustrated by a higher frequency of CSI after OLT over time (p=0.0003, log rank analysis). Multivariate analysis (including the donor lectin complement pathway profile) showed independence of this R702W NOD2 association from other risk factors (HR 2.0; p=0.04). The other NOD2 variants, G908R and 3020insC, in the recipient were not associated with CSI. There was no association with CSI after OLT for any of the NOD2 variants in the donor. Conclusion The mutated NOD2 R702W genotype in the recipient is independently associated with an increased risk of bacterial infections after liver transplantation, indicating a predisposing role for this genetic factor impairing the recipient’s innate immune system. PMID:23977330

1H NMR based pharmacometabolomics analysis of urine identifies metabolic phenotype of clopidogrel high on treatment platelets reactivity in coronary artery disease patients.

PubMed

Amin, Arwa M; Sheau Chin, Lim; Teh, Chin-Hoe; Mostafa, Hamza; Mohamed Noor, Dzul Azri; Sk Abdul Kader, Muhamad Ali; Kah Hay, Yuen; Ibrahim, Baharudin

2017-11-30

Clopidogrel high on treatment platelets reactivity (HTPR) has burdened achieving optimum therapeutic outcome. Although there are known genetic and non-genetic factors associated with clopidogrel HTPR, which explain in part clopidogrel HTPR, yet, great portion remains unknown, often hindering personalizing antiplatelet therapy. Nuclear magnetic resonance ( 1 H NMR) pharmacometabolomics analysis is useful technique to phenotype drug response. We investigated using 1 H NMR analysis to phenotype clopidogrel HTPR in urine. Urine samples were collected from 71 coronary artery disease (CAD) patients who were planned for interventional angiographic procedure prior to taking 600mg clopidogrel loading dose (LD) and 6h post LD. Patients' platelets function testing was assessed with the VerifyNow ® P2Y12 assay at 6h after LD. Urine samples were analysed using 1 H NMR. Multivariate statistical analysis was used to identify metabolites associated with clopidogrel HTPR. In pre-dose samples, 16 metabolites were associated with clopidogrel HTPR. However, 18 metabolites were associated with clopidogrel HTPR in post-dose samples. The pathway analysis of the identified biomarkers reflected that multifactorial conditions are associated with clopidogrel HTPR. It also revealed the implicated role of gut microbiota in clopidogrel HTPR. Pharmacometabolomics not only discovered novel biomarkers of clopidogrel HTPR but also revealed implicated pathways and conditions. Copyright © 2017 Elsevier B.V. All rights reserved.

Determinants of airflow obstruction in severe alpha‐1‐antitrypsin deficiency

PubMed Central

DeMeo, Dawn L; Sandhaus, Robert A; Barker, Alan F; Brantly, Mark L; Eden, Edward; McElvaney, N Gerard; Rennard, Stephen; Burchard, Esteban; Stocks, James M; Stoller, James K; Strange, Charlie; Turino, Gerard M; Campbell, Edward J; Silverman, Edwin K

2007-01-01

Background Severe α1‐antitrypsin (AAT) deficiency is an autosomal recessive genetic condition associated with an increased but variable risk for chronic obstructive pulmonary disease (COPD). A study was undertaken to assess the impact of chronic bronchitis, pneumonia, asthma and sex on the development of COPD in individuals with severe AAT deficiency. Methods The AAT Genetic Modifier Study is a multicentre family‐based cohort study designed to study the genetic and epidemiological determinants of COPD in AAT deficiency. 378 individuals (age range 33–80 years), confirmed to be homozygous for the SERPINA1 Z mutation, were included in the analyses. The primary outcomes of interest were a quantitative outcome, forced expiratory volume in 1 s (FEV1) percentage predicted, and a qualitative outcome, severe airflow obstruction (FEV1 <50% predicted). Results In multivariate analysis of the overall cohort, cigarette smoking, sex, asthma, chronic bronchitis and pneumonia were risk factors for reduced FEV1 percentage predicted and severe airflow obstruction (p<0.01). Index cases had lower FEV1 values, higher smoking histories and more reports of adult asthma, pneumonia and asthma before age 16 than non‐index cases (p<0.01). Men had lower pre‐ and post‐bronchodilator FEV1 percentage predicted than women (p<0.0001); the lowest FEV1 values were observed in men reporting a history of childhood asthma (26.9%). This trend for more severe obstruction in men remained when index and non‐index groups were examined separately, with men representing the majority of non‐index individuals with airflow obstruction (71%). Chronic bronchitis (OR 3.8, CI 1.8 to 12.0) and a physician's report of asthma (OR 4.2, CI 1.4 to 13.1) were predictors of severe airflow obstruction in multivariate analysis of non‐index men but not women. Conclusion In individuals with severe AAT deficiency, sex, asthma, chronic bronchitis and pneumonia are risk factors for severe COPD, in addition to cigarette smoking. These results suggest that, in subjects severely deficient in AAT, men, individuals with symptoms of chronic bronchitis and/or a past diagnosis of asthma or pneumonia may benefit from closer monitoring and potentially earlier treatment. PMID:17389752

Multivariate analysis in thoracic research.

PubMed

Mengual-Macenlle, Noemí; Marcos, Pedro J; Golpe, Rafael; González-Rivas, Diego

2015-03-01

Multivariate analysis is based in observation and analysis of more than one statistical outcome variable at a time. In design and analysis, the technique is used to perform trade studies across multiple dimensions while taking into account the effects of all variables on the responses of interest. The development of multivariate methods emerged to analyze large databases and increasingly complex data. Since the best way to represent the knowledge of reality is the modeling, we should use multivariate statistical methods. Multivariate methods are designed to simultaneously analyze data sets, i.e., the analysis of different variables for each person or object studied. Keep in mind at all times that all variables must be treated accurately reflect the reality of the problem addressed. There are different types of multivariate analysis and each one should be employed according to the type of variables to analyze: dependent, interdependence and structural methods. In conclusion, multivariate methods are ideal for the analysis of large data sets and to find the cause and effect relationships between variables; there is a wide range of analysis types that we can use.

Experimental evolution for generalists and specialists reveals multivariate genetic constraints on thermal reaction norms.

PubMed

Berger, D; Walters, R J; Blanckenhorn, W U

2014-09-01

Theory predicts the emergence of generalists in variable environments and antagonistic pleiotropy to favour specialists in constant environments, but empirical data seldom support such generalist-specialist trade-offs. We selected for generalists and specialists in the dung fly Sepsis punctum (Diptera: Sepsidae) under conditions that we predicted would reveal antagonistic pleiotropy and multivariate trade-offs underlying thermal reaction norms for juvenile development. We performed replicated laboratory evolution using four treatments: adaptation at a hot (31 °C) or a cold (15 °C) temperature, or under regimes fluctuating between these temperatures, either within or between generations. After 20 generations, we assessed parental effects and genetic responses of thermal reaction norms for three correlated life-history traits: size at maturity, juvenile growth rate and juvenile survival. We find evidence for antagonistic pleiotropy for performance at hot and cold temperatures, and a temperature-mediated trade-off between juvenile survival and size at maturity, suggesting that trade-offs associated with environmental tolerance can arise via intensified evolutionary compromises between genetically correlated traits. However, despite this antagonistic pleiotropy, we found no support for the evolution of increased thermal tolerance breadth at the expense of reduced maximal performance, suggesting low genetic variance in the generalist-specialist dimension. © 2014 The Authors. Journal of Evolutionary Biology © 2014 European Society For Evolutionary Biology.

Genetic correlations between wellbeing, depression and anxiety symptoms and behavioral responses to the emotional faces task in healthy twins.

PubMed

Routledge, Kylie M; Williams, Leanne M; Harris, Anthony W F; Schofield, Peter R; Clark, C Richard; Gatt, Justine M

2018-06-01

Currently there is a very limited understanding of how mental wellbeing versus anxiety and depression symptoms are associated with emotion processing behaviour. For the first time, we examined these associations using a behavioural emotion task of positive and negative facial expressions in 1668 healthy adult twins. Linear mixed model results suggested faster reaction times to happy facial expressions was associated with higher wellbeing scores, and slower reaction times with higher depression and anxiety scores. Multivariate twin modelling identified a significant genetic correlation between depression and anxiety symptoms and reaction time to happy facial expressions, in the absence of any significant correlations with wellbeing. We also found a significant negative phenotypic relationship between depression and anxiety symptoms and accuracy for identifying neutral emotions, although the genetic or environment correlations were not significant in the multivariate model. Overall, the phenotypic relationships between speed of identifying happy facial expressions and wellbeing on the one hand, versus depression and anxiety symptoms on the other, were in opposing directions. Twin modelling revealed a small common genetic correlation between response to happy faces and depression and anxiety symptoms alone, suggesting that wellbeing and depression and anxiety symptoms show largely independent relationships with emotion processing at the behavioral level. Copyright © 2018 Elsevier B.V. All rights reserved.

Evolutionary rates for multivariate traits: the role of selection and genetic variation.

PubMed

Pitchers, William; Wolf, Jason B; Tregenza, Tom; Hunt, John; Dworkin, Ian

2014-08-19

A fundamental question in evolutionary biology is the relative importance of selection and genetic architecture in determining evolutionary rates. Adaptive evolution can be described by the multivariate breeders' equation (Δz(-)=Gβ), which predicts evolutionary change for a suite of phenotypic traits (Δz(-)) as a product of directional selection acting on them (β) and the genetic variance-covariance matrix for those traits (G ). Despite being empirically challenging to estimate, there are enough published estimates of G and β to allow for synthesis of general patterns across species. We use published estimates to test the hypotheses that there are systematic differences in the rate of evolution among trait types, and that these differences are, in part, due to genetic architecture. We find some evidence that sexually selected traits exhibit faster rates of evolution compared with life-history or morphological traits. This difference does not appear to be related to stronger selection on sexually selected traits. Using numerous proposed approaches to quantifying the shape, size and structure of G, we examine how these parameters relate to one another, and how they vary among taxonomic and trait groupings. Despite considerable variation, they do not explain the observed differences in evolutionary rates. © 2014 The Author(s) Published by the Royal Society. All rights reserved.

Relationship between ADD1 Gly460Trp gene polymorphism and essential hypertension in Madeira Island.

PubMed

Sousa, Ana Célia; Palma Dos Reis, Roberto; Pereira, Andreia; Borges, Sofia; Freitas, Ana Isabel; Guerra, Graça; Góis, Teresa; Rodrigues, Mariana; Henriques, Eva; Freitas, Sónia; Ornelas, Ilídio; Pereira, Décio; Brehm, António; Mendonça, Maria Isabel

2017-10-01

Essential hypertension (EH) is a complex disease in which physiological, environmental, and genetic factors are involved in its genesis. The genetic variant of the alpha-adducin gene (ADD1) has been described as a risk factor for EH, but with controversial results.The objective of this study was to evaluate the association of ADD1 (Gly460Trp) gene polymorphism with the EH risk in a population from Madeira Island.A case-control study with 1614 individuals of Caucasian origin was performed, including 817 individuals with EH and 797 controls. Cases and controls were matched for sex and age, by frequency-matching method. All participants collected blood for biochemical and genotypic analysis for the Gly460Trp polymorphism. We further investigated which variables were independently associated to EH, and, consequently, analyzed their interactions.In our study, we found a significant association between the ADD1 gene polymorphism and EH (odds ratio 2.484, P = .01). This association remained statistically significant after the multivariate analysis (odds ratio 2.548, P = .02).The ADD1 Gly460Trp gene polymorphism is significantly and independently associated with EH risk in our population. The knowledge of genetic polymorphisms associated with EH is of paramount importance because it leads to a better understanding of the etiology and pathophysiology of this pathology.

Relationship between ADD1 Gly460Trp gene polymorphism and essential hypertension in Madeira Island

PubMed Central

Sousa, Ana Célia; Palma dos Reis, Roberto; Pereira, Andreia; Borges, Sofia; Freitas, Ana Isabel; Guerra, Graça; Góis, Teresa; Rodrigues, Mariana; Henriques, Eva; Freitas, Sónia; Ornelas, Ilídio; Pereira, Décio; Brehm, António; Mendonça, Maria Isabel

2017-01-01

Abstract Essential hypertension (EH) is a complex disease in which physiological, environmental, and genetic factors are involved in its genesis. The genetic variant of the alpha-adducin gene (ADD1) has been described as a risk factor for EH, but with controversial results. The objective of this study was to evaluate the association of ADD1 (Gly460Trp) gene polymorphism with the EH risk in a population from Madeira Island. A case-control study with 1614 individuals of Caucasian origin was performed, including 817 individuals with EH and 797 controls. Cases and controls were matched for sex and age, by frequency-matching method. All participants collected blood for biochemical and genotypic analysis for the Gly460Trp polymorphism. We further investigated which variables were independently associated to EH, and, consequently, analyzed their interactions. In our study, we found a significant association between the ADD1 gene polymorphism and EH (odds ratio 2.484, P = .01). This association remained statistically significant after the multivariate analysis (odds ratio 2.548, P = .02). The ADD1 Gly460Trp gene polymorphism is significantly and independently associated with EH risk in our population. The knowledge of genetic polymorphisms associated with EH is of paramount importance because it leads to a better understanding of the etiology and pathophysiology of this pathology. PMID:29049185

Integrating Multiple Correlated Phenotypes for Genetic Association Analysis by Maximizing Heritability

PubMed Central

Zhou, Jin J.; Cho, Michael H.; Lange, Christoph; Lutz, Sharon; Silverman, Edwin K.; Laird, Nan M.

2015-01-01

Many correlated disease variables are analyzed jointly in genetic studies in the hope of increasing power to detect causal genetic variants. One approach involves assessing the relationship between each phenotype and each single nucleotide polymorphism (SNP) individually and using a Bonferroni correction for the effective number of tests conducted. Alternatively, one can apply a multivariate regression or a dimension reduction technique, such as principal component analysis (PCA), and test for the association with the principal components (PC) of the phenotypes rather than the individual phenotypes. Inspired by the previous approaches of combining phenotypes to maximize heritability at individual SNPs, in this paper, we propose to construct a maximally heritable phenotype (MaxH) by taking advantage of the estimated total heritability and co-heritability. The heritability and co-heritability only need to be estimated once, therefore our method is applicable to genome-wide scans. MaxH phenotype is a linear combination of the individual phenotypes with increased heritability and power over the phenotypes being combined. Simulations show that the heritability and power achieved agree well with the theory for large samples and two phenotypes. We compare our approach with commonly used methods and assess both the heritability and the power of the MaxH phenotype. Moreover we provide suggestions for how to choose the phenotypes for combination. An application of our approach to a COPD genome-wide association study shows the practical relevance. PMID:26111731

Near infrared spectrometric technique for testing fruit quality: optimisation of regression models using genetic algorithms

NASA Astrophysics Data System (ADS)

Isingizwe Nturambirwe, J. Frédéric; Perold, Willem J.; Opara, Umezuruike L.

2016-02-01

Near infrared (NIR) spectroscopy has gained extensive use in quality evaluation. It is arguably one of the most advanced spectroscopic tools in non-destructive quality testing of food stuff, from measurement to data analysis and interpretation. NIR spectral data are interpreted through means often involving multivariate statistical analysis, sometimes associated with optimisation techniques for model improvement. The objective of this research was to explore the extent to which genetic algorithms (GA) can be used to enhance model development, for predicting fruit quality. Apple fruits were used, and NIR spectra in the range from 12000 to 4000 cm-1 were acquired on both bruised and healthy tissues, with different degrees of mechanical damage. GAs were used in combination with partial least squares regression methods to develop bruise severity prediction models, and compared to PLS models developed using the full NIR spectrum. A classification model was developed, which clearly separated bruised from unbruised apple tissue. GAs helped improve prediction models by over 10%, in comparison with full spectrum-based models, as evaluated in terms of error of prediction (Root Mean Square Error of Cross-validation). PLS models to predict internal quality, such as sugar content and acidity were developed and compared to the versions optimized by genetic algorithm. Overall, the results highlighted the potential use of GA method to improve speed and accuracy of fruit quality prediction.

Examining the etiological associations among higher-order temperament dimensions

PubMed Central

Allan, Nicholas P.; Mikolajewski, Amy J.; Lonigan, Christopher J.; Hart, Sara A.; Taylor, Jeanette

2014-01-01

A multivariate independent pathway model was used to examine the shared and unique genetic and environmental influences of Positive Affect (PA), Negative Affect (NA), and effortful control (EC) in a sample of 686 twin pairs (M age = 10.07, SD = 1.74). There were common genetic influences and nonshared environmental influences shared across all three temperament dimensions and shared environmental influences in common to NA and EC. There were also significant independent genetic influences unique to PA and NA and significant independent shared environmental influences unique to PA. This study demonstrates that there are genetic and environmental influences that affect the covariance among temperament dimensions as well as unique genetic and environmental influences that influence the dimensions independently. PMID:24729641

Medical mistrust influences black women's level of engagement in BRCA 1/2 genetic counseling and testing.

PubMed

Sheppard, Vanessa B; Mays, Darren; LaVeist, Thomas; Tercyak, Kenneth P

2013-01-01

Clinical evidence supports the value of BRCA1/2 genetic counseling and testing for managing hereditary breast and ovarian cancer risk; however, BRCA1/2 genetic counseling and testing are underutilized among black women, and reasons for low use remain elusive. We examined the potential influence of sociocultural factors (medical mistrust, concerns about genetic discrimination) on genetic counseling and testing engagement in a sample of 100 black women at increased risk for carrying a BRCA1/2 mutation. Eligible participants fell into 1 of 3 groups: (1) healthy women with at least 1 first-degree relative affected by breast and/or ovarian cancer, (2) women diagnosed with breast cancer at age less than or equal to 50 years; and (3) women diagnosed with breast and/or ovarian cancer at age greater than or equal to 50 years with either 1 first-degree relative or 2 second-degree relatives with breast and/or ovarian cancer. Participants were recruited from clinical anid community settings and completed a semistructured interview. Study variable relationships were examined using bivariate tests and multivariate regression analysis. As expected, genetic counseling and testing engagement among this sample was low (28%). After accounting for;sociodemographic factors and self-efficacy (beta=0.37, p<.001), women with higher medical mistrust had lower genetic counseling and testing engagement (beta=-0.26, p<.01). Community-level and individual interventions are needed to improve utilization of genetic counseling and testing among underserved women. Along with trust building between patients and providers, strategies should enhance women's personal confidence. The impact of medical mistrust on the realization of the benefits of personalized medicine in minority populations should be further examined in future studies.

Identifying Multimodal Intermediate Phenotypes between Genetic Risk Factors and Disease Status in Alzheimer’s Disease

PubMed Central

Hao, Xiaoke; Yao, Xiaohui; Yan, Jingwen; Risacher, Shannon L.; Saykin, Andrew J.; Zhang, Daoqiang; Shen, Li

2016-01-01

Neuroimaging genetics has attracted growing attention and interest, which is thought to be a powerful strategy to examine the influence of genetic variants (i.e., single nucleotide polymorphisms (SNPs)) on structures or functions of human brain. In recent studies, univariate or multivariate regression analysis methods are typically used to capture the effective associations between genetic variants and quantitative traits (QTs) such as brain imaging phenotypes. The identified imaging QTs, although associated with certain genetic markers, may not be all disease specific. A useful, but underexplored, scenario could be to discover only those QTs associated with both genetic markers and disease status for revealing the chain from genotype to phenotype to symptom. In addition, multimodal brain imaging phenotypes are extracted from different perspectives and imaging markers consistently showing up in multimodalities may provide more insights for mechanistic understanding of diseases (i.e., Alzheimer’s disease (AD)). In this work, we propose a general framework to exploit multi-modal brain imaging phenotypes as intermediate traits that bridge genetic risk factors and multi-class disease status. We applied our proposed method to explore the relation between the well-known AD risk SNP APOE rs429358 and three baseline brain imaging modalities (i.e., structural magnetic resonance imaging (MRI), fluorodeoxyglucose positron emission tomography (FDG-PET) and F-18 florbetapir PET scans amyloid imaging (AV45)) from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database. The empirical results demonstrate that our proposed method not only helps improve the performances of imaging genetic associations, but also discovers robust and consistent regions of interests (ROIs) across multi-modalities to guide the disease-induced interpretation. PMID:27277494

An Underlying Common Factor, Influenced by Genetics and Unique Environment, Explains the Covariation Between Major Depressive Disorder, Generalized Anxiety Disorder, and Burnout: A Swedish Twin Study.

PubMed

Mather, Lisa; Blom, Victoria; Bergström, Gunnar; Svedberg, Pia

2016-12-01

Depression and anxiety are highly comorbid due to shared genetic risk factors, but less is known about whether burnout shares these risk factors. We aimed to examine whether the covariation between major depressive disorder (MDD), generalized anxiety disorder (GAD), and burnout is explained by common genetic and/or environmental factors. This cross-sectional study included 25,378 Swedish twins responding to a survey in 2005-2006. Structural equation models were used to analyze whether the trait variances and covariances were due to additive genetics, non-additive genetics, shared environment, and unique environment. Univariate analyses tested sex limitation models and multivariate analysis tested Cholesky, independent pathway, and common pathway models. The phenotypic correlations were 0.71 (0.69-0.74) between MDD and GAD, 0.58 (0.56-0.60) between MDD and burnout, and 0.53 (0.50-0.56) between GAD and burnout. Heritabilities were 45% for MDD, 49% for GAD, and 38% for burnout; no statistically significant sex differences were found. A common pathway model was chosen as the final model. The common factor was influenced by genetics (58%) and unique environment (42%), and explained 77% of the variation in MDD, 69% in GAD, and 44% in burnout. GAD and burnout had additive genetic factors unique to the phenotypes (11% each), while MDD did not. Unique environment explained 23% of the variability in MDD, 20% in GAD, and 45% in burnout. In conclusion, the covariation was explained by an underlying common factor, largely influenced by genetics. Burnout was to a large degree influenced by unique environmental factors not shared with MDD and GAD.

Consequences of a demographic bottleneck on genetic structure and variation in the Scandinavian brown bear.

PubMed

Xenikoudakis, G; Ersmark, E; Tison, J-L; Waits, L; Kindberg, J; Swenson, J E; Dalén, L

2015-07-01

The Scandinavian brown bear went through a major decline in population size approximately 100 years ago, due to intense hunting. After being protected, the population subsequently recovered and today numbers in the thousands. The genetic diversity in the contemporary population has been investigated in considerable detail, and it has been shown that the population consists of several subpopulations that display relatively high levels of genetic variation. However, previous studies have been unable to resolve the degree to which the demographic bottleneck impacted the contemporary genetic structure and diversity. In this study, we used mitochondrial and microsatellite DNA markers from pre- and postbottleneck Scandinavian brown bear samples to investigate the effect of the bottleneck. Simulation and multivariate analysis suggested the same genetic structure for the historical and modern samples, which are clustered into three subpopulations in southern, central and northern Scandinavia. However, the southern subpopulation appears to have gone through a marked change in allele frequencies. When comparing the mitochondrial DNA diversity in the whole population, we found a major decline in haplotype numbers across the bottleneck. However, the loss of autosomal genetic diversity was less pronounced, although a significant decline in allelic richness was observed in the southern subpopulation. Approximate Bayesian computations provided clear support for a decline in effective population size during the bottleneck, in both the southern and northern subpopulations. These results have implications for the future management of the Scandinavian brown bear because they indicate a recent loss in genetic diversity and also that the current genetic structure may have been caused by historical ecological processes rather than recent anthropogenic persecution. © 2015 John Wiley & Sons Ltd.

Contribution of genetic background, traditional risk factors, and HIV-related factors to coronary artery disease events in HIV-positive persons.

PubMed

Rotger, Margalida; Glass, Tracy R; Junier, Thomas; Lundgren, Jens; Neaton, James D; Poloni, Estella S; van 't Wout, Angélique B; Lubomirov, Rubin; Colombo, Sara; Martinez, Raquel; Rauch, Andri; Günthard, Huldrych F; Neuhaus, Jacqueline; Wentworth, Deborah; van Manen, Danielle; Gras, Luuk A; Schuitemaker, Hanneke; Albini, Laura; Torti, Carlo; Jacobson, Lisa P; Li, Xiuhong; Kingsley, Lawrence A; Carli, Federica; Guaraldi, Giovanni; Ford, Emily S; Sereti, Irini; Hadigan, Colleen; Martinez, Esteban; Arnedo, Mireia; Egaña-Gorroño, Lander; Gatell, Jose M; Law, Matthew; Bendall, Courtney; Petoumenos, Kathy; Rockstroh, Jürgen; Wasmuth, Jan-Christian; Kabamba, Kabeya; Delforge, Marc; De Wit, Stephane; Berger, Florian; Mauss, Stefan; de Paz Sierra, Mariana; Losso, Marcelo; Belloso, Waldo H; Leyes, Maria; Campins, Antoni; Mondi, Annalisa; De Luca, Andrea; Bernardino, Ignacio; Barriuso-Iglesias, Mónica; Torrecilla-Rodriguez, Ana; Gonzalez-Garcia, Juan; Arribas, José R; Fanti, Iuri; Gel, Silvia; Puig, Jordi; Negredo, Eugenia; Gutierrez, Mar; Domingo, Pere; Fischer, Julia; Fätkenheuer, Gerd; Alonso-Villaverde, Carlos; Macken, Alan; Woo, James; McGinty, Tara; Mallon, Patrick; Mangili, Alexandra; Skinner, Sally; Wanke, Christine A; Reiss, Peter; Weber, Rainer; Bucher, Heiner C; Fellay, Jacques; Telenti, Amalio; Tarr, Philip E

2013-07-01

Persons infected with human immunodeficiency virus (HIV) have increased rates of coronary artery disease (CAD). The relative contribution of genetic background, HIV-related factors, antiretroviral medications, and traditional risk factors to CAD has not been fully evaluated in the setting of HIV infection. In the general population, 23 common single-nucleotide polymorphisms (SNPs) were shown to be associated with CAD through genome-wide association analysis. Using the Metabochip, we genotyped 1875 HIV-positive, white individuals enrolled in 24 HIV observational studies, including 571 participants with a first CAD event during the 9-year study period and 1304 controls matched on sex and cohort. A genetic risk score built from 23 CAD-associated SNPs contributed significantly to CAD (P = 2.9 × 10(-4)). In the final multivariable model, participants with an unfavorable genetic background (top genetic score quartile) had a CAD odds ratio (OR) of 1.47 (95% confidence interval [CI], 1.05-2.04). This effect was similar to hypertension (OR = 1.36; 95% CI, 1.06-1.73), hypercholesterolemia (OR = 1.51; 95% CI, 1.16-1.96), diabetes (OR = 1.66; 95% CI, 1.10-2.49), ≥ 1 year lopinavir exposure (OR = 1.36; 95% CI, 1.06-1.73), and current abacavir treatment (OR = 1.56; 95% CI, 1.17-2.07). The effect of the genetic risk score was additive to the effect of nongenetic CAD risk factors, and did not change after adjustment for family history of CAD. In the setting of HIV infection, the effect of an unfavorable genetic background was similar to traditional CAD risk factors and certain adverse antiretroviral exposures. Genetic testing may provide prognostic information complementary to family history of CAD.

A Twin Study of Sleep Duration and Body Mass Index

PubMed Central

Watson, Nathaniel F.; Buchwald, Dedra; Vitiello, Michael V.; Noonan, Carolyn; Goldberg, Jack

2010-01-01

Study Objective: To determine the relative importance of genetic and environmental contributions to the association between sleep duration and body mass index (BMI). Methods: Twins from the University of Washington Twin Registry, a community-based sample of U.S. twins, provided self-reported height and weight for BMI calculation and habitual sleep duration. A generalized estimating equation model evaluated the overall and within twin pair effects of sleep duration on BMI with and without stratification by twin zygosity. A structural equation model was used to assess genetic and non-genetic contributions to BMI and sleep duration. Results: The study sample included 1,224 twins comprised of 423 monozygotic, 143 dizygotic, and 46 indeterminate pairs. The mean age was 36.9 years; 69% were female. A multivariate adjusted analysis of all twins revealed an elevated mean BMI (26.0 kg/m2) in short sleeping twins (< 7 h/night) compared to twins sleeping 7–8.9 h/night (BMI 24.8 kg/m2; p < 0.01). The within-twin pair analysis revealed similar results, with the short sleeping twins having a mean BMI of 25.8 kg/m2 compared to 24.9 kg/m2 for the 7–8.9 h/night sleep duration group (p = 0.02). When restricted to monozygotic twins, the within-twin pair analysis continued to reveal an elevated BMI in the short sleeping twins (25.7 kg/m2) compared to the 7–8.9 h/night reference group (24.7 kg/m2; p = 0.02). No differences in mean BMI were observed between the 7–8.9 h/night reference group twins and longer sleeping twins (≥ 9 h/night) in the analysis of all twins, the overall within-twin pair analysis, or the within-twin pair analysis stratified by zygosity. The heritability of sleep duration was 0.31 (p = 0.08) and BMI 0.76 (p < 0.01). Bivariate genetic analysis revealed little evidence of shared genetics between sleep duration and BMI (p = 0.28). Conclusions: Short sleep was associated with elevated BMI following careful adjustment for genetics and shared environment. These findings point toward an environmental cause of the relationship between sleep duration and BMI. Citation: Watson NF; Buchwald D; Vitiello MV; Noonan C; Goldberg J. A twin study of sleep duration and body mass index. J Clin Sleep Med 2010;6(1):11-17. PMID:20191932

Gene movement and genetic association with regional climate gradients in California valley oak (Quercus lobata Née) in the face of climate change

USGS Publications Warehouse

Sork, Victoria L.; Davis, Frank W.; Westfall, Robert; Flint, Alan L.; Ikegami, Makihiko; Wang, Hongfang; Grivet, Delphine

2010-01-01

Rapid climate change jeopardizes tree populations by shifting current climate zones. To avoid extinction, tree populations must tolerate, adapt, or migrate. Here we investigate geographic patterns of genetic variation in valley oak, Quercus lobata N??e, to assess how underlying genetic structure of populations might influence this species' ability to survive climate change. First, to understand how genetic lineages shape spatial genetic patterns, we examine historical patterns of colonization. Second, we examine the correlation between multivariate nuclear genetic variation and climatic variation. Third, to illustrate how geographic genetic variation could interact with regional patterns of 21st Century climate change, we produce region-specific bioclimatic distributions of valley oak using Maximum Entropy (MAXENT) models based on downscaled historical (1971-2000) and future (2070-2100) climate grids. Future climatologies are based on a moderate-high (A2) carbon emission scenario and two different global climate models. Chloroplast markers indicate historical range-wide connectivity via colonization, especially in the north. Multivariate nuclear genotypes show a strong association with climate variation that provides opportunity for local adaptation to the conditions within their climatic envelope. Comparison of regional current and projected patterns of climate suitability indicates that valley oaks grow in distinctly different climate conditions in different parts of their range. Our models predict widely different regional outcomes from local displacement of a few kilometres to hundreds of kilometres. We conclude that the relative importance of migration, adaptation, and tolerance are likely to vary widely for populations among regions, and that late 21st Century conditions could lead to regional extinctions. ?? 2010 Blackwell Publishing Ltd.

Gene movement and genetic association with regional climate gradients in California valley oak (Quercus lobata Née) in the face of climate change.

PubMed

Sork, Victoria L; Davis, Frank W; Westfall, Robert; Flint, Alan; Ikegami, Makihiko; Wang, Hongfang; Grivet, Delphine

2010-09-01

Rapid climate change jeopardizes tree populations by shifting current climate zones. To avoid extinction, tree populations must tolerate, adapt, or migrate. Here we investigate geographic patterns of genetic variation in valley oak, Quercus lobata Née, to assess how underlying genetic structure of populations might influence this species' ability to survive climate change. First, to understand how genetic lineages shape spatial genetic patterns, we examine historical patterns of colonization. Second, we examine the correlation between multivariate nuclear genetic variation and climatic variation. Third, to illustrate how geographic genetic variation could interact with regional patterns of 21st Century climate change, we produce region-specific bioclimatic distributions of valley oak using Maximum Entropy (MAXENT) models based on downscaled historical (1971-2000) and future (2070-2100) climate grids. Future climatologies are based on a moderate-high (A2) carbon emission scenario and two different global climate models. Chloroplast markers indicate historical range-wide connectivity via colonization, especially in the north. Multivariate nuclear genotypes show a strong association with climate variation that provides opportunity for local adaptation to the conditions within their climatic envelope. Comparison of regional current and projected patterns of climate suitability indicates that valley oaks grow in distinctly different climate conditions in different parts of their range. Our models predict widely different regional outcomes from local displacement of a few kilometres to hundreds of kilometres. We conclude that the relative importance of migration, adaptation, and tolerance are likely to vary widely for populations among regions, and that late 21st Century conditions could lead to regional extinctions.

Correlative and multivariate analysis of increased radon concentration in underground laboratory.

PubMed

Maletić, Dimitrije M; Udovičić, Vladimir I; Banjanac, Radomir M; Joković, Dejan R; Dragić, Aleksandar L; Veselinović, Nikola B; Filipović, Jelena

2014-11-01

The results of analysis using correlative and multivariate methods, as developed for data analysis in high-energy physics and implemented in the Toolkit for Multivariate Analysis software package, of the relations of the variation of increased radon concentration with climate variables in shallow underground laboratory is presented. Multivariate regression analysis identified a number of multivariate methods which can give a good evaluation of increased radon concentrations based on climate variables. The use of the multivariate regression methods will enable the investigation of the relations of specific climate variable with increased radon concentrations by analysis of regression methods resulting in 'mapped' underlying functional behaviour of radon concentrations depending on a wide spectrum of climate variables. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

GENETIC INFLUENCE OF APOE4 GENOTYPE ON HIPPOCAMPAL MORPHOMETRY - AN N=725 SURFACE-BASED ADNI STUDY

PubMed Central

Shi, Jie; Leporé, Natasha; Gutman, Boris A.; Thompson, Paul M.; Baxter, Leslie C.; Caselli, Richard L.; Wang, Yalin

2014-01-01

The apolipoprotein E (APOE) e4 allele is the most prevalent genetic risk factor for Alzheimer’s disease (AD). Hippocampal volumes are generally smaller in AD patients carrying the e4 allele compared to e4 non-carriers. Here we examined the effect of APOE e4 on hippocampal morphometry in a large imaging database – the Alzheimer’s Disease Neuroimaging Initiative (ADNI). We automatically segmented and constructed hippocampal surfaces from the baseline MR images of 725 subjects with known APOE genotype information including 167 with AD, 354 with mild cognitive impairment (MCI), and 204 normal controls. High-order correspondences between hippocampal surfaces were enforced across subjects with a novel inverse consistent surface fluid registration method. Multivariate statistics consisting of multivariate tensor-based morphometry (mTBM) and radial distance were computed for surface deformation analysis. Using Hotelling’s T2 test, we found significant morphological deformation in APOE e4 carriers relative to non-carriers in the entire cohort as well as in the non-demented (pooled MCI and control) subjects, affecting the left hippocampus more than the right, and this effect was more pronounced in e4 homozygotes than heterozygotes. Our findings are consistent with previous studies that showed e4 carriers exhibit accelerated hippocampal atrophy; we extend these findings to a novel measure of hippocampal morphometry. Hippocampal morphometry has significant potential as an imaging biomarker of early stage AD. PMID:24453132

An integrated phenomic approach to multivariate allelic association

PubMed Central

Medland, Sarah Elizabeth; Neale, Michael Churton

2010-01-01

The increased feasibility of genome-wide association has resulted in association becoming the primary method used to localize genetic variants that cause phenotypic variation. Much attention has been focused on the vast multiple testing problems arising from analyzing large numbers of single nucleotide polymorphisms. However, the inflation of experiment-wise type I error rates through testing numerous phenotypes has received less attention. Multivariate analyses can be used to detect both pleiotropic effects that influence a latent common factor, and monotropic effects that operate at a variable-specific levels, whilst controlling for non-independence between phenotypes. In this study, we present a maximum likelihood approach, which combines both latent and variable-specific tests and which may be used with either individual or family data. Simulation results indicate that in the presence of factor-level association, the combined multivariate (CMV) analysis approach performs well with a minimal loss of power as compared with a univariate analysis of a factor or sum score (SS). As the deviation between the pattern of allelic effects and the factor loadings increases, the power of univariate analyses of both factor and SSs decreases dramatically, whereas the power of the CMV approach is maintained. We show the utility of the approach by examining the association between dopamine receptor D2 TaqIA and the initiation of marijuana, tranquilizers and stimulants in data from the Add Health Study. Perl scripts that takes ped and dat files as input and produces Mx scripts and data for running the CMV approach can be downloaded from www.vipbg.vcu.edu/~sarahme/WriteMx. PMID:19707246

Genetic and environmental influences on dimensional representations of DSM-IV cluster C personality disorders: a population-based multivariate twin study.

PubMed

Reichborn-Kjennerud, Ted; Czajkowski, Nikolai; Neale, Michael C; Ørstavik, Ragnhild E; Torgersen, Svenn; Tambs, Kristian; Røysamb, Espen; Harris, Jennifer R; Kendler, Kenneth S

2007-05-01

The DSM-IV cluster C Axis II disorders include avoidant (AVPD), dependent (DEPD) and obsessive-compulsive (OCPD) personality disorders. We aimed to estimate the genetic and environmental influences on dimensional representations of these disorders and examine the validity of the cluster C construct by determining to what extent common familial factors influence the individual PDs. PDs were assessed using the Structured Interview for DSM-IV Personality (SIDP-IV) in a sample of 1386 young adult twin pairs from the Norwegian Institute of Public Health Twin Panel (NIPHTP). A single-factor independent pathway multivariate model was applied to the number of endorsed criteria for the three cluster C disorders, using the statistical modeling program Mx. The best-fitting model included genetic and unique environmental factors only, and equated parameters for males and females. Heritability ranged from 27% to 35%. The proportion of genetic variance explained by a common factor was 83, 48 and 15% respectively for AVPD, DEPD and OCPD. Common genetic and environmental factors accounted for 54% and 64% respectively of the variance in AVPD and DEPD but only 11% of the variance in OCPD. Cluster C PDs are moderately heritable. No evidence was found for shared environmental or sex effects. Common genetic and individual environmental factors account for a substantial proportion of the variance in AVPD and DEPD. However, OCPD appears to be largely etiologically distinct from the other two PDs. The results do not support the validity of the DSM-IV cluster C construct in its present form.

Gene × dietary pattern interactions in obesity: analysis of up to 68 317 adults of European ancestry.

PubMed

Nettleton, Jennifer A; Follis, Jack L; Ngwa, Julius S; Smith, Caren E; Ahmad, Shafqat; Tanaka, Toshiko; Wojczynski, Mary K; Voortman, Trudy; Lemaitre, Rozenn N; Kristiansson, Kati; Nuotio, Marja-Liisa; Houston, Denise K; Perälä, Mia-Maria; Qi, Qibin; Sonestedt, Emily; Manichaikul, Ani; Kanoni, Stavroula; Ganna, Andrea; Mikkilä, Vera; North, Kari E; Siscovick, David S; Harald, Kennet; Mckeown, Nicola M; Johansson, Ingegerd; Rissanen, Harri; Liu, Yongmei; Lahti, Jari; Hu, Frank B; Bandinelli, Stefania; Rukh, Gull; Rich, Stephen; Booij, Lisanne; Dmitriou, Maria; Ax, Erika; Raitakari, Olli; Mukamal, Kenneth; Männistö, Satu; Hallmans, Göran; Jula, Antti; Ericson, Ulrika; Jacobs, David R; Van Rooij, Frank J A; Deloukas, Panos; Sjögren, Per; Kähönen, Mika; Djousse, Luc; Perola, Markus; Barroso, Inês; Hofman, Albert; Stirrups, Kathleen; Viikari, Jorma; Uitterlinden, André G; Kalafati, Ioanna P; Franco, Oscar H; Mozaffarian, Dariush; Salomaa, Veikko; Borecki, Ingrid B; Knekt, Paul; Kritchevsky, Stephen B; Eriksson, Johan G; Dedoussis, George V; Qi, Lu; Ferrucci, Luigi; Orho-Melander, Marju; Zillikens, M Carola; Ingelsson, Erik; Lehtimäki, Terho; Renström, Frida; Cupples, L Adrienne; Loos, Ruth J F; Franks, Paul W

2015-08-15

Obesity is highly heritable. Genetic variants showing robust associations with obesity traits have been identified through genome-wide association studies. We investigated whether a composite score representing healthy diet modifies associations of these variants with obesity traits. Totally, 32 body mass index (BMI)- and 14 waist-hip ratio (WHR)-associated single nucleotide polymorphisms were genotyped, and genetic risk scores (GRS) were calculated in 18 cohorts of European ancestry (n = 68 317). Diet score was calculated based on self-reported intakes of whole grains, fish, fruits, vegetables, nuts/seeds (favorable) and red/processed meats, sweets, sugar-sweetened beverages and fried potatoes (unfavorable). Multivariable adjusted, linear regression within each cohort followed by inverse variance-weighted, fixed-effects meta-analysis was used to characterize: (a) associations of each GRS with BMI and BMI-adjusted WHR and (b) diet score modification of genetic associations with BMI and BMI-adjusted WHR. Nominally significant interactions (P = 0.006-0.04) were observed between the diet score and WHR-GRS (but not BMI-GRS), two WHR loci (GRB14 rs10195252; LYPLAL1 rs4846567) and two BMI loci (LRRN6C rs10968576; MTIF3 rs4771122), for the respective BMI-adjusted WHR or BMI outcomes. Although the magnitudes of these select interactions were small, our data indicated that associations between genetic predisposition and obesity traits were stronger with a healthier diet. Our findings generate interesting hypotheses; however, experimental and functional studies are needed to determine their clinical relevance. © The Author 2015. Published by Oxford University Press.

Increased genetic risk for obesity in premature coronary artery disease.

PubMed

Cole, Christopher B; Nikpay, Majid; Stewart, Alexandre F R; McPherson, Ruth

2016-04-01

There is ongoing controversy as to whether obesity confers risk for CAD independently of associated risk factors including diabetes mellitus. We have carried out a Mendelian randomization study using a genetic risk score (GRS) for body mass index (BMI) based on 35 risk alleles to investigate this question in a population of 5831 early onset CAD cases without diabetes mellitus and 3832 elderly healthy control subjects, all of strictly European ancestry, with adjustment for traditional risk factors (TRFs). We then estimated the genetic correlation between these BMI and CAD (rg) by relating the pairwise genetic similarity matrix to a phenotypic covariance matrix between these two traits. GRSBMI significantly (P=2.12 × 10(-12)) associated with CAD status in a multivariate model adjusted for TRFs, with a per allele odds ratio (OR) of 1.06 (95% CI 1.042-1.076). The addition of GRSBMI to TRFs explained 0.75% of CAD variance and yielded a continuous net recombination index of 16.54% (95% CI=11.82-21.26%, P<0.0001). To test whether GRSBMI explained CAD status when adjusted for measured BMI, separate models were constructed in which the score and BMI were either included as covariates or not. The addition of BMI explained ~1.9% of CAD variance and GRSBMI plus BMI explained 2.65% of CAD variance. Finally, using bivariate restricted maximum likelihood analysis, we provide strong evidence of genome-wide pleiotropy between obesity and CAD. This analysis supports the hypothesis that obesity is a causal risk factor for CAD.

Gene × dietary pattern interactions in obesity: analysis of up to 68 317 adults of European ancestry

PubMed Central

Nettleton, Jennifer A.; Follis, Jack L.; Ngwa, Julius S.; Smith, Caren E.; Ahmad, Shafqat; Tanaka, Toshiko; Wojczynski, Mary K.; Voortman, Trudy; Lemaitre, Rozenn N.; Kristiansson, Kati; Nuotio, Marja-Liisa; Houston, Denise K.; Perälä, Mia-Maria; Qi, Qibin; Sonestedt, Emily; Manichaikul, Ani; Kanoni, Stavroula; Ganna, Andrea; Mikkilä, Vera; North, Kari E.; Siscovick, David S.; Harald, Kennet; Mckeown, Nicola M.; Johansson, Ingegerd; Rissanen, Harri; Liu, Yongmei; Lahti, Jari; Hu, Frank B.; Bandinelli, Stefania; Rukh, Gull; Rich, Stephen; Booij, Lisanne; Dmitriou, Maria; Ax, Erika; Raitakari, Olli; Mukamal, Kenneth; Männistö, Satu; Hallmans, Göran; Jula, Antti; Ericson, Ulrika; Jacobs,, David R.; Van Rooij, Frank J. A.; Deloukas, Panos; Sjögren, Per; Kähönen, Mika; Djousse, Luc; Perola, Markus; Barroso, Inês; Hofman, Albert; Stirrups, Kathleen; Viikari, Jorma; Uitterlinden, André G.; Kalafati, Ioanna P.; Franco, Oscar H.; Mozaffarian, Dariush; Salomaa, Veikko; Borecki, Ingrid B.; Knekt, Paul; Kritchevsky, Stephen B.; Eriksson, Johan G.; Dedoussis, George V.; Qi, Lu; Ferrucci, Luigi; Orho-Melander, Marju; Zillikens, M. Carola; Ingelsson, Erik; Lehtimäki, Terho; Renström, Frida; Cupples, L. Adrienne; Loos, Ruth J. F.; Franks, Paul W.

2015-01-01

Abstract Obesity is highly heritable. Genetic variants showing robust associations with obesity traits have been identified through genome-wide association studies. We investigated whether a composite score representing healthy diet modifies associations of these variants with obesity traits. Totally, 32 body mass index (BMI)- and 14 waist–hip ratio (WHR)-associated single nucleotide polymorphisms were genotyped, and genetic risk scores (GRS) were calculated in 18 cohorts of European ancestry (n = 68 317). Diet score was calculated based on self-reported intakes of whole grains, fish, fruits, vegetables, nuts/seeds (favorable) and red/processed meats, sweets, sugar-sweetened beverages and fried potatoes (unfavorable). Multivariable adjusted, linear regression within each cohort followed by inverse variance-weighted, fixed-effects meta-analysis was used to characterize: (a) associations of each GRS with BMI and BMI-adjusted WHR and (b) diet score modification of genetic associations with BMI and BMI-adjusted WHR. Nominally significant interactions (P = 0.006–0.04) were observed between the diet score and WHR-GRS (but not BMI-GRS), two WHR loci (GRB14 rs10195252; LYPLAL1 rs4846567) and two BMI loci (LRRN6C rs10968576; MTIF3 rs4771122), for the respective BMI-adjusted WHR or BMI outcomes. Although the magnitudes of these select interactions were small, our data indicated that associations between genetic predisposition and obesity traits were stronger with a healthier diet. Our findings generate interesting hypotheses; however, experimental and functional studies are needed to determine their clinical relevance. PMID:25994509

Estimation and Psychometric Analysis of Component Profile Scores via Multivariate Generalizability Theory

ERIC Educational Resources Information Center

Grochowalski, Joseph H.

2015-01-01

Component Universe Score Profile analysis (CUSP) is introduced in this paper as a psychometric alternative to multivariate profile analysis. The theoretical foundations of CUSP analysis are reviewed, which include multivariate generalizability theory and constrained principal components analysis. Because CUSP is a combination of generalizability…

PTEN Loss as Determined by Clinical-grade Immunohistochemistry Assay Is Associated with Worse Recurrence-free Survival in Prostate Cancer

PubMed Central

Lotan, Tamara L.; Wei, Wei; Morais, Carlos L.; Hawley, Sarah T.; Fazli, Ladan; Hurtado-Coll, Antonio; Troyer, Dean; McKenney, Jesse K.; Simko, Jeffrey; Carroll, Peter R.; Gleave, Martin; Lance, Raymond; Lin, Daniel W.; Nelson, Peter S.; Thompson, Ian M.; True, Lawrence D.; Feng, Ziding; Brooks, James D.

2015-01-01

Background PTEN is the most commonly deleted tumor suppressor gene in primary prostate cancer (PCa) and its loss is associated with poor clinical outcomes and ERG gene rearrangement. Objective We tested whether PTEN loss is associated with shorter recurrence-free survival (RFS) in surgically treated PCa patients with known ERG status. Design, setting, and participants A genetically validated, automated PTEN immunohistochemistry (IHC) protocol was used for 1275 primary prostate tumors from the Canary Foundation retrospective PCa tissue microarray cohort to assess homogeneous (in all tumor tissue sampled) or heterogeneous (in a subset of tumor tissue sampled) PTEN loss. ERG status as determined by a genetically validated IHC assay was available for a subset of 938 tumors. Outcome measurements and statistical analysis Associations between PTEN and ERG status were assessed using Fisher’s exact test. Kaplan-Meier and multivariate weighted Cox proportional models for RFS were constructed. Results and limitations When compared to intact PTEN, homogeneous (hazard ratio [HR] 1.66, p = 0.001) but not heterogeneous (HR 1.24, p = 0.14) PTEN loss was significantly associated with shorter RFS in multivariate models. Among ERG-positive tumors, homogeneous (HR 3.07, p < 0.0001) but not heterogeneous (HR 1.46, p = 0.10) PTEN loss was significantly associated with shorter RFS. Among ERG-negative tumors, PTEN did not reach significance for inclusion in the final multivariate models. The interaction term for PTEN and ERG status with respect to RFS did not reach statistical significance (p = 0.11) for the current sample size. Conclusions These data suggest that PTEN is a useful prognostic biomarker and that there is no statistically significant interaction between PTEN and ERG status for RFS. Patient summary We found that loss of the PTEN tumor suppressor gene in prostate tumors as assessed by tissue staining is correlated with shorter time to prostate cancer recurrence after radical prostatectomy. PMID:27617307

Identification by the DArTseq method of the genetic origin of the Coffea canephora cultivated in Vietnam and Mexico.

PubMed

Garavito, Andrea; Montagnon, Christophe; Guyot, Romain; Bertrand, Benoît

2016-11-04

The coffee species Coffea canephora is commercially identified as "Conilon" when produced in Brazil, or "Robusta" when produced elsewhere in the world. It represents approximately 40 % of coffee production worldwide. While the genetic diversity of wild C. canephora has been well studied in the past, only few studies have addressed the genetic diversity of currently cultivated varieties around the globe. Vietnam is the largest Robusta producer in the world, while Mexico is the only Latin American country, besides Brazil, that has a significant Robusta production. Knowledge of the genetic origin of Robusta cultivated varieties in countries as important as Vietnam and Mexico is therefore of high interest. Through the use of Sequencing-based diversity array technology-DArTseq method-on a collection of C. canephora composed of known accessions and accessions cultivated in Vietnam and Mexico, 4,021 polymorphic SNPs were identified. We used a multivariate analysis using SNP data from reference accessions in order to confirm and further fine-tune the genetic diversity of C. canephora. Also, by interpolating the data obtained for the varieties from Vietnam and Mexico, we determined that they are closely related to each other, and identified that their genetic origin is the Robusta Congo - Uganda group. The genetic characterization based on SNP markers of the varieties grown throughout the world, increased our knowledge on the genetic diversity of C. canephora, and contributed to the understanding of the genetic background of varieties from very important coffee producers. Given the common genetic origin of the Robusta varieties cultivated in Vietnam, Mexico and Uganda, and the similar characteristics of climatic areas and relatively high altitude where they are grown, we can state that the Vietnamese and the Mexican Robusta have the same genetic potential to produce good cup quality.

Effects of UGT1A9 genetic polymorphisms on monohydroxylated derivative of oxcarbazepine concentrations and oxcarbazepine monotherapeutic efficacy in Chinese patients with epilepsy.

PubMed

Lu, Yao; Fang, Youxin; Wu, Xunyi; Ma, Chunlai; Wang, Yue; Xu, Lan

2017-03-01

The human UDP-glucuronosyltransferase which is genetically polymorphic catalyzes glucuronidations of various drugs. The interactions among UGT1A4, UGT1A6, UGT1A9, and UGT2B15 genetic polymorphisms, monohydroxylated derivative (MHD) of oxcarbazepine (OXC) plasma concentrations, and OXC monotherapeutic efficacy were explored in 124 Chinese patients with epilepsy receiving OXC monotherapy. MHD is the major active metabolite of OXC, and its plasma concentration was measured using high-performance liquid chromatography when patients reached their maintenance dose of OXC. Genomic DNA was extracted from whole blood and SNP genotyping performed using PCR followed by dideoxy chain termination sequencing. We followed the patients for at least 1 year to evaluate the OXC monotherapy efficacy. Patients were divided into two groups according to their therapeutic outcome: group 1, seizure free; group 2, not seizure free. The data were analyzed using T test, one-way analysis of variance (ANOVA), Kruskal-Wallis test, chi-square test, Fisher's exact test, correlation analysis, and multivariate regression analysis. T test analysis showed that MHD plasma concentrations were significantly different between the two groups (p = 0.002). One-way ANOVA followed by Bonferroni post hoc testing of four candidate SNPs revealed that carriers of the UGT1A9 variant allele I399 C > T (TT 13.28 ± 7.44 mg/L, TC 16.41 ± 6.53 mg/L) had significantly lower MHD plasma concentrations and poorer seizure control than noncarriers (CC 22.24 ± 8.49 mg/L, p < 0.05). In our study, we have demonstrated the effects of UGT1A9 genetic polymorphisms on MHD plasma concentrations and OXC therapeutic efficacy. Through MHD monitoring, we can predict OXC therapeutic efficacy, which may be useful for the personalization of OXC therapy in epileptic patients.

Chemometrics Methods for Specificity, Authenticity and Traceability Analysis of Olive Oils: Principles, Classifications and Applications

PubMed Central

Messai, Habib; Farman, Muhammad; Sarraj-Laabidi, Abir; Hammami-Semmar, Asma; Semmar, Nabil

2016-01-01

Background. Olive oils (OOs) show high chemical variability due to several factors of genetic, environmental and anthropic types. Genetic and environmental factors are responsible for natural compositions and polymorphic diversification resulting in different varietal patterns and phenotypes. Anthropic factors, however, are at the origin of different blends’ preparation leading to normative, labelled or adulterated commercial products. Control of complex OO samples requires their (i) characterization by specific markers; (ii) authentication by fingerprint patterns; and (iii) monitoring by traceability analysis. Methods. These quality control and management aims require the use of several multivariate statistical tools: specificity highlighting requires ordination methods; authentication checking calls for classification and pattern recognition methods; traceability analysis implies the use of network-based approaches able to separate or extract mixed information and memorized signals from complex matrices. Results. This chapter presents a review of different chemometrics methods applied for the control of OO variability from metabolic and physical-chemical measured characteristics. The different chemometrics methods are illustrated by different study cases on monovarietal and blended OO originated from different countries. Conclusion. Chemometrics tools offer multiple ways for quantitative evaluations and qualitative control of complex chemical variability of OO in relation to several intrinsic and extrinsic factors. PMID:28231172

Support vector regression and artificial neural network models for stability indicating analysis of mebeverine hydrochloride and sulpiride mixtures in pharmaceutical preparation: A comparative study

NASA Astrophysics Data System (ADS)

Naguib, Ibrahim A.; Darwish, Hany W.

2012-02-01

A comparison between support vector regression (SVR) and Artificial Neural Networks (ANNs) multivariate regression methods is established showing the underlying algorithm for each and making a comparison between them to indicate the inherent advantages and limitations. In this paper we compare SVR to ANN with and without variable selection procedure (genetic algorithm (GA)). To project the comparison in a sensible way, the methods are used for the stability indicating quantitative analysis of mixtures of mebeverine hydrochloride and sulpiride in binary mixtures as a case study in presence of their reported impurities and degradation products (summing up to 6 components) in raw materials and pharmaceutical dosage form via handling the UV spectral data. For proper analysis, a 6 factor 5 level experimental design was established resulting in a training set of 25 mixtures containing different ratios of the interfering species. An independent test set consisting of 5 mixtures was used to validate the prediction ability of the suggested models. The proposed methods (linear SVR (without GA) and linear GA-ANN) were successfully applied to the analysis of pharmaceutical tablets containing mebeverine hydrochloride and sulpiride mixtures. The results manifest the problem of nonlinearity and how models like the SVR and ANN can handle it. The methods indicate the ability of the mentioned multivariate calibration models to deconvolute the highly overlapped UV spectra of the 6 components' mixtures, yet using cheap and easy to handle instruments like the UV spectrophotometer.

The genetic links between the big five personality traits and general interest domains.

PubMed

Kandler, Christian; Bleidorn, Wiebke; Riemann, Rainer; Angleitner, Alois; Spinath, Frank M

2011-12-01

This is the first genetically informative study in which multiple informants were used to quantify the genetic and environmental sources of individual differences in general interests as well as the phenotypic and genetic links between general interests and Big Five personality traits. Self-reports and two peer ratings from 844 individuals, including 225 monozygotic and 113 dizygotic complete twin pairs, were collected. Multiple-rater scores (composites) revealed that the averaged levels of genetic and environmental effects on seven broad interest domains were similar to those on personality traits. Multivariate analyses showed that about 35% of the genetic and 9% of the environmental variance in interests were explained by personality domains, in particular by Openness. The findings suggest that interests cannot easily be considered as a byproduct of the interactions between personality genotypes and the environmental influences but rather as an internal regulation of behavior with an own genetic basis.

The genetic epidemiology of personality disorders

PubMed Central

Reichborn-Kjennerud, Ted

2010-01-01

Genetic epidemiologic studies indicate that all ten personality disorders (PDs) classified on the DSM-IV axis II are modestly to moderately heritable. Shared environmental and nonadditive genetic factors are of minor or no importance. No sex differences have been identified. Multivariate studies suggest that the extensive comorbidity between the PDs can be explained by three common genetic and environmental risk factors. The genetic factors do not reflect the DSM-IV cluster structure, but rather: i) broad vulnerability to PD pathology or negative emotionality; ii) high impulsivity/low agreeableness; and iii) introversion. Common genetic and environmental liability factors contribute to comorbidity between pairs or clusters of axis I and axis II disorders. Molecular genetic studies of PDs, mostly candidate gene association studies, indicate that genes linked to neurotransmitter pathways, especially in the serotonergic and dopaminergic systems, are involved. Future studies, using newer methods like genome-wide association, might take advantage of the use of endophenotypes. PMID:20373672

Genetic specificity of face recognition.

PubMed

Shakeshaft, Nicholas G; Plomin, Robert

2015-10-13

Specific cognitive abilities in diverse domains are typically found to be highly heritable and substantially correlated with general cognitive ability (g), both phenotypically and genetically. Recent twin studies have found the ability to memorize and recognize faces to be an exception, being similarly heritable but phenotypically substantially uncorrelated both with g and with general object recognition. However, the genetic relationships between face recognition and other abilities (the extent to which they share a common genetic etiology) cannot be determined from phenotypic associations. In this, to our knowledge, first study of the genetic associations between face recognition and other domains, 2,000 18- and 19-year-old United Kingdom twins completed tests assessing their face recognition, object recognition, and general cognitive abilities. Results confirmed the substantial heritability of face recognition (61%), and multivariate genetic analyses found that most of this genetic influence is unique and not shared with other cognitive abilities.

Genetic specificity of face recognition

PubMed Central

Shakeshaft, Nicholas G.; Plomin, Robert

2015-01-01

Specific cognitive abilities in diverse domains are typically found to be highly heritable and substantially correlated with general cognitive ability (g), both phenotypically and genetically. Recent twin studies have found the ability to memorize and recognize faces to be an exception, being similarly heritable but phenotypically substantially uncorrelated both with g and with general object recognition. However, the genetic relationships between face recognition and other abilities (the extent to which they share a common genetic etiology) cannot be determined from phenotypic associations. In this, to our knowledge, first study of the genetic associations between face recognition and other domains, 2,000 18- and 19-year-old United Kingdom twins completed tests assessing their face recognition, object recognition, and general cognitive abilities. Results confirmed the substantial heritability of face recognition (61%), and multivariate genetic analyses found that most of this genetic influence is unique and not shared with other cognitive abilities. PMID:26417086

Clinical-genetic model predicts incident impulse control disorders in Parkinson's disease.

PubMed

Kraemmer, Julia; Smith, Kara; Weintraub, Daniel; Guillemot, Vincent; Nalls, Mike A; Cormier-Dequaire, Florence; Moszer, Ivan; Brice, Alexis; Singleton, Andrew B; Corvol, Jean-Christophe

2016-10-01

Impulse control disorders (ICD) are commonly associated with dopamine replacement therapy (DRT) in patients with Parkinson's disease (PD). Our aims were to estimate ICD heritability and to predict ICD by a candidate genetic multivariable panel in patients with PD. Data from de novo patients with PD, drug-naïve and free of ICD behaviour at baseline, were obtained from the Parkinson's Progression Markers Initiative cohort. Incident ICD behaviour was defined as positive score on the Questionnaire for Impulsive-Compulsive Disorders in PD. ICD heritability was estimated by restricted maximum likelihood analysis on whole exome sequencing data. 13 candidate variants were selected from the DRD2, DRD3, DAT1, COMT, DDC, GRIN2B, ADRA2C, SERT, TPH2, HTR2A, OPRK1 and OPRM1 genes. ICD prediction was evaluated by the area under the curve (AUC) of receiver operating characteristic (ROC) curves. Among 276 patients with PD included in the analysis, 86% started DRT, 40% were on dopamine agonists (DA), 19% reported incident ICD behaviour during follow-up. We found heritability of this symptom to be 57%. Adding genotypes from the 13 candidate variants significantly increased ICD predictability (AUC=76%, 95% CI (70% to 83%)) compared to prediction based on clinical variables only (AUC=65%, 95% CI (58% to 73%), p=0.002). The clinical-genetic prediction model reached highest accuracy in patients initiating DA therapy (AUC=87%, 95% CI (80% to 93%)). OPRK1, HTR2A and DDC genotypes were the strongest genetic predictive factors. Our results show that adding a candidate genetic panel increases ICD predictability, suggesting potential for developing clinical-genetic models to identify patients with PD at increased risk of ICD development and guide DRT management. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/

Scope of Gradient and Genetic Algorithms in Multivariable Function Optimization

NASA Technical Reports Server (NTRS)

Shaykhian, Gholam Ali; Sen, S. K.

2007-01-01

Global optimization of a multivariable function - constrained by bounds specified on each variable and also unconstrained - is an important problem with several real world applications. Deterministic methods such as the gradient algorithms as well as the randomized methods such as the genetic algorithms may be employed to solve these problems. In fact, there are optimization problems where a genetic algorithm/an evolutionary approach is preferable at least from the quality (accuracy) of the results point of view. From cost (complexity) point of view, both gradient and genetic approaches are usually polynomial-time; there are no serious differences in this regard, i.e., the computational complexity point of view. However, for certain types of problems, such as those with unacceptably erroneous numerical partial derivatives and those with physically amplified analytical partial derivatives whose numerical evaluation involves undesirable errors and/or is messy, a genetic (stochastic) approach should be a better choice. We have presented here the pros and cons of both the approaches so that the concerned reader/user can decide which approach is most suited for the problem at hand. Also for the function which is known in a tabular form, instead of an analytical form, as is often the case in an experimental environment, we attempt to provide an insight into the approaches focusing our attention toward accuracy. Such an insight will help one to decide which method, out of several available methods, should be employed to obtain the best (least error) output. *

Shared genetic determinants of axial length and height in children: the Guangzhou twin eye study.

PubMed

Zhang, Jian; Hur, Yoon-Mi; Huang, Wenyong; Ding, Xiaohu; Feng, Ke; He, Mingguang

2011-01-01

To describe the association between axial length (AL) and height and to estimate the extent to which shared genetic or environmental factors influence this covariance. Study participants were recruited from the Guangzhou Twin Registry. Axial length was measured using partial coherence laser interferometry. Height was measured with the participants standing without shoes. We computed twin pairwise correlations and cross-twin cross-trait correlations between AL and height for monozygotic and dizygotic twins and performed model-fitting analyses using a multivariate Cholesky model. The right eye was arbitrarily selected to represent AL of participants. Five hundred sixty-five twin pairs (359 monozygotic and 206 dizygotic) aged 7 to 15 years were available for analysis. Phenotypic correlation between AL and height was 0.46 but decreased to 0.19 after adjusting for age, sex, and age × sex interaction. Bivariate Cholesky model-fitting analyses revealed that 89% of phenotypic correlation was due to shared genetic factors and 11% was due to shared random environmental factors, which includes measurement error. Covariance of AL and height is largely attributable to shared genes. Given that AL is a key determinant of myopia, further work is needed to confirm gene sharing between myopia and stature.

Beyond the big five: the Dark Triad and the supernumerary personality inventory.

PubMed

Veselka, Livia; Schermer, Julie Aitken; Vernon, Philip A

2011-04-01

The Dark Triad of personality, comprising Machiavellianism, narcissism, and psychopathy, was investigated in relation to the Supernumerary Personality Inventory (SPI) traits, because both sets of variables are predominantly distinct from the Big Five model of personality. Correlational and principal factor analyses were conducted to assess the relations between the Dark Triad and SPI traits. Multivariate behavioral genetic model-fitting analyses were also conducted to determine the correlated genetic and/or environmental underpinnings of the observed phenotypic correlations. Participants were 358 monozygotic and 98 same-sex dizygotic adult twin pairs from North America. As predicted, results revealed significant correlations between the Dark Triad and most SPI traits, and these correlations were primarily attributable to common genetic and non-shared environmental factors, except in the case of Machiavellianism, where shared environmental effects emerged. Three correlated factors were extracted during joint factor analysis of the Dark Triad and SPI traits, as well as a heritable general factor of personality - results that clarified the structure of the Dark Triad construct. It is concluded that the Dark Triad represents an exploitative and antisocial construct that extends beyond the Big Five model and shares a theoretical space with the SPI traits.

Association of genetic polymorphisms of telomere binding proteins with cholinesterase activity in omethoate-exposed workers.

PubMed

Ding, Mingcui; Yang, Yongli; Duan, Xiaoran; Wang, Sihua; Feng, Xiaolei; Wang, Tuanwei; Wang, Pengpeng; Liu, Suxiang; Li, Lei; Liu, Junling; Tang, Lixia; Niu, Xinhua; Zhang, Yuhong; Li, Guoyu; Yao, Wu; Cui, Liuxin; Wang, Wei

2018-06-18

Omethoate, an organophosphorous pesticide, can cause a variety of health effects, especially the decrease of cholinesterase activity. The aim of this study is to explore the association of genetic polymorphisms of telomere binding proteins with cholinesterase activity in omethoate-exposed population. Cholinesterase activities in whole blood, red blood cell and plasma were detected using acetylthiocholine and dithio-bis-(nitrobenzoic acid) method; Genetic Genotyping of POT1 rs1034794, POT1 rs10250202, TERF1 rs3863242 and TERT rs2736098 were performed with PCR-RFLP. The cholinesterase activities of whole blood, red blood cells and plasma in exposure group are significantly lower than that of the control group (P < 0.001). Multivariate analysis indicates that exposure group (b = - 1.016, P < 0.001), agender (b = 0.365, P < 0.001), drinking (b = 0.271, P = 0.004) and TERF1rs3863242 (b = - 0.368, P = 0.016) had an impact on cholinesterase activities. The results suggest that individual carrying AG+GG genotypes in TERF1 gene rs3863242 polymorphism were susceptible to damage in cholinesterase induced by omethoate. Copyright © 2018 Elsevier Inc. All rights reserved.

Evolving Attractive Faces Using Morphing Technology and a Genetic Algorithm: A New Approach to Determining Ideal Facial Aesthetics

PubMed Central

Wong, Brian J. F.; Karmi, Koohyar; Devcic, Zlatko; McLaren, Christine E.; Chen, Wen-Pin

2013-01-01

Objectives The objectives of this study were to: 1) determine if a genetic algorithm in combination with morphing software can be used to evolve more attractive faces; and 2) evaluate whether this approach can be used as a tool to define or identify the attributes of the ideal attractive face. Study Design Basic research study incorporating focus group evaluations. Methods Digital images were acquired of 250 female volunteers (18–25 y). Randomly selected images were used to produce a parent generation (P) of 30 synthetic faces using morphing software. Then, a focus group of 17 trained volunteers (18–25 y) scored each face on an attractiveness scale ranging from 1 (unattractive) to 10 (attractive). A genetic algorithm was used to select 30 new pairs from the parent generation, and these were morphed using software to produce a new first generation (F1) of faces. The F1 faces were scored by the focus group, and the process was repeated for a total of four iterations of the algorithm. The algorithm mimics natural selection by using the attractiveness score as the selection pressure; the more attractive faces are more likely to morph. All five generations (P-F4) were then scored by three focus groups: a) surgeons (n = 12), b) cosmetology students (n = 44), and c) undergraduate students (n = 44). Morphometric measurements were made of 33 specific features on each of the 150 synthetic faces, and correlated with attractiveness scores using univariate and multivariate analysis. Results The average facial attractiveness scores increased with each generation and were 3.66 (+0.60), 4.59 (±0.73), 5.50 (±0.62), 6.23 (±0.31), and 6.39 (±0.24) for P and F1–F4 generations, respectively. Histograms of attractiveness score distributions show a significant shift in the skew of each curve toward more attractive faces with each generation. Univariate analysis identified nasal width, eyebrow arch height, and lip thickness as being significantly correlated with attractiveness scores. Multivariate analysis identified a similar collection of morphometric measures. No correlation with more commonly accepted measures such as the length facial thirds or fifths were identified. When images are examined as a montage (by generation), clear distinct trends are identified: oval shaped faces, distinct arched eyebrows, and full lips predominate. Faces evolve to approximate the guidelines suggested by classical canon. F3 and F4 generation faces look profoundly similar. The statistical and qualitative analysis indicates that the algorithm and methodology succeeds in generating successively more attractive faces. Conclusions The use of genetic algorithms in combination with a morphing software and traditional focus-group derived attractiveness scores can be used to evolve attractive synthetic faces. We have demonstrated that the evolution of attractive faces can be mimicked in software. Genetic algorithms and morphing provide a robust alternative to traditional approaches rooted in comparing attractiveness scores with a series of morphometric measurements in human subjects. PMID:18401273

A genetic variant in the LDLR promoter is responsible for part of the LDL-cholesterol variability in primary hypercholesterolemia

PubMed Central

2014-01-01

Background GWAS have consistently revealed that LDLR locus variability influences LDL-cholesterol in general population. Severe LDLR mutations are responsible for familial hypercholesterolemia (FH). However, most primary hypercholesterolemias are polygenic diseases. Although Cis-regulatory regions might be the cause of LDL-cholesterol variability; an extensive analysis of the LDLR distal promoter has not yet been performed. We hypothesized that genetic variants in this region are responsible for the LDLR association with LDL-cholesterol found in GWAS. Methods Four-hundred seventy-seven unrelated subjects with polygenic hypercholesterolemia (PH) and without causative FH-mutations and 525 normolipemic subjects were selected. A 3103 pb from LDLR (-625 to +2468) was sequenced in 125 subjects with PH. All subjects were genotyped for 4 SNPs (rs17242346, rs17242739, rs17248720 and rs17249120) predicted to be potentially involved in transcription regulation by in silico analysis. EMSA and luciferase assays were carried out for the rs17248720 variant. Multivariable linear regression analysis using LDL-cholesterol levels as the dependent variable were done in order to find out the variables that were independently associated with LDL-cholesterol. Results The sequencing of the 125 PH subjects did not show variants with minor allele frequency ≥ 10%. The T-allele from g.3131C > T (rs17248720) had frequencies of 9% (PH) and 16.4% (normolipemic), p < 0.00001. Studies of this variant with EMSA and luciferase assays showed a higher affinity for transcription factors and an increase of 2.5 times in LDLR transcriptional activity (T-allele vs C-allele). At multivariate analysis, this polymorphism with the lipoprotein(a) and age explained ≈ 10% of LDL-cholesterol variability. Conclusion Our results suggest that the T-allele at the g.3131 T > C SNP is associated with LDL-cholesterol levels, and explains part of the LDL-cholesterol variability. As a plausible cause, the T-allele produces an increase in LDLR transcriptional activity and lower LDL-cholesterol levels. PMID:24708769

Multivariate meta-analysis: potential and promise.

PubMed

Jackson, Dan; Riley, Richard; White, Ian R

2011-09-10

The multivariate random effects model is a generalization of the standard univariate model. Multivariate meta-analysis is becoming more commonly used and the techniques and related computer software, although continually under development, are now in place. In order to raise awareness of the multivariate methods, and discuss their advantages and disadvantages, we organized a one day 'Multivariate meta-analysis' event at the Royal Statistical Society. In addition to disseminating the most recent developments, we also received an abundance of comments, concerns, insights, critiques and encouragement. This article provides a balanced account of the day's discourse. By giving others the opportunity to respond to our assessment, we hope to ensure that the various view points and opinions are aired before multivariate meta-analysis simply becomes another widely used de facto method without any proper consideration of it by the medical statistics community. We describe the areas of application that multivariate meta-analysis has found, the methods available, the difficulties typically encountered and the arguments for and against the multivariate methods, using four representative but contrasting examples. We conclude that the multivariate methods can be useful, and in particular can provide estimates with better statistical properties, but also that these benefits come at the price of making more assumptions which do not result in better inference in every case. Although there is evidence that multivariate meta-analysis has considerable potential, it must be even more carefully applied than its univariate counterpart in practice. Copyright © 2011 John Wiley & Sons, Ltd.

Four factors underlying mouse behavior in an open field

PubMed Central

Tanaka, Shoji; Young, Jared W.; Halberstadt, Adam L.; Masten, Virginia L.; Geyer, Mark A.

2012-01-01

The observation of the locomotor and exploratory behaviors of rodents in an open field is one of the most fundamental methods used in the field of behavioral pharmacology. A variety of behaviors can be recorded automatically and can readily generate a multivariate pattern of pharmacological effects. Nevertheless, the optimal ways to characterize observed behaviors and concomitant drug effects are still under development. The aim of this study was to extract meaningful behavioral factors that could explain variations in the observed variables from mouse exploration. Behavioral data were recorded from male C57BL/6J mice (n = 268) using the Behavioral Pattern Monitor (BPM). The BPM data were subjected to the exploratory factor analysis. The factor analysis extracted four factors: activity, sequential organization, diversive exploration, and inspective exploration. The activity factor and the two types of exploration factors correlated positively with one another, while the sequential organization factor negatively correlated with the remaining factors. The extracted factor structure constitutes a behavioral model of mouse exploration. This model will provide a platform on which one can assess the effects of psychoactive drugs and genetic manipulations on mouse exploratory behavior. Further studies are currently underway to examine the factor structure of similar multivariate data sets from humans tested in a human BPM. PMID:22569582

Four factors underlying mouse behavior in an open field.

PubMed

Tanaka, Shoji; Young, Jared W; Halberstadt, Adam L; Masten, Virginia L; Geyer, Mark A

2012-07-15

The observation of the locomotor and exploratory behaviors of rodents in an open field is one of the most fundamental methods used in the field of behavioral pharmacology. A variety of behaviors can be recorded automatically and can readily generate a multivariate pattern of pharmacological effects. Nevertheless, the optimal ways to characterize observed behaviors and concomitant drug effects are still under development. The aim of this study was to extract meaningful behavioral factors that could explain variations in the observed variables from mouse exploration. Behavioral data were recorded from male C57BL/6J mice (n=268) using the Behavioral Pattern Monitor (BPM). The BPM data were subjected to the exploratory factor analysis. The factor analysis extracted four factors: activity, sequential organization, diversive exploration, and inspective exploration. The activity factor and the two types of exploration factors correlated positively with one another, while the sequential organization factor negatively correlated with the remaining factors. The extracted factor structure constitutes a behavioral model of mouse exploration. This model will provide a platform on which one can assess the effects of psychoactive drugs and genetic manipulations on mouse exploratory behavior. Further studies are currently underway to examine the factor structure of similar multivariate data sets from humans tested in a human BPM. Copyright © 2012 Elsevier B.V. All rights reserved.

Genetic polymorphisms in pre-miRNAs predict the survival of non-small-cell lung cancer in Chinese population: a cohort study and a meta-analysis

PubMed Central

Xia, Lingzi; Yin, Zhihua; Li, Xuelian; Ren, Yangwu; Zhang, Haibo; Zhao, Yuxia; Zhou, Baosen

2017-01-01

Background To explore the association of genetic polymorphisms in pre-miRNA 30c-1 rs928508 and pre-miRNA 27a rs895819 with non-small-cell lung cancer prognosis. Materials and Methods 480 patients from five hospitals were enrolled in this prospective cohort study. They were followed up for five years. The association between genotypes and overall survival was assessed by Cox proportional hazards regression models. A meta-analysis was conducted to provide evidence for the effect of microRNA 27a rs895819 on cancer survival. Results G-allele containing genotypes of microRNA 30c-1 polymorphisms and C-allele containing genotypes of microRNA 27a were significantly associated with poorer overall survival. Multivariate Cox regression models indicated that these genetic polymorhpisms were independently predictive factors of poorer overall survival. In stratified analysis, the effect was observed in many strata. The significant joint effect was also observed in our study. Patients with G allele of microRNA 30c-1 rs928508 and C allele of microRNA 27a rs895819 had the poorer overall survival than patients with C allele of rs928508 and T allele of rs895819. The effect of the microRNA 27a rs895819 on non-small cell lung cancer overall survival was supported by the meta-analysis results. Conclusions The two single nucleotide polymorphisms in microRNA 30c-1 and microRNA 27a can predict the outcome of non-small cell lung cancer patients and they may decrease the sensitivity to anti-cancer drugs. PMID:29100439

Genetic analysis of body weights of individually fed beef bulls in South Africa using random regression models.

PubMed

Selapa, N W; Nephawe, K A; Maiwashe, A; Norris, D

2012-02-08

The aim of this study was to estimate genetic parameters for body weights of individually fed beef bulls measured at centralized testing stations in South Africa using random regression models. Weekly body weights of Bonsmara bulls (N = 2919) tested between 1999 and 2003 were available for the analyses. The model included a fixed regression of the body weights on fourth-order orthogonal Legendre polynomials of the actual days on test (7, 14, 21, 28, 35, 42, 49, 56, 63, 70, 77, and 84) for starting age and contemporary group effects. Random regressions on fourth-order orthogonal Legendre polynomials of the actual days on test were included for additive genetic effects and additional uncorrelated random effects of the weaning-herd-year and the permanent environment of the animal. Residual effects were assumed to be independently distributed with heterogeneous variance for each test day. Variance ratios for additive genetic, permanent environment and weaning-herd-year for weekly body weights at different test days ranged from 0.26 to 0.29, 0.37 to 0.44 and 0.26 to 0.34, respectively. The weaning-herd-year was found to have a significant effect on the variation of body weights of bulls despite a 28-day adjustment period. Genetic correlations amongst body weights at different test days were high, ranging from 0.89 to 1.00. Heritability estimates were comparable to literature using multivariate models. Therefore, random regression model could be applied in the genetic evaluation of body weight of individually fed beef bulls in South Africa.

Pleiotropy and genotype by diet interaction: A multivariate genetic analysis of HDL-C subfractions

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

Mahaney, M.C.; Blangero, J.; Comuzzie, A.G.

1994-09-01

Reduced high density lipoprotein cholesterol (HDL-C) is a risk factor for cardiovascular disease in humans. Both major genes and major genotype by diet interaction have been reported for HDL-C, but the genetics of the HDL-C subfractions are less well known. In a baboon model for human atherosclerosis, we investigated the pleiotropic effects of genes on normal quantitative variation in three HDL-C subfractions (HDL{sub 1}-C, HDL{sub 2}-C, and HDL{sub 3}-C) in two dietary environments -- a basal diet and a 7 week high cholesterol, saturated fat (HCSF) diet. We analyzed data on serum HDL-C subfraction levels, quantified by gradient gel eletrophoresis,more » for 942 baboons (Papo hamadryas, sensu lato) from 17 pedigrees. We used multivariate maximum likelihood methods to simultaneously estimate phenotypic means, standard deviations, and heritabilities (h{sup 2}); effects of sex, age-by-sex, age{sup 2}-by-sex, percent subspecies admixture, and infant feeding modality; plus estimated significant h{sup 2} values for all three subfractions on both diets. When tested within dietary environments, we obtained significant genetic correlations between all three subfractions [i.e., P({rho}{sub G} = 0) < 0.001] and evidence of complete pleiotropy [i.e., P({vert_bar}{rho}{sub G}{vert_bar} = 1.0) > 0.1] between HDL{sub 1}-C and HDL{sub 3}-C ({rho}{sub G} = 0.81) on the basal diet. On the HCSF diet, only the genetic correlation between HDL{sub 1}-C and HDL{sub 3}-C ({rho}{sub g} = 0.61) was significant (p > 0.1). Complete pleiotropy was observed for each of the three subfractions between both diets. Given these results, we reject genotype by diet interaction for HDL{sub 1}-C, HDL{sub 2}-C or HDL{sub 3}-C; i.e., the same genes influence variation in each subfraction to the same degree on either diet. However, the apparent disruption of pleiotropy between HDL{sub 2}-C and the other two subfractions needs to be investigated further.« less

Association of donor and recipient SUMO4 rs237025 genetic variant with new-onset diabetes mellitus after liver transplantation in a Chinese population.

PubMed

Zhang, Tao; Liu, Yuan; Hu, Yibo; Zhang, Xiaoqing; Zhong, Lin; Fan, Junwei; Peng, Zhihai

2017-09-05

New-onset diabetes mellitus (NODM) is a common complication after liver transplantation (LT). The small ubiquitin-like modifier 4 (SUMO4) rs237025 polymorphism has been reported to be associated with type 2 diabetes mellitus (T2DM). In this study, we aimed to evaluate the association of donor and recipient SUMO4 rs237025 polymorphisms with NODM and the long-term consequences of NODM after LT. A total of 126 liver transplant patients were enrolled in the study. One single nucleotide polymorphism, SUMO4 rs237025, was genotyped in both donors and recipients. Both donor and recipient SUMO4 rs237025 polymorphisms were found to be significantly associated with NODM after LT. In multivariate analysis, recipient age>50 years, tacrolimus trough concentrations>10ng/mL at 1month after LT, donor and recipient rs237025 genetic variant, and the combined donor and recipient rs237025 genetic variant were independent predictive factors of NODM. Area under the receiver operating characteristic curve (AUROC) analysis indicated the higher predictive ability of the model containing combined donor and recipient rs237025 polymorphisms than the clinical model (p=0.046). Furthermore, Kaplan-Meier survival analysis demonstrated that NODM was related to significantly poorer patient survival in comparison with non-NODM patients (p=0.041). Both donor and recipient SUMO4 rs237025 polymorphisms contribute to the development of NODM after LT and NODM is a frequent complication that negatively affects patient survival. Copyright © 2017. Published by Elsevier B.V.

Genetic Variability among Lucerne Cultivars Based on Biochemical (SDS-PAGE) and Morphological Markers

NASA Astrophysics Data System (ADS)

Farshadfar, M.; Farshadfar, E.

The present research was conducted to determine the genetic variability of 18 Lucerne cultivars, based on morphological and biochemical markers. The traits studied were plant height, tiller number, biomass, dry yield, dry yield/biomass, dry leaf/dry yield, macro and micro elements, crude protein, dry matter, crude fiber and ash percentage and SDS- PAGE in seed and leaf samples. Field experiments included 18 plots of two meter rows. Data based on morphological, chemical and SDS-PAGE markers were analyzed using SPSSWIN soft ware and the multivariate statistical procedures: cluster analysis (UPGMA), principal component. Analysis of analysis of variance and mean comparison for morphological traits reflected significant differences among genotypes. Genotype 13 and 15 had the greatest values for most traits. The Genotypic Coefficient of Variation (GCV), Phenotypic Coefficient of Variation (PCV) and Heritability (Hb) parameters for different characters raged from 12.49 to 26.58% for PCV, hence the GCV ranged from 6.84 to 18.84%. The greatest value of Hb was 0.94 for stem number. Lucerne genotypes could be classified, based on morphological traits, into four clusters and 94% of the variance among the genotypes was explained by two PCAs: Based on chemical traits they were classified into five groups and 73.492% of variance was explained by four principal components: Dry matter, protein, fiber, P, K, Na, Mg and Zn had higher variance. Genotypes based on the SDS-PAGE patterns all genotypes were classified into three clusters. The greatest genetic distance was between cultivar 10 and others, therefore they would be suitable parent in a breeding program.

Association of functional MMP-2 gene variant with intracranial aneurysms: case-control genetic association study and meta-analysis.

PubMed

Alg, Varinder S; Ke, Xiayi; Grieve, Joan; Bonner, Stephen; Walsh, Daniel C; Bulters, Diederik; Kitchen, Neil; Houlden, Henry; Werring, David J

2018-01-15

Abnormalities in Matrix Metalloproteinase (MMP) genes, which are important in extracellular matrix (ECM) maintenance and therefore arterial wall integrity are a plausible underlying mechanism of intracranial aneurysm (IA) formation, growth and subsequent rupture. We investigated whether the rs243865 C > T SNP (single nucleotide polymorphism) within the MMP-2 gene (which influences gene transcription) is associated with IA compared to matched controls. We conducted a case-control genetic association study, adjusted for known IA risk factors (smoking and hypertension), in a UK Caucasian population of 1409 patients with intracranial aneurysms (IA), and 1290 matched controls, to determine the association of the rs243865 C > T functional MMP-2 gene SNP with IA (overall, and classified as ruptured and unruptured). We also undertook a meta-analysis of two previous studies examining this SNP. The rs243865 T allele was associated with IA presence in univariate (OR 1.18 [95% CI 1.04-1.33], p = .01) and in multi-variable analyses adjusted for smoking and hypertension status (OR 1.16 [95% CI 1.01-1.35], p = .042). Subgroup analysis demonstrated an association of the rs243865 SNP with ruptured IA (OR 1.18 [95% CI 1.03-1.34] p = .017), but, not unruptured IA (OR 1.17 [95% CI 0.97-1.42], p = .11). Our study demonstrated an association between the functional MMP-2 rs243865 variant and IAs. Our findings suggest a genetic role for altered extracellular matrix integrity in the pathogenesis of IA development and rupture.

The influence of habitats on female mobility in Central and Western Africa inferred from human mitochondrial variation

PubMed Central

2013-01-01

Background When studying the genetic structure of human populations, the role of cultural factors may be difficult to ascertain due to a lack of formal models. Linguistic diversity is a typical example of such a situation. Patrilocality, on the other hand, can be integrated into a biological framework, allowing the formulation of explicit working hypotheses. The present study is based on the assumption that patrilocal traditions make the hypervariable region I of the mtDNA a valuable tool for the exploration of migratory dynamics, offering the opportunity to explore the relationships between genetic and linguistic diversity. We studied 85 Niger-Congo-speaking patrilocal populations that cover regions from Senegal to Central African Republic. A total of 4175 individuals were included in the study. Results By combining a multivariate analysis aimed at investigating the population genetic structure, with a Bayesian approach used to test models and extent of migration, we were able to detect a stepping-stone migration model as the best descriptor of gene flow across the region, with the main discontinuities corresponding to forested areas. Conclusions Our analyses highlight an aspect of the influence of habitat variation on human genetic diversity that has yet to be understood. Rather than depending simply on geographic linear distances, patterns of female genetic variation vary substantially between savannah and rainforest environments. Our findings may be explained by the effects of recent gene flow constrained by environmental factors, which superimposes on a background shaped by pre-agricultural peopling. PMID:23360301

The heritability of mental health and wellbeing defined using COMPAS-W, a new composite measure of wellbeing.

PubMed

Gatt, Justine M; Burton, Karen L O; Schofield, Peter R; Bryant, Richard A; Williams, Leanne M

2014-09-30

Mental health is not simply the absence of mental illness; rather it is a distinct entity representing wellness. Models of wellbeing have been proposed that emphasize components of subjective wellbeing, psychological wellbeing, or a combination of both. A new 26-item scale of wellbeing (COMPAS-W) was developed in a cohort of 1669 healthy adult twins (18-61 years). The scale was derived using factor analysis of multiple scales of complementary constructs and confirmed using tests of reliability and convergent validity. Bivariate genetic modeling confirmed its heritability. From an original 89 items we identified six independent subcomponents that contributed to wellbeing. The COMPAS-W scale and its subcomponents showed construct validity against psychological and physical health behaviors, high internal consistency (average r=0.71, Wellbeing r=0.84), and 12-month test-retest reliability (average r=0.62, Wellbeing r=0.82). There was a moderate contribution of genetics to total Wellbeing (heritability h(2)=48%) and its subcomponents: Composure (h(2)=24%), Own-worth (h(2)=42%), Mastery (h(2)=40%), Positivity (h(2)=42%), Achievement (h(2)=32%) and Satisfaction (h(2)=43%). Multivariate genetic modeling indicated genetic variance was correlated across the scales, suggesting common genetic factors contributed to Wellbeing and its subcomponents. The COMPAS-W scale provides a validated indicator of wellbeing and offers a new tool to quantify mental health. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Nature vs nurture: are leaders born or made? A behavior genetic investigation of leadership style.

PubMed

Johnson, A M; Vernon, P A; McCarthy, J M; Molson, M; Harris, J A; Jang, K L

1998-12-01

With the recent resurgence in popularity of trait theories of leadership, it is timely to consider the genetic determination of the multiple factors comprising the leadership construct. Individual differences in personality traits have been found to be moderately to highly heritable, and so it follows that if there are reliable personality trait differences between leaders and non-leaders, then there may be a heritable component to these individual differences. Despite this connection between leadership and personality traits, however, there are no studies of the genetic basis of leadership using modern behavior genetic methodology. The present study proposes to address the lack of research in this area by examining the heritability of leadership style, as measured by self-report psychometric inventories. The Multifactor Leadership Questionnaire (MLQ), the Leadership Ability Evaluation, and the Adjective Checklist were completed by 247 adult twin pairs (183 monozygotic and 64 same-sex dizygotic). Results indicated that most of the leadership dimensions examined in this study are heritable, as are two higher level factors (resembling transactional and transformational leadership) derived from an obliquely rotated principal components factors analysis of the MLQ. Univariate analyses suggested that 48% of the variance in transactional leadership may be explained by additive heritability, and 59% of the variance in transformational leadership may be explained by non-additive (dominance) heritability. Multivariate analyses indicated that most of the variables studied shared substantial genetic covariance, suggesting a large overlap in the underlying genes responsible for the leadership dimensions.

Participation of Korean families at high risk for hereditary breast and ovarian cancer in BRCA1/2 genetic testing.

PubMed

Sun, Young; Kang, Eunyoung; Baek, Hyunnam; Jung, Jaehag; Hwang, Euijun; Koo, Jauk; Kim, Eun-Kyu; Kim, Sung-Won

2015-06-01

The aim of our study was to determine the rate of participation in genetic testing, to determine the reasons for non-participation and to identify the factors affecting participation in BRCA genetic testing for high-risk patients. This study was performed through a retrospective review of 804 individuals who underwent genetic counseling for BRCA1/2 gene mutations at Seoul National University Bundang Hospital between July 2003 and September 2012. In total, 728 (90.5%) individuals underwent BRCA1/2 mutation screening after the initial genetic counseling; 88.2% of 647 probands and 100% of 157 family members were screened. In multivariate analysis, family history of breast cancer and younger age were independent variables affecting participation in genetic testing. Of the 132 people who initially declined genetic testing, 58 (43.9%) postponed the decision, 30 (22.7%) needed time to discuss the issue with family members, 22 (16.7%) did not want to know if they had a BRCA1/2 mutation, and 22 (16.7%) declined the test because of financial problems. When analyzing refusal of testing according to the time period before and after the implementation of national health insurance coverage for BRCA1/2 genetic testing, the critical reason given for refusal was different. After insurance coverage, refusal for financial reason was decreased from 61.1 to 9.6%. A family history of breast cancer and a younger age were important factors associated with participation in genetic testing. National health insurance decreased the proportion of individuals who did not participate in testing owing to a financial reason. In genetic counseling, we have to understand these issues and consider several factors that may influence an individual's decision to be tested. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Chaotic homes and school achievement: a twin study

PubMed Central

Hanscombe, Ken B; Haworth, Claire MA; Davis, Oliver SP; Jaffee, Sara R; Plomin, Robert

2011-01-01

Background Chaotic homes predict poor school performance. Given that it is known that genes affect both children's experience of household chaos and their school achievement, to what extent is the relationship between high levels of noise and environmental confusion in the home, and children's school performance, mediated by heritable child effects? This is the first study to explore the genetic and environmental pathways between household chaos and academic performance. Method Children's perceptions of family chaos at ages 9 and 12 and their school performance at age 12 were assessed in more than 2,300 twin pairs. The use of child-specific measures in a multivariate genetic analysis made it possible to investigate the genetic and environmental origins of the covariation between children's experience of chaos in the home and their school achievement. Results Children's experience of family chaos and their school achievement were significantly correlated in the expected negative direction (r = −.26). As expected, shared environmental factors explained a large proportion (63%) of the association. However, genetic factors accounted for a significant proportion (37%) of the association between children's experience of household chaos and their school performance. Conclusions The association between chaotic homes and poor performance in school, previously assumed to be entirely environmental in origin, is in fact partly genetic. How children's home environment affects their academic achievement is not simply in the direction environment → child → outcome. Instead, genetic factors that influence children's experience of the disordered home environment also affect how well they do at school. The relationship between the child, their environment and their performance at school is complex: both genetic and environmental factors play a role. PMID:21675992

Can multivariate models based on MOAKS predict OA knee pain? Data from the Osteoarthritis Initiative

NASA Astrophysics Data System (ADS)

Luna-Gómez, Carlos D.; Zanella-Calzada, Laura A.; Galván-Tejada, Jorge I.; Galván-Tejada, Carlos E.; Celaya-Padilla, José M.

2017-03-01

Osteoarthritis is the most common rheumatic disease in the world. Knee pain is the most disabling symptom in the disease, the prediction of pain is one of the targets in preventive medicine, this can be applied to new therapies or treatments. Using the magnetic resonance imaging and the grading scales, a multivariate model based on genetic algorithms is presented. Using a predictive model can be useful to associate minor structure changes in the joint with the future knee pain. Results suggest that multivariate models can be predictive with future knee chronic pain. All models; T0, T1 and T2, were statistically significant, all p values were < 0.05 and all AUC > 0.60.

Genetic and environmental determinants of violence risk in psychotic disorders: a multivariate quantitative genetic study of 1.8 million Swedish twins and siblings

PubMed Central

Sariaslan, A; Larsson, H; Fazel, S

2016-01-01

Patients diagnosed with psychotic disorders (for example, schizophrenia and bipolar disorder) have elevated risks of committing violent acts, particularly if they are comorbid with substance misuse. Despite recent insights from quantitative and molecular genetic studies demonstrating considerable pleiotropy in the genetic architecture of these phenotypes, there is currently a lack of large-scale studies that have specifically examined the aetiological links between psychotic disorders and violence. Using a sample of all Swedish individuals born between 1958 and 1989 (n=3 332 101), we identified a total of 923 259 twin-sibling pairs. Patients were identified using the National Patient Register using validated algorithms based on International Classification of Diseases (ICD) 8–10. Univariate quantitative genetic models revealed that all phenotypes (schizophrenia, bipolar disorder, substance misuse, and violent crime) were highly heritable (h2=53–71%). Multivariate models further revealed that schizophrenia was a stronger predictor of violence (r=0.32; 95% confidence interval: 0.30–0.33) than bipolar disorder (r=0.23; 0.21–0.25), and large proportions (51–67%) of these phenotypic correlations were explained by genetic factors shared between each disorder, substance misuse, and violence. Importantly, we found that genetic influences that were unrelated to substance misuse explained approximately a fifth (21% 20–22%) of the correlation with violent criminality in bipolar disorder but none of the same correlation in schizophrenia (Pbipolar disorder<0.001; Pschizophrenia=0.55). These findings highlight the problems of not disentangling common and unique sources of covariance across genetically similar phenotypes as the latter sources may include aetiologically important clues. Clinically, these findings underline the importance of assessing risk of different phenotypes together and integrating interventions for psychiatric disorders, substance misuse, and violence. PMID:26666206

Human leukocyte antigen class I region single-nucleotide polymorphisms are associated with leprosy susceptibility in Vietnam and India.

PubMed

Alter, Andrea; Huong, Nguyen Thu; Singh, Meenakshi; Orlova, Marianna; Van Thuc, Nguyen; Katoch, Kiran; Gao, Xiaojiang; Thai, Vu Hong; Ba, Nguyen Ngoc; Carrington, Mary; Abel, Laurent; Mehra, Narinder; Alcaïs, Alexandre; Schurr, Erwin

2011-05-01

Experimental evidence suggested the existence of unidentified leprosy susceptibility loci in the human leukocyte antigen (HLA) complex. To identify such genetic risk factors, a high-density association scan of a 1.9-mega-base (Mb) region in the HLA complex was performed. Among 682 single-nucleotide polymorphisms (SNPs), 59 were associated with leprosy (P <.01) in 198 Vietnamese single-case leprosy families. Genotyping of these SNPs in an independent sample of 292 Vietnamese single-case leprosy families replicated the association of 12 SNPs (P <.01). Multivariate analysis of these 12 SNPs showed that the association information could be captured by 2 intergenic HLA class I region SNPs (P = 9.4 × 10⁻⁹)-rs2394885 and rs2922997 (marginal multivariate P = 2.1 × 10⁻⁷ and P = .0016, respectively). SNP rs2394885 tagged the HLA-C*15:05 allele in the Vietnamese population. The identical associations were validated in a third sample of 364 patients with leprosy and 371 control subjects from North India. These results implicated class I alleles in leprosy pathogenesis.

Human Leukocyte Antigen Class I Region Single-Nucleotide Polymorphisms are Associated with Leprosy Susceptibility in Vietnam and India

PubMed Central

Alter, Andrea; Huong, Nguyen Thu; Singh, Meenakshi; Orlova, Marianna; Van Thuc, Nguyen; Katoch, Kiran; Gao, Xiaojiang; Thai, Vu Hong; Ba, Nguyen Ngoc; Carrington, Mary; Abel, Laurent; Mehra, Narinder; Alcaïs, Alexandre

2011-01-01

Experimental evidence suggested the existence of unidentified leprosy susceptibility loci in the human leukocyte antigen (HLA) complex. To identify such genetic risk factors, a high-density association scan of a 1.9-mega-base (Mb) region in the HLA complex was performed. Among 682 single-nucleotide polymorphisms (SNPs), 59 were associated with leprosy (P <.01) in 198 Vietnamese single-case leprosy families. Genotyping of these SNPs in an independent sample of 292 Vietnamese single-case leprosy families replicated the association of 12 SNPs (P <.01). Multivariate analysis of these 12 SNPs showed that the association information could be captured by 2 intergenic HLA class I region SNPs (P = 9.4 × 10−9)—rs2394885 and rs2922997 (marginal multivariate P = 2.1 × 10−7 and P = .0016, respectively). SNP rs2394885 tagged the HLA-C*15:05 allele in the Vietnamese population. The identical associations were validated in a third sample of 364 patients with leprosy and 371 control subjects from North India. These results implicated class I alleles in leprosy pathogenesis. PMID:21459816

Predictive analysis of beer quality by correlating sensory evaluation with higher alcohol and ester production using multivariate statistics methods.

PubMed

Dong, Jian-Jun; Li, Qing-Liang; Yin, Hua; Zhong, Cheng; Hao, Jun-Guang; Yang, Pan-Fei; Tian, Yu-Hong; Jia, Shi-Ru

2014-10-15

Sensory evaluation is regarded as a necessary procedure to ensure a reproducible quality of beer. Meanwhile, high-throughput analytical methods provide a powerful tool to analyse various flavour compounds, such as higher alcohol and ester. In this study, the relationship between flavour compounds and sensory evaluation was established by non-linear models such as partial least squares (PLS), genetic algorithm back-propagation neural network (GA-BP), support vector machine (SVM). It was shown that SVM with a Radial Basis Function (RBF) had a better performance of prediction accuracy for both calibration set (94.3%) and validation set (96.2%) than other models. Relatively lower prediction abilities were observed for GA-BP (52.1%) and PLS (31.7%). In addition, the kernel function of SVM played an essential role of model training when the prediction accuracy of SVM with polynomial kernel function was 32.9%. As a powerful multivariate statistics method, SVM holds great potential to assess beer quality. Copyright © 2014 Elsevier Ltd. All rights reserved.

Multivariate Models for Normal and Binary Responses in Intervention Studies

ERIC Educational Resources Information Center

Pituch, Keenan A.; Whittaker, Tiffany A.; Chang, Wanchen

2016-01-01

Use of multivariate analysis (e.g., multivariate analysis of variance) is common when normally distributed outcomes are collected in intervention research. However, when mixed responses--a set of normal and binary outcomes--are collected, standard multivariate analyses are no longer suitable. While mixed responses are often obtained in…

Systematic wavelength selection for improved multivariate spectral analysis

DOEpatents

Thomas, Edward V.; Robinson, Mark R.; Haaland, David M.

1995-01-01

Methods and apparatus for determining in a biological material one or more unknown values of at least one known characteristic (e.g. the concentration of an analyte such as glucose in blood or the concentration of one or more blood gas parameters) with a model based on a set of samples with known values of the known characteristics and a multivariate algorithm using several wavelength subsets. The method includes selecting multiple wavelength subsets, from the electromagnetic spectral region appropriate for determining the known characteristic, for use by an algorithm wherein the selection of wavelength subsets improves the model's fitness of the determination for the unknown values of the known characteristic. The selection process utilizes multivariate search methods that select both predictive and synergistic wavelengths within the range of wavelengths utilized. The fitness of the wavelength subsets is determined by the fitness function F=.function.(cost, performance). The method includes the steps of: (1) using one or more applications of a genetic algorithm to produce one or more count spectra, with multiple count spectra then combined to produce a combined count spectrum; (2) smoothing the count spectrum; (3) selecting a threshold count from a count spectrum to select these wavelength subsets which optimize the fitness function; and (4) eliminating a portion of the selected wavelength subsets. The determination of the unknown values can be made: (1) noninvasively and in vivo; (2) invasively and in vivo; or (3) in vitro.

Genetic diversity analysis among male and female Jojoba genotypes employing gene targeted molecular markers, start codon targeted (SCoT) polymorphism and CAAT box-derived polymorphism (CBDP) markers.

PubMed

Heikrujam, Monika; Kumar, Jatin; Agrawal, Veena

2015-09-01

To detect genetic variations among different Simmondsia chinensis genotypes, two gene targeted markers, start codon targeted (SCoT) polymorphism and CAAT box-derived polymorphism (CBDP) were employed in terms of their informativeness and efficiency in analyzing genetic relationships among different genotypes. A total of 15 SCoT and 17 CBDP primers detected genetic polymorphism among 39 Jojoba genotypes (22 females and 17 males). Comparatively, CBDP markers proved to be more effective than SCoT markers in terms of percentage polymorphism as the former detecting an average of 53.4% and the latter as 49.4%. The Polymorphic information content (PIC) value and marker index (MI) of CBPD were 0.43 and 1.10, respectively which were higher than those of SCoT where the respective values of PIC and MI were 0.38 and 1.09. While comparing male and female genotype populations, the former showed higher variation in respect of polymorphic percentage and PIC, MI and Rp values over female populations. Nei's diversity (h) and Shannon index (I) were calculated for each genotype and found that the genotype "MS F" (in both markers) was highly diverse and genotypes "Q104 F" (SCoT) and "82-18 F" (CBDP) were least diverse among the female genotype populations. Among male genotypes, "32 M" (CBDP) and "MS M" (SCoT) revealed highest h and I values while "58-5 M" (both markers) was the least diverse. Jaccard's similarity co-efficient of SCoT markers ranged from 0.733 to 0.922 in female genotypes and 0.941 to 0.746 in male genotype population. Likewise, CBDP data analysis also revealed similarity ranging from 0.751 to 0.958 within female genotypes and 0.754 to 0.976 within male genotype populations thereby, indicating genetically diverse Jojoba population. Employing the NTSYS (Numerical taxonomy and multivariate analysis system) Version 2.1 software, both the markers generated dendrograms which revealed that all the Jojoba genotypes were clustered into two major groups, one group consisting of all female genotypes and another group comprising of all male genotypes. During the present investigation, CBDP markers proved more informative in studying genetic diversity among Jojoba. Such genetically diverse genotypes would thus be of great significance for breeding, management and conservation of elite (high yielding) Jojoba germplasm.

Evolutionary dynamics of the leaf phenological cycle in an oak metapopulation along an elevation gradient.

PubMed

Firmat, C; Delzon, S; Louvet, J-M; Parmentier, J; Kremer, A

2017-12-01

It has been predicted that environmental changes will radically alter the selective pressures on phenological traits. Long-lived species, such as trees, will be particularly affected, as they may need to undergo major adaptive change over only one or a few generations. The traits describing the annual life cycle of trees are generally highly evolvable, but nothing is known about the strength of their genetic correlations. Tight correlations can impose strong evolutionary constraints, potentially hampering the adaptation of multivariate phenological phenotypes. In this study, we investigated the evolutionary, genetic and environmental components of the timing of leaf unfolding and senescence within an oak metapopulation along an elevation gradient. Population divergence, estimated from in situ and common-garden data, was compared to expectations under neutral evolution, based on microsatellite markers. This approach made it possible (1) to evaluate the influence of genetic correlation on multivariate local adaptation to elevation and (2) to identify traits probably exposed to past selective pressures due to the colder climate at high elevation. The genetic correlation was positive but very weak, indicating that genetic constraints did not shape the local adaptation pattern for leaf phenology. Both spring and fall (leaf unfolding and senescence, respectively) phenology timings were involved in local adaptation, but leaf unfolding was probably the trait most exposed to climate change-induced selection. Our data indicated that genetic variation makes a much smaller contribution to adaptation than the considerable plastic variation displayed by a tree during its lifetime. The evolutionary potential of leaf phenology is, therefore, probably not the most critical aspect for short-term population survival in a changing climate. © 2017 European Society For Evolutionary Biology. Journal of Evolutionary Biology © 2017 European Society For Evolutionary Biology.

A Multivariate Twin Study of Hippocampal Volume, Self-Esteem and Well-Being in Middle Aged Men

PubMed Central

Kubarych, Thomas S.; Prom-Wormley, Elizabeth C.; Franz, Carol E.; Panizzon, Matthew S.; Dale, Anders M.; Fischl, Bruce; Eyler, Lisa T.; Fennema-Notestine, Christine; Grant, Michael D.; Hauger, Richard L.; Hellhammer, Dirk H.; Jak, Amy J.; Jernigan, Terry L.; Lupien, Sonia J.; Lyons, Michael J.; Mendoza, Sally P.; Neale, Michael C.; Seidman, Larry J.; Tsuang, Ming T.; Kremen, William S.

2012-01-01

Self-esteem and well-being are important for successful aging, and some evidence suggests that self-esteem and well-being are associated with hippocampal volume, cognition, and stress responsivity. Whereas most of this evidence is based on studies of older adults, we investigated self-esteem, well-being and hippocampal volume in 474 male middle-age twins. Self-esteem was significantly positively correlated with hippocampal volume (.09, p=.03 for left hippocampus, .10, p=.04 for right). Correlations for well-being were not significant (ps ≫.05). There were strong phenotypic correlations between self-esteem and well-being (.72, p<.001) and between left and right hippocampal volume (.72, p<.001). In multivariate genetic analyses, a 2-factor AE model with well-being and self-esteem on one factor and left and right hippocampal volumes on the other factor fit the data better than Cholesky, independent pathway or common pathway models. The correlation between the two genetic factors was .12 (p=.03); the correlation between the environmental factors was .09 (p>05). Our results indicate that largely different genetic and environmental factors underlie self-esteem and well-being on the one hand and hippocampal volume on the other. PMID:22471516

Simple Penalties on Maximum-Likelihood Estimates of Genetic Parameters to Reduce Sampling Variation

PubMed Central

Meyer, Karin

2016-01-01

Multivariate estimates of genetic parameters are subject to substantial sampling variation, especially for smaller data sets and more than a few traits. A simple modification of standard, maximum-likelihood procedures for multivariate analyses to estimate genetic covariances is described, which can improve estimates by substantially reducing their sampling variances. This is achieved by maximizing the likelihood subject to a penalty. Borrowing from Bayesian principles, we propose a mild, default penalty—derived assuming a Beta distribution of scale-free functions of the covariance components to be estimated—rather than laboriously attempting to determine the stringency of penalization from the data. An extensive simulation study is presented, demonstrating that such penalties can yield very worthwhile reductions in loss, i.e., the difference from population values, for a wide range of scenarios and without distorting estimates of phenotypic covariances. Moreover, mild default penalties tend not to increase loss in difficult cases and, on average, achieve reductions in loss of similar magnitude to computationally demanding schemes to optimize the degree of penalization. Pertinent details required for the adaptation of standard algorithms to locate the maximum of the likelihood function are outlined. PMID:27317681

Genetic Biopsy for Prediction of Surveillance Intervals after Endoscopic Resection of Colonic Polyps: Results of the GENESIS Study

PubMed Central

Berger, Andreas W; Raedler, Katja; Langner, Cord; Ludwig, Leopold; Dikopoulos, Nektarios; Becker, Karl F; Slotta-Huspenina, Julia; Quante, Michael; Schwerdel, Daniel; Perkhofer, Lukas; Kleger, Alexander; Zizer, Eugen; Oswald, Franz; Seufferlein, Thomas; Meining, Alexander

2017-01-01

Background and objective Current surveillance strategies for colorectal cancer following polypectomy are determined by endoscopic and histopathological factors. Such a distinction has been challenged. The present study was designed to identify molecular parameters in colonic polyps potentially defining new sub-groups at risk. Methods One hundred patients were enrolled in this multicentre study. Polyps biopsies underwent formalin-free processing (PAXgene, PreAnalytiX) and targeted next generation sequencing (38 genes (QIAGEN), NextSeq 500 platform (Illumina)). Genetic and histopathological analyses were done blinded to other data. Results In 100 patients, 224 polyps were removed. Significant associations of genetic alterations with endoscopic or histological polyp characteristics were observed for BRAF, KRAS, TCF7L2, FBXW7 and CTNNB1 mutations. Multivariate analysis revealed that polyps ≥ 10 mm have a significant higher relative risk for harbouring oncogene mutations (relative risk 3.467 (1.742–6.933)). Adenomas and right-sided polyps are independent risk factors for CTNNB1 mutations (relative risk 18.559 (2.371–145.245) and 12.987 (1.637–100.00)). Conclusions Assessment of the mutational landscape of polyps can be integrated in the workflow of current colonoscopy practice. There are distinct genetic patterns related to polyp size and location. These results suffice to optimise individual risk calculation and may help to better define surveillance intervals. PMID:29511559

Relationships between Genetic Variations of PNPLA3, TM6SF2 and Histological Features of Nonalcoholic Fatty Liver Disease in Japan.

PubMed

Akuta, Norio; Kawamura, Yusuke; Arase, Yasuji; Suzuki, Fumitaka; Sezaki, Hitomi; Hosaka, Tetsuya; Kobayashi, Masahiro; Kobayashi, Mariko; Saitoh, Satoshi; Suzuki, Yoshiyuki; Ikeda, Kenji; Kumada, Hiromitsu

2016-05-23

It is important to determine the noninvasive parameters of histological features in nonalcoholic fatty liver disease (NAFLD). The aim of this study was to investigate the value of genetic variations as surrogate markers of histological features. The parameters that affected the histological features of NAFLD were investigated in 211 Japanese patients with biopsy-proven NAFLD. The relationships between genetic variations in PNPLA3 rs738409 or TM6SF2 rs58542926 and histological features were analyzed. Furthermore, the impact of genetic variations that affected the pathological criteria for the diagnosis of nonalcoholic steatohepatitis (NASH) (Matteoni classification and NAFLD activity score) was evaluated. The fibrosis stage of PNPLA3 GG was significantly more progressive than that of CG by multiple comparisons. Multivariate analysis identified PNPLA3 genotypes as predictors of fibrosis of stage 2 or more, but the impact tended to decrease at stage 3 or greater. There were no significant differences among the histological features of the three genotypes of TM6SF2. PNPLA3 genotypes partly affected the definition of NASH by the NAFLD activity score, but TM6SF2 genotypes did not affect the definition of NASH. In Japanese patients with biopsy-proven NAFLD, PNPLA3 genotypes may partly affect histological features, including stage of fibrosis, but the TM6SF2 genotype does not affect histological features.

Factors affecting maternal participation in the genetic component of the National Birth Defects Prevention Study-United States, 1997-2007.

PubMed

Glidewell, Jill; Reefhuis, Jennita; Rasmussen, Sonja A; Woomert, Alison; Hobbs, Charlotte; Romitti, Paul A; Crider, Krista S

2014-04-01

As epidemiological studies expand to examine gene-environment interaction effects, it is important to identify factors associated with participation in genetic studies. The National Birth Defects Prevention Study is a multisite case-control study designed to investigate environmental and genetic risk factors for major birth defects. The National Birth Defects Prevention Study includes maternal telephone interviews and mailed buccal cell self-collection kits. Because subjects can participate in the interview, independent of buccal cell collection, detailed analysis of factors associated with participation in buccal cell collection was possible. Multivariable logistic regression models were used to identify the factors associated with participation in the genetic component of the study. Buccal cell participation rates varied by race/ethnicity (non-Hispanic whites, 66.9%; Hispanics, 60.4%; and non-Hispanic blacks, 47.3%) and study site (50.2-74.2%). Additional monetary incentive following return of buccal cell kit and shorter interval between infant's estimated date of delivery and interview were associated with increased participation across all racial/ethnic groups. Higher education and delivering an infant with a birth defect were associated with increased participation among non-Hispanic whites and Hispanics. Factors associated with participation varied by race/ethnicity. Improved understanding of factors associated with participation may facilitate strategies to increase participation, thereby improving generalizability of study findings.

Short communication: Principal components and factor analytic models for test-day milk yield in Brazilian Holstein cattle.

PubMed

Bignardi, A B; El Faro, L; Rosa, G J M; Cardoso, V L; Machado, P F; Albuquerque, L G

2012-04-01

A total of 46,089 individual monthly test-day (TD) milk yields (10 test-days), from 7,331 complete first lactations of Holstein cattle were analyzed. A standard multivariate analysis (MV), reduced rank analyses fitting the first 2, 3, and 4 genetic principal components (PC2, PC3, PC4), and analyses that fitted a factor analytic structure considering 2, 3, and 4 factors (FAS2, FAS3, FAS4), were carried out. The models included the random animal genetic effect and fixed effects of the contemporary groups (herd-year-month of test-day), age of cow (linear and quadratic effects), and days in milk (linear effect). The residual covariance matrix was assumed to have full rank. Moreover, 2 random regression models were applied. Variance components were estimated by restricted maximum likelihood method. The heritability estimates ranged from 0.11 to 0.24. The genetic correlation estimates between TD obtained with the PC2 model were higher than those obtained with the MV model, especially on adjacent test-days at the end of lactation close to unity. The results indicate that for the data considered in this study, only 2 principal components are required to summarize the bulk of genetic variation among the 10 traits. Copyright © 2012 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Integrating multiple lines of evidence to better understand the evolutionary divergence of humpback dolphins along their entire distribution range: a new dolphin species in Australian waters?

PubMed

Mendez, Martin; Jefferson, Thomas A; Kolokotronis, Sergios-Orestis; Krützen, Michael; Parra, Guido J; Collins, Tim; Minton, Giana; Baldwin, Robert; Berggren, Per; Särnblad, Anna; Amir, Omar A; Peddemors, Vic M; Karczmarski, Leszek; Guissamulo, Almeida; Smith, Brian; Sutaria, Dipani; Amato, George; Rosenbaum, Howard C

2013-12-01

The conservation of humpback dolphins, distributed in coastal waters of the Indo-West Pacific and eastern Atlantic Oceans, has been hindered by a lack of understanding about the number of species in the genus (Sousa) and their population structure. To address this issue, we present a combined analysis of genetic and morphologic data collected from beach-cast, remote-biopsied and museum specimens from throughout the known Sousa range. We extracted genetic sequence data from 235 samples from extant populations and explored the mitochondrial control region and four nuclear introns through phylogenetic, population-level and population aggregation frameworks. In addition, 180 cranial specimens from the same geographical regions allowed comparisons of 24 morphological characters through multivariate analyses. The genetic and morphological data showed significant and concordant patterns of geographical segregation, which are typical for the kind of demographic isolation displayed by species units, across the Sousa genus distribution range. Based on our combined genetic and morphological analyses, there is convincing evidence for at least four species within the genus (S. teuszii in the Atlantic off West Africa, S. plumbea in the central and western Indian Ocean, S. chinensis in the eastern Indian and West Pacific Oceans, and a new as-yet-unnamed species off northern Australia). © 2013 John Wiley & Sons Ltd.

Contemporary and historical evolutionary processes interact to shape patterns of within-lake phenotypic divergences in polyphenic pumpkinseed sunfish, Lepomis gibbosus.

PubMed

Weese, Dylan J; Ferguson, Moira M; Robinson, Beren W

2012-03-01

Historical and contemporary evolutionary processes can both contribute to patterns of phenotypic variation among populations of a species. Recent studies are revealing how interactions between historical and contemporary processes better explain observed patterns of phenotypic divergence than either process alone. Here, we investigate the roles of evolutionary history and adaptation to current environmental conditions in structuring phenotypic variation among polyphenic populations of sunfish inhabiting 12 postglacial lakes in eastern North America. The pumpkinseed sunfish polyphenism includes sympatric ecomorphs specialized for littoral or pelagic lake habitats. First, we use population genetic methods to test the evolutionary independence of within-lake phenotypic divergences of ecomorphs and to describe patterns of genetic structure among lake populations that clustered into three geographical groupings. We then used multivariate analysis of covariance (MANCOVA) to partition body shape variation (quantified with geometric morphometrics) among the effects of evolutionary history (reflecting phenotypic variation among genetic clusters), the shared phenotypic response of all populations to alternate habitats within lakes (reflecting adaptation to contemporary conditions), and unique phenotypic responses to habitats within lakes nested within genetic clusters. All effects had a significant influence on body form, but the effects of history and the interaction between history and contemporary habitat were larger than contemporary processes in structuring phenotypic variation. This highlights how divergence can be better understood against a known backdrop of evolutionary history.

First Insights into the Genetic Diversity of the Pinewood Nematode in Its Native Area Using New Polymorphic Microsatellite Loci

PubMed Central

Mallez, Sophie; Castagnone, Chantal; Espada, Margarida; Vieira, Paulo; Eisenback, Jonathan D.; Mota, Manuel; Guillemaud, Thomas; Castagnone-Sereno, Philippe

2013-01-01

The pinewood nematode, Bursaphelenchus xylophilus, native to North America, is the causative agent of pine wilt disease and among the most important invasive forest pests in the East-Asian countries, such as Japan and China. Since 1999, it has been found in Europe in the Iberian Peninsula, where it also causes significant damage. In a previous study, 94 pairs of microsatellite primers have been identified in silico in the pinewood nematode genome. In the present study, specific PCR amplifications and polymorphism tests to validate these loci were performed and 17 microsatellite loci that were suitable for routine analysis of B. xylophilus genetic diversity were selected. The polymorphism of these markers was evaluated on nematodes from four field origins and one laboratory collection strain, all originate from the native area. The number of alleles and the expected heterozygosity varied between 2 and 11 and between 0.039 and 0.777, respectively. First insights into the population genetic structure of B. xylophilus were obtained using clustering and multivariate methods on the genotypes obtained from the field samples. The results showed that the pinewood nematode genetic diversity is spatially structured at the scale of the pine tree and probably at larger scales. The role of dispersal by the insect vector versus human activities in shaping this structure is discussed. PMID:23554990

Deconstructing multivariate decoding for the study of brain function.

PubMed

Hebart, Martin N; Baker, Chris I

2017-08-04

Multivariate decoding methods were developed originally as tools to enable accurate predictions in real-world applications. The realization that these methods can also be employed to study brain function has led to their widespread adoption in the neurosciences. However, prior to the rise of multivariate decoding, the study of brain function was firmly embedded in a statistical philosophy grounded on univariate methods of data analysis. In this way, multivariate decoding for brain interpretation grew out of two established frameworks: multivariate decoding for predictions in real-world applications, and classical univariate analysis based on the study and interpretation of brain activation. We argue that this led to two confusions, one reflecting a mixture of multivariate decoding for prediction or interpretation, and the other a mixture of the conceptual and statistical philosophies underlying multivariate decoding and classical univariate analysis. Here we attempt to systematically disambiguate multivariate decoding for the study of brain function from the frameworks it grew out of. After elaborating these confusions and their consequences, we describe six, often unappreciated, differences between classical univariate analysis and multivariate decoding. We then focus on how the common interpretation of what is signal and noise changes in multivariate decoding. Finally, we use four examples to illustrate where these confusions may impact the interpretation of neuroimaging data. We conclude with a discussion of potential strategies to help resolve these confusions in interpreting multivariate decoding results, including the potential departure from multivariate decoding methods for the study of brain function. Copyright © 2017. Published by Elsevier Inc.

Genetic characterization of Colombian Bahman cattle using microsatellites markers.

PubMed

Gómez, Y M; Fernandez, M; Rivera, D; Gómez, G; Bernal, J E

2013-07-01

Genetic structure and diversity of 3789 animals of the Brahman breed from 23 Colombian regions were assessed. Considering the Brahman Zebu cattle as a single population, the multilocus test based on the HW equilibrium, shows significant differences (P < 0.001). Genetic characterization made on the cattle population allowed to examine the genetic variability, calculating a H(o) = 0.6621. Brahman population in Colombia was a small subdivision within populations (F(it) = 0.045), a geographic subdivision almost non-existent or low differentiation (F(st) = 0.003) and the F(is) calculated (0.042) indicates no detriment to the variability in the population, despite the narrow mating takes place or there is a force that causes the variability is sustained without inbreeding actually affect the cattle population. The outcomes of multivariate analyses, Bayesian inferences and interindividual genetic distances suggested that there is no genetic sub-structure in the population, because of the high rate of animal migration among regions.

Genetic risk, coronary heart disease events, and the clinical benefit of statin therapy: an analysis of primary and secondary prevention trials.

PubMed

Mega, J L; Stitziel, N O; Smith, J G; Chasman, D I; Caulfield, M; Devlin, J J; Nordio, F; Hyde, C; Cannon, C P; Sacks, F; Poulter, N; Sever, P; Ridker, P M; Braunwald, E; Melander, O; Kathiresan, S; Sabatine, M S

2015-06-06

Genetic variants have been associated with the risk of coronary heart disease. In this study, we tested whether or not a composite of these variants could ascertain the risk of both incident and recurrent coronary heart disease events and identify those individuals who derive greater clinical benefit from statin therapy. A community-based cohort study (the Malmo Diet and Cancer Study) and four randomised controlled trials of both primary prevention (JUPITER and ASCOT) and secondary prevention (CARE and PROVE IT-TIMI 22) with statin therapy, comprising a total of 48,421 individuals and 3477 events, were included in these analyses. We studied the association of a genetic risk score based on 27 genetic variants with incident or recurrent coronary heart disease, adjusting for traditional clinical risk factors. We then investigated the relative and absolute risk reductions in coronary heart disease events with statin therapy stratified by genetic risk. We combined data from the different studies using a meta-analysis. When individuals were divided into low (quintile 1), intermediate (quintiles 2-4), and high (quintile 5) genetic risk categories, a significant gradient in risk for incident or recurrent coronary heart disease was shown. Compared with the low genetic risk category, the multivariable-adjusted hazard ratio for coronary heart disease for the intermediate genetic risk category was 1·34 (95% CI 1·22-1·47, p<0·0001) and that for the high genetic risk category was 1·72 (1·55-1·92, p<0·0001). In terms of the benefit of statin therapy in the four randomised trials, we noted a significant gradient (p=0·0277) of increasing relative risk reductions across the low (13%), intermediate (29%), and high (48%) genetic risk categories. Similarly, we noted greater absolute risk reductions in those individuals in higher genetic risk categories (p=0·0101), resulting in a roughly threefold decrease in the number needed to treat to prevent one coronary heart disease event in the primary prevention trials. Specifically, in the primary prevention trials, the number needed to treat to prevent one such event in 10 years was 66 in people at low genetic risk, 42 in those at intermediate genetic risk, and 25 in those at high genetic risk in JUPITER, and 57, 47, and 20, respectively, in ASCOT. A genetic risk score identified individuals at increased risk for both incident and recurrent coronary heart disease events. People with the highest burden of genetic risk derived the largest relative and absolute clinical benefit from statin therapy. National Institutes of Health. Copyright © 2015 Elsevier Ltd. All rights reserved.

Genetic predictors of recovery in low back and lumbar radicular pain.

PubMed

Bjorland, Siri; Røe, Cecilie; Moen, Aurora; Schistad, Elina; Mahmood, Aqsa; Gjerstad, Johannes

2017-08-01

Previous data suggest that persistent back pain may be associated with genetic variability. In this study, we assessed the correlation between 8 genetic polymorphisms (VDR, COL11, MMP1, MMP9, IL-1α, IL-1RN, OPRM1, COMT) and pain recovery in patients with low back pain (LBP) and lumbar radicular pain (LRP). In total, 296 patients with LBP or LRP were followed for 5 years. The patients underwent standardized clinical examination and completed pain and function questionnaires. Univariate linear regression associations with P values <0.1 were included in the multivariable analysis, adjusting for pain intensity at baseline, age, sex, smoking, body mass index, and LBP or LRP. Pain intensity at 5-year follow-up was associated with VDR rs731236 (B = -0.5, 95% confidence interval [CI] -0.9 to -0.1, P = 0.017), MMP9 rs17576 (B = 0.5, 95% CI 0.1-0.9, P = 0.022), and OPRM1 rs1799971 (B = -0.8, 95% CI -1.4 to -0.2, P = 0.006) in the univariate analyses. MMP9 rs17576 and OPRM1 rs1799971 remained significant (B = 0.4, 95% CI 0.05-0.8, P = 0.026 and B = -0.8, 95% CI -1.3 to -0.2, P = 0.007) in the multivariable model. Thus, the data demonstrated that the rare allele of MMP9 rs17576 was associated with poor pain recovery, whereas the rare allele of OPRM1 rs1799971 was associated with better pain recovery at 5-year follow-up in the LBP and LRP patients. In particular, the present study suggested that the OPRM1 rs179971 A>G in men was associated with better long-term pain recovery. In men, the OPRM1 rs1799971 explained 4.7% of the variance of pain intensity. We conclude that the MMP9 rs17576 and OPRM1 rs1799971 genotypes may affect 5-year recovery in patients with LBP and LRP.

Multivariate meta-analysis: Potential and promise

PubMed Central

Jackson, Dan; Riley, Richard; White, Ian R

2011-01-01

The multivariate random effects model is a generalization of the standard univariate model. Multivariate meta-analysis is becoming more commonly used and the techniques and related computer software, although continually under development, are now in place. In order to raise awareness of the multivariate methods, and discuss their advantages and disadvantages, we organized a one day ‘Multivariate meta-analysis’ event at the Royal Statistical Society. In addition to disseminating the most recent developments, we also received an abundance of comments, concerns, insights, critiques and encouragement. This article provides a balanced account of the day's discourse. By giving others the opportunity to respond to our assessment, we hope to ensure that the various view points and opinions are aired before multivariate meta-analysis simply becomes another widely used de facto method without any proper consideration of it by the medical statistics community. We describe the areas of application that multivariate meta-analysis has found, the methods available, the difficulties typically encountered and the arguments for and against the multivariate methods, using four representative but contrasting examples. We conclude that the multivariate methods can be useful, and in particular can provide estimates with better statistical properties, but also that these benefits come at the price of making more assumptions which do not result in better inference in every case. Although there is evidence that multivariate meta-analysis has considerable potential, it must be even more carefully applied than its univariate counterpart in practice. Copyright © 2011 John Wiley & Sons, Ltd. PMID:21268052

Geostatistics for spatial genetic structures: study of wild populations of perennial ryegrass.

PubMed

Monestiez, P; Goulard, M; Charmet, G

1994-04-01

Methods based on geostatistics were applied to quantitative traits of agricultural interest measured on a collection of 547 wild populations of perennial ryegrass in France. The mathematical background of these methods, which resembles spatial autocorrelation analysis, is briefly described. When a single variable is studied, the spatial structure analysis is similar to spatial autocorrelation analysis, and a spatial prediction method, called "kriging", gives a filtered map of the spatial pattern over all the sampled area. When complex interactions of agronomic traits with different evaluation sites define a multivariate structure for the spatial analysis, geostatistical methods allow the spatial variations to be broken down into two main spatial structures with ranges of 120 km and 300 km, respectively. The predicted maps that corresponded to each range were interpreted as a result of the isolation-by-distance model and as a consequence of selection by environmental factors. Practical collecting methodology for breeders may be derived from such spatial structures.

Population genetic structure of rare and endangered plants using molecular markers

USGS Publications Warehouse

Raji, Jennifer; Atkinson, Carter T.

2013-01-01

This study was initiated to assess the levels of genetic diversity and differentiation in the remaining populations of Phyllostegia stachyoides and Melicope zahlbruckneri in Hawai`i Volcanoes National Park and determine the extent of gene flow to identify genetically distinct individuals or groups for conservation purposes. Thirty-six Amplified Fragment Length Polymorphic (AFLP) primer combinations generated a total of 3,242 polymorphic deoxyribonucleic acid (DNA) fragments in the P. stachyoides population with a percentage of polymorphic bands (PPB) ranging from 39.3 to 65.7% and 2,780 for the M. zahlbruckneri population with a PPB of 18.8 to 64.6%. Population differentiation (Fst) of AFLP loci between subpopulations of P. stachyoides was low (0.043) across populations. Analysis of molecular variance of P. stachyoides showed that 4% of the observed genetic differentiation occurred between populations in different kīpuka and 96% when individuals were pooled from all kīpuka. Moderate genetic diversity was detected within the M. zahlbruckneri population. Bayesian and multivariate analyses both classified the P. stachyoides and M. zahlbruckneri populations into genetic groups with considerable sub-structuring detected in the P. stachyoides population. The proportion of genetic differentiation among populations explained by geographical distance was estimated by Mantel tests. No spatial correlation was found between genetic and geographic distances in both populations. Finally, a moderate but significant gene flow that could be attributed to insect or bird-mediated dispersal of pollen across the different kīpuka was observed. The results of this study highlight the utility of a multi-allelic DNA-based marker in screening a large number of polymorphic loci in small and closely related endangered populations and revealed the presence of genetically unique groups of individuals in both M. zahlbruckneri and P. stachyoides populations. Based on these findings, approaches that can assist conservation efforts of these species are proposed. 

Genetic Knowledge Among Participants in the Coriell Personalized Medicine Collaborative.

PubMed

Schmidlen, Tara J; Scheinfeldt, Laura; Zhaoyang, Ruixue; Kasper, Rachel; Sweet, Kevin; Gordon, Erynn S; Keller, Margaret; Stack, Cathy; Gharani, Neda; Daly, Mary B; Jarvis, Joseph; Christman, Michael F

2016-04-01

Genetic literacy is essential for the effective integration of genomic information into healthcare; yet few recent studies have been conducted to assess the current state of this knowledge base. Participants in the Coriell Personalized Medicine Collaborative (CPMC), a prospective study assessing the impact of personalized genetic risk reports for complex diseases and drug response on behavior and health outcomes, completed genetic knowledge questionnaires and other surveys through an online portal. To assess the association between genetic knowledge and genetic education background, multivariate linear regression was performed. 4 062 participants completed a genetic knowledge and genetic education background questionnaire. Most were older (mean age: 50), Caucasian (90 %), female (59 %), highly educated (69 % bachelor's or higher), with annual household income over $100 000 (49 %). Mean percent correct was 76 %. Controlling for demographics revealed that health care providers, participants previously exposed to genetics, and participants with 'better than most' self-rated knowledge were significantly more likely to have a higher knowledge score (p < 0.001). Overall, genetic knowledge was high with previous genetic education experience predictive of higher genetic knowledge score. Education is likely to improve genetic literacy, an important component to expanded use of genomics in personalized medicine.

Multivariate Longitudinal Analysis with Bivariate Correlation Test

PubMed Central

Adjakossa, Eric Houngla; Sadissou, Ibrahim; Hounkonnou, Mahouton Norbert; Nuel, Gregory

2016-01-01

In the context of multivariate multilevel data analysis, this paper focuses on the multivariate linear mixed-effects model, including all the correlations between the random effects when the dimensional residual terms are assumed uncorrelated. Using the EM algorithm, we suggest more general expressions of the model’s parameters estimators. These estimators can be used in the framework of the multivariate longitudinal data analysis as well as in the more general context of the analysis of multivariate multilevel data. By using a likelihood ratio test, we test the significance of the correlations between the random effects of two dependent variables of the model, in order to investigate whether or not it is useful to model these dependent variables jointly. Simulation studies are done to assess both the parameter recovery performance of the EM estimators and the power of the test. Using two empirical data sets which are of longitudinal multivariate type and multivariate multilevel type, respectively, the usefulness of the test is illustrated. PMID:27537692

Multivariate Longitudinal Analysis with Bivariate Correlation Test.

PubMed

Adjakossa, Eric Houngla; Sadissou, Ibrahim; Hounkonnou, Mahouton Norbert; Nuel, Gregory

2016-01-01

In the context of multivariate multilevel data analysis, this paper focuses on the multivariate linear mixed-effects model, including all the correlations between the random effects when the dimensional residual terms are assumed uncorrelated. Using the EM algorithm, we suggest more general expressions of the model's parameters estimators. These estimators can be used in the framework of the multivariate longitudinal data analysis as well as in the more general context of the analysis of multivariate multilevel data. By using a likelihood ratio test, we test the significance of the correlations between the random effects of two dependent variables of the model, in order to investigate whether or not it is useful to model these dependent variables jointly. Simulation studies are done to assess both the parameter recovery performance of the EM estimators and the power of the test. Using two empirical data sets which are of longitudinal multivariate type and multivariate multilevel type, respectively, the usefulness of the test is illustrated.

Molecular Classification Substitutes for the Prognostic Variables Stage, Age, and MYCN Status in Neuroblastoma Risk Assessment.

PubMed

Rosswog, Carolina; Schmidt, Rene; Oberthuer, André; Juraeva, Dilafruz; Brors, Benedikt; Engesser, Anne; Kahlert, Yvonne; Volland, Ruth; Bartenhagen, Christoph; Simon, Thorsten; Berthold, Frank; Hero, Barbara; Faldum, Andreas; Fischer, Matthias

2017-12-01

Current risk stratification systems for neuroblastoma patients consider clinical, histopathological, and genetic variables, and additional prognostic markers have been proposed in recent years. We here sought to select highly informative covariates in a multistep strategy based on consecutive Cox regression models, resulting in a risk score that integrates hazard ratios of prognostic variables. A cohort of 695 neuroblastoma patients was divided into a discovery set (n=75) for multigene predictor generation, a training set (n=411) for risk score development, and a validation set (n=209). Relevant prognostic variables were identified by stepwise multivariable L1-penalized least absolute shrinkage and selection operator (LASSO) Cox regression, followed by backward selection in multivariable Cox regression, and then integrated into a novel risk score. The variables stage, age, MYCN status, and two multigene predictors, NB-th24 and NB-th44, were selected as independent prognostic markers by LASSO Cox regression analysis. Following backward selection, only the multigene predictors were retained in the final model. Integration of these classifiers in a risk scoring system distinguished three patient subgroups that differed substantially in their outcome. The scoring system discriminated patients with diverging outcome in the validation cohort (5-year event-free survival, 84.9±3.4 vs 63.6±14.5 vs 31.0±5.4; P<.001), and its prognostic value was validated by multivariable analysis. We here propose a translational strategy for developing risk assessment systems based on hazard ratios of relevant prognostic variables. Our final neuroblastoma risk score comprised two multigene predictors only, supporting the notion that molecular properties of the tumor cells strongly impact clinical courses of neuroblastoma patients. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

DPYD, TYMS, TYMP, TK1, and TK2 Genetic Expressions as Response Markers in Locally Advanced Rectal Cancer Patients Treated with Fluoropyrimidine-Based Chemoradiotherapy

PubMed Central

Wu, Chan-Han; Huang, Chun-Ming; Chung, Fu-Yen; Huang, Ching-Wen; Tsai, Hsiang-Lin; Chen, Chin-Fan; Wang, Jaw-Yuan

2013-01-01

This study is to investigate multiple chemotherapeutic agent- and radiation-related genetic biomarkers in locally advanced rectal cancer (LARC) patients following fluoropyrimidine-based concurrent chemoradiotherapy (CCRT) for response prediction. We initially selected 6 fluoropyrimidine metabolism-related genes (DPYD, ORPT, TYMS, TYMP, TK1, and TK2) and 3 radiotherapy response-related genes (GLUT1, HIF-1 α, and HIF-2 α) as targets for gene expression identification in 60 LARC cancer specimens. Subsequently, a high-sensitivity weighted enzymatic chip array was designed and constructed to predict responses following CCRT. After CCRT, 39 of 60 (65%) LARC patients were classified as responders (pathological tumor regression grade 2 ~ 4). Using a panel of multiple genetic biomarkers (chip), including DPYD, TYMS, TYMP, TK1, and TK2, at a cutoff value for 3 positive genes, a sensitivity of 89.7% and a specificity of 81% were obtained (AUC: 0.915; 95% CI: 0.840–0.991). Negative chip results were significantly correlated to poor CCRT responses (TRG 0-1) (P = 0.014, hazard ratio: 22.704, 95% CI: 3.055–235.448 in multivariate analysis). Disease-free survival analysis showed significantly better survival rate in patients with positive chip results (P = 0.0001). We suggest that a chip including DPYD, TYMS, TYMP, TK1, and TK2 genes is a potential tool to predict response in LARC following fluoropyrimidine-based CCRT. PMID:24455740

A novel prognostic model in myeloma based on co-segregating adverse FISH lesions and the ISS: analysis of patients treated in the MRC Myeloma IX trial.

PubMed

Boyd, K D; Ross, F M; Chiecchio, L; Dagrada, G P; Konn, Z J; Tapper, W J; Walker, B A; Wardell, C P; Gregory, W M; Szubert, A J; Bell, S E; Child, J A; Jackson, G H; Davies, F E; Morgan, G J

2012-02-01

The association of genetic lesions detected by fluorescence in situ hybridization (FISH) with survival was analyzed in 1069 patients with newly presenting myeloma treated in the Medical Research Council Myeloma IX trial, with the aim of identifying patients associated with the worst prognosis. A comprehensive FISH panel was performed, and the lesions associated with short progression-free survival and overall survival (OS) in multivariate analysis were +1q21, del(17p13) and an adverse immunoglobulin heavy chain gene (IGH) translocation group incorporating t(4;14), t(14;16) and t(14;20). These lesions frequently co-segregated, and there was an association between the accumulation of these adverse FISH lesions and a progressive impairment of survival. This observation was used to define a series of risk groups based on number of adverse lesions. Taking this approach, we defined a favorable risk group by the absence of adverse genetic lesions, an intermediate group with one adverse lesion and a high-risk group defined by the co-segregation of >1 adverse lesion. This genetic grouping was independent of the International Staging System (ISS) and so was integrated with the ISS to identify an ultra-high-risk group defined by ISS II or III and >1 adverse lesion. This group constituted 13.8% of patients and was associated with a median OS of 19.4 months.

Identification of novel potential genetic predictors of urothelial bladder carcinoma susceptibility in Pakistani population.

PubMed

Ali, Syeda Hafiza Benish; Bangash, Kashif Sardar; Rauf, Abdur; Younis, Muhammad; Anwar, Khursheed; Khurram, Raja; Khawaja, Muhammad Athar; Azam, Maleeha; Qureshi, Abid Ali; Akhter, Saeed; Kiemeney, Lambertus A; Qamar, Raheel

2017-10-01

Urothelial bladder carcinoma (UBC) is the most common among urinary bladder neoplasms. We carried out a preliminary study to determine the genetic etiology of UBC in Pakistani population, for this 25 sequence variants from 17 candidate genes were studied in 400 individuals by using polymerase chain reaction-based techniques. Multivariate logistic regression analysis was performed for association analysis of the overall data as well as the data stratified by smoking status, tumor grade and tumor stage. Variants of GSTM1, IGFBP3, LEPR and ACE were found to be associated with altered UBC risk in the overall comparison. CYP1B1 and CDKN1A variants displayed a risk modulation among smokers; IGFBP3 and LEPR variants among non-smokers while GSTM1 polymorphism exhibited association with both. GSTM1 and LEPR variants conferred an altered susceptibility to low grade UBC; GSTT1, IGFBP3 and PPARG variants to high grade UBC while ACE polymorphism to both grades. GSTM1 and LEPR variants exhibited risk modulation for non-muscle-invasive bladder cancer (NMIBC); GSTT1 and PPARG variants for muscle-invasive bladder cancer (MIBC), and ACE variant for NMIBC as well as MIBC. In general, the susceptibility markers were common for low grade and NMIBC; and distinct from those for high grade and MIBC indicating the distinct pathologies of both groups. In brief, our results conform to reports of previously associated variants in addition to identifying novel potential genetic predictors of UBC susceptibility.

Genetic Polymorphisms in RNA Binding Proteins Contribute to Breast Cancer Survival

PubMed Central

Upadhyay, Rohit; Sanduja, Sandhya; Kaza, Vimala; Dixon, Dan A.

2012-01-01

The RNA-binding proteins TTP and HuR control expression of numerous genes associated with breast cancer pathogenesis by regulating mRNA stability. However, the role of genetic variation in TTP (ZFP36) and HuR (ELAVL1) genes is unknown in breast cancer prognosis. A total of 251 breast cancer patients (170 Caucasians and 81 African-Americans) were enrolled and followed-up from 2001 to 2011 (or until death). Genotyping was performed for 10 SNPs in ZFP36 and 7 in ELAVL1 genes. On comparing both races with one another, significant differences were found for clinical and genetic variables. The influence of genetic polymorphisms on survival was analyzed by using Cox-regression, Kaplan-Meier analysis, and the log-rank test. Univariate (Kaplan-Meier/Cox-regression) and multivariate (Cox-regression) analysis showed that the TTP gene polymorphism ZFP36*2 A>G was significantly associated with poor prognosis of Caucasian patients (HR = 2.03; 95% CI = 1.09–3.76; P = 0.025; log-rank P = 0.022). None of the haplotypes, but presence of more than six risk genotypes in Caucasian patients, was significantly associated with poor prognosis (HR=2.42; 95% CI=1.17–4.99; P = 0.017; log-rank P = 0.007). The effect of ZFP36*2 A>G on gene expression was evaluated from patients' tissue samples. Both TTP mRNA and protein expression was significantly decreased in ZFP36*2 G allele carriers compared to A allele homozygotes. Conversely, upregulation of the TTP-target gene COX-2 was observed ZFP36*2 G allele carriers. Through its ability to attenuate TTP gene expression, the ZFP36*2 A>G gene polymorphism has appeared as a novel prognostic breast cancer marker in Caucasian patients. PMID:22907529

Conservatism and novelty in the genetic architecture of adaptation in Heliconius butterflies.

PubMed

Huber, B; Whibley, A; Poul, Y L; Navarro, N; Martin, A; Baxter, S; Shah, A; Gilles, B; Wirth, T; McMillan, W O; Joron, M

2015-05-01

Understanding the genetic architecture of adaptive traits has been at the centre of modern evolutionary biology since Fisher; however, evaluating how the genetic architecture of ecologically important traits influences their diversification has been hampered by the scarcity of empirical data. Now, high-throughput genomics facilitates the detailed exploration of variation in the genome-to-phenotype map among closely related taxa. Here, we investigate the evolution of wing pattern diversity in Heliconius, a clade of neotropical butterflies that have undergone an adaptive radiation for wing-pattern mimicry and are influenced by distinct selection regimes. Using crosses between natural wing-pattern variants, we used genome-wide restriction site-associated DNA (RAD) genotyping, traditional linkage mapping and multivariate image analysis to study the evolution of the architecture of adaptive variation in two closely related species: Heliconius hecale and H. ismenius. We implemented a new morphometric procedure for the analysis of whole-wing pattern variation, which allows visualising spatial heatmaps of genotype-to-phenotype association for each quantitative trait locus separately. We used the H. melpomene reference genome to fine-map variation for each major wing-patterning region uncovered, evaluated the role of candidate genes and compared genetic architectures across the genus. Our results show that, although the loci responding to mimicry selection are highly conserved between species, their effect size and phenotypic action vary throughout the clade. Multilocus architecture is ancestral and maintained across species under directional selection, whereas the single-locus (supergene) inheritance controlling polymorphism in H. numata appears to have evolved only once. Nevertheless, the conservatism in the wing-patterning toolkit found throughout the genus does not appear to constrain phenotypic evolution towards local adaptive optima.

Validation of genetic modifiers for Duchenne muscular dystrophy: a multicentre study assessing SPP1 and LTBP4 variants.

PubMed

van den Bergen, Janneke C; Hiller, Monika; Böhringer, Stefan; Vijfhuizen, Linda; Ginjaar, Hendrika B; Chaouch, Amina; Bushby, Kate; Straub, Volker; Scoto, Mariacristina; Cirak, Sebahattin; Humbertclaude, Véronique; Claustres, Mireille; Scotton, Chiara; Passarelli, Chiara; Lochmüller, Hanns; Muntoni, Francesco; Tuffery-Giraud, Sylvie; Ferlini, Alessandra; Aartsma-Rus, Annemieke M; Verschuuren, Jan J G M; 't Hoen, Peter Ac; Spitali, Pietro

2015-10-01

Duchenne muscular dystrophy (DMD) is characterised by progressive muscle weakness. It has recently been reported that single nucleotide polymorphisms (SNPs) located in the SPP1 and LTBP4 loci can account for some of the inter-individual variability observed in the clinical disease course. The validation of genetic association in large independent cohorts is a key process for rare diseases in order to qualify prognostic biomarkers and stratify patients in clinical trials. Duchenne patients from five European neuromuscular centres were included. Information about age at wheelchair dependence and steroid use was gathered. Melting curve analysis of PCR fragments or Sanger sequencing were used to genotype SNP rs28357094 in the SPP1 gene in 336 patients. The genotype of SNPs rs2303729, rs1131620, rs1051303 and rs10880 in the LTBP4 locus was determined in 265 patients by mass spectrometry. For both loci, a multivariate analysis was performed, using genotype/haplotype, steroid use and cohort as covariates. We show that corticosteroid treatment and the IAAM haplotype of the LTBP4 gene are significantly associated with prolonged ambulation in patients with DMD. There was no significant association between the SNP rs28357094 in the SPP1 gene and the age of ambulation loss. This study underlines the importance of replicating genetic association studies for rare diseases in large independent cohorts to identify the most robust associations. We anticipate that genotyping of validated genetic associations will become important for the design and interpretation of clinical trials. 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.

Extended diversity analysis of cultivated grapevine Vitis vinifera with 10K genome-wide SNPs.

PubMed

Laucou, Valérie; Launay, Amandine; Bacilieri, Roberto; Lacombe, Thierry; Adam-Blondon, Anne-Françoise; Bérard, Aurélie; Chauveau, Aurélie; de Andrés, Maria Teresa; Hausmann, Ludger; Ibáñez, Javier; Le Paslier, Marie-Christine; Maghradze, David; Martinez-Zapater, José Miguel; Maul, Erika; Ponnaiah, Maharajah; Töpfer, Reinhard; Péros, Jean-Pierre; Boursiquot, Jean-Michel

2018-01-01

Grapevine is a very important crop species that is mainly cultivated worldwide for fruits, wine and juice. Identification of the genetic bases of performance traits through association mapping studies requires a precise knowledge of the available diversity and how this diversity is structured and varies across the whole genome. An 18k SNP genotyping array was evaluated on a panel of Vitis vinifera cultivars and we obtained a data set with no missing values for a total of 10207 SNPs and 783 different genotypes. The average inter-SNP spacing was ~47 kbp, the mean minor allele frequency (MAF) was 0.23 and the genetic diversity in the sample was high (He = 0.32). Fourteen SNPs, chosen from those with the highest MAF values, were sufficient to identify each genotype in the sample. Parentage analysis revealed 118 full parentages and 490 parent-offspring duos, thus confirming the close pedigree relationships within the cultivated grapevine. Structure analyses also confirmed the main divisions due to an eastern-western gradient and human usage (table vs. wine). Using a multivariate approach, we refined the structure and identified a total of eight clusters. Both the genetic diversity (He, 0.26-0.32) and linkage disequilibrium (LD, 28.8-58.2 kbp) varied between clusters. Despite the short span LD, we also identified some non-recombining haplotype blocks that may complicate association mapping. Finally, we performed a genome-wide association study that confirmed previous works and also identified new regions for important performance traits such as acidity. Taken together, all the results contribute to a better knowledge of the genetics of the cultivated grapevine.

Depressive Symptoms and Heart Rate Variability: Evidence for a Shared Genetic Substrate in a Study of Twins

PubMed Central

Vaccarino, Viola; Lampert, Rachel; Bremner, J. Douglas; Lee, Forrester; Su, Shaoyong; Maisano, Carisa; Murrah, Nancy V.; Jones, Linda; Jawed, Farhan; Afzal, Nadeem; Ashraf, Ali; Goldberg, Jack

2018-01-01

Objective To clarify the relationship between depression and heart rate variability (HRV) in a sample of twins. Reduced HRV, a measure of autonomic dysfunction, has been linked to depression but many studies have inadequately controlled for familial and environmental factors. Furthermore, little is known about whether depression and HRV share common genetic pathways. Methods We performed power spectral analysis on 24-hour ambulatory electrocardiograms in 288 middle-aged male twins. Log-normalized ultra low, very low, low, high frequency, and total power were calculated. A lifetime history of major depressive disorder (MDD) was determined, using the Structured Clinical Interview for Psychiatry Disorders, and current depressive symptoms were measured with the Beck Depression Inventory. Mixed-effect regression models were used to account for intrapair variability and estimate within-pair effects at the same time controlling for potential confounders. Results Both current depressive symptoms and a history of MDD were significantly associated with lower HRV. There was a graded effect, and power in each frequency band was 29% to 36% lower in the lowest band compared with the highest BDI category. All HRV measures except high frequency remained significantly associated with current depressive symptoms in multivariable analysis, but not with lifetime history of MDD. When analyses were stratified by zygosity, a significant within-pair association between BDI score and HRV was found in the dizygotic but not in the monozygotic twins, suggesting a genetic influence on the association. Conclusions A shared, genetically influenced biological pathway underlies the association between depression and lower HRV. These two phenotypes may be the expression of a generalized neurobiological perturbation. PMID:18606724

Extended diversity analysis of cultivated grapevine Vitis vinifera with 10K genome-wide SNPs

PubMed Central

Launay, Amandine; Bacilieri, Roberto; Lacombe, Thierry; Adam-Blondon, Anne-Françoise; Bérard, Aurélie; Chauveau, Aurélie; de Andrés, Maria Teresa; Maghradze, David; Maul, Erika; Ponnaiah, Maharajah; Töpfer, Reinhard; Péros, Jean-Pierre; Boursiquot, Jean-Michel

2018-01-01

Grapevine is a very important crop species that is mainly cultivated worldwide for fruits, wine and juice. Identification of the genetic bases of performance traits through association mapping studies requires a precise knowledge of the available diversity and how this diversity is structured and varies across the whole genome. An 18k SNP genotyping array was evaluated on a panel of Vitis vinifera cultivars and we obtained a data set with no missing values for a total of 10207 SNPs and 783 different genotypes. The average inter-SNP spacing was ~47 kbp, the mean minor allele frequency (MAF) was 0.23 and the genetic diversity in the sample was high (He = 0.32). Fourteen SNPs, chosen from those with the highest MAF values, were sufficient to identify each genotype in the sample. Parentage analysis revealed 118 full parentages and 490 parent-offspring duos, thus confirming the close pedigree relationships within the cultivated grapevine. Structure analyses also confirmed the main divisions due to an eastern-western gradient and human usage (table vs. wine). Using a multivariate approach, we refined the structure and identified a total of eight clusters. Both the genetic diversity (He, 0.26–0.32) and linkage disequilibrium (LD, 28.8–58.2 kbp) varied between clusters. Despite the short span LD, we also identified some non-recombining haplotype blocks that may complicate association mapping. Finally, we performed a genome-wide association study that confirmed previous works and also identified new regions for important performance traits such as acidity. Taken together, all the results contribute to a better knowledge of the genetics of the cultivated grapevine. PMID:29420602

Epidemiology, genetics, and subtyping of preserved ratio impaired spirometry (PRISm) in COPDGene.

PubMed

Wan, Emily S; Castaldi, Peter J; Cho, Michael H; Hokanson, John E; Regan, Elizabeth A; Make, Barry J; Beaty, Terri H; Han, MeiLan K; Curtis, Jeffrey L; Curran-Everett, Douglas; Lynch, David A; DeMeo, Dawn L; Crapo, James D; Silverman, Edwin K

2014-08-06

Preserved Ratio Impaired Spirometry (PRISm), defined as a reduced FEV1 in the setting of a preserved FEV1/FVC ratio, is highly prevalent and is associated with increased respiratory symptoms, systemic inflammation, and mortality. Studies investigating quantitative chest tomographic features, genetic associations, and subtypes in PRISm subjects have not been reported. Data from current and former smokers enrolled in COPDGene (n = 10,192), an observational, cross-sectional study which recruited subjects aged 45-80 with ≥10 pack years of smoking, were analyzed. To identify epidemiological and radiographic predictors of PRISm, we performed univariate and multivariate analyses comparing PRISm subjects both to control subjects with normal spirometry and to subjects with COPD. To investigate common genetic predictors of PRISm, we performed a genome-wide association study (GWAS). To explore potential subgroups within PRISm, we performed unsupervised k-means clustering. The prevalence of PRISm in COPDGene is 12.3%. Increased dyspnea, reduced 6-minute walk distance, increased percent emphysema and decreased total lung capacity, as well as increased segmental bronchial wall area percentage were significant predictors (p-value <0.05) of PRISm status when compared to control subjects in multivariate models. Although no common genetic variants were identified on GWAS testing, a significant association with Klinefelter's syndrome (47XXY) was observed (p-value < 0.001). Subgroups identified through k-means clustering include a putative "COPD-subtype", "Restrictive-subtype", and a highly symptomatic "Metabolic-subtype". PRISm subjects are clinically and genetically heterogeneous. Future investigations into the pathophysiological mechanisms behind and potential treatment options for subgroups within PRISm are warranted. Clinicaltrials.gov Identifier: NCT000608764.

The structure of genetic and environmental risk factors for phobias in women.

PubMed

Czajkowski, N; Kendler, K S; Tambs, K; Røysamb, E; Reichborn-Kjennerud, T

2011-09-01

To explore the genetic and environmental factors underlying the co-occurrence of lifetime diagnoses of DSM-IV phobia. Female twins (n=1430) from the population-based Norwegian Institute of Public Health Twin Panel were assessed at personal interview for DSM-IV lifetime specific phobia, social phobia and agoraphobia. Comorbidity between the phobias were assessed by odds ratios (ORs) and polychoric correlations and multivariate twin models were fitted in Mx. Phenotypic correlations of lifetime phobia diagnoses ranged from 0.55 (agoraphobia and social phobia, OR 10.95) to 0.06 (animal phobia and social phobia, OR 1.21). In the best fitting twin model, which did not include shared environmental factors, heritability estimates for the phobias ranged from 0.43 to 0.63. Comorbidity between the phobias was accounted for by two common liability factors. The first loaded principally on animal phobia and did not influence the complex phobias (agoraphobia and social phobia). The second liability factor strongly influenced the complex phobias, but also loaded weak to moderate on all the other phobias. Blood phobia was mainly influenced by a specific genetic factor, which accounted for 51% of the total and 81% of the genetic variance. Phobias are highly co-morbid and heritable. Our results suggest that the co-morbidity between phobias is best explained by two distinct liability factors rather than a single factor, as has been assumed in most previous multivariate twin analyses. One of these factors was specific to the simple phobias, while the other was more general. Blood phobia was mainly influenced by disorder specific genetic factors.

The structure of genetic and environmental risk factors for phobias in women

PubMed Central

Czajkowski, N.; Kendler, K. S.; Tambs, K.; Røysamb, E.; Reichborn-Kjennerud, T.

2011-01-01

Background To explore the genetic and environmental factors underlying the co-occurrence of lifetime diagnoses of DSM-IV phobia. Method Female twins (n = 1430) from the population-based Norwegian Institute of Public Health Twin Panel were assessed at personal interview for DSM-IV lifetime specific phobia, social phobia and agoraphobia. Comorbidity between the phobias were assessed by odds ratios (ORs) and polychoric correlations and multivariate twin models were fitted in Mx. Results Phenotypic correlations of lifetime phobia diagnoses ranged from 0.55 (agoraphobia and social phobia, OR 10.95) to 0.06 (animal phobia and social phobia, OR 1.21). In the best fitting twin model, which did not include shared environmental factors, heritability estimates for the phobias ranged from 0.43 to 0.63. Comorbidity between the phobias was accounted for by two common liability factors. The first loaded principally on animal phobia and did not influence the complex phobias (agoraphobia and social phobia). The second liability factor strongly influenced the complex phobias, but also loaded weak to moderate on all the other phobias. Blood phobia was mainly influenced by a specific genetic factor, which accounted for 51% of the total and 81% of the genetic variance. Conclusions Phobias are highly co-morbid and heritable. Our results suggest that the co-morbidity between phobias is best explained by two distinct liability factors rather than a single factor, as has been assumed in most previous multivariate twin analyses. One of these factors was specific to the simple phobias, while the other was more general. Blood phobia was mainly influenced by disorder specific genetic factors. PMID:21211096

Parasites as Biological Tags for Stock Discrimination of Beaked Redfish (Sebastes mentella): Parasite Infra-Communities vs. Limited Resolution of Cytochrome Markers

PubMed Central

Klapper, Regina; Kochmann, Judith; O’Hara, Robert B.; Karl, Horst; Kuhn, Thomas

2016-01-01

The use of parasites as biological tags for discrimination of fish stocks has become a commonly used approach in fisheries management. Metazoan parasite community analysis and anisakid nematode population genetics based on a mitochondrial cytochrome marker were applied in order to assess the usefulness of the two parasitological methods for stock discrimination of beaked redfish Sebastes mentella of three fishing grounds in the North East Atlantic. Multivariate, model-based approaches demonstrated that the metazoan parasite fauna of beaked redfish from East Greenland differed from Tampen, northern North Sea, and Bear Island, Barents Sea. A joint model (latent variable model) was used to estimate the effects of covariates on parasite species and identified four parasite species as main source of differences among fishing grounds; namely Chondracanthus nodosus, Anisakis simplex s.s., Hysterothylacium aduncum, and Bothriocephalus scorpii. Due to its high abundance and differences between fishing grounds, Anisakis simplex s.s. was considered as a major biological tag for host stock differentiation. Whilst the sole examination of Anisakis simplex s.s. on a population genetic level is only of limited use, anisakid nematodes (in particular, A. simplex s.s.) can serve as biological tags on a parasite community level. This study confirmed the use of multivariate analyses as a tool to evaluate parasite infra-communities and to identify parasite species that might serve as biological tags. The present study suggests that S. mentella in the northern North Sea and Barents Sea is not sub-structured. PMID:27104735

Transmission of sporadic Creutzfeldt-Jakob disease by blood transfusion: risk factor or possible biases.

PubMed

Puopolo, Maria; Ladogana, Anna; Vetrugno, Vito; Pocchiari, Maurizio

2011-07-01

The occurrence of transfusion transmissions of variant Creutzfeldt-Jakob disease (CJD) cases has reawakened attention to the possible similar risk posed by other forms of CJD. CJD with a definite or probable diagnosis (sporadic CJD, n = 741; genetic CJD, n = 175) and no-CJD patients with definite alternative diagnosis (n = 482) with available blood transfusion history were included in the study. The risk of exposure to blood transfusion occurring more than 10 years before disease onset and for some possible confounding factors was evaluated by calculating crude odds ratios (ORs). Variables with significant ORs in univariate analyses were included in multivariate logistic regression analyses. In the univariate model, blood transfusion occurring more than 10 years before clinical onset is 4.1-fold more frequent in sporadic CJD than in other neurologic disorders. This significance is lost when the 10-year lag time was not considered. Multivariate analyses show that the risk of developing sporadic CJD after transfusion increases (OR, 5.05) after adjusting for possible confounding factors. Analysis conducted on patients with genetic CJD did not reveal any significant risk factor associated with transfusion. This is the first case-control study showing a significant risk of transfusion occurring more than 10 years before clinical onset in sporadic CJD patients. It remains questionable whether the significance of these data is biologically plausible or the consequence of biases in the design of the study, but they counterbalance previous epidemiologic negative reports that might have overestimated the assessment of blood safety in sporadic CJD. © 2010 American Association of Blood Banks.

GENETIC INTERACTIONS BETWEEN ADRB2 AND PTGER4 ON RESPONSES TO SALMETEROL OR MONTELUKAST IN JAPANESE PATIENTS WITH MILD PERSISTENT ASTHMA.

PubMed

Yamada, Hideyasu; Masuko, Hironori; Inui, Toshihide; Kanazawa, Jun; Yatagai, Yohei; Sakamoto, Tohru; Iijima, Hiroaki; Konno, Satoshi; Shimizu, Kaoruko; Makita, Hironi; Nishimura, Masaharu; Kokubu, Fumio; Saito, Takefumi; Endo, Takeo; Ninomiya, Hiroki; Kaneko, Norihiro; Hizawa, Nobuyuki

2016-01-01

Long-acting β 2 -agonists (LABA) and leukotriene receptor antagonists (LTRA) are two principal agents that can be added to inhaled corticosteroids (ICS) for patients with asthma that is not adequately controlled by ICS alone. In our previous study, the Gly16Arg genotype of the β 2 -adrenergic receptor (ADRB2) gene did not influence the differential bronchodilator effect of salmeterol versus montelukast as an add-on therapy to ICS within 16 weeks of follow-up (the J-Blossom study). We examined if genes encoding CYSLTR1, CYSLTR2, PTGER2 or PTGER4 could explain differential responses to salmeterol versus montelukast using the participants of the J-Blossom study. This study included 76 patients with mild-to-moderate asthma. The difference in peak expiratory flow (PEF) (ΔPEF, l/min) after 16 weeks of treatment with salmeterol (ΔPEFsal) versus montelukast (ΔPEFmon) was associated with the genotypes at each of 4 genes. In addition, multivariate analyses were used to identify a gene-gene interaction between ADRB2 gene and each of these 4 genes. Although none of 4 genes were associated with ΔPEFsal-ΔPEFmon in the univariate analyses, multivariate analysis showed that PTGER4 gene, interacting with ADRB2 Gly16Arg, was associated with ΔPEFsal-ΔPEFmon (p=0.0032). Our findings suggested that the interactions between two genetic loci at ADRB2 and PTGER4 is important in determining the differential response to salmeterol versus montelukast in patients with chronic adult asthma.

Genetic diversity and structure related to expansion history and habitat isolation: stone marten populating rural-urban habitats.

PubMed

Wereszczuk, Anna; Leblois, Raphaël; Zalewski, Andrzej

2017-12-22

Population genetic diversity and structure are determined by past and current evolutionary processes, among which spatially limited dispersal, genetic drift, and shifts in species distribution boundaries have major effects. In most wildlife species, environmental modifications by humans often lead to contraction of species' ranges and/or limit their dispersal by acting as environmental barriers. However, in species well adapted to anthropogenic habitat or open landscapes, human induced environmental changes may facilitate dispersal and range expansions. In this study, we analysed whether isolation by distance and deforestation, among other environmental features, promotes or restricts dispersal and expansion in stone marten (Martes foina) populations. We genotyped 298 martens from eight sites at twenty-two microsatellite loci to characterize the genetic variability, population structure and demographic history of stone martens in Poland. At the landscape scale, limited genetic differentiation between sites in a mosaic of urban, rural and forest habitats was mostly influenced by isolation by distance. Statistical clustering and multivariate analyses showed weak genetic structuring with two to four clusters and a high rate of gene flow between them. Stronger genetic differentiation was detected for one stone marten population (NE1) located inside a large forest complex. Genetic differentiation between this site and all others was 20% higher than between other sites separated by similar distances. The genetic uniqueness index of NE1 was also twofold higher than in other sites. Past demographic history analyses showed recent expansion of this species in north-eastern Poland. A decrease in genetic diversity from south to north, and MIGRAINE analyses indicated the direction of expansion of stone marten. Our results showed that two processes, changes in species distribution boundaries and limited dispersal associated with landscape barriers, affect genetic diversity and structure in stone marten. Analysis of local barriers that reduced dispersal and large scale analyses of genetic structure and demographic history highlight the importance of isolation by distance and forest cover for the past colonization of central Europe by stone marten. This confirmed the hypothesis that human-landscape changes (deforestation) accelerated stone marten expansion, to which climate warming probably has also been contributing over the last few decades.

The 372 T/C genetic polymorphism of TIMP-1 is associated with serum levels of TIMP-1 and survival in patients with severe sepsis

PubMed Central

2013-01-01

Introduction Previous studies have found higher circulating levels of tissue inhibitor of matrix metalloproteinase (TIMP)-1 in nonsurviving septic patients than in surviving septic patients, and an association between the 372 T/C genetic polymorphism of TIMP-1 and the risk of developing certain diseases. However, the relationship between genetic polymorphisms of TIMP-1, circulating TIMP-1 levels and survival in patients with severe sepsis has not been examined, and this was the objective of the study. Methods This multicentre, prospective, observational study was carried out in six Spanish ICUs. We determined the 372 T/C genetic polymorphism of TIMP-1 (rs4898), serum levels of TIMP-1, matrix metalloproteinase (MMP)-9, MMP-10, TNFα, IL-10 and plasma plasminogen activator inhibitor-1 (PAI-1). Survival at 30 days from ICU admission was the endpoint assessed. The association between continuous variables was carried out using Spearman's rank correlation coefficient or Spearman's rho coefficient. Multivariate logistic regression analysis was applied to determine the association between the 372 T/C genetic polymorphism and survival 30 days from ICU admission. Results Of 275 patients with severe sepsis, 80 had genotype CC, 55 had genotype CT and 140 had genotype TT of the 372 T/C genetic polymorphism of TIMP-1. Patients with the T allele showed higher serum levels of TIMP-1 than patients without the T allele (P = 0.004). Multiple logistic regression analysis showed that the T allele was associated with higher mortality at 30 days (odds ratio = 2.08; 95% confidence interval = 1.06 to 4.09; P = 0.03). Survival analysis showed that patients with the T allele presented lower 30-day survival than patients without the T allele (χ2 = 5.77; P = 0.016). We found an association between TIMP-1 levels and levels of MMP-9 (ρ = -0.19; P = 0.002), MMP-10 (ρ = 0.55; P <0.001), TNFα (ρ = 0.56; P <0.001), IL-10 (ρ = 0.48; P <0.001) and PAI-1 (ρ = 0.49; P <0.001). Conclusion The novel findings of our study are that septic patients with the T allele in the 372 T/C genetic polymorphism of TIMP-1 showed higher serum TIMP-1 levels and lower survival rate. The determination of the 372 T/C genetic polymorphism of TIMP-1 thus has prognostic implications and could help in the selection of patients who may benefit from modulation of the MMP/TIMP balance. PMID:23706069

COMT Val158Met polymorphism is associated with post-traumatic stress disorder and functional outcome following mild traumatic brain injury

PubMed Central

Winkler, Ethan A.; Yue, John K.; Ferguson, Adam R.; Temkin, Nancy R.; Stein, Murray B.; Barber, Jason; Yuh, Esther L.; Sharma, Sourabh; Satris, Gabriela G.; McAllister, Thomas W.; Rosand, Jonathan; Sorani, Marco D.; Lingsma, Hester F.; Tarapore, Phiroz E.; Burchard, Esteban G.; Hu, Donglei; Eng, Celeste; Wang, Kevin K.W.; Mukherjee, Pratik; Okonkwo, David O.; Diaz-Arrastia, Ramon; Manley, Geoffrey T.

2017-01-01

Mild traumatic brain injury (mTBI) results in variable clinical trajectories and outcomes. The source of variability remains unclear, but may involve genetic variations, such as single nucleotide polymorphisms (SNPs). A SNP in catechol-o-methyltransferase (COMT) is suggested to influence development of post-traumatic stress disorder (PTSD), but its role in TBI remains unclear. Here, we utilize the Transforming Research and Clinical Knowledge in Traumatic Brain Injury Pilot (TRACK-TBI Pilot) study to investigate whether the COMT Val158Met polymorphism is associated with PTSD and global functional outcome as measured by the PTSD Checklist – Civilian Version and Glasgow Outcome Scale Extended (GOSE), respectively. Results in 93 predominately Caucasian subjects with mTBI show that the COMT Met158 allele is associated with lower incidence of PTSD (univariate odds ratio (OR) of 0.25, 95% CI [0.09–0.69]) and higher GOSE scores (univariate OR 2.87, 95% CI [1.20–6.86]) 6-months following injury. The COMT Val158Met genotype and PTSD association persists after controlling for race (multivariable OR of 0.29, 95% CI [0.10–0.83]) and pre-existing psychiatric disorders/substance abuse (multivariable OR of 0.32, 95% CI [0.11–0.97]). PTSD emerged as a strong predictor of poorer outcome on GOSE (multivariable OR 0.09, 95% CI [0.03–0.26]), which persists after controlling for age, GCS, and race. When accounting for PTSD in multivariable analysis, the association of COMT genotype and GOSE did not remain significant (multivariable OR 1.73, 95% CI [0.69–4.35]). Whether COMT genotype indirectly influences global functional outcome through PTSD remains to be determined and larger studies in more diverse populations are needed to confirm these findings. PMID:27769642

COMT Val158Met polymorphism is associated with post-traumatic stress disorder and functional outcome following mild traumatic brain injury.

PubMed

Winkler, Ethan A; Yue, John K; Ferguson, Adam R; Temkin, Nancy R; Stein, Murray B; Barber, Jason; Yuh, Esther L; Sharma, Sourabh; Satris, Gabriela G; McAllister, Thomas W; Rosand, Jonathan; Sorani, Marco D; Lingsma, Hester F; Tarapore, Phiroz E; Burchard, Esteban G; Hu, Donglei; Eng, Celeste; Wang, Kevin K W; Mukherjee, Pratik; Okonkwo, David O; Diaz-Arrastia, Ramon; Manley, Geoffrey T

2017-01-01

Mild traumatic brain injury (mTBI) results in variable clinical trajectories and outcomes. The source of variability remains unclear, but may involve genetic variations, such as single nucleotide polymorphisms (SNPs). A SNP in catechol-o-methyltransferase (COMT) is suggested to influence development of post-traumatic stress disorder (PTSD), but its role in TBI remains unclear. Here, we utilize the Transforming Research and Clinical Knowledge in Traumatic Brain Injury Pilot (TRACK-TBI Pilot) study to investigate whether the COMT Val 158 Met polymorphism is associated with PTSD and global functional outcome as measured by the PTSD Checklist - Civilian Version and Glasgow Outcome Scale Extended (GOSE), respectively. Results in 93 predominately Caucasian subjects with mTBI show that the COMT Met 158 allele is associated with lower incidence of PTSD (univariate odds ratio (OR) of 0.25, 95% CI [0.09-0.69]) and higher GOSE scores (univariate OR 2.87, 95% CI [1.20-6.86]) 6-months following injury. The COMT Val 158 Met genotype and PTSD association persists after controlling for race (multivariable OR of 0.29, 95% CI [0.10-0.83]) and pre-existing psychiatric disorders/substance abuse (multivariable OR of 0.32, 95% CI [0.11-0.97]). PTSD emerged as a strong predictor of poorer outcome on GOSE (multivariable OR 0.09, 95% CI [0.03-0.26]), which persists after controlling for age, GCS, and race. When accounting for PTSD in multivariable analysis, the association of COMT genotype and GOSE did not remain significant (multivariable OR 1.73, 95% CI [0.69-4.35]). Whether COMT genotype indirectly influences global functional outcome through PTSD remains to be determined and larger studies in more diverse populations are needed to confirm these findings. Copyright © 2016 Elsevier Ltd. All rights reserved.

Multivariate Regression Analysis and Slaughter Livestock,

DTIC Science & Technology

AGRICULTURE, *ECONOMICS), (*MEAT, PRODUCTION), MULTIVARIATE ANALYSIS, REGRESSION ANALYSIS , ANIMALS, WEIGHT, COSTS, PREDICTIONS, STABILITY, MATHEMATICAL MODELS, STORAGE, BEEF, PORK, FOOD, STATISTICAL DATA, ACCURACY

Classification and regression tree analysis vs. multivariable linear and logistic regression methods as statistical tools for studying haemophilia.

PubMed

Henrard, S; Speybroeck, N; Hermans, C

2015-11-01

Haemophilia is a rare genetic haemorrhagic disease characterized by partial or complete deficiency of coagulation factor VIII, for haemophilia A, or IX, for haemophilia B. As in any other medical research domain, the field of haemophilia research is increasingly concerned with finding factors associated with binary or continuous outcomes through multivariable models. Traditional models include multiple logistic regressions, for binary outcomes, and multiple linear regressions for continuous outcomes. Yet these regression models are at times difficult to implement, especially for non-statisticians, and can be difficult to interpret. The present paper sought to didactically explain how, why, and when to use classification and regression tree (CART) analysis for haemophilia research. The CART method is non-parametric and non-linear, based on the repeated partitioning of a sample into subgroups based on a certain criterion. Breiman developed this method in 1984. Classification trees (CTs) are used to analyse categorical outcomes and regression trees (RTs) to analyse continuous ones. The CART methodology has become increasingly popular in the medical field, yet only a few examples of studies using this methodology specifically in haemophilia have to date been published. Two examples using CART analysis and previously published in this field are didactically explained in details. There is increasing interest in using CART analysis in the health domain, primarily due to its ease of implementation, use, and interpretation, thus facilitating medical decision-making. This method should be promoted for analysing continuous or categorical outcomes in haemophilia, when applicable. © 2015 John Wiley & Sons Ltd.

Predictors of associated autoimmune diseases (AAID) in families with type 1 diabetes (T1D). Results from the Type 1 Diabetes Genetics Consortium (T1DGC)

PubMed Central

Wägner, Ana M; Santana, Ángelo; Hernández, Marta; Wiebe, Julia C; Nóvoa, Javier; Mauricio, Didac

2011-01-01

Background Type 1 diabetes (T1D) is a clinically heterogeneous disease. The presence of associated autoimmune diseases (AAID) may represent a distinct form of autoimmune diabetes, with involvement of specific mechanisms. The aim of this study was to find predictors of AAID in the Type 1 Diabetes Genetics Consortium (T1DGC) data set. Methods 3263 families with at least 2 siblings with T1D were included. Clinical information was obtained using questionnaires, anti-GAD and anti-IA-2 were measured and HLA-genotyping was performed. Siblings with T1D with and without AAID were compared and a multivariate regression analysis was performed to find predictors of AAID. T1D-associated HLA haplotypes were defined as the 4 most susceptible and protective, respectively. Results AAID was present in 14.4% of the T1D affected siblings. Age of diabetes onset, current age and time since diagnosis were higher, and there was a female predominance and more family history of AAID in the group with AAID, as well as more frequent anti-GAD and less frequent anti-IA2 positivity. Risk and protective HLA haplotype distributions were similar, though DRB1*0301-DQA1*0501-DQB1*0201 was more frequent in the group with AAID. In the multivariate analysis, female gender, age of onset, family history of AAID, time since diagnosis and anti-GAD positivity were significantly associated with AAID. Conclusions In patients with T1D, the presence of AAID is associated with female predominance, more frequent family history of AAID, later onset of T1D and more anti-GAD antibodies, despite longer duration of the disease. The predominance of certain HLA haplotypes suggests that specific mechanisms of disease may be involved. PMID:21744463

Predictors of associated autoimmune diseases in families with type 1 diabetes: results from the Type 1 Diabetes Genetics Consortium.

PubMed

Wägner, Ana M; Santana, Angelo; Herńndez, Marta; Wiebe, Julia C; Nóvoa, Javier; Mauricio, Dídac

2011-07-01

Type 1 diabetes (T1D) is a clinically heterogeneous disease. The presence of associated autoimmune diseases (AAIDs) may represent a distinct form of autoimmune diabetes, with involvement of specific mechanisms. The aim of this study was to find predictors of AAIDs in the Type 1 Diabetes Genetics Consortium data set. Three thousand two hundred and sixty-three families with at least two siblings with T1D were included. Clinical information was obtained using questionnaires, anti-GAD (glutamic acid decarboxylase) and anti-protein tyrosine phosphatase (IA-2) were measured and human leukocyte antigen (HLA) genotyping was performed. Siblings with T1D with and without AAIDs were compared and a multivariate regression analysis was performed to find predictors of AAIDs. T1D-associated HLA haplotypes were defined as the four most susceptible and protective, respectively. One or more AAIDs were present in 14.4% of the T1D affected siblings. Age of diabetes onset, current age and time since diagnosis were higher, there was a female predominance and more family history of AAIDs in the group with AAIDs, as well as more frequent anti-GAD and less frequent anti-IA-2 antibodies. Risk and protective HLA haplotype distributions were similar, though DRB1*0301-DQA1*0501-DQB1*0201 was more frequent in the group with AAIDs. In the multivariate analysis, female gender, age of onset, family history of AAID, time since diagnosis and anti-GAD positivity were significantly associated with AAIDs. In patients with T1D, the presence of AAIDs is associated with female predominance, more frequent family history of AAIDs, later onset of T1D and more anti-GAD antibodies, despite longer duration of the disease. The predominance of certain HLA haplotypes suggests that specific mechanisms of disease may be involved. Copyright © 2011 John Wiley & Sons, Ltd.

An Analytic Solution to the Computation of Power and Sample Size for Genetic Association Studies under a Pleiotropic Mode of Inheritance.

PubMed

Gordon, Derek; Londono, Douglas; Patel, Payal; Kim, Wonkuk; Finch, Stephen J; Heiman, Gary A

2016-01-01

Our motivation here is to calculate the power of 3 statistical tests used when there are genetic traits that operate under a pleiotropic mode of inheritance and when qualitative phenotypes are defined by use of thresholds for the multiple quantitative phenotypes. Specifically, we formulate a multivariate function that provides the probability that an individual has a vector of specific quantitative trait values conditional on having a risk locus genotype, and we apply thresholds to define qualitative phenotypes (affected, unaffected) and compute penetrances and conditional genotype frequencies based on the multivariate function. We extend the analytic power and minimum-sample-size-necessary (MSSN) formulas for 2 categorical data-based tests (genotype, linear trend test [LTT]) of genetic association to the pleiotropic model. We further compare the MSSN of the genotype test and the LTT with that of a multivariate ANOVA (Pillai). We approximate the MSSN for statistics by linear models using a factorial design and ANOVA. With ANOVA decomposition, we determine which factors most significantly change the power/MSSN for all statistics. Finally, we determine which test statistics have the smallest MSSN. In this work, MSSN calculations are for 2 traits (bivariate distributions) only (for illustrative purposes). We note that the calculations may be extended to address any number of traits. Our key findings are that the genotype test usually has lower MSSN requirements than the LTT. More inclusive thresholds (top/bottom 25% vs. top/bottom 10%) have higher sample size requirements. The Pillai test has a much larger MSSN than both the genotype test and the LTT, as a result of sample selection. With these formulas, researchers can specify how many subjects they must collect to localize genes for pleiotropic phenotypes. © 2017 S. Karger AG, Basel.

Estimating non-genetic and genetic parameters of pre-weaning growth traits in Raini Cashmere goat.

PubMed

Barazandeh, Arsalan; Moghbeli, Sadrollah Molaei; Vatankhah, Mahmood; Mohammadabadi, Mohammadreza

2012-04-01

Data and pedigree information used in the present study were 3,022 records of kids obtained from the breeding station of Raini goat. The studied traits were birth weight (BW), weaning weight (WW), average daily gain from birth to weaning (ADG) and Kleiber ratio at weaning (KR). The model included the fixed effects of sex of kid, type of birth, age of dam, year of birth, month of birth, and age of kid (days) as covariate that had significant effects, and random effects direct additive genetic, maternal additive genetic, maternal permanent environmental effects and residual. (Co) variance components were estimated using univariate and multivariate analysis by WOMBAT software applying four animal models including and ignoring maternal effects. Likelihood ratio test used to determine the most appropriate models. Heritability (h(a)(2)) estimates for BW, WW, ADG, and KR according to suitable model were 0.12 ± 0.05, 0.08 ± 0.06, 0.10 ± 0.06, and 0.06 ± 0.05, respectively. Estimates of the proportion of maternal permanent environmental effect to phenotypic variance (c(2)) were 0.17 ± 0.03, 0.07 ± 0.03, and 0.07 ± 0.03 for BW, WW, and ADG, respectively. Genetic correlations among traits were positive and ranged from 0.53 (BW-ADG) to 1.00 (WW-ADG, WW-KR, and ADG-KR). The maternal permanent environmental correlations between BW-WW, BW-ADG, and WW-ADG were 0.54, 0.48, and 0.99, respectively. Results indicated that maternal effects, especially maternal permanent environmental effects are an important source of variation in pre-weaning growth trait and ignoring those in the model redound incorrect genetic evaluation of kids.

Behavioral comparisons in autistic individuals from multiplex and singleton families.

PubMed

Cuccaro, Michael L; Shao, Yujun; Bass, Meredyth P; Abramson, Ruth K; Ravan, Sarah A; Wright, Harry H; Wolpert, Chantelle M; Donnelly, Shannon L; Pericak-Vance, Margaret A

2003-02-01

Autistic disorder (AD) is a complex neurodevelopmental disorder. The role of genetics in AD etiology is well established, and it is postulated that anywhere from 2 to 10 genes could be involved. As part of a larger study to identify these genetic effects we have ascertained a series of AD families: Sporadic (SP, 1 known AD case per family and no known history of AD) and multiplex (MP, > or = 2 cases per family). The underlying etiology of both family types is unknown. It is possible that MP families may constitute a unique subset of families in which the disease phenotype is more likely due to genetic factors. Clinical differences between the two family types could represent underlying genetic heterogeneity. We examined ADI-R data for 69 probands from MP families and 88 from SP families in order to compare and contrast the clinical phenotypes for each group as a function of verbal versus nonverbal status. Multivariate analysis controlling for covariates of age at examination, gender, and race (MANCOVA) revealed no differences between either the verbal or nonverbal MP and SP groups for the three ADI-R area scores: social interaction, communication, and restricted/repetitive interests or behaviors. These data failed to find clinical heterogeneity between MP and SP family types. This supports previous work that indicated that autism features are not useful as tools to index genetic heterogeneity. Thus, although there may be different underlying etiologic mechanisms in the SP and MP probands, there are no distinct behavioral patterns associated with probands from MP families versus SP families. These results suggests the possibility that common etiologic mechanisms, either genetic and/or environmental, could underlie all of AD.

Cross-sectional analysis of BioBank Japan clinical data: A large cohort of 200,000 patients with 47 common diseases.

PubMed

Hirata, Makoto; Kamatani, Yoichiro; Nagai, Akiko; Kiyohara, Yutaka; Ninomiya, Toshiharu; Tamakoshi, Akiko; Yamagata, Zentaro; Kubo, Michiaki; Muto, Kaori; Mushiroda, Taisei; Murakami, Yoshinori; Yuji, Koichiro; Furukawa, Yoichi; Zembutsu, Hitoshi; Tanaka, Toshihiro; Ohnishi, Yozo; Nakamura, Yusuke; Matsuda, Koichi

2017-03-01

To implement personalized medicine, we established a large-scale patient cohort, BioBank Japan, in 2003. BioBank Japan contains DNA, serum, and clinical information derived from approximately 200,000 patients with 47 diseases. Serum and clinical information were collected annually until 2012. We analyzed clinical information of participants at enrollment, including age, sex, body mass index, hypertension, and smoking and drinking status, across 47 diseases, and compared the results with the Japanese database on Patient Survey and National Health and Nutrition Survey. We conducted multivariate logistic regression analysis, adjusting for sex and age, to assess the association between family history and disease development. Distribution of age at enrollment reflected the typical age of disease onset. Analysis of the clinical information revealed strong associations between smoking and chronic obstructive pulmonary disease, drinking and esophageal cancer, high body mass index and metabolic disease, and hypertension and cardiovascular disease. Logistic regression analysis showed that individuals with a family history of keloid exhibited a higher odds ratio than those without a family history, highlighting the strong impact of host genetic factor(s) on disease onset. Cross-sectional analysis of the clinical information of participants at enrollment revealed characteristics of the present cohort. Analysis of family history revealed the impact of host genetic factors on each disease. BioBank Japan, by publicly distributing DNA, serum, and clinical information, could be a fundamental infrastructure for the implementation of personalized medicine. Copyright © 2017 The Authors. Production and hosting by Elsevier B.V. All rights reserved.

Comparison of morphological and genetic analyses reveals cryptic divergence and morphological plasticity in Stylophora (Cnidaria, Scleractinia)

NASA Astrophysics Data System (ADS)

Stefani, Fabrizio; Benzoni, F.; Yang, S.-Y.; Pichon, M.; Galli, P.; Chen, C. A.

2011-12-01

A combined morphological and genetic study of the coral genus Stylophora investigated species boundaries in the Gulf of Aden, Yemen. Two mitochondrial regions, including the hypervariable IGS9 spacer and the control region, and a fragment of rDNA were used for phylogenetic analysis. Results were compared by multivariate analysis on the basis of branch morphology and corallite morphometry. Two species were clearly discriminated by both approaches. The first species was characterised by small corallites and a low morphological variability and was ascribed to a new geographical record of Stylophora madagascarensis on the basis of its phylogenetic distinction and its morphological similarity to the type material. The second species was characterised by larger corallite size and greater morphological variability and was ascribed to Stylophora pistillata. The analysis was extended to the intrageneric level for other S. pistillata populations from the Red Sea and the Pacific Ocean. Strong internal divergence was evident in the genus Sty lophora. S. pistillata populations were split into two highly divergent Red Sea/Gulf of Aden and western Pacific lineages with significant morphological overlap, which suggests they represent two distinct cryptic species. The combined use of morphological and molecular approaches, so far proved to be a powerful tool for the re-delineation of species boundaries in corals, provided novel evidence of cryptic divergence in this group of marine metazoans.

Morphofunctional diversity of equine of varied genetic compositions raised in the Pantanal biome of Brazil.

PubMed

de Rezende, Marcos Paulo Gonçalves; de Souza, Julio Cesar; Carneiro, Paulo Luiz Souza; Bozzi, Riccardo; Jardim, Rodrigo Jose Delgado; Malhado, Carlos Henrique Mendes

2018-06-01

Evaluating phenotypic diversity makes it possible to identify discrepancies in aptitudes among animals of different genetic bases, which is an indicator of adaptive or selective differences between populations. The objective of this work was to evaluate the morphofunctional diversity of 452 male and female adult equines (Arabian, Quarter Mile, Pantaneiro, and Criollo breeds, and undefined crossbreeds of horses and mules) raised in the Pantanal biome (Brazil). Linear measurements were performed to estimate conformation indexes. Initially, a discriminant analysis was performed, regardless of the animal's size, followed by factor analysis. The factors were characterized and used as new variables. The diversity among equines and their relationship with the factors were evaluated using multivariate analysis. The factors were classified according to their decreasing importance: balance, rusticity, and robustness for the measurement factors; and load, ability, conformation, and equilibrium for the index factors. The genetic groups of equines have well-defined morphofunctional characteristics. The main differences are based on the rusticity and ability typologies in relation to those based on performance. Equines introduced to the Pantanal biome presented a more robust and compact body with good conformation. As a result, these horses may have superior athletic performance during equestrian activities when compared to the Pantaneiro local breed. However, this biotype may represent less rusticity (less adaptive capacity). Therefore, the regional breed can be equal or better in equestrian activities than breeds introduced to the Pantanal biome. Thus, breeders may cross horses from local breeds as an alternative to those introduced. Undefined crossbred male equines presented a different profile from the Pantaneiro breed, which may indicate little use of crossbreeds in breeding.

Use of Longitudinal Data in Genetic Studies in the Genome-wide Association Studies Era: Summary of Group 14

PubMed Central

Kerner, Berit; North, Kari E; Fallin, M Daniele

2010-01-01

Participants analyzed actual and simulated longitudinal data from the Framingham Heart Study for various metabolic and cardiovascular traits. The genetic information incorporated into these investigations ranged from selected single-nucleotide polymorphisms to genome-wide association arrays. Genotypes were incorporated using a broad range of methodological approaches including conditional logistic regression, linear mixed models, generalized estimating equations, linear growth curve estimation, growth modeling, growth mixture modeling, population attributable risk fraction based on survival functions under the proportional hazards models, and multivariate adaptive splines for the analysis of longitudinal data. The specific scientific questions addressed by these different approaches also varied, ranging from a more precise definition of the phenotype, bias reduction in control selection, estimation of effect sizes and genotype associated risk, to direct incorporation of genetic data into longitudinal modeling approaches and the exploration of population heterogeneity with regard to longitudinal trajectories. The group reached several overall conclusions: 1) The additional information provided by longitudinal data may be useful in genetic analyses. 2) The precision of the phenotype definition as well as control selection in nested designs may be improved, especially if traits demonstrate a trend over time or have strong age-of-onset effects. 3) Analyzing genetic data stratified for high-risk subgroups defined by a unique development over time could be useful for the detection of rare mutations in common multi-factorial diseases. 4) Estimation of the population impact of genomic risk variants could be more precise. The challenges and computational complexity demanded by genome-wide single-nucleotide polymorphism data were also discussed. PMID:19924713

Neuro-genetic multioptimization of the determination of polychlorinated biphenyl congeners in human milk by headspace solid phase microextraction coupled to gas chromatography with electron capture detection.

PubMed

Kowalski, Cláudia Hoffmann; da Silva, Gilmare Antônia; Poppi, Ronei Jesus; Godoy, Helena Teixeira; Augusto, Fabio

2007-02-28

Polychlorinated biphenyls (PCB) can eventually contaminate breast milk, which is a serious issue to the newborn due to their high vulnerability. Solid phase microextraction (SPME) can be a very convenient technique for their isolation and pre-concentration prior chromatographic analysis. Here, a simultaneous multioptimization strategy based on a neuro-genetic approach was applied to a headspace SPME method for determination of 12 PCB in human milk. Gas chromatography with electron capture detection (ECD) was adopted for the separation and detection of the analytes. Experiments according to a Doehlert design were carried out with varied extraction time and temperature, media ionic strength and concentration of the methanol (co-solvent). To find the best model that simultaneously correlate all PCB peak areas and SPME extraction conditions, a multivariate calibration method based on a Bayesian Neural Network (BNN) was applied. The net output from the neural network was used as input in a genetic algorithm (GA) optimization operation (neuro-genetic approach). The GA pointed out that the best values of the overall SPME operational conditions were the saturation of the media with NaCl, extraction temperature of 95 degrees C, extraction time of 60 min and addition of 5% (v/v) methanol to the media. These optimized parameters resulted in the decrease of the detection limits and increase on the sensitivity for all tested analytes, showing that the use of neuro-genetic approach can be a promising way for optimization of SPME methods.

Drug development for exceptionally rare metabolic diseases: challenging but not impossible.

PubMed

Putzeist, Michelle; Mantel-Teeuwisse, Aukje K; Wied, Christine C Gispen-de; Hoes, Arno W; Leufkens, Hubert G M; de Vrueh, Remco L A

2013-11-15

We studied to what extent the level of scientific knowledge on exceptionally rare metabolic inherited diseases and their potential orphan medicinal products is associated with sponsors deciding to apply for an orphan designation at the US Food and Drug Administration (FDA) or the European Medicines Agency (EMA). All metabolic diseases with a genetic cause and prevalence of less than 10 patients per 1 million of the population were selected from the 'Orphanet database of Rare diseases'. The outcome of interest was the application for an orphan designation at FDA or EMA. The level of publicly available knowledge of the disease and drug candidate before an orphan designation application was defined as whether the physiological function corresponding with the pathologic gene and initiation of the pathophysiological pathway was known, whether an appropriate animal study was identified for the disease, whether preclinical proof of concept was ascertained and the availability of data in humans. Other determinants included in the study were metabolic disease class, the prevalence of the disease, prognosis and time of first description of the disease in the literature. Univariate relative risks (RRs) and 95% confidence intervals (CIs) of an orphan designation application were calculated for each of these determinants. In addition, a multivariate Cox regression analysis was conducted (Forward LR). In total, 166 rare metabolic genetic diseases were identified and included in the analysis. For only 42 (25%) of the diseases an orphan designation application was submitted at either FDA or EMA before January 2012. The multivariate analysis identified preclinical proof of concept of a potential medicinal product as major knowledge related determinant associated with an orphan designation application (RRadj 3.9, 95% CI 1.9-8.3) and confirmed that prevalence of the disease is also associated with filing an application for an orphan designation (RRadj 2.8, 95% CI 1.4-5.4). For only one out of four known exceptionally rare metabolic inherited diseases sponsors applied for an orphan designation at FDA or EMA. These applications were found to be associated with the prevalence of the rare disease and the level of available scientific knowledge on the proof of concept linking possible drug candidates to the disease of interest.

Re-sequencing of the APOAI promoter region and the genetic association of the -75G > A polymorphism with increased cholesterol and low density lipoprotein levels among a sample of the Kuwaiti population

PubMed Central

2013-01-01

Background APOAI, a member of the APOAI/CIII/IV/V gene cluster on chromosome 11q23-24, encodes a major protein component of HDL that has been associated with serum lipid levels. The aim of this study was to determine the genetic association of polymorphisms in the APOAI promoter region with plasma lipid levels in a cohort of healthy Kuwaiti volunteers. Methods A 435 bp region of the APOAI promoter was analyzed by re-sequencing in 549 Kuwaiti samples. DNA was extracted from blood taken from 549 healthy Kuwaiti volunteers who had fasted for the previous 12 h. Univariate and multivariate analysis was used to determine allele association with serum lipid levels. Results The target sequence included a partial segment of the promoter region, 5’UTR and exon 1 located between nucleotides −141 to +294 upstream of the APOAI gene on chromosome 11. No novel single nucleotide polymorphisms (SNPs) were observed. The sequences obtained were deposited with the NCBI GenBank with accession number [GenBank: JX438706]. The allelic frequencies for the three SNPs were as follows: APOAI rs670G = 0.807; rs5069C = 0.964; rs1799837G = 0.997 and found to be in HWE. A significant association (p < 0.05) was observed for the APOAI rs670 polymorphism with increased serum LDL-C. Multivariate analysis showed that APOAI rs670 was an independent predictive factor when controlling for age, sex and BMI for both LDL-C (OR: 1.66, p = 0.014) and TC (OR: 1.77, p = 0.006) levels. Conclusion This study is the first to report sequence analysis of the APOAI promoter in an Arab population. The unexpected positive association found between the APOAI rs670 polymorphism and increased levels of LDL-C and TC may be due to linkage disequilibrium with other polymorphisms in candidate and neighboring genes known to be associated with lipid metabolism and transport. PMID:24028463

Re-sequencing of the APOAI promoter region and the genetic association of the -75G > A polymorphism with increased cholesterol and low density lipoprotein levels among a sample of the Kuwaiti population.

PubMed

Al-Bustan, Suzanne A; Al-Serri, Ahmad E; Annice, Babitha G; Alnaqeeb, Majed A; Ebrahim, Ghada A

2013-09-12

APOAI, a member of the APOAI/CIII/IV/V gene cluster on chromosome 11q23-24, encodes a major protein component of HDL that has been associated with serum lipid levels. The aim of this study was to determine the genetic association of polymorphisms in the APOAI promoter region with plasma lipid levels in a cohort of healthy Kuwaiti volunteers. A 435 bp region of the APOAI promoter was analyzed by re-sequencing in 549 Kuwaiti samples. DNA was extracted from blood taken from 549 healthy Kuwaiti volunteers who had fasted for the previous 12 h. Univariate and multivariate analysis was used to determine allele association with serum lipid levels. The target sequence included a partial segment of the promoter region, 5'UTR and exon 1 located between nucleotides -141 to +294 upstream of the APOAI gene on chromosome 11. No novel single nucleotide polymorphisms (SNPs) were observed. The sequences obtained were deposited with the NCBI GenBank with accession number [GenBank: JX438706]. The allelic frequencies for the three SNPs were as follows: APOAI rs670G = 0.807; rs5069C = 0.964; rs1799837G = 0.997 and found to be in HWE. A significant association (p < 0.05) was observed for the APOAI rs670 polymorphism with increased serum LDL-C. Multivariate analysis showed that APOAI rs670 was an independent predictive factor when controlling for age, sex and BMI for both LDL-C (OR: 1.66, p = 0.014) and TC (OR: 1.77, p = 0.006) levels. This study is the first to report sequence analysis of the APOAI promoter in an Arab population. The unexpected positive association found between the APOAI rs670 polymorphism and increased levels of LDL-C and TC may be due to linkage disequilibrium with other polymorphisms in candidate and neighboring genes known to be associated with lipid metabolism and transport.

Determination of deferasirox plasma concentrations: do gender, physical and genetic differences affect chelation efficacy?

PubMed

Mattioli, Francesca; Puntoni, Matteo; Marini, Valeria; Fucile, Carmen; Milano, Giulia; Robbiano, Luigi; Perrotta, Silverio; Pinto, Valeria; Martelli, Antonietta; Forni, Gian Luca

2015-04-01

Bioavailability of deferasirox (DFX) is significantly affected by the timing of administration relative to times and to composition of meals. Its elimination half-life is also highly variable - in some patients as a result of gene polymorphisms. Understanding whether deferasirox plasma levels are related to specific characteristics of patients could help physicians to devise a drug regimen tailored the individual patient. We analyzed deferasirox plasma concentrations (CDFX ) in 80 patients with transfusion-dependent anemias, such as thalassemia, by a high performance liquid chromatography (HPLC) assay. We used a multivariate linear regression model to find significant associations between CDFX and clinical/demographical characteristics of patients. All patients were genotyped for UGT1A1. Fifty-six patients were female, 24 were male, the great majority (88%) affected by β-thalassemia, and 15 were children and adolescents. No statistical correlation was detectable between CDFX and DFX dose (P = 0.6). Age, time from last drug intake to blood sampling, and ferritin levels in the 6 months before study initiation were significantly and inversely associated with CDFX in univariate analysis. In the multivariate analysis, the only two factors independently and inversely associated with CDFX levels were time from last drug intake to blood sampling and ferritin levels (P = 0.006). A significant inverse correlation (P = 0.03) was observed between CDFX and UGT1A1*28 gene polymorphism, but only in patients with levels of lean body mass (LBM) below the median (P for interaction = 0.05). The results could indicate that a higher plasma DFX concentration could be associated with greater chelation efficacy. As a correlation between dose and CDFX was not demonstrated, it seems useful to monitor the concentrations to optimize and determine the most appropriate dose for each patient. Interesting results emerged from the analysis of genetic and physical characteristics of patients: LBM was a borderline significant effect modifier of the relationship between UGT1A1 polymorphisms and CDFX . Individual patient-tailored dosing of DFX should help to improve iron chelation efficacy and to reduce dose-dependent drug toxicity. © 2014 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Multivariate calibration in Laser-Induced Breakdown Spectroscopy quantitative analysis: The dangers of a 'black box' approach and how to avoid them

NASA Astrophysics Data System (ADS)

Safi, A.; Campanella, B.; Grifoni, E.; Legnaioli, S.; Lorenzetti, G.; Pagnotta, S.; Poggialini, F.; Ripoll-Seguer, L.; Hidalgo, M.; Palleschi, V.

2018-06-01

The introduction of multivariate calibration curve approach in Laser-Induced Breakdown Spectroscopy (LIBS) quantitative analysis has led to a general improvement of the LIBS analytical performances, since a multivariate approach allows to exploit the redundancy of elemental information that are typically present in a LIBS spectrum. Software packages implementing multivariate methods are available in the most diffused commercial and open source analytical programs; in most of the cases, the multivariate algorithms are robust against noise and operate in unsupervised mode. The reverse of the coin of the availability and ease of use of such packages is the (perceived) difficulty in assessing the reliability of the results obtained which often leads to the consideration of the multivariate algorithms as 'black boxes' whose inner mechanism is supposed to remain hidden to the user. In this paper, we will discuss the dangers of a 'black box' approach in LIBS multivariate analysis, and will discuss how to overcome them using the chemical-physical knowledge that is at the base of any LIBS quantitative analysis.

Linear regression analysis and its application to multivariate chromatographic calibration for the quantitative analysis of two-component mixtures.

PubMed

Dinç, Erdal; Ozdemir, Abdil

2005-01-01

Multivariate chromatographic calibration technique was developed for the quantitative analysis of binary mixtures enalapril maleate (EA) and hydrochlorothiazide (HCT) in tablets in the presence of losartan potassium (LST). The mathematical algorithm of multivariate chromatographic calibration technique is based on the use of the linear regression equations constructed using relationship between concentration and peak area at the five-wavelength set. The algorithm of this mathematical calibration model having a simple mathematical content was briefly described. This approach is a powerful mathematical tool for an optimum chromatographic multivariate calibration and elimination of fluctuations coming from instrumental and experimental conditions. This multivariate chromatographic calibration contains reduction of multivariate linear regression functions to univariate data set. The validation of model was carried out by analyzing various synthetic binary mixtures and using the standard addition technique. Developed calibration technique was applied to the analysis of the real pharmaceutical tablets containing EA and HCT. The obtained results were compared with those obtained by classical HPLC method. It was observed that the proposed multivariate chromatographic calibration gives better results than classical HPLC.

Contribution of Genetic Background, Traditional Risk Factors, and HIV-Related Factors to Coronary Artery Disease Events in HIV-Positive Persons

PubMed Central

Rotger, Margalida; Glass, Tracy R.; Junier, Thomas; Lundgren, Jens; Neaton, James D.; Poloni, Estella S.; van 't Wout, Angélique B.; Lubomirov, Rubin; Colombo, Sara; Martinez, Raquel; Rauch, Andri; Günthard, Huldrych F.; Neuhaus, Jacqueline; Wentworth, Deborah; van Manen, Danielle; Gras, Luuk A.; Schuitemaker, Hanneke; Albini, Laura; Torti, Carlo; Jacobson, Lisa P.; Li, Xiuhong; Kingsley, Lawrence A.; Carli, Federica; Guaraldi, Giovanni; Ford, Emily S.; Sereti, Irini; Hadigan, Colleen; Martinez, Esteban; Arnedo, Mireia; Egaña-Gorroño, Lander; Gatell, Jose M.; Law, Matthew; Bendall, Courtney; Petoumenos, Kathy; Rockstroh, Jürgen; Wasmuth, Jan-Christian; Kabamba, Kabeya; Delforge, Marc; De Wit, Stephane; Berger, Florian; Mauss, Stefan; de Paz Sierra, Mariana; Losso, Marcelo; Belloso, Waldo H.; Leyes, Maria; Campins, Antoni; Mondi, Annalisa; De Luca, Andrea; Bernardino, Ignacio; Barriuso-Iglesias, Mónica; Torrecilla-Rodriguez, Ana; Gonzalez-Garcia, Juan; Arribas, José R.; Fanti, Iuri; Gel, Silvia; Puig, Jordi; Negredo, Eugenia; Gutierrez, Mar; Domingo, Pere; Fischer, Julia; Fätkenheuer, Gerd; Alonso-Villaverde, Carlos; Macken, Alan; Woo, James; McGinty, Tara; Mallon, Patrick; Mangili, Alexandra; Skinner, Sally; Wanke, Christine A.; Reiss, Peter; Weber, Rainer; Bucher, Heiner C.; Fellay, Jacques; Telenti, Amalio; Tarr, Philip E.

2013-01-01

Background Persons infected with human immunodeficiency virus (HIV) have increased rates of coronary artery disease (CAD). The relative contribution of genetic background, HIV-related factors, antiretroviral medications, and traditional risk factors to CAD has not been fully evaluated in the setting of HIV infection. Methods In the general population, 23 common single-nucleotide polymorphisms (SNPs) were shown to be associated with CAD through genome-wide association analysis. Using the Metabochip, we genotyped 1875 HIV-positive, white individuals enrolled in 24 HIV observational studies, including 571 participants with a first CAD event during the 9-year study period and 1304 controls matched on sex and cohort. Results A genetic risk score built from 23 CAD-associated SNPs contributed significantly to CAD (P = 2.9×10−4). In the final multivariable model, participants with an unfavorable genetic background (top genetic score quartile) had a CAD odds ratio (OR) of 1.47 (95% confidence interval [CI], 1.05–2.04). This effect was similar to hypertension (OR = 1.36; 95% CI, 1.06–1.73), hypercholesterolemia (OR = 1.51; 95% CI, 1.16–1.96), diabetes (OR = 1.66; 95% CI, 1.10–2.49), ≥1 year lopinavir exposure (OR = 1.36; 95% CI, 1.06–1.73), and current abacavir treatment (OR = 1.56; 95% CI, 1.17–2.07). The effect of the genetic risk score was additive to the effect of nongenetic CAD risk factors, and did not change after adjustment for family history of CAD. Conclusions In the setting of HIV infection, the effect of an unfavorable genetic background was similar to traditional CAD risk factors and certain adverse antiretroviral exposures. Genetic testing may provide prognostic information complementary to family history of CAD. PMID:23532479

Genetic and epigenetic regulation of YKL-40 in childhood.

PubMed

Guerra, Stefano; Melén, Erik; Sunyer, Jordi; Xu, Cheng-Jian; Lavi, Iris; Benet, Marta; Bustamante, Mariona; Carsin, Anne-Elie; Dobaño, Carlota; Guxens, Mònica; Tischer, Christina; Vrijheid, Martine; Kull, Inger; Bergström, Anna; Kumar, Ashish; Söderhäll, Cilla; Gehring, Ulrike; Dijkstra, Dorieke J; van der Vlies, Pieter; Wickman, Magnus; Bousquet, Jean; Postma, Dirkje S; Anto, Josep M; Koppelman, Gerard H

2018-03-01

Circulating levels of the chitinase-like protein YKL-40 are influenced by genetic variation in its encoding gene (chitinase 3-like 1 [CHI3L1]) and are increased in patients with several diseases, including asthma. Epigenetic regulation of circulating YKL-40 early in life is unknown. We sought to determine (1) whether methylation levels at CHI3L1 CpG sites mediate the association of CHI3L1 single nucleotide polymorphisms (SNPs) with YKL-40 levels in the blood and (2) whether these biomarkers (CHI3L1 SNPs, methylation profiles, and YKL-40 levels) are associated with asthma in early childhood. We used data from up to 2405 participants from the Spanish Infancia y Medio Ambiente; the Swedish Barn/Children, Allergy, Milieu, Stockholm, Epidemiological survey; and the Dutch Prevention and Incidence of Asthma and Mite Allergy birth cohorts. Associations between 68 CHI3L1 SNPs, methylation levels at 14 CHI3L1 CpG sites in whole-blood DNA, and circulating YKL-40 levels at 4 years of age were tested by using correlation analysis, multivariable regression, and mediation analysis. Each of these biomarkers was also tested for association with asthma at 4 years of age by using multivariable logistic regression. YKL-40 levels were significantly associated with 7 SNPs and with methylation at 5 CpG sites. Consistent associations between these 7 SNPs (particularly rs10399931 and rs4950928) and 5 CpG sites were observed. Alleles linked to lower YKL-40 levels were associated with higher methylation levels. Participants with high YKL-40 levels (defined as the highest YKL-40 tertile) had increased odds for asthma compared with subjects with low YKL-40 levels (meta-analyzed adjusted odds ratio, 1.90 [95% CI, 1.08-3.36]). In contrast, neither SNPs nor methylation levels at CpG sites in CHI3L1 were associated with asthma. The effects of CHI3L1 genetic variation on circulating YKL-40 levels are partly mediated by methylation profiles. In our study YKL-40 levels, but not CHI3L1 SNPs or methylation levels, were associated with childhood asthma. Copyright © 2017 American Academy of Allergy, Asthma & Immunology. Published by Elsevier Inc. All rights reserved.

Multivariate analyses of crater parameters and the classification of craters

NASA Technical Reports Server (NTRS)

Siegal, B. S.; Griffiths, J. C.

1974-01-01

Multivariate analyses were performed on certain linear dimensions of six genetic types of craters. A total of 320 craters, consisting of laboratory fluidization craters, craters formed by chemical and nuclear explosives, terrestrial maars and other volcanic craters, and terrestrial meteorite impact craters, authenticated and probable, were analyzed in the first data set in terms of their mean rim crest diameter, mean interior relief, rim height, and mean exterior rim width. The second data set contained an additional 91 terrestrial craters of which 19 were of experimental percussive impact and 28 of volcanic collapse origin, and which was analyzed in terms of mean rim crest diameter, mean interior relief, and rim height. Principal component analyses were performed on the six genetic types of craters. Ninety per cent of the variation in the variables can be accounted for by two components. Ninety-nine per cent of the variation in the craters formed by chemical and nuclear explosives is explained by the first component alone.

Analysis of genetic population structure in Acacia caven (Leguminosae, Mimosoideae), comparing one exploratory and two Bayesian-model-based methods.

PubMed

Pometti, Carolina L; Bessega, Cecilia F; Saidman, Beatriz O; Vilardi, Juan C

2014-03-01

Bayesian clustering as implemented in STRUCTURE or GENELAND software is widely used to form genetic groups of populations or individuals. On the other hand, in order to satisfy the need for less computer-intensive approaches, multivariate analyses are specifically devoted to extracting information from large datasets. In this paper, we report the use of a dataset of AFLP markers belonging to 15 sampling sites of Acacia caven for studying the genetic structure and comparing the consistency of three methods: STRUCTURE, GENELAND and DAPC. Of these methods, DAPC was the fastest one and showed accuracy in inferring the K number of populations (K = 12 using the find.clusters option and K = 15 with a priori information of populations). GENELAND in turn, provides information on the area of membership probabilities for individuals or populations in the space, when coordinates are specified (K = 12). STRUCTURE also inferred the number of K populations and the membership probabilities of individuals based on ancestry, presenting the result K = 11 without prior information of populations and K = 15 using the LOCPRIOR option. Finally, in this work all three methods showed high consistency in estimating the population structure, inferring similar numbers of populations and the membership probabilities of individuals to each group, with a high correlation between each other.

Genetic association analysis of Osteopontin and Matrix Gla Protein genes polymorphisms with primary knee osteoarthritis in Mexican population.

PubMed

Borgonio-Cuadra, Verónica Marusa; González-Huerta, Norma Celia; Rojas-Toledo, Emma Xochitl; Morales-Hernández, Eugenio; Pérez-Hernández, Nonanzit; Rodríguez-Pérez, José Manuel; Tovilla-Zárate, Carlos Alfonso; González-Castro, Thelma Beatriz; Hernández-Díaz, Yazmín; López-Narváez, María Lilia; Miranda-Duarte, Antonio

2018-05-18

Primary osteoarthritis (OA) is a complex entity in which several loci related to different molecular pathways or classes of molecules are associated with its development as demonstrated through genetic association studies. Genes involved in bone formation and mineralization, such as osteopontin (OPN) and Matrix Gla protein (MGP), could also be related with OA. The aim of this study was to evaluate the association between the genetic variants of OPN and MGP with primary knee osteoarthritis in a Mexican population. A case-control study was conducted in 296 patients with primary knee osteoarthritis and in 354 control subjects. Study groups were assessed radiologically. The rs11730582 of OPN and rs1800802, rs1800801, and rs4236 of MGP were determined by TaqMan allele discrimination assays. The haplotypes of the polymorphisms of MGP were constructed. The association was tested through univariate and multivariate non-conditional logistic regression analyses. The polymorphisms of MGP complied with Hardy-Weinberg (HW) equilibrium. The polymorphisms of OPN and MGP were not significantly associated with primary knee osteoarthritis in the codominant, dominant, and recessive models (p > 0.05). Our study suggests that there are no associations between OPN and MGP polymorphisms with primary knee osteoarthritis in Mexican population.

The methylation status of RASSF1A promoter predicts responsiveness to chemotherapy and eventual cure in hepatoblastoma patients.

PubMed

Honda, Shohei; Haruta, Masayuki; Sugawara, Waka; Sasaki, Fumiaki; Ohira, Miki; Matsunaga, Tadashi; Yamaoka, Hiroaki; Horie, Hiroshi; Ohnuma, Naomi; Nakagawara, Akira; Hiyama, Eiso; Todo, Satoru; Kaneko, Yasuhiko

2008-09-01

Despite the progress of therapy, outcomes of advanced hepatoblastoma patients who are refractory to standard preoperative chemotherapy remain unsatisfactory. To improve the mortality rate, novel prognostic markers are needed for better therapy planning. We examined the methylation status of 13 candidate tumor suppressor genes in 20 hepatoblastoma tumors by conventional methylation-specific PCR (MSP) and found hypermethylation in 3 of the 13 genes. We analyzed the methylation status of these 3 genes (RASSF1A, SOCS1 and CASP8) in 97 tumors and found hypermethylation in 30.9, 33.0 and 15.5%, respectively. Univariate analysis showed that only the methylation status of RASSF1A but not the other 2 genes predicted the outcome, and multivariate analysis showed a weak contribution of RASSF1A methylation to overall survival. Using quantitative MSP, we found RASSF1A methylation in 44.3% of the 97 tumors. CTNNB1 mutation was detected in 67.0% of the 97 tumors. While univariate analysis demonstrated RASSF1A methylation, CTNNB1 mutation and other clinicopathological variables as prognostic factors, multivariate analysis identified RASSF1A methylation (p = 0.043; relative risk 9.39) and the disease stage (p = 0.002; relative risk 7.67) but not CTNNB1 mutation as independent prognostic factors. In survival analysis of 33 patients in stage 3B or 4, patients with unmethylated tumor had better overall survival than those with methylated tumor (p = 0.035). RASSF1A methylation may be a promising molecular-genetic marker to predict the treatment outcome and may be used to stratify patients when clinical trials are carried out.

Multivariate analysis: A statistical approach for computations

NASA Astrophysics Data System (ADS)

Michu, Sachin; Kaushik, Vandana

2014-10-01

Multivariate analysis is a type of multivariate statistical approach commonly used in, automotive diagnosis, education evaluating clusters in finance etc and more recently in the health-related professions. The objective of the paper is to provide a detailed exploratory discussion about factor analysis (FA) in image retrieval method and correlation analysis (CA) of network traffic. Image retrieval methods aim to retrieve relevant images from a collected database, based on their content. The problem is made more difficult due to the high dimension of the variable space in which the images are represented. Multivariate correlation analysis proposes an anomaly detection and analysis method based on the correlation coefficient matrix. Anomaly behaviors in the network include the various attacks on the network like DDOs attacks and network scanning.

Effectiveness of the combined evaluation of KLK3 genetics and free-to-total prostate specific antigen ratio for prostate cancer diagnosis.

PubMed

Zambon, Carlo-Federico; Prayer-Galetti, Tommaso; Basso, Daniela; Padoan, Andrea; Rossi, Elisa; Secco, Silvia; Pelloso, Michela; Fogar, Paola; Navaglia, Filippo; Moz, Stefania; Zattoni, Filiberto; Plebani, Mario

2012-10-01

Of serum prostate specific antigen variability 40% depends on inherited factors. We ascertained whether the knowledge of KLK3 genetics would enhance prostate specific antigen diagnostic performance in patients with clinical suspicion of prostate cancer. We studied 1,058 men who consecutively underwent prostate biopsy for clinical suspicion of prostate cancer. At histology prostate cancer was present in 401 cases and absent in 657. Serum total prostate specific antigen and the free-to-total prostate specific antigen ratio were determined. Four polymorphisms of the KLK3 gene (rs2569733, rs2739448, rs925013 and rs2735839) and 1 polymorphism of the SRD5A2 gene (rs523349) were studied. The influence of genetics on prostate specific antigen variability was evaluated by multivariate linear regression analysis. The performance of total prostate specific antigen and the free-to-total prostate specific antigen ratio alone or combined with a genetically based patient classification were defined by ROC curve analyses. For prostate cancer diagnosis the free-to-total prostate specific antigen ratio index alone (cutoff 11%) was superior to total prostate specific antigen (cutoff 4 ng/ml) and to free-to-total prostate specific antigen ratio reflex testing (positive predictive value 61%, 43% and 54%, respectively). Prostate specific antigen correlated with KLK3 genetics (rs2735839 polymorphism p = 0.001, and rs2569733, rs2739448 and rs925013 haplotype combination p = 0.003). In patients with different KLK3 genetics 2 optimal free-to-total prostate specific antigen ratio cutoffs (11% and 14.5%) were found. For free-to-total prostate specific antigen ratio values between 11% and 14.5% the prostate cancer probability ranged from 30.0% to 47.4% according to patient genetics. The free-to-total prostate specific antigen ratio is superior to total prostate specific antigen for prostate cancer diagnosis, independent of total prostate specific antigen results. Free-to-total prostate specific antigen ratio findings below 11% are positively associated with prostate cancer and those above 14.5% are negatively associated with prostate cancer, while the interpretation of those between 11% and 14.5% is improved by patient KLK3 genetic analysis. Copyright © 2012 American Urological Association Education and Research, Inc. Published by Elsevier Inc. All rights reserved.

Multivariate Cluster Analysis.

ERIC Educational Resources Information Center

McRae, Douglas J.

Procedures for grouping students into homogeneous subsets have long interested educational researchers. The research reported in this paper is an investigation of a set of objective grouping procedures based on multivariate analysis considerations. Four multivariate functions that might serve as criteria for adequate grouping are given and…

Clinical Significance of MLH1 Methylation and CpG Island Methylator Phenotype as Prognostic Markers in Patients with Gastric Cancer

PubMed Central

Shigeyasu, Kunitoshi; Nagasaka, Takeshi; Mori, Yoshiko; Yokomichi, Naosuke; Kawai, Takashi; Fuji, Tomokazu; Kimura, Keisuke; Umeda, Yuzo; Kagawa, Shunsuke; Goel, Ajay; Fujiwara, Toshiyoshi

2015-01-01

Background To improve the outcome of patients suffering from gastric cancer, a better understanding of underlying genetic and epigenetic events in this malignancy is required. Although CpG island methylator phenotype (CIMP) and microsatellite instability (MSI) have been shown to play pivotal roles in gastric cancer pathogenesis, the clinical significance of these events on survival outcomes in patients with gastric cancer remains unknown. Methods This study included a patient cohort with pathologically confirmed gastric cancer who had surgical resections. A cohort of 68 gastric cancers was analyzed. CIMP and MSI statuses were determined by analyzing promoter CpG island methylation status of 28 genes/loci, and genomic instability at 10 microsatellite markers, respectively. A Cox’s proportional hazards model was performed for multivariate analysis including age, stage, tumor differentiation, KRAS mutation status, and combined CIMP/MLH1 methylation status in relation to overall survival (OS). Results By multivariate analysis, longer OS was significantly correlated with lower pathologic stage (P = 0.0088), better tumor differentiation (P = 0.0267) and CIMP-high and MLH1 3' methylated status (P = 0.0312). Stratification of CIMP status with regards to MLH1 methylation status further enabled prediction of gastric cancer prognosis. Conclusions CIMP and/or MLH1 methylation status may have a potential to be prognostic biomarkers for patients with gastric cancer. PMID:26121593

Patient preference: a comparison of electronic patient-completed questionnaires with paper among cancer patients.

PubMed

Martin, P; Brown, M C; Espin-Garcia, O; Cuffe, S; Pringle, D; Mahler, M; Villeneuve, J; Niu, C; Charow, R; Lam, C; Shani, R M; Hon, H; Otsuka, M; Xu, W; Alibhai, S; Jenkinson, J; Liu, G

2016-03-01

In this study, we compared cancer patients preference for computerised (tablet/web-based) surveys versus paper. We also assessed whether the understanding of a cancer-related topic, pharmacogenomics is affected by the survey format, and examined differences in demographic and medical characteristics which may affect patient preference and understanding. Three hundred and four cancer patients completed a tablet-administered survey and another 153 patients completed a paper-based survey. Patients who participated in the tablet survey were questioned regarding their preference for survey format administration (paper, tablet and web-based). Understanding was assessed with a 'direct' method, by asking patients to assess their understanding of genetic testing, and with a 'composite' score. Patients preferred administration with tablet (71%) compared with web-based (12%) and paper (17%). Patients <65 years old, non-Caucasians and white-collar professionals significantly preferred the computerised format following multivariate analysis. There was no significant difference in understanding between the paper and tablet survey with direct questioning or composite score. Age (<65 years) and white-collar professionals were associated with increased understanding (both P = 0.03). There was no significant difference in understanding between the tablet and print survey in a multivariate analysis. Patients overwhelmingly preferred computerised surveys and understanding of pharmacogenomics was not affected by survey format. © 2015 John Wiley & Sons Ltd.

A data-driven investigation of relationships between bipolar psychotic symptoms and schizophrenia genome-wide significant genetic loci.

PubMed

Leonenko, Ganna; Di Florio, Arianna; Allardyce, Judith; Forty, Liz; Knott, Sarah; Jones, Lisa; Gordon-Smith, Katherine; Owen, Michael J; Jones, Ian; Walters, James; Craddock, Nick; O'Donovan, Michael C; Escott-Price, Valentina

2018-06-01

The etiologies of bipolar disorder (BD) and schizophrenia include a large number of common risk alleles, many of which are shared across the disorders. BD is clinically heterogeneous and it has been postulated that the pattern of symptoms is in part determined by the particular risk alleles carried, and in particular, that risk alleles also confer liability to schizophrenia influence psychotic symptoms in those with BD. To investigate links between psychotic symptoms in BD and schizophrenia risk alleles we employed a data-driven approach in a genotyped and deeply phenotyped sample of subjects with BD. We used sparse canonical correlation analysis (sCCA) (Witten, Tibshirani, & Hastie, ) to analyze 30 psychotic symptoms, assessed with the OPerational CRITeria checklist, and 82 independent genome-wide significant single nucleotide polymorphisms (SNPs) identified by the Schizophrenia Working group of the Psychiatric Genomics Consortium for which we had data in our BD sample (3,903 subjects). As a secondary analysis, we applied sCCA to larger groups of SNPs, and also to groups of symptoms defined according to a published factor analyses of schizophrenia. sCCA analysis based on individual psychotic symptoms revealed a significant association (p = .033), with the largest weights attributed to a variant on chromosome 3 (rs11411529), chr3:180594593, build 37) and delusions of influence, bizarre behavior and grandiose delusions. sCCA analysis using the same set of SNPs supported association with the same SNP and the group of symptoms defined "factor 3" (p = .012). A significant association was also observed to the "factor 3" phenotype group when we included a greater number of SNPs that were less stringently associated with schizophrenia; although other SNPs contributed to the significant multivariate association result, the greatest weight remained assigned to rs11411529. Our results suggest that the canonical correlation is a useful tool to explore phenotype-genotype relationships. To the best of our knowledge, this is the first study to apply this approach to complex, polygenic psychiatric traits. The sparse canonical correlation approach offers the potential to include a larger number of fine-grained systematic descriptors, and to include genetic markers associated with other disorders that are genetically correlated with BD. © 2018 The Authors. American Journal of Medical Genetics Part B: Neuropsychiatric Genetics Published by Wiley Periodicals, Inc.

Repint of "Reframing autism as a behavioral syndrome and not a specific mental disorder: Implications of genetic and phenotypic heterogeneity".

PubMed

Tordjman, S; Cohen, D; Anderson, G M; Botbol, M; Canitano, R; Coulon, N; Roubertoux, P L

2018-06-01

Clinical and molecular genetics have advanced current knowledge on genetic disorders associated with autism. A review of diverse genetic disorders associated with autism is presented and for the first time discussed extensively with regard to possible common underlying mechanisms leading to a similar cognitive-behavioral phenotype of autism. The possible role of interactions between genetic and environmental factors, including epigenetic mechanisms, is in particular examined. Finally, the pertinence of distinguishing non-syndromic autism (isolated autism) from syndromic autism (autism associated with genetic disorders) will be reconsidered. Given the high genetic and etiological heterogeneity of autism, autism can be viewed as a behavioral syndrome related to known genetic disorders (syndromic autism) or currently unknown disorders (apparent non-syndromic autism), rather than a specific categorical mental disorder. It highlights the need to study autism phenotype and developmental trajectory through a multidimensional, non-categorical approach with multivariate analyses within autism spectrum disorder but also across mental disorders, and to conduct systematically clinical genetic examination searching for genetic disorders in all individuals (children but also adults) with autism. Copyright © 2018. Published by Elsevier Ltd.

Genetic Particle Swarm Optimization-Based Feature Selection for Very-High-Resolution Remotely Sensed Imagery Object Change Detection.

PubMed

Chen, Qiang; Chen, Yunhao; Jiang, Weiguo

2016-07-30

In the field of multiple features Object-Based Change Detection (OBCD) for very-high-resolution remotely sensed images, image objects have abundant features and feature selection affects the precision and efficiency of OBCD. Through object-based image analysis, this paper proposes a Genetic Particle Swarm Optimization (GPSO)-based feature selection algorithm to solve the optimization problem of feature selection in multiple features OBCD. We select the Ratio of Mean to Variance (RMV) as the fitness function of GPSO, and apply the proposed algorithm to the object-based hybrid multivariate alternative detection model. Two experiment cases on Worldview-2/3 images confirm that GPSO can significantly improve the speed of convergence, and effectively avoid the problem of premature convergence, relative to other feature selection algorithms. According to the accuracy evaluation of OBCD, GPSO is superior at overall accuracy (84.17% and 83.59%) and Kappa coefficient (0.6771 and 0.6314) than other algorithms. Moreover, the sensitivity analysis results show that the proposed algorithm is not easily influenced by the initial parameters, but the number of features to be selected and the size of the particle swarm would affect the algorithm. The comparison experiment results reveal that RMV is more suitable than other functions as the fitness function of GPSO-based feature selection algorithm.

Redescription of Nemachilichthys rueppelli, a senior synonym of N. shimogensis (Teleostei: Nemacheilidae).

PubMed

Keskar, Ashwini; Kumkar, Pradeep; Katwate, Unmesh; Ali, Anvar; Raghavan, Rajeev; Dahanukar, Neelesh

2015-12-23

The hill-stream loach genus Nemachilichthys, an endemic of the Western Ghats of India, comprises two nominal species, N. rueppelli and N. shimogensis. The validity of the latter has been questioned by several authors. Here we show that there is only a marginal raw mitochondrial genetic distance (0.5% in cytochrome oxidase subunit I and 1.2% in cytochrome b) between topotypic specimens of the two nominal species. Further, although population-level morphometric variations appear in a multivariate morphometric analysis, the two nominal species are morphologically similar, with apparently no significant characters separating them. We therefore consider N. shimogensis to be a junior synonym of N. rueppelli and redescribe the latter, providing further details on population variation and distribution.

Comparative forensic soil analysis of New Jersey state parks using a combination of simple techniques with multivariate statistics.

PubMed

Bonetti, Jennifer; Quarino, Lawrence

2014-05-01

This study has shown that the combination of simple techniques with the use of multivariate statistics offers the potential for the comparative analysis of soil samples. Five samples were obtained from each of twelve state parks across New Jersey in both the summer and fall seasons. Each sample was examined using particle-size distribution, pH analysis in both water and 1 M CaCl2 , and a loss on ignition technique. Data from each of the techniques were combined, and principal component analysis (PCA) and canonical discriminant analysis (CDA) were used for multivariate data transformation. Samples from different locations could be visually differentiated from one another using these multivariate plots. Hold-one-out cross-validation analysis showed error rates as low as 3.33%. Ten blind study samples were analyzed resulting in no misclassifications using Mahalanobis distance calculations and visual examinations of multivariate plots. Seasonal variation was minimal between corresponding samples, suggesting potential success in forensic applications. © 2014 American Academy of Forensic Sciences.

A multivariate ecogeographic analysis of macaque craniodental variation.

PubMed

Grunstra, Nicole D S; Mitteroecker, Philipp; Foley, Robert A

2018-06-01

To infer the ecogeographic conditions that underlie the evolutionary diversification of macaques, we investigated the within- and between-species relationships of craniodental dimensions, geography, and environment in extant macaque species. We studied evolutionary processes by contrasting macroevolutionary patterns, phylogeny, and within-species associations. Sixty-three linear measurements of the permanent dentition and skull along with data about climate, ecology (environment), and spatial geography were collected for 711 specimens of 12 macaque species and analyzed by a multivariate approach. Phylogenetic two-block partial least squares was used to identify patterns of covariance between craniodental and environmental variation. Phylogenetic reduced rank regression was employed to analyze spatial clines in morphological variation. Between-species associations consisted of two distinct multivariate patterns. The first represents overall craniodental size and is negatively associated with temperature and habitat, but positively with latitude. The second pattern shows an antero-posterior tooth size contrast related to diet, rainfall, and habitat productivity. After controlling for phylogeny, however, the latter dimension was diminished. Within-species analyses neither revealed significant association between morphology, environment, and geography, nor evidence of isolation by distance. We found evidence for environmental adaptation in macaque body and craniodental size, primarily driven by selection for thermoregulation. This pattern cannot be explained by the within-species pattern, indicating an evolved genetic basis for the between-species relationship. The dietary signal in relative tooth size, by contrast, can largely be explained by phylogeny. This cautions against adaptive interpretations of phenotype-environment associations when phylogeny is not explicitly modelled. © 2018 Wiley Periodicals, Inc.

Quantifying the impact of between-study heterogeneity in multivariate meta-analyses

PubMed Central

Jackson, Dan; White, Ian R; Riley, Richard D

2012-01-01

Measures that quantify the impact of heterogeneity in univariate meta-analysis, including the very popular I2 statistic, are now well established. Multivariate meta-analysis, where studies provide multiple outcomes that are pooled in a single analysis, is also becoming more commonly used. The question of how to quantify heterogeneity in the multivariate setting is therefore raised. It is the univariate R2 statistic, the ratio of the variance of the estimated treatment effect under the random and fixed effects models, that generalises most naturally, so this statistic provides our basis. This statistic is then used to derive a multivariate analogue of I2, which we call . We also provide a multivariate H2 statistic, the ratio of a generalisation of Cochran's heterogeneity statistic and its associated degrees of freedom, with an accompanying generalisation of the usual I2 statistic, . Our proposed heterogeneity statistics can be used alongside all the usual estimates and inferential procedures used in multivariate meta-analysis. We apply our methods to some real datasets and show how our statistics are equally appropriate in the context of multivariate meta-regression, where study level covariate effects are included in the model. Our heterogeneity statistics may be used when applying any procedure for fitting the multivariate random effects model. Copyright © 2012 John Wiley & Sons, Ltd. PMID:22763950

Inherited genetic variants associated with occurrence of multiple primary melanoma.

PubMed

Gibbs, David C; Orlow, Irene; Kanetsky, Peter A; Luo, Li; Kricker, Anne; Armstrong, Bruce K; Anton-Culver, Hoda; Gruber, Stephen B; Marrett, Loraine D; Gallagher, Richard P; Zanetti, Roberto; Rosso, Stefano; Dwyer, Terence; Sharma, Ajay; La Pilla, Emily; From, Lynn; Busam, Klaus J; Cust, Anne E; Ollila, David W; Begg, Colin B; Berwick, Marianne; Thomas, Nancy E

2015-06-01

Recent studies, including genome-wide association studies, have identified several putative low-penetrance susceptibility loci for melanoma. We sought to determine their generalizability to genetic predisposition for multiple primary melanoma in the international population-based Genes, Environment, and Melanoma (GEM) Study. GEM is a case-control study of 1,206 incident cases of multiple primary melanoma and 2,469 incident first primary melanoma participants as the control group. We investigated the odds of developing multiple primary melanoma for 47 SNPs from 21 distinct genetic regions previously reported to be associated with melanoma. ORs and 95% confidence intervals were determined using logistic regression models adjusted for baseline features (age, sex, age by sex interaction, and study center). We investigated univariable models and built multivariable models to assess independent effects of SNPs. Eleven SNPs in 6 gene neighborhoods (TERT/CLPTM1L, TYRP1, MTAP, TYR, NCOA6, and MX2) and a PARP1 haplotype were associated with multiple primary melanoma. In a multivariable model that included only the most statistically significant findings from univariable modeling and adjusted for pigmentary phenotype, back nevi, and baseline features, we found TERT/CLPTM1L rs401681 (P = 0.004), TYRP1 rs2733832 (P = 0.006), MTAP rs1335510 (P = 0.0005), TYR rs10830253 (P = 0.003), and MX2 rs45430 (P = 0.008) to be significantly associated with multiple primary melanoma, while NCOA6 rs4911442 approached significance (P = 0.06). The GEM Study provides additional evidence for the relevance of these genetic regions to melanoma risk and estimates the magnitude of the observed genetic effect on development of subsequent primary melanoma. ©2015 American Association for Cancer Research.

Inherited genetic variants associated with occurrence of multiple primary melanoma

PubMed Central

Gibbs, David C.; Orlow, Irene; Kanetsky, Peter A.; Luo, Li; Kricker, Anne; Armstrong, Bruce K.; Anton-Culver, Hoda; Gruber, Stephen B.; Marrett, Loraine D.; Gallagher, Richard P.; Zanetti, Roberto; Rosso, Stefano; Dwyer, Terence; Sharma, Ajay; La Pilla, Emily; From, Lynn; Busam, Klaus J.; Cust, Anne E.; Ollila, David W.; Begg, Colin B.; Berwick, Marianne; Thomas, Nancy E.

2015-01-01

Recent studies including genome-wide association studies have identified several putative low-penetrance susceptibility loci for melanoma. We sought to determine their generalizability to genetic predisposition for multiple primary melanoma in the international population-based Genes, Environment, and Melanoma (GEM) Study. GEM is a case-control study of 1,206 incident cases of multiple primary melanoma and 2,469 incident first primary melanoma participants as the control group. We investigated the odds of developing multiple primary melanoma for 47 single nucleotide polymorphisms (SNP) from 21 distinct genetic regions previously reported to be associated with melanoma. ORs and 95% CIs were determined using logistic regression models adjusted for baseline features (age, sex, age by sex interaction, and study center). We investigated univariable models and built multivariable models to assess independent effects of SNPs. Eleven SNPs in 6 gene neighborhoods (TERT/CLPTM1L, TYRP1, MTAP, TYR, NCOA6, and MX2) and a PARP1 haplotype were associated with multiple primary melanoma. In a multivariable model that included only the most statistically significant findings from univariable modeling and adjusted for pigmentary phenotype, back nevi, and baseline features, we found TERT/CLPTM1L rs401681 (P = 0.004), TYRP1 rs2733832 (P = 0.006), MTAP rs1335510 (P = 0.0005), TYR rs10830253 (P = 0.003), and MX2 rs45430 (P = 0.008) to be significantly associated with multiple primary melanoma while NCOA6 rs4911442 approached significance (P = 0.06). The GEM study provides additional evidence for the relevance of these genetic regions to melanoma risk and estimates the magnitude of the observed genetic effect on development of subsequent primary melanoma. PMID:25837821

Role of Blood Lipids in the Development of Ischemic Stroke and its Subtypes

PubMed Central

Engström, Gunnar; Larsson, Susanna C.; Traylor, Matthew; Markus, Hugh S.; Melander, Olle; Orho-Melander, Marju

2018-01-01

Background and Purpose— Statin therapy is associated with a lower risk of ischemic stroke supporting a causal role of low-density lipoprotein (LDL) cholesterol. However, more evidence is needed to answer the question whether LDL cholesterol plays a causal role in ischemic stroke subtypes. In addition, it is unknown whether high-density lipoprotein cholesterol and triglycerides have a causal relationship to ischemic stroke and its subtypes. Our aim was to investigate the causal role of LDL cholesterol, high-density lipoprotein cholesterol, and triglycerides in ischemic stroke and its subtypes through Mendelian randomization (MR). Methods— Summary data on 185 genome-wide lipids-associated single nucleotide polymorphisms were obtained from the Global Lipids Genetics Consortium and the Stroke Genetics Network for their association with ischemic stroke (n=16 851 cases and 32 473 controls) and its subtypes, including large artery atherosclerosis (n=2410), small artery occlusion (n=3186), and cardioembolic (n=3427) stroke. Inverse-variance–weighted MR was used to obtain the causal estimates. Inverse-variance–weighted multivariable MR, MR-Egger, and sensitivity exclusion of pleiotropic single nucleotide polymorphisms after Steiger filtering and MR-Pleiotropy Residual Sum and Outlier test were used to adjust for pleiotropic bias. Results— A 1-SD genetically elevated LDL cholesterol was associated with an increased risk of ischemic stroke (odds ratio: 1.12; 95% confidence interval: 1.04–1.20) and large artery atherosclerosis stroke (odds ratio: 1.28; 95% confidence interval: 1.10–1.49) but not with small artery occlusion or cardioembolic stroke in multivariable MR. A 1-SD genetically elevated high-density lipoprotein cholesterol was associated with a decreased risk of small artery occlusion stroke (odds ratio: 0.79; 95% confidence interval: 0.67–0.90) in multivariable MR. MR-Egger indicated no pleiotropic bias, and results did not markedly change after sensitivity exclusion of pleiotropic single nucleotide polymorphisms. Genetically elevated triglycerides did not associate with ischemic stroke or its subtypes. Conclusions— LDL cholesterol lowering is likely to prevent large artery atherosclerosis but may not prevent small artery occlusion nor cardioembolic strokes. High-density lipoprotein cholesterol elevation may lead to benefits in small artery disease prevention. Finally, triglyceride lowering may not yield benefits in ischemic stroke and its subtypes. PMID:29535274

Near-exact distributions for the block equicorrelation and equivariance likelihood ratio test statistic

NASA Astrophysics Data System (ADS)

Coelho, Carlos A.; Marques, Filipe J.

2013-09-01

In this paper the authors combine the equicorrelation and equivariance test introduced by Wilks [13] with the likelihood ratio test (l.r.t.) for independence of groups of variables to obtain the l.r.t. of block equicorrelation and equivariance. This test or its single block version may find applications in many areas as in psychology, education, medicine, genetics and they are important "in many tests of multivariate analysis, e.g. in MANOVA, Profile Analysis, Growth Curve analysis, etc" [12, 9]. By decomposing the overall hypothesis into the hypotheses of independence of groups of variables and the hypothesis of equicorrelation and equivariance we are able to obtain the expressions for the overall l.r.t. statistic and its moments. From these we obtain a suitable factorization of the characteristic function (c.f.) of the logarithm of the l.r.t. statistic, which enables us to develop highly manageable and precise near-exact distributions for the test statistic.

Parasites as valuable stock markers for fisheries in Australasia, East Asia and the Pacific Islands.

PubMed

Lester, R J G; Moore, B R

2015-01-01

Over 30 studies in Australasia, East Asia and the Pacific Islands region have collected and analysed parasite data to determine the ranges of individual fish, many leading to conclusions about stock delineation. Parasites used as biological tags have included both those known to have long residence times in the fish and those thought to be relatively transient. In many cases the parasitological conclusions have been supported by other methods especially analysis of the chemical constituents of otoliths, and to a lesser extent, genetic data. In analysing parasite data, authors have applied multiple different statistical methodologies, including summary statistics, and univariate and multivariate approaches. Recently, a growing number of researchers have found non-parametric methods, such as analysis of similarities and cluster analysis, to be valuable. Future studies into the residence times, life cycles and geographical distributions of parasites together with more robust analytical methods will yield much important information to clarify stock structures in the area.

Analyzing Multiple Outcomes in Clinical Research Using Multivariate Multilevel Models

PubMed Central

Baldwin, Scott A.; Imel, Zac E.; Braithwaite, Scott R.; Atkins, David C.

2014-01-01

Objective Multilevel models have become a standard data analysis approach in intervention research. Although the vast majority of intervention studies involve multiple outcome measures, few studies use multivariate analysis methods. The authors discuss multivariate extensions to the multilevel model that can be used by psychotherapy researchers. Method and Results Using simulated longitudinal treatment data, the authors show how multivariate models extend common univariate growth models and how the multivariate model can be used to examine multivariate hypotheses involving fixed effects (e.g., does the size of the treatment effect differ across outcomes?) and random effects (e.g., is change in one outcome related to change in the other?). An online supplemental appendix provides annotated computer code and simulated example data for implementing a multivariate model. Conclusions Multivariate multilevel models are flexible, powerful models that can enhance clinical research. PMID:24491071

Individual Differences in Executive Functions Are Almost Entirely Genetic in Origin

ERIC Educational Resources Information Center

Friedman, Naomi P.; Miyake, Akira; Young, Susan E.; DeFries, John C.; Corley, Robin P.; Hewitt, John K.

2008-01-01

Recent psychological and neuropsychological research suggests that executive functions--the cognitive control processes that regulate thought and action--are multifaceted and that different types of executive functions are correlated but separable. The present multivariate twin study of 3 executive functions (inhibiting dominant responses,…

Quantitative Genetic Modeling of the Parental Care Hypothesis for the Evolution of Endothermy

PubMed Central

Bacigalupe, Leonardo D.; Moore, Allen J.; Nespolo, Roberto F.; Rezende, Enrico L.; Bozinovic, Francisco

2017-01-01

There are two heuristic explanations proposed for the evolution of endothermy in vertebrates: a correlated response to selection for stable body temperatures, or as a correlated response to increased activity. Parental care has been suggested as a major driving force in this context given its impact on the parents' activity levels and energy budgets, and in the offspring's growth rates due to food provisioning and controlled incubation temperature. This results in a complex scenario involving multiple traits and transgenerational fitness benefits that can be hard to disentangle, quantify and ultimately test. Here we demonstrate how standard quantitative genetic models of maternal effects can be applied to study the evolution of endothermy, focusing on the interplay between daily energy expenditure (DEE) of the mother and growth rates of the offspring. Our model shows that maternal effects can dramatically exacerbate evolutionary responses to selection in comparison to regular univariate models (breeder's equation). This effect would emerge from indirect selection mediated by maternal effects concomitantly with a positive genetic covariance between DEE and growth rates. The multivariate nature of selection, which could favor a higher DEE, higher growth rates or both, might partly explain how high turnover rates were continuously favored in a self-reinforcing process. Overall, our quantitative genetic analysis provides support for the parental care hypothesis for the evolution of endothermy. We contend that much has to be gained from quantifying maternal and developmental effects on metabolic and thermoregulatory variation during adulthood. PMID:29311952

Genetic variability and founder effect in the pitcher plant Sarracenia purpurea (Sarraceniaceae) in populations introduced into Switzerland: from inbreeding to invasion.

PubMed

Parisod, Christian; Trippi, Charlotte; Galland, Nicole

2005-01-01

The long-lived and mainly outcrossing species Sarracenia purpurea has been introduced into Switzerland and become invasive. This creates the opportunity to study reactions to founder effect and how a species can circumvent deleterious effects of bottlenecks such as reduced genetic diversity, inbreeding and extinction through mutational meltdown, to emerge as a highly invasive plant. A population genetic survey by random amplified polymorphism DNA markers (RAPD) together with historical insights and a field pollination experiment were carried out. At the regional scale, S. purpurea shows low structure (thetast=0.072) due to a recent founder event and important subsequent growth. Nevertheless, multivariate statistical analyses reveal that, because of a bottleneck that shifted allele frequencies, most of the variability is independent among populations. In one population (Tenasses) the species has become invasive and genetic analysis reveals restricted gene flow and family structure (thetast=0.287). Although inbreeding appears to be high (Fis >0.410 from a Bayesian estimation), a field pollination experiment failed to detect significant inbreeding depression upon F1 seed number and seed weight fitness-traits. Furthermore, crosses between unrelated individuals produced F1 seeds with significantly reduced fitness, thus showing local outbreeding depression. The results suggest that, under restricted gene flow among families, the species may not only have rapidly purged deleterious alleles, but also have undergone some form of selection for inbreeding due to co-adaptation between loci.

Genetic and epigenetic transgenerational implications related to omega-3 fatty acids. Part I: maternal FADS2 genotype and DNA methylation correlate with polyunsaturated fatty acid status in toddlers: an exploratory analysis.

PubMed

Lupu, Daniel S; Cheatham, Carol L; Corbin, Karen D; Niculescu, Mihai D

2015-11-01

Polyunsaturated fatty acid metabolism in toddlers is regulated by a complex network of interacting factors. The contribution of maternal genetic and epigenetic makeup to this milieu is not well understood. In a cohort of mothers and toddlers 16 months of age (n = 65 mother-child pairs), we investigated the association between maternal genetic and epigenetic fatty acid desaturase 2 (FADS2) profiles and toddlers' n-6 and n-3 fatty acid metabolism. FADS2 rs174575 variation and DNA methylation status were interrogated in mothers and toddlers, as well as food intake and plasma fatty acid concentrations in toddlers. A multivariate fit model indicated that maternal rs174575 genotype, combined with DNA methylation, can predict α-linolenic acid plasma concentration in all toddlers and arachidonic acid concentrations in boys. Arachidonic acid intake was predictive for its plasma concentration in girls, whereas intake of 3 major n-3 species (eicosapentaenoic, docosapentaenoic, and docosahexaenoic acids) were predictive for their plasma concentrations in boys. FADS2 genotype and DNA methylation in toddlers were not related to plasma concentrations or food intakes, except for CpG8 methylation. Maternal FADS2 methylation was a predictor for the boys' α-linolenic acid intakes. This exploratory study suggests that maternal FADS2 genetic and epigenetic status could be related to toddlers' polyunsaturated fatty acid metabolism. Copyright © 2015 Elsevier Inc. All rights reserved.

[LDL-cholesterol control in patients with genetic dyslipidemia followed up by Lipid and Vascular Risk Units of the Spanish Society of Arteriosclerosis].

PubMed

Lahoz, Carlos; Mostaza, José María; Pintó, Xavier; de la Cruz, Juan José; Banegas, José Ramón; Pedro-Botet, Juan

2015-01-01

To evaluate low-density lipoprotein-cholesterol (LDLc) achieved in patients with genetic dyslipidemia treated during one year in Lipid and Vascular Risk Units (LVRU) of the Spanish Society of Arteriosclerosis (SSA). Observational, longitudinal, retrospective, multicenter national study that included consecutive patients of both sexes over 18 years of age referred due to dyslipidemia to LVRU of the SSA. Information was collected from medical records corresponding to two visits in the lipid unit. A total of 527 patients (mean age 48 years, 60.0% men) diagnosed with genetic dyslipidemia (241 with heterozygous familial hypercholesterolemia, and 286 with familial combined hyperlipidemia) were included. The mean follow-up was 12.9 months. In the last visit, 94% were taking statins, one third combined with ezetimibe, although only 41% were taking a high-intensity hypolipidemic treatment. Overall, 28.5% of patients attained an LDLc level<100 mg/dL, 35.8% decreased their LDLc by >50%, and 53.8% achieved one of the two. Predictors of target LDLc levels in the multivariate analysis were age, smoking habit and the presence of vascular disease. Over half of the patients with genetic dyslipidemia followed up by LVRU of SSA achieve LDLc objectives after one year of follow-up. The use of high-intensity hypolipidemic treatment could improve these results. Copyright © 2014 Sociedad Española de Arteriosclerosis. Published by Elsevier España. All rights reserved.

Heritability of semen traits in German Warmblood stallions.

PubMed

Gottschalk, M; Sieme, H; Martinsson, G; Distl, O

2016-07-01

The objectives of the present study were to evaluate genetic parameters for semen quality traits of 241 fertile German Warmblood stallions regularly employed in artificial insemination (AI). Stallions were owned by the National Studs Celle and Warendorf in Germany. Semen traits analyzed were gel-free volume, sperm concentration, total number of sperm, progressive motility and total number of progressively motile sperm. Semen protocols from a total of 63,972 ejaculates were collected between the years 2001 and 2014 for the present analysis. A multivariate linear animal model was employed for estimation of additive genetic and permanent environmental variances among stallions and breeding values (EBVs) for semen traits. Heritabilities estimated for all German Warmblood stallions were highest for gel-free volume (h(2)=0.28) and lowest for total number of progressively motile sperm (h(2)=0.13). The additive genetic correlation among gel-free volume and sperm concentration was highly negative (rg=-0.76). Average reliabilities of EBVs were at 0.37-0.68 for the 241 stallions with own records. The inter-stallion variance explained between 33 and 61% of the trait variance, underlining the major impact of the individual stallion on semen quality traits analyzed here. Recording of semen traits from stallions employed in AI may be recommended because EBVs achieve sufficient accuracies to improve semen quality in future generations. Due to favorable genetic correlations, sperm concentration, total number of sperm and total number of progressively motile sperm may be increased simultaneously. Copyright © 2016 Elsevier B.V. All rights reserved.

Linkage Analysis of Urine Arsenic Species Patterns in the Strong Heart Family Study

PubMed Central

Gribble, Matthew O.; Voruganti, Venkata Saroja; Cole, Shelley A.; Haack, Karin; Balakrishnan, Poojitha; Laston, Sandra L.; Tellez-Plaza, Maria; Francesconi, Kevin A.; Goessler, Walter; Umans, Jason G.; Thomas, Duncan C.; Gilliland, Frank; North, Kari E.; Franceschini, Nora; Navas-Acien, Ana

2015-01-01

Arsenic toxicokinetics are important for disease risks in exposed populations, but genetic determinants are not fully understood. We examined urine arsenic species patterns measured by HPLC-ICPMS among 2189 Strong Heart Study participants 18 years of age and older with data on ∼400 genome-wide microsatellite markers spaced ∼10 cM and arsenic speciation (683 participants from Arizona, 684 from Oklahoma, and 822 from North and South Dakota). We logit-transformed % arsenic species (% inorganic arsenic, %MMA, and %DMA) and also conducted principal component analyses of the logit % arsenic species. We used inverse-normalized residuals from multivariable-adjusted polygenic heritability analysis for multipoint variance components linkage analysis. We also examined the contribution of polymorphisms in the arsenic metabolism gene AS3MT via conditional linkage analysis. We localized a quantitative trait locus (QTL) on chromosome 10 (LOD 4.12 for %MMA, 4.65 for %DMA, and 4.84 for the first principal component of logit % arsenic species). This peak was partially but not fully explained by measured AS3MT variants. We also localized a QTL for the second principal component of logit % arsenic species on chromosome 5 (LOD 4.21) that was not evident from considering % arsenic species individually. Some other loci were suggestive or significant for 1 geographical area but not overall across all areas, indicating possible locus heterogeneity. This genome-wide linkage scan suggests genetic determinants of arsenic toxicokinetics to be identified by future fine-mapping, and illustrates the utility of principal component analysis as a novel approach that considers % arsenic species jointly. PMID:26209557

Multivariate analysis to evaluate genetic groups and production traits of crossbred Holstein × Zebu cows.

PubMed

Fraga, Angelina Bossi; de Lima Silva, Fabiane; Hongyu, Kuang; Da Silva Santos, Darlim; Murphy, Thomas Wayne; Lopes, Fernando Brito

2016-03-01

The objective of this research was to try to unveil the relationship between production traits and genotypic proportions of crossbred dairy cattle using principal component analysis (PCA) and cluster analysis. The herd consists of crossbred animals of Holstein (H) and Zebu (Z) (Gir and Guzerat) in different genotypic proportions; the composition of which varies from 12.5 to 100.0 % of the genetic group H. For this study, 834 milk production records from 257 cows from the years 1997 to 2014 were analyzed. The animals were all managed at a farm located in northeastern Brazil. The variables in the PCA were total milk yield per lactation (MY), milk yield adjusted to 305 days (MY305), lactation length (LL), and proportion of H and Z breeding. This analysis reduced the size of the sample space from the original five variables to two principal components (PCs) that together explained 89.4 % of the total variation. MY, MY305, LL, and genotypic proportion of H all contributed positively to PC1. The genotypic proportion of Z contributed negatively, which established a contrast between H and Z. Further cluster analysis identified two distinct groups when considering production performance and genotype of the animals. The high-performance group was predominantly Holstein breeding, while the lower performing group consisted mostly of Zebu. Under the environmental and management conditions in which this research was conducted, the best performances for the traits considered were achieved from cows whose genotypic proportion was between 38.0 and 94.0 % Holstein breeding.

Systems genetic analysis of multivariate response to iron deficiency in mice

PubMed Central

Yin, Lina; Unger, Erica L.; Jellen, Leslie C.; Earley, Christopher J.; Allen, Richard P.; Tomaszewicz, Ann; Fleet, James C.

2012-01-01

The aim of this study was to identify genes that influence iron regulation under varying dietary iron availability. Male and female mice from 20+ BXD recombinant inbred strains were fed iron-poor or iron-adequate diets from weaning until 4 mo of age. At death, the spleen, liver, and blood were harvested for the measurement of hemoglobin, hematocrit, total iron binding capacity, transferrin saturation, and liver, spleen and plasma iron concentration. For each measure and diet, we found large, strain-related variability. A principal-components analysis (PCA) was performed on the strain means for the seven parameters under each dietary condition for each sex, followed by quantitative trait loci (QTL) analysis on the factors. Compared with the iron-adequate diet, iron deficiency altered the factor structure of the principal components. QTL analysis, combined with PosMed (a candidate gene searching system) published gene expression data and literature citations, identified seven candidate genes, Ptprd, Mdm1, Picalm, lip1, Tcerg1, Skp2, and Frzb based on PCA factor, diet, and sex. Expression of each of these is cis-regulated, significantly correlated with the corresponding PCA factor, and previously reported to regulate iron, directly or indirectly. We propose that polymorphisms in multiple genes underlie individual differences in iron regulation, especially in response to dietary iron challenge. This research shows that iron management is a highly complex trait, influenced by multiple genes. Systems genetics analysis of iron homeostasis holds promise for developing new methods for prevention and treatment of iron deficiency anemia and related diseases. PMID:22461179

Awareness and attitude of the public toward personalized medicine in Korea

PubMed Central

Lee, Iyn-Hyang; Kang, Hye-Young; Suh, Hae Sun; Lee, Sukhyang; Oh, Eun Sil

2018-01-01

Objectives As personalized medicine (PM) is expected to greatly improve health outcomes, efforts have recently been made for its clinical implementation in Korea. We aimed to evaluate public awareness and attitude regarding PM. Methods We performed a self-administered questionnaire survey to 703 adults, who participated in the survey on a voluntary basis. The primary outcome measures included public knowledge, attitude, and acceptance of PM. We conducted multinomial multivariate logistic analysis for outcome variables with three response categories and performed multivariate logistic regression analyses for dichotomous outcome variables. Results Only 28% of participants had knowledge that genetic factors can contribute to inter-individual variations in drug response and the definition of PM (199 out of 702). Higher family income was correlated with greater knowledge concerning PM (OR = 3.76, p = 0.034). A majority of respondents preferred integrated pharmacogenomic testing over drug-specific testing and agreed to inclusion of pharmacogenomic testing in the national health examination (64% and 77%, respectively), but only 51% were willing to pay for it. Discussion Our results identify the urgent need for public education as well as the potential health disparities in access to PM. This study helps to frame policies for implementing PM in clinical practice. PMID:29451916

Genetic diversity analysis among male and female Jojoba genotypes employing gene targeted molecular markers, start codon targeted (SCoT) polymorphism and CAAT box-derived polymorphism (CBDP) markers

PubMed Central

Heikrujam, Monika; Kumar, Jatin; Agrawal, Veena

2015-01-01

To detect genetic variations among different Simmondsia chinensis genotypes, two gene targeted markers, start codon targeted (SCoT) polymorphism and CAAT box-derived polymorphism (CBDP) were employed in terms of their informativeness and efficiency in analyzing genetic relationships among different genotypes. A total of 15 SCoT and 17 CBDP primers detected genetic polymorphism among 39 Jojoba genotypes (22 females and 17 males). Comparatively, CBDP markers proved to be more effective than SCoT markers in terms of percentage polymorphism as the former detecting an average of 53.4% and the latter as 49.4%. The Polymorphic information content (PIC) value and marker index (MI) of CBPD were 0.43 and 1.10, respectively which were higher than those of SCoT where the respective values of PIC and MI were 0.38 and 1.09. While comparing male and female genotype populations, the former showed higher variation in respect of polymorphic percentage and PIC, MI and Rp values over female populations. Nei's diversity (h) and Shannon index (I) were calculated for each genotype and found that the genotype “MS F” (in both markers) was highly diverse and genotypes “Q104 F” (SCoT) and “82–18 F” (CBDP) were least diverse among the female genotype populations. Among male genotypes, “32 M” (CBDP) and “MS M” (SCoT) revealed highest h and I values while “58-5 M” (both markers) was the least diverse. Jaccard's similarity co-efficient of SCoT markers ranged from 0.733 to 0.922 in female genotypes and 0.941 to 0.746 in male genotype population. Likewise, CBDP data analysis also revealed similarity ranging from 0.751 to 0.958 within female genotypes and 0.754 to 0.976 within male genotype populations thereby, indicating genetically diverse Jojoba population. Employing the NTSYS (Numerical taxonomy and multivariate analysis system) Version 2.1 software, both the markers generated dendrograms which revealed that all the Jojoba genotypes were clustered into two major groups, one group consisting of all female genotypes and another group comprising of all male genotypes. During the present investigation, CBDP markers proved more informative in studying genetic diversity among Jojoba. Such genetically diverse genotypes would thus be of great significance for breeding, management and conservation of elite (high yielding) Jojoba germplasm. PMID:26110116

Trends in childhood cancer incidence: review of environmental linkages.

PubMed

Buka, Irena; Koranteng, Samuel; Osornio Vargas, Alvaro R

2007-02-01

Cancer in children is rare and accounts for about 1% of all malignancies. In the developed world, however, it is the commonest cause of disease-related deaths in childhood, carrying with it a great economic and emotional cost. Cancers are assumed to be multivariate, multifactorial diseases that occur when a complex and prolonged process involving genetic and environmental factors interact in a multistage sequence. This article explores the available evidence for this process, primarily from the environmental linkages perspective but including some evidence of the genetic factors.

Faà di Bruno's formula and the distributions of random partitions in population genetics and physics.

PubMed

Hoppe, Fred M

2008-06-01

We show that the formula of Faà di Bruno for the derivative of a composite function gives, in special cases, the sampling distributions in population genetics that are due to Ewens and to Pitman. The composite function is the same in each case. Other sampling distributions also arise in this way, such as those arising from Dirichlet, multivariate hypergeometric, and multinomial models, special cases of which correspond to Bose-Einstein, Fermi-Dirac, and Maxwell-Boltzmann distributions in physics. Connections are made to compound sampling models.

Analysis techniques for multivariate root loci. [a tool in linear control systems

NASA Technical Reports Server (NTRS)

Thompson, P. M.; Stein, G.; Laub, A. J.

1980-01-01

Analysis and techniques are developed for the multivariable root locus and the multivariable optimal root locus. The generalized eigenvalue problem is used to compute angles and sensitivities for both types of loci, and an algorithm is presented that determines the asymptotic properties of the optimal root locus.

Methods for presentation and display of multivariate data

NASA Technical Reports Server (NTRS)

Myers, R. H.

1981-01-01

Methods for the presentation and display of multivariate data are discussed with emphasis placed on the multivariate analysis of variance problems and the Hotelling T(2) solution in the two-sample case. The methods utilize the concepts of stepwise discrimination analysis and the computation of partial correlation coefficients.

A Primer on Multivariate Analysis of Variance (MANOVA) for Behavioral Scientists

ERIC Educational Resources Information Center

Warne, Russell T.

2014-01-01

Reviews of statistical procedures (e.g., Bangert & Baumberger, 2005; Kieffer, Reese, & Thompson, 2001; Warne, Lazo, Ramos, & Ritter, 2012) show that one of the most common multivariate statistical methods in psychological research is multivariate analysis of variance (MANOVA). However, MANOVA and its associated procedures are often not…

The Principal Genetic Determinants for Nasopharyngeal Carcinoma in China Involve the HLA Class I Antigen Recognition Groove

PubMed Central

Tang, Minzhong; Lautenberger, James A.; Gao, Xiaojiang; Sezgin, Efe; Hendrickson, Sher L.; Troyer, Jennifer L.; David, Victor A.; Guan, Li; Mcintosh, Carl E.; Guo, Xiuchan; Zheng, Yuming; Liao, Jian; Deng, Hong; Malasky, Michael; Kessing, Bailey; Winkler, Cheryl A.; Carrington, Mary; dé The, Guy; Zeng, Yi; O'Brien, Stephen J.

2012-01-01

Nasopharyngeal carcinoma (NPC) is an epithelial malignancy facilitated by Epstein-Barr Virus infection. Here we resolve the major genetic influences for NPC incidence using a genome-wide association study (GWAS), independent cohort replication, and high-resolution molecular HLA class I gene typing including 4,055 study participants from the Guangxi Zhuang Autonomous Region and Guangdong province of southern China. We detect and replicate strong association signals involving SNPs, HLA alleles, and amino acid (aa) variants across the major histocompatibility complex-HLA-A, HLA –B, and HLA -C class I genes (PHLA-A-aa-site-62 = 7.4×10−29; P HLA-B-aa-site-116 = 6.5×10−19; P HLA-C-aa-site-156 = 6.8×10−8 respectively). Over 250 NPC-HLA associated variants within HLA were analyzed in concert to resolve separate and largely independent HLA-A, -B, and -C gene influences. Multivariate logistical regression analysis collapsed significant associations in adjacent genes spanning 500 kb (OR2H1, GABBR1, HLA-F, and HCG9) as proxies for peptide binding motifs carried by HLA- A*11:01. A similar analysis resolved an independent association signal driven by HLA-B*13:01, B*38:02, and B*55:02 alleles together. NPC resistance alleles carrying the strongly associated amino acid variants implicate specific class I peptide recognition motifs in HLA-A and -B peptide binding groove as conferring strong genetic influence on the development of NPC in China. PMID:23209447

Association between a polymorphism in the human programmed death-1 (PD-1) gene and cytomegalovirus infection after kidney transplantation.

PubMed

Hoffmann, Thomas W; Halimi, Jean-Michel; Büchler, Mathias; Velge-Roussel, Florence; Goudeau, Alain; Al-Najjar, Azmi; Marliere, Jean-Frédéric; Lebranchu, Yvon; Baron, Christophe

2010-01-01

Cytomegalovirus (CMV) infection is the most frequent infectious disease following organ transplantation. Strategies to prevent this infection remain a matter for debate, and discovering genetic risk factors might assist in adapting preventive strategies. By inhibiting IFNgamma production, programmed death 1 (PD-1) has a crucial role in anti-CMV immune response. A single nucleotide polymorphism (SNP) within intron 4 of the gene (rs11568821), called PD-1.3, has recently been reported to be clinically relevant in several immune disorders. However, its association with CMV infection has never been reported. In this study, the risk of CMV infection according to PD-1.3 genotype was investigated in 469 kidney graft recipients transplanted between 1995 and 2005. It was found that the A allele was associated with the risk of CMV infection in seropositive patients who did not receive CMV prophylaxis (OR=2.60, p=0.006). Multivariate analysis including other risk factors for CMV infection showed that this allele was independently associated with CMV infection (OR=2.54; p=0.010). Interestingly, combined analysis of PD-1.3 with the IL12B 3'UTR SNPs (previously shown to be associated with CMV infection) revealed that patients with the PD-1.3 A allele had a much higher risk of CMV infection compared to those having neither risk allele (OR=3.76; p=0.0003). This study identified a new genetic risk factor for CMV infection after kidney transplantation and suggests that an adjustment of CMV prophylaxis based on genetic markers would merit further investigation.

Gene-environment interaction in atopic diseases: a population-based twin study of early-life exposures.

PubMed

Kahr, Niklas; Naeser, Vibeke; Stensballe, Lone Graff; Kyvik, Kirsten Ohm; Skytthe, Axel; Backer, Vibeke; Bønnelykke, Klaus; Thomsen, Simon Francis

2015-01-01

The development of atopic diseases early in life suggests an important role of perinatal risk factors. To study whether early-life exposures modify the genetic influence on atopic diseases in a twin population. Questionnaire data on atopic diseases from 850 monozygotic and 2279 like-sex dizygotic twin pairs, 3-9 years of age, from the Danish Twin Registry were cross-linked with data on prematurity, Cesarean section, maternal age at birth, parental cohabitation, season of birth and maternal smoking during pregnancy, from the Danish National Birth Registry. Significant predictors of atopic diseases were identified with logistic regression and subsequently tested for genetic effect modification using variance components analysis. After multivariable adjustment, prematurity (gestational age below 32 weeks) [odds ratio (OR) = 1.93, confidence interval (CI) = 1.45-2.56], Cesarean section (OR = 1.25, CI = 1.05-1.49) and maternal smoking during pregnancy (OR = 1.70, CI = 1.42-2.04) significantly influenced the risk of asthma, whereas none of the factors were significantly associated with atopic dermatitis and hay fever. Variance components analysis stratified by exposure status showed no significant change in the heritability of asthma according to the identified risk factors. In this population-based study of children, there was no evidence of genetic effect modification of atopic diseases by several identified early-life risk factors. The causal relationship between these risk factors and atopic diseases may therefore be mediated via mechanisms different from gene-environment interaction. © 2014 John Wiley & Sons Ltd.

Meta-analysis of Genome Wide Association Studies Identifies Genetic Markers of Late Toxicity Following Radiotherapy for Prostate Cancer.

PubMed

Kerns, Sarah L; Dorling, Leila; Fachal, Laura; Bentzen, Søren; Pharoah, Paul D P; Barnes, Daniel R; Gómez-Caamaño, Antonio; Carballo, Ana M; Dearnaley, David P; Peleteiro, Paula; Gulliford, Sarah L; Hall, Emma; Michailidou, Kyriaki; Carracedo, Ángel; Sia, Michael; Stock, Richard; Stone, Nelson N; Sydes, Matthew R; Tyrer, Jonathan P; Ahmed, Shahana; Parliament, Matthew; Ostrer, Harry; Rosenstein, Barry S; Vega, Ana; Burnet, Neil G; Dunning, Alison M; Barnett, Gillian C; West, Catharine M L

2016-08-01

Nearly 50% of cancer patients undergo radiotherapy. Late radiotherapy toxicity affects quality-of-life in long-term cancer survivors and risk of side-effects in a minority limits doses prescribed to the majority of patients. Development of a test predicting risk of toxicity could benefit many cancer patients. We aimed to meta-analyze individual level data from four genome-wide association studies from prostate cancer radiotherapy cohorts including 1564 men to identify genetic markers of toxicity. Prospectively assessed two-year toxicity endpoints (urinary frequency, decreased urine stream, rectal bleeding, overall toxicity) and single nucleotide polymorphism (SNP) associations were tested using multivariable regression, adjusting for clinical and patient-related risk factors. A fixed-effects meta-analysis identified two SNPs: rs17599026 on 5q31.2 with urinary frequency (odds ratio [OR] 3.12, 95% confidence interval [CI] 2.08-4.69, p-value 4.16×10(-8)) and rs7720298 on 5p15.2 with decreased urine stream (OR 2.71, 95% CI 1.90-3.86, p-value=3.21×10(-8)). These SNPs lie within genes that are expressed in tissues adversely affected by pelvic radiotherapy including bladder, kidney, rectum and small intestine. The results show that heterogeneous radiotherapy cohorts can be combined to identify new moderate-penetrance genetic variants associated with radiotherapy toxicity. The work provides a basis for larger collaborative efforts to identify enough variants for a future test involving polygenic risk profiling. Copyright © 2016 The Ohio State University Wexner Medical Center. Published by Elsevier B.V. All rights reserved.

The effects of stress and sex on selection, genetic covariance, and the evolutionary response.

PubMed

Holman, L; Jacomb, F

2017-10-01

The capacity of a population to adapt to selection (evolvability) depends on whether the structure of genetic variation permits the evolution of fitter trait combinations. Selection, genetic variance and genetic covariance can change under environmental stress, and males and females are not genetically independent, yet the combined effects of stress and dioecy on evolvability are not well understood. Here, we estimate selection, genetic (co)variance and evolvability in both sexes of Tribolium castaneum flour beetles under stressful and benign conditions, using a half-sib breeding design. Although stress uncovered substantial latent heritability, stress also affected genetic covariance, such that evolvability remained low under stress. Sexual selection on males and natural selection on females favoured a similar phenotype, and there was positive intersex genetic covariance. Consequently, sexual selection on males augmented adaptation in females, and intralocus sexual conflict was weak or absent. This study highlights that increased heritability does not necessarily increase evolvability, suggests that selection can deplete genetic variance for multivariate trait combinations with strong effects on fitness, and tests the recent hypothesis that sexual conflict is weaker in stressful or novel environments. © 2017 European Society For Evolutionary Biology. Journal of Evolutionary Biology © 2017 European Society For Evolutionary Biology.

Educational Tool for Optimal Controller Tuning Using Evolutionary Strategies

ERIC Educational Resources Information Center

Carmona Morales, D.; Jimenez-Hornero, J. E.; Vazquez, F.; Morilla, F.

2012-01-01

In this paper, an optimal tuning tool is presented for control structures based on multivariable proportional-integral-derivative (PID) control, using genetic algorithms as an alternative to traditional optimization algorithms. From an educational point of view, this tool provides students with the necessary means to consolidate their knowledge on…

The association between GGCX, miR-133 genetic polymorphisms and warfarin stable dosage in Han Chinese patients with mechanical heart valve replacement.

PubMed

Tang, X-Y; Zhang, J; Peng, J; Tan, S-L; Zhang, W; Song, G-B; Liu, L-M; Li, C-L; Ren, H; Zeng, L; Liu, Z-Q; Chen, X-P; Zhou, X-M; Zhou, H-H; Hu, J-X; Li, Z

2017-08-01

Warfarin is a widely used anticoagulant with a narrow therapeutic index. Polymorphisms in the VKORC1, CYP2C9 and CYP4F2 genes have been verified to correlate with warfarin stable dosage (WSD). Whether any other genes or variants affect the dosage is unknown. The aim of our study was to investigate the relationship between GGCX, miR-133 variants and the WSD in Han Chinese patients with mechanical heart valve replacement (MHVR). A total of 231 patients were enrolled in the study. Blood samples were collected for genotyping. The average WSD among subjects with different GGCX or miR-133 genotypes was compared. Regression analyses were performed to test for any association of genetic polymorphisms with WSD. The warfarin dosage in patients with the GGCX rs699664 TT and rs12714145 TT genotypes was 3.77±0.93 (95% CI: 3.35-4.19) mg/d and 3.70±1.00 (95% CI: 3.32-4.09) mg/d, respectively. The GGCX rs699664 and rs12714145 genotypes were significantly associated with WSD (P<.05). But they were ruled out in the multivariate regression analysis. There were no significant differences in the average warfarin stable dosage between subjects with MIR133B rs142410335 wild-type and variant genotypes (P>.05). The genotypes of GGCX rs699644 and rs12714145 were significantly associated with WSD (P<.05), but their contributions were not significant after accounting for other factors. MIR133B rs142410335 makes no significant contributions to warfarin stable dosage in Han Chinese patients with MHVR neither in univariate regression nor in multivariate regression analyses. © 2017 John Wiley & Sons Ltd.