Joint genome-wide prediction in several populations accounting for randomness of genotypes: A hierarchical Bayes approach. I: Multivariate Gaussian priors for marker effects and derivation of the joint probability mass function of genotypes.

PubMed

Martínez, Carlos Alberto; Khare, Kshitij; Banerjee, Arunava; Elzo, Mauricio A

2017-03-21

It is important to consider heterogeneity of marker effects and allelic frequencies in across population genome-wide prediction studies. Moreover, all regression models used in genome-wide prediction overlook randomness of genotypes. In this study, a family of hierarchical Bayesian models to perform across population genome-wide prediction modeling genotypes as random variables and allowing population-specific effects for each marker was developed. Models shared a common structure and differed in the priors used and the assumption about residual variances (homogeneous or heterogeneous). Randomness of genotypes was accounted for by deriving the joint probability mass function of marker genotypes conditional on allelic frequencies and pedigree information. As a consequence, these models incorporated kinship and genotypic information that not only permitted to account for heterogeneity of allelic frequencies, but also to include individuals with missing genotypes at some or all loci without the need for previous imputation. This was possible because the non-observed fraction of the design matrix was treated as an unknown model parameter. For each model, a simpler version ignoring population structure, but still accounting for randomness of genotypes was proposed. Implementation of these models and computation of some criteria for model comparison were illustrated using two simulated datasets. Theoretical and computational issues along with possible applications, extensions and refinements were discussed. Some features of the models developed in this study make them promising for genome-wide prediction, the use of information contained in the probability distribution of genotypes is perhaps the most appealing. Further studies to assess the performance of the models proposed here and also to compare them with conventional models used in genome-wide prediction are needed. Copyright © 2017 Elsevier Ltd. All rights reserved.

Immunological tumor status may predict response to neoadjuvant chemotherapy and outcome after radical cystectomy in bladder cancer.

PubMed

Tervahartiala, Minna; Taimen, Pekka; Mirtti, Tuomas; Koskinen, Ilmari; Ecke, Thorsten; Jalkanen, Sirpa; Boström, Peter J

2017-10-04

Bladder cancer (BC) is the ninth most common cancer worldwide. Radical cystectomy (RC) with neoadjuvant chemotherapy (NAC) is recommended for muscle-invasive BC. The challenge of the neoadjuvant approach relates to challenges in selection of patients to chemotherapy that are likely to respond to the treatment. To date, there are no validated molecular markers or baseline clinical characteristics to identify these patients. Different inflammatory markers, including tumor associated macrophages with their plastic pro-tumorigenic and anti-tumorigenic functions, have extensively been under interests as potential prognostic and predictive biomarkers in different cancer types. In this immunohistochemical study we evaluated the predictive roles of three immunological markers, CD68, MAC387, and CLEVER-1, in response to NAC and outcome of BC. 41% of the patients had a complete response (pT0N0) to NAC. Basic clinicopathological variables did not predict response to NAC. In contrast, MAC387 + cells and CLEVER-1 + macrophages associated with poor NAC response, while CLEVER-1 + vessels associated with more favourable response to NAC. Higher counts of CLEVER-1 + macrophages associated with poorer overall survival and CD68 + macrophages seem to have an independent prognostic value in BC patients treated with NAC. Our findings point out that CD68, MAC387, and CLEVER-1 may be useful prognostic and predictive markers in BC.

Predicting complex traits using a diffusion kernel on genetic markers with an application to dairy cattle and wheat data

PubMed Central

2013-01-01

Background Arguably, genotypes and phenotypes may be linked in functional forms that are not well addressed by the linear additive models that are standard in quantitative genetics. Therefore, developing statistical learning models for predicting phenotypic values from all available molecular information that are capable of capturing complex genetic network architectures is of great importance. Bayesian kernel ridge regression is a non-parametric prediction model proposed for this purpose. Its essence is to create a spatial distance-based relationship matrix called a kernel. Although the set of all single nucleotide polymorphism genotype configurations on which a model is built is finite, past research has mainly used a Gaussian kernel. Results We sought to investigate the performance of a diffusion kernel, which was specifically developed to model discrete marker inputs, using Holstein cattle and wheat data. This kernel can be viewed as a discretization of the Gaussian kernel. The predictive ability of the diffusion kernel was similar to that of non-spatial distance-based additive genomic relationship kernels in the Holstein data, but outperformed the latter in the wheat data. However, the difference in performance between the diffusion and Gaussian kernels was negligible. Conclusions It is concluded that the ability of a diffusion kernel to capture the total genetic variance is not better than that of a Gaussian kernel, at least for these data. Although the diffusion kernel as a choice of basis function may have potential for use in whole-genome prediction, our results imply that embedding genetic markers into a non-Euclidean metric space has very small impact on prediction. Our results suggest that use of the black box Gaussian kernel is justified, given its connection to the diffusion kernel and its similar predictive performance. PMID:23763755

Maternal Psychopathology and Early Child Temperament Predict Young Children's Salivary Cortisol 3 Years Later

ERIC Educational Resources Information Center

Dougherty, Lea R.; Smith, Victoria C.; Olino, Thomas M.; Dyson, Margaret W.; Bufferd, Sara J.; Rose, Suzanne A.; Klein, Daniel N.

2013-01-01

Neuroendocrine dysfunction is hypothesized to be an early emerging vulnerability marker for depression. We tested whether the main and interactive effects of maternal psychopathology and early child temperamental vulnerability for depression assessed at age three predicted offspring's basal cortisol function at age 6 years. 228 (122 males)…

Epigenetic variation predicts regional and local intraspecific functional diversity in a perennial herb.

PubMed

Medrano, Mónica; Herrera, Carlos M; Bazaga, Pilar

2014-10-01

The ecological significance of epigenetic variation has been generally inferred from studies on model plants under artificial conditions, but the importance of epigenetic differences between individuals as a source of intraspecific diversity in natural plant populations remains essentially unknown. This study investigates the relationship between epigenetic variation and functional plant diversity by conducting epigenetic (methylation-sensitive amplified fragment length polymorphisms, MSAP) and genetic (amplified fragment length polymorphisms, AFLP) marker-trait association analyses for 20 whole-plant, leaf and regenerative functional traits in a large sample of wild-growing plants of the perennial herb Helleborus foetidus from ten sampling sites in south-eastern Spain. Plants differed widely in functional characteristics, and exhibited greater epigenetic than genetic diversity, as shown by per cent polymorphism of MSAP fragments (92%) or markers (69%) greatly exceeding that for AFLP ones (41%). After controlling for genetic structuring and possible cryptic relatedness, every functional trait considered exhibited a significant association with at least one AFLP or MSAP marker. A total of 27 MSAP (13.0% of total) and 12 AFLP (4.4%) markers were involved in significant associations, which explained on average 8.2% and 8.0% of trait variance, respectively. Individual MSAP markers were more likely to be associated with functional traits than AFLP markers. Between-site differences in multivariate functional diversity were directly related to variation in multilocus epigenetic diversity after multilocus genetic diversity was statistically accounted for. Results suggest that epigenetic variation can be an important source of intraspecific functional diversity in H. foetidus, possibly endowing this species with the capacity to exploit a broad range of ecological conditions despite its modest genetic diversity. © 2014 John Wiley & Sons Ltd.

Financial Exploitation Is Associated With Structural and Functional Brain Differences in Healthy Older Adults.

PubMed

Spreng, R Nathan; Cassidy, Benjamin N; Darboh, Bri S; DuPre, Elizabeth; Lockrow, Amber W; Setton, Roni; Turner, Gary R

2017-10-01

Age-related brain changes leading to altered socioemotional functioning may increase vulnerability to financial exploitation. If confirmed, this would suggest a novel mechanism leading to heightened financial exploitation risk in older adults. Development of predictive neural markers could facilitate increased vigilance and prevention. In this preliminary study, we sought to identify structural and functional brain differences associated with financial exploitation in older adults. Financially exploited older adults (n = 13, 7 female) and a matched cohort of older adults who had been exposed to, but avoided, a potentially exploitative situation (n = 13, 7 female) were evaluated. Using magnetic resonance imaging, we examined cortical thickness and resting state functional connectivity. Behavioral data were collected using standardized cognitive assessments, self-report measures of mood and social functioning. The exploited group showed cortical thinning in anterior insula and posterior superior temporal cortices, regions associated with processing affective and social information, respectively. Functional connectivity encompassing these regions, within default and salience networks, was reduced, while between network connectivity was increased. Self-reported anger and hostility was higher for the exploited group. We observed financial exploitation associated with brain differences in regions involved in socioemotional functioning. These exploratory and preliminary findings suggest that alterations in brain regions implicated in socioemotional functioning may be a marker of financial exploitation risk. Large-scale, prospective studies are necessary to validate this neural mechanism, and develop predictive markers for use in clinical practice. © The Author 2017. Published by Oxford University Press on behalf of The Gerontological Society of America.

Biomarkers of collagen turnover are related to annual change in FEV1 in patients with chronic obstructive pulmonary disease within the ECLIPSE study.

PubMed

Leeming, Diana J; Byrjalsen, Inger; Sand, Jannie M B; Bihlet, Asger R; Lange, Peter; Thal-Singer, Ruth; Miller, Bruce E; Karsdal, Morten A; Vestbo, Jørgen

2017-12-04

Change in forced expiratory volume in one second (FEV 1 ) is important for defining severity of chronic obstructive pulmonary disease (COPD). Serological neoepitope markers of collagen turnover may predict rate of change in FEV 1 . One thousand COPD subjects from the observational, multicentre, three-year ECLIPSE (Evaluation of COPD Longitudinally to Identify Predictive Surrogate Endpoints) study (NCT00292552, trial registration in February 2006) were included. Matrix metalloproteinase (MMP)-generated fragments of collagen type I, and type VI (C1M and C6M) were assessed in month six serum samples. A random-coefficient model with both a random intercept and a random slope was used to test the ability of the markers to predict post-dose bronchodilator FEV 1 (PD-FEV 1 ) change over two years adjusting for sex, age, BMI, smoking, bronchodilator reversibility, prior exacerbations, emphysema and chronic bronchitis status at baseline. Annual change of PD-FEV 1 was estimated from a linear model for the two-year study period. Serum C1M and C6M were independent predictors of lung function change (p = 0.007/0.005). Smoking, bronchodilator reversibility, plasma hsCRP and emphysema were also significant predictors. The effect estimate between annual change in PD-FEV 1 per one standard deviation (1SD) increase of C1M and C6M was +10.4 mL/yr. and +8.6 mL/yr. C1M, and C6M, had a significant association with baseline FEV 1 . We demonstrated that markers of tissue turnover were significantly associated with lung function change. These markers may function as prognostic biomarkers and possibly as efficacy biomarkers in clinical trials focusing on lung function change in COPD. NCT00292552 , Retrospectively registered, trial registration in February 2006.

Comparison of Measured GFR, Serum Creatinine, Cystatin C, and Beta-Trace Protein to Predict ESRD in African Americans With Hypertensive CKD

PubMed Central

Bhavsar, Nrupen A.; Appel, Lawrence J.; Kusek, John W.; Contreras, Gabriel; Bakris, George; Coresh, Josef; Astor, Brad C.

2011-01-01

Background Identification of persons with chronic kidney disease (CKD) who are at highest risk to progress to end stage renal disease (ESRD) is necessary to reduce the burden of kidney failure. The relative utility of traditional markers of kidney function, including estimated glomerular filtration rate (GFR) and serum creatinine, and emerging markers of kidney function, including cystatin C and beta-trace protein (BTP), to predict ESRD and mortality has yet to be established. Study Design Randomized clinical trial followed by an observational cohort study. Setting & Participants 865 African American individuals with hypertensive CKD enrolled in a clinical trial of two levels of blood pressure control and three different antihypertensive drugs as initial therapy and subsequently followed by an observational cohort study. Predictors Quintile of measured GFR (mGFR) by iothalamate clearance, serum creatinine, serum creatinine-based estimated GFR (eGFRSCr), cystatin C, and BTP. Outcomes and Measurements Incidence of ESRD and mortality. Results A total of 246 participants reached ESRD over a median follow-up of 102 months. The incidence rate of ESRD was higher with higher quintiles of each marker. The association between higher BTP and ESRD was stronger than those for the other markers, including mGFR. All the markers remained significantly associated with ESRD after adjustment for mGFR and relevant covariates (all p<0.05), with BTP retaining the strongest association (HR for highest versus lowest quintile, 5.7; 95% CI, 2.2-14.9). Associations with the combined endpoint of ESRD or mortality (n=390) were weaker, but remained significant for cystatin C (p=0.05) and BTP (p=0.004). Limitations The ability of these markers to predict ESRD and mortality in other racial and ethnic groups and among individuals with CKD due to other causes is unknown. Conclusions Plasma BTP and cystatin C may be useful adjuncts to serum creatinine and mGFR in evaluating risk for progression of kidney disease. PMID:21944667

Combinatorial markers of mild cognitive impairment conversion to Alzheimer's disease--cytokines and MRI measures together predict disease progression.

PubMed

Furney, Simon J; Kronenberg, Deborah; Simmons, Andrew; Güntert, Andreas; Dobson, Richard J; Proitsi, Petroula; Wahlund, Lars Olof; Kloszewska, Iwona; Mecocci, Patrizia; Soininen, Hilkka; Tsolaki, Magda; Vellas, Bruno; Spenger, Christian; Lovestone, Simon

2011-01-01

Progression of people presenting with Mild Cognitive Impairment (MCI) to dementia is not certain and it is not possible for clinicians to predict which people are most likely to convert. The inability of clinicians to predict progression limits the use of MCI as a syndrome for treatment in prevention trials and, as more people present with this syndrome in memory clinics, and as earlier diagnosis is a major goal of health services, this presents an important clinical problem. Some data suggest that CSF biomarkers and functional imaging using PET might act as markers to facilitate prediction of conversion. However, both techniques are costly and not universally available. The objective of our study was to investigate the potential added benefit of combining biomarkers that are more easily obtained in routine clinical practice to predict conversion from MCI to Alzheimer's disease. To explore this we combined automated regional analysis of structural MRI with analysis of plasma cytokines and chemokines and compared these to measures of APOE genotype and clinical assessment to assess which best predict progression. In a total of 205 people with MCI, 77 of whom subsequently converted to Alzheimer's disease, we find biochemical markers of inflammation to be better predictors of conversion than APOE genotype or clinical measures (Area under the curve (AUC) 0.65, 0.62, 0.59 respectively). In a subset of subjects who also had MRI scans the combination of serum markers of inflammation and MRI automated imaging analysis provided the best predictor of conversion (AUC 0.78). These results show that the combination of imaging and cytokine biomarkers provides an improvement in prediction of MCI to AD conversion compared to either datatype alone, APOE genotype or clinical data and an accuracy of prediction that would have clinical utility.

Estimation of treatment effects in all-comers randomized clinical trials with a predictive marker.

PubMed

Choai, Yuki; Matsui, Shigeyuki

2015-03-01

Recent advances in genomics and biotechnologies have accelerated the development of molecularly targeted treatments and accompanying markers to predict treatment responsiveness. However, it is common at the initiation of a definitive phase III clinical trial that there is no compelling biological basis or early trial data for a candidate marker regarding its capability in predicting treatment effects. In this case, it is reasonable to include all patients as eligible for randomization, but to plan for prospective subgroup analysis based on the marker. One analysis plan in such all-comers designs is the so-called fallback approach that first tests for overall treatment efficacy and then proceeds to testing in a biomarker-positive subgroup if the first test is not significant. In this approach, owing to the adaptive nature of the analysis and a correlation between the two tests, a bias will arise in estimating the treatment effect in the biomarker-positive subgroup after a non-significant first overall test. In this article, we formulate the bias function and show a difficulty in obtaining unbiased estimators for a whole range of an associated parameter. To address this issue, we propose bias-corrected estimation methods, including those based on an approximation of the bias function under a bounded range of the parameter using polynomials. We also provide an interval estimation method based on a bivariate doubly truncated normal distribution. Simulation experiments demonstrated a success in bias reduction. Application to a phase III trial for lung cancer is provided. © 2014, The International Biometric Society.

Multi-allelic haplotype model based on genetic partition for genomic prediction and variance component estimation using SNP markers.

PubMed

Da, Yang

2015-12-18

The amount of functional genomic information has been growing rapidly but remains largely unused in genomic selection. Genomic prediction and estimation using haplotypes in genome regions with functional elements such as all genes of the genome can be an approach to integrate functional and structural genomic information for genomic selection. Towards this goal, this article develops a new haplotype approach for genomic prediction and estimation. A multi-allelic haplotype model treating each haplotype as an 'allele' was developed for genomic prediction and estimation based on the partition of a multi-allelic genotypic value into additive and dominance values. Each additive value is expressed as a function of h - 1 additive effects, where h = number of alleles or haplotypes, and each dominance value is expressed as a function of h(h - 1)/2 dominance effects. For a sample of q individuals, the limit number of effects is 2q - 1 for additive effects and is the number of heterozygous genotypes for dominance effects. Additive values are factorized as a product between the additive model matrix and the h - 1 additive effects, and dominance values are factorized as a product between the dominance model matrix and the h(h - 1)/2 dominance effects. Genomic additive relationship matrix is defined as a function of the haplotype model matrix for additive effects, and genomic dominance relationship matrix is defined as a function of the haplotype model matrix for dominance effects. Based on these results, a mixed model implementation for genomic prediction and variance component estimation that jointly use haplotypes and single markers is established, including two computing strategies for genomic prediction and variance component estimation with identical results. The multi-allelic genetic partition fills a theoretical gap in genetic partition by providing general formulations for partitioning multi-allelic genotypic values and provides a haplotype method based on the quantitative genetics model towards the utilization of functional and structural genomic information for genomic prediction and estimation.

Functional status predicts acute care readmission in the traumatic spinal cord injury population.

PubMed

Huang, Donna; Slocum, Chloe; Silver, Julie K; Morgan, James W; Goldstein, Richard; Zafonte, Ross; Schneider, Jeffrey C

2018-03-29

Context/objective Acute care readmission has been identified as an important marker of healthcare quality. Most previous models assessing risk prediction of readmission incorporate variables for medical comorbidity. We hypothesized that functional status is a more robust predictor of readmission in the spinal cord injury population than medical comorbidities. Design Retrospective cross-sectional analysis. Setting Inpatient rehabilitation facilities, Uniform Data System for Medical Rehabilitation data from 2002 to 2012 Participants traumatic spinal cord injury patients. Outcome measures A logistic regression model for predicting acute care readmission based on demographic variables and functional status (Functional Model) was compared with models incorporating demographics, functional status, and medical comorbidities (Functional-Plus) or models including demographics and medical comorbidities (Demographic-Comorbidity). The primary outcomes were 3- and 30-day readmission, and the primary measure of model performance was the c-statistic. Results There were a total of 68,395 patients with 1,469 (2.15%) readmitted at 3 days and 7,081 (10.35%) readmitted at 30 days. The c-statistics for the Functional Model were 0.703 and 0.654 for 3 and 30 days. The Functional Model outperformed Demographic-Comorbidity models at 3 days (c-statistic difference: 0.066-0.096) and outperformed two of the three Demographic-Comorbidity models at 30 days (c-statistic difference: 0.029-0.056). The Functional-Plus models exhibited negligible improvements (0.002-0.010) in model performance compared to the Functional models. Conclusion Readmissions are used as a marker of hospital performance. Function-based readmission models in the spinal cord injury population outperform models incorporating medical comorbidities. Readmission risk models for this population would benefit from the inclusion of functional status.

Accuracy of Genomic Prediction for Foliar Terpene Traits in Eucalyptus polybractea.

PubMed

Kainer, David; Stone, Eric A; Padovan, Amanda; Foley, William J; Külheim, Carsten

2018-06-11

Unlike agricultural crops, most forest species have not had millennia of improvement through phenotypic selection, but can contribute energy and material resources and possibly help alleviate climate change. Yield gains similar to those achieved in agricultural crops over millennia could be made in forestry species with the use of genomic methods in a much shorter time frame. Here we compare various methods of genomic prediction for eight traits related to foliar terpene yield in Eucalyptus polybractea , a tree grown predominantly for the production of Eucalyptus oil. The genomic markers used in this study are derived from shallow whole genome sequencing of a population of 480 trees. We compare the traditional pedigree-based additive best linear unbiased predictors (ABLUP), genomic BLUP (GBLUP), BayesB genomic prediction model, and a form of GBLUP based on weighting markers according to their influence on traits (BLUP|GA). Predictive ability is assessed under varying marker densities of 10,000, 100,000 and 500,000 SNPs. Our results show that BayesB and BLUP|GA perform best across the eight traits. Predictive ability was higher for individual terpene traits, such as foliar α-pinene and 1,8-cineole concentration (0.59 and 0.73, respectively), than aggregate traits such as total foliar oil concentration (0.38). This is likely a function of the trait architecture and markers used. BLUP|GA was the best model for the two biomass related traits, height and 1 year change in height (0.25 and 0.19, respectively). Predictive ability increased with marker density for most traits, but with diminishing returns. The results of this study are a solid foundation for yield improvement of essential oil producing eucalypts. New markets such as biopolymers and terpene-derived biofuels could benefit from rapid yield increases in undomesticated oil-producing species. Copyright © 2018, G3: Genes, Genomes, Genetics.

Prognostic Cell Biological Markers in Cervical Cancer Patients Primarily Treated With (Chemo)radiation: A Systematic Review

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

Noordhuis, Maartje G.; Eijsink, Jasper J.H.; Roossink, Frank

2011-02-01

The aim of this study was to systematically review the prognostic and predictive significance of cell biological markers in cervical cancer patients primarily treated with (chemo)radiation. A PubMed, Embase, and Cochrane literature search was performed. Studies describing a relation between a cell biological marker and survival in {>=}50 cervical cancer patients primarily treated with (chemo)radiation were selected. Study quality was assessed, and studies with a quality score of 4 or lower were excluded. Cell biological markers were clustered on biological function, and the prognostic and predictive significance of these markers was described. In total, 42 studies concerning 82 cell biologicalmore » markers were included in this systematic review. In addition to cyclooxygenase-2 (COX-2) and serum squamous cell carcinoma antigen (SCC-ag) levels, markers associated with poor prognosis were involved in epidermal growth factor receptor (EGFR) signaling (EGFR and C-erbB-2) and in angiogenesis and hypoxia (carbonic anhydrase 9 and hypoxia-inducible factor-1{alpha}). Epidermal growth factor receptor and C-erbB-2 were also associated with poor response to (chemo)radiation. In conclusion, EGFR signaling is associated with poor prognosis and response to therapy in cervical cancer patients primarily treated with (chemo)radiation, whereas markers involved in angiogenesis and hypoxia, COX-2, and serum SCC-ag levels are associated with a poor prognosis. Therefore, targeting these pathways in combination with chemoradiation may improve survival in advanced-stage cervical cancer patients.« less

Genomic relationships based on X chromosome markers and accuracy of genomic predictions with and without X chromosome markers

PubMed Central

2014-01-01

Background Although the X chromosome is the second largest bovine chromosome, markers on the X chromosome are not used for genomic prediction in some countries and populations. In this study, we presented a method for computing genomic relationships using X chromosome markers, investigated the accuracy of imputation from a low density (7K) to the 54K SNP (single nucleotide polymorphism) panel, and compared the accuracy of genomic prediction with and without using X chromosome markers. Methods The impact of considering X chromosome markers on prediction accuracy was assessed using data from Nordic Holstein bulls and different sets of SNPs: (a) the 54K SNPs for reference and test animals, (b) SNPs imputed from the 7K to the 54K SNP panel for test animals, (c) SNPs imputed from the 7K to the 54K panel for half of the reference animals, and (d) the 7K SNP panel for all animals. Beagle and Findhap were used for imputation. GBLUP (genomic best linear unbiased prediction) models with or without X chromosome markers and with or without a residual polygenic effect were used to predict genomic breeding values for 15 traits. Results Averaged over the two imputation datasets, correlation coefficients between imputed and true genotypes for autosomal markers, pseudo-autosomal markers, and X-specific markers were 0.971, 0.831 and 0.935 when using Findhap, and 0.983, 0.856 and 0.937 when using Beagle. Estimated reliabilities of genomic predictions based on the imputed datasets using Findhap or Beagle were very close to those using the real 54K data. Genomic prediction using all markers gave slightly higher reliabilities than predictions without X chromosome markers. Based on our data which included only bulls, using a G matrix that accounted for sex-linked relationships did not improve prediction, compared with a G matrix that did not account for sex-linked relationships. A model that included a polygenic effect did not recover the loss of prediction accuracy from exclusion of X chromosome markers. Conclusions The results from this study suggest that markers on the X chromosome contribute to accuracy of genomic predictions and should be used for routine genomic evaluation. PMID:25080199

Metagenomics of prebiotic and probiotic supplemented broilers gastrointestinal tract microbiome

USDA-ARS?s Scientific Manuscript database

Phylogenetic investigation of communities by reconstruction of unobserved states (PICRUSt) is a recently developed computational approach for prediction of functional composition of a microbiome comparing marker gene data with a reference genome database. The procedure established significant link ...

A two step Bayesian approach for genomic prediction of breeding values.

PubMed

Shariati, Mohammad M; Sørensen, Peter; Janss, Luc

2012-05-21

In genomic models that assign an individual variance to each marker, the contribution of one marker to the posterior distribution of the marker variance is only one degree of freedom (df), which introduces many variance parameters with only little information per variance parameter. A better alternative could be to form clusters of markers with similar effects where markers in a cluster have a common variance. Therefore, the influence of each marker group of size p on the posterior distribution of the marker variances will be p df. The simulated data from the 15th QTL-MAS workshop were analyzed such that SNP markers were ranked based on their effects and markers with similar estimated effects were grouped together. In step 1, all markers with minor allele frequency more than 0.01 were included in a SNP-BLUP prediction model. In step 2, markers were ranked based on their estimated variance on the trait in step 1 and each 150 markers were assigned to one group with a common variance. In further analyses, subsets of 1500 and 450 markers with largest effects in step 2 were kept in the prediction model. Grouping markers outperformed SNP-BLUP model in terms of accuracy of predicted breeding values. However, the accuracies of predicted breeding values were lower than Bayesian methods with marker specific variances. Grouping markers is less flexible than allowing each marker to have a specific marker variance but, by grouping, the power to estimate marker variances increases. A prior knowledge of the genetic architecture of the trait is necessary for clustering markers and appropriate prior parameterization.

Reliability of functional and predictive methods to estimate the hip joint centre in human motion analysis in healthy adults.

PubMed

Kainz, Hans; Hajek, Martin; Modenese, Luca; Saxby, David J; Lloyd, David G; Carty, Christopher P

2017-03-01

In human motion analysis predictive or functional methods are used to estimate the location of the hip joint centre (HJC). It has been shown that the Harrington regression equations (HRE) and geometric sphere fit (GSF) method are the most accurate predictive and functional methods, respectively. To date, the comparative reliability of both approaches has not been assessed. The aims of this study were to (1) compare the reliability of the HRE and the GSF methods, (2) analyse the impact of the number of thigh markers used in the GSF method on the reliability, (3) evaluate how alterations to the movements that comprise the functional trials impact HJC estimations using the GSF method, and (4) assess the influence of the initial guess in the GSF method on the HJC estimation. Fourteen healthy adults were tested on two occasions using a three-dimensional motion capturing system. Skin surface marker positions were acquired while participants performed quite stance, perturbed and non-perturbed functional trials, and walking trials. Results showed that the HRE were more reliable in locating the HJC than the GSF method. However, comparison of inter-session hip kinematics during gait did not show any significant difference between the approaches. Different initial guesses in the GSF method did not result in significant differences in the final HJC location. The GSF method was sensitive to the functional trial performance and therefore it is important to standardize the functional trial performance to ensure a repeatable estimate of the HJC when using the GSF method. Copyright © 2017 Elsevier B.V. All rights reserved.

Evaluating surrogate endpoints, prognostic markers, and predictive markers: Some simple themes.

PubMed

Baker, Stuart G; Kramer, Barnett S

2015-08-01

A surrogate endpoint is an endpoint observed earlier than the true endpoint (a health outcome) that is used to draw conclusions about the effect of treatment on the unobserved true endpoint. A prognostic marker is a marker for predicting the risk of an event given a control treatment; it informs treatment decisions when there is information on anticipated benefits and harms of a new treatment applied to persons at high risk. A predictive marker is a marker for predicting the effect of treatment on outcome in a subgroup of patients or study participants; it provides more rigorous information for treatment selection than a prognostic marker when it is based on estimated treatment effects in a randomized trial. We organized our discussion around a different theme for each topic. "Fundamentally an extrapolation" refers to the non-statistical considerations and assumptions needed when using surrogate endpoints to evaluate a new treatment. "Decision analysis to the rescue" refers to use the use of decision analysis to evaluate an additional prognostic marker because it is not possible to choose between purely statistical measures of marker performance. "The appeal of simplicity" refers to a straightforward and efficient use of a single randomized trial to evaluate overall treatment effect and treatment effect within subgroups using predictive markers. The simple themes provide a general guideline for evaluation of surrogate endpoints, prognostic markers, and predictive markers. © The Author(s) 2014.

Corpus callosum atrophy as a marker of clinically meaningful cognitive decline in secondary progressive multiple sclerosis. Impact on employment status.

PubMed

Papathanasiou, Athanasios; Messinis, Lambros; Zampakis, Petros; Papathanasopoulos, Panagiotis

2017-09-01

Cognitive impairment in Multiple Sclerosis (MS) is more frequent and pronounced in secondary progressive MS (SPMS). Cognitive decline is an important predictor of employment status in patients with MS. Magnetic Resonance Imaging (MRI) markers have been used to associate tissue damage with cognitive dysfunction. The aim of the study was to designate the MRI marker that predicts cognitive decline in SPMS and explore its effect on employment status. 30 SPMS patients and 30 healthy participants underwent neuropsychological assessment using the Trail Making Test (TMT) parts A and B, semantic and phonological verbal fluency task and a computerized cognitive screening battery (Central Nervous System Vital Signs). Employment status was obtained as a quality of life measure. Brain MRI was performed in all participants. We measured total lesion volume, third ventricle width, thalamic and corpus callosum atrophy. The frequency of cognitive decline for our SPMS patients was 80%. SPMS patients differed significantly from controls in all neuropsychological measures. Corpus callosum area was correlated with cognitive flexibility, processing speed, composite memory, executive functions, psychomotor speed, reaction time and phonological verbal fluency task. Processing speed and composite memory were the most sensitive markers for predicting employment status. Corpus callosum area was the most sensitive MRI marker for memory and processing speed. Corpus callosum atrophy predicts a clinically meaningful cognitive decline, affecting employment status in our SPMS patients. Copyright © 2017 Elsevier Ltd. All rights reserved.

Evaluating surrogate endpoints, prognostic markers, and predictive markers — some simple themes

PubMed Central

Baker, Stuart G.; Kramer, Barnett S.

2014-01-01

Background A surrogate endpoint is an endpoint observed earlier than the true endpoint (a health outcome) that is used to draw conclusions about the effect of treatment on the unobserved true endpoint. A prognostic marker is a marker for predicting the risk of an event given a control treatment; it informs treatment decisions when there is information on anticipated benefits and harms of a new treatment applied to persons at high risk. A predictive marker is a marker for predicting the effect of treatment on outcome in a subgroup of patients or study participants; it provides more rigorous information for treatment selection than a prognostic marker when it is based on estimated treatment effects in a randomized trial. Methods We organized our discussion around a different theme for each topic. Results “Fundamentally an extrapolation” refers to the non-statistical considerations and assumptions needed when using surrogate endpoints to evaluate a new treatment. “Decision analysis to the rescue” refers to use the use of decision analysis to evaluate an additional prognostic marker because it is not possible to choose between purely statistical measures of marker performance. “The appeal of simplicity” refers to a straightforward and efficient use of a single randomized trial to evaluate overall treatment effect and treatment effect within subgroups using predictive markers. Conclusion The simple themes provide a general guideline for evaluation of surrogate endpoints, prognostic markers, and predictive markers. PMID:25385934

Pupil dilation signals uncertainty and surprise in a learning gambling task.

PubMed

Lavín, Claudio; San Martín, René; Rosales Jubal, Eduardo

2013-01-01

Pupil dilation under constant illumination is a physiological marker where modulation is related to several cognitive functions involved in daily decision making. There is evidence for a role of pupil dilation change during decision-making tasks associated with uncertainty, reward-prediction errors and surprise. However, while some work suggests that pupil dilation is mainly modulated by reward predictions, others point out that this marker is related to uncertainty signaling and surprise. Supporting the latter hypothesis, the neural substrate of this marker is related to noradrenaline (NA) activity which has been also related to uncertainty signaling. In this work we aimed to test whether pupil dilation is a marker for uncertainty and surprise in a learning task. We recorded pupil dilation responses in 10 participants performing the Iowa Gambling Task (IGT), a decision-making task that requires learning and constant monitoring of outcomes' feedback, which are important variables within the traditional study of human decision making. Results showed that pupil dilation changes were modulated by learned uncertainty and surprise regardless of feedback magnitudes. Interestingly, greater pupil dilation changes were found during positive feedback (PF) presentation when there was lower uncertainty about a future negative feedback (NF); and by surprise during NF presentation. These results support the hypothesis that pupil dilation is a marker of learned uncertainty, and may be used as a marker of NA activity facing unfamiliar situations in humans.

Pupil dilation signals uncertainty and surprise in a learning gambling task

PubMed Central

Lavín, Claudio; San Martín, René; Rosales Jubal, Eduardo

2014-01-01

Pupil dilation under constant illumination is a physiological marker where modulation is related to several cognitive functions involved in daily decision making. There is evidence for a role of pupil dilation change during decision-making tasks associated with uncertainty, reward-prediction errors and surprise. However, while some work suggests that pupil dilation is mainly modulated by reward predictions, others point out that this marker is related to uncertainty signaling and surprise. Supporting the latter hypothesis, the neural substrate of this marker is related to noradrenaline (NA) activity which has been also related to uncertainty signaling. In this work we aimed to test whether pupil dilation is a marker for uncertainty and surprise in a learning task. We recorded pupil dilation responses in 10 participants performing the Iowa Gambling Task (IGT), a decision-making task that requires learning and constant monitoring of outcomes’ feedback, which are important variables within the traditional study of human decision making. Results showed that pupil dilation changes were modulated by learned uncertainty and surprise regardless of feedback magnitudes. Interestingly, greater pupil dilation changes were found during positive feedback (PF) presentation when there was lower uncertainty about a future negative feedback (NF); and by surprise during NF presentation. These results support the hypothesis that pupil dilation is a marker of learned uncertainty, and may be used as a marker of NA activity facing unfamiliar situations in humans. PMID:24427126

Endothelial Progenitor Cell Levels Predict Future Physical Function: An Exploratory Analysis From the VA Enhanced Fitness Study.

PubMed

Povsic, Thomas J; Sloane, Richard; Pieper, Carl F; Pearson, Megan P; Peterson, Eric D; Cohen, Harvey J; Morey, Miriam C

2016-03-01

Levels of circulating progenitor cells (CPCs) are depleted with aging and chronic injury and are associated with level of physical functioning; however, little is known about the correlation of CPCs with longer-term measures of physical capabilities. We sought to determine the association of CPCs with future levels of physical function and with changes in physical function over time. CPCs were measured in 117 participants with impaired glucose tolerance in the Enhanced Fitness clinical trial based on the cell surface markers CD34 and CD133 and aldehyde dehydrogenase (ALDH) activity at baseline, 3 months, and 12 months. Physical function was assessed using usual and rapid gait speed, 6-minute walk distance, chair stand time, and SF-36 physical functioning score and reassessed at 3 and 12 months after clinical intervention. Higher baseline levels of CD133(+), CD34(+), CD133(+)CD34(+), and ALDH(br) were each highly predictive of faster gait speed and longer distance walked in 6 minutes at both 3 and 12 months. These associations remained robust after adjustment for age, body mass index, baseline covariates, and inflammation and were independent of interventions to improve physical fitness. Further, higher CPC levels predicted greater improvements in usual and rapid gait speed over 1 year. Baseline CPC levels are associated not only with baseline mobility but also with future physical function, including changes in gait speed. These findings suggest that CPC measurement may be useful as a marker of both current and future physiologic aging and functional decline. © The Author 2015. Published by Oxford University Press on behalf of The Gerontological Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Non-Cholesterol Sterol Levels Predict Hyperglycemia and Conversion to Type 2 Diabetes in Finnish Men

PubMed Central

Cederberg, Henna; Gylling, Helena; Miettinen, Tatu A.; Paananen, Jussi; Vangipurapu, Jagadish; Pihlajamäki, Jussi; Kuulasmaa, Teemu; Stančáková, Alena; Smith, Ulf; Kuusisto, Johanna; Laakso, Markku

2013-01-01

We investigated the levels of non-cholesterol sterols as predictors for the development of hyperglycemia (an increase in the glucose area under the curve in an oral glucose tolerance test) and incident type 2 diabetes in a 5-year follow-up study of a population-based cohort of Finnish men (METSIM Study, N = 1,050) having non-cholesterol sterols measured at baseline. Additionally we determined the association of 538,265 single nucleotide polymorphisms (SNP) with non-cholesterol sterol levels in a cross-sectional cohort of non-diabetic offspring of type 2 diabetes (the Kuopio cohort of the EUGENE2 Study, N = 273). We found that in a cross-sectional METSIM Study the levels of sterols indicating cholesterol absorption were reduced as a function of increasing fasting glucose levels, whereas the levels of sterols indicating cholesterol synthesis were increased as a function of increasing 2-hour glucose levels. A cholesterol synthesis marker desmosterol significantly predicted an increase, and two absorption markers (campesterol and avenasterol) a decrease in the risk of hyperglycemia and incident type 2 diabetes in a 5-year follow-up of the METSIM cohort, mainly attributable to insulin sensitivity. A SNP of ABCG8 was associated with fasting plasma glucose levels in a cross-sectional study but did not predict hyperglycemia or incident type 2 diabetes. In conclusion, the levels of some, but not all non-cholesterol sterols are markers of the worsening of hyperglycemia and type 2 diabetes. PMID:23840693

A 3-Protein Expression Signature of Neuroblastoma for Outcome Prediction.

PubMed

Xie, Yi; Xu, Hua; Fang, Fang; Li, Zhiheng; Zhou, Huiting; Pan, Jian; Guo, Wanliang; Zhu, Xueming; Wang, Jian; Wu, Yi

2018-05-22

Neuroblastoma (NB) is the most common extracranial solid tumor in children with contrasting outcomes. Precise risk assessment contributes to prognosis prediction, which is critical for treatment strategy decisions. In this study, we developed a 3-protein predictor model, including the neural stem cell marker Msi1, neural differentiation marker ID1, and proliferation marker proliferating cell nuclear antigen (PCNA), to improve clinical risk assessment of patients with NB. Kaplan-Meier analysis in the microarray data (GSE16476) revealed that low expression of ID1 and high expression of Msi1 and PCNA were associated with poor prognosis in NB patients. Combined application of these 3 markers to constitute a signature further stratified NB patients into different risk subgroups can help obtain more accurate prediction performance. Survival prognostic power of age and Msi1_ID1_PCNA signature by receiver operating characteristics analysis showed that this signature predicted more effectively and sensitively compared with classic risk stratification system, compensating for the deficiency of the prediction function of the age. Furthermore, we validated the expressions of these 3 proteins in neuroblastic tumor spectrum tissues by immunohistochemistry revealed that Msi1 and PCNA exhibited increased expression in NB compared with intermedial ganglioneuroblastoma and benign ganglioneuroma, whereas ID1 levels were reduced in NB. In conclusion, we established a robust risk assessment predictor model based on simple immunohistochemistry for therapeutic decisions of NB patients.This is an open-access article distributed under the terms of the Creative Commons Attribution-Non Commercial-No Derivatives License 4.0 (CCBY-NC-ND), where it is permissible to download and share the work provided it is properly cited. The work cannot be changed in any way or used commercially without permission from the journal. http://creativecommons.org/licenses/by-nc-nd/4.0/.

Visit-to-visit blood pressure variability as a prognostic marker in patients with cardiovascular and cerebrovascular diseases--relationships and comparisons with vascular markers of atherosclerosis.

PubMed

Lau, Kui Kai; Wong, Yuen Kwun; Chan, Yap Hang; Teo, Kay Cheong; Chan, Koon Ho; Wai Li, Leonard Sheung; Cheung, Raymond Tak Fai; Siu, Chung Wah; Ho, Shu Leong; Tse, Hung Fat

2014-07-01

Visit-to-visit blood pressure variability (BPV) is a simple surrogate marker for the development of atherosclerotic diseases, cardiovascular and all-cause mortality. Nevertheless, the relative prognostic value of BPV in comparison with other established vascular assessments remain uncertain. We prospectively followed-up 656 high-risk patients with diabetes or established cardiovascular or cerebrovascular diseases for the occurrence of major adverse cardiovascular events (MACEs). Baseline brachial endothelial function, carotid intima-media thickness (IMT) and plaque burden, ankle-brachial index and arterial stiffness were determined. Visit-to-visit BPV were recorded during a mean 18 ± 9 outpatient clinic visits. After a mean 81 ± 12 month's follow-up, 123 patients (19%) developed MACEs. Patients who developed a MACE had significantly higher systolic BPV, more severe endothelial function, arterial stiffness and systemic atherosclerotic burden compared to patients who did not develop a MACE (all P<0.01). BPV significantly correlated with all of the vascular assessments (P<0.01). A high carotid IMT had the greatest prognostic value in predicting development of a MACE (area under receiver operating characteristic curve (AUC) 0.69 ± 0.03, P<0.01). A high BPV also had moderate prognostic value in prediction of MACE (AUC 0.65 ± 0.03, P<0.01). After adjustment of confounding factors, a high BPV remained a significant independent predictor of MACE (hazards ratio 1.67, 95% confidence interval 1.14-2.43, P<0.01). Compared with established surrogate markers of atherosclerosis, visit-to-visit BPV provides similar prognostic information and may represent a new and simple marker for adverse outcomes in patients with vascular diseases. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Do Executive Function and Impulsivity Predict Adolescent Health Behaviour after Accounting for Intelligence? Findings from the ALSPAC Cohort

PubMed Central

Pechey, Rachel; Couturier, Dominique-Laurent; Deary, Ian J.; Marteau, Theresa M.

2016-01-01

Objective Executive function, impulsivity, and intelligence are correlated markers of cognitive resource that predict health-related behaviours. It is unknown whether executive function and impulsivity are unique predictors of these behaviours after accounting for intelligence. Methods Data from 6069 participants from the Avon Longitudinal Study of Parents and Children were analysed to investigate whether components of executive function (selective attention, attentional control, working memory, and response inhibition) and impulsivity (parent-rated) measured between ages 8 and 10, predicted having ever drunk alcohol, having ever smoked, fruit and vegetable consumption, physical activity, and overweight at age 13, after accounting for intelligence at age 8 and childhood socioeconomic characteristics. Results Higher intelligence predicted having drunk alcohol, not smoking, greater fruit and vegetable consumption, and not being overweight. After accounting for intelligence, impulsivity predicted alcohol use (odds ratio = 1.10; 99% confidence interval = 1.02, 1.19) and smoking (1.22; 1.11, 1.34). Working memory predicted not being overweight (0.90; 0.81, 0.99). Conclusions After accounting for intelligence, executive function predicts overweight status but not health-related behaviours in early adolescence, whilst impulsivity predicts the onset of alcohol and cigarette use, all with small effects. This suggests overlap between executive function and intelligence as predictors of health behaviour in this cohort, with trait impulsivity accounting for additional variance. PMID:27479488

Do Executive Function and Impulsivity Predict Adolescent Health Behaviour after Accounting for Intelligence? Findings from the ALSPAC Cohort.

PubMed

Stautz, Kaidy; Pechey, Rachel; Couturier, Dominique-Laurent; Deary, Ian J; Marteau, Theresa M

2016-01-01

Executive function, impulsivity, and intelligence are correlated markers of cognitive resource that predict health-related behaviours. It is unknown whether executive function and impulsivity are unique predictors of these behaviours after accounting for intelligence. Data from 6069 participants from the Avon Longitudinal Study of Parents and Children were analysed to investigate whether components of executive function (selective attention, attentional control, working memory, and response inhibition) and impulsivity (parent-rated) measured between ages 8 and 10, predicted having ever drunk alcohol, having ever smoked, fruit and vegetable consumption, physical activity, and overweight at age 13, after accounting for intelligence at age 8 and childhood socioeconomic characteristics. Higher intelligence predicted having drunk alcohol, not smoking, greater fruit and vegetable consumption, and not being overweight. After accounting for intelligence, impulsivity predicted alcohol use (odds ratio = 1.10; 99% confidence interval = 1.02, 1.19) and smoking (1.22; 1.11, 1.34). Working memory predicted not being overweight (0.90; 0.81, 0.99). After accounting for intelligence, executive function predicts overweight status but not health-related behaviours in early adolescence, whilst impulsivity predicts the onset of alcohol and cigarette use, all with small effects. This suggests overlap between executive function and intelligence as predictors of health behaviour in this cohort, with trait impulsivity accounting for additional variance.

Comparison of copeptin, B-type natriuretic peptide, and amino-terminal pro-B-type natriuretic peptide in patients with chronic heart failure: prediction of death at different stages of the disease.

PubMed

Neuhold, Stephanie; Huelsmann, Martin; Strunk, Guido; Stoiser, Brigitte; Struck, Joachim; Morgenthaler, Nils G; Bergmann, Andreas; Moertl, Deddo; Berger, Rudolf; Pacher, Richard

2008-07-22

This study sought to evaluate the predictive value of copeptin over the entire spectrum of heart failure (HF) and compare it to the current benchmark markers, B-type natriuretic peptide (BNP) and N-terminal pro-B-type natriuretic peptide (NT-proBNP). Vasopressin has been shown to increase with the severity of chronic HF. Copeptin is a fragment of pre-pro-vasopressin that is synthesized and secreted in equimolar amounts to vasopressin. Both hormones have a short lifetime in vivo, similar to BNPs, but in contrast to vasopressin, copeptin is very stable in vitro. The predictive value of copeptin has been shown in advanced HF, where it was superior to BNP for predicting 24-month mortality. This was a long-term observational study in 786 HF patients from the whole spectrum of heart failure (New York Heart Association [NYHA] functional class I to IV, BNP 688 +/- 948 pg/ml [range 3 to 8,536 pg/ml], left ventricular ejection fraction 25 +/- 10% [range 5% to 65%]). The NYHA functional class was the most potent single predictor of 24-month outcome in a stepwise Cox regression model. The BNP, copeptin, and glomerular filtration rate were related to NYHA functional class (p < 0.0001 for trend). Copeptin was the most potent single predictor of mortality in patients with NYHA functional class II (p < 0.0001) and class III (p < 0.0001). In NYHA functional class IV, the outcome of patients was best predicted by serum sodium, but again, copeptin added additional independent information. Increased levels of copeptin are linked to excess mortality, and this link is maintained irrespective of the clinical signs of severity of the disease. Copeptin was superior to BNP or NT-proBNP in this study, but the markers seem to be closely related.

Clinical Correlates and Prognostic Value of Proenkephalin in Acute and Chronic Heart Failure.

PubMed

Matsue, Yuya; Ter Maaten, Jozine M; Struck, Joachim; Metra, Marco; O'Connor, Christopher M; Ponikowski, Piotr; Teerlink, John R; Cotter, Gad; Davison, Beth; Cleland, John G; Givertz, Michael M; Bloomfield, Daniel M; Dittrich, Howard C; van Veldhuisen, Dirk J; van der Meer, Peter; Damman, Kevin; Voors, Adriaan A

2017-03-01

Proenkephalin (pro-ENK) has emerged as a novel biomarker associated with both renal function and cardiac function. However, its clinical and prognostic value have not been well evaluated in symptomatic patients with heart failure. The association between pro-ENK and markers of renal function was evaluated in 95 patients with chronic heart failure who underwent renal hemodynamic measurements, including renal blood flow (RBF) and glomerular filtration rate (GFR) with the use of 131 I-Hippuran and 125 I-iothalamate clearances, respectively. The association between pro-ENK and clinical outcome in acute heart failure was assessed in another 1589 patients. Pro-ENK was strongly correlated with both RBF (P < .001) and GFR (P < .001), but not with renal tubular markers. In the acute heart failure cohort, pro-ENK was a predictor of death through 180 days, heart failure rehospitalization through 60 days, and death or cardiovascular or renal rehospitalization through day 60 in univariable analyses, but its predictive value was lost in a multivariable model when other renal markers were entered in the model. In patients with chronic and acute heart failure, pro-ENK is strongly associated with glomerular function, but not with tubular damage. Pro-ENK provides limited prognostic information in patients with acute heart failure on top of established renal markers. Copyright © 2016 Elsevier Inc. All rights reserved.

Enhancing genomic prediction with genome-wide association studies in multiparental maize populations

USDA-ARS?s Scientific Manuscript database

Genome-wide association mapping using dense marker sets has identified some nucleotide variants affecting complex traits which have been validated with fine-mapping and functional analysis. Many sequence variants associated with complex traits in maize have small effects and low repeatability, howev...

Molecular markers for urothelial bladder cancer prognosis: toward implementation in clinical practice.

PubMed

van Rhijn, Bas W G; Catto, James W; Goebell, Peter J; Knüchel, Ruth; Shariat, Shahrokh F; van der Poel, Henk G; Sanchez-Carbayo, Marta; Thalmann, George N; Schmitz-Dräger, Bernd J; Kiemeney, Lambertus A

2014-10-01

To summarize the current status of clinicopathological and molecular markers for the prediction of recurrence or progression or both in non-muscle-invasive and survival in muscle-invasive urothelial bladder cancer, to address the reproducibility of pathology and molecular markers, and to provide directions toward implementation of molecular markers in future clinical decision making. Immunohistochemistry, gene signatures, and FGFR3-based molecular grading were used as molecular examples focussing on prognostics and issues related to robustness of pathological and molecular assays. The role of molecular markers to predict recurrence is limited, as clinical variables are currently more important. The prediction of progression and survival using molecular markers holds considerable promise. Despite a plethora of prognostic (clinical and molecular) marker studies, reproducibility of pathology and molecular assays has been understudied, and lack of reproducibility is probably the main reason that individual prediction of disease outcome is currently not reliable. Molecular markers are promising to predict progression and survival, but not recurrence. However, none of these are used in the daily clinical routine because of reproducibility issues. Future studies should focus on reproducibility of marker assessment and consistency of study results by incorporating scoring systems to reduce heterogeneity of reporting. This may ultimately lead to incorporation of molecular markers in clinical practice. Copyright © 2014 Elsevier Inc. All rights reserved.

Large splenic volume may be a useful predictor for partial splenic embolization-induced liver functional improvement in cirrhotic patients.

PubMed

Hayashi, Hiromitsu; Beppu, Toru; Masuda, Toshiro; Okabe, Hirohisa; Imai, Katsunori; Hashimoto, Daisuke; Ikuta, Yoshiaki; Chikamoto, Akira; Watanabe, Masayuki; Baba, Hideo

2014-01-01

Partial splenic embolization (PSE) for cirrhotic patients has been reported not only to achieve an improvement in thrombocytopenia and portal hypertension, but also to induce PSE-associated fringe benefit such as individual liver functional improvement. The purpose of this study was to clarify the predictive marker of liver functional improvement due from PSE in cirrhotic patients. From April 1999 to January 2009, 83 cirrhotic patients with hypersplenism-induced thrombocytopenia (platelet count <10 × 10(4)/μl) underwent PSE. Of them, 71 patients with follow-up for more than one year after PSE were retrospectively investigated. In liver tissues after PSE, proliferating cell nuclear antigen (PCNA)-positive hepatocytes were remarkably increased, speculating that PSE induced liver regenerative response. Indeed, serum albumin and cholinesterase levels increased to 104 ± 14% and 130 ± 65% each of the pretreatment level at one year after PSE. In a multiple linear regression analysis, preoperative splenic volume was extracted as the predictive factor for the improvement in cholinesterase level after PSE. Cirrhotic patients with preoperative splenic volume >600 ml obtained significantly higher serum albumin and cholinesterase levels at one year after PSE compared to those with less than 600 ml (P-values were 0.029 in both). A large preoperative splenic volume was the useful predictive marker for an effective PSE-induced liver functional improvement. © 2013 Japanese Society of Hepato-Biliary-Pancreatic Surgery.

Variable selection models for genomic selection using whole-genome sequence data and singular value decomposition.

PubMed

Meuwissen, Theo H E; Indahl, Ulf G; Ødegård, Jørgen

2017-12-27

Non-linear Bayesian genomic prediction models such as BayesA/B/C/R involve iteration and mostly Markov chain Monte Carlo (MCMC) algorithms, which are computationally expensive, especially when whole-genome sequence (WGS) data are analyzed. Singular value decomposition (SVD) of the genotype matrix can facilitate genomic prediction in large datasets, and can be used to estimate marker effects and their prediction error variances (PEV) in a computationally efficient manner. Here, we developed, implemented, and evaluated a direct, non-iterative method for the estimation of marker effects for the BayesC genomic prediction model. The BayesC model assumes a priori that markers have normally distributed effects with probability [Formula: see text] and no effect with probability (1 - [Formula: see text]). Marker effects and their PEV are estimated by using SVD and the posterior probability of the marker having a non-zero effect is calculated. These posterior probabilities are used to obtain marker-specific effect variances, which are subsequently used to approximate BayesC estimates of marker effects in a linear model. A computer simulation study was conducted to compare alternative genomic prediction methods, where a single reference generation was used to estimate marker effects, which were subsequently used for 10 generations of forward prediction, for which accuracies were evaluated. SVD-based posterior probabilities of markers having non-zero effects were generally lower than MCMC-based posterior probabilities, but for some regions the opposite occurred, resulting in clear signals for QTL-rich regions. The accuracies of breeding values estimated using SVD- and MCMC-based BayesC analyses were similar across the 10 generations of forward prediction. For an intermediate number of generations (2 to 5) of forward prediction, accuracies obtained with the BayesC model tended to be slightly higher than accuracies obtained using the best linear unbiased prediction of SNP effects (SNP-BLUP model). When reducing marker density from WGS data to 30 K, SNP-BLUP tended to yield the highest accuracies, at least in the short term. Based on SVD of the genotype matrix, we developed a direct method for the calculation of BayesC estimates of marker effects. Although SVD- and MCMC-based marker effects differed slightly, their prediction accuracies were similar. Assuming that the SVD of the marker genotype matrix is already performed for other reasons (e.g. for SNP-BLUP), computation times for the BayesC predictions were comparable to those of SNP-BLUP.

Evaluation of an ensemble of genetic models for prediction of a quantitative trait.

PubMed

Milton, Jacqueline N; Steinberg, Martin H; Sebastiani, Paola

2014-01-01

Many genetic markers have been shown to be associated with common quantitative traits in genome-wide association studies. Typically these associated genetic markers have small to modest effect sizes and individually they explain only a small amount of the variability of the phenotype. In order to build a genetic prediction model without fitting a multiple linear regression model with possibly hundreds of genetic markers as predictors, researchers often summarize the joint effect of risk alleles into a genetic score that is used as a covariate in the genetic prediction model. However, the prediction accuracy can be highly variable and selecting the optimal number of markers to be included in the genetic score is challenging. In this manuscript we present a strategy to build an ensemble of genetic prediction models from data and we show that the ensemble-based method makes the challenge of choosing the number of genetic markers more amenable. Using simulated data with varying heritability and number of genetic markers, we compare the predictive accuracy and inclusion of true positive and false positive markers of a single genetic prediction model and our proposed ensemble method. The results show that the ensemble of genetic models tends to include a larger number of genetic variants than a single genetic model and it is more likely to include all of the true genetic markers. This increased sensitivity is obtained at the price of a lower specificity that appears to minimally affect the predictive accuracy of the ensemble.

Imbalance of gut microbiome and intestinal epithelial barrier dysfunction in patients with high blood pressure

PubMed Central

Kim, Seungbum; Goel, Ruby; Kumar, Ashok; Qi, Yanfei; Lobaton, Gil; Hosaka, Koji; Mohammed, Mohammed; Handberg, Eileen M.; Richards, Elaine M.; Pepine, Carl J.; Raizada, Mohan K.

2018-01-01

Recent evidence indicates a link between gut pathology and microbiome with hypertension (HTN) in animal models. However, whether this association exists in humans is unknown. Thus, our objectives in the present study were to test the hypotheses that high blood pressure (BP) patients have distinct gut microbiomes and that gut–epithelial barrier function markers and microbiome composition could predict systolic BP (SBP). Fecal samples, analyzed by shotgun metagenomics, displayed taxonomic and functional changes, including altered butyrate production between patients with high BP and reference subjects. Significant increases in plasma of intestinal fatty acid binding protein (I-FABP), lipopolysaccharide (LPS), and augmented gut-targetting proinflammatory T helper 17 (Th17) cells in high BP patients demonstrated increased intestinal inflammation and permeability. Zonulin, a gut epithelial tight junction protein regulator, was markedly elevated, further supporting gut barrier dysfunction in high BP. Zonulin strongly correlated with SBP (R2 = 0.5301, P<0.0001). Two models predicting SBP were built using stepwise linear regression analysis of microbiome data and circulating markers of gut health, and validated in a separate cohort by prediction of SBP from zonulin in plasma (R2 = 0.4608, P<0.0001). The mouse model of HTN, chronic angiotensin II (Ang II) infusion, was used to confirm the effects of butyrate and gut barrier function on the cardiovascular system and BP. These results support our conclusion that intestinal barrier dysfunction and microbiome function are linked to HTN in humans. They suggest that manipulation of gut microbiome and its barrier functions could be the new therapeutic and diagnostic avenues for HTN. PMID:29507058

Short communication: Improving the accuracy of genomic prediction of body conformation traits in Chinese Holsteins using markers derived from high-density marker panels.

PubMed

Song, H; Li, L; Ma, P; Zhang, S; Su, G; Lund, M S; Zhang, Q; Ding, X

2018-06-01

This study investigated the efficiency of genomic prediction with adding the markers identified by genome-wide association study (GWAS) using a data set of imputed high-density (HD) markers from 54K markers in Chinese Holsteins. Among 3,056 Chinese Holsteins with imputed HD data, 2,401 individuals born before October 1, 2009, were used for GWAS and a reference population for genomic prediction, and the 220 younger cows were used as a validation population. In total, 1,403, 1,536, and 1,383 significant single nucleotide polymorphisms (SNP; false discovery rate at 0.05) associated with conformation final score, mammary system, and feet and legs were identified, respectively. About 2 to 3% genetic variance of 3 traits was explained by these significant SNP. Only a very small proportion of significant SNP identified by GWAS was included in the 54K marker panel. Three new marker sets (54K+) were herein produced by adding significant SNP obtained by linear mixed model for each trait into the 54K marker panel. Genomic breeding values were predicted using a Bayesian variable selection (BVS) model. The accuracies of genomic breeding value by BVS based on the 54K+ data were 2.0 to 5.2% higher than those based on the 54K data. The imputed HD markers yielded 1.4% higher accuracy on average (BVS) than the 54K data. Both the 54K+ and HD data generated lower bias of genomic prediction, and the 54K+ data yielded the lowest bias in all situations. Our results show that the imputed HD data were not very useful for improving the accuracy of genomic prediction and that adding the significant markers derived from the imputed HD marker panel could improve the accuracy of genomic prediction and decrease the bias of genomic prediction. Copyright © 2018 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Paternal Autistic Traits Are Predictive of Infants Visual Attention

ERIC Educational Resources Information Center

Ronconi, Luca; Facoetti, Andrea; Bulf, Hermann; Franchin, Laura; Bettoni, Roberta; Valenza, Eloisa

2014-01-01

Since subthreshold autistic social impairments aggregate in family members, and since attentional dysfunctions appear to be one of the earliest cognitive markers of children with autism, we investigated in the general population the relationship between infants' attentional functioning and the autistic traits measured in their parents.…

Association of Functional SNPs in Pig Calpastatin Regulatory Regions with Tenderness

USDA-ARS?s Scientific Manuscript database

The identification of predictive DNA markers for pork quality would allow U.S. pork producers and breeders to more quickly and efficiently select genetically superior animals for production of consistent, high quality meat. Genome scans have identified QTL for tenderness on pig chromosome 2 which ha...

Haplotype-Based Genome-Wide Prediction Models Exploit Local Epistatic Interactions Among Markers

PubMed Central

Jiang, Yong; Schmidt, Renate H.; Reif, Jochen C.

2018-01-01

Genome-wide prediction approaches represent versatile tools for the analysis and prediction of complex traits. Mostly they rely on marker-based information, but scenarios have been reported in which models capitalizing on closely-linked markers that were combined into haplotypes outperformed marker-based models. Detailed comparisons were undertaken to reveal under which circumstances haplotype-based genome-wide prediction models are superior to marker-based models. Specifically, it was of interest to analyze whether and how haplotype-based models may take local epistatic effects between markers into account. Assuming that populations consisted of fully homozygous individuals, a marker-based model in which local epistatic effects inside haplotype blocks were exploited (LEGBLUP) was linearly transformable into a haplotype-based model (HGBLUP). This theoretical derivation formally revealed that haplotype-based genome-wide prediction models capitalize on local epistatic effects among markers. Simulation studies corroborated this finding. Due to its computational efficiency the HGBLUP model promises to be an interesting tool for studies in which ultra-high-density SNP data sets are studied. Applying the HGBLUP model to empirical data sets revealed higher prediction accuracies than for marker-based models for both traits studied using a mouse panel. In contrast, only a small subset of the traits analyzed in crop populations showed such a benefit. Cases in which higher prediction accuracies are observed for HGBLUP than for marker-based models are expected to be of immediate relevance for breeders, due to the tight linkage a beneficial haplotype will be preserved for many generations. In this respect the inheritance of local epistatic effects very much resembles the one of additive effects. PMID:29549092

Haplotype-Based Genome-Wide Prediction Models Exploit Local Epistatic Interactions Among Markers.

PubMed

Jiang, Yong; Schmidt, Renate H; Reif, Jochen C

2018-05-04

Genome-wide prediction approaches represent versatile tools for the analysis and prediction of complex traits. Mostly they rely on marker-based information, but scenarios have been reported in which models capitalizing on closely-linked markers that were combined into haplotypes outperformed marker-based models. Detailed comparisons were undertaken to reveal under which circumstances haplotype-based genome-wide prediction models are superior to marker-based models. Specifically, it was of interest to analyze whether and how haplotype-based models may take local epistatic effects between markers into account. Assuming that populations consisted of fully homozygous individuals, a marker-based model in which local epistatic effects inside haplotype blocks were exploited (LEGBLUP) was linearly transformable into a haplotype-based model (HGBLUP). This theoretical derivation formally revealed that haplotype-based genome-wide prediction models capitalize on local epistatic effects among markers. Simulation studies corroborated this finding. Due to its computational efficiency the HGBLUP model promises to be an interesting tool for studies in which ultra-high-density SNP data sets are studied. Applying the HGBLUP model to empirical data sets revealed higher prediction accuracies than for marker-based models for both traits studied using a mouse panel. In contrast, only a small subset of the traits analyzed in crop populations showed such a benefit. Cases in which higher prediction accuracies are observed for HGBLUP than for marker-based models are expected to be of immediate relevance for breeders, due to the tight linkage a beneficial haplotype will be preserved for many generations. In this respect the inheritance of local epistatic effects very much resembles the one of additive effects. Copyright © 2018 Jiang et al.

Muscle enzyme release does not predict muscle function impairment after triathlon.

PubMed

Margaritis, I; Tessier, F; Verdera, F; Bermon, S; Marconnet, P

1999-06-01

We sought to determine the effects of a long distance triathlon (4 km swim, 120 km bike-ride, and 30 km run) on the four-day kinetics of the biochemical markers of muscle damage, and whether they were quantitatively linked with muscle function impairment and soreness. Data were collected from 2 days before until 4 days after the completion of the race. Twelve triathletes performed the triathlon and five did not. Maximal voluntary contraction (MVC), muscle soreness (DOMS) and total serum CK, CK-MB, LDH, AST and ALT activities were assessed. Significant changes after triathlon completion were found for all muscle damage indirect markers over time (p < 0.0001). MVC of the knee extensor and flexor muscles decreased over time (p < 0.05). There is disparity in the time point at which peak values where reached for DOMS, MVC and enzyme leakage. There is no correlation between serum enzyme leakage, DOMS and MVC impairment which occur after triathlon. Long distance triathlon race caused muscle damage, but extent, as well as muscle recovery cannot be evaluated by the magnitude of changes in serum enzyme activities. Muscle enzyme release cannot be used to predict the magnitude of the muscle function impairment caused by muscle damage.

Fluctuations, noise, and numerical methods in gyrokinetic particle-in-cell simulations

NASA Astrophysics Data System (ADS)

Jenkins, Thomas Grant

In this thesis, the role of the "marker weight" (or "particle weight") used in gyrokinetic particle-in-cell (PIC) simulations is explored. Following a review of the foundations and major developments of gyrokinetic theory, key concepts of the Monte Carlo methods which form the basis for PIC simulations are set forth. Consistent with these methods, a Klimontovich representation for the set of simulation markers is developed in the extended phase space {R, v||, v ⊥, W, P} (with the additional coordinates representing weight fields); clear distinctions are consequently established between the marker distribution function and various physical distribution functions (arising from diverse moments of the marker distribution). Equations describing transport in the simulation are shown to be easily derivable using the formalism. The necessity of a two-weight model for nonequilibrium simulations is demonstrated, and a simple method for calculating the second (background-related) weight is presented. Procedures for arbitrary marker loading schemes in gyrokinetic PIC simulations are outlined; various initialization methods for simulations are compared. Possible effects of inadequate velocity-space resolution in gyrokinetic continuum simulations are explored. The "partial-f" simulation method is developed and its limitations indicated. A quasilinear treatment of electrostatic drift waves is shown to correctly predict nonlinear saturation amplitudes, and the relevance of the gyrokinetic fluctuation-dissipation theorem in assessing the effects of discrete-marker-induced statistical noise on the resulting marginally stable states is demonstrated.

Potential and limits to unravel the genetic architecture and predict the variation of Fusarium head blight resistance in European winter wheat (Triticum aestivum L.).

PubMed

Jiang, Y; Zhao, Y; Rodemann, B; Plieske, J; Kollers, S; Korzun, V; Ebmeyer, E; Argillier, O; Hinze, M; Ling, J; Röder, M S; Ganal, M W; Mette, M F; Reif, J C

2015-03-01

Genome-wide mapping approaches in diverse populations are powerful tools to unravel the genetic architecture of complex traits. The main goals of our study were to investigate the potential and limits to unravel the genetic architecture and to identify the factors determining the accuracy of prediction of the genotypic variation of Fusarium head blight (FHB) resistance in wheat (Triticum aestivum L.) based on data collected with a diverse panel of 372 European varieties. The wheat lines were phenotyped in multi-location field trials for FHB resistance and genotyped with 782 simple sequence repeat (SSR) markers, and 9k and 90k single-nucleotide polymorphism (SNP) arrays. We applied genome-wide association mapping in combination with fivefold cross-validations and observed surprisingly high accuracies of prediction for marker-assisted selection based on the detected quantitative trait loci (QTLs). Using a random sample of markers not selected for marker-trait associations revealed only a slight decrease in prediction accuracy compared with marker-based selection exploiting the QTL information. The same picture was confirmed in a simulation study, suggesting that relatedness is a main driver of the accuracy of prediction in marker-assisted selection of FHB resistance. When the accuracy of prediction of three genomic selection models was contrasted for the three marker data sets, no significant differences in accuracies among marker platforms and genomic selection models were observed. Marker density impacted the accuracy of prediction only marginally. Consequently, genomic selection of FHB resistance can be implemented most cost-efficiently based on low- to medium-density SNP arrays.

Ratio of mean platelet volume to platelet count is a potential surrogate marker predicting liver cirrhosis.

PubMed

Iida, Hiroya; Kaibori, Masaki; Matsui, Kosuke; Ishizaki, Morihiko; Kon, Masanori

2018-01-27

To provide a simple surrogate marker predictive of liver cirrhosis (LC). Specimens from 302 patients who underwent resection for hepatocellular carcinoma between January 2006 and December 2012 were retrospectively analyzed. Based on pathologic findings, patients were divided into groups based on whether or not they had LC. Parameters associated with hepatic functional reserve were compared in these two groups using Mann-Whitney U -test for univariate analysis. Factors differing significantly in univariate analyses were entered into multivariate logistic regression analysis. There were significant differences between the LC group ( n = 100) and non-LC group ( n = 202) in prothrombin activity, concentrations of alanine aminotransferase, aspartate aminotransferase, total bilirubin, albumin, cholinesterase, type IV collagen, hyaluronic acid, indocyanine green retention rate at 15 min, maximal removal rate of technitium-99m diethylene triamine penta-acetic acid-galactosyl human serum albumin and ratio of mean platelet volume to platelet count (MPV/PLT). Multivariate analysis showed that prothrombin activity, concentrations of alanine aminotransferase, aspartate aminotransferase, total bilirubin and hyaluronic acid, and MPV/PLT ratio were factors independently predictive of LC. The area under the curve value for MPV/PLT was 0.78, with a 0.8 cutoff value having a sensitivity of 65% and a specificity of 78%. The MPV/PLT ratio, which can be determined simply from the complete blood count, may be a simple surrogate marker predicting LC.

Quantifying and comparing dynamic predictive accuracy of joint models for longitudinal marker and time-to-event in presence of censoring and competing risks.

PubMed

Blanche, Paul; Proust-Lima, Cécile; Loubère, Lucie; Berr, Claudine; Dartigues, Jean-François; Jacqmin-Gadda, Hélène

2015-03-01

Thanks to the growing interest in personalized medicine, joint modeling of longitudinal marker and time-to-event data has recently started to be used to derive dynamic individual risk predictions. Individual predictions are called dynamic because they are updated when information on the subject's health profile grows with time. We focus in this work on statistical methods for quantifying and comparing dynamic predictive accuracy of this kind of prognostic models, accounting for right censoring and possibly competing events. Dynamic area under the ROC curve (AUC) and Brier Score (BS) are used to quantify predictive accuracy. Nonparametric inverse probability of censoring weighting is used to estimate dynamic curves of AUC and BS as functions of the time at which predictions are made. Asymptotic results are established and both pointwise confidence intervals and simultaneous confidence bands are derived. Tests are also proposed to compare the dynamic prediction accuracy curves of two prognostic models. The finite sample behavior of the inference procedures is assessed via simulations. We apply the proposed methodology to compare various prediction models using repeated measures of two psychometric tests to predict dementia in the elderly, accounting for the competing risk of death. Models are estimated on the French Paquid cohort and predictive accuracies are evaluated and compared on the French Three-City cohort. © 2014, The International Biometric Society.

Using spatial information about recurrence risk for robust optimization of dose-painting prescription functions

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

Bender, Edward T.

Purpose: To develop a robust method for deriving dose-painting prescription functions using spatial information about the risk for disease recurrence. Methods: Spatial distributions of radiobiological model parameters are derived from distributions of recurrence risk after uniform irradiation. These model parameters are then used to derive optimal dose-painting prescription functions given a constant mean biologically effective dose. Results: An estimate for the optimal dose distribution can be derived based on spatial information about recurrence risk. Dose painting based on imaging markers that are moderately or poorly correlated with recurrence risk are predicted to potentially result in inferior disease control when comparedmore » the same mean biologically effective dose delivered uniformly. A robust optimization approach may partially mitigate this issue. Conclusions: The methods described here can be used to derive an estimate for a robust, patient-specific prescription function for use in dose painting. Two approximate scaling relationships were observed: First, the optimal choice for the maximum dose differential when using either a linear or two-compartment prescription function is proportional to R, where R is the Pearson correlation coefficient between a given imaging marker and recurrence risk after uniform irradiation. Second, the predicted maximum possible gain in tumor control probability for any robust optimization technique is nearly proportional to the square of R.« less

Reduced Marker of Vascularization in the Anterior Hippocampus in a Female Monkey Model of Depression

PubMed Central

Kalidindi, Anisha; Kelly, Sean D.; Singleton, Kaela S.; Guzman, Dora; Merrill, Liana; Willard, Stephanie L.; Shively, Carol A.; Neigh, Gretchen N.

2016-01-01

Depression is a common and debilitating mood disorder that impacts women more often than men. The mechanisms that result in depressive behaviors are not fully understood; however, the hippocampus has been noted as a key structure in the pathophysiology of depression. In addition to neural implications of depression, the cardiovascular system is impacted. Although not as commonly considered, the cerebrovasculature is critical to brain function, impacted by environmental stimuli, and is capable of altering neural function and thereby behavior. In the current study, we assessed the relationship between depressive behavior and a marker of vascularization of the hippocampus in adult female cynomolgus macaques (Macaca fascicularis). Similar to previously noted impacts on neuropil and glia, the depressed phenotype predicts a reduction in a marker of vascular length in the anterior hippocampus. These data reinforce the growing recognition of the effects of depression on vasculature and support further consideration of vascular endpoints in studies aimed at the elucidation of the mechanisms underlying depression. PMID:27423324

Improving lung cancer prognosis assessment by incorporating synthetic minority oversampling technique and score fusion method

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

Yan, Shiju; Qian, Wei; Guan, Yubao

2016-06-15

Purpose: This study aims to investigate the potential to improve lung cancer recurrence risk prediction performance for stage I NSCLS patients by integrating oversampling, feature selection, and score fusion techniques and develop an optimal prediction model. Methods: A dataset involving 94 early stage lung cancer patients was retrospectively assembled, which includes CT images, nine clinical and biological (CB) markers, and outcome of 3-yr disease-free survival (DFS) after surgery. Among the 94 patients, 74 remained DFS and 20 had cancer recurrence. Applying a computer-aided detection scheme, tumors were segmented from the CT images and 35 quantitative image (QI) features were initiallymore » computed. Two normalized Gaussian radial basis function network (RBFN) based classifiers were built based on QI features and CB markers separately. To improve prediction performance, the authors applied a synthetic minority oversampling technique (SMOTE) and a BestFirst based feature selection method to optimize the classifiers and also tested fusion methods to combine QI and CB based prediction results. Results: Using a leave-one-case-out cross-validation (K-fold cross-validation) method, the computed areas under a receiver operating characteristic curve (AUCs) were 0.716 ± 0.071 and 0.642 ± 0.061, when using the QI and CB based classifiers, respectively. By fusion of the scores generated by the two classifiers, AUC significantly increased to 0.859 ± 0.052 (p < 0.05) with an overall prediction accuracy of 89.4%. Conclusions: This study demonstrated the feasibility of improving prediction performance by integrating SMOTE, feature selection, and score fusion techniques. Combining QI features and CB markers and performing SMOTE prior to feature selection in classifier training enabled RBFN based classifier to yield improved prediction accuracy.« less

Prospective evaluation of bone markers, parathormone and 1,25-(OH)₂ vitamin D in HIV-positive patients after the initiation of tenofovir/emtricitabine with atazanavir/ritonavir or efavirenz.

PubMed

Focà, Emanuele; Motta, Davide; Borderi, Marco; Gotti, Daria; Albini, Laura; Calabresi, Alessandra; Izzo, Ilaria; Bellagamba, Rita; Narciso, Pasquale; Sighinolfi, Laura; Clò, Alberto; Gibellini, Davide; Quiros-Roldan, Eugenia; Brianese, Nigritella; Cesana, Bruno Mario; Re, Maria Carla; Torti, Carlo

2012-02-14

Increased risk of fractures and osteoporosis have been associated with the use of antiretroviral drugs. There is a paucity of prospective evaluations of bone markers after the initiation of drugs currently recommended to treat HIV infection and results on the evolution of these markers are conflicting. Lastly, the effect of tenofovir on 1,25-(OH)₂ vitamin D is uncertain. We performed a prospective study on the evolution of bone markers, parathormone and 1,25-(OH)₂ vitamin D before and after standard antiretroviral regimens. This was a sub-study of a trial conducted in antiretroviral-naïve patients randomized to tenofovir + emtricitabine in combination with either atazanavir/ritonavir (ATV/r) or efavirenz (EFV). Follow-up lasted 48 weeks. The following bone markers were analyzed: C-terminal cross-laps (CTx), osteocalcin (OC), osteoprotegerin (OPG), and receptor activator of nuclear factor κB ligand (RANKL). Mixed-factorial analysis of variance with random-coefficient general linear model was used to compare their trends over time and linear multivariable regression was performed with a backward selection method to assess predictors of their variations from baseline to week 48. Trends of parathormone and 1,25-(OH)₂ vitamin D were also evaluated. Seventy-five patients were studied: 33 received EFV and 42 ATV/r. Significant increases were found for all markers except for RANKL. There was a significant direct association between CTx and OC increases. Multivariable analysis showed that higher glomerular filtration rate (estimated through cystatin C clearance) predicted greater OPG increase, while older age, higher HIV RNA at baseline and use of ATV/r predicted greater CTx increase. A significant increase of parathormone accompanied the evolution of the study markers. 1,25-(OH)₂ vitamin D remained stable, though a seasonality variation was demonstrated. These data demonstrate CTx increase (bone resorption marker) corresponding to OC increase (bone formation marker) early upon HAART initiation. Moreover, predictors of bone marker increases have been suggested, possibly indicating that a stricter monitoring of bone health and pro-active interventions are needed in older patients, those with higher HIV RNA, prescribed ATV/r rather than EFV, and with decreased renal function at baseline. Further studies are needed to clarify the mechanisms responsible for up-regulation of bone turnover markers, as well as to understand if and what markers are best correlated or predictive of pathological fractures.

Accuracy of Genomic Prediction in Switchgrass (Panicum virgatum L.) Improved by Accounting for Linkage Disequilibrium

PubMed Central

Ramstein, Guillaume P.; Evans, Joseph; Kaeppler, Shawn M.; Mitchell, Robert B.; Vogel, Kenneth P.; Buell, C. Robin; Casler, Michael D.

2016-01-01

Switchgrass is a relatively high-yielding and environmentally sustainable biomass crop, but further genetic gains in biomass yield must be achieved to make it an economically viable bioenergy feedstock. Genomic selection (GS) is an attractive technology to generate rapid genetic gains in switchgrass, and meet the goals of a substantial displacement of petroleum use with biofuels in the near future. In this study, we empirically assessed prediction procedures for genomic selection in two different populations, consisting of 137 and 110 half-sib families of switchgrass, tested in two locations in the United States for three agronomic traits: dry matter yield, plant height, and heading date. Marker data were produced for the families’ parents by exome capture sequencing, generating up to 141,030 polymorphic markers with available genomic-location and annotation information. We evaluated prediction procedures that varied not only by learning schemes and prediction models, but also by the way the data were preprocessed to account for redundancy in marker information. More complex genomic prediction procedures were generally not significantly more accurate than the simplest procedure, likely due to limited population sizes. Nevertheless, a highly significant gain in prediction accuracy was achieved by transforming the marker data through a marker correlation matrix. Our results suggest that marker-data transformations and, more generally, the account of linkage disequilibrium among markers, offer valuable opportunities for improving prediction procedures in GS. Some of the achieved prediction accuracies should motivate implementation of GS in switchgrass breeding programs. PMID:26869619

[Social dysfunction in schizotypy].

PubMed

de Wachter, O; De La Asuncion, J; Sabbe, B; Morrens, M

2016-01-01

Schizotypy is a personality organisation that is closely related to schizotypal personality disorder and schizophrenia and is characterised by deficits in social functioning. Although the dimensions of social dysfunction have not yet been fully explored certain aspects of social dysfunction are promising predictive markers for schizophrenia. To describe schizotypy and its influence on social functioning. We reviewed the literature systematically using the online databases PubMed and PsycINFO. The disorder known as schizotypy lies at the basis of schizotypal personality disorder. Both disorders are characterised by an increased risk for schizophrenia. The social dysfunctioning seen in schizotypy corresponds to the social dysfunction seen in schizophrenia. Impairments in social cognition are causal factors of this social dysfunction. Both the negative and the positive dimension of schizotypy influence social cognition. More focused, objective and interactive research to the various aspects of social functioning in schizotypy is needed in order to discover potential premorbid markers for schizophrenia.

Circulating microRNA are predictive of aging and acute adaptive response to resistance exercise in men

USDA-ARS?s Scientific Manuscript database

Circulating microRNA (c-miRNA) have the potential to function as novel noninvasive markers of the underlying physiological state of skeletal muscle. This investigation sought to determine the influence of aging on c-miRNA expression at rest and following resistance exercise in male volunteers (Young...

Diesel exhaust exposure among adolescents in Harlem: a community-driven study.

PubMed

Northridge, M E; Yankura, J; Kinney, P L; Santella, R M; Shepard, P; Riojas, Y; Aggarwal, M; Strickland, P

1999-07-01

This study sought individual-level data on diesel exhaust exposure and lung function among adolescents in Harlem as part of a community-driven research agenda. High school students administered in-person surveys to seventh grade students to ascertain information on demographics, asthma history, and self-reported and maternal smoking. Urine samples were assayed for 1-hydroxypyrene (1-HP), a marker of diesel exhaust exposure, and cotinine, a marker of tobacco smoke exposure. Computer-assisted spirometry was used to measure lung function. Three quarters (76%) of the participating students had detectable levels of 1-HP. Three students (13%) had an FEF25-75 of less than or equal to 80% of their predicted measurements, and 4 students (17%) had results between 80% and 90% of the predicted value, all of which are suggestive of possible lung impairment. These data suggest that most adolescents in Harlem are exposed to detectable levels of diesel exhaust, a known exacerbator and possible cause of chronic lung disorders such as asthma. Community-driven research initiatives are important for empowering communities to make needed changes to improve their environments and health.

Probability density function of a puff dispersing from the wall of a turbulent channel

NASA Astrophysics Data System (ADS)

Nguyen, Quoc; Papavassiliou, Dimitrios

2015-11-01

Study of dispersion of passive contaminants in turbulence has proved to be helpful in understanding fundamental heat and mass transfer phenomena. Many simulation and experimental works have been carried out to locate and track motions of scalar markers in a flow. One method is to combine Direct Numerical Simulation (DNS) and Lagrangian Scalar Tracking (LST) to record locations of markers. While this has proved to be useful, high computational cost remains a concern. In this study, we develop a model that could reproduce results obtained by DNS and LST for turbulent flow. Puffs of markers with different Schmidt numbers were released into a flow field at a frictional Reynolds number of 150. The point of release was at the channel wall, so that both diffusion and convection contribute to the puff dispersion pattern, defining different stages of dispersion. Based on outputs from DNS and LST, we seek the most suitable and feasible probability density function (PDF) that represents distribution of markers in the flow field. The PDF would play a significant role in predicting heat and mass transfer in wall turbulence, and would prove to be helpful where DNS and LST are not always available.

A 4-gene panel as a marker at chromosome 8q in Asian gastric cancer patients.

PubMed

Cheng, Lei; Zhang, Qing; Yang, Sheng; Yang, Yanqing; Zhang, Wen; Gao, Hengjun; Deng, Xiaxing; Zhang, Qinghua

2013-10-01

A widely held viewpoint is that the use of multiple markers, combined in some type of algorithm, will be necessary to provide high enough discrimination between diseased cases and non-diseased. We applied stepwise logistic regression analysis to identify the best combination of the 32 biomarkers at chromosome 8q on an independent public microarray test set of 80 paired gastric samples. A combination of SULF1, INTS8, ATP6V1C1, and GPR172A was identified with a prediction accuracy of 98.0% for discriminating carcinomas from adjacent noncancerous tissues in our previous 25 paired samples. Interestingly, the overexpression of SULF1 was associated with tumor invasion and metastasis. Function prediction analysis revealed that the 4-marker panel was mainly associated with acidification of intracellular compartments. Taken together, we found a 4-gene panel that accurately discriminated gastric carcinomas from adjacent noncancerous tissues and these results had potential clinical significance in the early diagnosis and targeted treatment of gastric cancer. Copyright © 2013 Elsevier Inc. All rights reserved.

iDBPs: a web server for the identification of DNA binding proteins.

PubMed

Nimrod, Guy; Schushan, Maya; Szilágyi, András; Leslie, Christina; Ben-Tal, Nir

2010-03-01

The iDBPs server uses the three-dimensional (3D) structure of a query protein to predict whether it binds DNA. First, the algorithm predicts the functional region of the protein based on its evolutionary profile; the assumption is that large clusters of conserved residues are good markers of functional regions. Next, various characteristics of the predicted functional region as well as global features of the protein are calculated, such as the average surface electrostatic potential, the dipole moment and cluster-based amino acid conservation patterns. Finally, a random forests classifier is used to predict whether the query protein is likely to bind DNA and to estimate the prediction confidence. We have trained and tested the classifier on various datasets and shown that it outperformed related methods. On a dataset that reflects the fraction of DNA binding proteins (DBPs) in a proteome, the area under the ROC curve was 0.90. The application of the server to an updated version of the N-Func database, which contains proteins of unknown function with solved 3D-structure, suggested new putative DBPs for experimental studies. http://idbps.tau.ac.il/

Identification of differentially expressed genes in the zebrafish hypothalamus - pituitary axis

PubMed Central

Toro, Sabrina; Wegner, Jeremy; Muller, Marc; Westerfield, Monte; Varga, Zoltan M.

2009-01-01

The vertebrate hypothalamic-pituitary axis (HP) is the main link between the central nervous system and endocrine system. Although several signal pathways and regulatory genes have been implicated in adenohypophysis ontogenesis, little is known about hypothalamic and neurohypophysial development or when the HP matures and becomes functional. To identify markers of the HP, we constructed subtractive cDNA libraries between adult zebrafish hypothalamus and pituitary. We identified previously published genes and ESTs and novel zebrafish genes, some of which were predicted by genomic database analysis. We also analyzed expression patterns of these genes and found that several are expressed in the embryonic and larval hypothalamus, neurohypophysis, and/or adenohypophysis. Expression at these stages makes these genes useful markers to study HP maturation and function. PMID:19166982

Fluid and flexible minds: Intelligence reflects synchrony in the brain’s intrinsic network architecture

PubMed Central

Ferguson, Michael A.; Anderson, Jeffrey S.; Spreng, R. Nathan

2017-01-01

Human intelligence has been conceptualized as a complex system of dissociable cognitive processes, yet studies investigating the neural basis of intelligence have typically emphasized the contributions of discrete brain regions or, more recently, of specific networks of functionally connected regions. Here we take a broader, systems perspective in order to investigate whether intelligence is an emergent property of synchrony within the brain’s intrinsic network architecture. Using a large sample of resting-state fMRI and cognitive data (n = 830), we report that the synchrony of functional interactions within and across distributed brain networks reliably predicts fluid and flexible intellectual functioning. By adopting a whole-brain, systems-level approach, we were able to reliably predict individual differences in human intelligence by characterizing features of the brain’s intrinsic network architecture. These findings hold promise for the eventual development of neural markers to predict changes in intellectual function that are associated with neurodevelopment, normal aging, and brain disease.

Accuracy of genomic prediction in switchgrass ( Panicum virgatum L.) improved by accounting for linkage disequilibrium

DOE PAGES

Ramstein, Guillaume P.; Evans, Joseph; Kaeppler, Shawn M.; ...

2016-02-11

Switchgrass is a relatively high-yielding and environmentally sustainable biomass crop, but further genetic gains in biomass yield must be achieved to make it an economically viable bioenergy feedstock. Genomic selection (GS) is an attractive technology to generate rapid genetic gains in switchgrass, and meet the goals of a substantial displacement of petroleum use with biofuels in the near future. In this study, we empirically assessed prediction procedures for genomic selection in two different populations, consisting of 137 and 110 half-sib families of switchgrass, tested in two locations in the United States for three agronomic traits: dry matter yield, plant height,more » and heading date. Marker data were produced for the families’ parents by exome capture sequencing, generating up to 141,030 polymorphic markers with available genomic-location and annotation information. We evaluated prediction procedures that varied not only by learning schemes and prediction models, but also by the way the data were preprocessed to account for redundancy in marker information. More complex genomic prediction procedures were generally not significantly more accurate than the simplest procedure, likely due to limited population sizes. Nevertheless, a highly significant gain in prediction accuracy was achieved by transforming the marker data through a marker correlation matrix. Our results suggest that marker-data transformations and, more generally, the account of linkage disequilibrium among markers, offer valuable opportunities for improving prediction procedures in GS. Furthermore, some of the achieved prediction accuracies should motivate implementation of GS in switchgrass breeding programs.« less

Accuracy of genomic prediction in switchgrass ( Panicum virgatum L.) improved by accounting for linkage disequilibrium

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

Ramstein, Guillaume P.; Evans, Joseph; Kaeppler, Shawn M.

Switchgrass is a relatively high-yielding and environmentally sustainable biomass crop, but further genetic gains in biomass yield must be achieved to make it an economically viable bioenergy feedstock. Genomic selection (GS) is an attractive technology to generate rapid genetic gains in switchgrass, and meet the goals of a substantial displacement of petroleum use with biofuels in the near future. In this study, we empirically assessed prediction procedures for genomic selection in two different populations, consisting of 137 and 110 half-sib families of switchgrass, tested in two locations in the United States for three agronomic traits: dry matter yield, plant height,more » and heading date. Marker data were produced for the families’ parents by exome capture sequencing, generating up to 141,030 polymorphic markers with available genomic-location and annotation information. We evaluated prediction procedures that varied not only by learning schemes and prediction models, but also by the way the data were preprocessed to account for redundancy in marker information. More complex genomic prediction procedures were generally not significantly more accurate than the simplest procedure, likely due to limited population sizes. Nevertheless, a highly significant gain in prediction accuracy was achieved by transforming the marker data through a marker correlation matrix. Our results suggest that marker-data transformations and, more generally, the account of linkage disequilibrium among markers, offer valuable opportunities for improving prediction procedures in GS. Furthermore, some of the achieved prediction accuracies should motivate implementation of GS in switchgrass breeding programs.« less

Microbial Functional Gene Diversity Predicts Groundwater Contamination and Ecosystem Functioning.

PubMed

He, Zhili; Zhang, Ping; Wu, Linwei; Rocha, Andrea M; Tu, Qichao; Shi, Zhou; Wu, Bo; Qin, Yujia; Wang, Jianjun; Yan, Qingyun; Curtis, Daniel; Ning, Daliang; Van Nostrand, Joy D; Wu, Liyou; Yang, Yunfeng; Elias, Dwayne A; Watson, David B; Adams, Michael W W; Fields, Matthew W; Alm, Eric J; Hazen, Terry C; Adams, Paul D; Arkin, Adam P; Zhou, Jizhong

2018-02-20

Contamination from anthropogenic activities has significantly impacted Earth's biosphere. However, knowledge about how environmental contamination affects the biodiversity of groundwater microbiomes and ecosystem functioning remains very limited. Here, we used a comprehensive functional gene array to analyze groundwater microbiomes from 69 wells at the Oak Ridge Field Research Center (Oak Ridge, TN), representing a wide pH range and uranium, nitrate, and other contaminants. We hypothesized that the functional diversity of groundwater microbiomes would decrease as environmental contamination (e.g., uranium or nitrate) increased or at low or high pH, while some specific populations capable of utilizing or resistant to those contaminants would increase, and thus, such key microbial functional genes and/or populations could be used to predict groundwater contamination and ecosystem functioning. Our results indicated that functional richness/diversity decreased as uranium (but not nitrate) increased in groundwater. In addition, about 5.9% of specific key functional populations targeted by a comprehensive functional gene array (GeoChip 5) increased significantly ( P < 0.05) as uranium or nitrate increased, and their changes could be used to successfully predict uranium and nitrate contamination and ecosystem functioning. This study indicates great potential for using microbial functional genes to predict environmental contamination and ecosystem functioning. IMPORTANCE Disentangling the relationships between biodiversity and ecosystem functioning is an important but poorly understood topic in ecology. Predicting ecosystem functioning on the basis of biodiversity is even more difficult, particularly with microbial biomarkers. As an exploratory effort, this study used key microbial functional genes as biomarkers to provide predictive understanding of environmental contamination and ecosystem functioning. The results indicated that the overall functional gene richness/diversity decreased as uranium increased in groundwater, while specific key microbial guilds increased significantly as uranium or nitrate increased. These key microbial functional genes could be used to successfully predict environmental contamination and ecosystem functioning. This study represents a significant advance in using functional gene markers to predict the spatial distribution of environmental contaminants and ecosystem functioning toward predictive microbial ecology, which is an ultimate goal of microbial ecology. Copyright © 2018 He et al.

BFLCRM: A BAYESIAN FUNCTIONAL LINEAR COX REGRESSION MODEL FOR PREDICTING TIME TO CONVERSION TO ALZHEIMER’S DISEASE*

PubMed Central

Lee, Eunjee; Zhu, Hongtu; Kong, Dehan; Wang, Yalin; Giovanello, Kelly Sullivan; Ibrahim, Joseph G

2015-01-01

The aim of this paper is to develop a Bayesian functional linear Cox regression model (BFLCRM) with both functional and scalar covariates. This new development is motivated by establishing the likelihood of conversion to Alzheimer’s disease (AD) in 346 patients with mild cognitive impairment (MCI) enrolled in the Alzheimer’s Disease Neuroimaging Initiative 1 (ADNI-1) and the early markers of conversion. These 346 MCI patients were followed over 48 months, with 161 MCI participants progressing to AD at 48 months. The functional linear Cox regression model was used to establish that functional covariates including hippocampus surface morphology and scalar covariates including brain MRI volumes, cognitive performance (ADAS-Cog), and APOE status can accurately predict time to onset of AD. Posterior computation proceeds via an efficient Markov chain Monte Carlo algorithm. A simulation study is performed to evaluate the finite sample performance of BFLCRM. PMID:26900412

Predicting response to EGFR inhibitors in metastatic colorectal cancer: current practice and future directions.

PubMed

Shankaran, Veena; Obel, Jennifer; Benson, Al B

2010-01-01

The identification of KRAS mutational status as a predictive marker of response to antibodies against the epidermal growth factor receptor (EGFR) has been one of the most significant and practice-changing recent advances in colorectal cancer research. Recently, data suggesting a potential role for other markers (including BRAF mutations, loss of phosphatase and tension homologue deleted on chromosome ten expression, and phosphatidylinositol-3-kinase-AKT pathway mutations) in predicting response to anti-EGFR therapy have emerged. Ongoing clinical trials and correlative analyses are essential to definitively identify predictive markers and develop therapeutic strategies for patients who may not derive benefit from anti-EGFR therapy. This article reviews recent clinical trials supporting the predictive role of KRAS, recent changes to clinical guidelines and pharmaceutical labeling, investigational predictive molecular markers, and newer clinical trials targeting patients with mutated KRAS.

Comparative genome analysis of a large Dutch Legionella pneumophila strain collection identifies five markers highly correlated with clinical strains

PubMed Central

2010-01-01

Background Discrimination between clinical and environmental strains within many bacterial species is currently underexplored. Genomic analyses have clearly shown the enormous variability in genome composition between different strains of a bacterial species. In this study we have used Legionella pneumophila, the causative agent of Legionnaire's disease, to search for genomic markers related to pathogenicity. During a large surveillance study in The Netherlands well-characterized patient-derived strains and environmental strains were collected. We have used a mixed-genome microarray to perform comparative-genome analysis of 257 strains from this collection. Results Microarray analysis indicated that 480 DNA markers (out of in total 3360 markers) showed clear variation in presence between individual strains and these were therefore selected for further analysis. Unsupervised statistical analysis of these markers showed the enormous genomic variation within the species but did not show any correlation with a pathogenic phenotype. We therefore used supervised statistical analysis to identify discriminating markers. Genetic programming was used both to identify predictive markers and to define their interrelationships. A model consisting of five markers was developed that together correctly predicted 100% of the clinical strains and 69% of the environmental strains. Conclusions A novel approach for identifying predictive markers enabling discrimination between clinical and environmental isolates of L. pneumophila is presented. Out of over 3000 possible markers, five were selected that together enabled correct prediction of all the clinical strains included in this study. This novel approach for identifying predictive markers can be applied to all bacterial species, allowing for better discrimination between strains well equipped to cause human disease and relatively harmless strains. PMID:20630115

Exhaled Breath Temperature as a Novel Marker of Future Development of COPD: Results of a Follow-Up Study in Smokers.

PubMed

Labor, Marina; Vrbica, Žarko; Gudelj, Ivan; Labor, Slavica; Jurić, Iva; Plavec, Davor

2016-12-01

Although only less than one-third of smokers develop COPD, early marker(s) of COPD development are lacking. The aim of this research was to assess the ability of an average equilibrium exhaled breath temperature (EBT) in identifying susceptibility to cigarette smoke so as to predict COPD development in smokers at risk. The study was a part of a multicenter prospective cohort study in current smokers (N = 140, both sexes, 40-65 years, ≥20 pack-years) with no prior diagnosis of COPD. Diagnostic workup includes history, physical, quality of life, hematology and highly sensitive CRP, EBT before and after smoking a cigarette, lung function with bronchodilator test, and 6-minute walk test. Patients without a diagnosis of COPD and in GOLD 1 stage at initial assessment were reassessed after 2 years. COPD was additionally diagnosed based on lower level of normal (LLN) lung function criteria. Utility of EBT for disease progression was analyzed using receiver operator curve (ROC) and logistic regression analyses. Change in EBT after smoking a cigarette at initial visit (ΔEBT) was significantly predictive for disease progression (newly diagnosed COPD; newly diagnosed COPD + severity progression) after 2 years (p < 0.05 for both). ΔEBT had an AUC of 0.859 (p = 0.011) with sensitivity of 66.7% and specificity of 98.1% for newly diagnosed COPD using LLN criteria. We conclude that EBT shows potential for predicting the future development of COPD in current smokers. This was best seen using LLN to diagnose COPD, adding further evidence to question the use of GOLD criteria for diagnosing COPD.

Genomic selection in plant breeding.

PubMed

Newell, Mark A; Jannink, Jean-Luc

2014-01-01

Genomic selection (GS) is a method to predict the genetic value of selection candidates based on the genomic estimated breeding value (GEBV) predicted from high-density markers positioned throughout the genome. Unlike marker-assisted selection, the GEBV is based on all markers including both minor and major marker effects. Thus, the GEBV may capture more of the genetic variation for the particular trait under selection.

Genomic selection in plant breeding

USDA-ARS?s Scientific Manuscript database

Genomic selection (GS) is a method to predict the genetic value of selection candidates based on the genomic estimated breeding value (GEBV) predicted from high-density markers positioned throughout the genome. Unlike marker-assisted selection, the GEBV is based on all markers including both minor ...

Genome-wide association analysis of seedling root development in maize (Zea mays L.).

PubMed

Pace, Jordon; Gardner, Candice; Romay, Cinta; Ganapathysubramanian, Baskar; Lübberstedt, Thomas

2015-02-05

Plants rely on the root system for anchorage to the ground and the acquisition and absorption of nutrients critical to sustaining productivity. A genome wide association analysis enables one to analyze allelic diversity of complex traits and identify superior alleles. 384 inbred lines from the Ames panel were genotyped with 681,257 single nucleotide polymorphism markers using Genotyping-by-Sequencing technology and 22 seedling root architecture traits were phenotyped. Utilizing both a general linear model and mixed linear model, a GWAS study was conducted identifying 268 marker trait associations (p ≤ 5.3×10(-7)). Analysis of significant SNP markers for multiple traits showed that several were located within gene models with some SNP markers localized within regions of previously identified root quantitative trait loci. Gene model GRMZM2G153722 located on chromosome 4 contained nine significant markers. This predicted gene is expressed in roots and shoots. This study identifies putatively associated SNP markers associated with root traits at the seedling stage. Some SNPs were located within or near (<1 kb) gene models. These gene models identify possible candidate genes involved in root development at the seedling stage. These and respective linked or functional markers could be targets for breeders for marker assisted selection of seedling root traits.

Marker-trait association analysis of frost tolerance of 672 worldwide pea (Pisum sativum L.) collections.

PubMed

Liu, Rong; Fang, Li; Yang, Tao; Zhang, Xiaoyan; Hu, Jinguo; Zhang, Hongyan; Han, Wenliang; Hua, Zeke; Hao, Junjie; Zong, Xuxiao

2017-07-19

Frost stress is one of the major abiotic stresses causing seedling death and yield reduction in winter pea. To improve the frost tolerance of pea, field evaluation of frost tolerance was conducted on 672 diverse pea accessions at three locations in Northern China in three growing seasons from 2013 to 2016 and marker-trait association analysis of frost tolerance were performed with 267 informative SSR markers in this study. Sixteen accessions were identified as the most winter-hardy for their ability to survive in all nine field experiments with a mean survival rate of 0.57, ranging from 0.41 to 0.75. Population structure analysis revealed a structured population of two sub-populations plus some admixtures in the 672 accessions. Association analysis detected seven markers that repeatedly had associations with frost tolerance in at least two different environments with two different statistical models. One of the markers is the functional marker EST1109 on LG VI which was predicted to co-localize with a gene involved in the metabolism of glycoproteins in response to chilling stress and may provide a novel mechanism of frost tolerance in pea. These winter-hardy germplasms and frost tolerance associated markers will play a vital role in marker-assisted breeding for winter-hardy pea cultivar.

Associations between Markers of Glucose and Insulin Function and Cognitive Function in Healthy African American Elders

PubMed Central

Skinner, Jeannine S.; Morgan, Amy; Hernandez-Saucedo, Hector; Hansen, Angela; Corbett, Selena; Arbuckle, Matthew; Leverenz, James BA; Wilkins, Consuelo H.; Craft, Suzanne; Baker, Laura D.

2015-01-01

Background Glucose and insulin are important moderators of cognitive function. African Americans have poorer glycemic control across the glycemic spectrum and are at increased risk for type 2 diabetes and poor cognitive health. It is unclear which glucoregulatory markers predict cognitive function in this at-risk population. The purpose of this study was to examine the association between cognitive function and common markers of glucoregulation in non-diabetic African Americans elders. Methods Thirty-four, community-dwelling African Americans, aged 50-75 years completed cognitive testing and blood collection as part of a health screening assessment. Cognitive outcomes were composite scores derived from neuropsychological tests of executive function and verbal memory. Linear regression was used to examine relationships between cognitive composite scores and fasting blood levels of glucose, insulin, and hemoglobin A1C, with adjustments for age, education, body mass index, and antihypertensive medication use. Results Fasting plasma glucose was negatively associated with executive function (β=−0.41, p=0.03). There was a trend of an association between fasting plasma glucose and verbal memory (β=−0.34, p=0.06). Fasting insulin and hemoglobin A1c were not associated with cognitive function. Conclusion High non-diabetic fasting glucose levels were associated with poorer executive function and verbal memory. These results provide preliminary support for proactive glucose control in older African Americans even before glycemic criteria for type 2 diabetes are met. Our findings suggests that high-normal FPG levels may represent an early red-flag to signify increased risk of cognitive impairment or decline. PMID:26798567

Beyond an AFLP genome scan towards the identification of immune genes involved in plague resistance in Rattus rattus from Madagascar.

PubMed

Tollenaere, C; Jacquet, S; Ivanova, S; Loiseau, A; Duplantier, J-M; Streiff, R; Brouat, C

2013-01-01

Genome scans using amplified fragment length polymorphism (AFLP) markers became popular in nonmodel species within the last 10 years, but few studies have tried to characterize the anonymous outliers identified. This study follows on from an AFLP genome scan in the black rat (Rattus rattus), the reservoir of plague (Yersinia pestis infection) in Madagascar. We successfully sequenced 17 of the 22 markers previously shown to be potentially affected by plague-mediated selection and associated with a plague resistance phenotype. Searching these sequences in the genome of the closely related species Rattus norvegicus assigned them to 14 genomic regions, revealing a random distribution of outliers in the genome (no clustering). We compared these results with those of an in silico AFLP study of the R. norvegicus genome, which showed that outlier sequences could not have been inferred by this method in R. rattus (only four of the 15 sequences were predicted). However, in silico analysis allowed the prediction of AFLP markers distribution and the estimation of homoplasy rates, confirming its potential utility for designing AFLP studies in nonmodel species. The 14 genomic regions surrounding AFLP outliers (less than 300 kb from the marker) contained 75 genes encoding proteins of known function, including nine involved in immune function and pathogen defence. We identified the two interleukin 1 genes (Il1a and Il1b) that share homology with an antigen of Y. pestis, as the best candidates for genes subject to plague-mediated natural selection. At least six other genes known to be involved in proinflammatory pathways may also be affected by plague-mediated selection. © 2012 Blackwell Publishing Ltd.

Impact of enzyme replacement therapy on cardiac morphology and function and late enhancement in Fabry's cardiomyopathy.

PubMed

Beer, Meinrad; Weidemann, Frank; Breunig, Frank; Knoll, Anita; Koeppe, Sabrina; Machann, Wolfram; Hahn, Dietbert; Wanner, Christoph; Strotmann, Jörg; Sandstede, Jörn

2006-05-15

The present study evaluated the evolution of cardiac morphology, function, and late enhancement as a noninvasive marker of myocardial fibrosis, and their inter-relation during enzyme replacement therapy in patients with Fabry's disease using magnetic resonance imaging and color Doppler myocardial imaging. Late enhancement, which was present in up to 50% of patients, was associated with increased left ventricular mass, the failure of a significant regression of hypertrophy during enzyme replacement therapy, and worse segmental myocardial function. Late enhancement may predict the effect of enzyme replacement therapy on left ventricular mass and cardiac function.

Congenital hypogonadotropic hypogonadism, functional hypogonadotropism or constitutional delay of growth and puberty? An analysis of a large patient series from a single tertiary center.

PubMed

Varimo, Tero; Miettinen, Päivi J; Känsäkoski, Johanna; Raivio, Taneli; Hero, Matti

2017-01-01

What diagnoses underlie delayed puberty (DP) and predict its outcome? A multitude of different diagnoses underlie DP, and in boys a history of cryptorchidism, small testicular size and slow growth velocity (GV) predict its clinical course. DP is caused by a variety of underlying etiologies. Hormonal markers can be used in the differential diagnosis of DP but none of them have shown complete diagnostic accuracy. Medical records of 589 patients evaluated for DP in a single tertiary care center between 2004 and 2014 were retrospectively reviewed. Clinical and biochemical data of 174 boys and 70 girls who fulfilled the criteria of DP were included in the analyses. We characterized the frequencies of underlying conditions and evaluated the predictive efficacy of selected clinical and hormonal markers. Thirty etiologies that underlie DP were identified. No markers of clinical value could be identified in the girls, whereas a history of cryptorchidism in the boys was associated with an increase in the risk of permanent hypogonadism (odds ratio 17.2 (95% CI; 3.4-85.4, P < 0.001)). The conditions that cause functional hypogonadotropic hypogonadism were more frequent in boys with a GV below 3 cm/yr than in those growing faster (19% vs 4%, P < 0.05). In this series, the most effective markers to discriminate the prepubertal boys with constitutional delay of growth and puberty (CDGP) from those with congenital hypogonadotropic hypogonadism (CHH) were testicular volume (cut-off 1.1 ml with a sensitivity of 100% and a specificity of 91%), GnRH-induced maximal LH (cut-off 4.3 IU/L; 100%, 75%) and basal inhibin B (INHB) level (cut-off 61 ng/L; 90%, 83%). The main limitation of the study is the retrospective design. Prior cryptorchidism and slow GV are two important clinical cues that may help clinicians to predict the clinical course of DP in boys, whereas markers of similar value could not be identified in girls. In prepubertal boys, testicular size appeared as effective as INHB and GnRH-induced LH levels in the differential diagnosis between CHH and CDGP. This study was supported by the Academy of Finland (268356), Foundation for Pediatric Research (7495), Sigrid Juselius Foundation (2613) and the Finnish Medical Foundation (011115). The authors have no competing interests to report. Not applicable. © The Author 2016. Published by Oxford University Press on behalf of the European Society of Human Reproduction and Embryology. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Pareidolias in REM Sleep Behavior Disorder: A Possible Predictive Marker of Lewy Body Diseases?

PubMed

Sasai-Sakuma, Taeko; Nishio, Yoshiyuki; Yokoi, Kayoko; Mori, Etsuro; Inoue, Yuichi

2017-02-01

To investigate conditions and clinical significance of pareidolias in patients with idiopathic rapid eyemovent (REM) sleep behavior disorder (iRBD). This cross-sectional study examined 202 patients with iRBD (66.8 ± 8.0 yr, 58 female) and 46 healthy control subjects (64.7 ± 5.8 years, 14 females). They underwent the Pareidolia test, a newly developed instrument for evoking pareidolias, video polysomnography, olfactory tests, and Addenbrooke's cognitive examination-revised. Results show that 53.5% of iRBD patients exhibited one or more pareidolic responses: The rate was higher than control subjects showed (21.7%). The pictures evoking pareidolic responses were more numerous for iRBD patients than for control subjects (1.2 ± 1.8 vs. 0.4 ± 0.8, p < .001). Subgroup analyses revealed that iRBD patients with pareidolic responses had higher amounts of REM sleep without atonia (RWA), with lower sleep efficiency, lower cognitive function, and older age than subjects without pareidolic responses. Results of multivariate analyses show the number of pareidolic responses as a factor associated with decreased cognitive function in iRBD patients with better predictive accuracy. Morbidity length and severity of iRBD, olfactory function, and the amount of RWA were not factors associated with better predictive accuracy. Half or more of the iRBD patients showed pareidolic responses. The responses were proven to be associated more intimately with their cognitive decline than clinical or physiological variables related to RBD. Pareidolias in iRBD are useful as a predictive marker of future development of Lewy body diseases. © Sleep Research Society 2017. Published by Oxford University Press on behalf of the Sleep Research Society. All rights reserved. For permissions, please e-mail journals.permissions@oup.com.

Increasing the predictive accuracy of amyloid-β blood-borne biomarkers in Alzheimer's disease.

PubMed

Watt, Andrew D; Perez, Keyla A; Faux, Noel G; Pike, Kerryn E; Rowe, Christopher C; Bourgeat, Pierrick; Salvado, Olivier; Masters, Colin L; Villemagne, Victor L; Barnham, Kevin J

2011-01-01

Diagnostic measures for Alzheimer's disease (AD) commonly rely on evaluating the levels of amyloid-β (Aβ) peptides within the cerebrospinal fluid (CSF) of affected individuals. These levels are often combined with levels of an additional non-Aβ marker to increase predictive accuracy. Recent efforts to overcome the invasive nature of CSF collection led to the observation of Aβ species within the blood cellular fraction, however, little is known of what additional biomarkers may be found in this membranous fraction. The current study aimed to undertake a discovery-based proteomic investigation of the blood cellular fraction from AD patients (n = 18) and healthy controls (HC; n = 15) using copper immobilized metal affinity capture and Surface Enhanced Laser Desorption/Ionisation Time-Of-Flight Mass Spectrometry. Three candidate biomarkers were observed which could differentiate AD patients from HC (ROC AUC > 0.8). Bivariate pairwise comparisons revealed significant correlations between these markers and measures of AD severity including; MMSE, composite memory, brain amyloid burden, and hippocampal volume. A partial least squares regression model was generated using the three candidate markers along with blood levels of Aβ. This model was able to distinguish AD from HC with high specificity (90%) and sensitivity (77%) and was able to separate individuals with mild cognitive impairment (MCI) who converted to AD from MCI non-converters. While requiring further characterization, these candidate biomarkers reaffirm the potential efficacy of blood-based investigations into neurodegenerative conditions. Furthermore, the findings indicate that the incorporation of non-amyloid markers into predictive models, function to increase the accuracy of the diagnostic potential of Aβ.

Evidence for a Cystic Fibrosis Enteropathy

PubMed Central

Adriaanse, Marlou P. M.; van der Sande, Linda J. T. M.; van den Neucker, Anita M.; Menheere, Paul P. C. A.; Dompeling, Edward; Buurman, Wim A.; Vreugdenhil, Anita C. E.

2015-01-01

Background Previous studies have suggested the existence of enteropathy in cystic fibrosis (CF), which may contribute to intestinal function impairment, a poor nutritional status and decline in lung function. This study evaluated enterocyte damage and intestinal inflammation in CF and studied its associations with nutritional status, CF-related morbidities such as impaired lung function and diabetes, and medication use. Methods Sixty-eight CF patients and 107 controls were studied. Levels of serum intestinal-fatty acid binding protein (I-FABP), a specific marker for enterocyte damage, were retrospectively determined. The faecal intestinal inflammation marker calprotectin was prospectively studied. Nutritional status, lung function (FEV1), exocrine pancreatic insufficiency (EPI), CF-related diabetes (CFRD) and use of proton pump inhibitors (PPI) were obtained from the medical charts. Results Serum I-FABP levels were elevated in CF patients as compared with controls (p<0.001), and correlated negatively with FEV1 predicted value in children (r-.734, p<0.05). Faecal calprotectin level was elevated in 93% of CF patients, and correlated negatively with FEV1 predicted value in adults (r-.484, p<0.05). No correlation was found between calprotectin levels in faeces and sputum. Faecal calprotectin level was significantly associated with the presence of CFRD, EPI, and PPI use. Conclusion This study demonstrated enterocyte damage and intestinal inflammation in CF patients, and provides evidence for an inverse correlation between enteropathy and lung function. The presented associations of enteropathy with important CF-related morbidities further emphasize the clinical relevance. PMID:26484665

Review of functional markers for improving cooking, eating, and the nutritional qualities of rice

PubMed Central

Lau, Wendy C. P.; Rafii, Mohd Y.; Ismail, Mohd R.; Puteh, Adam; Latif, Mohammad A.; Ramli, Asfaliza

2015-01-01

After yield, quality is one of the most important aspects of rice breeding. Preference for rice quality varies among cultures and regions; therefore, rice breeders have to tailor the quality according to the preferences of local consumers. Rice quality assessment requires routine chemical analysis procedures. The advancement of molecular marker technology has revolutionized the strategy in breeding programs. The availability of rice genome sequences and the use of forward and reverse genetics approaches facilitate gene discovery and the deciphering of gene functions. A well-characterized gene is the basis for the development of functional markers, which play an important role in plant genotyping and, in particular, marker-assisted breeding. In addition, functional markers offer advantages that counteract the limitations of random DNA markers. Some functional markers have been applied in marker-assisted breeding programs and have successfully improved rice quality to meet local consumers’ preferences. Although functional markers offer a plethora of advantages over random genetic markers, the development and application of functional markers should be conducted with care. The decreasing cost of sequencing will enable more functional markers for rice quality improvement to be developed, and application of these markers in rice quality breeding programs is highly anticipated. PMID:26528304

[Non-small cell lung cancer. Subtyping and predictive molecular marker investigations in cytology].

PubMed

Savic, S; Bihl, M P; Bubendorf, L

2012-07-01

The diagnosis and treatment of non-small cell lung cancer (NSCLC) have been revolutionized over the last few years. Requirements for cytopathologists in lung cancer diagnosis have therefore changed. The general diagnostic category of NSLC is no longer sufficient. In addition cytological specimens need to be evaluated for adequacy regarding predictive marker analyses. Accurate NSCLC subtyping with a distinction of adenocarcinoma from squamous cell carcinoma is crucial for treatment decisions as the subtype will decide on the chemotherapy regimen and the choice of predictive marker analyses for targeted treatment. In the majority of cases, the subtype can be diagnosed by morphology alone. Cytology is equally well suited as biopsy specimens for the assessment of molecular predictive markers. The best results are achieved when both cytology and biopsy specimens are compared to choose the most appropriate specimen for morphological subtyping and molecular testing. In this paper, we discuss special issues of NSCLC subtyping and currently recommended predictive molecular marker analyses.

Associations between a neurophysiological marker of central cholinergic activity and cognitive functions in young and older adults

PubMed Central

2012-01-01

Background The deterioration of the central cholinergic system in aging is hypothesized to underlie declines in several cognitive domains, including memory and executive functions. However, there is surprisingly little direct evidence regarding acetylcholine’s specific role(s) in normal human cognitive aging. Methods We used short-latency afferent inhibition (SAI) with transcranial magnetic stimulation (TMS) as a putative marker of cholinergic activity in vivo in young (n = 24) and older adults (n = 31). Results We found a significant age difference in SAI, concordant with other evidence of cholinergic decline in normal aging. We also found clear age differences on several of the memory and one of the executive function measures. Individual differences in SAI levels predicted memory but not executive functions. Conclusion Individual differences in SAI levels were better predictors of memory than executive functions. We discuss cases in which the relations between SAI and cognition might be even stronger, and refer to other age-related biological changes that may interact with cholinergic activity in cognitive aging. PMID:22537877

Genetic diversity and trait genomic prediction in a pea diversity panel.

PubMed

Burstin, Judith; Salloignon, Pauline; Chabert-Martinello, Marianne; Magnin-Robert, Jean-Bernard; Siol, Mathieu; Jacquin, Françoise; Chauveau, Aurélie; Pont, Caroline; Aubert, Grégoire; Delaitre, Catherine; Truntzer, Caroline; Duc, Gérard

2015-02-21

Pea (Pisum sativum L.), a major pulse crop grown for its protein-rich seeds, is an important component of agroecological cropping systems in diverse regions of the world. New breeding challenges imposed by global climate change and new regulations urge pea breeders to undertake more efficient methods of selection and better take advantage of the large genetic diversity present in the Pisum sativum genepool. Diversity studies conducted so far in pea used Simple Sequence Repeat (SSR) and Retrotransposon Based Insertion Polymorphism (RBIP) markers. Recently, SNP marker panels have been developed that will be useful for genetic diversity assessment and marker-assisted selection. A collection of diverse pea accessions, including landraces and cultivars of garden, field or fodder peas as well as wild peas was characterised at the molecular level using newly developed SNP markers, as well as SSR markers and RBIP markers. The three types of markers were used to describe the structure of the collection and revealed different pictures of the genetic diversity among the collection. SSR showed the fastest rate of evolution and RBIP the slowest rate of evolution, pointing to their contrasted mode of evolution. SNP markers were then used to predict phenotypes -the date of flowering (BegFlo), the number of seeds per plant (Nseed) and thousand seed weight (TSW)- that were recorded for the collection. Different statistical methods were tested including the LASSO (Least Absolute Shrinkage ans Selection Operator), PLS (Partial Least Squares), SPLS (Sparse Partial Least Squares), Bayes A, Bayes B and GBLUP (Genomic Best Linear Unbiased Prediction) methods and the structure of the collection was taken into account in the prediction. Despite a limited number of 331 markers used for prediction, TSW was reliably predicted. The development of marker assisted selection has not reached its full potential in pea until now. This paper shows that the high-throughput SNP arrays that are being developed will most probably allow for a more efficient selection in this species.

Immunohistochemistry predictive markers for primary colorectal cancer tumors: where are we and where are we going?

PubMed

Bărbălan, Alexandru; Nicolaescu, Andrei Cristian; Măgăran, Antoanela Valentina; Mercuţ, Răzvan; Bălăşoiu, Maria; Băncescu, Gabriela; Şerbănescu, Mircea Sebastian; Lazăr, Octavian Fulger; Săftoiu, Adrian

2018-01-01

The aim of our study is to highlight and organize the recently published immunohistochemistry (IHC) predictive biomarkers of primary colorectal cancers (CRCs) that could lead to practical implementation. We reviewed articles that examined CRC samples with significant statistic correlation between the IHC marker expression and disease progression over time, relationships with the available clinical features and those who detect the prognosis of drug effects. Our analysis showed that nine markers could correlate with medical treatment response of CRCs in different stages. When using better overall survival (OS) and better disease-free survival (DFS) as a grouping factor, there were 14 markers that could be used in assessing CRC prognosis. By using poor prognostic for the OS and the DFS as a grouping factor, we found 43 markers. Subgroup analysis was also performed based on the 32 markers recently confirmed to predict metastasis evolution or the recurrence risks. Venous invasion could be predictable for tumors, statistically significant metastasis susceptibility was observed for markers and also the capacity to evaluate recurrence. CRCs integrate a variety of localizations and there are proofs that distinguish the sites of tumors. The studies reporting data specifically for rectal cancer separating it from colon cancer contained seven IHC markers. In order to be able to implement a predictive biomarker in clinical practice, it must comply with certain criteria as clinical value and analytical proof. Unique biological signature of CRC can be distinguished by identifying biomarkers expression. Several markers have shown potential, but the majority still need to render clinical utility.

Molecular alterations and biomarkers in colorectal cancer

PubMed Central

Grady, William M.; Pritchard, Colin C.

2013-01-01

The promise of precision medicine is now a clinical reality. Advances in our understanding of the molecular genetics of colorectal cancer genetics is leading to the development of a variety of biomarkers that are being used as early detection markers, prognostic markers, and markers for predicting treatment responses. This is no more evident than in the recent advances in testing colorectal cancers for specific molecular alterations in order to guide treatment with the monoclonal antibody therapies cetuximab and panitumumab, which target the epidermal growth factor receptor (EGFR). In this review, we update a prior review published in 2010 and describe our current understanding of the molecular pathogenesis of colorectal cancer and how these alterations relate to emerging biomarkers for early detection and risk stratification (diagnostic markers), prognosis (prognostic markers), and the prediction of treatment responses (predictive markers). PMID:24178577

[Studies of marker screening efficiency and corresponding influencing factors in QTL composite interval mapping].

PubMed

Gao, Yong-Ming; Wan, Ping

2002-06-01

Screening markers efficiently is the foundation of mapping QTLs by composite interval mapping. Main and interaction markers distinguished, besides using background control for genetic variation, could also be used to construct intervals of two-way searching for mapping QTLs with epistasis, which can save a lot of calculation time. Therefore, the efficiency of marker screening would affect power and precision of QTL mapping. A doubled haploid population with 200 individuals and 5 chromosomes was constructed, with 50 markers evenly distributed at 10 cM space. Among a total of 6 QTLs, one was placed on chromosome I, two linked on chromosome II, and the other three linked on chromosome IV. QTL setting included additive effects and epistatic effects of additive x additive, the corresponding QTL interaction effects were set if data were collected under multiple environments. The heritability was assumed to be 0.5 if no special declaration. The power of marker screening by stepwise regression, forward regression, and three methods for random effect prediction, e.g. best linear unbiased prediction (BLUP), linear unbiased prediction (LUP) and adjusted unbiased prediction (AUP), was studied and compared through 100 Monte Carlo simulations. The results indicated that the marker screening power by stepwise regression at 0.1, 0.05 and 0.01 significant level changed from 2% to 68%, the power changed from 2% to 72% by forward regression. The larger the QTL effects, the higher the marker screening power. While the power of marker screening by three random effect prediction was very low, the maximum was only 13%. That suggested that regression methods were much better than those by using the approaches of random effect prediction to identify efficient markers flanking QTLs, and forward selection method was more simple and efficient. The results of simulation study on heritability showed that heightening of both general heritability and interaction heritability of genotype x environments could enhance marker screening power, the former had a greater influence on QTLs with larger main and/or epistatic effects, while the later on QTLs with small main and/or epistatic effects. The simulation of 100 times was also conducted to study the influence of different marker number and density on marker screening power. It is indicated that the marker screening power would decrease if there were too many markers, especially with high density in a mapping population, which suggested that a mapping population with definite individuals could only hold limited markers. According to the simulation study, the reasonable number of markers should not be more than individuals. The simulation study of marker screening under multiple environments showed high total power of marker screening. In order to relieve the problem that marker screening power restricted the efficiency of QTL mapping, markers identified in multiple environments could be used to construct two search intervals.

Identification of genetic variants predictive of early onset pancreatic cancer through a population science analysis of functional genomic datasets

PubMed Central

Chen, Jinyun; Wu, Xifeng; Huang, Yujing; Chen, Wei; Brand, Randall E.; Killary, Ann M.; Sen, Subrata; Frazier, Marsha L.

2016-01-01

Biomarkers are critically needed for the early detection of pancreatic cancer (PC) are urgently needed. Our purpose was to identify a panel of genetic variants that, combined, can predict increased risk for early-onset PC and thereby identify individuals who should begin screening at an early age. Previously, we identified genes using a functional genomic approach that were aberrantly expressed in early pathways to PC tumorigenesis. We now report the discovery of single nucleotide polymorphisms (SNPs) in these genes associated with early age at diagnosis of PC using a two-phase study design. In silico and bioinformatics tools were used to examine functional relevance of the identified SNPs. Eight SNPs were consistently associated with age at diagnosis in the discovery phase, validation phase and pooled analysis. Further analysis of the joint effects of these 8 SNPs showed that, compared to participants carrying none of these unfavorable genotypes (median age at PC diagnosis 70 years), those carrying 1–2, 3–4, or 5 or more unfavorable genotypes had median ages at diagnosis of 64, 63, and 62 years, respectively (P = 3.0E–04). A gene-dosage effect was observed, with age at diagnosis inversely related to number of unfavorable genotypes (Ptrend = 1.0E–04). Using bioinformatics tools, we found that all of the 8 SNPs were predicted to play functional roles in the disruption of transcription factor and/or enhancer binding sites and most of them were expression quantitative trait loci (eQTL) of the target genes. The panel of genetic markers identified may serve as susceptibility markers for earlier PC diagnosis. PMID:27486767

Sex specific differences in the predictive value of cholesterol homeostasis markers and 10-Year CVD event rate in Framingham Offspring Study participants

USDA-ARS?s Scientific Manuscript database

Available data are inconsistent on factors influencing plasma cholesterol homeostasis marker concentrations and their value in predicting subsequent cardiovascular disease (CVD) events. To address this issue the relationship between markers of cholesterol absorption (campesterol, sitosterol, cholest...

Metaphylogenomic and potential functionality of the limpet Patella pellucida's gastrointestinal tract microbiome.

PubMed

Dudek, Magda; Adams, Jessica; Swain, Martin; Hegarty, Matthew; Huws, Sharon; Gallagher, Joe

2014-10-20

This study investigated the microbial diversity associated with the digestive tract of the seaweed grazing marine limpet Patella pellucida. Using a modified indirect DNA extraction protocol and performing metagenomic profiling based on specific prokaryotic marker genes, the abundance of bacterial groups was identified from the analyzed metagenome. The members of three significantly abundant phyla of Proteobacteria, Firmicutes and Bacteroidetes were characterized through the literature and their predicted functions towards the host, as well as potential applications in the industrial environment assessed.

Predicting Quantitative Traits With Regression Models for Dense Molecular Markers and Pedigree

PubMed Central

de los Campos, Gustavo; Naya, Hugo; Gianola, Daniel; Crossa, José; Legarra, Andrés; Manfredi, Eduardo; Weigel, Kent; Cotes, José Miguel

2009-01-01

The availability of genomewide dense markers brings opportunities and challenges to breeding programs. An important question concerns the ways in which dense markers and pedigrees, together with phenotypic records, should be used to arrive at predictions of genetic values for complex traits. If a large number of markers are included in a regression model, marker-specific shrinkage of regression coefficients may be needed. For this reason, the Bayesian least absolute shrinkage and selection operator (LASSO) (BL) appears to be an interesting approach for fitting marker effects in a regression model. This article adapts the BL to arrive at a regression model where markers, pedigrees, and covariates other than markers are considered jointly. Connections between BL and other marker-based regression models are discussed, and the sensitivity of BL with respect to the choice of prior distributions assigned to key parameters is evaluated using simulation. The proposed model was fitted to two data sets from wheat and mouse populations, and evaluated using cross-validation methods. Results indicate that inclusion of markers in the regression further improved the predictive ability of models. An R program that implements the proposed model is freely available. PMID:19293140

Identification of novel serum autoantibodies against EID3 in non-functional pancreatic neuroendocrine tumors

PubMed Central

Hontani, Koji; Tsuchikawa, Takahiro; Hiwasa, Takaki; Nakamura, Toru; Ueno, Takashi; Kushibiki, Toshihiro; Takahashi, Mizuna; Inoko, Kazuho; Takano, Hironobu; Takeuchi, Satoshi; Dosaka-Akita, Hirotoshi; Kuwatani, Masaki; Sakamoto, Naoya; Hatanaka, Yutaka; Mitsuhashi, Tomoko; Shimada, Hideaki; Shichinohe, Toshiaki; Hirano, Satoshi

2017-01-01

Pancreatic neuroendocrine tumors (pNETs) are relatively rare heterogenous tumors, comprising only 1–2% of all pancreatic neoplasms. The majority of pNETs are non-functional tumors (NF-pNETs) that do not produce hormones, and as such, do not cause any hormone-related symptoms. As a result, these tumors are often diagnosed at an advanced stage because patients do not present with specific symptoms. Although tumor markers are used to help diagnosis and predict some types of cancers, chromogranin A, a widely used tumor marker of pNETs, has significant limitations. To identify novel NF-pNET-associated antigens, we performed serological identification of antigens by recombinant cDNA expression cloning (SEREX) and identified five tumor antigens (phosphatase and tensin homolog, EP300-interacting inhibitor of differentiation 3 [EID3], EH domain-containing protein 1, galactoside-binding soluble 9, and BRCA1-associated protein). Further analysis using the AlphaLISA® immunoassay to compare serum antibody levels revealed that antibody levels against the EID3 antigen was significantly higher in the patient group than in the healthy donor group (n = 25, both groups). In addition, higher serum anti-EID3 antibody levels in NF-pNET patients correlated with shorter disease-free survival. The AUC calculated by ROC analysis was 0.784 with moderate diagnostic accuracy. In conclusion, serum anti-EID3 antibody levels may be useful as a tumor marker for prediction of tumor recurrence in NF-pNETs. PMID:29290942

Inflammatory and Other Biomarkers: Role in Pathophysiology and Prediction of Gestational Diabetes Mellitus

PubMed Central

Abell, Sally K.; De Courten, Barbora; Boyle, Jacqueline A.; Teede, Helena J.

2015-01-01

Understanding pathophysiology and identifying mothers at risk of major pregnancy complications is vital to effective prevention and optimal management. However, in current antenatal care, understanding of pathophysiology of complications is limited. In gestational diabetes mellitus (GDM), risk prediction is mostly based on maternal history and clinical risk factors and may not optimally identify high risk pregnancies. Hence, universal screening is widely recommended. Here, we will explore the literature on GDM and biomarkers including inflammatory markers, adipokines, endothelial function and lipids to advance understanding of pathophysiology and explore risk prediction, with a goal to guide prevention and treatment of GDM. PMID:26110385

iDBPs: a web server for the identification of DNA binding proteins

PubMed Central

Nimrod, Guy; Schushan, Maya; Szilágyi, András; Leslie, Christina; Ben-Tal, Nir

2010-01-01

Summary: The iDBPs server uses the three-dimensional (3D) structure of a query protein to predict whether it binds DNA. First, the algorithm predicts the functional region of the protein based on its evolutionary profile; the assumption is that large clusters of conserved residues are good markers of functional regions. Next, various characteristics of the predicted functional region as well as global features of the protein are calculated, such as the average surface electrostatic potential, the dipole moment and cluster-based amino acid conservation patterns. Finally, a random forests classifier is used to predict whether the query protein is likely to bind DNA and to estimate the prediction confidence. We have trained and tested the classifier on various datasets and shown that it outperformed related methods. On a dataset that reflects the fraction of DNA binding proteins (DBPs) in a proteome, the area under the ROC curve was 0.90. The application of the server to an updated version of the N-Func database, which contains proteins of unknown function with solved 3D-structure, suggested new putative DBPs for experimental studies. Availability: http://idbps.tau.ac.il/ Contact: NirB@tauex.tau.ac.il Supplementary information: Supplementary data are available at Bioinformatics online. PMID:20089514

Emotion suppression moderates the quadratic association between RSA and executive function

PubMed Central

Spangler, Derek P.; Bell, Martha Ann; Deater-Deckard, Kirby

2016-01-01

There is uncertainty about whether respiratory sinus arrhythmia (RSA), a cardiac marker of adaptive emotion regulation, is involved in relatively low or high executive function performance. In the present study, we investigated: (1) whether RSA during rest and tasks predict both relatively low and high executive function within a larger quadratic association among the two variables, and (2) the extent to which this quadratic trend was moderated by individual differences in emotion regulation. To achieve these aims, a sample of ethnically and socioeconomically diverse women self-reported reappraisal and emotion suppression. They next experienced a two-minute resting period during which ECG was continually assessed. In the next phase, the women completed an array of executive function and non-executive cognitive tasks while ECG was measured throughout. As anticipated, resting RSA showed a quadratic association with executive function that was strongest for high suppression. These results suggest that relatively high resting RSA may predict poor executive function ability when emotion regulation consumes executive control resources needed for ongoing cognitive performance. PMID:26018941

Early Prognostication Markers in Cardiac Arrest Patients Treated with Hypothermia

PubMed Central

Karapetkova, Maria; Koenig, Matthew A.; Jia, Xiaofeng

2015-01-01

Background and purpose Established prognostication markers, such as clinical findings, electroencephalography (EEG), and biochemical markers, used by clinicians to predict neurologic outcome after cardiac arrest (CA) are altered under therapeutic hypothermia (TH) conditions and their validity remains uncertain. Methods MEDLINE and EMBASE were searched for evidence on the current standards for neurologic outcome prediction for out-of-hospital CA patients treated with TH and the validity of a wide range of prognostication markers. Relevant studies that suggested one or several established biomarkers, and multimodal approaches for prognostication were included and reviewed. Results While the prognostic accuracy of various tests has been questioned after TH, pupillary light reflexes and somatosensory evoked potentials (SSEP) are still strongly associated with negative outcome for early prognostication. Increasingly, EEG background activity has also been identified as a valid predictor for outcome after 72 hours after CA and a preferred prognostic method in clinical settings. Neuroimaging techniques, such as MRI and CT, can identify functional and structural brain injury, but are not readily available at the patient’s bedside because of limited availability and high costs. Conclusions A multimodal algorithm composed of neurological examination, EEG-based quantitative testing, and SSEP, in conjunction with newer MRI sequences, if available, holds promise for accurate prognostication in CA patients treated with TH. In order to avoid premature withdrawal of care, prognostication should be performed later than 72 hours after CA. PMID:26228521

Early prognostication markers in cardiac arrest patients treated with hypothermia.

PubMed

Karapetkova, M; Koenig, M A; Jia, X

2016-03-01

Established prognostication markers, such as clinical findings, electroencephalography (EEG) and biochemical markers, used by clinicians to predict neurological outcome after cardiac arrest (CA) are altered under therapeutic hypothermia (TH) conditions and their validity remains uncertain. MEDLINE and Embase were searched for evidence on the current standards for neurological outcome prediction for out-of-hospital CA patients treated with TH and the validity of a wide range of prognostication markers. Relevant studies that suggested one or several established biomarkers and multimodal approaches for prognostication are included and reviewed. Whilst the prognostic accuracy of various tests after TH has been questioned, pupillary light reflexes and somatosensory evoked potentials are still strongly associated with negative outcome for early prognostication. Increasingly, EEG background activity has also been identified as a valid predictor for outcome after 72 h after CA and a preferred prognostic method in clinical settings. Neuroimaging techniques, such as magnetic resonance imaging and computed tomography, can identify functional and structural brain injury but are not readily available at the patient's bedside because of limited availability and high costs. A multimodal algorithm composed of neurological examination, EEG-based quantitative testing and somatosensory evoked potentials, in conjunction with newer magnetic resonance imaging sequences, if available, holds promise for accurate prognostication in CA patients treated with TH. In order to avoid premature withdrawal of care, prognostication should be performed more than 72 h after CA. © 2015 EAN.

Transcriptome Sequencing, and Rapid Development and Application of SNP Markers for the Legume Pod Borer Maruca vitrata (Lepidoptera: Crambidae)

PubMed Central

Margam, Venu M.; Coates, Brad S.; Bayles, Darrell O.; Hellmich, Richard L.; Agunbiade, Tolulope; Seufferheld, Manfredo J.; Sun, Weilin; Kroemer, Jeremy A.; Ba, Malick N.; Binso-Dabire, Clementine L.; Baoua, Ibrahim; Ishiyaku, Mohammad F.; Covas, Fernando G.; Srinivasan, Ramasamy; Armstrong, Joel; Murdock, Larry L.; Pittendrigh, Barry R.

2011-01-01

The legume pod borer, Maruca vitrata (Lepidoptera: Crambidae), is an insect pest species of crops grown by subsistence farmers in tropical regions of Africa. We present the de novo assembly of 3729 contigs from 454- and Sanger-derived sequencing reads for midgut, salivary, and whole adult tissues of this non-model species. Functional annotation predicted that 1320 M. vitrata protein coding genes are present, of which 631 have orthologs within the Bombyx mori gene model. A homology-based analysis assigned M. vitrata genes into a group of paralogs, but these were subsequently partitioned into putative orthologs following phylogenetic analyses. Following sequence quality filtering, a total of 1542 putative single nucleotide polymorphisms (SNPs) were predicted within M. vitrata contig assemblies. Seventy one of 1078 designed molecular genetic markers were used to screen M. vitrata samples from five collection sites in West Africa. Population substructure may be present with significant implications in the insect resistance management recommendations pertaining to the release of biological control agents or transgenic cowpea that express Bacillus thuringiensis crystal toxins. Mutation data derived from transcriptome sequencing is an expeditious and economical source for genetic markers that allow evaluation of ecological differentiation. PMID:21754987

Biochemical markers of acute limb ischemia, rhabdomyolysis, and impact on limb salvage.

PubMed

Watson, J Devin B; Gifford, Shaun M; Clouse, W Darrin

2014-12-01

Biochemical markers of ischemia reperfusion injury have been of interest to vascular surgeons and researchers for many years. Acute limb ischemia is the quintessential clinical scenario where these markers would seem relevant. The use of biomarkers to preoperatively or perioperatively predict which patients will not tolerate limb-salvage efforts or who will have poor functional outcomes after salvage is of immense interest. Creatinine phosphokinase, myoglobin, lactate, lactate dehydrogenase, potassium, bicarbonate, and neutrophil/leukocyte ratios are a few of the studied biomarkers available. Currently, the most well-studied aspect of ischemia reperfusion injury is rhabdomyolysis leading to acute kidney injury. The last 10 years have seen significant progression and improvement in the treatment of rhabdomyolysis, from minor supportive care to use of continuous renal replacement therapy. Identification of specific biomarkers with predictive outcome characteristics in the setting of ischemia reperfusion injury will help guide therapeutic development and potentially mitigate pathophysiologic changes in acute limb ischemia, including rhabdomyolysis. These may further lead to improvements in short- and long-term surgical outcomes and limb salvage, as well as a better understanding of the timing and selection of intervention. Copyright © 2015 Elsevier Inc. All rights reserved.

How to interpret a small increase in AUC with an additional risk prediction marker: decision analysis comes through.

PubMed

Baker, Stuart G; Schuit, Ewoud; Steyerberg, Ewout W; Pencina, Michael J; Vickers, Andrew; Vickers, Andew; Moons, Karel G M; Mol, Ben W J; Lindeman, Karen S

2014-09-28

An important question in the evaluation of an additional risk prediction marker is how to interpret a small increase in the area under the receiver operating characteristic curve (AUC). Many researchers believe that a change in AUC is a poor metric because it increases only slightly with the addition of a marker with a large odds ratio. Because it is not possible on purely statistical grounds to choose between the odds ratio and AUC, we invoke decision analysis, which incorporates costs and benefits. For example, a timely estimate of the risk of later non-elective operative delivery can help a woman in labor decide if she wants an early elective cesarean section to avoid greater complications from possible later non-elective operative delivery. A basic risk prediction model for later non-elective operative delivery involves only antepartum markers. Because adding intrapartum markers to this risk prediction model increases AUC by 0.02, we questioned whether this small improvement is worthwhile. A key decision-analytic quantity is the risk threshold, here the risk of later non-elective operative delivery at which a patient would be indifferent between an early elective cesarean section and usual care. For a range of risk thresholds, we found that an increase in the net benefit of risk prediction requires collecting intrapartum marker data on 68 to 124 women for every correct prediction of later non-elective operative delivery. Because data collection is non-invasive, this test tradeoff of 68 to 124 is clinically acceptable, indicating the value of adding intrapartum markers to the risk prediction model. Copyright © 2014 John Wiley & Sons, Ltd.

Differences between suicide attempters and non-attempters in depressed older patients: Depression severity, white matter lesions, and cognitive functioning

PubMed Central

Sachs-Ericsson, Natalie; Hames, Jennifer L.; Joiner, Thomas E.; Corsentino, Elizabeth; Rushing, Nicole C.; Palmer, Emily; Gotlib, Ian H.; Selby, Edward A.; Zarit, Steven; Steffens, David C.

2012-01-01

Objectives Older adults with major depressive disorder (MDD) have the highest population-rate of suicide. White matter brain lesions (WML) are a potential biological marker for suicidality in young and middle-age adults and are correlated with cognitive impairment (CI) in older adults. In the current study of older patients with MDD, we examined 1) if a history of suicide attempts was associated with a more severe course of MDD; 2) if WML are a biological marker for suicide; and 3) if suicide attempt history is associated with CI mediated by WML. Setting Data from the Neurocognitive Outcomes of Depression in the Elderly. Participants Depressed patients (60+) who had ever attempted suicide (n=23) were compared to depressed patients (60+) who had not attempted suicide (n=223). Measurements Baseline and follow-up assessments were obtained for depressive symptoms (every 3 months) and cognitive functioning (every six months) over two years. Three MRI scans were conducted. Results At baseline, suicide attempters reported more severe past and present symptoms (e.g., depressive symptoms, current suicidal thoughts, psychotic symptoms, earlier age of onset, and more lifetime episodes) than non-attempters. Suicide attempters had more left WML at baseline, and suicide attempt history predicted a greater growth in both left and right WML. WML predicted cognitive decline; nonetheless, history of suicide attempt was unrelated to cognitive functioning. Conclusions Severity of depressive symptoms and WML are associated with suicide attempts in geriatric depressed patients. Suicide attempts predicted neurological changes, which may contribute to poorer long-term outcomes in elder attempters. PMID:23933424

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

USDA-ARS?s Scientific Manuscript database

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

C-reactive protein and other markers of inflammation in hemodialysis patients

PubMed Central

Heidari, Behzad

2013-01-01

Hemodialysis patients are at greater risk of cardiovascular disease. Higher than expected cardiovascular morbidity and mortality in this population has been attributed to dislipidemia as well as inflammation. The causes of inflammation in hemodialysis patients are multifactorial. Several markers were used for the detection of inflammatory reaction in patients with chronic renal disease. These markers can be used for the prediction of future cardiovascular events. Among the several parameters of inflammatory markers, serum, CRP is well known and its advantages for the detection of inflammation and its predictor ability has been evaluated in several studies. This review addressed the associated factors and markers of inflammation in hemodialysis patients. In addition, their ability in predicting future atherosclerosis and effect of treatment has been reviewed. However, this context particularly in using CRP as a prediction marker of inflammation and morbidity requires further studies. PMID:24009946

C-reactive protein and other markers of inflammation in hemodialysis patients.

PubMed

Heidari, Behzad

2013-01-01

Hemodialysis patients are at greater risk of cardiovascular disease. Higher than expected cardiovascular morbidity and mortality in this population has been attributed to dislipidemia as well as inflammation. The causes of inflammation in hemodialysis patients are multifactorial. Several markers were used for the detection of inflammatory reaction in patients with chronic renal disease. These markers can be used for the prediction of future cardiovascular events. Among the several parameters of inflammatory markers, serum, CRP is well known and its advantages for the detection of inflammation and its predictor ability has been evaluated in several studies. This review addressed the associated factors and markers of inflammation in hemodialysis patients. In addition, their ability in predicting future atherosclerosis and effect of treatment has been reviewed. However, this context particularly in using CRP as a prediction marker of inflammation and morbidity requires further studies.

HoloVir: A Workflow for Investigating the Diversity and Function of Viruses in Invertebrate Holobionts

PubMed Central

Laffy, Patrick W.; Wood-Charlson, Elisha M.; Turaev, Dmitrij; Weynberg, Karen D.; Botté, Emmanuelle S.; van Oppen, Madeleine J. H.; Webster, Nicole S.; Rattei, Thomas

2016-01-01

Abundant bioinformatics resources are available for the study of complex microbial metagenomes, however their utility in viral metagenomics is limited. HoloVir is a robust and flexible data analysis pipeline that provides an optimized and validated workflow for taxonomic and functional characterization of viral metagenomes derived from invertebrate holobionts. Simulated viral metagenomes comprising varying levels of viral diversity and abundance were used to determine the optimal assembly and gene prediction strategy, and multiple sequence assembly methods and gene prediction tools were tested in order to optimize our analysis workflow. HoloVir performs pairwise comparisons of single read and predicted gene datasets against the viral RefSeq database to assign taxonomy and additional comparison to phage-specific and cellular markers is undertaken to support the taxonomic assignments and identify potential cellular contamination. Broad functional classification of the predicted genes is provided by assignment of COG microbial functional category classifications using EggNOG and higher resolution functional analysis is achieved by searching for enrichment of specific Swiss-Prot keywords within the viral metagenome. Application of HoloVir to viral metagenomes from the coral Pocillopora damicornis and the sponge Rhopaloeides odorabile demonstrated that HoloVir provides a valuable tool to characterize holobiont viral communities across species, environments, or experiments. PMID:27375564

A and MdMYB1 allele-specific markers controlling apple (Malus x domestica Borkh.) skin color and suitability for marker-assisted selection.

PubMed

Zhang, X J; Wang, L X; Chen, X X; Liu, Y L; Meng, R; Wang, Y J; Zhao, Z Y

2014-10-31

Pre-selection for fruit skin color at the seedling stage would be highly advantageous, with marker-assisted selection offering a potential method for apple pre-selection. A and MdMYB1 alleles are allele-specific DNA markers that are potentially associated with apple skin color, and co-segregate with the Rf and Rni loci, respectively. Here, we assessed the potential application of these 2 alleles for marker-assisted breeding across 30 diverse cultivars and 2 apple seedling progenies. The red skin color phenotype was usually associated with the MdMYB1-1 allele and A(1) allele, respectively, while the 2 molecular markers provided approximately 91% predictability in the 'Fuji' x 'Cripps Pink' and 'Fuji' x 'Gala' progenies. The results obtained from the 30 cultivars and 2 progenies were consistent for the 2 molecular markers. Hence, the results supported that Rf and Rni could be located in a gene cluster, or even correspond to alleles of the same gene. Our results are consistent with the hypothesis that red/yellow dimorphism is controlled by a monogenic system, with the presence of the red anthocyanin pigmentation being dominant. In addition, our results supported that the practical utilization of the 2 function markers to efficiently and accurately select red-skinned apple cultivars in apple scion breeding programs.

Risk Classification with an Adaptive Naive Bayes Kernel Machine Model.

PubMed

Minnier, Jessica; Yuan, Ming; Liu, Jun S; Cai, Tianxi

2015-04-22

Genetic studies of complex traits have uncovered only a small number of risk markers explaining a small fraction of heritability and adding little improvement to disease risk prediction. Standard single marker methods may lack power in selecting informative markers or estimating effects. Most existing methods also typically do not account for non-linearity. Identifying markers with weak signals and estimating their joint effects among many non-informative markers remains challenging. One potential approach is to group markers based on biological knowledge such as gene structure. If markers in a group tend to have similar effects, proper usage of the group structure could improve power and efficiency in estimation. We propose a two-stage method relating markers to disease risk by taking advantage of known gene-set structures. Imposing a naive bayes kernel machine (KM) model, we estimate gene-set specific risk models that relate each gene-set to the outcome in stage I. The KM framework efficiently models potentially non-linear effects of predictors without requiring explicit specification of functional forms. In stage II, we aggregate information across gene-sets via a regularization procedure. Estimation and computational efficiency is further improved with kernel principle component analysis. Asymptotic results for model estimation and gene set selection are derived and numerical studies suggest that the proposed procedure could outperform existing procedures for constructing genetic risk models.

Multi-parametric spinal cord MRI as potential progression marker in amyotrophic lateral sclerosis.

PubMed

El Mendili, Mohamed-Mounir; Cohen-Adad, Julien; Pelegrini-Issac, Mélanie; Rossignol, Serge; Morizot-Koutlidis, Régine; Marchand-Pauvert, Véronique; Iglesias, Caroline; Sangari, Sina; Katz, Rose; Lehericy, Stéphane; Benali, Habib; Pradat, Pierre-François

2014-01-01

To evaluate multimodal MRI of the spinal cord in predicting disease progression and one-year clinical status in amyotrophic lateral sclerosis (ALS) patients. After a first MRI (MRI1), 29 ALS patients were clinically followed during 12 months; 14/29 patients underwent a second MRI (MRI2) at 11±3 months. Cross-sectional area (CSA) that has been shown to be a marker of lower motor neuron degeneration was measured in cervical and upper thoracic spinal cord from T2-weighted images. Fractional anisotropy (FA), axial/radial/mean diffusivities (λ⊥, λ//, MD) and magnetization transfer ratio (MTR) were measured within the lateral corticospinal tract in the cervical region. Imaging metrics were compared with clinical scales: Revised ALS Functional Rating Scale (ALSFRS-R) and manual muscle testing (MMT) score. At MRI1, CSA correlated significantly (P<0.05) with MMT and arm ALSFRS-R scores. FA correlated significantly with leg ALFSRS-R scores. One year after MRI1, CSA predicted (P<0.01) arm ALSFSR-R subscore and FA predicted (P<0.01) leg ALSFRS-R subscore. From MRI1 to MRI2, significant changes (P<0.01) were detected for CSA and MTR. CSA rate of change (i.e. atrophy) highly correlated (P<0.01) with arm ALSFRS-R and arm MMT subscores rate of change. Atrophy and DTI metrics predicted ALS disease progression. Cord atrophy was a better biomarker of disease progression than diffusion and MTR. Our study suggests that multimodal MRI could provide surrogate markers of ALS that may help monitoring the effect of disease-modifying drugs.

Impact of laparoscopic ovarian drilling on serum anti-mullerian hormone levels in patients with anovulatory Polycystic Ovarian syndrome.

PubMed

Paramu, Sobhana

2016-12-01

Anti-mullerian hormone (AMH) is a marker of the activity of recruitable ovarian follicles. It is useful in the prediction of ovarian reserve. Women with polycystic ovarian syndrome (PCOS) have elevated circulating and intrafollicular AMH levels. Laparoscopic ovarian drilling (LOD) in patients with PCOS destroys ovarian androgen-producing tissue and reduces their peripheral conversion to estrogens. Identifying factors that determine the response of patients with PCOS to LOD will help in selecting the patients who would likely benefit from this treatment. AMH is one such marker that can predict the response to LOD. To evaluate the effect of LOD on serum AMH levels among PCOS responders and non-responders and the usefulness of AMH as a tool in predicting the response to LOD, and to whether there was loss of ovarian function after LOD. This is a prospective cohort study including 30 clomiphene-resistant women with anovulatory PCOS undergoing LOD. Statistical analysis was performed to evaluate the effect of LOD on serum levels of AMH on these women. A significant fall in the levels of AMH was observed after LOD in both responders and non-responders (p<0.001). Women with AMH >8.3 ng/mL showed a significantly lower ovulation rate (33.3%). LOD was not associated with a risk of diminished ovarian reserve. LOD is an effective first-line treatment for women with PCOS who are clomiphene resistant. LOD has no negative effect on ovarian reserve. AMH is a useful marker in predicting the outcome of LOD.

Genomic Selection in Multi-environment Crop Trials.

PubMed

Oakey, Helena; Cullis, Brian; Thompson, Robin; Comadran, Jordi; Halpin, Claire; Waugh, Robbie

2016-05-03

Genomic selection in crop breeding introduces modeling challenges not found in animal studies. These include the need to accommodate replicate plants for each line, consider spatial variation in field trials, address line by environment interactions, and capture nonadditive effects. Here, we propose a flexible single-stage genomic selection approach that resolves these issues. Our linear mixed model incorporates spatial variation through environment-specific terms, and also randomization-based design terms. It considers marker, and marker by environment interactions using ridge regression best linear unbiased prediction to extend genomic selection to multiple environments. Since the approach uses the raw data from line replicates, the line genetic variation is partitioned into marker and nonmarker residual genetic variation (i.e., additive and nonadditive effects). This results in a more precise estimate of marker genetic effects. Using barley height data from trials, in 2 different years, of up to 477 cultivars, we demonstrate that our new genomic selection model improves predictions compared to current models. Analyzing single trials revealed improvements in predictive ability of up to 5.7%. For the multiple environment trial (MET) model, combining both year trials improved predictive ability up to 11.4% compared to a single environment analysis. Benefits were significant even when fewer markers were used. Compared to a single-year standard model run with 3490 markers, our partitioned MET model achieved the same predictive ability using between 500 and 1000 markers depending on the trial. Our approach can be used to increase accuracy and confidence in the selection of the best lines for breeding and/or, to reduce costs by using fewer markers. Copyright © 2016 Oakey et al.

An original approach was used to better evaluate the capacity of a prognostic marker using published survival curves.

PubMed

Dantan, Etienne; Combescure, Christophe; Lorent, Marine; Ashton-Chess, Joanna; Daguin, Pascal; Classe, Jean-Marc; Giral, Magali; Foucher, Yohann

2014-04-01

Predicting chronic disease evolution from a prognostic marker is a key field of research in clinical epidemiology. However, the prognostic capacity of a marker is not systematically evaluated using the appropriate methodology. We proposed the use of simple equations to calculate time-dependent sensitivity and specificity based on published survival curves and other time-dependent indicators as predictive values, likelihood ratios, and posttest probability ratios to reappraise prognostic marker accuracy. The methodology is illustrated by back calculating time-dependent indicators from published articles presenting a marker as highly correlated with the time to event, concluding on the high prognostic capacity of the marker, and presenting the Kaplan-Meier survival curves. The tools necessary to run these direct and simple computations are available online at http://www.divat.fr/en/online-calculators/evalbiom. Our examples illustrate that published conclusions about prognostic marker accuracy may be overoptimistic, thus giving potential for major mistakes in therapeutic decisions. Our approach should help readers better evaluate clinical articles reporting on prognostic markers. Time-dependent sensitivity and specificity inform on the inherent prognostic capacity of a marker for a defined prognostic time. Time-dependent predictive values, likelihood ratios, and posttest probability ratios may additionally contribute to interpret the marker's prognostic capacity. Copyright © 2014 Elsevier Inc. All rights reserved.

Inflammation, Endothelial Dysfunction and Arterial Stiffness as Therapeutic Targets in Cardiovascular Medicine.

PubMed

Della Corte, Vittoriano; Tuttolomondo, Antonino; Pecoraro, Rosaria; Di Raimondo, Domenico; Vassallo, Valerio; Pinto, Antonio

2016-01-01

In the last decades, many factors thought to be associated with the atherosclerotic process and cardiovascular events have been studied, and some of these have been shown to correlate with clinical outcome, such as arterial stiffness, endothelial dysfunction and immunoinflammatory markers. Arterial stiffness is an important surrogate marker that describes the capability of an artery to expand and contract in response to pressure changes. It can be assessed with different techniques, such as the evaluation of PWV and AIx. It is related to central systolic pressure and it is an independent predictor of cardiovascular morbidity and mortality in hypertensive patients, type 2 diabetes, end-stage renal disease and in elderly populations. The endothelium has emerged as the key regulator of vascular homeostasis, in fact, it has not merely a barrier function but also acts as an active signal transducer for circulating influences that modify the vessel wall phenotype. When its function is lost, it predisposes the vasculature to vasoconstriction, leukocyte adherence, platelet activation, thrombosis and atherosclerosis. Non-invasive methods were developed to evaluate endothelial function, such as the assesment of FMD, L-FMC and RHI. Moreover in the last years, a large number of studies have clarified the role of inflammation and the underlying cellular and molecular mechanisms that contribute to atherogenesis. For clinical purposes, the most promising inflammatory biomarker appears to be CRP and a variety of population-based studies have showed that baseline CRP levels predict future cardiovascular events. Each of the markers listed above has its importance from the pathophysiological and clinical point of view, and those can also be good therapeutic targets. However, it must be stressed that assessments of these vascular markers are not mutually exclusive, but rather complementary and those can offer different views of the same pathology. The purpose of this review is to analyze the role of arterial stiffness, endothelial dysfunction and immunoinflammatory markers as surrogate endpoint, assessing the correlations between these markers and evaluating the therapeutic perspectives that these offer.

Immunosenescence-Related Transcriptomic and Immunologic Changes in Older Individuals Following Influenza Vaccination

PubMed Central

Kennedy, Richard B.; Ovsyannikova, Inna G.; Haralambieva, Iana H.; Oberg, Ann L.; Zimmermann, Michael T.; Grill, Diane E.; Poland, Gregory A.

2016-01-01

The goal of annual influenza vaccination is to reduce mortality and morbidity associated with this disease through the generation of protective immune responses. The objective of the current study was to examine markers of immunosenescence and identify immunosenescence-related differences in gene expression, gene regulation, cytokine secretion, and immunologic changes in an older study population receiving seasonal influenza A/H1N1 vaccination. Surprisingly, prior studies in this cohort revealed weak correlations between immunosenescence markers and humoral immune response to vaccination. In this report, we further examined the relationship of each immunosenescence marker (age, T cell receptor excision circle frequency, telomerase expression, percentage of CD28− CD4+ T cells, percentage of CD28− CD8+ T cells, and the CD4/CD8 T cell ratio) with additional markers of immune response (serum cytokine and chemokine expression) and measures of gene expression and/or regulation. Many of the immunosenescence markers indeed correlated with distinct sets of individual DNA methylation sites, miRNA expression levels, mRNA expression levels, serum cytokines, and leukocyte subsets. However, when the individual immunosenescence markers were grouped by pathways or functional terms, several shared biological functions were identified: antigen processing and presentation pathways, MAPK, mTOR, TCR, BCR, and calcium signaling pathways, as well as key cellular metabolic, proliferation and survival activities. Furthermore, the percent of CD4+ and/or CD8+ T cells lacking CD28 expression also correlated with miRNAs regulating clusters of genes known to be involved in viral infection. Integrated (DNA methylation, mRNA, miRNA, and protein levels) network biology analysis of immunosenescence-related pathways and genesets identified both known pathways (e.g., chemokine signaling, CTL, and NK cell activity), as well as a gene expression module not previously annotated with a known function. These results may improve our ability to predict immune responses to influenza and aid in new vaccine development, and highlight the need for additional studies to better define and characterize immunosenescence. PMID:27853459

Extension and refinement of the predictive value of different classes of markers in ADNI: Four year follow-up data

PubMed Central

Gomar, Jesus J; Conejero-Goldberg, Concepcion; Davies, Peter; Goldberg, Terry E

2014-01-01

Background This study examined the predictive value of different classes of markers in the progression from Mild Cognitive Impairment (MCI) to Alzheimer’s disease (AD) over an extended 4 year follow-up in ADNI. Methods MCI patients assessed on clinical, cognitive, MRI, PET-FDG, and CSF markers at baseline, and followed on a yearly basis for four years to ascertain progression to AD. Logistic regression models were fitted in clusters including demographics, APOE genotype, cognitive markers, and biomarkers (morphometric, PET-FDG, CSF Abeta and tau). Results The predictive model at four years revealed that two cognitive measures, an episodic memory measure and a clock drawing screening test, were the best predictors of conversion (AUC= 0.78). Conclusions This model of prediction is consistent to the previous model at two years, thus highlighting the importance of cognitive measures in progression from MCI to AD. Cognitive markers were more robust predictors than biomarkers. PMID:24613706

Metabotypes with properly functioning mitochondria and anti-inflammation predict extended productive life span in dairy cows

PubMed Central

Huber, K.; Dänicke, S.; Rehage, J.; Sauerwein, H.; Otto, W.; Rolle-Kampczyk, U.; von Bergen, M.

2016-01-01

The failure to adapt metabolism to the homeorhetic demands of lactation is considered as a main factor in reducing the productive life span of dairy cows. The so far defined markers of production performance and metabolic health in dairy cows do not predict the length of productive life span satisfyingly. This study aimed to identify novel pathways and biomarkers related to productive life in dairy cows by means of (targeted) metabolomics. In a longitudinal study from 42 days before up to 100 days after parturition, we identified metabolites such as long-chain acylcarnitines and biogenic amines associated with extended productive life spans. These metabolites are mainly secreted by the liver and depend on the functionality of hepatic mitochondria. The concentrations of biogenic amines and some acylcarnitines differed already before the onset of lactation thus indicating their predictive potential for continuation or early ending of productive life. PMID:27089826

Metabotypes with properly functioning mitochondria and anti-inflammation predict extended productive life span in dairy cows.

PubMed

Huber, K; Dänicke, S; Rehage, J; Sauerwein, H; Otto, W; Rolle-Kampczyk, U; von Bergen, M

2016-04-19

The failure to adapt metabolism to the homeorhetic demands of lactation is considered as a main factor in reducing the productive life span of dairy cows. The so far defined markers of production performance and metabolic health in dairy cows do not predict the length of productive life span satisfyingly. This study aimed to identify novel pathways and biomarkers related to productive life in dairy cows by means of (targeted) metabolomics. In a longitudinal study from 42 days before up to 100 days after parturition, we identified metabolites such as long-chain acylcarnitines and biogenic amines associated with extended productive life spans. These metabolites are mainly secreted by the liver and depend on the functionality of hepatic mitochondria. The concentrations of biogenic amines and some acylcarnitines differed already before the onset of lactation thus indicating their predictive potential for continuation or early ending of productive life.

The predictive effect of inflammatory markers and lipid accumulation product index on clinical symptoms associated with polycystic ovary syndrome in nonobese adolescents and younger aged women.

PubMed

Tola, Esra Nur; Yalcin, Serenat Eris; Dugan, Nadiye

2017-07-01

The aim of our study is to analyse the inflammatory markers and lipid accumulation product (LAP) index in nonobese adolescents and younger aged women with polycystic ovary syndrome (PCOS) compared with age and body mass index (BMI)-matched healthy controls and to determine whether the investigated parameters are potential markers for the etiopathogenesis of PCOS. We also aim to determine whether these inflammatory markers are predictive for developing some clinical implications, such as cardiovascular disease (CVD) and insulin resistance (IR), associated with PCOS. A total of 34 adolescents and younger aged females with PCOS, and 33 age and BMI-matched healthy controls were recruited for our study. All participants were nonobese (BMI<25). Neopterin (NEO), C-reactive protein (CRP) levels and complete blood parameters were assessed. LAP index and homeostasis model assessment of IR (HOMA-IR) were calculated; anthropometric, clinical and biochemical parameters were also recorded. Serum NEO, CRP levels and LAP index were significantly increased in nonobese adolescents and younger aged females with PCOS compared to healthy controls. We could not found any predictive effect of investigated inflammatory markers and LAP index on CVD risk among PCOS patients after adjustment for abdominal obesity. We also found a positive predictive effect of WBC and a negative predictive effect of lymphocytes on IR in PCOS patients after adjustment for abdominal obesity. We did not find any predictor effect of NEO on IR, but it was a positive predictive marker for an elevated HOMA-IR index. Elevated NEO, CRP levels and LAP index could have potential roles in the etiopathogenesis of PCOS in nonobese adolescents and younger aged females,NEO could be a predictive marker for elevated HOMA-IR index, and WBC and lymphocytes could be predictive for the development of IR among nonobese adolescents and younger aged females with PCOS. Copyright © 2017 Elsevier B.V. All rights reserved.

Using Brain Oscillations and Corticospinal Excitability to Understand and Predict Post-Stroke Motor Function

PubMed Central

Thibaut, Aurore; Simis, Marcel; Battistella, Linamara Rizzo; Fanciullacci, Chiara; Bertolucci, Federica; Huerta-Gutierrez, Rodrigo; Chisari, Carmelo; Fregni, Felipe

2017-01-01

What determines motor recovery in stroke is still unknown and finding markers that could predict and improve stroke recovery is a challenge. In this study, we aimed at understanding the neural mechanisms of motor function recovery after stroke using neurophysiological markers by means of cortical excitability (transcranial magnetic stimulation—TMS) and brain oscillations (electroencephalography—EEG). In this cross-sectional study, 55 subjects with chronic stroke (62 ± 14 yo, 17 women, 32 ± 42 months post-stroke) were recruited in two sites. We analyzed TMS measures (i.e., motor threshold—MT—of the affected and unaffected sides) and EEG variables (i.e., power spectrum in different frequency bands and different brain regions of the affected and unaffected hemispheres) and their correlation with motor impairment as measured by Fugl-Meyer. Multiple univariate and multivariate linear regression analyses were performed to identify the predictors of good motor function. A significant interaction effect of MT in the affected hemisphere and power in beta bandwidth over the central region for both affected and unaffected hemispheres was found. We identified that motor function positively correlates with beta rhythm over the central region of the unaffected hemisphere, while it negatively correlates with beta rhythm in the affected hemisphere. Our results suggest that cortical activity in the affected and unaffected hemisphere measured by EEG provides new insights on the association between high-frequency rhythms and motor impairment, highlighting the role of an excess of beta in the affected central cortical region in poor motor function in stroke recovery. PMID:28539912

Using Brain Oscillations and Corticospinal Excitability to Understand and Predict Post-Stroke Motor Function.

PubMed

Thibaut, Aurore; Simis, Marcel; Battistella, Linamara Rizzo; Fanciullacci, Chiara; Bertolucci, Federica; Huerta-Gutierrez, Rodrigo; Chisari, Carmelo; Fregni, Felipe

2017-01-01

What determines motor recovery in stroke is still unknown and finding markers that could predict and improve stroke recovery is a challenge. In this study, we aimed at understanding the neural mechanisms of motor function recovery after stroke using neurophysiological markers by means of cortical excitability (transcranial magnetic stimulation-TMS) and brain oscillations (electroencephalography-EEG). In this cross-sectional study, 55 subjects with chronic stroke (62 ± 14 yo, 17 women, 32 ± 42 months post-stroke) were recruited in two sites. We analyzed TMS measures (i.e., motor threshold-MT-of the affected and unaffected sides) and EEG variables (i.e., power spectrum in different frequency bands and different brain regions of the affected and unaffected hemispheres) and their correlation with motor impairment as measured by Fugl-Meyer. Multiple univariate and multivariate linear regression analyses were performed to identify the predictors of good motor function. A significant interaction effect of MT in the affected hemisphere and power in beta bandwidth over the central region for both affected and unaffected hemispheres was found. We identified that motor function positively correlates with beta rhythm over the central region of the unaffected hemisphere, while it negatively correlates with beta rhythm in the affected hemisphere. Our results suggest that cortical activity in the affected and unaffected hemisphere measured by EEG provides new insights on the association between high-frequency rhythms and motor impairment, highlighting the role of an excess of beta in the affected central cortical region in poor motor function in stroke recovery.

Concise Review: Multifaceted Characterization of Human Mesenchymal Stem Cells for Use in Regenerative Medicine

PubMed Central

Samsonraj, Rebekah M.; Raghunath, Michael; Nurcombe, Victor; Hui, James H.

2017-01-01

Abstract Mesenchymal stem cells (MSC) hold great potential for regenerative medicine because of their ability for self‐renewal and differentiation into tissue‐specific cells such as osteoblasts, chondrocytes, and adipocytes. MSCs orchestrate tissue development, maintenance and repair, and are useful for musculoskeletal regenerative therapies to treat age‐related orthopedic degenerative diseases and other clinical conditions. Importantly, MSCs produce secretory factors that play critical roles in tissue repair that support both engraftment and trophic functions (autocrine and paracrine). The development of uniform protocols for both preparation and characterization of MSCs, including standardized functional assays for evaluation of their biological potential, are critical factors contributing to their clinical utility. Quality control and release criteria for MSCs should include cell surface markers, differentiation potential, and other essential cell parameters. For example, cell surface marker profiles (surfactome), bone‐forming capacities in ectopic and orthotopic models, as well as cell size and granularity, telomere length, senescence status, trophic factor secretion (secretome), and immunomodulation, should be thoroughly assessed to predict MSC utility for regenerative medicine. We propose that these and other functionalities of MSCs should be characterized prior to use in clinical applications as part of comprehensive and uniform guidelines and release criteria for their clinical‐grade production to achieve predictably favorable treatment outcomes for stem cell therapy. Stem Cells Translational Medicine 2017;6:2173–2185 PMID:29076267

De novo assembly and characterization of leaf transcriptome for the development of functional molecular markers of the extremophile multipurpose tree species Prosopis alba

PubMed Central

2013-01-01

Background Prosopis alba (Fabaceae) is an important native tree adapted to arid and semiarid regions of north-western Argentina which is of great value as multipurpose species. Despite its importance, the genomic resources currently available for the entire Prosopis genus are still limited. Here we describe the development of a leaf transcriptome and the identification of new molecular markers that could support functional genetic studies in natural and domesticated populations of this genus. Results Next generation DNA pyrosequencing technology applied to P. alba transcripts produced a total of 1,103,231 raw reads with an average length of 421 bp. De novo assembling generated a set of 15,814 isotigs and 71,101 non-assembled sequences (singletons) with an average of 991 bp and 288 bp respectively. A total of 39,000 unique singletons were identified after clustering natural and artificial duplicates from pyrosequencing reads. Regarding the non-redundant sequences or unigenes, 22,095 out of 54,814 were successfully annotated with Gene Ontology terms. Moreover, simple sequence repeats (SSRs) and single nucleotide polymorphisms (SNPs) were searched, resulting in 5,992 and 6,236 markers, respectively, throughout the genome. For the validation of the the predicted SSR markers, a subset of 87 SSRs selected through functional annotation evidence was successfully amplified from six DNA samples of seedlings. From this analysis, 11 of these 87 SSRs were identified as polymorphic. Additionally, another set of 123 nuclear polymorphic SSRs were determined in silico, of which 50% have the probability of being effectively polymorphic. Conclusions This study generated a successful global analysis of the P. alba leaf transcriptome after bioinformatic and wet laboratory validations of RNA-Seq data. The limited set of molecular markers currently available will be significantly increased with the thousands of new markers that were identified in this study. This information will strongly contribute to genomics resources for P. alba functional analysis and genetics. Finally, it will also potentially contribute to the development of population-based genome studies in the genera. PMID:24125525

Comparison of Models and Whole-Genome Profiling Approaches for Genomic-Enabled Prediction of Septoria Tritici Blotch, Stagonospora Nodorum Blotch, and Tan Spot Resistance in Wheat.

PubMed

Juliana, Philomin; Singh, Ravi P; Singh, Pawan K; Crossa, Jose; Rutkoski, Jessica E; Poland, Jesse A; Bergstrom, Gary C; Sorrells, Mark E

2017-07-01

The leaf spotting diseases in wheat that include Septoria tritici blotch (STB) caused by , Stagonospora nodorum blotch (SNB) caused by , and tan spot (TS) caused by pose challenges to breeding programs in selecting for resistance. A promising approach that could enable selection prior to phenotyping is genomic selection that uses genome-wide markers to estimate breeding values (BVs) for quantitative traits. To evaluate this approach for seedling and/or adult plant resistance (APR) to STB, SNB, and TS, we compared the predictive ability of least-squares (LS) approach with genomic-enabled prediction models including genomic best linear unbiased predictor (GBLUP), Bayesian ridge regression (BRR), Bayes A (BA), Bayes B (BB), Bayes Cπ (BC), Bayesian least absolute shrinkage and selection operator (BL), and reproducing kernel Hilbert spaces markers (RKHS-M), a pedigree-based model (RKHS-P) and RKHS markers and pedigree (RKHS-MP). We observed that LS gave the lowest prediction accuracies and RKHS-MP, the highest. The genomic-enabled prediction models and RKHS-P gave similar accuracies. The increase in accuracy using genomic prediction models over LS was 48%. The mean genomic prediction accuracies were 0.45 for STB (APR), 0.55 for SNB (seedling), 0.66 for TS (seedling) and 0.48 for TS (APR). We also compared markers from two whole-genome profiling approaches: genotyping by sequencing (GBS) and diversity arrays technology sequencing (DArTseq) for prediction. While, GBS markers performed slightly better than DArTseq, combining markers from the two approaches did not improve accuracies. We conclude that implementing GS in breeding for these diseases would help to achieve higher accuracies and rapid gains from selection. Copyright © 2017 Crop Science Society of America.

Genomewide predictions from maize single-cross data.

PubMed

Massman, Jon M; Gordillo, Andres; Lorenzana, Robenzon E; Bernardo, Rex

2013-01-01

Maize (Zea mays L.) breeders evaluate many single-cross hybrids each year in multiple environments. Our objective was to determine the usefulness of genomewide predictions, based on marker effects from maize single-cross data, for identifying the best untested single crosses and the best inbreds within a biparental cross. We considered 479 experimental maize single crosses between 59 Iowa Stiff Stalk Synthetic (BSSS) inbreds and 44 non-BSSS inbreds. The single crosses were evaluated in multilocation experiments from 2001 to 2009 and the BSSS and non-BSSS inbreds had genotypic data for 669 single nucleotide polymorphism (SNP) markers. Single-cross performance was predicted by a previous best linear unbiased prediction (BLUP) approach that utilized marker-based relatedness and information on relatives, and from genomewide marker effects calculated by ridge-regression BLUP (RR-BLUP). With BLUP, the mean prediction accuracy (r(MG)) of single-cross performance was 0.87 for grain yield, 0.90 for grain moisture, 0.69 for stalk lodging, and 0.84 for root lodging. The BLUP and RR-BLUP models did not lead to r(MG) values that differed significantly. We then used the RR-BLUP model, developed from single-cross data, to predict the performance of testcrosses within 14 biparental populations. The r(MG) values within each testcross population were generally low and were often negative. These results were obtained despite the above-average level of linkage disequilibrium, i.e., r(2) between adjacent markers of 0.35 in the BSSS inbreds and 0.26 in the non-BSSS inbreds. Overall, our results suggested that genomewide marker effects estimated from maize single crosses are not advantageous (cofmpared with BLUP) for predicting single-cross performance and have erratic usefulness for predicting testcross performance within a biparental cross.

Management of hepatocellular carcinoma: Predictive value of immunohistochemical markers for postoperative survival

PubMed Central

Niu, Zhao-Shan; Niu, Xiao-Jun; Wang, Mei

2015-01-01

Hepatocellular carcinoma (HCC) accounts for over 90% of all primary liver cancers. With an ever increasing incidence trend year by year, it has become the third most common cause of death from cancer worldwide. Hepatic resection is generally considered to be one of the most effective therapies for HCC patients, however, there is a high risk of recurrence in postoperative HCC. In clinical practice, there exists an urgent need for valid prognostic markers to identify patients with prognosis, hence the importance of studies on prognostic markers in improving the prediction of HCC prognosis. This review focuses on the most promising immunohistochemical prognostic markers in predicting the postoperative survival of HCC patients. PMID:25624992

D-dimer, factor VIII and von Willebrand factor predict a non-dipping pattern of blood pressure in hypertensive patients.

PubMed

Agorasti, Athanasia; Trivellas, Theodoros; Mourvati, Efthimia; Papadopoulos, Vasilios; Tsatalas, Konstantinos; Vargemezis, Vasilios; Passadakis, Ploumis

2013-06-01

The aim of this study is to assess whether the haemostatic markers D-dimer, factor VIII (FVIII) and von Willebrand factor (VWF) are predictive of non-dipping status in treated hypertensive patients; so, as easy available laboratory data can predict non-dipping pattern and help with the selection of the patients whom circadian blood pressure should be re-examined. Forty treated hypertensive patients with essential hypertension were included in the study. Twenty-four-hour ambulatory blood pressure monitoring was performed in all patients. Daytime and nocturnal average systolic, diastolic and mean blood pressures were calculated. Patients were characterised as "non-dippers" on the basis of a less than 10 % decline in nocturnal blood pressure (BP); either systolic or diastolic or mean (MAP). D-dimer as marker of fibrinolytic function, FVIII activity and VWF antigen as marker of endothelial dysfunction were measured on plasma. The predictive efficiency was analysed by receiver operating characteristic (ROC) curves. Youden index was used for the estimation of the cut-off points and the associated values for sensitivity and 1-specificity. Plasma levels of D-dimer, FVIII and VWF were significantly higher in non-dippers as compared with dippers, irrespective of the classification used (BP index); all P < 0.05. The ROC curves indicated a good diagnostic efficiency for D-dimer (AUC(ROC) = 0.697, 0.715 and 0.774), FVIII (AUC(ROC) = 0.714, 0.692 and 0.755) and VWF (AUC(ROC) = 0.706, 0.740 and 0.708) in distinguishing non-dipping pattern (systolic, diastolic or mean) in the study population; all P < 0.05. Among the three haemostatic markers, D-dimer presents the most satisfactory sensitivity/1-specificity for the differentiation of non-dippers, with a cut-off point >168 ng/ml (sensitivity/1-specificity for systolic BP non-dippers of 0.789/0.381, for diastolic BP non-dippers 0.923/0.444 and for MAP non-dippers 0.875/0.375). In conclusion, D-dimer has a good predictive value for non-dipping pattern and the decision for the 24-h ambulatory blood pressure re-monitoring among dippers could rely on its values.

Genome sequencing elucidates Sardinian genetic architecture and augments association analyses for lipid and blood inflammatory markers

PubMed Central

Zoledziewska, Magdalena; Mulas, Antonella; Pistis, Giorgio; Steri, Maristella; Danjou, Fabrice; Kwong, Alan; Ortega del Vecchyo, Vicente Diego; Chiang, Charleston W. K.; Bragg-Gresham, Jennifer; Pitzalis, Maristella; Nagaraja, Ramaiah; Tarrier, Brendan; Brennan, Christine; Uzzau, Sergio; Fuchsberger, Christian; Atzeni, Rossano; Reinier, Frederic; Berutti, Riccardo; Huang, Jie; Timpson, Nicholas J; Toniolo, Daniela; Gasparini, Paolo; Malerba, Giovanni; Dedoussis, George; Zeggini, Eleftheria; Soranzo, Nicole; Jones, Chris; Lyons, Robert; Angius, Andrea; Kang, Hyun M.; Novembre, John; Sanna, Serena; Schlessinger, David; Cucca, Francesco; Abecasis, Gonçalo R

2015-01-01

We report ~17.6M genetic variants from whole-genome sequencing of 2,120 Sardinians; 22% are absent from prior sequencing-based compilations and enriched for predicted functional consequence. Furthermore, ~76K variants common in our sample (frequency >5%) are rare elsewhere (<0.5% in the 1000 Genomes Project). We assessed the impact of these variants on circulating lipid levels and five inflammatory biomarkers. Fourteen signals, including two major new loci, were observed for lipid levels, and 19, including two novel loci, for inflammatory markers. New associations would be missed in analyses based on 1000 Genomes data, underlining the advantages of large-scale sequencing in this founder population. PMID:26366554

Individual differences in socioemotional sensitivity are an index of salience network function.

PubMed

Toller, Gianina; Brown, Jesse; Sollberger, Marc; Shdo, Suzanne M; Bouvet, Laura; Sukhanov, Paul; Seeley, William W; Miller, Bruce L; Rankin, Katherine P

2018-06-01

Connectivity in intrinsically connected networks (ICNs) may predict individual differences in cognition and behavior. The drastic alterations in socioemotional awareness of patients with behavioral variant frontotemporal dementia (bvFTD) are presumed to arise from changes in one such ICN, the salience network (SN). We examined how individual differences in SN connectivity are reflected in overt social behavior in healthy individuals and patients, both to provide neuroscientific insight into this key brain-behavior relationship, and to provide a practical tool to diagnose patients with early bvFTD. We measured SN functional connectivity and socioemotional sensitivity in 65 healthy older adults and 103 patients in the earliest stage [Clinical Dementia Rating (CDR) Scale score ≤1] of five neurodegenerative diseases [14 bvFTD, 29 Alzheimer's disease (AD), 20 progressive supranuclear palsy (PSP), 21 semantic variant primary progressive aphasia (svPPA), and 19 non-fluent variant primary progressive aphasia (nfvPPA)]. All participants underwent resting-state functional imaging and an informant described their responsiveness to subtle emotional expressions using the Revised Self-Monitoring Scale (RSMS). Higher functional connectivity in the SN, predominantly between the right anterior insula (AI) and both "hub" cortical and "interoceptive" subcortical nodes, predicted socioemotional sensitivity among healthy individuals, showing that socioemotional sensitivity is a behavioral marker of SN function, and particularly of right AI functional connectivity. The continuity of this relationship in both healthy and neurologically affected individuals highlights the role of socioemotional sensitivity as an early diagnostic marker of SN connectivity. Clinically, this is particularly important for identification of patients in the earliest stage of bvFTD, where the SN is selectively vulnerable. Copyright © 2018 Elsevier Ltd. All rights reserved.

Biomarkers for predicting type 2 diabetes development-Can metabolomics improve on existing biomarkers?

PubMed

Savolainen, Otto; Fagerberg, Björn; Vendelbo Lind, Mads; Sandberg, Ann-Sofie; Ross, Alastair B; Bergström, Göran

2017-01-01

The aim was to determine if metabolomics could be used to build a predictive model for type 2 diabetes (T2D) risk that would improve prediction of T2D over current risk markers. Gas chromatography-tandem mass spectrometry metabolomics was used in a nested case-control study based on a screening sample of 64-year-old Caucasian women (n = 629). Candidate metabolic markers of T2D were identified in plasma obtained at baseline and the power to predict diabetes was tested in 69 incident cases occurring during 5.5 years follow-up. The metabolomics results were used as a standalone prediction model and in combination with established T2D predictive biomarkers for building eight T2D prediction models that were compared with each other based on their sensitivity and selectivity for predicting T2D. Established markers of T2D (impaired fasting glucose, impaired glucose tolerance, insulin resistance (HOMA), smoking, serum adiponectin)) alone, and in combination with metabolomics had the largest areas under the curve (AUC) (0.794 (95% confidence interval [0.738-0.850]) and 0.808 [0.749-0.867] respectively), with the standalone metabolomics model based on nine fasting plasma markers having a lower predictive power (0.657 [0.577-0.736]). Prediction based on non-blood based measures was 0.638 [0.565-0.711]). Established measures of T2D risk remain the best predictor of T2D risk in this population. Additional markers detected using metabolomics are likely related to these measures as they did not enhance the overall prediction in a combined model.

Biomarkers for predicting type 2 diabetes development—Can metabolomics improve on existing biomarkers?

PubMed Central

Savolainen, Otto; Fagerberg, Björn; Vendelbo Lind, Mads; Sandberg, Ann-Sofie; Ross, Alastair B.; Bergström, Göran

2017-01-01

Aim The aim was to determine if metabolomics could be used to build a predictive model for type 2 diabetes (T2D) risk that would improve prediction of T2D over current risk markers. Methods Gas chromatography-tandem mass spectrometry metabolomics was used in a nested case-control study based on a screening sample of 64-year-old Caucasian women (n = 629). Candidate metabolic markers of T2D were identified in plasma obtained at baseline and the power to predict diabetes was tested in 69 incident cases occurring during 5.5 years follow-up. The metabolomics results were used as a standalone prediction model and in combination with established T2D predictive biomarkers for building eight T2D prediction models that were compared with each other based on their sensitivity and selectivity for predicting T2D. Results Established markers of T2D (impaired fasting glucose, impaired glucose tolerance, insulin resistance (HOMA), smoking, serum adiponectin)) alone, and in combination with metabolomics had the largest areas under the curve (AUC) (0.794 (95% confidence interval [0.738–0.850]) and 0.808 [0.749–0.867] respectively), with the standalone metabolomics model based on nine fasting plasma markers having a lower predictive power (0.657 [0.577–0.736]). Prediction based on non-blood based measures was 0.638 [0.565–0.711]). Conclusions Established measures of T2D risk remain the best predictor of T2D risk in this population. Additional markers detected using metabolomics are likely related to these measures as they did not enhance the overall prediction in a combined model. PMID:28692646

Covariance Association Test (CVAT) Identifies Genetic Markers Associated with Schizophrenia in Functionally Associated Biological Processes.

PubMed

Rohde, Palle Duun; Demontis, Ditte; Cuyabano, Beatriz Castro Dias; Børglum, Anders D; Sørensen, Peter

2016-08-01

Schizophrenia is a psychiatric disorder with large personal and social costs, and understanding the genetic etiology is important. Such knowledge can be obtained by testing the association between a disease phenotype and individual genetic markers; however, such single-marker methods have limited power to detect genetic markers with small effects. Instead, aggregating genetic markers based on biological information might increase the power to identify sets of genetic markers of etiological significance. Several set test methods have been proposed: Here we propose a new set test derived from genomic best linear unbiased prediction (GBLUP), the covariance association test (CVAT). We compared the performance of CVAT to other commonly used set tests. The comparison was conducted using a simulated study population having the same genetic parameters as for schizophrenia. We found that CVAT was among the top performers. When extending CVAT to utilize a mixture of SNP effects, we found an increase in power to detect the causal sets. Applying the methods to a Danish schizophrenia case-control data set, we found genomic evidence for association of schizophrenia with vitamin A metabolism and immunological responses, which previously have been implicated with schizophrenia based on experimental and observational studies. Copyright © 2016 by the Genetics Society of America.

Metaphylogenomic and Potential Functionality of the Limpet Patella pellucida’s Gastrointestinal Tract Microbiome

PubMed Central

Dudek, Magda; Adams, Jessica; Swain, Martin; Hegarty, Matthew; Huws, Sharon; Gallagher, Joe

2014-01-01

This study investigated the microbial diversity associated with the digestive tract of the seaweed grazing marine limpet Patella pellucida. Using a modified indirect DNA extraction protocol and performing metagenomic profiling based on specific prokaryotic marker genes, the abundance of bacterial groups was identified from the analyzed metagenome. The members of three significantly abundant phyla of Proteobacteria, Firmicutes and Bacteroidetes were characterized through the literature and their predicted functions towards the host, as well as potential applications in the industrial environment assessed. PMID:25334059

Markers predicting response to bacillus Calmette-Guérin immunotherapy in high-risk bladder cancer patients: a systematic review.

PubMed

Zuiverloon, Tahlita C M; Nieuweboer, Annemieke J M; Vékony, Hedvig; Kirkels, Wim J; Bangma, Chris H; Zwarthoff, Ellen C

2012-01-01

Currently, bacillus Calmette-Guérin (BCG) intravesical instillations are standard treatment for patients with high-grade non-muscle-invasive bladder cancer; however, no markers are available to predict BCG response. To review the contemporary literature on markers predicting BCG response, to discuss the key issues concerning the identification of predictive markers, and to provide recommendations for further research studies. We performed a systematic review of the literature using PubMed and Embase databases in the period 1996-2010. The free-text search was extended by adding the following keywords: recurrence, progression, survival, molecular marker, prognosis, TP53, Ki-67, RB, fibronectin, immunotherapy, cytokine, interleukin, natural killer, macrophage, PMN, polymorphism, SNP, single nucleotide polymorphism, and gene signature. If thresholds for the detection of urinary interleukin (IL)-8, IL-18, and tumour necrosis factor apoptosis-inducing ligand levels are standardised, measurement of these cytokines holds promise in the assessment of BCG therapy outcome. Studies on immunohistochemical markers (ie, TP53, Ki-67, and retinoblastoma) display contradictory results, probably because of the small patient groups that were used and seem unsuitable to predict BCG response. Exploring combinations of protein levels might prove to be more helpful to establish the effect of BCG therapy. Single nucleotide polymorphisms, either in cytokines or in genes involved in DNA repair, need to be investigated in different ethnicities before their clinical relevance can be determined. Measurement of urinary IL-2 levels seems to be the most potent marker of all the clinical parameters reviewed. IL-2 levels are currently the most promising predictive markers of BCG response. For future studies focusing on new biomarkers, it is essential to make more use of new biomedical techniques such as microRNA profiling and genomewide sequencing. Copyright © 2011 European Association of Urology. Published by Elsevier B.V. All rights reserved.

Oxidative stress markers, cognitive functions, and psychosocial functioning in bipolar disorder: an empirical cross-sectional study.

PubMed

Aydemir, Ömer; Çubukçuoğlu, Zeynep; Erdin, Soner; Taş, Cumhur; Onur, Ece; Berk, Michael

2014-01-01

This study aimed to evaluate the relationship between oxidative stress markers and cognitive functions and domains of psychosocial functioning in bipolar disorder. Oxidative stress markers, cognitive functions, and domains of psychosocial functioning were evaluated in 51 patients with bipolar disorder who were in remission. Correlation analyses between these parameters were calculated with data controlled for duration of illness and number of episodes. There was no statistically significant correlation between oxidative stress markers and cognitive functions. In terms of psychosocial functioning, significant correlations were found between malondialdehyde and sense of stigmatization (r = -0.502); household activities and superoxide dismutase (r = 0.501); participation in social activities and nitric oxide (r = 0.414); hobbies and leisure time activities and total glutathione (r = -0.567), superoxide dismutase (r = 0.667), and neurotrophin 4 (r = 0.450); and taking initiative and self-sufficiency and superoxide dismutase (r = 0.597). There was no correlation between other domains of psychosocial functioning and oxidative stress markers. These results imply that oxidative stress markers do not appear to correlate clearly with cognitive impairment and reduced psychosocial functioning. However, there were some associations between selected oxidative markers and activity-oriented functional markers. This may represent a true negative association, or may be an artifact of oxidative stress being a state rather than a trait marker.

Novel Applications of Multi-task Learning and Multiple Output Regression to Multiple Genetic Trait Prediction

USDA-ARS?s Scientific Manuscript database

Given a set of biallelic molecular markers, such as SNPs, with genotype values encoded numerically on a collection of plant, animal or human samples, the goal of genetic trait prediction is to predict the quantitative trait values by simultaneously modeling all marker effects. Genetic trait predicti...

Lysophosphatidic Acid and Apolipoprotein A1 Predict Increased Risk of Developing World Trade Center Lung Injury: A Nested Case-Control Study

PubMed Central

Tsukiji, Jun; Cho, Soo Jung; Echevarria, Ghislaine C.; Kwon, Sophia; Joseph, Phillip; Schenck, Edward J.; Naveed, Bushra; Prezant, David J.; Rom, William N.; Schmidt, Ann Marie; Weiden, Michael D.; Nolan, Anna

2014-01-01

Rationale Metabolic syndrome, inflammatory and vascular injury markers measured in serum after WTC exposures predict abnormal FEV1. We hypothesized that elevated LPA levels predict FEV1

ERCC1 and RRM1: ready for prime time?

PubMed

Besse, Benjamin; Olaussen, Ken A; Soria, Jean-Charles

2013-03-10

The quest for markers of sensitivity to cytotoxic agents has been ongoing for decades. In non-small-cell lung cancer, platinum compounds represent the cornerstone of systemic therapy. They target DNA and induce damage that cancer cells struggle to overcome. Somatic excision repair cross-complementing rodent repair deficiency, complementation group 1 (ERCC1), and ribonucleotide reductase M1 (RRM1) expression levels have been extensively explored as markers of DNA repair capacity in tumor cells. Although low ERCC1 and/or RRM1 expression is generally associated with sensitivity to platinum, the results published in retrospective and prospective studies are not always consistent. Against this background, we will examine in this review the function of these two biomarkers as well as the tools available for their assessment and the associated technical issues. Their prognostic and predictive values will be summarized and considered in terms of customizing systemic therapy according to biomarker (ERCC1 and RRM1) expression levels. We will also discuss why the use of both markers should at this point be restricted to clinical research and underline that functional readouts of DNA repair will help boost future strategies for biomarker discovery in the field.

EVALUATING RISK-PREDICTION MODELS USING DATA FROM ELECTRONIC HEALTH RECORDS.

PubMed

Wang, L E; Shaw, Pamela A; Mathelier, Hansie M; Kimmel, Stephen E; French, Benjamin

2016-03-01

The availability of data from electronic health records facilitates the development and evaluation of risk-prediction models, but estimation of prediction accuracy could be limited by outcome misclassification, which can arise if events are not captured. We evaluate the robustness of prediction accuracy summaries, obtained from receiver operating characteristic curves and risk-reclassification methods, if events are not captured (i.e., "false negatives"). We derive estimators for sensitivity and specificity if misclassification is independent of marker values. In simulation studies, we quantify the potential for bias in prediction accuracy summaries if misclassification depends on marker values. We compare the accuracy of alternative prognostic models for 30-day all-cause hospital readmission among 4548 patients discharged from the University of Pennsylvania Health System with a primary diagnosis of heart failure. Simulation studies indicate that if misclassification depends on marker values, then the estimated accuracy improvement is also biased, but the direction of the bias depends on the direction of the association between markers and the probability of misclassification. In our application, 29% of the 1143 readmitted patients were readmitted to a hospital elsewhere in Pennsylvania, which reduced prediction accuracy. Outcome misclassification can result in erroneous conclusions regarding the accuracy of risk-prediction models.

IGF-I levels reflect hypopituitarism severity in adults with pituitary dysfunction.

PubMed

Tirosh, Amit; Toledano, Yoel; Masri-Iraqi, Hiba; Eizenberg, Yoav; Tzvetov, Gloria; Hirsch, Dania; Benbassat, Carlos; Robenshtok, Eyal; Shimon, Ilan

2016-08-01

To evaluate the utility of Insulin-like growth factor I (IGF-I) standard deviation score (SDS) as a surrogate marker of severity of hypopituitarism in adults with pituitary pathology. We performed a retrospective data analysis, including 269 consecutive patients with pituitary disease attending a tertiary endocrine clinic in 1990-2015. The medical files were reviewed for the complete pituitary hormone profile, including IGF-I, and clinical data. Age-adjusted assay reference ranges of IGF-I were used to calculate IGF-I SDS for each patient. The main outcome measures were positive and negative predictive values of low and high IGF-I SDS, respectively, for the various pituitary hormone deficiencies. IGF-I SDS correlated negatively with the number of altered pituitary axes (p < 0.001). Gonadotropin was affected in 76.6 % of cases, followed by thyrotropin (58.4 %), corticotropin (49.1 %), and prolactin (22.7 %). Positive and negative predictive values yielded a clear trend for the probability of low/high IGF-I SDS for all affected pituitary axes. Rates of diabetes insipidus correlated with IGF-I SDS values both for the full study population, and specifically for patients with non-functioning pituitary adenomas. IGF-I SDS can be used to evaluate the somatotroph function, as a valid substitute to absolute IGF-I levels. Moreover, IGF-I SDS predicted the extent of hypopituitarism in adults with pituitary disease, and thus can serve as a marker of hypopituitarism severity.

Serum-circulating miRNAs predict neuroblastoma progression in mouse model of high-risk metastatic disease.

PubMed

Ramraj, Satish Kumar; Aravindan, Sheeja; Somasundaram, Dinesh Babu; Herman, Terence S; Natarajan, Mohan; Aravindan, Natarajan

2016-04-05

Circulating miRNAs have momentous clinical relevance as prognostic biomarkers and in the progression of solid tumors. Recognizing novel candidates of neuroblastoma-specific circulating miRNAs would allow us to identify potential prognostic biomarkers that could predict the switch from favorable to high-risk metastatic neuroblastoma (HR-NB). Utilizing mouse models of favorable and HR-NB and whole miRnome profiling, we identified high serum levels of 34 and low levels of 46 miRNAs in animals with HR-NB. Preferential sequence homology exclusion of mouse miRNAs identified 25 (11 increased; 14 decreased) human-specific prognostic marker candidates, of which, 21 were unique to HR-NB. miRNA QPCR validated miRnome profile. Target analysis defined the candidate miRNAs' signal transduction flow-through and demonstrated their converged roles in tumor progression. miRNA silencing studies verified the function of select miRNAs on the translation of at least 14 target proteins. Expressions of critical targets that correlate tumor progression in tissue of multifarious organs identify the orchestration of HR-NB. Significant (>10 fold) increase in serum levels of miR-381, miR-548h, and miR-580 identify them as potential prognostic markers for neuroblastoma progression. For the first time, we identified serum-circulating miRNAs that predict the switch from favorable to HR-NB and, further imply that these miRNAs could play a functional role in tumor progression.

Relationships between Rapid Eye Movement Sleep Behavior Disorder and Neurodegenerative Diseases: Clinical Assessments, Biomarkers, and Treatment

PubMed Central

Li, Min; Wang, Li; Liu, Jiang-Hong; Zhan, Shu-Qin

2018-01-01

Objective: Rapid eye movement sleep behavior disorder (RBD) is characterized by dream enactment and loss of muscle atonia during rapid eye movement sleep. RBD is closely related to α-synucleinopathies including Parkinson's disease, dementia with Lewy bodies, and multiple system atrophy. Many studies have investigated the markers of imaging and neurophysiological, genetic, cognitive, autonomic function of RBD and their predictive value for neurodegenerative diseases. This report reviewed the progress of these studies and discussed their limitations and future research directions. Data Sources: Using the combined keywords: “RBD”, “neurodegenerative disease”, “Parkinson disease”, and “magnetic resonance imaging”, the PubMed/MEDLINE literature search was conducted up to January 1, 2018. Study Selection: A total of 150 published articles were initially identified citations. Of the 150 articles, 92 articles were selected after further detailed review. This study referred to all the important English literature in full. Results: Single-nucleotide polymorphisms in SCARB2 (rs6812193) and MAPT (rs12185268) were significantly associated with RBD. The olfactory loss, autonomic dysfunction, marked electroencephalogram slowing during both wakefulness and rapid eye movement sleep, and cognitive impairments were potential predictive markers for RBD conversion to neurodegenerative diseases. Traditional structural imaging studies reported relatively inconsistent results, whereas reduced functional connectivity between the left putamen and substantia nigra and dopamine transporter uptake demonstrated by functional imaging techniques were relatively consistent findings. Conclusions: More longitudinal studies should be conducted to evaluate the predictive value of biomarkers of RBD. Moreover, because the glucose and dopamine metabolisms are not specific for assessing cognitive cognition, the molecular metabolism directly related to cognition should be investigated. There is a need for more treatment trials to determine the effectiveness of interventions of RBD on preventing the conversion to neurodegenerative diseases. PMID:29664058

Blend sign predicts poor outcome in patients with intracerebral hemorrhage.

PubMed

Li, Qi; Yang, Wen-Song; Wang, Xing-Chen; Cao, Du; Zhu, Dan; Lv, Fa-Jin; Liu, Yang; Yuan, Liang; Zhang, Gang; Xiong, Xin; Li, Rui; Hu, Yun-Xin; Qin, Xin-Yue; Xie, Peng

2017-01-01

Blend sign has been recently described as a novel imaging marker that predicts hematoma expansion. The purpose of our study was to investigate the prognostic value of CT blend sign in patients with ICH. Patients with intracerebral hemorrhage who underwent baseline CT scan within 6 hours were included. The presence of blend sign on admission nonenhanced CT was independently assessed by two readers. The functional outcome was assessed by using the modified Rankin Scale (mRS) at 90 days. Blend sign was identified in 40 of 238 (16.8%) patients on admission CT scan. The proportion of patients with a poor functional outcome was significantly higher in patients with blend sign than those without blend sign (75.0% versus 47.5%, P = 0.001). The multivariate logistic regression analysis demonstrated that age, intraventricular hemorrhage, admission GCS score, baseline hematoma volume and presence of blend sign on baseline CT independently predict poor functional outcome at 90 days. The CT blend sign independently predicts poor outcome in patients with ICH (odds ratio 3.61, 95% confidence interval [1.47-8.89];p = 0.005). Early identification of blend sign is useful in prognostic stratification and may serve as a potential therapeutic target for prospective interventional studies.

Prediction of genetic values of quantitative traits in plant breeding using pedigree and molecular markers.

PubMed

Crossa, José; Campos, Gustavo de Los; Pérez, Paulino; Gianola, Daniel; Burgueño, Juan; Araus, José Luis; Makumbi, Dan; Singh, Ravi P; Dreisigacker, Susanne; Yan, Jianbing; Arief, Vivi; Banziger, Marianne; Braun, Hans-Joachim

2010-10-01

The availability of dense molecular markers has made possible the use of genomic selection (GS) for plant breeding. However, the evaluation of models for GS in real plant populations is very limited. This article evaluates the performance of parametric and semiparametric models for GS using wheat (Triticum aestivum L.) and maize (Zea mays) data in which different traits were measured in several environmental conditions. The findings, based on extensive cross-validations, indicate that models including marker information had higher predictive ability than pedigree-based models. In the wheat data set, and relative to a pedigree model, gains in predictive ability due to inclusion of markers ranged from 7.7 to 35.7%. Correlation between observed and predictive values in the maize data set achieved values up to 0.79. Estimates of marker effects were different across environmental conditions, indicating that genotype × environment interaction is an important component of genetic variability. These results indicate that GS in plant breeding can be an effective strategy for selecting among lines whose phenotypes have yet to be observed.

Multi-Parametric Spinal Cord MRI as Potential Progression Marker in Amyotrophic Lateral Sclerosis

PubMed Central

El Mendili, Mohamed-Mounir; Cohen-Adad, Julien; Pelegrini-Issac, Mélanie; Rossignol, Serge; Morizot-Koutlidis, Régine; Marchand-Pauvert, Véronique; Iglesias, Caroline; Sangari, Sina; Katz, Rose; Lehericy, Stéphane; Benali, Habib; Pradat, Pierre-François

2014-01-01

Objective To evaluate multimodal MRI of the spinal cord in predicting disease progression and one-year clinical status in amyotrophic lateral sclerosis (ALS) patients. Materials and Methods After a first MRI (MRI1), 29 ALS patients were clinically followed during 12 months; 14/29 patients underwent a second MRI (MRI2) at 11±3 months. Cross-sectional area (CSA) that has been shown to be a marker of lower motor neuron degeneration was measured in cervical and upper thoracic spinal cord from T2-weighted images. Fractional anisotropy (FA), axial/radial/mean diffusivities (λ⊥, λ//, MD) and magnetization transfer ratio (MTR) were measured within the lateral corticospinal tract in the cervical region. Imaging metrics were compared with clinical scales: Revised ALS Functional Rating Scale (ALSFRS-R) and manual muscle testing (MMT) score. Results At MRI1, CSA correlated significantly (P<0.05) with MMT and arm ALSFRS-R scores. FA correlated significantly with leg ALFSRS-R scores. One year after MRI1, CSA predicted (P<0.01) arm ALSFSR-R subscore and FA predicted (P<0.01) leg ALSFRS-R subscore. From MRI1 to MRI2, significant changes (P<0.01) were detected for CSA and MTR. CSA rate of change (i.e. atrophy) highly correlated (P<0.01) with arm ALSFRS-R and arm MMT subscores rate of change. Conclusion Atrophy and DTI metrics predicted ALS disease progression. Cord atrophy was a better biomarker of disease progression than diffusion and MTR. Our study suggests that multimodal MRI could provide surrogate markers of ALS that may help monitoring the effect of disease-modifying drugs. PMID:24755826

A function accounting for training set size and marker density to model the average accuracy of genomic prediction.

PubMed

Erbe, Malena; Gredler, Birgit; Seefried, Franz Reinhold; Bapst, Beat; Simianer, Henner

2013-01-01

Prediction of genomic breeding values is of major practical relevance in dairy cattle breeding. Deterministic equations have been suggested to predict the accuracy of genomic breeding values in a given design which are based on training set size, reliability of phenotypes, and the number of independent chromosome segments ([Formula: see text]). The aim of our study was to find a general deterministic equation for the average accuracy of genomic breeding values that also accounts for marker density and can be fitted empirically. Two data sets of 5'698 Holstein Friesian bulls genotyped with 50 K SNPs and 1'332 Brown Swiss bulls genotyped with 50 K SNPs and imputed to ∼600 K SNPs were available. Different k-fold (k = 2-10, 15, 20) cross-validation scenarios (50 replicates, random assignment) were performed using a genomic BLUP approach. A maximum likelihood approach was used to estimate the parameters of different prediction equations. The highest likelihood was obtained when using a modified form of the deterministic equation of Daetwyler et al. (2010), augmented by a weighting factor (w) based on the assumption that the maximum achievable accuracy is [Formula: see text]. The proportion of genetic variance captured by the complete SNP sets ([Formula: see text]) was 0.76 to 0.82 for Holstein Friesian and 0.72 to 0.75 for Brown Swiss. When modifying the number of SNPs, w was found to be proportional to the log of the marker density up to a limit which is population and trait specific and was found to be reached with ∼20'000 SNPs in the Brown Swiss population studied.

Does point-of-care functional echocardiography enhance cardiovascular care in the NICU?

PubMed

Sehgal, A; McNamara, P J

2008-11-01

Although the last two decades have seen major advances in the care of sick, extremely premature newborns, the approach to cardiovascular assessment and monitoring remains suboptimal owing to an overreliance on poorly predictive clinical markers such as heart rate or capillary refill time. Point-of-care functional echocardiography (PCFecho) enables real-time evaluation of cardiac performance and systemic hemodynamics to characterize acute physiology, identify the exact nature of cardiovascular compromise and guide therapeutic decisions. In this article, we will review four clinical scenarios where bedside functional cardiac imaging enabled delineation of the real clinical problem and refinement of the therapeutic care plan with direct patient benefits.

Association of Inflammation With Loss Of Ability to Walk 400 Meters: Longitudinal Findings From the Inchianti Study

PubMed Central

Vasunilashorn, Sarinnapha; Ferrucci, Luigi; Crimmins, Eileen M.; Bandinelli, Stefania; Guralnik, Jack M.; Patel, Kushang V.

2013-01-01

Objectives To examine relationships between eight markers of inflammation (interleukin [IL]-6, IL-6 receptor [R], C-reactive protein [CRP], tumor necrosis factor [TNF]-α, TNF receptor 1[R1], TNFR2, IL-1 receptor antagonist, IL-18) and incident loss of ability to walk 400 m. Design Prospective cohort study. Setting Older adults enrolled in the InvecchiareInChianti Study. Participants One thousand six community-dwelling participants aged 65+. Measurements The eight inflammatory markers were measured at baseline, and an inflammation score was calculated based on the number of inflammatory markers for which the participant was in the highest quartile. Incidence of mobility disability was determined among participants able to walk 400 m at baseline. Logistic regression models were used to determine whether each of the inflammatory markers and the inflammation score predicts loss of the ability to walk 400 m at six-year follow-up. Results After adjusting for covariates, individuals with aTNFR1 level in each of the top 3 quartiles (Q2, 3, 4) were more likely to be unable to walk 400 m at follow-up compared to those with TNFR1 levels in Q1. When adjusting for the same covariates, participants with an inflammation score of 3 or 4 were more likely to become unable to complete the 400 m walk at follow-up compared to participants with a score of 0. Conclusion These results bring additional evidence to the notion that inflammation is implicated in the mechanisms that cause incident mobility disability and suggest that a combined measure of inflammatory markers may improve our prediction of functional prognosis. PMID:24083386

Association of inflammation with loss of ability to walk 400 meters: longitudinal findings from the Invecchiare in Chianti Study.

PubMed

Vasunilashorn, Sarinnapha; Ferrucci, Luigi; Crimmins, Eileen M; Bandinelli, Stefania; Guralnik, Jack M; Patel, Kushang V

2013-10-01

To examine relationships between eight markers of inflammation (interleukin (IL)-6, IL-6 receptor (R), C-reactive protein (CRP), tumor necrosis factor (TNF)-alpha, TNF receptor 1 (R1), TNFR2, IL-1 receptor antagonist, IL-18) and incident loss of ability to walk 400 m. Prospective cohort study. Older adults enrolled in the Invecchiare in Chianti Study. Community-dwelling participants aged 65 and older (N = 1,006). The eight inflammatory markers were measured at baseline, and an inflammation score was calculated based on the number of inflammatory markers for which the participant was in the highest quartile. Incidence of mobility disability was determined in participants able to walk 400 m at baseline. Logistic regression models were used to determine whether each of the inflammatory markers and the inflammation score predicted loss of the ability to walk 400 m at 6-year follow-up. After adjusting for covariates, individuals with a TNFR1 level in each of the highest three quartiles (Q2, 3, 4) were more likely to be unable to walk 400 m at follow-up than those with TNFR1 levels in Q1. When adjusting for the same covariates, participants with an inflammation score of 3 or 4 were more likely to become unable to walk 400 m at follow-up than participants with a score of 0. These results provide additional evidence that inflammation is a factor in the mechanisms that cause incident mobility disability and suggest that a combined measure of inflammatory markers may improve prediction of functional prognosis. © 2013, Copyright the Authors Journal compilation © 2013, The American Geriatrics Society.

Markers of Bone Metabolism Are Affected by Renal Function and Growth Hormone Therapy in Children with Chronic Kidney Disease

PubMed Central

Doyon, Anke; Fischer, Dagmar-Christiane; Bayazit, Aysun Karabay; Canpolat, Nur; Duzova, Ali; Sözeri, Betül; Bacchetta, Justine; Balat, Ayse; Büscher, Anja; Candan, Cengiz; Cakar, Nilgun; Donmez, Osman; Dusek, Jiri; Heckel, Martina; Klaus, Günter; Mir, Sevgi; Özcelik, Gül; Sever, Lale; Shroff, Rukshana; Vidal, Enrico; Wühl, Elke; Gondan, Matthias; Melk, Anette; Querfeld, Uwe; Haffner, Dieter; Schaefer, Franz

2015-01-01

Objectives The extent and relevance of altered bone metabolism for statural growth in children with chronic kidney disease is controversial. We analyzed the impact of renal dysfunction and recombinant growth hormone therapy on a panel of serum markers of bone metabolism in a large pediatric chronic kidney disease cohort. Methods Bone alkaline phosphatase (BAP), tartrate-resistant acid phosphatase 5b (TRAP5b), sclerostin and C-terminal FGF-23 (cFGF23) normalized for age and sex were analyzed in 556 children aged 6–18 years with an estimated glomerular filtration rate (eGFR) of 10–60 ml/min/1.73m2. 41 children receiving recombinant growth hormone therapy were compared to an untreated matched control group. Results Standardized levels of BAP, TRAP5b and cFGF-23 were increased whereas sclerostin was reduced. BAP was correlated positively and cFGF-23 inversely with eGFR. Intact serum parathormone was an independent positive predictor of BAP and TRAP5b and negatively associated with sclerostin. BAP and TRAP5B were negatively affected by increased C-reactive protein levels. In children receiving recombinant growth hormone, BAP was higher and TRAP5b lower than in untreated controls. Sclerostin levels were in the normal range and higher than in untreated controls. Serum sclerostin and cFGF-23 independently predicted height standard deviation score, and BAP and TRAP5b the prospective change in height standard deviation score. Conclusion Markers of bone metabolism indicate a high-bone turnover state in children with chronic kidney disease. Growth hormone induces an osteoanabolic pattern and normalizes osteocyte activity. The osteocyte markers cFGF23 and sclerostin are associated with standardized height, and the markers of bone turnover predict height velocity. PMID:25659076

Emotion suppression moderates the quadratic association between RSA and executive function.

PubMed

Spangler, Derek P; Bell, Martha Ann; Deater-Deckard, Kirby

2015-09-01

There is uncertainty about whether respiratory sinus arrhythmia (RSA), a cardiac marker of adaptive emotion regulation, is involved in relatively low or high executive function performance. In the present study, we investigated (a) whether RSA during rest and tasks predict both relatively low and high executive function within a larger quadratic association among the two variables, and (b) the extent to which this quadratic trend was moderated by individual differences in emotion regulation. To achieve these aims, a sample of ethnically and socioeconomically diverse women self-reported reappraisal and emotion suppression. They next experienced a 2-min resting period during which electrocardiogram (ECG) was continually assessed. In the next phase, the women completed an array of executive function and nonexecutive cognitive tasks while ECG was measured throughout. As anticipated, resting RSA showed a quadratic association with executive function that was strongest for high suppression. These results suggest that relatively high resting RSA may predict poor executive function ability when emotion regulation consumes executive control resources needed for ongoing cognitive performance. © 2015 Society for Psychophysiological Research.

Simpler score of routine laboratory tests predicts liver fibrosis in patients with chronic hepatitis B.

PubMed

Zhou, Kun; Gao, Chun-Fang; Zhao, Yun-Peng; Liu, Hai-Lin; Zheng, Rui-Dan; Xian, Jian-Chun; Xu, Hong-Tao; Mao, Yi-Min; Zeng, Min-De; Lu, Lun-Gen

2010-09-01

In recent years, a great interest has been dedicated to the development of noninvasive predictive models to substitute liver biopsy for fibrosis assessment and follow-up. Our aim was to provide a simpler model consisting of routine laboratory markers for predicting liver fibrosis in patients chronically infected with hepatitis B virus (HBV) in order to optimize their clinical management. Liver fibrosis was staged in 386 chronic HBV carriers who underwent liver biopsy and routine laboratory testing. Correlations between routine laboratory markers and fibrosis stage were statistically assessed. After logistic regression analysis, a novel predictive model was constructed. This S index was validated in an independent cohort of 146 chronic HBV carriers in comparison to the SLFG model, Fibrometer, Hepascore, Hui model, Forns score and APRI using receiver operating characteristic (ROC) curves. The diagnostic values of each marker panels were better than single routine laboratory markers. The S index consisting of gamma-glutamyltransferase (GGT), platelets (PLT) and albumin (ALB) (S-index: 1000 x GGT/(PLT x ALB(2))) had a higher diagnostic accuracy in predicting degree of fibrosis than any other mathematical model tested. The areas under the ROC curves (AUROC) were 0.812 and 0.890 for predicting significant fibrosis and cirrhosis in the validation cohort, respectively. The S index, a simpler mathematical model consisting of routine laboratory markers predicts significant fibrosis and cirrhosis in patients with chronic HBV infection with a high degree of accuracy, potentially decreasing the need for liver biopsy.

Contrasting olfaction, vision, and audition as predictors of cognitive change and impairment in non-demented older adults.

PubMed

MacDonald, Stuart W S; Keller, Connor J C; Brewster, Paul W H; Dixon, Roger A

2018-05-01

This study examines the relative utility of a particular class of noninvasive functional biomarkers-sensory functions-for detecting those at risk of cognitive decline and impairment. Three central research objectives were examined including whether (a) olfactory function, vision, and audition exhibited significant longitudinal declines in nondemented older adults; (b) multiwave change for these sensory function indicators predicted risk of mild cognitive impairment (MCI); and (c) change within persons for each sensory measure shared dynamic time-varying associations with within-person change in cognitive functioning. A longitudinal sample (n = 408) from the Victoria Longitudinal Study was assembled. Three cognitive status subgroups were identified: not impaired cognitively, single-assessment MCI, and multiple-assessment MCI. We tested independent predictive associations, contrasting change in sensory function as predictors of cognitive decline and impairment, utilizing both linear mixed models and logistic regression analysis. Olfaction and, to a lesser extent, vision were identified as the most robust predictors of cognitive status and decline; audition showed little predictive influence. These findings underscore the potential utility of deficits in olfactory function, in particular, as an early marker of age- and pathology-related cognitive decline. Functional biomarkers may represent potential candidates for use in the early stages of a multistep screening approach for detecting those at risk of cognitive impairment, as well as for targeted intervention. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Brain age predicts mortality

PubMed Central

Cole, J H; Ritchie, S J; Bastin, M E; Valdés Hernández, M C; Muñoz Maniega, S; Royle, N; Corley, J; Pattie, A; Harris, S E; Zhang, Q; Wray, N R; Redmond, P; Marioni, R E; Starr, J M; Cox, S R; Wardlaw, J M; Sharp, D J; Deary, I J

2018-01-01

Age-associated disease and disability are placing a growing burden on society. However, ageing does not affect people uniformly. Hence, markers of the underlying biological ageing process are needed to help identify people at increased risk of age-associated physical and cognitive impairments and ultimately, death. Here, we present such a biomarker, ‘brain-predicted age’, derived using structural neuroimaging. Brain-predicted age was calculated using machine-learning analysis, trained on neuroimaging data from a large healthy reference sample (N=2001), then tested in the Lothian Birth Cohort 1936 (N=669), to determine relationships with age-associated functional measures and mortality. Having a brain-predicted age indicative of an older-appearing brain was associated with: weaker grip strength, poorer lung function, slower walking speed, lower fluid intelligence, higher allostatic load and increased mortality risk. Furthermore, while combining brain-predicted age with grey matter and cerebrospinal fluid volumes (themselves strong predictors) not did improve mortality risk prediction, the combination of brain-predicted age and DNA-methylation-predicted age did. This indicates that neuroimaging and epigenetics measures of ageing can provide complementary data regarding health outcomes. Our study introduces a clinically-relevant neuroimaging ageing biomarker and demonstrates that combining distinct measurements of biological ageing further helps to determine risk of age-related deterioration and death. PMID:28439103

A Secreted Form of the Asialoglycoprotein Receptor, sH2a, as a Novel Potential Noninvasive Marker for Liver Fibrosis

PubMed Central

Lurie, Yoav; Ron, Efrat; Santo, Moshe; Reif, Shimon; Elashvili, Irma; Bar, Lana; Lederkremer, Gerardo Z.

2011-01-01

Background and Aim The human asialoglycoprotein receptor is a membrane heterooligomer expressed exclusively in hepatocytes. A soluble secreted form, sH2a, arises, not by shedding at the cell surface, but by intracellular cleavage of its membrane-bound precursor, which is encoded by an alternatively spliced form of the receptor H2 subunit. Here we determined and report that sH2a, present at constant levels in serum from healthy individuals is altered upon liver fibrosis, reflecting the status of hepatocyte function. Methods We measured sH2a levels in serum using a monoclonal antibody and an ELISA assay that we developed, comparing with routine liver function markers. We compared blindly pretreatment serum samples from a cohort of 44 hepatitis C patients, which had METAVIR-scored biopsies, with 28 healthy individuals. Results sH2a levels varied minimally for the healthy individuals (150±21 ng/ml), whereas the levels deviated from this normal range increasingly in correlation with fibrosis stage. A simple algorithm combining sH2a levels with those of alanine aminotransferase allowed prediction of fibrosis stage, with a very high area under the ROC curve of 0.86. Conclusions sH2a has the potential to be a uniquely sensitive and specific novel marker for liver fibrosis and function. PMID:22096539

Spontaneous eye blink rate as predictor of dopamine-related cognitive function-A review.

PubMed

Jongkees, Bryant J; Colzato, Lorenza S

2016-12-01

An extensive body of research suggests the spontaneous eye blink rate (EBR) is a non-invasive indirect marker of central dopamine (DA) function, with higher EBR predicting higher DA function. In the present review we provide a comprehensive overview of this literature. We broadly divide the available research in studies that aim to disentangle the dopaminergic underpinnings of EBR, investigate its utility in diagnosis of DA-related disorders and responsivity to drug treatment, and, lastly, investigate EBR as predictor of individual differences in DA-related cognitive performance. We conclude (i) EBR can reflect both DA receptor subtype D1 and D2 activity, although baseline EBR might be most strongly related to the latter, (ii) EBR can predict hypo- and hyperdopaminergic activity as well as normalization of this activity following treatment, and (iii) EBR can reliably predict individual differences in performance on many cognitive tasks, in particular those related to reward-driven behavior and cognitive flexibility. In sum, this review establishes EBR as a useful predictor of DA in a wide variety of contexts. Copyright © 2016 Elsevier Ltd. All rights reserved.

Isolation and characterization of new highly polymorphic DNA markers from the Huntington disease region

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

Weber, B.; Hedrick, A.; Andrew, S.

1992-02-01

The defect causing Huntington disease (HD) has been mapped to 4p16.3, distal to the DNA marker D4S10. Subsequently, additional polymorphic markers closer to the HD gene have been isolated, which has led to the establishment of predictive testing programs for individuals at risk for HD. Approximately 17% of persons presenting to the Canadian collaborative study for predictive testing for HD have not received any modification of risk, in part because of limited informativeness of currently available DNA markers. Therefore, more highly polymorphic DNA markers are needed, which well further increase the accuracy and availability of predictive testing, specifically for familiesmore » with complex or incomplete pedigree structures. In addition, new markers are urgently needed in order to refine the breakpoints in the few known recombinant HD chromosomes, which could allow a more accurate localization of the HD gene within 4p16.3 and, therefore, accelerate the cloning of the disease gene. In this study, the authors present the identification and characterization of nine new polymorphic DNA markers, including three markers which detect highly informative multiallelic VNTR-like polymorphisms with PIC values of up to .84. These markers have been isolated from a cloned region of DNA which has been previously mapped approximately 1,000 kb from the 4p telomere.« less

Functional Roles of Neural Preparatory Processes in a Cued Stroop Task Revealed by Linking Electrophysiology with Behavioral Performance.

PubMed

Wang, Chao; Ding, Mingzhou; Kluger, Benzi M

2015-01-01

It is well established that cuing facilitates behavioral performance and that different aspects of instructional cues evoke specific neural preparatory processes in cued task-switching paradigms. To deduce the functional role of these neural preparatory processes the majority of studies vary aspects of the experimental paradigm and describe how these variations alter markers of neural preparatory processes. Although these studies provide important insights, they also have notable limitations, particularly in terms of understanding the causal or functional relationship of neural markers to cognitive and behavioral processes. In this study, we sought to address these limitations and uncover the functional roles of neural processes by examining how variability in the amplitude of neural preparatory processes predicts behavioral performance to subsequent stimuli. To achieve this objective 16 young adults were recruited to perform a cued Stroop task while their brain activity was measured using high-density electroencephalography. Four temporally overlapping but functionally and topographically distinct cue-triggered event related potentials (ERPs) were identified: 1) A left-frontotemporal negativity (250-700 ms) that was positively associated with word-reading performance; 2) a midline-frontal negativity (450-800 ms) that was positively associated with color-naming and incongruent performance; 3) a left-frontal negativity (450-800 ms) that was positively associated with switch trial performance; and 4) a centroparietal positivity (450-800 ms) that was positively associated with performance for almost all trial types. These results suggest that at least four dissociable cognitive processes are evoked by instructional cues in the present task, including: 1) domain-specific task facilitation; 2) switch-specific task-set reconfiguration; 3) preparation for response conflict; and 4) proactive attentional control. Examining the relationship between ERPs and behavioral performance provides a functional link between neural markers and the cognitive processes they index.

Prom1 Function in Development, Intestinal Inflammation, and Intestinal Tumorigenesis

PubMed Central

Karim, Baktiar O.; Rhee, Ki-Jong; Liu, Guosheng; Yun, Kyuson; Brant, Steven R.

2014-01-01

Prom1/CD133 has been identified in colorectal, hepatocellular, and pancreatic cancer as a cancer stem cell marker and has been used as such to predict colon cancer recurrence in humans. Its potential molecular function as well as its role as a marker of intestinal regeneration is still not fully known. We evaluated the role of Prom1 in intestinal regeneration in inflammatory bowel disease (IBD), determined the function of Prom1, and characterized the effect of a lack of Prom1 on intestinal tumor formation in animal models. Our results suggest that Apc mutations lead to an increase in Prom1 expressing cells in the intestinal crypt stem cell compartment and in early intestinal adenomas. Also, Prom1 knockout mice are more susceptible to intestinal tumor formation. We conclude that Prom1 likely plays a role in regulating intestinal homeostasis and that these results clearly illustrate the role of Prom1 in intestinal regeneration. We further conclude that Prom1 may provide a novel therapeutic target for patients with gastrointestinal conditions such as IBD, short bowel syndrome, and colorectal cancer. PMID:25452936

The effect of using genealogy-based haplotypes for genomic prediction

PubMed Central

2013-01-01

Background Genomic prediction uses two sources of information: linkage disequilibrium between markers and quantitative trait loci, and additive genetic relationships between individuals. One way to increase the accuracy of genomic prediction is to capture more linkage disequilibrium by regression on haplotypes instead of regression on individual markers. The aim of this study was to investigate the accuracy of genomic prediction using haplotypes based on local genealogy information. Methods A total of 4429 Danish Holstein bulls were genotyped with the 50K SNP chip. Haplotypes were constructed using local genealogical trees. Effects of haplotype covariates were estimated with two types of prediction models: (1) assuming that effects had the same distribution for all haplotype covariates, i.e. the GBLUP method and (2) assuming that a large proportion (π) of the haplotype covariates had zero effect, i.e. a Bayesian mixture method. Results About 7.5 times more covariate effects were estimated when fitting haplotypes based on local genealogical trees compared to fitting individuals markers. Genealogy-based haplotype clustering slightly increased the accuracy of genomic prediction and, in some cases, decreased the bias of prediction. With the Bayesian method, accuracy of prediction was less sensitive to parameter π when fitting haplotypes compared to fitting markers. Conclusions Use of haplotypes based on genealogy can slightly increase the accuracy of genomic prediction. Improved methods to cluster the haplotypes constructed from local genealogy could lead to additional gains in accuracy. PMID:23496971

The effect of using genealogy-based haplotypes for genomic prediction.

PubMed

Edriss, Vahid; Fernando, Rohan L; Su, Guosheng; Lund, Mogens S; Guldbrandtsen, Bernt

2013-03-06

Genomic prediction uses two sources of information: linkage disequilibrium between markers and quantitative trait loci, and additive genetic relationships between individuals. One way to increase the accuracy of genomic prediction is to capture more linkage disequilibrium by regression on haplotypes instead of regression on individual markers. The aim of this study was to investigate the accuracy of genomic prediction using haplotypes based on local genealogy information. A total of 4429 Danish Holstein bulls were genotyped with the 50K SNP chip. Haplotypes were constructed using local genealogical trees. Effects of haplotype covariates were estimated with two types of prediction models: (1) assuming that effects had the same distribution for all haplotype covariates, i.e. the GBLUP method and (2) assuming that a large proportion (π) of the haplotype covariates had zero effect, i.e. a Bayesian mixture method. About 7.5 times more covariate effects were estimated when fitting haplotypes based on local genealogical trees compared to fitting individuals markers. Genealogy-based haplotype clustering slightly increased the accuracy of genomic prediction and, in some cases, decreased the bias of prediction. With the Bayesian method, accuracy of prediction was less sensitive to parameter π when fitting haplotypes compared to fitting markers. Use of haplotypes based on genealogy can slightly increase the accuracy of genomic prediction. Improved methods to cluster the haplotypes constructed from local genealogy could lead to additional gains in accuracy.

Genomic selection for slaughter age in pigs using the Cox frailty model.

PubMed

Santos, V S; Martins Filho, S; Resende, M D V; Azevedo, C F; Lopes, P S; Guimarães, S E F; Glória, L S; Silva, F F

2015-10-19

The aim of this study was to compare genomic selection methodologies using a linear mixed model and the Cox survival model. We used data from an F2 population of pigs, in which the response variable was the time in days from birth to the culling of the animal and the covariates were 238 markers [237 single nucleotide polymorphism (SNP) plus the halothane gene]. The data were corrected for fixed effects, and the accuracy of the method was determined based on the correlation of the ranks of predicted genomic breeding values (GBVs) in both models with the corrected phenotypic values. The analysis was repeated with a subset of SNP markers with largest absolute effects. The results were in agreement with the GBV prediction and the estimation of marker effects for both models for uncensored data and for normality. However, when considering censored data, the Cox model with a normal random effect (S1) was more appropriate. Since there was no agreement between the linear mixed model and the imputed data (L2) for the prediction of genomic values and the estimation of marker effects, the model S1 was considered superior as it took into account the latent variable and the censored data. Marker selection increased correlations between the ranks of predicted GBVs by the linear and Cox frailty models and the corrected phenotypic values, and 120 markers were required to increase the predictive ability for the characteristic analyzed.

Genetically informed ecological niche models improve climate change predictions.

PubMed

Ikeda, Dana H; Max, Tamara L; Allan, Gerard J; Lau, Matthew K; Shuster, Stephen M; Whitham, Thomas G

2017-01-01

We examined the hypothesis that ecological niche models (ENMs) more accurately predict species distributions when they incorporate information on population genetic structure, and concomitantly, local adaptation. Local adaptation is common in species that span a range of environmental gradients (e.g., soils and climate). Moreover, common garden studies have demonstrated a covariance between neutral markers and functional traits associated with a species' ability to adapt to environmental change. We therefore predicted that genetically distinct populations would respond differently to climate change, resulting in predicted distributions with little overlap. To test whether genetic information improves our ability to predict a species' niche space, we created genetically informed ecological niche models (gENMs) using Populus fremontii (Salicaceae), a widespread tree species in which prior common garden experiments demonstrate strong evidence for local adaptation. Four major findings emerged: (i) gENMs predicted population occurrences with up to 12-fold greater accuracy than models without genetic information; (ii) tests of niche similarity revealed that three ecotypes, identified on the basis of neutral genetic markers and locally adapted populations, are associated with differences in climate; (iii) our forecasts indicate that ongoing climate change will likely shift these ecotypes further apart in geographic space, resulting in greater niche divergence; (iv) ecotypes that currently exhibit the largest geographic distribution and niche breadth appear to be buffered the most from climate change. As diverse agents of selection shape genetic variability and structure within species, we argue that gENMs will lead to more accurate predictions of species distributions under climate change. © 2016 John Wiley & Sons Ltd.

[Clinical end-points and surrogate markers of pulmonary arterial hypertension in the light of evidence-based treatment].

PubMed

Can, Mehmet Mustafa; Kaymaz, Cihangir

2010-08-01

Pulmonary arterial hypertension (PAH) is a rare, fatal and progressive disease. There is an acceleration in the advent of new therapies in parallel to the development of the knowledge about etiogenesis and pathogenesis of PAH. Therefore, to optimize the goals of PAH-specific treatment and to determine the time to shift from monotherapy to combination therapy, simple, objective and reproducible end-points, which may predict the disease severity, progression rate and life expectancy are needed. The adventure of end points in PAH has started with six minute walk distance and functional capacity, and continues with new parameters (biochemical marker, time to clinical worsening, echocardiography and magnetic resonance imaging etc.), which can better reflect the clinical outcome.

Spiked GBS: A unified, open platform for single marker genotyping and whole-genome profiling

USDA-ARS?s Scientific Manuscript database

In plant breeding, there are two primary applications for DNA markers in selection: 1) selection of known genes using a single marker assay (marker-assisted selection; MAS); and 2) whole-genome profiling and prediction (genomic selection; GS). Typically, marker platforms have addressed only one of t...

The Physalis peruviana leaf transcriptome: assembly, annotation and gene model prediction

PubMed Central

2012-01-01

Background Physalis peruviana commonly known as Cape gooseberry is a member of the Solanaceae family that has an increasing popularity due to its nutritional and medicinal values. A broad range of genomic tools is available for other Solanaceae, including tomato and potato. However, limited genomic resources are currently available for Cape gooseberry. Results We report the generation of a total of 652,614 P. peruviana Expressed Sequence Tags (ESTs), using 454 GS FLX Titanium technology. ESTs, with an average length of 371 bp, were obtained from a normalized leaf cDNA library prepared using a Colombian commercial variety. De novo assembling was performed to generate a collection of 24,014 isotigs and 110,921 singletons, with an average length of 1,638 bp and 354 bp, respectively. Functional annotation was performed using NCBI’s BLAST tools and Blast2GO, which identified putative functions for 21,191 assembled sequences, including gene families involved in all the major biological processes and molecular functions as well as defense response and amino acid metabolism pathways. Gene model predictions in P. peruviana were obtained by using the genomes of Solanum lycopersicum (tomato) and Solanum tuberosum (potato). We predict 9,436 P. peruviana sequences with multiple-exon models and conserved intron positions with respect to the potato and tomato genomes. Additionally, to study species diversity we developed 5,971 SSR markers from assembled ESTs. Conclusions We present the first comprehensive analysis of the Physalis peruviana leaf transcriptome, which will provide valuable resources for development of genetic tools in the species. Assembled transcripts with gene models could serve as potential candidates for marker discovery with a variety of applications including: functional diversity, conservation and improvement to increase productivity and fruit quality. P. peruviana was estimated to be phylogenetically branched out before the divergence of five other Solanaceae family members, S. lycopersicum, S. tuberosum, Capsicum spp, S. melongena and Petunia spp. PMID:22533342

The Physalis peruviana leaf transcriptome: assembly, annotation and gene model prediction.

PubMed

Garzón-Martínez, Gina A; Zhu, Z Iris; Landsman, David; Barrero, Luz S; Mariño-Ramírez, Leonardo

2012-04-25

Physalis peruviana commonly known as Cape gooseberry is a member of the Solanaceae family that has an increasing popularity due to its nutritional and medicinal values. A broad range of genomic tools is available for other Solanaceae, including tomato and potato. However, limited genomic resources are currently available for Cape gooseberry. We report the generation of a total of 652,614 P. peruviana Expressed Sequence Tags (ESTs), using 454 GS FLX Titanium technology. ESTs, with an average length of 371 bp, were obtained from a normalized leaf cDNA library prepared using a Colombian commercial variety. De novo assembling was performed to generate a collection of 24,014 isotigs and 110,921 singletons, with an average length of 1,638 bp and 354 bp, respectively. Functional annotation was performed using NCBI's BLAST tools and Blast2GO, which identified putative functions for 21,191 assembled sequences, including gene families involved in all the major biological processes and molecular functions as well as defense response and amino acid metabolism pathways. Gene model predictions in P. peruviana were obtained by using the genomes of Solanum lycopersicum (tomato) and Solanum tuberosum (potato). We predict 9,436 P. peruviana sequences with multiple-exon models and conserved intron positions with respect to the potato and tomato genomes. Additionally, to study species diversity we developed 5,971 SSR markers from assembled ESTs. We present the first comprehensive analysis of the Physalis peruviana leaf transcriptome, which will provide valuable resources for development of genetic tools in the species. Assembled transcripts with gene models could serve as potential candidates for marker discovery with a variety of applications including: functional diversity, conservation and improvement to increase productivity and fruit quality. P. peruviana was estimated to be phylogenetically branched out before the divergence of five other Solanaceae family members, S. lycopersicum, S. tuberosum, Capsicum spp, S. melongena and Petunia spp.

Concise Review: Multifaceted Characterization of Human Mesenchymal Stem Cells for Use in Regenerative Medicine.

PubMed

Samsonraj, Rebekah M; Raghunath, Michael; Nurcombe, Victor; Hui, James H; van Wijnen, Andre J; Cool, Simon M

2017-12-01

Mesenchymal stem cells (MSC) hold great potential for regenerative medicine because of their ability for self-renewal and differentiation into tissue-specific cells such as osteoblasts, chondrocytes, and adipocytes. MSCs orchestrate tissue development, maintenance and repair, and are useful for musculoskeletal regenerative therapies to treat age-related orthopedic degenerative diseases and other clinical conditions. Importantly, MSCs produce secretory factors that play critical roles in tissue repair that support both engraftment and trophic functions (autocrine and paracrine). The development of uniform protocols for both preparation and characterization of MSCs, including standardized functional assays for evaluation of their biological potential, are critical factors contributing to their clinical utility. Quality control and release criteria for MSCs should include cell surface markers, differentiation potential, and other essential cell parameters. For example, cell surface marker profiles (surfactome), bone-forming capacities in ectopic and orthotopic models, as well as cell size and granularity, telomere length, senescence status, trophic factor secretion (secretome), and immunomodulation, should be thoroughly assessed to predict MSC utility for regenerative medicine. We propose that these and other functionalities of MSCs should be characterized prior to use in clinical applications as part of comprehensive and uniform guidelines and release criteria for their clinical-grade production to achieve predictably favorable treatment outcomes for stem cell therapy. Stem Cells Translational Medicine 2017;6:2173-2185. © 2017 The Authors Stem Cells Translational Medicine published by Wiley Periodicals, Inc. on behalf of AlphaMed Press.

Prediction of miscarriage in women with viable intrauterine pregnancy-A systematic review and diagnostic accuracy meta-analysis.

PubMed

Pillai, Rekha N; Konje, Justin C; Richardson, Matthew; Tincello, Douglas G; Potdar, Neelam

2018-01-01

Both ultrasound and biochemical markers either alone or in combination have been described in the literature for the prediction of miscarriage. We performed this systematic review and meta-analysis to determine the best combination of biochemical, ultrasound and demographic markers to predict miscarriage in women with viable intrauterine pregnancy. The electronic database search included Medline (1946-June 2017), Embase (1980-June 2017), CINAHL (1981-June 2017) and Cochrane library. Key MESH and Boolean terms were used for the search. Data extraction and collection was performed based on the eligibility criteria by two authors independently. Quality assessment of the individual studies was done using QUADAS 2 (Quality Assessment for Diagnostic Accuracy Studies-2: A Revised Tool) and statistical analysis performed using the Cochrane systematic review manager 5.3 and STATA vs.13.0. Due to the diversity of the combinations used for prediction in the included papers it was not possible to perform a meta-analysis on combination markers. Therefore, we proceeded to perform a meta-analysis on ultrasound markers alone to determine the best marker that can help to improve the diagnostic accuracy of predicting miscarriage in women with viable intrauterine pregnancy. The systematic review identified 18 eligible studies for the quantitative meta-analysis with a total of 5584 women. Among the ultrasound scan markers, fetal bradycardia (n=10 studies, n=1762 women) on hierarchical summary receiver operating characteristic showed sensitivity of 68.41%, specificity of 97.84%, positive likelihood ratio of 31.73 (indicating a large effect on increasing the probability of predicting miscarriage) and negative likelihood ratio of 0.32. In studies for women with threatened miscarriage (n=5 studies, n=771 women) fetal bradycardia showed further increase in sensitivity (84.18%) for miscarriage prediction. Although there is gestational age dependent variation in the fetal heart rate, a plot of fetal heart rate cut off level versus log diagnostic odds ratio showed that at ≤110 beat per minutes the diagnostic power to predict miscarriage is higher. Other markers of intra uterine hematoma, crown rump length and yolk sac had significantly decreased predictive value. Therefore in women with threatened miscarriage and presence of fetal bradycardia on ultrasound scan, there is a role for offering repeat ultrasound scan in a week to ten days interval. Crown Copyright © 2017. Published by Elsevier B.V. All rights reserved.

Amygdala functional connectivity as a longitudinal biomarker of symptom changes in generalized anxiety.

PubMed

Makovac, Elena; Watson, David R; Meeten, Frances; Garfinkel, Sarah N; Cercignani, Mara; Critchley, Hugo D; Ottaviani, Cristina

2016-11-01

Generalized anxiety disorder (GAD) is characterized by excessive worry, autonomic dysregulation and functional amygdala dysconnectivity, yet these illness markers have rarely been considered together, nor their interrelationship tested longitudinally. We hypothesized that an individual's capacity for emotion regulation predicts longer-term changes in amygdala functional connectivity, supporting the modification of GAD core symptoms. Sixteen patients with GAD (14 women) and individually matched controls were studied at two time points separated by 1 year. Resting-state fMRI data and concurrent measurement of vagally mediated heart rate variability were obtained before and after the induction of perseverative cognition. A greater rise in levels of worry following the induction predicted a stronger reduction in connectivity between right amygdala and ventromedial prefrontal cortex, and enhanced coupling between left amygdala and ventral tegmental area at follow-up. Similarly, amplified physiological responses to the induction predicted increased connectivity between right amygdala and thalamus. Longitudinal shifts in a distinct set of functional connectivity scores were associated with concomitant changes in GAD symptomatology over the course of the year. Results highlight the prognostic value of indices of emotional dysregulation and emphasize the integral role of the amygdala as a critical hub in functional neural circuitry underlying the progression of GAD symptomatology. © The Author (2016). Published by Oxford University Press.

Can we predict age at natural menopause using ovarian reserve tests or mother's age at menopause? A systematic literature review.

PubMed

Depmann, Martine; Broer, Simone L; van der Schouw, Yvonne T; Tehrani, Fahimeh R; Eijkemans, Marinus J; Mol, Ben W; Broekmans, Frank J

2016-02-01

This review aimed to appraise data on prediction of age at natural menopause (ANM) based on antimüllerian hormone (AMH), antral follicle count (AFC), and mother's ANM to evaluate clinical usefulness and to identify directions for further research. We conducted three systematic reviews of the literature to identify studies of menopause prediction based on AMH, AFC, or mother's ANM, corrected for baseline age. Six studies selected in the search for AMH all consistently demonstrated AMH as being capable of predicting ANM (hazard ratio, 5.6-9.2). The sole study reporting on mother's ANM indicated that AMH was capable of predicting ANM (hazard ratio, 9.1-9.3). Two studies provided analyses of AFC and yielded conflicting results, making this marker less strong. AMH is currently the most promising marker for ANM prediction. The predictive capacity of mother's ANM demonstrated in a single study makes this marker a promising contributor to AMH for menopause prediction. Models, however, do not predict the extremes of menopause age very well and have wide prediction interval. These markers clearly need improvement before they can be used for individual prediction of menopause in the clinical setting. Moreover, potential limitations for such use include variations in AMH assays used and a lack of correction for factors or diseases affecting AMH levels or ANM. Future studies should include women of a broad age range (irrespective of cycle regularity) and should base predictions on repeated AMH measurements. Furthermore, currently unknown candidate predictors need to be identified.

Hyperglycemic clamp and oral glucose tolerance test for 3-year prediction of clinical onset in persistently autoantibody-positive offspring and siblings of type 1 diabetic patients.

PubMed

Balti, Eric V; Vandemeulebroucke, Evy; Weets, Ilse; Van De Velde, Ursule; Van Dalem, Annelien; Demeester, Simke; Verhaeghen, Katrijn; Gillard, Pieter; De Block, Christophe; Ruige, Johannes; Keymeulen, Bart; Pipeleers, Daniel G; Decochez, Katelijn; Gorus, Frans K

2015-02-01

In preparation of future prevention trials, we aimed to identify predictors of 3-year diabetes onset among oral glucose tolerance test (OGTT)- and hyperglycemic clamp-derived metabolic markers in persistently islet autoantibody positive (autoAb(+)) offspring and siblings of patients with type 1 diabetes (T1D). The design is a registry-based study. Functional tests were performed in a hospital setting. Persistently autoAb(+) first-degree relatives of patients with T1D (n = 81; age 5-39 years). We assessed 3-year predictive ability of OGTT- and clamp-derived markers using receiver operating characteristics (ROC) and Cox regression analysis. Area under the curve of clamp-derived first-phase C-peptide release (AUC(5-10 min); min 5-10) was determined in all relatives and second-phase release (AUC(120-150 min); min 120-150) in those aged 12-39 years (n = 62). Overall, the predictive ability of AUC(5-10 min) was better than that of peak C-peptide, the best predictor among OGTT-derived parameters (ROC-AUC [95%CI]: 0.89 [0.80-0.98] vs 0.81 [0.70-0.93]). Fasting blood glucose (FBG) and AUC(5-10 min) provided the best combination of markers for prediction of diabetes within 3 years; (ROC-AUC [95%CI]: 0.92 [0.84-1.00]). In multivariate Cox regression analysis, AUC(5-10 min)) (P = .001) was the strongest independent predictor and interacted significantly with all tested OGTT-derived parameters. AUC(5-10 min) below percentile 10 of controls was associated with 50-70% progression to T1D regardless of age. Similar results were obtained for AUC(120-150 min). Clamp-derived first-phase C-peptide release can be used as an efficient and simple screening strategy in persistently autoAb(+) offspring and siblings of T1D patients to predict impending diabetes.

Marker genes that are less conserved in their sequences are useful for predicting genome-wide similarity levels between closely related prokaryotic strains

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

Lan, Yemin; Rosen, Gail; Hershberg, Ruth

The 16s rRNA gene is so far the most widely used marker for taxonomical classification and separation of prokaryotes. Since it is universally conserved among prokaryotes, it is possible to use this gene to classify a broad range of prokaryotic organisms. At the same time, it has often been noted that the 16s rRNA gene is too conserved to separate between prokaryotes at finer taxonomic levels. In this paper, we examine how well levels of similarity of 16s rRNA and 73 additional universal or nearly universal marker genes correlate with genome-wide levels of gene sequence similarity. We demonstrate that themore » percent identity of 16s rRNA predicts genome-wide levels of similarity very well for distantly related prokaryotes, but not for closely related ones. In closely related prokaryotes, we find that there are many other marker genes for which levels of similarity are much more predictive of genome-wide levels of gene sequence similarity. Finally, we show that the identities of the markers that are most useful for predicting genome-wide levels of similarity within closely related prokaryotic lineages vary greatly between lineages. However, the most useful markers are always those that are least conserved in their sequences within each lineage. In conclusion, our results show that by choosing markers that are less conserved in their sequences within a lineage of interest, it is possible to better predict genome-wide gene sequence similarity between closely related prokaryotes than is possible using the 16s rRNA gene. We point readers towards a database we have created (POGO-DB) that can be used to easily establish which markers show lowest levels of sequence conservation within different prokaryotic lineages.« less

Marker genes that are less conserved in their sequences are useful for predicting genome-wide similarity levels between closely related prokaryotic strains

DOE PAGES

Lan, Yemin; Rosen, Gail; Hershberg, Ruth

2016-05-03

The 16s rRNA gene is so far the most widely used marker for taxonomical classification and separation of prokaryotes. Since it is universally conserved among prokaryotes, it is possible to use this gene to classify a broad range of prokaryotic organisms. At the same time, it has often been noted that the 16s rRNA gene is too conserved to separate between prokaryotes at finer taxonomic levels. In this paper, we examine how well levels of similarity of 16s rRNA and 73 additional universal or nearly universal marker genes correlate with genome-wide levels of gene sequence similarity. We demonstrate that themore » percent identity of 16s rRNA predicts genome-wide levels of similarity very well for distantly related prokaryotes, but not for closely related ones. In closely related prokaryotes, we find that there are many other marker genes for which levels of similarity are much more predictive of genome-wide levels of gene sequence similarity. Finally, we show that the identities of the markers that are most useful for predicting genome-wide levels of similarity within closely related prokaryotic lineages vary greatly between lineages. However, the most useful markers are always those that are least conserved in their sequences within each lineage. In conclusion, our results show that by choosing markers that are less conserved in their sequences within a lineage of interest, it is possible to better predict genome-wide gene sequence similarity between closely related prokaryotes than is possible using the 16s rRNA gene. We point readers towards a database we have created (POGO-DB) that can be used to easily establish which markers show lowest levels of sequence conservation within different prokaryotic lineages.« less

Development of a gene-centered ssr atlas as a resource for papaya (Carica papaya) marker-assisted selection and population genetic studies.

PubMed

Vidal, Newton Medeiros; Grazziotin, Ana Laura; Ramos, Helaine Christine Cancela; Pereira, Messias Gonzaga; Venancio, Thiago Motta

2014-01-01

Carica papaya (papaya) is an economically important tropical fruit. Molecular marker-assisted selection is an inexpensive and reliable tool that has been widely used to improve fruit quality traits and resistance against diseases. In the present study we report the development and validation of an atlas of papaya simple sequence repeat (SSR) markers. We integrated gene predictions and functional annotations to provide a gene-centered perspective for marker-assisted selection studies. Our atlas comprises 160,318 SSRs, from which 21,231 were located in genic regions (i.e. inside exons, exon-intron junctions or introns). A total of 116,453 (72.6%) of all identified repeats were successfully mapped to one of the nine papaya linkage groups. Primer pairs were designed for markers from 9,594 genes (34.5% of the papaya gene complement). Using papaya-tomato orthology assessments, we assembled a list of 300 genes (comprising 785 SSRs) potentially involved in fruit ripening. We validated our atlas by screening 73 SSR markers (including 25 fruit ripening genes), achieving 100% amplification rate and uncovering 26% polymorphism rate between the parental genotypes (Sekati and JS12). The SSR atlas presented here is the first comprehensive gene-centered collection of annotated and genome positioned papaya SSRs. These features combined with thousands of high-quality primer pairs make the atlas an important resource for the papaya research community.

Genome wide selection in Citrus breeding.

PubMed

Gois, I B; Borém, A; Cristofani-Yaly, M; de Resende, M D V; Azevedo, C F; Bastianel, M; Novelli, V M; Machado, M A

2016-10-17

Genome wide selection (GWS) is essential for the genetic improvement of perennial species such as Citrus because of its ability to increase gain per unit time and to enable the efficient selection of characteristics with low heritability. This study assessed GWS efficiency in a population of Citrus and compared it with selection based on phenotypic data. A total of 180 individual trees from a cross between Pera sweet orange (Citrus sinensis Osbeck) and Murcott tangor (Citrus sinensis Osbeck x Citrus reticulata Blanco) were evaluated for 10 characteristics related to fruit quality. The hybrids were genotyped using 5287 DArT_seq TM (diversity arrays technology) molecular markers and their effects on phenotypes were predicted using the random regression - best linear unbiased predictor (rr-BLUP) method. The predictive ability, prediction bias, and accuracy of GWS were estimated to verify its effectiveness for phenotype prediction. The proportion of genetic variance explained by the markers was also computed. The heritability of the traits, as determined by markers, was 16-28%. The predictive ability of these markers ranged from 0.53 to 0.64, and the regression coefficients between predicted and observed phenotypes were close to unity. Over 35% of the genetic variance was accounted for by the markers. Accuracy estimates with GWS were lower than those obtained by phenotypic analysis; however, GWS was superior in terms of genetic gain per unit time. Thus, GWS may be useful for Citrus breeding as it can predict phenotypes early and accurately, and reduce the length of the selection cycle. This study demonstrates the feasibility of genomic selection in Citrus.

A proof-of-principle simulation for closed-loop control based on preexisting experimental thalamic DBS-enhanced instrumental learning.

PubMed

Wang, Ching-Fu; Yang, Shih-Hung; Lin, Sheng-Huang; Chen, Po-Chuan; Lo, Yu-Chun; Pan, Han-Chi; Lai, Hsin-Yi; Liao, Lun-De; Lin, Hui-Ching; Chen, Hsu-Yan; Huang, Wei-Chen; Huang, Wun-Jhu; Chen, You-Yin

Deep brain stimulation (DBS) has been applied as an effective therapy for treating Parkinson's disease or essential tremor. Several open-loop DBS control strategies have been developed for clinical experiments, but they are limited by short battery life and inefficient therapy. Therefore, many closed-loop DBS control systems have been designed to tackle these problems by automatically adjusting the stimulation parameters via feedback from neural signals, which has been reported to reduce the power consumption. However, when the association between the biomarkers of the model and stimulation is unclear, it is difficult to develop an optimal control scheme for other DBS applications, i.e., DBS-enhanced instrumental learning. Furthermore, few studies have investigated the effect of closed-loop DBS control for cognition function, such as instrumental skill learning, and have been implemented in simulation environments. In this paper, we proposed a proof-of-principle design for a closed-loop DBS system, cognitive-enhancing DBS (ceDBS), which enhanced skill learning based on in vivo experimental data. The ceDBS acquired local field potential (LFP) signal from the thalamic central lateral (CL) nuclei of animals through a neural signal processing system. A strong coupling of the theta oscillation (4-7 Hz) and the learning period was found in the water reward-related lever-pressing learning task. Therefore, the theta-band power ratio, which was the averaged theta band to averaged total band (1-55 Hz) power ratio, could be used as a physiological marker for enhancement of instrumental skill learning. The on-line extraction of the theta-band power ratio was implemented on a field-programmable gate array (FPGA). An autoregressive with exogenous inputs (ARX)-based predictor was designed to construct a CL-thalamic DBS model and forecast the future physiological marker according to the past physiological marker and applied DBS. The prediction could further assist the design of a closed-loop DBS controller. A DBS controller based on a fuzzy expert system was devised to automatically control DBS according to the predicted physiological marker via a set of rules. The simulated experimental results demonstrate that the ceDBS based on the closed-loop control architecture not only reduced power consumption using the predictive physiological marker, but also achieved a desired level of physiological marker through the DBS controller. Copyright © 2017 Elsevier Inc. All rights reserved.

Investigation of apoptosis-related gene expression levels in preimplantation biopsies as predictors of delayed kidney graft function.

PubMed

Goncalves-Primo, Amador; Mourão, Tuíla B; Andrade-Oliveira, Vinícius; Campos, Erika F; Medina-Pestana, José O; Tedesco-Silva, Hélio; Gerbase-DeLima, Maria

2014-06-27

The purpose of this study was to investigate the expression of the gene coding for the antiapoptotic molecule Bcl-2, the proapoptotic molecule Bax, and the apoptosis executor enzyme caspase-3 in preimplantation renal biopsies (PIB) as markers for delayed graft function. In this prospective single-center study, gene expression levels were evaluated using real-time TaqMan polymerase chain reaction in PIB of kidneys from 72 deceased donors (DDs) and 18 living donors (LDs). CASP3 and BAX expression levels were higher, whereas those of BCL2 were lower, in DD than in LD PIB. In biopsies from DD, BCL2 levels were lower in cases with DGF, whereas no differences were observed concerning CASP3 and BAX. The BAX/BCL2 gene expression ratio greater than 2.29 associated with DGF with an odds ratio of 2.00. A multiple regression analysis including data of TLR4 expression in the first day posttransplant PB from a previous study of our group conducted in the same patients revealed a very strong association of the combination of BAX/BCL2 greater than 2.3 in PIB and TLR4 of 0.95 uRE or lesser in PB with the occurrence of DGF, with OR of 120 and positive and negative predictive values of 91% and 92%, respectively. The power to predict DGF of the combination of high BAX/BCL2 expression in PIB and low TLR4 expression in the first day posttransplant peripheral blood observed in the present study is extremely high, in comparison to any other marker or combinations of markers so far published in the literature.

Hopelessness and cognitive impairment are risk markers for mortality in systolic heart failure patients.

PubMed

Byrne, Claire J; Toukhsati, Samia R; Toia, Deidre; O'Halloran, Paul D; Hare, David L

2018-06-01

Depression exacerbates the burden of heart failure and independently predicts mortality. The aim of this study was to investigate which specific symptoms of depression predict all-cause mortality in systolic heart failure patients. Consecutive outpatients with heart failure and impaired left ventricular ejection fraction (LVEF), attending an Australian metropolitan heart function clinic between 2001 and 2011, were enrolled. The Cardiac Depression Scale (CDS) was completed as a component of usual care. Baseline clinical characteristics were drawn from hospital databases. The primary end-point was all-cause mortality, obtained from the Australian National Death Index. A total of 324 patients (68.5% male) were included (mean age at enrolment = 66.8 ± 14.36 years), with a median follow-up time of 6.7 years (95% CI 5.97-7.39) and a mortality rate of 50% by the census date. Mean LVEF = 31.0 ± 11.31%, with 25% having NYHA functional class of III or IV. Factor analysis of the CDS extracted six symptom dimensions: Hopelessness, Cognitive Impairment, Anhedonia/Mood, Irritability, Worry, and Sleep Disturbance. Cox regression analyses identified Hopelessness (HR 1.024, 95% CI 1.004-1.045, p = .018) and Cognitive Impairment (HR 1.048, 95% CI 1.005-1.093, p = .028) as independent risk markers of all-cause mortality, following adjustment of known prognostic clinical factors. Hopelessness and cognitive impairment are stronger risk markers for all-cause mortality than other symptoms of depression in systolic heart failure. These data will allow more specific risk assessment and potentially new targets for more effective treatment and management of depression in this population. Copyright © 2018 Elsevier Inc. All rights reserved.

Validity, prognostic value and optimal cutoff of respiratory muscle strength in patients with chronic heart failure changes with beta-blocker treatment.

PubMed

Frankenstein, Lutz; Nelles, Manfred; Meyer, F Joachim; Sigg, Caroline; Schellberg, Dieter; Remppis, B Andrew; Katus, Hugo A; Zugck, Christian

2009-08-01

Training studies frequently use maximum inspiratory mouth occlusion pressure (PImax) as a therapeutic target and surrogate marker. For patients on beta-blocker (BBL), prognostic data allowing this extrapolation do not exist. Furthermore, the effects of BBL, mainstay of modern chronic heart failure therapy, on respiratory muscle function remain controversial. Finally, no proper separate cutoff according to treatment exists. Prospective, observational inclusion of patients with stable systolic chronic heart failure and recording of 1 year and all-time mortality for endpoint analysis. In 686 patients, 81% men, 494 patients on BBL, PImax was measured along with clinical evaluation. The median follow-up was 50 months (interquartile range: 26-75 months). Patients with or without BBL did not differ significantly for PImax, percentage of predicted PImax or other marker of disease severity. PImax was a significant (hazard ratio: 0.925; 95% confidence interval: 0.879-0.975; chi(2): 8.62) marker of adverse outcome, independent of BBL-status or aetiology. Percentage of predicted PImax was not independent of PImax. The cutoff identified through receiver-operated characteristics for 1-year mortality was 4.14 kPa for patients on BBL and 7.29 kPa for patients not on BBL. When separated accordingly, 1-year mortality was 8.5 versus 21.4%, P=0.02, for patients not on BBL and 4.3 versus 16.2%, P<0.001, for patients on BBL. This study fills the gap between trials targeting respiratory muscle on a functional basis and the resultant prognostic information with regard to BBL. BBL lowered the optimal PImax cutoff values for risk stratification without changing the measured values of PImax. This should be considered at inclusion and evaluation of trials and interpretation of exercise parameters.

Psychosis prediction and clinical utility in familial high-risk studies: Selective review, synthesis, and implications for early detection and intervention

PubMed Central

Shah, Jai L.; Tandon, Neeraj; Keshavan, Matcheri S.

2016-01-01

Aim Accurate prediction of which individuals will go on to develop psychosis would assist early intervention and prevention paradigms. We sought to review investigations of prospective psychosis prediction based on markers and variables examined in longitudinal familial high-risk (FHR) studies. Methods We performed literature searches in MedLine, PubMed and PsycINFO for articles assessing performance characteristics of predictive clinical tests in FHR studies of psychosis. Studies were included if they reported one or more predictive variables in subjects at FHR for psychosis. We complemented this search strategy with references drawn from articles, reviews, book chapters and monographs. Results Across generations of familial high-risk projects, predictive studies have investigated behavioral, cognitive, psychometric, clinical, neuroimaging, and other markers. Recent analyses have incorporated multivariate and multi-domain approaches to risk ascertainment, although with still generally modest results. Conclusions While a broad range of risk factors has been identified, no individual marker or combination of markers can at this time enable accurate prospective prediction of emerging psychosis for individuals at FHR. We outline the complex and multi-level nature of psychotic illness, the myriad of factors influencing its development, and methodological hurdles to accurate and reliable prediction. Prospects and challenges for future generations of FHR studies are discussed in the context of early detection and intervention strategies. PMID:23693118

Genome-enabled prediction models for yield related traits in chickpea

USDA-ARS?s Scientific Manuscript database

Genomic selection (GS) unlike marker-assisted backcrossing (MABC) predicts breeding values of lines using genome-wide marker profiling and allows selection of lines prior to field-phenotyping, thereby shortening the breeding cycle. A collection of 320 elite breeding lines was selected and phenotyped...

TARGET Research Goals

Cancer.gov

TARGET researchers use various sequencing and array-based methods to examine the genomes, transcriptomes, and for some diseases epigenomes of select childhood cancers. This “multi-omic” approach generates a comprehensive profile of molecular alterations for each cancer type. Alterations are changes in DNA or RNA, such as rearrangements in chromosome structure or variations in gene expression, respectively. Through computational analyses and assays to validate biological function, TARGET researchers predict which alterations disrupt the function of a gene or pathway and promote cancer growth, progression, and/or survival. Researchers identify candidate therapeutic targets and/or prognostic markers from the cancer-associated alterations.

Prefrontal mediation of the reading network predicts intervention response in dyslexia.

PubMed

Aboud, Katherine S; Barquero, Laura A; Cutting, Laurie E

2018-04-01

A primary challenge facing the development of interventions for dyslexia is identifying effective predictors of intervention response. While behavioral literature has identified core cognitive characteristics of response, the distinction of reading versus executive cognitive contributions to response profiles remains unclear, due in part to the difficulty of segregating these constructs using behavioral outputs. In the current study we used functional neuroimaging to piece apart the mechanisms of how/whether executive and reading network relationships are predictive of intervention response. We found that readers who are responsive to intervention have more typical pre-intervention functional interactions between executive and reading systems compared to nonresponsive readers. These findings suggest that intervention response in dyslexia is influenced not only by domain-specific reading regions, but also by contributions from intervening domain-general networks. Our results make a significant gain in identifying predictive bio-markers of outcomes in dyslexia, and have important implications for the development of personalized clinical interventions. Copyright © 2018 Elsevier Ltd. All rights reserved.

Nonparametric method for genomics-based prediction of performance of quantitative traits involving epistasis in plant breeding.

PubMed

Sun, Xiaochun; Ma, Ping; Mumm, Rita H

2012-01-01

Genomic selection (GS) procedures have proven useful in estimating breeding value and predicting phenotype with genome-wide molecular marker information. However, issues of high dimensionality, multicollinearity, and the inability to deal effectively with epistasis can jeopardize accuracy and predictive ability. We, therefore, propose a new nonparametric method, pRKHS, which combines the features of supervised principal component analysis (SPCA) and reproducing kernel Hilbert spaces (RKHS) regression, with versions for traits with no/low epistasis, pRKHS-NE, to high epistasis, pRKHS-E. Instead of assigning a specific relationship to represent the underlying epistasis, the method maps genotype to phenotype in a nonparametric way, thus requiring fewer genetic assumptions. SPCA decreases the number of markers needed for prediction by filtering out low-signal markers with the optimal marker set determined by cross-validation. Principal components are computed from reduced marker matrix (called supervised principal components, SPC) and included in the smoothing spline ANOVA model as independent variables to fit the data. The new method was evaluated in comparison with current popular methods for practicing GS, specifically RR-BLUP, BayesA, BayesB, as well as a newer method by Crossa et al., RKHS-M, using both simulated and real data. Results demonstrate that pRKHS generally delivers greater predictive ability, particularly when epistasis impacts trait expression. Beyond prediction, the new method also facilitates inferences about the extent to which epistasis influences trait expression.

Nonparametric Method for Genomics-Based Prediction of Performance of Quantitative Traits Involving Epistasis in Plant Breeding

PubMed Central

Sun, Xiaochun; Ma, Ping; Mumm, Rita H.

2012-01-01

Genomic selection (GS) procedures have proven useful in estimating breeding value and predicting phenotype with genome-wide molecular marker information. However, issues of high dimensionality, multicollinearity, and the inability to deal effectively with epistasis can jeopardize accuracy and predictive ability. We, therefore, propose a new nonparametric method, pRKHS, which combines the features of supervised principal component analysis (SPCA) and reproducing kernel Hilbert spaces (RKHS) regression, with versions for traits with no/low epistasis, pRKHS-NE, to high epistasis, pRKHS-E. Instead of assigning a specific relationship to represent the underlying epistasis, the method maps genotype to phenotype in a nonparametric way, thus requiring fewer genetic assumptions. SPCA decreases the number of markers needed for prediction by filtering out low-signal markers with the optimal marker set determined by cross-validation. Principal components are computed from reduced marker matrix (called supervised principal components, SPC) and included in the smoothing spline ANOVA model as independent variables to fit the data. The new method was evaluated in comparison with current popular methods for practicing GS, specifically RR-BLUP, BayesA, BayesB, as well as a newer method by Crossa et al., RKHS-M, using both simulated and real data. Results demonstrate that pRKHS generally delivers greater predictive ability, particularly when epistasis impacts trait expression. Beyond prediction, the new method also facilitates inferences about the extent to which epistasis influences trait expression. PMID:23226325

Structure-Based Design of Inhibitors to the Cytotoxin Ricin

DTIC Science & Technology

2006-07-01

markers for the receptor may be predicted by these programs. To follow up on this experiment, we began to screen a large commercial data base, the...of the Huisgen thermal [3+2] cycloaddition reaction (Table 1). The advantages of this click chemistry approach include the potential for favorable...41, 2113-2116. Hartmuth C. Kolb, M. G. F. K. B. S. (2001). Click Chemistry: Diverse Chemical Function from a Few Good Reactions . Angewandte

Circulating metabolomic profile can predict dyslipidemia in HIV patients undergoing antiretroviral therapy.

PubMed

Rodríguez-Gallego, Esther; Gómez, Josep; Domingo, Pere; Ferrando-Martínez, Sara; Peraire, Joaquim; Viladés, Consuelo; Veloso, Sergi; López-Dupla, Miguel; Beltrán-Debón, Raúl; Alba, Verónica; Vargas, Montserrat; Castellano, Alfonso J; Leal, Manuel; Pacheco, Yolanda María; Ruiz-Mateos, Ezequiel; Gutiérrez, Félix; Vidal, Francesc; Rull, Anna

2018-06-01

Dyslipidemia in HIV-infected patients is unique and pathophysiologically associated with host factors, HIV itself and the use of antiretroviral therapy (ART). The use of nuclear magnetic resonance spectroscopy (NMR) provides additional data to conventional lipid measurements concerning the number of lipoprotein subclasses and particle sizes. To investigate the ability of lipoprotein profile, we used a circulating metabolomic approach in a cohort of 103 ART-naive HIV-infected patients, who were initiating non-nucleoside analogue transcriptase inhibitor (NNRTI)-based ART, and we subsequently followed up these patients for 36 months. Univariate and multivariate analyses were performed to evaluate the predictive power of NMR spectroscopy. VLDL-metabolism (including VLDL lipid concentrations, sizes, and particle numbers), total triglycerides and lactate levels resulted in good classifiers of dyslipidemia (AUC 0.903). Total particles/HDL-P ratio was significantly higher in ART-associated dyslipidemia compared to ART-normolipidemia (p = 0.001). Large VLDL-Ps were positively associated with both LDL-triglycerides (ρ 0.682, p < 0.001) and lactate concentrations (ρ 0.416, p < 0.001), the last one a marker of mitochondrial low oxidative capacity. Our data suggest that circulating metabolites have better predictive values for HIV/ART-related dyslipidemia onset than do the biochemical markers associated with conventional lipid measurements. NMR identifies changes in VLDL-P, lactate and LDL-TG as potential clinical markers of baseline HIV-dyslipidemia predisposition. Differences in circulating metabolomics, especially differences in particle size, are indicators of important derangements of mitochondrial function that are linked to ART-related dyslipidemia. Copyright © 2018 The Authors. Published by Elsevier B.V. All rights reserved.

Leaders and followers in adolescent close friendships: Susceptibility to peer influence as a predictor of risky behavior, friendship instability, and depression

PubMed Central

ALLEN, JOSEPH P.; PORTER, MARYFRANCES R.; MCFARLAND, F. CHRISTY

2006-01-01

Adolescents’ susceptibility to peer influence was examined as a marker of difficulties in the general process of autonomy development that was likely to be related to deficits across multiple domains of psychosocial functioning. A laboratory-based assessment of susceptibility to peer influence in interactions with a close friend was developed and examined in relation to corollary reports obtained from adolescents, their mothers, and close peers at ages 13 and 14. As hypothesized, observed susceptibility to peer influence with a close friend predicted future responses to negative peer pressure, but it was also related to broader markers of problems in functioning, including decreases in popularity, and increasing levels of depressive symptoms, over time. Susceptibility to peer influence was also linked to higher concurrent levels of substance use, externalizing behavior, and sexual activity. Results are interpreted as reflecting the central role of establishing autonomy with peers in psychosocial development. PMID:16478557

S100b and BNP predict functional neurological outcome after intracerebral hemorrhage

PubMed Central

James, Michael L.; Blessing, Robert; Phillips-Bute, Barbara G.; Bennett, Ellen; Laskowitz, Daniel T.

2009-01-01

Objective To determine the predictive value of S100b and brain natriuretic peptide (BNP) to accurately and quickly determine discharge prognosis after primary supratentorial intracerebral hemorrhage (ICH). Methods After IRB approval and informed consent, blood samples were obtained and analyzed from 28 adult patients consecutively admitted to the neuroscience intensive care unit with computed tomography-proven supratentorial ICH from June 2003 and December 2004 within the first 24 h after symptom onset for S100b and BNP. Functional outcomes on discharge were dichotomized to favorable (mRS<3) or unfavorable. Results BNP (a neurohormone) and S100b (a marker of glial activation) were found to be independently highly predictive of functional neurological outcome at the time of discharge as measured by modified Rankin Score (BNP:p<0.01, r=0.46; S100b: p<0.01, r=0.42) and Barthel Index (BNP:p<0.01, r=0.54; s100b:p<0.01, r=0.50). Although inclusion of either biomarker produced additive value when included with traditional clinical prognostic variables, such as the ICH Score (Barthel index: p<0.01, r=0.66; mRS:p<0.01, r=0.96), little predictive power is added with inclusion of both biomarkers in a regression model for neurological outcome. Conclusions Serum S100b and BNP levels in the first 24 h after injury accurately predict neurological function at discharge after supratentorial ICH. PMID:19505208

Inflamm-aging does not simply reflect increases in pro-inflammatory markers.

PubMed

Morrisette-Thomas, Vincent; Cohen, Alan A; Fülöp, Tamàs; Riesco, Éléonor; Legault, Véronique; Li, Qing; Milot, Emmanuel; Dusseault-Bélanger, Françis; Ferrucci, Luigi

2014-07-01

Many biodemographic studies use biomarkers of inflammation to understand or predict chronic disease and aging. Inflamm-aging, i.e. chronic low-grade inflammation during aging, is commonly characterized by pro-inflammatory biomarkers. However, most studies use just one marker at a time, sometimes leading to conflicting results due to complex interactions among the markers. A multidimensional approach allows a more robust interpretation of the various relationships between the markers. We applied principal component analysis (PCA) to 19 inflammatory biomarkers from the InCHIANTI study. We identified a clear, stable structure among the markers, with the first axis explaining inflammatory activation (both pro- and anti-inflammatory markers loaded strongly and positively) and the second axis innate immune response. The first but not the second axis was strongly correlated with age (r=0.56, p<0.0001, r=0.08 p=0.053), and both were strongly predictive of mortality (hazard ratios per PCA unit (95% CI): 1.33 (1.16-1.53) and 0.87 (0.76-0.98) respectively) and multiple chronic diseases, but in opposite directions. Both axes were more predictive than any individual markers for baseline chronic diseases and mortality. These results show that PCA can uncover a novel biological structure in the relationships among inflammatory markers, and that key axes of this structure play important roles in chronic disease. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Draft Sequences of the Radish (Raphanus sativus L.) Genome

PubMed Central

Kitashiba, Hiroyasu; Li, Feng; Hirakawa, Hideki; Kawanabe, Takahiro; Zou, Zhongwei; Hasegawa, Yoichi; Tonosaki, Kaoru; Shirasawa, Sachiko; Fukushima, Aki; Yokoi, Shuji; Takahata, Yoshihito; Kakizaki, Tomohiro; Ishida, Masahiko; Okamoto, Shunsuke; Sakamoto, Koji; Shirasawa, Kenta; Tabata, Satoshi; Nishio, Takeshi

2014-01-01

Radish (Raphanus sativus L., n = 9) is one of the major vegetables in Asia. Since the genomes of Brassica and related species including radish underwent genome rearrangement, it is quite difficult to perform functional analysis based on the reported genomic sequence of Brassica rapa. Therefore, we performed genome sequencing of radish. Short reads of genomic sequences of 191.1 Gb were obtained by next-generation sequencing (NGS) for a radish inbred line, and 76,592 scaffolds of ≥300 bp were constructed along with the bacterial artificial chromosome-end sequences. Finally, the whole draft genomic sequence of 402 Mb spanning 75.9% of the estimated genomic size and containing 61,572 predicted genes was obtained. Subsequently, 221 single nucleotide polymorphism markers and 768 PCR-RFLP markers were used together with the 746 markers produced in our previous study for the construction of a linkage map. The map was combined further with another radish linkage map constructed mainly with expressed sequence tag-simple sequence repeat markers into a high-density integrated map of 1,166 cM with 2,553 DNA markers. A total of 1,345 scaffolds were assigned to the linkage map, spanning 116.0 Mb. Bulked PCR products amplified by 2,880 primer pairs were sequenced by NGS, and SNPs in eight inbred lines were identified. PMID:24848699

LPL is the strongest prognostic factor in a comparative analysis of RNA-based markers in early chronic lymphocytic leukemia.

PubMed

Kaderi, Mohd Arifin; Kanduri, Meena; Buhl, Anne Mette; Sevov, Marie; Cahill, Nicola; Gunnarsson, Rebeqa; Jansson, Mattias; Smedby, Karin Ekström; Hjalgrim, Henrik; Jurlander, Jesper; Juliusson, Gunnar; Mansouri, Larry; Rosenquist, Richard

2011-08-01

The expression levels of LPL, ZAP70, TCL1A, CLLU1 and MCL1 have recently been proposed as prognostic factors in chronic lymphocytic leukemia. However, few studies have systematically compared these different RNA-based markers. Using real-time quantitative PCR, we measured the mRNA expression levels of these genes in unsorted samples from 252 newly diagnosed chronic lymphocytic leukemia patients and correlated our data with established prognostic markers (for example Binet stage, CD38, IGHV gene mutational status and genomic aberrations) and clinical outcome. High expression levels of all RNA-based markers, except MCL1, predicted shorter overall survival and time to treatment, with LPL being the most significant. In multivariate analysis including the RNA-based markers, LPL expression was the only independent prognostic marker for overall survival and time to treatment. When studying LPL expression and the established markers, LPL expression retained its independent prognostic strength for overall survival. All of the RNA-based markers, albeit with varying ability, added prognostic information to established markers, with LPL expression giving the most significant results. Notably, high LPL expression predicted a worse outcome in good-prognosis subgroups, such as patients with mutated IGHV genes, Binet stage A, CD38 negativity or favorable cytogenetics. In particular, the combination of LPL expression and CD38 could further stratify Binet stage A patients. LPL expression is the strongest RNA-based prognostic marker in chronic lymphocytic leukemia that could potentially be applied to predict outcome in the clinical setting, particularly in the large group of patients with favorable prognosis.

Molecular Pathology: Predictive, Prognostic, and Diagnostic Markers in Uterine Tumors.

PubMed

Ritterhouse, Lauren L; Howitt, Brooke E

2016-09-01

This article focuses on the diagnostic, prognostic, and predictive molecular biomarkers in uterine malignancies, in the context of morphologic diagnoses. The histologic classification of endometrial carcinomas is reviewed first, followed by the description and molecular classification of endometrial epithelial malignancies in the context of histologic classification. Taken together, the molecular and histologic classifications help clinicians to approach troublesome areas encountered in clinical practice and evaluate the utility of molecular alterations in the diagnosis and subclassification of endometrial carcinomas. Putative prognostic markers are reviewed. The use of molecular alterations and surrogate immunohistochemistry as prognostic and predictive markers is also discussed. Copyright © 2016 Elsevier Inc. All rights reserved.

Early pregnancy factor as a marker for assessing embryonic viability in threatened and missed abortions.

PubMed

Shahani, S K; Moniz, C L; Bordekar, A D; Gupta, S M; Naik, K

1994-01-01

It is now well recognized that the presence of early pregnancy factor (EPF) can signify the occurrence of fertilization, continuation of pregnancy and the existence of a viable embryo. With this in view, a study was undertaken to observe the potential of EPF as a marker in assessing embryo viability in cases complicated with vaginal bleeding during early pregnancy. The results indicated that the sensitivity of EPF as a marker in predicting threatened or missed abortion was 78.9% and the specificity 95.6%. The positive predictive value was observed to be 93.8% and the negative predictive value 84.6%. Our studies have shown that since EPF is present in viable but absent in non-viable pregnancies, it could be a useful marker of prognostic value in threatened abortions.

Improving the Flight Path Marker Symbol on Rotorcraft Synthetic Vision Displays

NASA Technical Reports Server (NTRS)

Szoboszlay, Zoltan P.; Hardy, Gordon H.; Welsh, Terence M.

2004-01-01

Two potential improvements to the flight path marker symbol were evaluated on a panel-mounted, synthetic vision, primary flight display in a rotorcraft simulation. One concept took advantage of the fact that synthetic vision systems have terrain height information available ahead of the aircraft. For this first concept, predicted altitude and ground track information was added to the flight path marker. In the second concept, multiple copies of the flight path marker were displayed at 3, 4, and 5 second prediction times as compared to a single prediction time of 3 seconds. Objective and subjective data were collected for eight rotorcraft pilots. The first concept produced significant improvements in pilot attitude control, ground track control, workload ratings, and preference ratings. The second concept did not produce significant differences in the objective or subjective measures.

Prediction of lung density changes after radiotherapy by cone beam computed tomography response markers and pre-treatment factors for non-small cell lung cancer patients.

PubMed

Bernchou, Uffe; Hansen, Olfred; Schytte, Tine; Bertelsen, Anders; Hope, Andrew; Moseley, Douglas; Brink, Carsten

2015-10-01

This study investigates the ability of pre-treatment factors and response markers extracted from standard cone-beam computed tomography (CBCT) images to predict the lung density changes induced by radiotherapy for non-small cell lung cancer (NSCLC) patients. Density changes in follow-up computed tomography scans were evaluated for 135 NSCLC patients treated with radiotherapy. Early response markers were obtained by analysing changes in lung density in CBCT images acquired during the treatment course. The ability of pre-treatment factors and CBCT markers to predict lung density changes induced by radiotherapy was investigated. Age and CBCT markers extracted at 10th, 20th, and 30th treatment fraction significantly predicted lung density changes in a multivariable analysis, and a set of response models based on these parameters were established. The correlation coefficient for the models was 0.35, 0.35, and 0.39, when based on the markers obtained at the 10th, 20th, and 30th fraction, respectively. The study indicates that younger patients without lung tissue reactions early into their treatment course may have minimal radiation induced lung density increase at follow-up. Further investigations are needed to examine the ability of the models to identify patients with low risk of symptomatic toxicity. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Prefrontal Markers and Cognitive Performance Are Dissociated during Progressive Dopamine Lesion

PubMed Central

Wilson, Charles R. E.; Vezoli, Julien; Faraut, Maïlys C. M.; Leviel, Vincent; Knoblauch, Kenneth; Procyk, Emmanuel

2016-01-01

Dopamine is thought to directly influence the neurophysiological mechanisms of both performance monitoring and cognitive control—two processes that are critically linked in the production of adapted behaviour. Changing dopamine levels are also thought to induce cognitive changes in several neurological and psychiatric conditions. But the working model of this system as a whole remains untested. Specifically, although many researchers assume that changing dopamine levels modify neurophysiological mechanisms and their markers in frontal cortex, and that this in turn leads to cognitive changes, this causal chain needs to be verified. Using longitudinal recordings of frontal neurophysiological markers over many months during progressive dopaminergic lesion in non-human primates, we provide data that fail to support a simple interaction between dopamine, frontal function, and cognition. Feedback potentials, which are performance-monitoring signals sometimes thought to drive successful control, ceased to differentiate feedback valence at the end of the lesion, just before clinical motor threshold. In contrast, cognitive control performance and beta oscillatory markers of cognitive control were unimpaired by the lesion. The differing dynamics of these measures throughout a dopamine lesion suggests they are not all driven by dopamine in the same way. These dynamics also demonstrate that a complex non-linear set of mechanisms is engaged in the brain in response to a progressive dopamine lesion. These results question the direct causal chain from dopamine to frontal physiology and on to cognition. They imply that biomarkers of cognitive functions are not directly predictive of dopamine loss. PMID:27824858

Deciphering the message broadcast by tumor-infiltrating dendritic cells.

PubMed

Karthaus, Nina; Torensma, Ruurd; Tel, Jurjen

2012-09-01

Human dendritic cells (DCs) infiltrate solid tumors, but this infiltration occurs in favorable and unfavorable disease prognoses. The statistical inference is that tumor-infiltrating DCs (TIDCs) play no conclusive role in predicting disease progression. This is remarkable because DCs are highly specialized antigen-presenting cells linking innate and adaptive immunity. DCs either boost the immune system (enhancing immunity) or dampen it (leading to tolerance). This dual effect explains the dual outcomes of cancer progression. The reverse functional characteristics of DCs depend on their maturation status. This review elaborates on the markers used to detect DCs in tumors. In many cases, the identification of DCs in human cancers relies on staining for S-100 and CD1a. These two markers are mainly expressed by Langerhans cells, which are one of several functionally different DC subsets. The activation status of DCs is based on the expression of CD83, DC-SIGN, and DC-LAMP, which are nonspecific markers of DC maturation. The detection of TIDCs has not kept pace with the increased knowledge about the identification of DC subsets and their maturation status. Therefore, it is difficult to draw a conclusion about the performance of DCs in tumors. We suggest a novel selection of markers to distinguish human DC subsets and maturation states. The use of these biomarkers will be of pivotal importance to scrutinize the prognostic significance of TIDCs. Copyright © 2012 American Society for Investigative Pathology. Published by Elsevier Inc. All rights reserved.

Chronic hepatitis C virus infection: Serum biomarkers in predicting liver damage

PubMed Central

Valva, Pamela; Ríos, Daniela A; De Matteo, Elena; Preciado, Maria V

2016-01-01

Currently, a major clinical challenge in the management of the increasing number of hepatitis C virus (HCV) infected patients is determining the best means for evaluating liver impairment. Prognosis and treatment of chronic hepatitis C (CHC) are partly dependent on the assessment of histological activity, namely cell necrosis and inflammation, and the degree of liver fibrosis. These parameters can be provided by liver biopsy; however, in addition to the risks related to an invasive procedure, liver biopsy has been associated with sampling error mostly due to suboptimal biopsy size. To avoid these pitfalls, several markers have been proposed as non-invasive alternatives for the diagnosis of liver damage. Distinct approaches among the currently available non-invasive methods are (1) the physical ones based on imaging techniques; and (2) the biological ones based on serum biomarkers. In this review, we discuss these approaches with special focus on currently available non-invasive serum markers. We will discuss: (1) class I serum biomarkers individually and as combined panels, particularly those that mirror the metabolism of liver extracellular matrix turnover and/or fibrogenic cell changes; (2) class II biomarkers that are indirect serum markers and are based on the evaluation of common functional alterations in the liver; and (3) biomarkers of liver cell death, since hepatocyte apoptosis plays a significant role in the pathogenesis of HCV infection. We highlight in this review the evidence behind the use of these markers and assess the diagnostic accuracy as well as advantages, limitations, and application in clinical practice of each test for predicting liver damage in CHC. PMID:26819506

Socioeconomic status, psychological resources, and inflammatory markers: Results from the MIDUS Study

PubMed Central

Elliot, Ari J.; Chapman, Benjamin P.

2016-01-01

Objective To investigate interactions of psychological resources and socioeconomic status in predicting markers of systemic inflammation, as well as potential gender differences and the explanatory role of childhood and adult stress exposures, health behaviors, and negative and positive affect. Method We utilized a sample of adults from the Midlife in the United States Survey (MIDUS) who provided biomarker data (N=1,152). SES was operationalized as a composite of education, income, and occupational prestige, and psychological resources as a latent factor measured with optimism, perceived control, and self-esteem. Linear regression models examined these two factors and their interaction in predicting interleukin-6 (IL-6) and C-reactive protein (CRP) measured on average 2 years later, as well as three-way interactions involving gender and the impact of covariate adjustment. Results Psychological resources interacted with SES in men (for IL-6: p<.001; for CRP: p=.04) but not in women. In men, greater psychological resources were associated with lower concentrations of IL-6 at lower levels of SES, but higher concentrations of both markers at higher levels of SES. The inverse association between resources and IL-6 at low SES was moderately attenuated upon adjustment for negative affect. Conclusion Socioeconomic status might modulate the linkage between psychological resources and systemic inflammation in men. At lower levels of SES, resources may be related to lower inflammation in part through lower negative affect. Associations with higher inflammation at higher SES add to growing evidence suggesting that adaptive psychological characteristics may be associated with markers of poorer physiological function under certain conditions. PMID:27280368

Serum biomarkers of bone metabolism in castration-resistant prostate cancer patients with skeletal metastases: results from SWOG 0421.

PubMed

Lara, Primo N; Ely, Benjamin; Quinn, David I; Mack, Philip C; Tangen, Catherine; Gertz, Erik; Twardowski, Przemyslaw W; Goldkorn, Amir; Hussain, Maha; Vogelzang, Nicholas J; Thompson, Ian M; Van Loan, Marta D

2014-04-01

Prior studies suggest that elevated markers of bone turnover are prognostic for poor survival in castration-resistant prostate cancer (CRPC). The predictive role of these markers relative to bone-targeted therapy is unknown. We prospectively evaluated the prognostic and predictive value of bone biomarkers in sera from CRPC patients treated on a placebo-controlled phase III trial of docetaxel with or without the bone targeted endothelin-A receptor antagonist atrasentan (SWOG S0421). Markers for bone resorption (N-telopeptide and pyridinoline) and formation (C-terminal collagen propeptide and bone alkaline phosphatase) were assayed in pretreatment and serial sera. Cox proportional hazards regression models were fit for overall survival. Models were fit with main effects for marker levels and with/without terms for marker-treatment interaction, adjusted for clinical variables, to assess the prognostic and predictive value of atrasentan. Analysis was adjusted for multiple comparisons. Two-sided P values were calculated using the Wald test. Sera from 778 patients were analyzed. Elevated baseline levels of each of the markers were associated with worse survival (P < .001). Increasing marker levels by week nine of therapy were also associated with subsequent poor survival (P < .001). Patients with the highest marker levels (upper 25th percentile for all markers) not only had a poor prognosis (hazard ratio [HR] = 4.3; 95% confidence interval [CI] = 2.41 to 7.65; P < .001) but also had a survival benefit from atrasentan (HR = 0.33; 95% CI = 0.15 to 0.71; median survival = 13 [atrasentan] vs 5 months [placebo]; P interaction = .005). Serum bone metabolism markers have statistically significant independent prognostic value in CRPC. Importantly, a small group of patients (6%) with highly elevated markers of bone turnover appear to preferentially benefit from atrasentan therapy.

Bridging the gap between genome analysis and precision breeding in potato.

PubMed

Gebhardt, Christiane

2013-04-01

Efficiency and precision in plant breeding can be enhanced by using diagnostic DNA-based markers for the selection of superior cultivars. This technique has been applied to many crops, including potatoes. The first generation of diagnostic DNA-based markers useful in potato breeding were enabled by several developments: genetic linkage maps based on DNA polymorphisms, linkage mapping of qualitative and quantitative agronomic traits, cloning and functional analysis of genes for pathogen resistance and genes controlling plant metabolism, and association genetics in collections of tetraploid varieties and advanced breeding clones. Although these have led to significant improvements in potato genetics, the prediction of most, if not all, natural variation in agronomic traits by diagnostic markers ultimately requires the identification of the causal genes and their allelic variants. This objective will be facilitated by new genomic tools, such as genomic resequencing and comparative profiling of the proteome, transcriptome, and metabolome in combination with phenotyping genetic materials relevant for variety development. Copyright © 2012 Elsevier Ltd. All rights reserved.

Systems immunology reveals markers of susceptibility to West Nile virus infection.

PubMed

Qian, Feng; Goel, Gautam; Meng, Hailong; Wang, Xiaomei; You, Fuping; Devine, Lesley; Raddassi, Khadir; Garcia, Melissa N; Murray, Kristy O; Bolen, Christopher R; Gaujoux, Renaud; Shen-Orr, Shai S; Hafler, David; Fikrig, Erol; Xavier, Ramnik; Kleinstein, Steven H; Montgomery, Ruth R

2015-01-01

West Nile virus (WNV) infection is usually asymptomatic but can cause severe neurological disease and death, particularly in older patients, and how individual variations in immunity contribute to disease severity is not yet defined. Animal studies identified a role for several immunity-related genes that determine the severity of infection. We have integrated systems-level transcriptional and functional data sets from stratified cohorts of subjects with a history of WNV infection to define whether these markers can distinguish susceptibility in a human population. Transcriptional profiles combined with immunophenotyping of primary cells identified a predictive signature of susceptibility that was detectable years after acute infection (67% accuracy), with the most prominent alteration being decreased IL1B induction following ex vivo infection of macrophages with WNV. Deconvolution analysis also determined a significant role for CXCL10 expression in myeloid dendritic cells. This systems analysis identified markers of pathogenic mechanisms and offers insights into potential therapeutic strategies. Copyright © 2015, American Society for Microbiology. All Rights Reserved.

Expression of Epithelial Mesenchymal Transition and Cancer Stem Cell Markers in Circulating Tumor Cells.

PubMed

Werner, Stefan; Stenzl, Arnulf; Pantel, Klaus; Todenhöfer, Tilman

2017-01-01

The characterization of circulating tumor cells (CTC) has the potential not only to provide important insights into molecular alterations of advanced tumor disease but also to facilitate risk prediction. Epithelial mesenchymal transition (EMT) has been discovered as important process for the development of metastases and the dissemination of tumor cells into the blood stream. In different tumor types, CTC with a mesenchymal phenotype have been reported that have presumably underwent EMT. Moreover, CTC with stem-cell like characteristics have been postulated as important drivers of tumor progression. Different platforms have been introduced to allow CTC enrichment independent of expression of epithelial antigens, as these may be downregulated in EMT- or stem-cell-like CTC. Both for CTCs with EMT- or stem-cell features different markers have been proposed. However, there is still a lack of evidence on the association of these markers with functional features and characteristics for stem cells and cells undergoing EMT.

Self-rated health among pregnant women: associations with objective health indicators, psychological functioning, and serum inflammatory markers.

PubMed

Christian, Lisa M; Iams, Jay; Porter, Kyle; Leblebicioglu, Binnaz

2013-12-01

Biobehavioral correlates of self-rated health in pregnancy are largely unknown. The goals of this study were to examine, in pregnant women, associations of self-rated health with (1) demographics, objective health status, health behaviors, and psychological factors, and (2) serum inflammatory markers. In the second trimester of pregnancy, 101 women provided a blood sample, completed measures of psychosocial stress, health status, and health behaviors, and received a comprehensive periodontal examination. The following independently predicted poorer self-rated health: (1) greater psychological stress, (2) greater objective health diagnoses, (3) higher body mass index, and (4) past smoking (versus never smoking). Poorer self-rated health was associated with higher serum interleukin-1β (p = 0.02) and marginally higher macrophage migration inhibitory factor (p = 0.06). These relationships were not fully accounted for by behavioral/psychological factors. This study provides novel data regarding factors influencing subjective ratings of health and the association of self-rated health with serum inflammatory markers in pregnant women.

Metabolomic prediction of yield in hybrid rice.

PubMed

Xu, Shizhong; Xu, Yang; Gong, Liang; Zhang, Qifa

2016-10-01

Rice (Oryza sativa) provides a staple food source for more than 50% of the world's population. An increase in yield can significantly contribute to global food security. Hybrid breeding can potentially help to meet this goal because hybrid rice often shows a considerable increase in yield when compared with pure-bred cultivars. We recently developed a marker-guided prediction method for hybrid yield and showed a substantial increase in yield through genomic hybrid breeding. We now have transcriptomic and metabolomic data as potential resources for prediction. Using six prediction methods, including least absolute shrinkage and selection operator (LASSO), best linear unbiased prediction (BLUP), stochastic search variable selection, partial least squares, and support vector machines using the radial basis function and polynomial kernel function, we found that the predictability of hybrid yield can be further increased using these omic data. LASSO and BLUP are the most efficient methods for yield prediction. For high heritability traits, genomic data remain the most efficient predictors. When metabolomic data are used, the predictability of hybrid yield is almost doubled compared with genomic prediction. Of the 21 945 potential hybrids derived from 210 recombinant inbred lines, selection of the top 10 hybrids predicted from metabolites would lead to a ~30% increase in yield. We hypothesize that each metabolite represents a biologically built-in genetic network for yield; thus, using metabolites for prediction is equivalent to using information integrated from these hidden genetic networks for yield prediction. © 2016 The Authors The Plant Journal © 2016 John Wiley & Sons Ltd.

Elucidation of the genetic basis of variation for stem strength characteristics in bread wheat by Associative Transcriptomics.

PubMed

Miller, Charlotte N; Harper, Andrea L; Trick, Martin; Werner, Peter; Waldron, Keith; Bancroft, Ian

2016-07-16

The current approach to reducing the tendency for wheat grown under high fertilizer conditions to collapse (lodge) under the weight of its grain is based on reducing stem height via the introduction of Rht genes. However, these reduce the yield of straw (itself an important commodity) and introduce other undesirable characteristics. Identification of alternative height-control loci is therefore of key interest. In addition, the improvement of stem mechanical strength provides a further way through which lodging can be reduced. To investigate the prospects for genetic alternatives to Rht, we assessed variation for plant height and stem strength properties in a training genetic diversity panel of 100 wheat accessions fixed for Rht. Using mRNAseq data derived from RNA purified from leaves, functional genotypes were developed for the panel comprising 42,066 Single Nucleotide Polymorphism (SNP) markers and 94,060 Gene Expression Markers (GEMs). In the first application in wheat of the recently-developed method of Associative Transcriptomics, we identified associations between trait variation and both SNPs and GEMs. Analysis of marker-trait associations revealed candidates for the causative genes underlying the trait variation, implicating xylan acetylation and the COP9 signalosome as contributing to stem strength and auxin in the control of the observed variation for plant height. Predictive capabilities of key markers for stem strength were validated using a test genetic diversity panel of 30 further wheat accessions. This work illustrates the power of Associative Transcriptomics for the exploration of complex traits of high agronomic importance in wheat. The careful selection of genotypes included in the analysis, allowed for high resolution mapping of novel trait-controlling loci in this staple crop. The use of Gene Expression markers coupled with the more traditional sequence-based markers, provides the power required to understand the biological context of the marker-trait associations observed. This not only adds to the wealth of knowledge that we strive to accumulate regarding gene function and plant adaptation, but also provides breeders with the information required to make more informed decisions regarding the potential consequences of incorporating the use of particular markers into future breeding programmes.

Association, effects and validation of polymorphisms within the NCAPG - LCORL locus located on BTA6 with feed intake, gain, meat and carcass traits in beef cattle

PubMed Central

2011-01-01

Background In a previously reported genome-wide association study based on a high-density bovine SNP genotyping array, 8 SNP were nominally associated (P ≤ 0.003) with average daily gain (ADG) and 3 of these were also associated (P ≤ 0.002) with average daily feed intake (ADFI) in a population of crossbred beef cattle. The SNP were clustered in a 570 kb region around 38 Mb on the draft sequence of bovine chromosome 6 (BTA6), an interval containing several positional and functional candidate genes including the bovine LAP3, NCAPG, and LCORL genes. The goal of the present study was to develop and examine additional markers in this region to optimize the ability to distinguish favorable alleles, with potential to identify functional variation. Results Animals from the original study were genotyped for 47 SNP within or near the gene boundaries of the three candidate genes. Sixteen markers in the NCAPG-LCORL locus displayed significant association with both ADFI and ADG even after stringent correction for multiple testing (P ≤ 005). These markers were evaluated for their effects on meat and carcass traits. The alleles associated with higher ADFI and ADG were also associated with higher hot carcass weight (HCW) and ribeye area (REA), and lower adjusted fat thickness (AFT). A reduced set of markers was genotyped on a separate, crossbred population including genetic contributions from 14 beef cattle breeds. Two of the markers located within the LCORL gene locus remained significant for ADG (P ≤ 0.04). Conclusions Several markers within the NCAPG-LCORL locus were significantly associated with feed intake and body weight gain phenotypes. These markers were also associated with HCW, REA and AFT suggesting that they are involved with lean growth and reduced fat deposition. Additionally, the two markers significant for ADG in the validation population of animals may be more robust for the prediction of ADG and possibly the correlated trait ADFI, across multiple breeds and populations of cattle. PMID:22168586

Can Serum Albumin Level and Total Lymphocyte Count be Surrogates for Malnutrition to Predict Wound Complications After Total Knee Arthroplasty?

PubMed

Morey, Vivek M; Song, Young Dong; Whang, Ji Sup; Kang, Yeon Gwi; Kim, Tae Kyun

2016-06-01

Although the serum albumin level and total lymphocyte count (TLC) have been reported as valid and reliable markers for defining malnutrition, their cutoff levels and predictive values for wound complications in patients undergoing total knee arthroplasty (TKA) remain questionable. A total of 3169 TKAs performed between April 2003 and December 2013 were retrospectively reviewed. We determined the prevalence of malnutrition on applying different definitions, with various cutoff values of serum albumin and TLC and analyzed the variations in outcome. The differences between groups with and without malnutrition in terms of functional outcome and complications were determined using Student's t test and analysis of variance. Multivariate logistic regression analysis was conducted to identify the independent risk factors. Among all the patients (N = 3169), the serum albumin level and TLC varied widely, with means of 4.1 g/dL and 2189 cells/mm(3), respectively. The prevalence of malnutrition (21%) as per the conventional definition (serum albumin level <3.5 g/dL or a serum TLC <1500 cells/mm(3)) dropped to only 1.6% when malnutrition was defined as serum albumin <3.5 g/dL "and" TLC <1500/mm(3), indicating a very small overlap between the 2 markers. No differences were observed between 2 groups in functional outcomes and incidence of wound complications. Our findings call into question the values of serum albumin level and TLC as a surrogate of malnutrition for predicting wound complications after TKA. Copyright © 2015 Elsevier Inc. All rights reserved.

Sunitinib-induced hypothyroidism predicts progression-free survival in metastatic renal cell carcinoma patients.

PubMed

Buda-Nowak, Anna; Kucharz, Jakub; Dumnicka, Paulina; Kuzniewski, Marek; Herman, Roman Maria; Zygulska, Aneta L; Kusnierz-Cabala, Beata

2017-04-01

Sunitinib is a tyrosine kinase inhibitor (TKI) used in treatment of metastatic renal cell carcinoma (mRCC), gastrointestinal stromal tumors and pancreatic neuroendocrine tumors. One of the most common side effects related to sunitinib is hypothyroidism. Recent trials suggest correlation between the incidence of hypothyroidism and treatment outcome in patients treated with TKI. This study evaluates whether development of hypothyroidism is a predictive marker of progression-free survival (PFS) in patients with mRCC treated with sunitinib. Twenty-seven patients diagnosed with clear cell mRCC, after nephrectomy and in 'good' or 'intermediate' MSKCC risk prognostic group, were included in the study. All patients received sunitinib as a first-line treatment on a standard schedule (initial dose 50 mg/day, 4 weeks on, 2 weeks off). The thyroid-stimulating hormone serum levels were obtained at the baseline and every 12 weeks of treatment. In statistic analyses, we used Kaplan-Meier method for assessment of progression-free survival; for comparison of survival, we used log-rank test. In our study, the incidence of hypothyroidism was 44%. The patients who had developed hypothyroidism had better median PFS to patients with normal thyroid function 28,3 months [95% (CI) 20.4-36.2 months] versus 9.8 months (6.4-13.1 months). In survival analysis, we perceive that thyroid dysfunction is a predictive factor of a progression-free survival (PFS). In the unified group of patients, the development of hypothyroidism during treatment with sunitinib is a positive marker for PFS. During that treatment, thyroid function should be evaluated regularly.

Integration of DNA marker information into breeding value predictions

USDA-ARS?s Scientific Manuscript database

Calves from seven breeds including 20 herds were genotyped with a reduced DNA marker panel for weaning weight. The marker panel used was derived using USMARC Cycle VII animals. The results from the current study suggest marker effects are not robust across breeds and that methodology exists to integ...

Quantitative trait loci markers derived from whole genome sequence data increases the reliability of genomic prediction.

PubMed

Brøndum, R F; Su, G; Janss, L; Sahana, G; Guldbrandtsen, B; Boichard, D; Lund, M S

2015-06-01

This study investigated the effect on the reliability of genomic prediction when a small number of significant variants from single marker analysis based on whole genome sequence data were added to the regular 54k single nucleotide polymorphism (SNP) array data. The extra markers were selected with the aim of augmenting the custom low-density Illumina BovineLD SNP chip (San Diego, CA) used in the Nordic countries. The single-marker analysis was done breed-wise on all 16 index traits included in the breeding goals for Nordic Holstein, Danish Jersey, and Nordic Red cattle plus the total merit index itself. Depending on the trait's economic weight, 15, 10, or 5 quantitative trait loci (QTL) were selected per trait per breed and 3 to 5 markers were selected to tag each QTL. After removing duplicate markers (same marker selected for more than one trait or breed) and filtering for high pairwise linkage disequilibrium and assaying performance on the array, a total of 1,623 QTL markers were selected for inclusion on the custom chip. Genomic prediction analyses were performed for Nordic and French Holstein and Nordic Red animals using either a genomic BLUP or a Bayesian variable selection model. When using the genomic BLUP model including the QTL markers in the analysis, reliability was increased by up to 4 percentage points for production traits in Nordic Holstein animals, up to 3 percentage points for Nordic Reds, and up to 5 percentage points for French Holstein. Smaller gains of up to 1 percentage point was observed for mastitis, but only a 0.5 percentage point increase was seen for fertility. When using a Bayesian model accuracies were generally higher with only 54k data compared with the genomic BLUP approach, but increases in reliability were relatively smaller when QTL markers were included. Results from this study indicate that the reliability of genomic prediction can be increased by including markers significant in genome-wide association studies on whole genome sequence data alongside the 54k SNP set. Copyright © 2015 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

NABIC marker database: A molecular markers information network of agricultural crops.

PubMed

Kim, Chang-Kug; Seol, Young-Joo; Lee, Dong-Jun; Jeong, In-Seon; Yoon, Ung-Han; Lee, Gang-Seob; Hahn, Jang-Ho; Park, Dong-Suk

2013-01-01

In 2013, National Agricultural Biotechnology Information Center (NABIC) reconstructs a molecular marker database for useful genetic resources. The web-based marker database consists of three major functional categories: map viewer, RSN marker and gene annotation. It provides 7250 marker locations, 3301 RSN marker property, 3280 molecular marker annotation information in agricultural plants. The individual molecular marker provides information such as marker name, expressed sequence tag number, gene definition and general marker information. This updated marker-based database provides useful information through a user-friendly web interface that assisted in tracing any new structures of the chromosomes and gene positional functions using specific molecular markers. The database is available for free at http://nabic.rda.go.kr/gere/rice/molecularMarkers/

Stress-Related Immune Markers in Depression: Implications for Treatment

PubMed Central

Hughes, Martina M.; Connor, Thomas J.

2016-01-01

Major depression is a serious psychiatric disorder; however, the precise biological basis of depression still remains elusive. A large body of evidence implicates a dysregulated endocrine and inflammatory response system in the pathogenesis of depression. Despite this, given the heterogeneity of depression, not all depressed patients exhibit dysregulation of the inflammatory and endocrine systems. Evidence suggests that inflammation is associated with depression in certain subgroups of patients and that those who have experienced stressful life events such as childhood trauma or bereavement may be at greater risk of developing depression. Consequently, prolonged exposure to stress is thought to be a key trigger for the onset of a depressive episode. This review assesses the relationship between stress and the immune system, with a particular interest in the mechanisms by which stress impacts immune function, and how altered immune functioning, in turn, may lead to a feed forward cascade of multiple systems dysregulation and the subsequent manifestation of depressive symptomology. The identification of stress-related immune markers and potential avenues for advances in therapeutic intervention is vital. Changes in specific biological markers may be used to characterize or differentiate depressive subtypes or specific symptoms and may predict treatment response, in turn facilitating a more effective, targeted, and fast-acting approach to treatment. PMID:26775294

Blend sign predicts poor outcome in patients with intracerebral hemorrhage

PubMed Central

Cao, Du; Zhu, Dan; Lv, Fa-Jin; Liu, Yang; Yuan, Liang; Zhang, Gang; Xiong, Xin; Li, Rui; Hu, Yun-Xin; Qin, Xin-Yue; Xie, Peng

2017-01-01

Introduction Blend sign has been recently described as a novel imaging marker that predicts hematoma expansion. The purpose of our study was to investigate the prognostic value of CT blend sign in patients with ICH. Objectives and methods Patients with intracerebral hemorrhage who underwent baseline CT scan within 6 hours were included. The presence of blend sign on admission nonenhanced CT was independently assessed by two readers. The functional outcome was assessed by using the modified Rankin Scale (mRS) at 90 days. Results Blend sign was identified in 40 of 238 (16.8%) patients on admission CT scan. The proportion of patients with a poor functional outcome was significantly higher in patients with blend sign than those without blend sign (75.0% versus 47.5%, P = 0.001). The multivariate logistic regression analysis demonstrated that age, intraventricular hemorrhage, admission GCS score, baseline hematoma volume and presence of blend sign on baseline CT independently predict poor functional outcome at 90 days. The CT blend sign independently predicts poor outcome in patients with ICH (odds ratio 3.61, 95% confidence interval [1.47–8.89];p = 0.005). Conclusions Early identification of blend sign is useful in prognostic stratification and may serve as a potential therapeutic target for prospective interventional studies. PMID:28829797

Predictive markers in calpastatin for tenderness in commercial pig populations

USDA-ARS?s Scientific Manuscript database

The identification of predictive DNA markers for pork quality would allow U.S. pork producers and breeders to more quickly and efficiently select genetically superior animals for production of consistent, high quality meat. Genome scans have identified QTL for tenderness on pig chromosome 2 which ha...

Molecular marker genes for ectomycorrhizal symbiosis

Treesearch

Shiv Hiremath; Carolyn McQuattie; Gopi Podila; Jenise Bauman

2013-01-01

Mycorrhizal symbiosis is a mutually beneficial association very commonly found among most vascular plants. Formation of mycorrhiza happens only between compatible partners and predicting this is often accomplished through a trial and error process. We investigated the possibility of using expression of symbiosis specific genes as markers to predict the formation of...

Serum biomarkers of bone metabolism in castration resistant prostate cancer patients with skeletal metastases

USDA-ARS?s Scientific Manuscript database

Background. Prior studies suggest that elevated markers of bone turnover are prognostic for poor survival in castration resistant prostate cancer (CRPC). The predictive role of these markers relative to bone-targeted therapy is unknown. We prospectively evaluated the prognostic and predictive value ...

Contrasting Olfaction, Vision, and Audition as Predictors of Cognitive Change and Impairment in Non-Demented Older Adults

PubMed Central

MacDonald, Stuart W.S.; Keller, Connor J.C.; Brewster, Paul W.H.; Dixon, Roger A.

2017-01-01

Objective This study examines the relative utility of a particular class of non-invasive functional biomarkers -- sensory functions -- for detecting those at risk of cognitive decline and impairment. Three central research objectives were examined including whether: (1) olfactory function, vision, and audition exhibited significant longitudinal declines in non-demented older adults, (2) multi-wave change for these sensory function indicators predicted risk of mild cognitive impairment, and (3) change within persons for each sensory measure shared dynamic time-varying associations with within-person change in cognitive functioning. Method A longitudinal sample (n=408) from the Victoria Longitudinal Study was assembled. Three cognitive status subgroups were identified: not impaired cognitively (NIC), single assessment mild cognitive impairment (SA-MCI), and multiple assessment mild cognitive impairment (MA-MCI). Results We tested independent predictive associations, contrasting change in sensory function as predictors of cognitive decline and impairment, utilizing both linear mixed models and logistic regression analysis. Olfaction and, to a lesser extent, vision were identified as the most robust predictors of cognitive status and decline; audition showed little predictive influence. Conclusions These findings underscore the potential utility of deficits in olfactory function, in particular, as an early marker of age- and pathology-related cognitive decline. Functional biomarkers may represent potential candidates for use in the early stages of a multi-step screening approach for detecting those at risk of cognitive impairment, as well as for targeted intervention. PMID:29809033

ACE and sIL-2R correlate with lung function improvement in sarcoidosis during methotrexate therapy.

PubMed

Vorselaars, Adriane D M; van Moorsel, Coline H M; Zanen, Pieter; Ruven, Henk J T; Claessen, Anke M E; van Velzen-Blad, Heleen; Grutters, Jan C

2015-02-01

In sarcoidosis, the search for disease activity markers that correlate with treatment response is ongoing. The aim of this study was to investigate the pattern of two proposed markers, serum angiotensin-converting enzyme (ACE) and soluble IL-2 receptor (sIL-2R) during methotrexate (MTX) therapy in sarcoidosis patients. We analysed 114 sarcoidosis patients who used MTX for six months, consisting of a subgroup of 76 patients with a pulmonary indication for treatment and a subgroup of 38 patients with an extra-pulmonary indication. ACE and sIL-2R serum levels were measured at baseline and after six months of treatment. Correlation coefficients (R) and odds ratios (ORs) were calculated to study the correlation and predictive effect of serum ACE and sIL-2R levels for pulmonary improvement. High baseline levels of ACE correlated significantly with lung function improvement after treatment (R = 0.45, p < 0.0001; stronger in the pulmonary subgroup R 0.57, p < 0.0001). ACE baseline levels >90 U/l predicted a 10% improvement in overall lung function (OR 3.55; CI 1.34-9.38), with the highest prediction level for 10% improvement in DLCO (OR 4.63; CI 1.23-17.4). After six months of MTX, mean ACE decreased with 17.2 U/l (p < 0.0001) and sIL-2R with 1850 pg/ml (p < 0.0001). Decreases in both ACE and sIL-2R correlated with an increase in lung function. The strongest correlation was found with change in DLCO in the pulmonary subgroup (ACE R = 0.63, P < 0.0001; sIL-2R R = 0.56, P < 0.0001). Baseline and serial serum ACE and sIL-2R levels correlate well with lung function improvement during MTX treatment. Serial measurements of these biomarkers are helpful in monitoring treatment effects in sarcoidosis patients. Copyright © 2014 Elsevier Ltd. All rights reserved.

Breeding Jatropha curcas by genomic selection: A pilot assessment of the accuracy of predictive models.

PubMed

Azevedo Peixoto, Leonardo de; Laviola, Bruno Galvêas; Alves, Alexandre Alonso; Rosado, Tatiana Barbosa; Bhering, Leonardo Lopes

2017-01-01

Genomic wide selection is a promising approach for improving the selection accuracy in plant breeding, particularly in species with long life cycles, such as Jatropha. Therefore, the objectives of this study were to estimate the genetic parameters for grain yield (GY) and the weight of 100 seeds (W100S) using restricted maximum likelihood (REML); to compare the performance of GWS methods to predict GY and W100S; and to estimate how many markers are needed to train the GWS model to obtain the maximum accuracy. Eight GWS models were compared in terms of predictive ability. The impact that the marker density had on the predictive ability was investigated using a varying number of markers, from 2 to 1,248. Because the genetic variance between evaluated genotypes was significant, it was possible to obtain selection gain. All of the GWS methods tested in this study can be used to predict GY and W100S in Jatropha. A training model fitted using 1,000 and 800 markers is sufficient to capture the maximum genetic variance and, consequently, maximum prediction ability of GY and W100S, respectively. This study demonstrated the applicability of genome-wide prediction to identify useful genetic sources of GY and W100S for Jatropha breeding. Further research is needed to confirm the applicability of the proposed approach to other complex traits.

Physical function and self-rated health status as predictors of mortality: results from longitudinal analysis in the ilSIRENTE study.

PubMed

Cesari, Matteo; Onder, Graziano; Zamboni, Valentina; Manini, Todd; Shorr, Ronald I; Russo, Andrea; Bernabei, Roberto; Pahor, Marco; Landi, Francesco

2008-12-22

Physical function measures have been shown to predict negative health-related events in older persons, including mortality. These markers of functioning may interact with the self-rated health (SRH) in the prediction of events. Aim of the present study is to compare the predictive value for mortality of measures of physical function and SRH status, and test their possible interactions. Data are from 335 older persons aged >or= 80 years (mean age 85.6 years) enrolled in the "Invecchiamento e Longevità nel Sirente" (ilSIRENTE) study. The predictive values for mortality of 4-meter walk test, Short Physical Performance Battery (SPPB), hand grip strength, Activities of Daily Living (ADL) scale, Instrumental ADL (IADL) scale, and a SRH scale were compared using proportional hazard models. Kaplan-Meier survival curves for mortality and Receiver Operating Characteristic (ROC) curve analyses were also computed to estimate the predictive value of the independent variables of interest for mortality (alone and in combination). During the 24-month follow-up (mean 1.8 years), 71 (21.2%) events occurred in the study sample. All the tested variables were able to significantly predict mortality. No significant interaction was reported between physical function measures and SRH. The SPPB score was the strongest predictor of overall mortality after adjustment for potential confounders (per SD increase; HR 0.64; 95%CI 0.48-0.86). A similar predictive value was showed by the SRH (per SD increase; HR 0.76; 95%CI 0.59-0.97). The chair stand test was the SPPB subtask showing the highest prognostic value. All the tested measures are able to predict mortality with different extents, but strongest results were obtained from the SPPB and the SRH. The chair stand test may be as useful as the complete SPPB in estimating the mortality risk.

Stigma and functional disability in relation to marriage and employment in young people with epilepsy in rural Tanzania.

PubMed

Goodall, Jack; Salem, Sabrine; Walker, Richard W; Gray, William K; Burton, Kathryn; Hunter, Ewan; Rogathi, Jane; Shali, Esther; Mohin, Ali; Mushi, Declare; Owens, Stephen

2018-01-01

To assess the impact of childhood epilepsy on social transitioning outcomes for young people with epilepsy (YPWE) living in Tanzania, and to explore influences on these outcomes. At six years from baseline, we followed up 84 YPWE and 79 age- sex- and village- matched controls recruited into a case-control study of childhood epilepsy in rural northern Tanzania. Data were collected from interviews with young people and their carers using a structured questionnaire. Perceived stigma was evaluated using the Kilifi Stigma Score and functional disability using the Barthel Index (BI). The effects of age, gender, functional disability and stigma on selected markers of social transitioning (education, employment and relationships) were estimated using multivariable modelling. Fewer YPWE than controls were in an intimate relationship (42.3% vs. 76.9%) or in education or paid employment (33.3% vs. 91.1%) and they reported elevated perceived stigma scores (27.4% vs. 3.8%). Among YPWE, a positive education or employment outcome was predicted by a lower seizure frequency (adjusted OR 3.79) and a higher BI score (adj. OR 12.12); a positive relationship outcome was predicted by a higher BI score (adj. OR 45.86) and being male (adj. OR 8.55). YPWE were more likely to experience adverse employment, educational and relationship outcomes in the transition to adult life than controls, with the greatest disadvantage experienced by females, those with greater functional disability and those with poorer seizure control. Markers of social transitioning should be included in any prospective evaluation of interventions designed to support these groups. Copyright © 2017 British Epilepsy Association. Published by Elsevier Ltd. All rights reserved.

Prediction of Wound Healing in Diabetic Foot Ulcers: an Observational Study in Tertiary Hospital in Indonesia.

PubMed

Soewondo, Pradana; Suyono, Slamet; Sastrosuwignyo, Mpu Kanoko; Harahap, Alida R; Sutrisna, Bambang; Makmun, Lukman H

2017-01-01

to evaluate the role of clinical characteristics, functional markers of vasodilation, inflammatory response, and atherosclerosis in predicting wound healing in diabetic foot ulcer. a cohort study (February - October 2010) was conducted from 40 subjects with acute diabetic foot ulcer at clinical ward of Dr. Cipto Mangunkusumo National Central General Hospital, Jakarta, Indonesia. Each subject underwent at least two variable measurements, i.e. during inflammatory phase and proliferation phase. The studied variables were clinical characteristics, complete peripheral blood count (CBC) and differential count, levels of HbA1c, ureum, creatinine, lipid profile, fasting blood glucose (FBG), marker of endothelial dysfunction (asymmetric dimethylarginine/ADMA, endothelin-1/ET-1, and flow-mediated dilation/FMD of brachial artery), and marker of vascular calcification (osteoprotegerin/OPG). median of time achieving 50% granulation tissue in our study was 21 days. There were nine factors that contribute in the development of 50% granulation tissue, i.e. family history of diabetes mellitus (DM), previous history of wound, wound area, duration of existing wound, captopril and simvastatin medications, levels of ADMA, ET-1, and OPG. There were three out of the nine factors that significantly correlated with wound healing, i.e. wound area, OPG levels, and simvastatin medications. in acute diabetic foot ulcers, wound area and OPG levels had positive correlation with wound healing, whereas simvastatin medications had negative correlation with wound healing.

Multiple Brain Markers are Linked to Age-Related Variation in Cognition

PubMed Central

Hedden, Trey; Schultz, Aaron P.; Rieckmann, Anna; Mormino, Elizabeth C.; Johnson, Keith A.; Sperling, Reisa A.; Buckner, Randy L.

2016-01-01

Age-related alterations in brain structure and function have been challenging to link to cognition due to potential overlapping influences of multiple neurobiological cascades. We examined multiple brain markers associated with age-related variation in cognition. Clinically normal older humans aged 65–90 from the Harvard Aging Brain Study (N = 186) were characterized on a priori magnetic resonance imaging markers of gray matter thickness and volume, white matter hyperintensities, fractional anisotropy (FA), resting-state functional connectivity, positron emission tomography markers of glucose metabolism and amyloid burden, and cognitive factors of processing speed, executive function, and episodic memory. Partial correlation and mediation analyses estimated age-related variance in cognition shared with individual brain markers and unique to each marker. The largest relationships linked FA and striatum volume to processing speed and executive function, and hippocampal volume to episodic memory. Of the age-related variance in cognition, 70–80% was accounted for by combining all brain markers (but only ∼20% of total variance). Age had significant indirect effects on cognition via brain markers, with significant markers varying across cognitive domains. These results suggest that most age-related variation in cognition is shared among multiple brain markers, but potential specificity between some brain markers and cognitive domains motivates additional study of age-related markers of neural health. PMID:25316342

MAP3K8/TPL-2/COT is a potential predictive marker for MEK inhibitor treatment in high-grade serous ovarian carcinomas.

PubMed

Gruosso, Tina; Garnier, Camille; Abelanet, Sophie; Kieffer, Yann; Lemesre, Vincent; Bellanger, Dorine; Bieche, Ivan; Marangoni, Elisabetta; Sastre-Garau, Xavier; Mieulet, Virginie; Mechta-Grigoriou, Fatima

2015-10-12

Ovarian cancer is a silent disease with a poor prognosis that urgently requires new therapeutic strategies. In low-grade ovarian tumours, mutations in the MAP3K BRAF gene constitutively activate the downstream kinase MEK. Here we demonstrate that an additional MAP3K, MAP3K8 (TPL-2/COT), accumulates in high-grade serous ovarian carcinomas (HGSCs) and is a potential prognostic marker for these tumours. By combining analyses on HGSC patient cohorts, ovarian cancer cells and patient-derived xenografts, we demonstrate that MAP3K8 controls cancer cell proliferation and migration by regulating key players in G1/S transition and adhesion dynamics. In addition, we show that the MEK pathway is the main pathway involved in mediating MAP3K8 function, and that MAP3K8 exhibits a reliable predictive value for the effectiveness of MEK inhibitor treatment. Our data highlight key roles for MAP3K8 in HGSC and indicate that MEK inhibitors could be a useful treatment strategy, in combination with conventional chemotherapy, for this disease.

Serum decoy receptor 3 level: a predictive marker for nodal metastasis and survival among oral cavity cancer patients.

PubMed

Tu, Hsi-Feng; Liu, Chung-Ji; Liu, Shyun-Yeu; Chen, Yu-Ping; Yu, En-Hao; Lin, Shu-Chun; Chang, Kuo-Wei

2011-03-01

Validating markers for prediction of nodal metastasis could be beneficial in treatment of oral cavity cancer. Decoy receptor 3 (DcR3), locus on 20q13, functions as a death decoy inhibiting apoptosis mediated by the tumor necrosis factor receptor (TNFR) family. This study analyzed the serum level of DcR3 in relationship to the clinical parameters of oral cavity cancer patients together with detection of DcR3 genomic copy number in primary and recurrent tumors. Elevated serum DcR3 was associated with nodal metastasis and worse prognosis. Gain of DcR3 copy number was detected in 17% of primary tumor tissue but not found in healthy areca chewers. Tissue from recurrent tumors showed more frequent DcR3 copy number alteration (48%) than the paired primary tumor tissue. Serum DcR3 level is a predictor for the nodal metastasis and survival among oral cavity cancer patients and the DcR3 copy number alteration could underlie oral carcinogenesis progression. Copyright © 2010 Wiley Periodicals, Inc.

Targeted Proteomics Approach for Precision Plant Breeding.

PubMed

Chawade, Aakash; Alexandersson, Erik; Bengtsson, Therese; Andreasson, Erik; Levander, Fredrik

2016-02-05

Selected reaction monitoring (SRM) is a targeted mass spectrometry technique that enables precise quantitation of hundreds of peptides in a single run. This technique provides new opportunities for multiplexed protein biomarker measurements. For precision plant breeding, DNA-based markers have been used extensively, but the potential of protein biomarkers has not been exploited. In this work, we developed an SRM marker panel with assays for 104 potato (Solanum tuberosum) peptides selected using univariate and multivariate statistics. Thereafter, using random forest classification, the prediction markers were identified for Phytopthora infestans resistance in leaves, P. infestans resistance in tubers, and plant yield in potato leaf secretome samples. The results suggest that the marker panel has the predictive potential for three traits, two of which have no commercial DNA markers so far. Furthermore, the marker panel was also tested and found to be applicable to potato clones not used during the marker development. The proposed workflow is thus a proof-of-concept for targeted proteomics as an efficient readout in accelerated breeding for complex and agronomically important traits.

Combining Biomarkers Linearly and Nonlinearly for Classification Using the Area Under the ROC Curve

PubMed Central

Fong, Youyi; Yin, Shuxin; Huang, Ying

2016-01-01

In biomedical studies, it is often of interest to classify/predict a subject’s disease status based on a variety of biomarker measurements. A commonly used classification criterion is based on AUC - Area under the Receiver Operating Characteristic Curve. Many methods have been proposed to optimize approximated empirical AUC criteria, but there are two limitations to the existing methods. First, most methods are only designed to find the best linear combination of biomarkers, which may not perform well when there is strong nonlinearity in the data. Second, many existing linear combination methods use gradient-based algorithms to find the best marker combination, which often result in sub-optimal local solutions. In this paper, we address these two problems by proposing a new kernel-based AUC optimization method called Ramp AUC (RAUC). This method approximates the empirical AUC loss function with a ramp function, and finds the best combination by a difference of convex functions algorithm. We show that as a linear combination method, RAUC leads to a consistent and asymptotically normal estimator of the linear marker combination when the data is generated from a semiparametric generalized linear model, just as the Smoothed AUC method (SAUC). Through simulation studies and real data examples, we demonstrate that RAUC out-performs SAUC in finding the best linear marker combinations, and can successfully capture nonlinear pattern in the data to achieve better classification performance. We illustrate our method with a dataset from a recent HIV vaccine trial. PMID:27058981

Generating linear regression model to predict motor functions by use of laser range finder during TUG.

PubMed

Adachi, Daiki; Nishiguchi, Shu; Fukutani, Naoto; Hotta, Takayuki; Tashiro, Yuto; Morino, Saori; Shirooka, Hidehiko; Nozaki, Yuma; Hirata, Hinako; Yamaguchi, Moe; Yorozu, Ayanori; Takahashi, Masaki; Aoyama, Tomoki

2017-05-01

The purpose of this study was to investigate which spatial and temporal parameters of the Timed Up and Go (TUG) test are associated with motor function in elderly individuals. This study included 99 community-dwelling women aged 72.9 ± 6.3 years. Step length, step width, single support time, variability of the aforementioned parameters, gait velocity, cadence, reaction time from starting signal to first step, and minimum distance between the foot and a marker placed to 3 in front of the chair were measured using our analysis system. The 10-m walk test, five times sit-to-stand (FTSTS) test, and one-leg standing (OLS) test were used to assess motor function. Stepwise multivariate linear regression analysis was used to determine which TUG test parameters were associated with each motor function test. Finally, we calculated a predictive model for each motor function test using each regression coefficient. In stepwise linear regression analysis, step length and cadence were significantly associated with the 10-m walk test, FTSTS and OLS test. Reaction time was associated with the FTSTS test, and step width was associated with the OLS test. Each predictive model showed a strong correlation with the 10-m walk test and OLS test (P < 0.01), which was not significant higher correlation than TUG test time. We showed which TUG test parameters were associated with each motor function test. Moreover, the TUG test time regarded as the lower extremity function and mobility has strong predictive ability in each motor function test. Copyright © 2017 The Japanese Orthopaedic Association. Published by Elsevier B.V. All rights reserved.

[The impact of the androgen receptor splice variant AR-V7 on the prognosis and treatment of advanced prostate cancer].

PubMed

Thelen, P; Taubert, H; Duensing, S; Kristiansen, G; Merseburger, A S; Cronauer, M V

2018-01-25

A recently discovered mechanism enabling prostate cancer cells to escape the effects of endocrine therapies consists in the synthesis of C-terminally truncated, constitutively active androgen receptor (AR) splice variants (AR-V). Devoid of a functional C-terminal hormone/ligand binding domain, various AR-Vs are insensitive to therapies targeting the androgen/AR signalling axis. Preliminary studies suggest that AR-V7, the most common AR-V, is a promising predictive tumour marker and a relevant selection marker for the treatment of advanced prostate cancer. This review critically outlines recent advances in AR-V7 diagnostics and presents an overview of current AR-V7 targeted therapies. © Georg Thieme Verlag KG Stuttgart · New York.

Ensemble Learning of QTL Models Improves Prediction of Complex Traits

PubMed Central

Bian, Yang; Holland, James B.

2015-01-01

Quantitative trait locus (QTL) models can provide useful insights into trait genetic architecture because of their straightforward interpretability but are less useful for genetic prediction because of the difficulty in including the effects of numerous small effect loci without overfitting. Tight linkage between markers introduces near collinearity among marker genotypes, complicating the detection of QTL and estimation of QTL effects in linkage mapping, and this problem is exacerbated by very high density linkage maps. Here we developed a thinning and aggregating (TAGGING) method as a new ensemble learning approach to QTL mapping. TAGGING reduces collinearity problems by thinning dense linkage maps, maintains aspects of marker selection that characterize standard QTL mapping, and by ensembling, incorporates information from many more markers-trait associations than traditional QTL mapping. The objective of TAGGING was to improve prediction power compared with QTL mapping while also providing more specific insights into genetic architecture than genome-wide prediction models. TAGGING was compared with standard QTL mapping using cross validation of empirical data from the maize (Zea mays L.) nested association mapping population. TAGGING-assisted QTL mapping substantially improved prediction ability for both biparental and multifamily populations by reducing both the variance and bias in prediction. Furthermore, an ensemble model combining predictions from TAGGING-assisted QTL and infinitesimal models improved prediction abilities over the component models, indicating some complementarity between model assumptions and suggesting that some trait genetic architectures involve a mixture of a few major QTL and polygenic effects. PMID:26276383

Applying a new mammographic imaging marker to predict breast cancer risk

NASA Astrophysics Data System (ADS)

Aghaei, Faranak; Danala, Gopichandh; Hollingsworth, Alan B.; Stoug, Rebecca G.; Pearce, Melanie; Liu, Hong; Zheng, Bin

2018-02-01

Identifying and developing new mammographic imaging markers to assist prediction of breast cancer risk has been attracting extensive research interest recently. Although mammographic density is considered an important breast cancer risk, its discriminatory power is lower for predicting short-term breast cancer risk, which is a prerequisite to establish a more effective personalized breast cancer screening paradigm. In this study, we presented a new interactive computer-aided detection (CAD) scheme to generate a new quantitative mammographic imaging marker based on the bilateral mammographic tissue density asymmetry to predict risk of cancer detection in the next subsequent mammography screening. An image database involving 1,397 women was retrospectively assembled and tested. Each woman had two digital mammography screenings namely, the "current" and "prior" screenings with a time interval from 365 to 600 days. All "prior" images were originally interpreted negative. In "current" screenings, these cases were divided into 3 groups, which include 402 positive, 643 negative, and 352 biopsy-proved benign cases, respectively. There is no significant difference of BIRADS based mammographic density ratings between 3 case groups (p < 0.6). When applying the CAD-generated imaging marker or risk model to classify between 402 positive and 643 negative cases using "prior" negative mammograms, the area under a ROC curve is 0.70+/-0.02 and the adjusted odds ratios show an increasing trend from 1.0 to 8.13 to predict the risk of cancer detection in the "current" screening. Study demonstrated that this new imaging marker had potential to yield significantly higher discriminatory power to predict short-term breast cancer risk.

Clinical symptoms predict concurrent social and global functioning in an early psychosis sample.

PubMed

Cacciotti-Saija, Cristina; Langdon, Robyn; Ward, Philip B; Hickie, Ian B; Guastella, Adam J

2018-04-01

Although well established in chronic schizophrenia, the key determinants of functioning remain unknown during the early phase of a psychotic disorder. The aim of this study was to comprehensively examine the social cognitive, basic neurocognitive and clinical predictors of concurrent social functioning and global functioning in an early psychosis sample. This study examined the relationship between social cognition, basic neurocognition and clinical symptoms with concurrent functioning in 51 early psychosis individuals. Assessments included a range of self-report, observational and clinician-rated measures of cognitive, symptom severity and functioning domains. Results revealed a significant association between self-reported social function and lower levels of both social interaction anxiety and negative psychotic symptoms. A significant association was also observed between lower levels of negative psychotic symptoms and observed social functioning. Lastly, results demonstrated a significant association between reduced negative psychotic symptoms and clinician-rated global functioning. Clinical domains such as negative symptoms and social interaction anxiety significantly contribute to an optimal model predicting outcome during the early phase of a psychotic disorder. These clinical features may also provide useful markers of an individual's capacity for social participation. Clinical implications include the need for early targeted intervention to address social anxiety and negative psychotic symptoms to facilitate optimum patient outcome. © 2015 Wiley Publishing Asia Pty Ltd.

Pulmonary function tests as outcomes for systemic sclerosis interstitial lung disease.

PubMed

Caron, Melissa; Hoa, Sabrina; Hudson, Marie; Schwartzman, Kevin; Steele, Russell

2018-06-30

Interstitial lung disease (ILD) is the leading cause of morbidity and mortality in systemic sclerosis (SSc). We performed a systematic review to characterise the use and validation of pulmonary function tests (PFTs) as surrogate markers for systemic sclerosis-associated interstitial lung disease (SSc-ILD) progression.Five electronic databases were searched to identify all relevant studies. Included studies either used at least one PFT measure as a longitudinal outcome for SSc-ILD progression ( i.e. outcome studies) and/or reported at least one classical measure of validity for the PFTs in SSc-ILD ( i.e. validation studies).This systematic review included 169 outcome studies and 50 validation studies. Diffusing capacity of the lung for carbon monoxide ( D LCO ) was cumulatively the most commonly used outcome until 2010 when it was surpassed by forced vital capacity (FVC). FVC (% predicted) was the primary endpoint in 70.4% of studies, compared to 11.3% for % predicted D LCO Only five studies specifically aimed to validate the PFTs: two concluded that D LCO was the best measure of SSc-ILD extent, while the others did not favour any PFT. These studies also showed respectable validity measures for total lung capacity (TLC).Despite the current preference for FVC, available evidence suggests that D LCO and TLC should not yet be discounted as potential surrogate markers for SSc-ILD progression. Copyright ©ERS 2018.

Identification and Validation of SNP Markers Linked to Dwarf Traits Using SLAF-Seq Technology in Lagerstroemia

PubMed Central

Ju, Yiqian; Jiao, Yao; Feng, Lu; Pan, Huitang; Cheng, Tangren; Zhang, Qixiang

2016-01-01

The genetic control of plant architecture is a promising approach to breed desirable cultivars, particularly in ornamental flowers. In this study, the F1 population (142 seedlings) derived from Lagerstroemia fauriei (non-dwarf) × L. indica ‘Pocomoke’ (dwarf) was phenotyped for six traits (plant height (PH), internode length (IL), internode number, primary lateral branch height (PLBH), secondary lateral branch height and primary branch number), and the IL and PLBH traits were positively correlated with the PH trait and considered representative indexes of PH. Fifty non-dwarf and dwarf seedlings were pooled and subjected to a specific-locus amplified fragment sequencing (SLAF-seq) method, which screened 1221 polymorphic markers. A total of 3 markers segregating between bulks were validated in the F1 population, with the M16337 and M38412 markers highly correlated with the IL trait and the M25207 marker highly correlated with the PLBH trait. These markers provide a predictability of approximately 80% using a single marker (M25207) and a predictability of 90% using marker combinations (M16337 + M25207) in the F1 population, which revealed that the IL and the PLBH traits, especially the PLBH, were the decisive elements for PH in terms of molecular regulation. Further validation was performed in the BC1 population and a set of 28 Lagerstroemia stocks using allele-specific PCR (AS-PCR) technology, and the results showed the stability and reliability of the SNP markers and the co-determination of PH by multiple genes. Our findings provide an important theoretical and practical basis for the early prediction and indirect selection of PH using the IL and the PLBH, and the detected SNPs may be useful for marker-assisted selection (MAS) in crape myrtle. PMID:27404662

Only White Matter Hyperintensities Predicts Post-Stroke Cognitive Performances Among Cerebral Small Vessel Disease Markers: Results from the TABASCO Study.

PubMed

Molad, Jeremy; Kliper, Efrat; Korczyn, Amos D; Ben Assayag, Einor; Ben Bashat, Dafna; Shenhar-Tsarfaty, Shani; Aizenstein, Orna; Shopin, Ludmila; Bornstein, Natan M; Auriel, Eitan

2017-01-01

White matter hyperintensities (WMH) were shown to predict cognitive decline following stroke or transient ischemic attack (TIA). However, WMH are only one among other radiological markers of cerebral small vessel disease (SVD). The aim of this study was to determine whether adding other SVD markers to WMH improves prediction of post-stroke cognitive performances. Consecutive first-ever stroke or TIA patients (n = 266) from the Tel Aviv Acute Brain Stroke Cohort (TABASCO) study were enrolled. MRI scans were performed within seven days of stroke onset. We evaluated the relationship between cognitive performances one year following stroke, and previously suggested total SVD burden score including WMH, lacunes, cerebral microbleeds (CMB), and perivascular spaces (PVS). Significant negative associations were found between WMH and cognition (p < 0.05). Adding other SVD markers (lacunes, CMB, PVS) to WMH did not improve predication of post-stroke cognitive performances. Negative correlations between SVD burden score and cognitive scores were observed for global cognitive, memory, and visual spatial scores (all p < 0.05). However, following an adjustment for confounders, no associations remained significant. WMH score was associated with poor post-stroke cognitive performance. Adding other SVD markers or SVD burden score, however, did not improve prediction.

Google Goes Cancer: Improving Outcome Prediction for Cancer Patients by Network-Based Ranking of Marker Genes

PubMed Central

Roy, Janine; Aust, Daniela; Knösel, Thomas; Rümmele, Petra; Jahnke, Beatrix; Hentrich, Vera; Rückert, Felix; Niedergethmann, Marco; Weichert, Wilko; Bahra, Marcus; Schlitt, Hans J.; Settmacher, Utz; Friess, Helmut; Büchler, Markus; Saeger, Hans-Detlev; Schroeder, Michael; Pilarsky, Christian; Grützmann, Robert

2012-01-01

Predicting the clinical outcome of cancer patients based on the expression of marker genes in their tumors has received increasing interest in the past decade. Accurate predictors of outcome and response to therapy could be used to personalize and thereby improve therapy. However, state of the art methods used so far often found marker genes with limited prediction accuracy, limited reproducibility, and unclear biological relevance. To address this problem, we developed a novel computational approach to identify genes prognostic for outcome that couples gene expression measurements from primary tumor samples with a network of known relationships between the genes. Our approach ranks genes according to their prognostic relevance using both expression and network information in a manner similar to Google's PageRank. We applied this method to gene expression profiles which we obtained from 30 patients with pancreatic cancer, and identified seven candidate marker genes prognostic for outcome. Compared to genes found with state of the art methods, such as Pearson correlation of gene expression with survival time, we improve the prediction accuracy by up to 7%. Accuracies were assessed using support vector machine classifiers and Monte Carlo cross-validation. We then validated the prognostic value of our seven candidate markers using immunohistochemistry on an independent set of 412 pancreatic cancer samples. Notably, signatures derived from our candidate markers were independently predictive of outcome and superior to established clinical prognostic factors such as grade, tumor size, and nodal status. As the amount of genomic data of individual tumors grows rapidly, our algorithm meets the need for powerful computational approaches that are key to exploit these data for personalized cancer therapies in clinical practice. PMID:22615549

Derivation of genetic biomarkers for cancer risk stratification in Barrett's oesophagus: a prospective cohort study

PubMed Central

Timmer, Margriet R.; Martinez, Pierre; Lau, Chiu T.; Westra, Wytske M.; Calpe, Silvia; Rygiel, Agnieszka M.; Rosmolen, Wilda D.; Meijer, Sybren L.; ten Kate, Fiebo J.W.; Dijkgraaf, Marcel G.W.; Mallant-Hent, Rosalie C.; Naber, Anton H.J.; van Oijen, Arnoud H.A.M.; Baak, Lubbertus C.; Scholten, Pieter; Böhmer, Clarisse J.M.; Fockens, Paul; Maley, Carlo C.; Graham, Trevor A.; Bergman, Jacques J.G.H.M.; Krishnadath, Kausilia K.

2016-01-01

Objective The risk of developing adenocarcinoma in non-dysplastic Barrett's oesophagus is low and difficult to predict. Accurate tools for risk stratification are needed to increase the efficiency of surveillance. We aimed to develop a prediction model for progression using clinical variables and genetic markers. Methods In a prospective cohort of patients with non-dysplastic Barrett's oesophagus, we evaluated six molecular markers: p16, p53, Her-2/neu, 20q, MYC, and aneusomy by DNA fluorescence in situ hybridisation on brush cytology specimens. Primary study outcomes were the development of high-grade dysplasia or oesophageal adenocarcinoma. The most predictive clinical variables and markers were determined using Cox proportional-hazards models, receiver-operating-characteristic curves and a leave-one-out analysis. Results A total of 428 patients participated (345 men; median age 60 years) with a cumulative follow-up of 2019 patient-years (median 45 months per patient). Of these patients, 22 progressed; nine developed high-grade dysplasia and 13 oesophageal adenocarcinoma. The clinical variables, age and circumferential Barrett's length, and the markers, p16 loss, MYC gain, and aneusomy, were significantly associated with progression on univariate analysis. We defined an ‘Abnormal Marker Count’ that counted abnormalities in p16, MYC and aneusomy, which significantly improved risk prediction beyond using just age and Barrett's length. In multivariate analysis, these three factors identified a high-risk group with an 8.7-fold (95% CI, 2.6 to 29.8) increased hazard ratio compared with the low-risk group, with an area under the curve of 0.76 (95% CI, 0.66 to 0.86). Conclusion A prediction model based on age, Barrett's length, and the markers p16, MYC, and aneusomy determines progression risk in non-dysplastic Barrett's oesophagus. PMID:26104750

Predictive markers of honey bee colony collapse.

PubMed

Dainat, Benjamin; Evans, Jay D; Chen, Yan Ping; Gauthier, Laurent; Neumann, Peter

2012-01-01

Across the Northern hemisphere, managed honey bee colonies, Apis mellifera, are currently affected by abrupt depopulation during winter and many factors are suspected to be involved, either alone or in combination. Parasites and pathogens are considered as principal actors, in particular the ectoparasitic mite Varroa destructor, associated viruses and the microsporidian Nosema ceranae. Here we used long term monitoring of colonies and screening for eleven disease agents and genes involved in bee immunity and physiology to identify predictive markers of honeybee colony losses during winter. The data show that DWV, Nosema ceranae, Varroa destructor and Vitellogenin can be predictive markers for winter colony losses, but their predictive power strongly depends on the season. In particular, the data support that V. destructor is a key player for losses, arguably in line with its specific impact on the health of individual bees and colonies.

Predictive Markers of Honey Bee Colony Collapse

PubMed Central

Dainat, Benjamin; Evans, Jay D.; Chen, Yan Ping; Gauthier, Laurent; Neumann, Peter

2012-01-01

Across the Northern hemisphere, managed honey bee colonies, Apis mellifera, are currently affected by abrupt depopulation during winter and many factors are suspected to be involved, either alone or in combination. Parasites and pathogens are considered as principal actors, in particular the ectoparasitic mite Varroa destructor, associated viruses and the microsporidian Nosema ceranae. Here we used long term monitoring of colonies and screening for eleven disease agents and genes involved in bee immunity and physiology to identify predictive markers of honeybee colony losses during winter. The data show that DWV, Nosema ceranae, Varroa destructor and Vitellogenin can be predictive markers for winter colony losses, but their predictive power strongly depends on the season. In particular, the data support that V. destructor is a key player for losses, arguably in line with its specific impact on the health of individual bees and colonies. PMID:22384162

Change in urinary markers of osteoclast activity following palliative radiotherapy for bone metastases.

PubMed

Chow, E; Hird, A; Zhang, Liying; Sinclair, E; Danjoux, C; Barnes, E; Tsao, M; Barbera, L; Wong, Shun; Vieth, R

2009-05-01

To examine the effect of radiotherapy for bone metastases on urinary markers of osteoclast activity. Patients with radiological evidence of bone metastases planned for palliative radiotherapy were eligible for the study. A urine specimen was collected before and 1 month after radiotherapy to assess levels of calcium, creatinine, magnesium, phosphate, N-telopeptide and pyridinoline. The Brief Pain Inventory was completed in person at baseline and by telephone follow-up at 1 month after radiotherapy. Patients were classified as responders (complete or partial pain response) or non-responders (stable or progressive pain) to radiotherapy based on the International Bone Metastases Consensus Criteria for end point measurements. Absolute values of urine markers were compared between responders and non-responders, or between responders and patients with progression. Our study population consisted of 74 men and 51 women. A single 8 Gy or 20 Gy in five daily fractions were commonly employed. At the 1 month follow-up, all Brief Pain Inventory functional interference scores showed a highly significant decrease from baseline (P<0.01). From our study population, 58 (64%) were classified as responders and 57 (46%) as non-responders to radiotherapy. We compared the urinary markers between the responders and the non-responders. There were no statistically significant differences between the two groups either in terms of baseline markers or in terms of month 1 follow-up markers. There was no significant change from baseline to the 1 month follow-up in responders or in non-responders to radiotherapy. Baseline levels of urinary markers could not predict which patient would benefit from palliative radiotherapy.

Predicting Risk of Type 2 Diabetes Mellitus with Genetic Risk Models on the Basis of Established Genome-wide Association Markers: A Systematic Review

PubMed Central

Bao, Wei; Hu, Frank B.; Rong, Shuang; Rong, Ying; Bowers, Katherine; Schisterman, Enrique F.; Liu, Liegang; Zhang, Cuilin

2013-01-01

This study aimed to evaluate the predictive performance of genetic risk models based on risk loci identified and/or confirmed in genome-wide association studies for type 2 diabetes mellitus. A systematic literature search was conducted in the PubMed/MEDLINE and EMBASE databases through April 13, 2012, and published data relevant to the prediction of type 2 diabetes based on genome-wide association marker–based risk models (GRMs) were included. Of the 1,234 potentially relevant articles, 21 articles representing 23 studies were eligible for inclusion. The median area under the receiver operating characteristic curve (AUC) among eligible studies was 0.60 (range, 0.55–0.68), which did not differ appreciably by study design, sample size, participants’ race/ethnicity, or the number of genetic markers included in the GRMs. In addition, the AUCs for type 2 diabetes did not improve appreciably with the addition of genetic markers into conventional risk factor–based models (median AUC, 0.79 (range, 0.63–0.91) vs. median AUC, 0.78 (range, 0.63–0.90), respectively). A limited number of included studies used reclassification measures and yielded inconsistent results. In conclusion, GRMs showed a low predictive performance for risk of type 2 diabetes, irrespective of study design, participants’ race/ethnicity, and the number of genetic markers included. Moreover, the addition of genome-wide association markers into conventional risk models produced little improvement in predictive performance. PMID:24008910

Recent advances in development of marker-free transgenic plants: regulation and biosafety concern.

PubMed

Tuteja, Narendra; Verma, Shiv; Sahoo, Ranjan Kumar; Raveendar, Sebastian; Reddy, I N Bheema Lingeshwara

2012-03-01

During the efficient genetic transformation of plants with the gene of interest, some selectable marker genes are also used in order to identify the transgenic plant cells or tissues. Usually, antibiotic- or herbicide-selective agents and their corresponding resistance genes are used to introduce economically valuable genes into crop plants. From the biosafety authority and consumer viewpoints, the presence of selectable marker genes in released transgenic crops may be transferred to weeds or pathogenic microorganisms in the gastrointestinal tract or soil, making them resistant to treatment with herbicides or antibiotics, respectively. Sexual crossing also raises the problem of transgene expression because redundancy of transgenes in the genome may trigger homology-dependent gene silencing. The future potential of transgenic technologies for crop improvement depends greatly on our abilities to engineer stable expression of multiple transgenic traits in a predictable fashion and to prevent the transfer of undesirable transgenic material to non-transgenic crops and related species. Therefore, it is now essential to develop an efficient marker-free transgenic system. These considerations underline the development of various approaches designed to facilitate timely elimination of transgenes when their function is no longer needed. Due to the limiting number of available selectable marker genes, in future the stacking of transgenes will be increasingly desirable. The production of marker-free transgenic plants is now a critical requisite for their commercial deployment and also for engineering multiple and complex trait. Here we describe the current technologies to eliminate the selectable marker genes (SMG) in order to develop marker-free transgenic plants and also discuss the regulation and biosafety concern of genetically modified (GM) crops.

Predictive Role of Coagulation, Fibrinolytic, and Endothelial Markers in Patients with Atrial Fibrillation, Stroke, and Thromboembolism: A Meta-Analysis, Meta-Regression, and Systematic Review.

PubMed

Weymann, Alexander; Sabashnikov, Anton; Ali-Hasan-Al-Saegh, Sadeq; Popov, Aron-Frederik; Jalil Mirhosseini, Seyed; Baker, William L; Lotfaliani, Mohammadreza; Liu, Tong; Dehghan, Hamidreza; Yavuz, Senol; de Oliveira Sá, Michel Pompeu Barros; Jang, Jae-Sik; Zeriouh, Mohamed; Meng, Lei; D'Ascenzo, Fabrizio; Deshmukh, Abhishek J; Biondi-Zoccai, Guiseppe; Dohmen, Pascal M; Calkins, Hugh; Cardiac Surgery And Cardiology-Group Imcsc-Group, Integrated Meta-Analysis Of Cardiac

2017-03-31

BACKGROUND The pathophysiological mechanism associated with the higher prothrombotic tendency in atrial fibrillation (AF) is complex and multifactorial. However, the role of prothrombotic markers in AF remains inconclusive. MATERIAL AND METHODS We conducted a meta-analysis of observational studies evaluating the association of coagulation activation, fibrinolytic, and endothelial function with occurrence of AF and clinical adverse events. A comprehensive subgroup analysis and meta-regression was performed to explore potential sources of heterogeneity. RESULTS A literature search of major databases retrieved 1703 studies. After screening, a total of 71 studies were identified. Pooled analysis showed the association of coagulation markers (D-dimer (weighted mean difference (WMD) =197.67 and p<0.001), fibrinogen (WMD=0.43 and p<0.001), prothrombin fragment 1-2 (WMD=0.53 and p<0.001), antithrombin III (WMD=23.90 and p=0.004), thrombin-antithrombin (WMD=5.47 and p=0.004));  fibrinolytic markers (tissue-type plasminogen activator (t-PA) (WMD=2.13 and p<0.001), plasminogen activator inhibitor (WMD=11.44 and p<0.001), fibrinopeptide-A (WMD=4.13 and p=0.01)); and  endothelial markers (von Willebrand factor (WMD=27.01 and p<0.001) and soluble thrombomodulin (WMD=3.92 and p<0.001)) with AF. CONCLUSIONS The levels of coagulation, fibrinolytic, and endothelial markers have been reported to be significantly higher in AF patients than in SR patients.

Development of a Gene-Centered SSR Atlas as a Resource for Papaya (Carica papaya) Marker-Assisted Selection and Population Genetic Studies

PubMed Central

Vidal, Newton Medeiros; Grazziotin, Ana Laura; Ramos, Helaine Christine Cancela; Pereira, Messias Gonzaga; Venancio, Thiago Motta

2014-01-01

Carica papaya (papaya) is an economically important tropical fruit. Molecular marker-assisted selection is an inexpensive and reliable tool that has been widely used to improve fruit quality traits and resistance against diseases. In the present study we report the development and validation of an atlas of papaya simple sequence repeat (SSR) markers. We integrated gene predictions and functional annotations to provide a gene-centered perspective for marker-assisted selection studies. Our atlas comprises 160,318 SSRs, from which 21,231 were located in genic regions (i.e. inside exons, exon-intron junctions or introns). A total of 116,453 (72.6%) of all identified repeats were successfully mapped to one of the nine papaya linkage groups. Primer pairs were designed for markers from 9,594 genes (34.5% of the papaya gene complement). Using papaya-tomato orthology assessments, we assembled a list of 300 genes (comprising 785 SSRs) potentially involved in fruit ripening. We validated our atlas by screening 73 SSR markers (including 25 fruit ripening genes), achieving 100% amplification rate and uncovering 26% polymorphism rate between the parental genotypes (Sekati and JS12). The SSR atlas presented here is the first comprehensive gene-centered collection of annotated and genome positioned papaya SSRs. These features combined with thousands of high-quality primer pairs make the atlas an important resource for the papaya research community. PMID:25393538

Predictive Role of Coagulation, Fibrinolytic, and Endothelial Markers in Patients with Atrial Fibrillation, Stroke, and Thromboembolism: A Meta-Analysis, Meta-Regression, and Systematic Review

PubMed Central

Weymann, Alexander; Sabashnikov, Anton; Ali-Hasan-Al-Saegh, Sadeq; Popov, Aron-Frederik; Mirhosseini, Seyed Jalil; Baker, William L.; Lotfaliani, Mohammadreza; Liu, Tong; Dehghan, Hamidreza; Yavuz, Senol; de Oliveira Sá, Michel Pompeu Barros; Jang, Jae-Sik; Zeriouh, Mohamed; Meng, Lei; D’Ascenzo, Fabrizio; Deshmukh, Abhishek J.; Biondi-Zoccai, Giuseppe; Dohmen, Pascal M.; Calkins, Hugh

2017-01-01

Background The pathophysiological mechanism associated with the higher prothrombotic tendency in atrial fibrillation (AF) is complex and multifactorial. However, the role of prothrombotic markers in AF remains inconclusive. Material/Methods We conducted a meta-analysis of observational studies evaluating the association of coagulation activation, fibrinolytic, and endothelial function with occurrence of AF and clinical adverse events. A comprehensive subgroup analysis and meta-regression was performed to explore potential sources of heterogeneity. Results A literature search of major databases retrieved 1703 studies. After screening, a total of 71 studies were identified. Pooled analysis showed the association of coagulation markers (D-dimer (weighted mean difference (WMD)=197.67 and p<0.001), fibrinogen (WMD=0.43 and p<0.001), prothrombin fragment 1–2 (WMD=0.53 and p<0.001), antithrombin III (WMD=23.90 and p=0.004), thrombin-antithrombin (WMD=5.47 and p=0.004)); fibrinolytic markers (tissue-type plasminogen activator (t-PA) (WMD=2.13 and p<0.001), plasminogen activator inhibitor (WMD=11.44 and p<0.001), fibrinopeptide-A (WMD=4.13 and p=0.01)); and endothelial markers (von Willebrand factor (WMD=27.01 and p<0.001) and soluble thrombomodulin (WMD=3.92 and p<0.001)) with AF. Conclusions The levels of coagulation, fibrinolytic, and endothelial markers have been reported to be significantly higher in AF patients than in SR patients. PMID:28360407

The potential predictive value of circulating immune cell ratio and tumor marker in atezolizumab treated advanced non-small cell lung cancer patients.

PubMed

Zhuo, Minglei; Chen, Hanxiao; Zhang, Tianzhuo; Yang, Xue; Zhong, Jia; Wang, Yuyan; An, Tongtong; Wu, Meina; Wang, Ziping; Huang, Jing; Zhao, Jun

2018-05-04

The PD-L1 antibody atezolizumab has shown promising efficacy in patients with advanced non-small cell lung cancer. But the predictive marker of clinical benefit has not been identified. This study aimed to search for potential predictive factors in circulating blood of patients receiving atezolizumab. Ten patients diagnosed with advanced non-small cell lung cancer were enrolled in this open-label observing study. Circulating immune cells and plasma tumor markers were examined in peripheral blood from these patients before and after atezolizumab treatment respectively. Relation between changes in circulating factors and anti-tumor efficacy were analyzed. Blood routine test showed that atezolizumab therapy induced slightly elevation of white blood cells count generally. The lymphocyte ratio was increased slightly in disease controlled patients but decreased prominently in disease progressed patients in response to atezolizumab therapy. Flow cytometric analysis revealed changes in percentage of various immune cell types, including CD4+ T cell, CD8+ T cell, myeloid-derived suppressor cell, regulatory T cell and PD-1 expressing T cell after atezolizumab. Levels of plasma tumor marker CEA, CA125 and CA199 were also altered after anti-PD-L1 therapy. In comparison with baseline, the disease progressed patients showed sharp increase in tumor marker levels, while those disease controlled patients were seen with decreased regulatory T cell and myeloid-derived suppressor cell ratios. The circulating immune cell ratios and plasma tumor marker levels were related with clinical efficacy of atezolizumab therapy. These factors could be potential predictive marker for anti-PD-L1 therapy in advanced non-small cell lung cancer.

Metabolite and transcript markers for the prediction of potato drought tolerance.

PubMed

Sprenger, Heike; Erban, Alexander; Seddig, Sylvia; Rudack, Katharina; Thalhammer, Anja; Le, Mai Q; Walther, Dirk; Zuther, Ellen; Köhl, Karin I; Kopka, Joachim; Hincha, Dirk K

2018-04-01

Potato (Solanum tuberosum L.) is one of the most important food crops worldwide. Current potato varieties are highly susceptible to drought stress. In view of global climate change, selection of cultivars with improved drought tolerance and high yield potential is of paramount importance. Drought tolerance breeding of potato is currently based on direct selection according to yield and phenotypic traits and requires multiple trials under drought conditions. Marker-assisted selection (MAS) is cheaper, faster and reduces classification errors caused by noncontrolled environmental effects. We analysed 31 potato cultivars grown under optimal and reduced water supply in six independent field trials. Drought tolerance was determined as tuber starch yield. Leaf samples from young plants were screened for preselected transcript and nontargeted metabolite abundance using qRT-PCR and GC-MS profiling, respectively. Transcript marker candidates were selected from a published RNA-Seq data set. A Random Forest machine learning approach extracted metabolite and transcript markers for drought tolerance prediction with low error rates of 6% and 9%, respectively. Moreover, by combining transcript and metabolite markers, the prediction error was reduced to 4.3%. Feature selection from Random Forest models allowed model minimization, yielding a minimal combination of only 20 metabolite and transcript markers that were successfully tested for their reproducibility in 16 independent agronomic field trials. We demonstrate that a minimum combination of transcript and metabolite markers sampled at early cultivation stages predicts potato yield stability under drought largely independent of seasonal and regional agronomic conditions. © 2017 The Authors. Plant Biotechnology Journal published by Society for Experimental Biology and The Association of Applied Biologists and John Wiley & Sons Ltd.

MicroRNAs in prostate cancer: Functional role as biomarkers.

PubMed

Kanwal, Rajnee; Plaga, Alexis R; Liu, Xiaoqi; Shukla, Girish C; Gupta, Sanjay

2017-10-28

MicroRNAs (miRNAs) are small endogenous non-coding molecules that alters gene expression through post-transcriptional regulation of messenger RNA. Compelling evidence suggest the role of miRNA in cancer biology having potential as diagnostic, prognostic and predictive biomarkers. This review summarizes the current knowledge on miRNA deregulated in prostate cancer and their role as oncogene, tumor suppressor and metastasis regulators. The emerging information elucidating the biological function of miRNA is promising and may lead to their potential usefulness as diagnostic/prognostic markers and development as effective therapeutic tools for management of prostate cancer. Copyright © 2017 Elsevier B.V. All rights reserved.

Genomic Predictions and Genome-Wide Association Study of Resistance Against Piscirickettsia salmonis in Coho Salmon (Oncorhynchus kisutch) Using ddRAD Sequencing

PubMed Central

Barría, Agustín; Christensen, Kris A.; Yoshida, Grazyella M.; Correa, Katharina; Jedlicki, Ana; Lhorente, Jean P.; Davidson, William S.; Yáñez, José M.

2018-01-01

Piscirickettsia salmonis is one of the main infectious diseases affecting coho salmon (Oncorhynchus kisutch) farming, and current treatments have been ineffective for the control of this disease. Genetic improvement for P. salmonis resistance has been proposed as a feasible alternative for the control of this infectious disease in farmed fish. Genotyping by sequencing (GBS) strategies allow genotyping of hundreds of individuals with thousands of single nucleotide polymorphisms (SNPs), which can be used to perform genome wide association studies (GWAS) and predict genetic values using genome-wide information. We used double-digest restriction-site associated DNA (ddRAD) sequencing to dissect the genetic architecture of resistance against P. salmonis in a farmed coho salmon population and to identify molecular markers associated with the trait. We also evaluated genomic selection (GS) models in order to determine the potential to accelerate the genetic improvement of this trait by means of using genome-wide molecular information. A total of 764 individuals from 33 full-sib families (17 highly resistant and 16 highly susceptible) were experimentally challenged against P. salmonis and their genotypes were assayed using ddRAD sequencing. A total of 9,389 SNPs markers were identified in the population. These markers were used to test genomic selection models and compare different GWAS methodologies for resistance measured as day of death (DD) and binary survival (BIN). Genomic selection models showed higher accuracies than the traditional pedigree-based best linear unbiased prediction (PBLUP) method, for both DD and BIN. The models showed an improvement of up to 95% and 155% respectively over PBLUP. One SNP related with B-cell development was identified as a potential functional candidate associated with resistance to P. salmonis defined as DD. PMID:29440129

Immune monitoring after pediatric liver transplantation - the prospective ChilSFree cohort study.

PubMed

Goldschmidt, Imeke; Karch, André; Mikolajczyk, Rafael; Mutschler, Frauke; Junge, Norman; Pfister, Eva Doreen; Möhring, Tamara; d'Antiga, Lorenzo; McKiernan, Patrick; Kelly, Deirdre; Debray, Dominique; McLin, Valérie; Pawlowska, Joanna; Hierro, Loreto; Daemen, Kerstin; Keil, Jana; Falk, Christine; Baumann, Ulrich

2018-05-16

Although trough levels of immunosuppressive drugs are largely used to monitor immunosuppressive therapy after solid organ transplantation, there is still no established tool that allows for a validated assessment of functional degree of immunosuppression or the identification of clinically relevant over- or under-immunosuppression, depending on graft homeostasis. Reliable non-invasive markers to predict biopsy proven acute rejection (BPAR) do not exist. Literature data suggest that longitudinal measurements of immune markers might be predictive of BPAR, but data in children are scarce. We therefore propose an observational prospective cohort study focusing on immune monitoring in children after liver transplantation. We aim to describe immune function in a cohort of children before and during the first year after liver transplantation and plan to investigate how the immune function profile is associated with clinical and laboratory findings. In an international multicenter prospective approach, children with end-stage liver disease who undergo liver transplantation are enrolled to the study and receive extensive immune monitoring before and at 1, 2, 3, 4 weeks and 3, 6, 12 months after transplantation, and whenever a clinically indicated liver biopsy is scheduled. Blood samples are analyzed for immune cell numbers and circulating levels of cytokines, chemokines and factors of angiogenesis reflecting immune cell activation. Statistical analysis will focus on the identification of trajectorial patterns of immune reactivity predictive for systemic non-inflammatory states, infectious complications or BPAR using joint modelling approaches. The ChilSFree study will help to understand the immune response after pLTx in different states of infection or rejection. It may provide insight into response mechanisms eventually facilitating immune tolerance towards the graft. Our analysis may yield an applicable immune panel for non-invasive early detection of acute cellular rejection, with the prospect of individually tailoring immunosuppressive therapy. The international collaborative set-up of this study allows for an appropriate sample size which is otherwise difficult to achieve in the field of pediatric liver transplantation.

Validation of artificial neural network models for predicting biochemical markers associated with male infertility.

PubMed

Vickram, A S; Kamini, A Rao; Das, Raja; Pathy, M Ramesh; Parameswari, R; Archana, K; Sridharan, T B

2016-08-01

Seminal fluid is the secretion from many glands comprised of several organic and inorganic compounds including free amino acids, proteins, fructose, glucosidase, zinc, and other scavenging elements like Mg(2+), Ca(2+), K(+), and Na(+). Therefore, in the view of development of novel approaches and proper diagnosis to male infertility, overall understanding of the biochemical and molecular composition and its role in regulation of sperm quality is highly desirable. Perhaps this can be achieved through artificial intelligence. This study was aimed to elucidate and predict various biochemical markers present in human seminal plasma with three different neural network models. A total of 177 semen samples were collected for this research (both fertile and infertile samples) and immediately processed to prepare a semen analysis report, based on the protocol of the World Health Organization (WHO [2010]). The semen samples were then categorized into oligoasthenospermia (n=35), asthenospermia (n=35), azoospermia (n=22), normospermia (n=34), oligospermia (n=34), and control (n=17). The major biochemical parameters like total protein content, fructose, glucosidase, and zinc content were elucidated by standard protocols. All the biochemical markers were predicted by using three different artificial neural network (ANN) models with semen parameters as inputs. Of the three models, the back propagation neural network model (BPNN) yielded the best results with mean absolute error 0.025, -0.080, 0.166, and -0.057 for protein, fructose, glucosidase, and zinc, respectively. This suggests that BPNN can be used to predict biochemical parameters for the proper diagnosis of male infertility in assisted reproductive technology (ART) centres. AAS: absorption spectroscopy; AI: artificial intelligence; ANN: artificial neural networks; ART: assisted reproductive technology; BPNN: back propagation neural network model; DT: decision tress; MLP: multilayer perceptron; PESA: percutaneous epididymal sperm spiration; RBFN: radical basis function network; SRNN: simple recurrent neural network; SVM: support vector machines; TSE: testicular sperm extraction; WHO: World Health Organization.

DNA methylation screening of primary prostate tumors identifies SRD5A2 and CYP11A1 as candidate markers for assessing risk of biochemical recurrence.

PubMed

Horning, Aaron M; Awe, Julius A; Wang, Chiou-Miin; Liu, Joseph; Lai, Zhao; Wang, Vickie Yao; Jadhav, Rohit R; Louie, Anna D; Lin, Chun-Lin; Kroczak, Tad; Chen, Yidong; Jin, Victor X; Abboud-Werner, Sherry L; Leach, Robin J; Hernandez, Javior; Thompson, Ian M; Saranchuk, Jeff; Drachenberg, Darrel; Chen, Chun-Liang; Mai, Sabine; Huang, Tim Hui-Ming

2015-11-01

Altered DNA methylation in CpG islands of gene promoters has been implicated in prostate cancer (PCa) progression and can be used to predict disease outcome. In this study, we determine whether methylation changes of androgen biosynthesis pathway (ABP)-related genes in patients' plasma cell-free DNA (cfDNA) can serve as prognostic markers for biochemical recurrence (BCR). Methyl-binding domain capture sequencing (MBDCap-seq) was used to identify differentially methylated regions (DMRs) in primary tumors of patients who subsequently developed BCR or not, respectively. Methylation pyrosequencing of candidate loci was validated in cfDNA samples of 86 PCa patients taken at and/or post-radical prostatectomy (RP) using univariate and multivariate prediction analyses. Putative DMRs in 13 of 30 ABP-related genes were found between tumors of BCR (n = 12) versus no evidence of disease (NED) (n = 15). In silico analysis of The Cancer Genome Atlas data confirmed increased DNA methylation of two loci-SRD5A2 and CYP11A1, which also correlated with their decreased expression, in tumors with subsequent BCR development. Their aberrant cfDNA methylation was also associated with detectable levels of PSA taken after patients' post-RP. Multivariate analysis of the change in cfDNA methylation at all of CpG sites measured along with patient's treatment history predicted if a patient will develop BCR with 77.5% overall accuracy. Overall, increased DNA methylation of SRD5A2 and CYP11A1 related to androgen biosynthesis functions may play a role in BCR after patients' RP. The correlation between aberrant cfDNA methylation and detectable PSA in post-RP further suggests their utility as predictive markers for PCa recurrence. . © 2015 Wiley Periodicals, Inc.

Phenotype analysis of early risk factors from electronic medical records improves image-derived diagnostic classifiers for optic nerve pathology

NASA Astrophysics Data System (ADS)

Chaganti, Shikha; Nabar, Kunal P.; Nelson, Katrina M.; Mawn, Louise A.; Landman, Bennett A.

2017-03-01

We examine imaging and electronic medical records (EMR) of 588 subjects over five major disease groups that affect optic nerve function. An objective evaluation of the role of imaging and EMR data in diagnosis of these conditions would improve understanding of these diseases and help in early intervention. We developed an automated image processing pipeline that identifies the orbital structures within the human eyes from computed tomography (CT) scans, calculates structural size, and performs volume measurements. We customized the EMR-based phenome-wide association study (PheWAS) to derive diagnostic EMR phenotypes that occur at least two years prior to the onset of the conditions of interest from a separate cohort of 28,411 ophthalmology patients. We used random forest classifiers to evaluate the predictive power of image-derived markers, EMR phenotypes, and clinical visual assessments in identifying disease cohorts from a control group of 763 patients without optic nerve disease. Image-derived markers showed more predictive power than clinical visual assessments or EMR phenotypes. However, the addition of EMR phenotypes to the imaging markers improves the classification accuracy against controls: the AUC improved from 0.67 to 0.88 for glaucoma, 0.73 to 0.78 for intrinsic optic nerve disease, 0.72 to 0.76 for optic nerve edema, 0.72 to 0.77 for orbital inflammation, and 0.81 to 0.85 for thyroid eye disease. This study illustrates the importance of diagnostic context for interpretation of image-derived markers and the proposed PheWAS technique provides a flexible approach for learning salient features of patient history and incorporating these data into traditional machine learning analyses.

Screening for malnutrition in nursing home residents: comparison of different risk markers and their association to functional impairment.

PubMed

Stange, I; Poeschl, K; Stehle, P; Sieber, C C; Volkert, D

2013-04-01

To identify nursing home residents with malnutrition or at risk of malnutrition by using different markers, determine if the Mini Nutritional Assessment (MNA®) is able to identify all residents at risk according to single risk markers and explore the relation between risk markers and functional impairment. Cross-sectional study. Six German nursing homes. 286 residents (86±7y, 89% female). Screening for malnutrition or its risk included low BMI (≤22 kg/m²), recent weight loss (WL), low food intake (LI) as single risk markers and MNA (<24 points, p.) as composite marker. Prevalence of single nutritional risk markers in different MNA categories was compared by cross-tables. Mental (cognition, mood) and physical function (mobility) were assessed by interviewing nursing staff and association of impaired status to nutritional risk markers determined by Chi² test. 32.9% of residents had a low BMI, 11.9% WL and 21.3% LI. 60.2% were categorized malnourished (18.2%) or at risk of malnutrition (42.0%) by MNA. 64% presented at least one of these nutritional risk markers. Of those classified malnourished by MNA, 96.2% also showed low BMI, WL or LI. In contrast, eleven residents (9.6%) considered well-nourished by MNA presented single risk markers (9 low BMI, 2 WL). Cognitive impairment, depressive symptoms and immobility was present in 59.0%, 20.8% and 25.5%, respectively. Functional impairment, and in particular severe impairment, was to a higher proportion present in residents at nutritional risk independent of the chosen marker (MNA<24 p., low BMI, WL, LI). The high prevalence of nutritional risk highlights the importance of regular screening of nursing home residents. The MNA identified nearly all residents with low BMI, WL and LI. The close association between nutritional risk and functional impairment requires increased awareness for nutritional problems especially in functionally impaired residents, to early initiate nutritional measures and thus, prevent further nutritional and functional deterioration.

Prognostic factors, predictive markers and cancer biology: the triad for successful oral cancer chemoprevention.

PubMed

Monteiro de Oliveira Novaes, Jose Augusto; William, William N

2016-10-01

Oral squamous cell carcinomas represent a significant cancer burden worldwide. Unfortunately, chemoprevention strategies investigated to date have failed to produce an agent considered standard of care to prevent oral cancers. Nonetheless, recent advances in clinical trial design may streamline drug development in this setting. In this manuscript, we review some of these improvements, including risk prediction tools based on molecular markers that help select patients most suitable for chemoprevention. We also discuss the opportunities that novel preclinical models and modern molecular profiling techniques will bring to the prevention field in the near future, and propose a clinical trials framework that incorporates molecular prognostic factors, predictive markers and cancer biology as a roadmap to improve chemoprevention strategies for oral cancers.

Optimum location of external markers using feature selection algorithms for real‐time tumor tracking in external‐beam radiotherapy: a virtual phantom study

PubMed Central

Nankali, Saber; Miandoab, Payam Samadi; Baghizadeh, Amin

2016-01-01

In external‐beam radiotherapy, using external markers is one of the most reliable tools to predict tumor position, in clinical applications. The main challenge in this approach is tumor motion tracking with highest accuracy that depends heavily on external markers location, and this issue is the objective of this study. Four commercially available feature selection algorithms entitled 1) Correlation‐based Feature Selection, 2) Classifier, 3) Principal Components, and 4) Relief were proposed to find optimum location of external markers in combination with two “Genetic” and “Ranker” searching procedures. The performance of these algorithms has been evaluated using four‐dimensional extended cardiac‐torso anthropomorphic phantom. Six tumors in lung, three tumors in liver, and 49 points on the thorax surface were taken into account to simulate internal and external motions, respectively. The root mean square error of an adaptive neuro‐fuzzy inference system (ANFIS) as prediction model was considered as metric for quantitatively evaluating the performance of proposed feature selection algorithms. To do this, the thorax surface region was divided into nine smaller segments and predefined tumors motion was predicted by ANFIS using external motion data of given markers at each small segment, separately. Our comparative results showed that all feature selection algorithms can reasonably select specific external markers from those segments where the root mean square error of the ANFIS model is minimum. Moreover, the performance accuracy of proposed feature selection algorithms was compared, separately. For this, each tumor motion was predicted using motion data of those external markers selected by each feature selection algorithm. Duncan statistical test, followed by F‐test, on final results reflected that all proposed feature selection algorithms have the same performance accuracy for lung tumors. But for liver tumors, a correlation‐based feature selection algorithm, in combination with a genetic search algorithm, proved to yield best performance accuracy for selecting optimum markers. PACS numbers: 87.55.km, 87.56.Fc PMID:26894358

Optimum location of external markers using feature selection algorithms for real-time tumor tracking in external-beam radiotherapy: a virtual phantom study.

PubMed

Nankali, Saber; Torshabi, Ahmad Esmaili; Miandoab, Payam Samadi; Baghizadeh, Amin

2016-01-08

In external-beam radiotherapy, using external markers is one of the most reliable tools to predict tumor position, in clinical applications. The main challenge in this approach is tumor motion tracking with highest accuracy that depends heavily on external markers location, and this issue is the objective of this study. Four commercially available feature selection algorithms entitled 1) Correlation-based Feature Selection, 2) Classifier, 3) Principal Components, and 4) Relief were proposed to find optimum location of external markers in combination with two "Genetic" and "Ranker" searching procedures. The performance of these algorithms has been evaluated using four-dimensional extended cardiac-torso anthropomorphic phantom. Six tumors in lung, three tumors in liver, and 49 points on the thorax surface were taken into account to simulate internal and external motions, respectively. The root mean square error of an adaptive neuro-fuzzy inference system (ANFIS) as prediction model was considered as metric for quantitatively evaluating the performance of proposed feature selection algorithms. To do this, the thorax surface region was divided into nine smaller segments and predefined tumors motion was predicted by ANFIS using external motion data of given markers at each small segment, separately. Our comparative results showed that all feature selection algorithms can reasonably select specific external markers from those segments where the root mean square error of the ANFIS model is minimum. Moreover, the performance accuracy of proposed feature selection algorithms was compared, separately. For this, each tumor motion was predicted using motion data of those external markers selected by each feature selection algorithm. Duncan statistical test, followed by F-test, on final results reflected that all proposed feature selection algorithms have the same performance accuracy for lung tumors. But for liver tumors, a correlation-based feature selection algorithm, in combination with a genetic search algorithm, proved to yield best performance accuracy for selecting optimum markers.

Genomic Prediction for Quantitative Traits Is Improved by Mapping Variants to Gene Ontology Categories in Drosophila melanogaster

PubMed Central

Edwards, Stefan M.; Sørensen, Izel F.; Sarup, Pernille; Mackay, Trudy F. C.; Sørensen, Peter

2016-01-01

Predicting individual quantitative trait phenotypes from high-resolution genomic polymorphism data is important for personalized medicine in humans, plant and animal breeding, and adaptive evolution. However, this is difficult for populations of unrelated individuals when the number of causal variants is low relative to the total number of polymorphisms and causal variants individually have small effects on the traits. We hypothesized that mapping molecular polymorphisms to genomic features such as genes and their gene ontology categories could increase the accuracy of genomic prediction models. We developed a genomic feature best linear unbiased prediction (GFBLUP) model that implements this strategy and applied it to three quantitative traits (startle response, starvation resistance, and chill coma recovery) in the unrelated, sequenced inbred lines of the Drosophila melanogaster Genetic Reference Panel. Our results indicate that subsetting markers based on genomic features increases the predictive ability relative to the standard genomic best linear unbiased prediction (GBLUP) model. Both models use all markers, but GFBLUP allows differential weighting of the individual genetic marker relationships, whereas GBLUP weighs the genetic marker relationships equally. Simulation studies show that it is possible to further increase the accuracy of genomic prediction for complex traits using this model, provided the genomic features are enriched for causal variants. Our GFBLUP model using prior information on genomic features enriched for causal variants can increase the accuracy of genomic predictions in populations of unrelated individuals and provides a formal statistical framework for leveraging and evaluating information across multiple experimental studies to provide novel insights into the genetic architecture of complex traits. PMID:27235308

Altered expression of HER-2 and the mismatch repair genes MLH1 and MSH2 predicts the outcome of T1 high-grade bladder cancer.

PubMed

Sanguedolce, Francesca; Cormio, Antonella; Massenio, Paolo; Pedicillo, Maria C; Cagiano, Simona; Fortunato, Francesca; Calò, Beppe; Di Fino, Giuseppe; Carrieri, Giuseppe; Bufo, Pantaleo; Cormio, Luigi

2018-04-01

The identification of factors predicting the outcome of stage T1 high-grade bladder cancer (BC) is a major clinical issue. We performed immunohistochemistry to assess the role of human epidermal growth factor receptor-2 (HER-2) and microsatellite instability (MSI) factors MutL homologue 1 (MLH1) and MutS homologue 2 (MSH2) in predicting recurrence and progression of T1 high-grade BCs having undergone transurethral resection of bladder tumor (TURBT) alone or TURBT + intravesical instillations of bacillus Calmette-Guerin (BCG). HER-2 overexpression was a significant predictor of disease-free survival (DFS) in the overall as well as in the two patients' population; as for progression-free survival (PFS), it was significant in the overall but not in the two patients' population. MLH1 was an independent predictor of PFS only in patients treated with BCG and MSH2 failed to predict DFS and PFS in all populations. Most importantly, the higher the number of altered markers the lowers the DFS and PFS. In multivariate Cox proportional-hazards regression analysis, the number of altered molecular markers and BCG treatment were significant predictors (p = 0.0004 and 0.0283, respectively) of DFS, whereas the number of altered molecular markers was the only significant predictor (p = 0.0054) of PFS. Altered expression of the proto-oncogene HER-2 and the two molecular markers of genetic instability MLH1 and MSH2 predicted T1 high-grade BC outcome with the higher the number of altered markers the lower the DFS and PFS. These findings provide grounds for further testing them in predicting the outcome of this challenging disease.

[Comparison of various noninvasive serum markers of liver fibrosis in chronic viral liver disease].

PubMed

Kim, Sun Min; Sohn, Joo Hyun; Kim, Tae Yeob; Roh, Young Wook; Eun, Chang Soo; Jeon, Yong Cheol; Han, Dong Soo; Oh, Young Ha

2009-12-01

The aim of this study was to determine the clinical performances of noninvasive serum markers for the prediction of liver fibrosis in chronic viral liver diseases. We analyzed a total of 225 patients with chronic viral liver diseases (180 with hepatitis B virus, 43 with hepatitis C virus, and 2 with hepatitis B+C virus) who underwent a liver biopsy procedure at the Hanyang University Guri Hospital between March 2002 and February 2007. Serum was also obtained at the time of liver biopsy. Liver fibrosis was staged according to the scoring system proposed by the Korean Study Group for the Pathology of Digestive Diseases. Various noninvasive serum markers were evaluated, including the aspartate aminotransferase (AST)/alanine aminotransferase (ALT) ratio (AAR), age-platelet (AP) index, AST/platelet ratio index (APRI), cirrhosis discriminant score (CDS), platelet count, hyaluronic acid (HA), and type IV collagen. There were 17, 40, 61, 74, and 33 patients at stages F0, F1, F2, F3, and F4, respectively. The overall diagnostic accuracies of each marker, as determined by the area under receiver operating characteristics curves, were APRI=0.822, CDS=0.776, platelet count=0.773, AP index=0.756, HA=0.749, type IV collagen=0.718, and AAR=0.642 for predicting significant fibrosis (> or =F2); and CDS=0.835, platelet count=0.795, AP index=0.794, HA=0.766, AAR=0.711, type IV collagen=0.697, and APRI=0.691 for predicting extensive fibrosis (> or =F3). All noninvasive serum markers evaluated in this study were useful for predicting significant or extensive liver fibrosis in chronic viral liver diseases. In particular, APRI was most useful for the prediction of significant fibrosis, and CDS was most useful for the prediction of extensive fibrosis.

Prosody and Functions of Discourse Markers in Mandarin Chinese Conversation: The Cases of "Ranhou," "Wo Juede," and "Meiyou"

ERIC Educational Resources Information Center

Wang, Wei

2017-01-01

This study investigates Mandarin discourse markers from both functional and prosodic perspectives. Discourse markers are defined as sequentially dependent elements which bracket units of talk (Schiffrin 1987). In this study, I focus on three discourse markers, "ranhou" "then", "wo juede" "I think/feel", and…

Association of Elevated Reward Prediction Error Response With Weight Gain in Adolescent Anorexia Nervosa.

PubMed

DeGuzman, Marisa; Shott, Megan E; Yang, Tony T; Riederer, Justin; Frank, Guido K W

2017-06-01

Anorexia nervosa is a psychiatric disorder of unknown etiology. Understanding associations between behavior and neurobiology is important in treatment development. Using a novel monetary reward task during functional magnetic resonance brain imaging, the authors tested how brain reward learning in adolescent anorexia nervosa changes with weight restoration. Female adolescents with anorexia nervosa (N=21; mean age, 16.4 years [SD=1.9]) underwent functional MRI (fMRI) before and after treatment; similarly, healthy female control adolescents (N=21; mean age, 15.2 years [SD=2.4]) underwent fMRI on two occasions. Brain function was tested using the reward prediction error construct, a computational model for reward receipt and omission related to motivation and neural dopamine responsiveness. Compared with the control group, the anorexia nervosa group exhibited greater brain response 1) for prediction error regression within the caudate, ventral caudate/nucleus accumbens, and anterior and posterior insula, 2) to unexpected reward receipt in the anterior and posterior insula, and 3) to unexpected reward omission in the caudate body. Prediction error and unexpected reward omission response tended to normalize with treatment, while unexpected reward receipt response remained significantly elevated. Greater caudate prediction error response when underweight was associated with lower weight gain during treatment. Punishment sensitivity correlated positively with ventral caudate prediction error response. Reward system responsiveness is elevated in adolescent anorexia nervosa when underweight and after weight restoration. Heightened prediction error activity in brain reward regions may represent a phenotype of adolescent anorexia nervosa that does not respond well to treatment. Prediction error response could be a neurobiological marker of illness severity that can indicate individual treatment needs.

Association of Elevated Reward Prediction Error Response With Weight Gain in Adolescent Anorexia Nervosa

PubMed Central

DeGuzman, Marisa; Shott, Megan E.; Yang, Tony T.; Riederer, Justin; Frank, Guido K.W.

2017-01-01

Objective Anorexia nervosa is a psychiatric disorder of unknown etiology. Understanding associations between behavior and neurobiology is important in treatment development. Using a novel monetary reward task during functional magnetic resonance brain imaging, the authors tested how brain reward learning in adolescent anorexia nervosa changes with weight restoration. Method Female adolescents with anorexia nervosa (N=21; mean age, 15.2 years [SD=2.4]) underwent functional MRI (fMRI) before and after treatment; similarly, healthy female control adolescents (N=21; mean age, 16.4 years [SD=1.9]) underwent fMRI on two occasions. Brain function was tested using the reward prediction error construct, a computational model for reward receipt and omission related to motivation and neural dopamine responsiveness. Results Compared with the control group, the anorexia nervosa group exhibited greater brain response 1) for prediction error regression within the caudate, ventral caudate/nucleus accumbens, and anterior and posterior insula, 2) to unexpected reward receipt in the anterior and posterior insula, and 3) to unexpected reward omission in the caudate body. Prediction error and unexpected reward omission response tended to normalize with treatment, while unexpected reward receipt response remained significantly elevated. Greater caudate prediction error response when underweight was associated with lower weight gain during treatment. Punishment sensitivity correlated positively with ventral caudate prediction error response. Conclusions Reward system responsiveness is elevated in adolescent anorexia nervosa when underweight and after weight restoration. Heightened prediction error activity in brain reward regions may represent a phenotype of adolescent anorexia nervosa that does not respond well to treatment. Prediction error response could be a neurobiological marker of illness severity that can indicate individual treatment needs. PMID:28231717

Exhaustion of Activated CD8 T Cells Predicts Disease Progression in Primary HIV-1 Infection

PubMed Central

Hickling, Stephen; Hurst, Jacob; Meyerowitz, Jodi; Willberg, Christian B.; Robinson, Nicola; Brown, Helen; Kinloch, Sabine; Babiker, Abdel; Nwokolo, Nneka; Fox, Julie; Fidler, Sarah; Phillips, Rodney; Frater, John

2016-01-01

The rate at which HIV-1 infected individuals progress to AIDS is highly variable and impacted by T cell immunity. CD8 T cell inhibitory molecules are up-regulated in HIV-1 infection and associate with immune dysfunction. We evaluated participants (n = 122) recruited to the SPARTAC randomised clinical trial to determine whether CD8 T cell exhaustion markers PD-1, Lag-3 and Tim-3 were associated with immune activation and disease progression. Expression of PD-1, Tim-3, Lag-3 and CD38 on CD8 T cells from the closest pre-therapy time-point to seroconversion was measured by flow cytometry, and correlated with surrogate markers of HIV-1 disease (HIV-1 plasma viral load (pVL) and CD4 T cell count) and the trial endpoint (time to CD4 count <350 cells/μl or initiation of antiretroviral therapy). To explore the functional significance of these markers, co-expression of Eomes, T-bet and CD39 was assessed. Expression of PD-1 on CD8 and CD38 CD8 T cells correlated with pVL and CD4 count at baseline, and predicted time to the trial endpoint. Lag-3 expression was associated with pVL but not CD4 count. For all exhaustion markers, expression of CD38 on CD8 T cells increased the strength of associations. In Cox models, progression to the trial endpoint was most marked for PD-1/CD38 co-expressing cells, with evidence for a stronger effect within 12 weeks from confirmed diagnosis of PHI. The effect of PD-1 and Lag-3 expression on CD8 T cells retained statistical significance in Cox proportional hazards models including antiretroviral therapy and CD4 count, but not pVL as co-variants. Expression of ‘exhaustion’ or ‘immune checkpoint’ markers in early HIV-1 infection is associated with clinical progression and is impacted by immune activation and the duration of infection. New markers to identify exhausted T cells and novel interventions to reverse exhaustion may inform the development of novel immunotherapeutic approaches. PMID:27415828

Associations Between Serum Bone Biomarkers in Early Breast Cancer and Development of Bone Metastasis: Results From the AZURE (BIG01/04) Trial.

PubMed

Brown, Janet; Rathbone, Emma; Hinsley, Samantha; Gregory, Walter; Gossiel, Fatma; Marshall, Helen; Burkinshaw, Roger; Shulver, Helen; Thandar, Hasina; Bertelli, Gianfilippo; Maccon, Keane; Bowman, Angela; Hanby, Andrew; Bell, Richard; Cameron, David; Coleman, Robert

2018-02-07

Adjuvant therapies can prevent/delay bone metastasis development in breast cancer. We investigated whether serum bone turnover markers in early disease have clinical utility in identifying patients with a high risk of developing bone metastasis. Markers of bone formation (N-terminal propeptide of type-1 collagen [P1NP]) and bone resorption (C-telopeptide of type-1 collagen [CTX], pyridinoline cross-linked carboxy-terminal telopeptide of type-1 collagen [1-CTP]) were measured in baseline (pretreatment blood samples from 872 patients from a large randomized trial of adjuvant zoledronic acid (AZURE-ISRCTN79831382) in early breast cancer. Cox proportional hazards regression and cumulative incidence functions (adjusted for factors having a statistically significant effect on outcome) were used to investigate prognostic and predictive associations between recurrence events, bone marker levels, and clinical variables. All statistical tests were two-sided. When considered as continuous variables (log transformed), P1NP, CTX, and 1-CTP were each prognostic for future bone recurrence at any time (P = .006, P = .009, P = .008, respectively). Harrell's c-indices were a P1NP of 0.57 (95% confidence interval [CI] = 0.51 to 0.63), CTX of 0.57 (95% CI = 0.51 to 0.62), and 1-CTP of 0.57 (95% CI = 0.52 to 0.63). In categorical analyses based on the normal range, high baseline P1NP (>70 ng/mL) and CTX (>0.299 ng/mL), but not 1-CTP (>4.2 ng/mL), were also prognostic for future bone recurrence (P = .03, P = .03, P = .10, respectively). None of the markers were prognostic for overall distant recurrence; that is, they were bone metastasis specific, and none of the markers were predictive of treatment benefit from zoledronic acid. Serum P1NP, CTX, and 1-CTP are clinically useful, easily measured markers that show good prognostic ability (though low-to-moderate discrimination) for bone-specific recurrence and are worthy of further study. © The Author(s) 2018. Published by Oxford University Press.

Pretransplant Recipient Circulating CD4+CD127lo/- Tumor Necrosis Factor Receptor 2+ Regulatory T Cells: A Surrogate of Regulatory T Cell-Suppressive Function and Predictor of Delayed and Slow Graft Function After Kidney Transplantation.

PubMed

Nguyen, Minh-Tri J P; Fryml, Elise; Sahakian, Sossy K; Liu, Shuqing; Cantarovich, Marcelo; Lipman, Mark; Tchervenkov, Jean I; Paraskevas, Steven

2016-02-01

Delayed graft function (DGF) and slow graft function (SGF) are ischemia-reperfusion-associated acute kidney injuries (AKI) that decrease long-term graft survival after kidney transplantation. Regulatory T (Treg) cells are protective in murine AKI, and their suppressive function predictive of AKI in kidney transplantation. The conventional Treg cell function coculture assay is however time-consuming and labor intensive. We sought a simpler alternative to measure Treg cell function and predict AKI. In this prospective observational cohort study, pretransplant recipient circulating CD4+CD25+CD127lo/- and CD4+CD127lo/- tumor necrosis factor receptor 2 (TNFR2)+ Treg cells were measured by flow cytometry in 76 deceased donor kidney transplant recipients (DGF, n = 18; SGF, n = 34; immediate graft function [IGF], n = 24). In a subset of 37 recipients, pretransplant circulating Treg cell-suppressive function was also quantified by measuring the suppression of autologous effector T-cell proliferation by Treg cell in coculture. The TNFR2+ expression on CD4+CD127lo/- T cells correlated with Treg cell-suppressive function (r = 0.63, P < 0.01). In receiver operating characteristic curves, percentage and absolute number of CD4+CD127lo/-TNFR2+ Treg cell predicted DGF from non-DGF (IGF + SGF) with area under the curves of 0.75 and 0.77, respectively, and also AKI (DGF + SGF) from IGF with area under the curves of 0.76 and 0.72, respectively (P < 0.01). Prediction of AKI (DGF + SGF) from IGF remained significant in multivariate logistic regression accounting for cold ischemic time, donor age, previous transplant, and pretransplant dialysis modality. Pretransplant recipient circulating CD4+CD127lo/-TNFR2+ Treg cell is potentially a simpler alternative to Treg cell function as a pretransplant recipient immune marker for AKI (DGF + SGF), independent from donor and organ procurement characteristics.

Biomarkers and Surrogate Markers: An FDA Perspective

PubMed Central

Katz, Russell

2004-01-01

Summary: Interest is increasing rapidly in the use of surrogate markers as primary measures of the effectiveness of investigational drugs in definitive drug trials. Many such surrogate markers have been proposed as potential candidates for use in definitive effectiveness trials of agents to treat neurologic or psychiatric disease, but as of this date, there are no such markers that have been adequately “validated,” that is, shown to predict the effect of the treatment on the clinical outcome of interest. While the current law and regulations permit the United States Food and Drug Administration to base the approval of a drug product on a determination the effect of the drug on an unvalidated surrogate marker (that is, one for which it is not known that an effect on the surrogate actually predicts the desired clinical benefit), there are a number of difficulties in interpreting trials that use surrogate markers as primary measures of drug effect. In this article, the relevant regulatory context will be discussed, as well as the epistemological problems related to the interpretation of clinical trials in which unvalidated surrogate markers are used as primary outcomes. PMID:15717019

Single Nucleotide Polymorphisms of Stemness Genes Predicted to Regulate RNA Splicing, microRNA and Oncogenic Signaling are Associated with Prostate Cancer Survival.

PubMed

Freedman, Jennifer A; Wang, Yanru; Li, Xuechan; Liu, Hongliang; Moorman, Patricia G; George, Daniel J; Lee, Norman H; Hyslop, Terry; Wei, Qingyi; Patierno, Steven R

2018-05-03

Prostate cancer is a clinically and molecularly heterogeneous disease, with variation in outcomes only partially predicted by grade and stage. Additional tools to distinguish indolent from aggressive disease are needed. Phenotypic characteristics of stemness correlate with poor cancer prognosis. Given this correlation, we identified single nucleotide polymorphisms (SNPs) of stemness-related genes and examined their associations with prostate cancer survival. SNPs within stemness-related genes were analyzed for association with overall survival of prostate cancer in the Prostate, Lung, Colorectal and Ovarian Cancer Screening Trial. Significant SNPs predicted to be functional were selected for linkage disequilibrium analysis and combined and stratified analyses. Identified SNPs were evaluated for association with gene expression. SNPs of CD44 (rs9666607), ABCC1 (rs35605 and rs212091) and GDF15 (rs1058587) were associated with prostate cancer survival and predicted to be functional. A role for rs9666607 of CD44 and rs35605 of ABCC1 in RNA splicing regulation, rs212091 of ABCC1 in miRNA binding site activity and rs1058587 of GDF15 in causing an amino acid change was predicted. These SNPs represent potential novel prognostic markers for overall survival of prostate cancer and support a contribution of the stemness pathway to prostate cancer patient outcome.

Predicting fibromyalgia, a narrative review: are we better than fools and children?

PubMed

Ablin, J N; Buskila, D

2014-09-01

Fibromyalgia syndrome (FMS) is a common and intriguing condition, manifest by chronic pain and fatigue. Although the pathogenesis of FMS is not yet completely understood, predicting the future development of FMS and chronic pain is a major challenge with great potential advantages, both from an individual as well as an epidemiological standpoint. Current knowledge indicates a genetic underpinning for FMS, and as increasing data are accumulated regarding the genetics involved, the prospect of utilizing these data for prediction becomes ever more attractive. The co-existence of FMS with multiple other functional disorders indicates that the clinical identification of such symptom constellations in a patient can alert the physician to the future development of FMS. Hypermobility syndrome is another clinical (as well as genetic) phenotype that has emerged as a risk factor for the development of FMS. Stressful events, including early life trauma, are also harbingers of the future development of FMS. Functional neuroimaging may help to elucidate the neural processes involved in central sensitization, and may ultimately also evolve into markers of predictive value. Last but not least, obesity and disturbed sleep are clinical (inter-related) features relevant for this spectrum. Future efforts will aim at integrating genetic, clinical and physiological data in the prediction of FMS and chronic pain. © 2014 European Pain Federation - EFIC®

Genomic Model with Correlation Between Additive and Dominance Effects.

PubMed

Xiang, Tao; Christensen, Ole Fredslund; Vitezica, Zulma Gladis; Legarra, Andres

2018-05-09

Dominance genetic effects are rarely included in pedigree-based genetic evaluation. With the availability of single nucleotide polymorphism markers and the development of genomic evaluation, estimates of dominance genetic effects have become feasible using genomic best linear unbiased prediction (GBLUP). Usually, studies involving additive and dominance genetic effects ignore possible relationships between them. It has been often suggested that the magnitude of functional additive and dominance effects at the quantitative trait loci are related, but there is no existing GBLUP-like approach accounting for such correlation. Wellmann and Bennewitz showed two ways of considering directional relationships between additive and dominance effects, which they estimated in a Bayesian framework. However, these relationships cannot be fitted at the level of individuals instead of loci in a mixed model and are not compatible with standard animal or plant breeding software. This comes from a fundamental ambiguity in assigning the reference allele at a given locus. We show that, if there has been selection, assigning the most frequent as the reference allele orients the correlation between functional additive and dominance effects. As a consequence, the most frequent reference allele is expected to have a positive value. We also demonstrate that selection creates negative covariance between genotypic additive and dominance genetic values. For parameter estimation, it is possible to use a combined additive and dominance relationship matrix computed from marker genotypes, and to use standard restricted maximum likelihood (REML) algorithms based on an equivalent model. Through a simulation study, we show that such correlations can easily be estimated by mixed model software and accuracy of prediction for genetic values is slightly improved if such correlations are used in GBLUP. However, a model assuming uncorrelated effects and fitting orthogonal breeding values and dominant deviations performed similarly for prediction. Copyright © 2018, Genetics.

Novel prognostic tissue markers in congestive heart failure.

PubMed

Stone, James R

2015-01-01

Heart failure is a relatively common disorder associated with high morbidity, mortality, and economic burden. Better tools to predict outcomes for patients with heart failure could allow for better decision making concerning patient treatment and management and better utilization of health care resources. Endomyocardial biopsy offers a mechanism to pathologically diagnose specific diseases in patients with heart failure, but such biopsies can often be negative, with no specific diagnostic information. Novel tissue markers in endomyocardial biopsies have been identified that may be useful in assessing prognosis in heart failure patients. Such tissue markers include ubiquitin, Gremlin-1, cyclophilin A, and heterogeneous nuclear ribonucleoprotein C. In some cases, tissue markers have been found to be independent of and even superior to clinical indices and serum markers in predicting prognosis for heart failure patients. In some cases, these novel tissue markers appear to offer prognostic information even in the setting of an otherwise negative endomyocardial biopsy. Copyright © 2014 Elsevier Inc. All rights reserved.

Functional Roles of Neural Preparatory Processes in a Cued Stroop Task Revealed by Linking Electrophysiology with Behavioral Performance

PubMed Central

Wang, Chao; Ding, Mingzhou; Kluger, Benzi M.

2015-01-01

It is well established that cuing facilitates behavioral performance and that different aspects of instructional cues evoke specific neural preparatory processes in cued task-switching paradigms. To deduce the functional role of these neural preparatory processes the majority of studies vary aspects of the experimental paradigm and describe how these variations alter markers of neural preparatory processes. Although these studies provide important insights, they also have notable limitations, particularly in terms of understanding the causal or functional relationship of neural markers to cognitive and behavioral processes. In this study, we sought to address these limitations and uncover the functional roles of neural processes by examining how variability in the amplitude of neural preparatory processes predicts behavioral performance to subsequent stimuli. To achieve this objective 16 young adults were recruited to perform a cued Stroop task while their brain activity was measured using high-density electroencephalography. Four temporally overlapping but functionally and topographically distinct cue-triggered event related potentials (ERPs) were identified: 1) A left-frontotemporal negativity (250-700 ms) that was positively associated with word-reading performance; 2) a midline-frontal negativity (450-800 ms) that was positively associated with color-naming and incongruent performance; 3) a left-frontal negativity (450-800 ms) that was positively associated with switch trial performance; and 4) a centroparietal positivity (450-800 ms) that was positively associated with performance for almost all trial types. These results suggest that at least four dissociable cognitive processes are evoked by instructional cues in the present task, including: 1) domain-specific task facilitation; 2) switch-specific task-set reconfiguration; 3) preparation for response conflict; and 4) proactive attentional control. Examining the relationship between ERPs and behavioral performance provides a functional link between neural markers and the cognitive processes they index. PMID:26230662

Clinical Relevance of Prognostic and Predictive Molecular Markers in Gliomas.

PubMed

Siegal, Tali

2016-01-01

Sorting and grading of glial tumors by the WHO classification provide clinicians with guidance as to the predicted course of the disease and choice of treatment. Nonetheless, histologically identical tumors may have very different outcome and response to treatment. Molecular markers that carry both diagnostic and prognostic information add useful tools to traditional classification by redefining tumor subtypes within each WHO category. Therefore, molecular markers have become an integral part of tumor assessment in modern neuro-oncology and biomarker status now guides clinical decisions in some subtypes of gliomas. The routine assessment of IDH status improves histological diagnostic accuracy by differentiating diffuse glioma from reactive gliosis. It carries a favorable prognostic implication for all glial tumors and it is predictive for chemotherapeutic response in anaplastic oligodendrogliomas with codeletion of 1p/19q chromosomes. Glial tumors that contain chromosomal codeletion of 1p/19q are defined as tumors of oligodendroglial lineage and have favorable prognosis. MGMT promoter methylation is a favorable prognostic marker in astrocytic high-grade gliomas and it is predictive for chemotherapeutic response in anaplastic gliomas with wild-type IDH1/2 and in glioblastoma of the elderly. The clinical implication of other molecular markers of gliomas like mutations of EGFR and ATRX genes and BRAF fusion or point mutation is highlighted. The potential of molecular biomarker-based classification to guide future therapeutic approach is discussed and accentuated.

Omics-Based Identification of Biomarkers for Nasopharyngeal Carcinoma

PubMed Central

2015-01-01

Nasopharyngeal carcinoma (NPC) is a head and neck cancer that is highly found in distinct geographic areas, such as Southeast Asia. The management of NPC remains burdensome as the prognosis is poor due to the late presentation of the disease and the complex nature of NPC pathogenesis. Therefore, it is necessary to find effective molecular markers for early detection and therapeutic measure of NPC. In this paper, the discovery of molecular biomarker for NPC through the emerging omics technologies including genomics, miRNA-omics, transcriptomics, proteomics, and metabolomics will be extensively reviewed. These markers have been shown to play roles in various cellular pathways in NPC progression. The knowledge on their function will help us understand in more detail the complexity in tumor biology, leading to the better strategies for early detection, outcome prediction, detection of disease recurrence, and therapeutic approach. PMID:25999660

A putative marker for human pathogenic strains of Anaplasma phagocytophilum correlates with geography and host, but not human tropism.

PubMed

Foley, Janet; Stephenson, Nicole; Cubilla, Michelle Pires; Qurollo, Barbara; Breitschwerdt, Edward B

2016-03-01

Anaplasma phagocytophilum is an Ixodes species tick-transmitted bacterium that is capable of infecting a variety of host species, although there is a diversity of bacterial strains with differing host tropism. Recent analysis of A. phagocytophilum strains suggested that "drhm", a gene locus designated "distantly related to human marker" (drhm), which was predicted to be an integral membrane protein with possible transporter functions was not present in available canine and human isolates. By assessing 117 strains from 14 host species from across the US, we extended this analysis. Phylogenetic clades were associated with geography, but not host species. Additionally, a virulent clade that lacks drhm and infects dogs, horses, and humans in northeastern US was identified. Copyright © 2015 Elsevier GmbH. All rights reserved.

The boundaries of the cognitive phenotype of autism: theory of mind, central coherence and ambiguous figure perception in young people with autistic traits.

PubMed

Best, Catherine S; Moffat, Vivien J; Power, Michael J; Owens, David G C; Johnstone, Eve C

2008-05-01

Theory of Mind, Weak Central Coherence and executive dysfunction, were investigated as a function of behavioural markers of autism. This was irrespective of the presence or absence of a diagnosis of an autistic spectrum disorder. Sixty young people completed the Social Communication Questionnaire (SCQ), false belief tests, the block design test, viewed visual illusions and an ambiguous figure. A logistic regression was performed and it was found that Theory of Mind, central coherence and ambiguous figure variables significantly contributed to prediction of behavioural markers of autism. These findings provide support for the continuum hypothesis of autism. That is, mild autistic behavioural traits are distributed through the population and these behavioural traits may have the same underlying cognitive determinants as autistic disorder.

On prediction of genetic values in marker-assisted selection.

PubMed Central

Lange, C; Whittaker, J C

2001-01-01

We suggest a new approximation for the prediction of genetic values in marker-assisted selection. The new approximation is compared to the standard approach. It is shown that the new approach will often provide substantially better prediction of genetic values; furthermore the new approximation avoids some of the known statistical problems of the standard approach. The advantages of the new approach are illustrated by a simulation study in which the new approximation outperforms both the standard approach and phenotypic selection. PMID:11729177

Prospects and Potential Uses of Genomic Prediction of Key Performance Traits in Tetraploid Potato.

PubMed

Stich, Benjamin; Van Inghelandt, Delphine

2018-01-01

Genomic prediction is a routine tool in breeding programs of most major animal and plant species. However, its usefulness for potato breeding has not yet been evaluated in detail. The objectives of this study were to (i) examine the prospects of genomic prediction of key performance traits in a diversity panel of tetraploid potato modeling additive, dominance, and epistatic effects, (ii) investigate the effects of size and make up of training set, number of test environments and molecular markers on prediction accuracy, and (iii) assess the effect of including markers from candidate genes on the prediction accuracy. With genomic best linear unbiased prediction (GBLUP), BayesA, BayesCπ, and Bayesian LASSO, four different prediction methods were used for genomic prediction of relative area under disease progress curve after a Phytophthora infestans infection, plant maturity, maturity corrected resistance, tuber starch content, tuber starch yield (TSY), and tuber yield (TY) of 184 tetraploid potato clones or subsets thereof genotyped with the SolCAP 8.3k SNP array. The cross-validated prediction accuracies with GBLUP and the three Bayesian approaches for the six evaluated traits ranged from about 0.5 to about 0.8. For traits with a high expected genetic complexity, such as TSY and TY, we observed an 8% higher prediction accuracy using a model with additive and dominance effects compared with a model with additive effects only. Our results suggest that for oligogenic traits in general and when diagnostic markers are available in particular, the use of Bayesian methods for genomic prediction is highly recommended and that the diagnostic markers should be modeled as fixed effects. The evaluation of the relative performance of genomic prediction vs. phenotypic selection indicated that the former is superior, assuming cycle lengths and selection intensities that are possible to realize in commercial potato breeding programs.

Prospects and Potential Uses of Genomic Prediction of Key Performance Traits in Tetraploid Potato

PubMed Central

Stich, Benjamin; Van Inghelandt, Delphine

2018-01-01

Genomic prediction is a routine tool in breeding programs of most major animal and plant species. However, its usefulness for potato breeding has not yet been evaluated in detail. The objectives of this study were to (i) examine the prospects of genomic prediction of key performance traits in a diversity panel of tetraploid potato modeling additive, dominance, and epistatic effects, (ii) investigate the effects of size and make up of training set, number of test environments and molecular markers on prediction accuracy, and (iii) assess the effect of including markers from candidate genes on the prediction accuracy. With genomic best linear unbiased prediction (GBLUP), BayesA, BayesCπ, and Bayesian LASSO, four different prediction methods were used for genomic prediction of relative area under disease progress curve after a Phytophthora infestans infection, plant maturity, maturity corrected resistance, tuber starch content, tuber starch yield (TSY), and tuber yield (TY) of 184 tetraploid potato clones or subsets thereof genotyped with the SolCAP 8.3k SNP array. The cross-validated prediction accuracies with GBLUP and the three Bayesian approaches for the six evaluated traits ranged from about 0.5 to about 0.8. For traits with a high expected genetic complexity, such as TSY and TY, we observed an 8% higher prediction accuracy using a model with additive and dominance effects compared with a model with additive effects only. Our results suggest that for oligogenic traits in general and when diagnostic markers are available in particular, the use of Bayesian methods for genomic prediction is highly recommended and that the diagnostic markers should be modeled as fixed effects. The evaluation of the relative performance of genomic prediction vs. phenotypic selection indicated that the former is superior, assuming cycle lengths and selection intensities that are possible to realize in commercial potato breeding programs. PMID:29563919

SOX9 as a Predictor for Neurogenesis Potentiality of Amniotic Fluid Stem Cells

PubMed Central

Wei, Pei-Cih; Chao, Angel; Peng, Hsiu-Huei; Chao, An-Shine; Chang, Yao-Lung; Chang, Shuenn-Dyh; Wang, Hsin-Shih; Chang, Yu-Jen; Tsai, Ming-Song; Sieber, Martin; Chen, Hua-Chien; Chen, Shu-Jen; Lee, Yun-Shien

2014-01-01

Preclinical studies of amniotic fluid-derived cell therapy have been successful in the research of neurodegenerative diseases, peripheral nerve injury, spinal cord injury, and brain ischemia. Transplantation of human amniotic fluid stem cells (AFSCs) into rat brain ventricles has shown improvement in symptoms of Parkinson's disease and also highlighted the minimal immune rejection risk of AFSCs, even between species. Although AFSCs appeared to be a promising resource for cell-based regenerative therapy, AFSCs contain a heterogeneous pool of distinct cell types, rendering each preparation of AFSCs unique. Identification of predictive markers for neuron-prone AFSCs is necessary before such stem cell-based therapeutics can become a reality. In an attempt to identify markers of AFSCs to predict their ability for neurogenesis, we performed a two-phase study. In the discovery phase of 23 AFSCs, we tested ZNF521/Zfp521, OCT6, SOX1, SOX2, SOX3, and SOX9 as predictive markers of AFSCs for neural differentiation. In the validation phase, the efficacy of these predictive markers was tested in independent sets of 18 AFSCs and 14 dental pulp stem cells (DPSCs). We found that high expression of SOX9 in AFSCs is associated with good neurogenetic ability, and these positive correlations were confirmed in independent sets of AFSCs and DPSCs. Furthermore, knockdown of SOX9 in AFSCs inhibited their neuronal differentiation. In conclusion, the discovery of SOX9 as a predictive marker for neuron-prone AFSCs could expedite the selection of useful clones for regenerative medicine, in particular, in neurological diseases and injuries. PMID:25154783

Genetic Markers of Toxicity From Capecitabine and Other Fluorouracil-Based Regimens: Investigation in the QUASAR2 Study, Systematic Review, and Meta-Analysis

PubMed Central

Rosmarin, Dan; Palles, Claire; Church, David; Domingo, Enric; Jones, Angela; Johnstone, Elaine; Wang, Haitao; Love, Sharon; Julier, Patrick; Scudder, Claire; Nicholson, George; Gonzalez-Neira, Anna; Martin, Miguel; Sargent, Daniel; Green, Erin; McLeod, Howard; Zanger, Ulrich M.; Schwab, Matthias; Braun, Michael; Seymour, Matthew; Thompson, Lindsay; Lacas, Benjamin; Boige, Valérie; Ribelles, Nuria; Afzal, Shoaib; Enghusen, Henrik; Jensen, Søren Astrup; Etienne-Grimaldi, Marie-Christine; Milano, Gérard; Wadelius, Mia; Glimelius, Bengt; Garmo, Hans; Gusella, Milena; Lecomte, Thierry; Laurent-Puig, Pierre; Martinez-Balibrea, Eva; Sharma, Rohini; Garcia-Foncillas, Jesus; Kleibl, Zdenek; Morel, Alain; Pignon, Jean-Pierre; Midgley, Rachel; Kerr, David; Tomlinson, Ian

2014-01-01

Purpose Fluourouracil (FU) is a mainstay of chemotherapy, although toxicities are common. Genetic biomarkers have been used to predict these adverse events, but their utility is uncertain. Patients and Methods We tested candidate polymorphisms identified from a systematic literature search for associations with capecitabine toxicity in 927 patients with colorectal cancer in the Quick and Simple and Reliable trial (QUASAR2). We then performed meta-analysis of QUASAR2 and 16 published studies (n = 4,855 patients) to examine the polymorphisms in various FU monotherapy and combination therapy regimens. Results Global capecitabine toxicity (grades 0/1/2 v grades 3/4/5) was associated with the rare, functional DPYD alleles 2846T>A and *2A (combined odds ratio, 5.51; P = .0013) and with the common TYMS polymorphisms 5′VNTR2R/3R and 3′UTR 6bp ins-del (combined odds ratio, 1.31; P = 9.4 × 10−6). There was weaker evidence that these polymorphisms predict toxicity from bolus and infusional FU monotherapy. No good evidence of association with toxicity was found for the remaining polymorphisms, including several currently included in predictive kits. No polymorphisms were associated with toxicity in combination regimens. Conclusion A panel of genetic biomarkers for capecitabine monotherapy toxicity would currently comprise only the four DPYD and TYMS variants above. We estimate this test could provide 26% sensitivity, 86% specificity, and 49% positive predictive value—better than most available commercial kits, but suboptimal for clinical use. The test panel might be extended to include additional, rare DPYD variants functionally equivalent to *2A and 2846A, though insufficient evidence supports its use in bolus, infusional, or combination FU. There remains a need to identify further markers of FU toxicity for all regimens. PMID:24590654

Successful Aging: Advancing the Science of Physical Independence in Older Adults

PubMed Central

Anton, Stephen D.; Woods, Adam J.; Ashizawa, Tetso; Barb, Diana; Buford, Thomas W.; Carter, Christy S.; Clark, David J.; Cohen, Ronald A.; Corbett, Duane B.; Cruz-Almeida, Yenisel; Dotson, Vonetta; Ebner, Natalie; Efron, Philip A.; Fillingim, Roger B.; Foster, Thomas C.; Gundermann, David M.; Joseph, Anna-Maria; Karabetian, Christy; Leeuwenburgh, Christiaan; Manini, Todd M.; Marsiske, Michael; Mankowski, Robert T.; Mutchie, Heather L.; Perri, Michael G.; Ranka, Sanjay; Rashidi, Parisa; Sandesara, Bhanuprasad; Scarpace, Philip J.; Sibille, Kimberly T.; Solberg, Laurence M.; Someya, Shinichi; Uphold, Connie; Wohlgemuth, Stephanie; Wu, Samuel Shangwu; Pahor, Marco

2015-01-01

The concept of ‘Successful Aging’ has long intrigued the scientific community. Despite this long-standing interest, a consensus definition has proven to be a difficult task, due to the inherent challenge involved in defining such a complex, multi-dimensional phenomenon. The lack of a clear set of defining characteristics for the construct of successful aging has made comparison of findings across studies difficult and has limited advances in aging research. The domain in which consensus on markers of successful aging is furthest developed is the domain of physical functioning. For example, walking speed appears to be an excellent surrogate marker of overall health and predicts the maintenance of physical independence, a cornerstone of successful aging. The purpose of the present article is to provide an overview and discussion of specific health conditions, behavioral factors, and biological mechanisms that mark declining mobility and physical function and promising interventions to counter these effects. With life expectancy continuing to increase in the United States and developed countries throughout the world, there is an increasing public health focus on the maintenance of physical independence among all older adults. PMID:26462882

The Prognostic Role of Cancer Stem Cell Markers for Long-term Outcome After Resection of Colonic Liver Metastases.

PubMed

Spelt, Lidewij; Sasor, Agata; Ansari, Daniel; Hilmersson, Katarzyna Said; Andersson, Roland

2018-01-01

To assess the expression of cancer stem cell (CSC) markers CD44, CD133 and CD24 in colon cancer liver metastases and analyse their predictive value for overall survival (OS) and disease-free survival (DFS) after liver resection. Patients operated on for colon cancer liver metastases were included. CSC marker expression was determined through immunohistochemistry analysis. OS and DFS were compared between marker-positive and marker-negative patients. Multivariate analysis was performed to select predictive variables for OS and DFS. CD133-positive patients had a worse DFS than CD133-negative patients, with a median DFS of 12 and 25 months (p=0.051). Multivariate analysis selected CD133 expression as a significant predictor for DFS. CD44 and CD24 were not found to predict OS or DFS. CD133 expression in colonic liver metastases is a negative prognostic factor for DFS after liver resection. In the future, CD133 could be used as a biomarker for risk stratification, and possibly for developing novel targeted therapy. Copyright© 2018, International Institute of Anticancer Research (Dr. George J. Delinasios), All rights reserved.

Resting right ventricular function is associated with exercise performance in PAH, but not in CTEPH.

PubMed

Rehman, Michaela Beatrice; Howard, Luke S; Christiaens, Luc P; Gill, Dipender; Gibbs, J Simon R; Nihoyannopoulos, Petros

2018-02-01

To assess whether resting right ventricular (RV) function assessed by Global RV longitudinal strain (RVLS) and RV fractional area change (FAC) is associated with exercise performance in pulmonary arterial hypertension (PAH) and in chronic thromboembolic pulmonary hypertension (CTEPH). We prospectively recruited 46 consecutive patients with PAH and 42 patients with CTEPH who were referred for cardio-pulmonary exercise testing (CPET) and transthoracic echocardiography. Resting RV systolic function was assessed with RVLS and FAC. CPET parameters analyzed were percentage of predicted maximal oxygen consumption (VO2max) and the slope of ventilation against carbon dioxide production (VE/VCO2). Spearman correlation was performed between echocardiographic measurements and CPET measurements. In PAH, spearman correlation found an association between RVLS and VE/VCO2 (coefficient = 0.556, P < 0.001) and percentage predicted VO2max (coefficient = -0.393, P = 0.007), while FAC was associated with VE/VCO2 (coefficient = -0.481, P = 0.001) and percentage of predicted VO2max (coefficient = 0.356, P = 0.015). Conversely, in CTEPH, resting RV function was neither associated with percentage of predicted VO2max nor with VE/VCO2, whether assessed by RVLS or FAC. In PAH, resting RV function as assessed by FAC or RVLS is associated with exercise performance and could therefore make a significant contribution to non-invasive assessment in PAH patients. This association is not found in CTEPH, suggesting a disconnection between resting RV function and exercise performance, with implications for the use of exercise measurements as a prognostic marker and clinical/research endpoint in CTEPH. Published on behalf of the European Society of Cardiology. All rights reserved. © The Author 2017. For permissions, please email: journals.permissions@oup.com.

Genetic markers on BTA14 predictive for residual feed intake in beef steers and their effects on carcass and meat quality traits

USDA-ARS?s Scientific Manuscript database

With the high cost of feed for animal production, genetic selection for animals that metabolize feed more efficiently could result in substantial cost savings for cattle producers. The purpose of this study was to identify DNA markers predictive for differences among cattle for traits associated wit...

Early prediction of cardiac resynchronization therapy response by non-invasive electrocardiogram markers.

PubMed

Ortigosa, Nuria; Pérez-Roselló, Víctor; Donoso, Víctor; Osca, Joaquín; Martínez-Dolz, Luis; Fernández, Carmen; Galbis, Antonio

2018-04-01

Cardiac resynchronization therapy (CRT) is an effective treatment for those patients with severe heart failure. Regrettably, there are about one third of CRT "non-responders", i.e. patients who have undergone this form of device therapy but do not respond to it, which adversely affects the utility and cost-effectiveness of CRT. In this paper, we assess the ability of a novel surface ECG marker to predict CRT response. We performed a retrospective exploratory study of the ECG previous to CRT implantation in 43 consecutive patients with ischemic (17) or non-ischemic (26) cardiomyopathy. We extracted the QRST complexes (consisting of the QRS complex, the S-T segment, and the T wave) and obtained a measure of their energy by means of spectral analysis. This ECG marker showed statistically significant lower values for non-responder patients and, joint with the duration of QRS complexes (the current gold-standard to predict CRT response), the following performances: 86% accuracy, 88% sensitivity, and 80% specificity. In this manner, the proposed ECG marker may help clinicians to predict positive response to CRT in a non-invasive way, in order to minimize unsuccessful procedures.

The scientific exploration of saliva in the post-proteomic era: from database back to basic function

PubMed Central

Ruhl, Stefan

2012-01-01

The proteome of human saliva can be considered as being essentially completed. Diagnostic markers for a number of diseases have been identified among salivary proteins and peptides, taking advantage of saliva as an easy-to-obtain biological fluid. Yet, the majority of disease markers identified so far are serum components and not intrinsic proteins produced by the salivary glands. Furthermore, despite the fact that saliva is essential for protecting the oral integuments and dentition, little progress has been made in finding risk predictors in the salivary proteome for dental caries or periodontal disease. Since salivary proteins, and in particular the attached glycans, play an important role in interactions with the microbial world, the salivary glycoproteome and other post-translational modifications of salivary proteins need to be studied. Risk markers for microbial diseases, including dental caries, are likely to be discovered among the highly glycosylated major protein species in saliva. This review will attempt to raise new ideas and also point to under-researched areas that may hold promise for future applicability in oral diagnostics and prediction of oral disease. PMID:22292826

Self-rated Health among Pregnant Women: Associations with Objective Health Indicators, Psychological Functioning, and Serum Inflammatory Markers

PubMed Central

Christian, Lisa M.; Iams, Jay; Porter, Kyle; Leblebicioglu, Binnaz

2013-01-01

Background Biobehavioral correlates of self-rated health in pregnancy are largely unknown. Purpose The goals of this study were to examine, in pregnant women, associations of self-rated health with 1) demographics, objective health status, health behaviors and psychological factors and 2) serum inflammatory markers. Methods In the 2nd trimester of pregnancy, 101 women provided a blood sample, completed measures of psychosocial stress, health status, and health behaviors, and received a comprehensive periodontal examination. Results The following independently predicted poorer self-rated health: 1) greater psychological stress, 2) greater objective health diagnoses, 3) higher body mass index, and 4) past smoking (versus never smoking). Poorer self-rated health was associated with higher serum interleukin-1β (p = .02) and marginally higher macrophage migration inhibitory factor (p = .06). These relationships were not fully accounted for by behavioral/psychological factors. Conclusions This study provides novel data regarding factors influencing subjective ratings of health and the association of self-rated health with serum inflammatory markers in pregnant women. PMID:23765366

Genomic and pedigree-based prediction for leaf, stem, and stripe rust resistance in wheat.

PubMed

Juliana, Philomin; Singh, Ravi P; Singh, Pawan K; Crossa, Jose; Huerta-Espino, Julio; Lan, Caixia; Bhavani, Sridhar; Rutkoski, Jessica E; Poland, Jesse A; Bergstrom, Gary C; Sorrells, Mark E

2017-07-01

Genomic prediction for seedling and adult plant resistance to wheat rusts was compared to prediction using few markers as fixed effects in a least-squares approach and pedigree-based prediction. The unceasing plant-pathogen arms race and ephemeral nature of some rust resistance genes have been challenging for wheat (Triticum aestivum L.) breeding programs and farmers. Hence, it is important to devise strategies for effective evaluation and exploitation of quantitative rust resistance. One promising approach that could accelerate gain from selection for rust resistance is 'genomic selection' which utilizes dense genome-wide markers to estimate the breeding values (BVs) for quantitative traits. Our objective was to compare three genomic prediction models including genomic best linear unbiased prediction (GBLUP), GBLUP A that was GBLUP with selected loci as fixed effects and reproducing kernel Hilbert spaces-markers (RKHS-M) with least-squares (LS) approach, RKHS-pedigree (RKHS-P), and RKHS markers and pedigree (RKHS-MP) to determine the BVs for seedling and/or adult plant resistance (APR) to leaf rust (LR), stem rust (SR), and stripe rust (YR). The 333 lines in the 45th IBWSN and the 313 lines in the 46th IBWSN were genotyped using genotyping-by-sequencing and phenotyped in replicated trials. The mean prediction accuracies ranged from 0.31-0.74 for LR seedling, 0.12-0.56 for LR APR, 0.31-0.65 for SR APR, 0.70-0.78 for YR seedling, and 0.34-0.71 for YR APR. For most datasets, the RKHS-MP model gave the highest accuracies, while LS gave the lowest. GBLUP, GBLUP A, RKHS-M, and RKHS-P models gave similar accuracies. Using genome-wide marker-based models resulted in an average of 42% increase in accuracy over LS. We conclude that GS is a promising approach for improvement of quantitative rust resistance and can be implemented in the breeding pipeline.

The Lack of Utility of Circulating Biomarkers of Inflammation and Endothelial Dysfunction for Type 2 Diabetes Risk Prediction Among Postmenopausal Women

PubMed Central

Chao, Chun; Song, Yiqing; Cook, Nancy; Tseng, Chi-Hong; Manson, JoAnn E.; Eaton, Charles; Margolis, Karen L.; Rodriguez, Beatriz; Phillips, Lawrence S.; Tinker, Lesley F.; Liu, Simin

2011-01-01

Background Recent studies have linked plasma markers of inflammation and endothelial dysfunction to type 2 diabetes mellitus (DM) development. However, the utility of these novel biomarkers for type 2 DM risk prediction remains uncertain. Methods The Women’s Health Initiative Observational Study (WHIOS), a prospective cohort, and a nested case-control study within the WHIOS of 1584 incident type 2 DM cases and 2198 matched controls were used to evaluate the utility of plasma markers of inflammation and endothelial dysfunction for type 2 DM risk prediction. Between September 1994 and December 1998, 93 676 women aged 50 to 79 years were enrolled in the WHIOS. Fasting plasma levels of glucose, insulin, white blood cells, tumor necrosis factor receptor 2, interleukin 6, high-sensitivity C-reactive protein, E-selectin, soluble intercellular adhesion molecule 1, and vascular cell adhesion molecule 1 were measured using blood samples collected at baseline. A series of prediction models including traditional risk factors and novel plasma markers were evaluated on the basis of global model fit, model discrimination, net reclassification improvement, and positive and negative predictive values. Results Although white blood cell count and levels of interleukin 6, high-sensitivity C-reactive protein, and soluble intercellular adhesion molecule 1 significantly enhanced model fit, none of the inflammatory and endothelial dysfunction markers improved the ability of model discrimination (area under the receiver operating characteristic curve, 0.93 vs 0.93), net reclassification, or predictive values (positive, 0.22 vs 0.24; negative, 0.99 vs 0.99 [using 15% 6-year type 2 DM risk as the cutoff]) compared with traditional risk factors. Similar results were obtained in ethnic-specific analyses. Conclusion Beyond traditional risk factors, measurement of plasma markers of systemic inflammation and endothelial dysfunction contribute relatively little additional value in clinical type 2 DM risk prediction in a multiethnic cohort of postmenopausal women. PMID:20876407

Association between Delayed graft function (DGF) biomarkers and long-term outcomes after living donor kidney transplantation.

PubMed

Sahraei, Zahra; Mehdizadeh, Mona; Salamzadeh, Jamshid; Nafar, Mohsen; Eshraghi, Azadeh

2018-05-21

The Association between preoperative Urine Neutrophil Gelatinase-associated Lipocalin (uNGAL) and interlukin-18 (uIL-18) with poor 1-year allograft function has been shown in deceased-donor kidney transplant recipients previously, and also these markers could predict 3-month allograft function. However, it is unknown whether there is any association between these postoperative biomarkers with important recipient outcomes beyond this time in live-donor transplants. NGAL and IL-18 four and 24 hours were measured in live-donor kidney transplant recipients after transplantation. The relationships between changes in these markers with clinical outcomes as well as kidney function were examined at 1 month and 2 years. Also, the association between delayed graft function with clinical outcome and serum creatinine (SrCr) were evaluated during this period. The Mean age for kidney recipients was 23.9 years. There was significant interaction between uNGAL 24 hr (pvalue=0.01) and uIL-18 four and 24 hr after transplantation (pvalue=0.04, 0.03; respectively) with patients' outcome after 1 month and changes in uNGAL with outcomes after 2 years (pvalue= 0.04). Changes in urine NGAL postoperative is associated with worse outcome 2 years after kidney transplantation, suggesting its potential role for identifying patients that are at high risk for diminished allograft function, outcome and survival. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Uromodulin: a new biomarker of fetal renal function?

PubMed

Botelho, Thais Emanuelle Faria; Pereira, Alamanda Kfoury; Teixeira, Patrícia Gonçalves; Lage, Eura Martins; Osanan, Gabriel Costa; Silva, Ana Cristina Simões E

2016-12-01

Obstructive uropathies are main diseases affecting the fetus. Early diagnosis allows to establish the appropriate therapy to minimize the risk of damage to kidney function at birth. Biochemical markers have been used to predict the prognosis of renal function in fetuses. Uromodulin, also known by Tamm-Horsfall protein (THP) is exclusively produced in the kidneys and in normal conditions is the protein excreted in larger amounts in human urine. It plays important roles in kidneys and urinary tract. Also it participates in ion transport processes, interact with various components of the immune system and has a role in defense against urinary tract infections. Moreover, this protein was proved to be a good marker of renal function in adult patients with several renal diseases. To evaluate if uromodulin is produced and eliminated by the kidneys during fetal life by analyzing fetal urine and amniotic fluid and to establish correlation with biochemical parameter of renal function already used in Fetal Medicine Center at the Clinic Hospital of UFMG (CEMEFE/HC). Between 2013 and 2015, were selected 29 fetuses with indication of invasive tests for fetal diagnosis in monitoring at the CEMEFE/HC. The determination of uromodulin was possible and measurable in all samples and showed statistically significant correlation with the osmolarity. There was a tendency of lower levels of Uromodulin values in fetuses with severe renal impairment prenatally. Thus, high levels of this protein in fetal amniotic fluid or fetal urine dosages possibly mean kidney function preserved.

Elevated pretransplantation soluble CD30 is associated with decreased early allograft function after human lung transplantation.

PubMed

Shah, Ashish S; Leffell, M Sue; Lucas, Donna; Zachary, Andrea A

2009-02-01

Early allograft function after lung transplantation is variable. Clinical criteria have limited predictive value for early graft function. Recipient immunologic state before LTx may affect early lung function. We investigated the association between pretransplantation soluble CD30 (sCD30), a marker of Th2-type T-cell activation, and early clinical parameters of allograft function. Between September 2002 and January 2007, a total of 80 transplantations were performed at Johns Hopkins Hospital. Of the patients, 43 had a pretransplantation sCD30 level determined. Pre- and postoperative patient variables were collected, and patients were stratified into two groups: sCD30 <20 (low sCD30) and >20 (high sCD30). High sCD30 (n = 26) and low sCD30 (n = 17) groups were similar in age, gender, and ischemia time. In the high sCD30 group, a higher percentage of patients had pulmonary fibrosis and a lower percentage had emphysema. Oxygenation at 48 hours was significantly worse in the high sCD30 group as compared with the low sCD30 (p = 0.003). Moreover, prolonged intubation and 90-day mortality were greater in the high sCD30 group. This represents the first report of the use of sCD30 as a marker for early allograft function in human lung transplanation. Increased pretransplantation recipient sCD30 appears to be associated with decreased early post-transplantation gas exchange, prolonged intubation, and early mortality.

COMBINE genetics study: the pharmacogenetics of alcoholism treatment response: genes and mechanisms.

PubMed

Goldman, David; Oroszi, Gabor; O'Malley, Stephanie; Anton, Raymond

2005-07-01

Partial efficacy of treatment and differences in adverse events across individuals are a challenge and an opportunity in the treatment of alcoholism. Individuation of therapy and understanding origins of differential treatment response may require identification of inherited functional variants of genes. The neurobiology of reward, executive cognitive function, anxiety and dysphoria have been identified as critical domains that may have a genetic basis that could predict treatment response. The COMBINE Study presents a unique opportunity to evaluate specific genetic loci (markers) that affect neurobiology central to addiction and extended withdrawal. The study also addresses variation in drug metabolism and action. Candidate genetic markers are selected for study based on functionality and abundance. COMT Vall58Met is a common (minor allele frequency 0.42), functional, catecholamine-metabolizing enzyme polymorphism with threefold relevance. Vall58Met alters executive cognitive function, stress and anxiety responses and brain endogenous opioid function. OPRM1 Asn40Asp is a common (minor allele frequency 0.10), functional polymorphism of the mu-opioid receptor, which may serve as a gatekeeper molecule in naltrexone's actions and was recently reported to affect naltrexone response. HTTLPR (minor allele frequency 0.40) alters serotonin transporter function to affect anxiety, dysphoria and obsessional behavior, which are assessed in COMBINE and may be related to relapse and addictive behavior. All genetic testing is consented through a separate human research protocol, and the testing is conducted nonclinically, confidentially and apart from the clinical record to protect human research participants who have volunteered for this aspect of COMBINE.

Association of interleukin-1 gene variations with moderate to severe chronic periodontitis in multiple ethnicities

PubMed Central

Wu, X; Offenbacher, S; Lόpez, N J; Chen, D; Wang, H-Y; Rogus, J; Zhou, J; Beck, J; Jiang, S; Bao, X; Wilkins, L; Doucette-Stamm, L; Kornman, K

2015-01-01

Background and Objective Genetic markers associated with disease are often non-functional and generally tag one or more functional “causative” variants in linkage disequilibrium. Markers may not show tight linkage to the causative variants across multiple ethnicities due to evolutionary divergence, and therefore may not be informative across different population groups. Validated markers of disease suggest causative variants exist in the gene and, if the causative variants can be identified, it is reasonable to hypothesize that such variants will be informative across diverse populations. The aim of this study was to test that hypothesis using functional Interleukin-1 (IL-1) gene variations across multiple ethnic populations to replace the non-functional markers originally associated with chronic adult periodontitis in Caucasians. Material and Methods Adult chronic periodontitis cases and controls from four ethnic groups (Caucasians, African Americans, Hispanics and Asians) were recruited in the USA, Chile and China. Genotypes of IL1B gene single nucleotide polymorphisms (SNPs), including three functional SNPs (rs16944, rs1143623, rs4848306) in the promoter and one intronic SNP (rs1143633), were determined using a single base extension method or TaqMan 5′ nuclease assay. Logistic regression and other statistical analyses were used to examine the association between moderate to severe periodontitis and IL1B gene variations, including SNPs, haplotypes and composite genotypes. Genotype patterns associated with disease in the discovery study were then evaluated in independent validation studies. Results Significant associations were identified in the discovery study, consisting of Caucasians and African Americans, between moderate to severe adult chronic periodontitis and functional variations in the IL1B gene, including a pattern of four IL1B SNPs (OR = 1.87, p < 0.0001). The association between the disease and this IL1B composite genotype pattern was validated in two additional studies consisting of Hispanics (OR = 1.95, p = 0.04) or Asians (OR = 3.27, p = 0.01). A meta-analysis of the three populations supported the association between the IL-1 genotype pattern and moderate to severe periodontitis (OR 1.95; p < 0.001). Our analysis also demonstrated that IL1B gene variations had added value to conventional risk factors in predicting chronic periodontitis. Conclusion This study validated the influence of IL-1 genetic factors on the severity of chronic periodontitis in four different ethnicities. PMID:24690098

Bcl-2 and BLIMP-1 expression predict worse prognosis in gastric diffuse large B cell lymphoma (DLCBL) while other markers for nodal DLBCL are not useful.

PubMed

Martin-Arruti, Maialen; Vaquero, Manuel; Díaz de Otazu, Ramón; Zabalza, Iñaki; Ballesteros, Javier; Roncador, Giovanna; García-Orad, Africa

2012-04-01

Previous studies have identified clinicopathological and immunohistochemical differences among diffuse large B cell lymphomas (DLBCL) as a function of disease location. Nevertheless, there is a continuing tendency to generalize the prognostic value of various identified markers without taking into account tumour site. Accordingly, we analysed the prognostic value of several of the immunohistochemical markers that have been proposed for nodal DLBCL in a group of patients with gastric DLBCL. Using histochemical methods, CD10, Bcl-6, Gcet1, MUM-1, Bcl-2 and BLIMP-1 expression was investigated in 43 cases of gastric DBLCL. As in nodal DLBCLs, expression of BLIMP-1, and of Bcl-2 in non-germinal centre B cell-like (non-GCB) patients, was associated with a worse prognosis. However, unlike nodal DBLCL, there was no significant association of prognosis with expression of CD10, Bcl-6, Gcet1 or MUM-1, or with categorization according to Hans or Muris algorithms. Although most markers of prognosis in nodal DLBCL are not useful indicators for gastric DLBCL, Bcl-2 or BLIMP-1 expression does correlate with worse prognosis. These data support the notion that clinicopathological features in DLBCL vary according to the disease location. © 2012 Blackwell Publishing Ltd.

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

Lu, Bo, E-mail: luboufl@gmail.com; Park, Justin C.; Fan, Qiyong

Purpose: Accurately localizing lung tumor localization is essential for high-precision radiation therapy techniques such as stereotactic body radiation therapy (SBRT). Since direct monitoring of tumor motion is not always achievable due to the limitation of imaging modalities for treatment guidance, placement of fiducial markers on the patient’s body surface to act as a surrogate for tumor position prediction is a practical alternative for tracking lung tumor motion during SBRT treatments. In this work, the authors propose an innovative and robust model to solve the multimarker position optimization problem. The model is able to overcome the major drawbacks of the sparsemore » optimization approach (SOA) model. Methods: The principle-component-analysis (PCA) method was employed as the framework to build the authors’ statistical prediction model. The method can be divided into two stages. The first stage is to build the surrogate tumor matrix and calculate its eigenvalues and associated eigenvectors. The second stage is to determine the “best represented” columns of the eigenvector matrix obtained from stage one and subsequently acquire the optimal marker positions as well as numbers. Using 4-dimensional CT (4DCT) and breath hold CT imaging data, the PCA method was compared to the SOA method with respect to calculation time, average prediction accuracy, prediction stability, noise resistance, marker position consistency, and marker distribution. Results: The PCA and SOA methods which were both tested were on all 11 patients for a total of 130 cases including 4DCT and breath-hold CT scenarios. The maximum calculation time for the PCA method was less than 1 s with 64 752 surface points, whereas the average calculation time for the SOA method was over 12 min with 400 surface points. Overall, the tumor center position prediction errors were comparable between the two methods, and all were less than 1.5 mm. However, for the extreme scenarios (breath hold), the prediction errors for the PCA method were not only smaller, but were also more stable than for the SOA method. Results obtained by imposing a series of random noises to the surrogates indicated that the PCA method was much more noise resistant than the SOA method. The marker position consistency tests using various combinations of 4DCT phases to construct the surrogates suggested that the marker position predictions of the PCA method were more consistent than those of the SOA method, in spite of surrogate construction. Marker distribution tests indicated that greater than 80% of the calculated marker positions fell into the high cross correlation and high motion magnitude regions for both of the algorithms. Conclusions: The PCA model is an accurate, efficient, robust, and practical model for solving the multimarker position optimization problem to predict lung tumor motion during SBRT treatments. Due to its generality, PCA model can also be applied to other imaging guidance system whichever using surface motion as the surrogates.« less

Brief Report: IQ Split Predicts Social Symptoms and Communication Abilities in High-Functioning Children with Autism Spectrum Disorders

PubMed Central

Wallace, Gregory L.; Sokoloff, Jennifer L.; Kenworthy, Lauren

2011-01-01

We investigated the relationship of discrepancies between VIQ and NVIQ (IQ split) to autism symptoms and adaptive behavior in a sample of high-functioning (mean FSIQ = 98.5) school-age children with autism spectrum disorders divided into three groups: discrepantly high VIQ (n = 18); discrepantly high NVIQ (n = 24); and equivalent VIQ and NVIQ (n = 36). Discrepantly high VIQ and NVIQ were associated with autism social symptoms but not communication symptoms or repetitive behaviors. Higher VIQ and NVIQ were associated with better adaptive communication but not socialization or Daily Living Skills. IQ discrepancy may be an important phenotypic marker in autism. Although better verbal abilities are associated with better functional outcomes in autism, discrepantly high VIQ in high-functioning children may also be associated with social difficulties. PMID:19572193

Microvascular function predicts cardiovascular events in primary prevention: long-term results from the Firefighters and Their Endothelium (FATE) study.

PubMed

Anderson, Todd J; Charbonneau, Francois; Title, Lawrence M; Buithieu, Jean; Rose, M Sarah; Conradson, Heather; Hildebrand, Kathy; Fung, Marinda; Verma, Subodh; Lonn, Eva M

2011-01-18

Biomarkers of atherosclerosis may refine clinical decision making in individuals at risk of cardiovascular disease. The purpose of the study was to determine the prognostic significance of endothelial function and other vascular markers in apparently healthy men. The cohort consisted of 1574 men (age, 49.4 years) free of vascular disease. Measurements included flow-mediated dilation and its microvascular stimulus, hyperemic velocity, carotid intima-media thickness, and C-reactive protein. Cox proportional hazard models evaluated the relationship between vascular markers, Framingham risk score, and time to a first composite cardiovascular end point of vascular death, revascularization, myocardial infarction, angina, and stroke. Subjects had low median Framingham risk score (7.9%). Cardiovascular events occurred in 71 subjects (111 events) over a mean follow-up of 7.2±1.7 years. Flow-mediated dilation was not associated with subsequent cardiovascular events (hazard ratio, 0.92; P=0.54). Both hyperemic velocity (hazard ratio, 0.70; 95% confidence interval, 0.54 to 0.90; P=0.006) and carotid intima-media thickness (hazard ratio, 1.45; confidence interval, 1.15 to 1.83; P=0.002) but not C-reactive protein (P=0.35) were related to events in a multivariable analysis that included Framingham risk score (per unit SD). Furthermore, the addition of hyperemic velocity to Framingham risk score resulted in a net clinical reclassification improvement of 28.7% (P<0.001) after 5 years of follow-up in the intermediate-risk group. Overall net reclassification improvement for hyperemic velocity was 6.9% (P=0.24). In men, hyperemic velocity, the stimulus for flow-mediated dilation, but not flow-mediated dilation itself was a significant risk marker for adverse cardiovascular outcomes. The prognostic value was additive to traditional risk factors and carotid intima-media thickness. Hyperemic velocity, a newly described marker of microvascular function, is a novel tool that may improve risk stratification of lower-risk healthy men.

An Integrative Framework for Bayesian Variable Selection with Informative Priors for Identifying Genes and Pathways

PubMed Central

Ander, Bradley P.; Zhang, Xiaoshuai; Xue, Fuzhong; Sharp, Frank R.; Yang, Xiaowei

2013-01-01

The discovery of genetic or genomic markers plays a central role in the development of personalized medicine. A notable challenge exists when dealing with the high dimensionality of the data sets, as thousands of genes or millions of genetic variants are collected on a relatively small number of subjects. Traditional gene-wise selection methods using univariate analyses face difficulty to incorporate correlational, structural, or functional structures amongst the molecular measures. For microarray gene expression data, we first summarize solutions in dealing with ‘large p, small n’ problems, and then propose an integrative Bayesian variable selection (iBVS) framework for simultaneously identifying causal or marker genes and regulatory pathways. A novel partial least squares (PLS) g-prior for iBVS is developed to allow the incorporation of prior knowledge on gene-gene interactions or functional relationships. From the point view of systems biology, iBVS enables user to directly target the joint effects of multiple genes and pathways in a hierarchical modeling diagram to predict disease status or phenotype. The estimated posterior selection probabilities offer probabilitic and biological interpretations. Both simulated data and a set of microarray data in predicting stroke status are used in validating the performance of iBVS in a Probit model with binary outcomes. iBVS offers a general framework for effective discovery of various molecular biomarkers by combining data-based statistics and knowledge-based priors. Guidelines on making posterior inferences, determining Bayesian significance levels, and improving computational efficiencies are also discussed. PMID:23844055

An integrative framework for Bayesian variable selection with informative priors for identifying genes and pathways.

PubMed

Peng, Bin; Zhu, Dianwen; Ander, Bradley P; Zhang, Xiaoshuai; Xue, Fuzhong; Sharp, Frank R; Yang, Xiaowei

2013-01-01

The discovery of genetic or genomic markers plays a central role in the development of personalized medicine. A notable challenge exists when dealing with the high dimensionality of the data sets, as thousands of genes or millions of genetic variants are collected on a relatively small number of subjects. Traditional gene-wise selection methods using univariate analyses face difficulty to incorporate correlational, structural, or functional structures amongst the molecular measures. For microarray gene expression data, we first summarize solutions in dealing with 'large p, small n' problems, and then propose an integrative Bayesian variable selection (iBVS) framework for simultaneously identifying causal or marker genes and regulatory pathways. A novel partial least squares (PLS) g-prior for iBVS is developed to allow the incorporation of prior knowledge on gene-gene interactions or functional relationships. From the point view of systems biology, iBVS enables user to directly target the joint effects of multiple genes and pathways in a hierarchical modeling diagram to predict disease status or phenotype. The estimated posterior selection probabilities offer probabilitic and biological interpretations. Both simulated data and a set of microarray data in predicting stroke status are used in validating the performance of iBVS in a Probit model with binary outcomes. iBVS offers a general framework for effective discovery of various molecular biomarkers by combining data-based statistics and knowledge-based priors. Guidelines on making posterior inferences, determining Bayesian significance levels, and improving computational efficiencies are also discussed.

Decline of Tumor Vascular Function as Assessed by Dynamic Contrast-Enhanced Magnetic Resonance Imaging Is Associated With Poor Responses to Radiation Therapy and Chemotherapy

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

Chen, Fang-Hsin; Wang, Chun-Chieh; Radiation Biology Research Center, Institute for Radiological Research, Chang Gung University/Chang Gung Memorial Hospital, Linkou, Taoyuan, Taiwan

Purpose: To investigate whether changes in the volume transfer coefficient (K{sup trans}) in a growing tumor could be used as a surrogate marker for predicting tumor responses to radiation therapy (RT) and chemotherapy (CT). Methods and Materials: Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) was consecutively performed on tumor-bearing mice, and temporal and spatial changes of K{sup trans} values were measured along with tumor growth. Tumor responses to RT and CT were studied before and after observed changes in K{sup trans} values with time. Results: Dynamic changes with an initial increase and subsequent decline in K{sup trans} values were found tomore » be associated with tumor growth. When each tumor was divided into core and peripheral regions, the K{sup trans} decline was greater in core, although neither vascular structure or necrosis could be linked to this spatial difference. Tumor responses to RT were worse if applied after the decline of K{sup trans}, and there was less drug distribution and cell death in the tumor core after CT. Conclusion: The K{sup trans} value in growing tumors, reflecting the changes of tumor microenvironment and vascular function, is strongly associated with tumor responses to RT and CT and could be a potential surrogate marker for predicting the tumor response to these treatments.« less

"If only I had done better": Perfectionism and the functionality of counterfactual thinking.

PubMed

Sirois, Fuschia M; Monforton, Jennifer; Simpson, Melissa

2010-12-01

Although a recent update on the functional theory of counterfactual thinking suggests that counterfactuals are important for behavior regulation, there is some evidence that counterfactuals may not be functional for everyone. Two studies found differences between maladaptive and high personal standards perfectionism in the functionality of counterfactuals and variables relevant to behavior regulation. Maladaptive but not personal standards perfectionism predicted making more upward counterfactuals after recalling a negative event and was linked to a variety of negative markers of achievement. Maladaptive perfectionism was associated with making controllable, subtractive, and less specific counterfactuals. High personal standards perfectionism moderated the effects of maladaptive perfectionism on counterfactual controllability. Generating counterfactuals increased motivation for personal standards perfectionists relative to a noncounterfactual control group but had no effect on motivation for maladaptive perfectionists. The findings suggest a continuum of counterfactual functionality for perfectionists and highlight the importance of considering counterfactual specificity and structure.

SNPs selection using support vector regression and genetic algorithms in GWAS

PubMed Central

2014-01-01

Introduction This paper proposes a new methodology to simultaneously select the most relevant SNPs markers for the characterization of any measurable phenotype described by a continuous variable using Support Vector Regression with Pearson Universal kernel as fitness function of a binary genetic algorithm. The proposed methodology is multi-attribute towards considering several markers simultaneously to explain the phenotype and is based jointly on statistical tools, machine learning and computational intelligence. Results The suggested method has shown potential in the simulated database 1, with additive effects only, and real database. In this simulated database, with a total of 1,000 markers, and 7 with major effect on the phenotype and the other 993 SNPs representing the noise, the method identified 21 markers. Of this total, 5 are relevant SNPs between the 7 but 16 are false positives. In real database, initially with 50,752 SNPs, we have reduced to 3,073 markers, increasing the accuracy of the model. In the simulated database 2, with additive effects and interactions (epistasis), the proposed method matched to the methodology most commonly used in GWAS. Conclusions The method suggested in this paper demonstrates the effectiveness in explaining the real phenotype (PTA for milk), because with the application of the wrapper based on genetic algorithm and Support Vector Regression with Pearson Universal, many redundant markers were eliminated, increasing the prediction and accuracy of the model on the real database without quality control filters. The PUK demonstrated that it can replicate the performance of linear and RBF kernels. PMID:25573332

CXCR6 identifies a putative population of retained human lung T cells characterised by co-expression of activation markers.

PubMed

Morgan, Angela J; Guillen, Cristina; Symon, Fiona A; Birring, Surinder S; Campbell, James J; Wardlaw, Andrew J

2008-01-01

Expressions of activation markers have been described on the surface of T cells in the blood and the lung in both health and disease. We have studied the distribution of activation markers on human lung T cells and have found that only certain populations exist. Importantly, the presence or absence of some markers appears to predict those of others, in particular cells which express CD103 also express CD49a and CD69, whereas cells which do not express CD69 also do not express CD49a or CD103. In view of the paucity of activation marker expression in the peripheral blood, we have hypothesised that these CD69+, CD49a+, and CD103+ (triple positive) cells are retained in the lung, possess effector function (IFNgamma secretion) and express particular chemokine receptors which allow them to be maintained in this environment. We have found that the ability of the triple negative cells to secrete IFNgamma is significantly less than the triple positive cells, suggesting that the expression of activation markers can highlight a highly specialised effector cell. We have studied the expression of 14 chemokine receptors and have found that the most striking difference between the triple negative cells and the triple positive cells is the expression of CXCR6 with 12.8+/-9.8% of triple negative cells expressing CXCR6 compared to 89.5+/-5.5% of triple positive cells. We propose therefore that CXCR6 may play an important role in the retention of T cells within the lung.

Gene expression markers in circulating tumor cells may predict bone metastasis and response to hormonal treatment in breast cancer

PubMed Central

WANG, HAIYING; MOLINA, JULIAN; JIANG, JOHN; FERBER, MATTHEW; PRUTHI, SANDHYA; JATKOE, TIMOTHY; DERECHO, CARLO; RAJPUROHIT, YASHODA; ZHENG, JIAN; WANG, YIXIN

2013-01-01

Circulating tumor cells (CTCs) have recently attracted attention due to their potential as prognostic and predictive markers for the clinical management of metastatic breast cancer patients. The isolation of CTCs from patients may enable the molecular characterization of these cells, which may help establish a minimally invasive assay for the prediction of metastasis and further optimization of treatment. Molecular markers of proven clinical value may therefore be useful in predicting disease aggressiveness and response to treatment. In our earlier study, we identified a gene signature in breast cancer that appears to be significantly associated with bone metastasis. Among the genes that constitute this signature, trefoil factor 1 (TFF1) was identified as the most differentially expressed gene associated with bone metastasis. In this study, we investigated 25 candidate gene markers in the CTCs of metastatic breast cancer patients with different metastatic sites. The panel of the 25 markers was investigated in 80 baseline samples (first blood draw of CTCs) and 30 follow-up samples. In addition, 40 healthy blood donors (HBDs) were analyzed as controls. The assay was performed using quantitative reverse transcriptase polymerase chain reaction (qRT-PCR) with RNA extracted from CTCs captured by the CellSearch system. Our study indicated that 12 of the genes were uniquely expressed in CTCs and 10 were highly expressed in the CTCs obtained from patients compared to those obtained from HBDs. Among these genes, the expression of keratin 19 was highly correlated with the CTC count. The TFF1 expression in CTCs was a strong predictor of bone metastasis and the patients with a high expression of estrogen receptor β in CTCs exhibited a better response to hormonal treatment. Molecular characterization of these genes in CTCs may provide a better understanding of the mechanism underlying tumor metastasis and identify gene markers in CTCs for predicting disease progression and response to treatment. PMID:24649289

Gene expression markers in circulating tumor cells may predict bone metastasis and response to hormonal treatment in breast cancer.

PubMed

Wang, Haiying; Molina, Julian; Jiang, John; Ferber, Matthew; Pruthi, Sandhya; Jatkoe, Timothy; Derecho, Carlo; Rajpurohit, Yashoda; Zheng, Jian; Wang, Yixin

2013-11-01

Circulating tumor cells (CTCs) have recently attracted attention due to their potential as prognostic and predictive markers for the clinical management of metastatic breast cancer patients. The isolation of CTCs from patients may enable the molecular characterization of these cells, which may help establish a minimally invasive assay for the prediction of metastasis and further optimization of treatment. Molecular markers of proven clinical value may therefore be useful in predicting disease aggressiveness and response to treatment. In our earlier study, we identified a gene signature in breast cancer that appears to be significantly associated with bone metastasis. Among the genes that constitute this signature, trefoil factor 1 (TFF1) was identified as the most differentially expressed gene associated with bone metastasis. In this study, we investigated 25 candidate gene markers in the CTCs of metastatic breast cancer patients with different metastatic sites. The panel of the 25 markers was investigated in 80 baseline samples (first blood draw of CTCs) and 30 follow-up samples. In addition, 40 healthy blood donors (HBDs) were analyzed as controls. The assay was performed using quantitative reverse transcriptase polymerase chain reaction (qRT-PCR) with RNA extracted from CTCs captured by the CellSearch system. Our study indicated that 12 of the genes were uniquely expressed in CTCs and 10 were highly expressed in the CTCs obtained from patients compared to those obtained from HBDs. Among these genes, the expression of keratin 19 was highly correlated with the CTC count. The TFF1 expression in CTCs was a strong predictor of bone metastasis and the patients with a high expression of estrogen receptor β in CTCs exhibited a better response to hormonal treatment. Molecular characterization of these genes in CTCs may provide a better understanding of the mechanism underlying tumor metastasis and identify gene markers in CTCs for predicting disease progression and response to treatment.

Assessing the Clinical Role of Genetic Markers of Early-Onset Prostate Cancer Among High-Risk Men Enrolled in Prostate Cancer Early Detection

PubMed Central

Hughes, Lucinda; Zhu, Fang; Ross, Eric; Gross, Laura; Uzzo, Robert G.; Chen, David Y. T.; Viterbo, Rosalia; Rebbeck, Timothy R.; Giri, Veda N.

2011-01-01

Background Men with familial prostate cancer (PCA) and African American men are at risk for developing PCA at younger ages. Genetic markers predicting early-onset PCA may provide clinically useful information to guide screening strategies for high-risk men. We evaluated clinical information from six polymorphisms associated with early-onset PCA in a longitudinal cohort of high-risk men enrolled in PCA early detection with significant African American participation. Methods Eligibility criteria include ages 35–69 with a family history of PCA or African American race. Participants undergo screening and biopsy per study criteria. Six markers associated with early-onset PCA (rs2171492 (7q32), rs6983561 (8q24), rs10993994 (10q11), rs4430796 (17q12), rs1799950 (17q21), and rs266849 (19q13)) were genotyped. Cox models were used to evaluate time to PCA diagnosis and PSA prediction for PCA by genotype. Harrell’s concordance index was used to evaluate predictive accuracy for PCA by PSA and genetic markers. Results 460 participants with complete data and ≥1 follow-up visit were included. 56% were African American. Among African American men, rs6983561 genotype was significantly associated with earlier time to PCA diagnosis (p=0.005) and influenced prediction for PCA by the PSA (p<0.001). When combined with PSA, rs6983561 improved predictive accuracy for PCA compared to PSA alone among African American men (PSA= 0.57 vs. PSA+rs6983561=0.75, p=0.03). Conclusions Early-onset marker rs6983561 adds potentially useful clinical information for African American men undergoing PCA risk assessment. Further study is warranted to validate these findings. Impact Genetic markers of early-onset PCA have potential to refine and personalize PCA early detection for high-risk men. PMID:22144497

Derivation of genetic biomarkers for cancer risk stratification in Barrett's oesophagus: a prospective cohort study.

PubMed

Timmer, Margriet R; Martinez, Pierre; Lau, Chiu T; Westra, Wytske M; Calpe, Silvia; Rygiel, Agnieszka M; Rosmolen, Wilda D; Meijer, Sybren L; Ten Kate, Fiebo J W; Dijkgraaf, Marcel G W; Mallant-Hent, Rosalie C; Naber, Anton H J; van Oijen, Arnoud H A M; Baak, Lubbertus C; Scholten, Pieter; Böhmer, Clarisse J M; Fockens, Paul; Maley, Carlo C; Graham, Trevor A; Bergman, Jacques J G H M; Krishnadath, Kausilia K

2016-10-01

The risk of developing adenocarcinoma in non-dysplastic Barrett's oesophagus is low and difficult to predict. Accurate tools for risk stratification are needed to increase the efficiency of surveillance. We aimed to develop a prediction model for progression using clinical variables and genetic markers. In a prospective cohort of patients with non-dysplastic Barrett's oesophagus, we evaluated six molecular markers: p16, p53, Her-2/neu, 20q, MYC and aneusomy by DNA fluorescence in situ hybridisation on brush cytology specimens. Primary study outcomes were the development of high-grade dysplasia or oesophageal adenocarcinoma. The most predictive clinical variables and markers were determined using Cox proportional-hazards models, receiver operating characteristic curves and a leave-one-out analysis. A total of 428 patients participated (345 men; median age 60 years) with a cumulative follow-up of 2019 patient-years (median 45 months per patient). Of these patients, 22 progressed; nine developed high-grade dysplasia and 13 oesophageal adenocarcinoma. The clinical variables, age and circumferential Barrett's length, and the markers, p16 loss, MYC gain and aneusomy, were significantly associated with progression on univariate analysis. We defined an 'Abnormal Marker Count' that counted abnormalities in p16, MYC and aneusomy, which significantly improved risk prediction beyond using just age and Barrett's length. In multivariate analysis, these three factors identified a high-risk group with an 8.7-fold (95% CI 2.6 to 29.8) increased HR when compared with the low-risk group, with an area under the curve of 0.76 (95% CI 0.66 to 0.86). A prediction model based on age, Barrett's length and the markers p16, MYC and aneusomy determines progression risk in non-dysplastic Barrett's oesophagus. 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/

Genomic selection and association mapping in rice (Oryza sativa): effect of trait genetic architecture, training population composition, marker number and statistical model on accuracy of rice genomic selection in elite, tropical rice breeding lines.

PubMed

Spindel, Jennifer; Begum, Hasina; Akdemir, Deniz; Virk, Parminder; Collard, Bertrand; Redoña, Edilberto; Atlin, Gary; Jannink, Jean-Luc; McCouch, Susan R

2015-02-01

Genomic Selection (GS) is a new breeding method in which genome-wide markers are used to predict the breeding value of individuals in a breeding population. GS has been shown to improve breeding efficiency in dairy cattle and several crop plant species, and here we evaluate for the first time its efficacy for breeding inbred lines of rice. We performed a genome-wide association study (GWAS) in conjunction with five-fold GS cross-validation on a population of 363 elite breeding lines from the International Rice Research Institute's (IRRI) irrigated rice breeding program and herein report the GS results. The population was genotyped with 73,147 markers using genotyping-by-sequencing. The training population, statistical method used to build the GS model, number of markers, and trait were varied to determine their effect on prediction accuracy. For all three traits, genomic prediction models outperformed prediction based on pedigree records alone. Prediction accuracies ranged from 0.31 and 0.34 for grain yield and plant height to 0.63 for flowering time. Analyses using subsets of the full marker set suggest that using one marker every 0.2 cM is sufficient for genomic selection in this collection of rice breeding materials. RR-BLUP was the best performing statistical method for grain yield where no large effect QTL were detected by GWAS, while for flowering time, where a single very large effect QTL was detected, the non-GS multiple linear regression method outperformed GS models. For plant height, in which four mid-sized QTL were identified by GWAS, random forest produced the most consistently accurate GS models. Our results suggest that GS, informed by GWAS interpretations of genetic architecture and population structure, could become an effective tool for increasing the efficiency of rice breeding as the costs of genotyping continue to decline.

Genomic Selection and Association Mapping in Rice (Oryza sativa): Effect of Trait Genetic Architecture, Training Population Composition, Marker Number and Statistical Model on Accuracy of Rice Genomic Selection in Elite, Tropical Rice Breeding Lines

PubMed Central

Spindel, Jennifer; Begum, Hasina; Akdemir, Deniz; Virk, Parminder; Collard, Bertrand; Redoña, Edilberto; Atlin, Gary; Jannink, Jean-Luc; McCouch, Susan R.

2015-01-01

Genomic Selection (GS) is a new breeding method in which genome-wide markers are used to predict the breeding value of individuals in a breeding population. GS has been shown to improve breeding efficiency in dairy cattle and several crop plant species, and here we evaluate for the first time its efficacy for breeding inbred lines of rice. We performed a genome-wide association study (GWAS) in conjunction with five-fold GS cross-validation on a population of 363 elite breeding lines from the International Rice Research Institute's (IRRI) irrigated rice breeding program and herein report the GS results. The population was genotyped with 73,147 markers using genotyping-by-sequencing. The training population, statistical method used to build the GS model, number of markers, and trait were varied to determine their effect on prediction accuracy. For all three traits, genomic prediction models outperformed prediction based on pedigree records alone. Prediction accuracies ranged from 0.31 and 0.34 for grain yield and plant height to 0.63 for flowering time. Analyses using subsets of the full marker set suggest that using one marker every 0.2 cM is sufficient for genomic selection in this collection of rice breeding materials. RR-BLUP was the best performing statistical method for grain yield where no large effect QTL were detected by GWAS, while for flowering time, where a single very large effect QTL was detected, the non-GS multiple linear regression method outperformed GS models. For plant height, in which four mid-sized QTL were identified by GWAS, random forest produced the most consistently accurate GS models. Our results suggest that GS, informed by GWAS interpretations of genetic architecture and population structure, could become an effective tool for increasing the efficiency of rice breeding as the costs of genotyping continue to decline. PMID:25689273

Molecular markers in bladder cancer: Novel research frontiers.

PubMed

Sanguedolce, Francesca; Cormio, Antonella; Bufo, Pantaleo; Carrieri, Giuseppe; Cormio, Luigi

2015-01-01

Bladder cancer (BC) is a heterogeneous disease encompassing distinct biologic features that lead to extremely different clinical behaviors. In the last 20 years, great efforts have been made to predict disease outcome and response to treatment by developing risk assessment calculators based on multiple standard clinical-pathological factors, as well as by testing several molecular markers. Unfortunately, risk assessment calculators alone fail to accurately assess a single patient's prognosis and response to different treatment options. Several molecular markers easily assessable by routine immunohistochemical techniques hold promise for becoming widely available and cost-effective tools for a more reliable risk assessment, but none have yet entered routine clinical practice. Current research is therefore moving towards (i) identifying novel molecular markers; (ii) testing old and new markers in homogeneous patients' populations receiving homogeneous treatments; (iii) generating a multimarker panel that could be easily, and thus routinely, used in clinical practice; (iv) developing novel risk assessment tools, possibly combining standard clinical-pathological factors with molecular markers. This review analyses the emerging body of literature concerning novel biomarkers, ranging from genetic changes to altered expression of a huge variety of molecules, potentially involved in BC outcome and response to treatment. Findings suggest that some of these indicators, such as serum circulating tumor cells and tissue mitochondrial DNA, seem to be easily assessable and provide reliable information. Other markers, such as the phosphoinositide-3-kinase (PI3K)/AKT (serine-threonine kinase)/mTOR (mammalian target of rapamycin) pathway and epigenetic changes in DNA methylation seem to not only have prognostic/predictive value but also, most importantly, represent valuable therapeutic targets. Finally, there is increasing evidence that the development of novel risk assessment tools combining standard clinical-pathological factors with molecular markers represents a major quest in managing this poorly predictable disease.

Predicting Breed Composition Using Breed Frequencies of 50,000 Markers from the U.S. Meat Animal Research Center 2,000 Bull Project

USDA-ARS?s Scientific Manuscript database

Our objective was to evaluate whether breed composition of crossbred cattle could be predicted using reference breed frequencies of SNP markers on the BovineSNP50 array. Semen DNA samples of over 2,000 bulls from 16 common commercial beef breeds were genotyped using the array and used to estimate cu...

An Investigation of Depression, Trauma History, and Symptom Severity in Individuals Enrolled in a Treatment Trial for Chronic PTSD

PubMed Central

Bedard-Gilligan, Michele; Duax Jakob, Jeanne M.; Doane, Lisa Stines; Jaeger, Jeff; Eftekhari, Afsoon; Feeny, Norah; Zoellner, Lori A.

2015-01-01

Objectives To explore how factors such as major depressive disorder (MDD) and trauma history, including the presence of childhood abuse, influence diverse clinical outcomes such as severity and functioning in a sample with posttraumatic stress disorder (PTSD). Method In this study, 200 men and women seeking treatment for chronic PTSD in a clinical trial were assessed for trauma history and major depressive disorder and compared on symptom severity, psychosocial functioning, dissociation, treatment history, and extent of diagnostic co-occurrence. Results Overall, childhood abuse did not consistently predict clinical severity. However, co-occurring MDD, and to a lesser extent a high level of trauma exposure, did predict greater severity, worse functioning, greater dissociation, more extensive treatment history, and additional co-occurring disorders. Conclusions These findings suggest that presence of co-occurring depression may be a more critical marker of severity and impairment than history of childhood abuse or repeated trauma exposure. Furthermore, they emphasize the importance of assessing MDD and its impact on treatment seeking and treatment response for those with PTSD. PMID:25900026

Interruption or deferral of antiretroviral therapy reduces markers of bone turnover compared with continuous therapy: the SMART Body Composition Substudy

PubMed Central

Hoy, Jennifer; Grund, Birgit; Roediger, Mollie; Ensrud, Kristine E.; Brar, Indira; Colebunders, Robert; De Castro, Nathalie; Johnson, Margaret; Sharma, Anjali; Carr, Andrew

2013-01-01

Bone mineral density (BMD) declines significantly in HIV patients on antiretroviral therapy (ART). We compared the effects of intermittent versus continuous ART on markers of bone turnover in the Body Composition substudy of the Strategies for Management of AntiRetroviral Therapy (SMART) trial and determined whether early changes in markers predicted subsequent change in BMD. For 202 participants (median age 44 years, 17% female, 74% on ART) randomised to continuous or intermittent ART, plasma markers of inflammation and bone turnover were evaluated at baseline, months 4 and 12; BMD at the spine (dual X-ray absorptiometry [DXA] and computed tomography) and hip (DXA) was evaluated annually. Compared to the continuous ART group, mean bone-specific alkaline phosphatase (bALP), osteocalcin, procollagen type 1 N-terminal propeptide (P1NP), N-terminal cross-linking telopeptide of type 1 collagen (NTX), and C-terminal cross-linking telopeptide of type 1 collagen (βCTX) decreased significantly in the intermittent ART group, whereas RANKL and the RANKL:osteoprotegerin (OPG) ratio increased (all p≤0.002 at month 4 and month 12). Increases in bALP, osteocalcin, P1NP, NTX, and βCTX at month 4 predicted decrease in hip BMD at month 12, while increases in RANKL and the RANKL:OPG ratio at month 4 predicted increase in hip and spine BMD at month 12. This study has shown that compared with continuous ART, interruption of ART results in a reduction in markers of bone turnover and increase in BMD at hip and spine, and that early changes in markers of bone turnover predict BMD changes at 12 months. PMID:23299909

Comparison of trunk acceleration ratios during stair negotiation in old-old females.

PubMed

Shin, Sun-Shil; Yoo, Won-Gyu

2016-06-01

[Purpose] This study compared trunk acceleration ratios in old-old adult females during stair negotiation. [Subjects and Methods] Twelve old-old adult females who could walk independently volunteered for this study. This study measured gait time and trunk acceleration ratios using an accelerometer during ascending and descending stairs [Results] The trunk acceleration ratio when descending stairs was significantly higher than that when ascending stairs. [Conclusion] These findings suggest that old-old females have greater deterioration of upper trunk control function for descending than for ascending stairs, regardless of task time. In addition, the trunk acceleration ratio during stair negotiation is a useful clinical marker to predict function and balance control ability in old-old females.

Predicting the Naturalistic Course of Major Depressive Disorder Using Clinical and Multimodal Neuroimaging Information: A Multivariate Pattern Recognition Study.

PubMed

Schmaal, Lianne; Marquand, Andre F; Rhebergen, Didi; van Tol, Marie-José; Ruhé, Henricus G; van der Wee, Nic J A; Veltman, Dick J; Penninx, Brenda W J H

2015-08-15

A chronic course of major depressive disorder (MDD) is associated with profound alterations in brain volumes and emotional and cognitive processing. However, no neurobiological markers have been identified that prospectively predict MDD course trajectories. This study evaluated the prognostic value of different neuroimaging modalities, clinical characteristics, and their combination to classify MDD course trajectories. One hundred eighteen MDD patients underwent structural and functional magnetic resonance imaging (MRI) (emotional facial expressions and executive functioning) and were clinically followed-up at 2 years. Three MDD trajectories (chronic n = 23, gradual improving n = 36, and fast remission n = 59) were identified based on Life Chart Interview measuring the presence of symptoms each month. Gaussian process classifiers were employed to evaluate prognostic value of neuroimaging data and clinical characteristics (including baseline severity, duration, and comorbidity). Chronic patients could be discriminated from patients with more favorable trajectories from neural responses to various emotional faces (up to 73% accuracy) but not from structural MRI and functional MRI related to executive functioning. Chronic patients could also be discriminated from remitted patients based on clinical characteristics (accuracy 69%) but not when age differences between the groups were taken into account. Combining different task contrasts or data sources increased prediction accuracies in some but not all cases. Our findings provide evidence that the prediction of naturalistic course of depression over 2 years is improved by considering neuroimaging data especially derived from neural responses to emotional facial expressions. Neural responses to emotional salient faces more accurately predicted outcome than clinical data. Copyright © 2015 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

Black Hole Sign Predicts Poor Outcome in Patients with Intracerebral Hemorrhage.

PubMed

Li, Qi; Yang, Wen-Song; Chen, Sheng-Li; Lv, Fu-Rong; Lv, Fa-Jin; Hu, Xi; Zhu, Dan; Cao, Du; Wang, Xing-Chen; Li, Rui; Yuan, Liang; Qin, Xin-Yue; Xie, Peng

2018-01-01

In spontaneous intracerebral hemorrhage (ICH), black hole sign has been proposed as a promising imaging marker that predicts hematoma expansion in patients with ICH. The aim of our study was to investigate whether admission CT black hole sign predicts hematoma growth in patients with ICH. From July 2011 till February 2016, patients with spontaneous ICH who underwent baseline CT scan within 6 h of symptoms onset and follow-up CT scan were recruited into the study. The presence of black hole sign on admission non-enhanced CT was independently assessed by 2 readers. The functional outcome was assessed using the modified Rankin Scale (mRS) at 90 days. Univariate and multivariable logistic regression analyses were performed to assess the association between the presence of the black hole sign and functional outcome. A total of 225 patients (67.6% male, mean age 60.3 years) were included in our study. Black hole sign was identified in 32 of 225 (14.2%) patients on admission CT scan. The multivariate logistic regression analysis demonstrated that age, intraventricular hemorrhage, baseline ICH volume, admission Glasgow Coma Scale score, and presence of black hole sign on baseline CT independently predict poor functional outcome at 90 days. There are significantly more patients with a poor functional outcome (defined as mRS ≥4) among patients with black hole sign than those without (84.4 vs. 32.1%, p < 0.001; OR 8.19, p = 0.001). The CT black hole sign independently predicts poor outcome in patients with ICH. Early identification of black hole sign is useful in prognostic stratification and may serve as a potential therapeutic target for anti-expansion clinical trials. © 2018 S. Karger AG, Basel.

Novel applications of multitask learning and multiple output regression to multiple genetic trait prediction.

PubMed

He, Dan; Kuhn, David; Parida, Laxmi

2016-06-15

Given a set of biallelic molecular markers, such as SNPs, with genotype values encoded numerically on a collection of plant, animal or human samples, the goal of genetic trait prediction is to predict the quantitative trait values by simultaneously modeling all marker effects. Genetic trait prediction is usually represented as linear regression models. In many cases, for the same set of samples and markers, multiple traits are observed. Some of these traits might be correlated with each other. Therefore, modeling all the multiple traits together may improve the prediction accuracy. In this work, we view the multitrait prediction problem from a machine learning angle: as either a multitask learning problem or a multiple output regression problem, depending on whether different traits share the same genotype matrix or not. We then adapted multitask learning algorithms and multiple output regression algorithms to solve the multitrait prediction problem. We proposed a few strategies to improve the least square error of the prediction from these algorithms. Our experiments show that modeling multiple traits together could improve the prediction accuracy for correlated traits. The programs we used are either public or directly from the referred authors, such as MALSAR (http://www.public.asu.edu/~jye02/Software/MALSAR/) package. The Avocado data set has not been published yet and is available upon request. dhe@us.ibm.com. © The Author 2016. Published by Oxford University Press.

[Prognostic and predictive molecular markers for urologic cancers].

PubMed

Hartmann, A; Schlomm, T; Bertz, S; Heinzelmann, J; Hölters, S; Simon, R; Stoehr, R; Junker, K

2014-04-01

Molecular prognostic factors and genetic alterations as predictive markers for cancer-specific targeted therapies are used today in the clinic for many malignancies. In recent years, many molecular markers for urogenital cancers have also been identified. However, these markers are not clinically used yet. In prostate cancer, novel next-generation sequencing methods revealed a detailed picture of the molecular changes. There is growing evidence that a combination of classical histopathological and validated molecular markers could lead to a more precise estimation of prognosis, thus, resulting in an increasing number of patients with active surveillance as a possible treatment option. In patients with urothelial carcinoma, histopathological factors but also the proliferation of the tumor, mutations in oncogenes leading to an increasing proliferation rate and changes in genes responsible for invasion and metastasis are important. In addition, gene expression profiles which could distinguish aggressive tumors with high risk of metastasis from nonmetastasizing tumors have been recently identified. In the future, this could potentially allow better selection of patients needing systemic perioperative treatment. In renal cell carcinoma, many molecular markers that are associated with metastasis and survival have been identified. Some of these markers were also validated as independent prognostic markers. Selection of patients with primarily organ-confined tumors and increased risk of metastasis for adjuvant systemic therapy could be clinically relevant in the future.

Effectiveness of genomic prediction of maize hybrid performance in different breeding populations and environments.

PubMed

Windhausen, Vanessa S; Atlin, Gary N; Hickey, John M; Crossa, Jose; Jannink, Jean-Luc; Sorrells, Mark E; Raman, Babu; Cairns, Jill E; Tarekegne, Amsal; Semagn, Kassa; Beyene, Yoseph; Grudloyma, Pichet; Technow, Frank; Riedelsheimer, Christian; Melchinger, Albrecht E

2012-11-01

Genomic prediction is expected to considerably increase genetic gains by increasing selection intensity and accelerating the breeding cycle. In this study, marker effects estimated in 255 diverse maize (Zea mays L.) hybrids were used to predict grain yield, anthesis date, and anthesis-silking interval within the diversity panel and testcross progenies of 30 F(2)-derived lines from each of five populations. Although up to 25% of the genetic variance could be explained by cross validation within the diversity panel, the prediction of testcross performance of F(2)-derived lines using marker effects estimated in the diversity panel was on average zero. Hybrids in the diversity panel could be grouped into eight breeding populations differing in mean performance. When performance was predicted separately for each breeding population on the basis of marker effects estimated in the other populations, predictive ability was low (i.e., 0.12 for grain yield). These results suggest that prediction resulted mostly from differences in mean performance of the breeding populations and less from the relationship between the training and validation sets or linkage disequilibrium with causal variants underlying the predicted traits. Potential uses for genomic prediction in maize hybrid breeding are discussed emphasizing the need of (1) a clear definition of the breeding scenario in which genomic prediction should be applied (i.e., prediction among or within populations), (2) a detailed analysis of the population structure before performing cross validation, and (3) larger training sets with strong genetic relationship to the validation set.

Gaussian covariance graph models accounting for correlated marker effects in genome-wide prediction.

PubMed

Martínez, C A; Khare, K; Rahman, S; Elzo, M A

2017-10-01

Several statistical models used in genome-wide prediction assume uncorrelated marker allele substitution effects, but it is known that these effects may be correlated. In statistics, graphical models have been identified as a useful tool for covariance estimation in high-dimensional problems and it is an area that has recently experienced a great expansion. In Gaussian covariance graph models (GCovGM), the joint distribution of a set of random variables is assumed to be Gaussian and the pattern of zeros of the covariance matrix is encoded in terms of an undirected graph G. In this study, methods adapting the theory of GCovGM to genome-wide prediction were developed (Bayes GCov, Bayes GCov-KR and Bayes GCov-H). In simulated data sets, improvements in correlation between phenotypes and predicted breeding values and accuracies of predicted breeding values were found. Our models account for correlation of marker effects and permit to accommodate general structures as opposed to models proposed in previous studies, which consider spatial correlation only. In addition, they allow incorporation of biological information in the prediction process through its use when constructing graph G, and their extension to the multi-allelic loci case is straightforward. © 2017 Blackwell Verlag GmbH.

Liver fatty-acid-binding protein in heart and kidney allograft recipients in relation to kidney function.

PubMed

Przybylowski, P; Koc-Zorawska, E; Malyszko, J S; Kozlowska, S; Mysliwiec, M; Malyszko, J

2011-10-01

Mammalian intracellular fatty-acid-binding proteins (FABPs), a large multigene family, encode 14-kD proteins that are members of a superfamily of lipid-binding proteins. FABPs are tissue specific. Liver-type FABP (L-FABP) can be filtered through the glomerulus owing to its small molecular size, similar to cystatin C, but it is reabsorbed by proximal tubule epithelial cells like other small proteins. In the human kidney, L-FABP is expressed predominantly in proximal tubules. It had been suggested that the presence of L-FABP in urine reflects hypoxic conditions resulting from decreased peritubular capillary flow, serving as a marker of acute kidney injury. The aim of this study was to assess urinary L-FABP in 111 heart and 76 kidney transplant recipients in relation to kidney function. Complete blood count, urea, fasting glucose, creatinine, and the N-terminal fragment of brain natriuretic protein were studied by standard laboratory methods; L-FABP and cystatin C, by ELISA using commercially available kits. Kidney transplant recipients displayed significantly higher L-FABP than heart recipients. Upon univariate analysis, urinary L-FABP correlated, with serum creatinine, cystatin C and estimated glomerular filtration ratio (eGFR) in kidney allograft recipients. However, in heart transplant recipients it was not related to kidney function, as reflected by creatinine or eGFR; was strongly related to cystatin C (r=0.34; P<.001) and urinary creatinine (r=-0.29; P<.01), and NGAL (r=0.29; P<.01). Upon multiple regression analysis, the best predictor of urinary L-FABP in kidney allograft recipients, was eGFR whereas in heart recipients, no parameter independently predicted L-FABP. Successful heart transplantation is associated with kidney injury as reflected by a reduced eGFR; however, in this population, L-FABP did not serve as a marker of kidney function. In contrast, in kidney allograft recipients, L-FABP may be a potential early marker for impaired kidney function/injury. Copyright © 2011 Elsevier Inc. All rights reserved.

Early predicted time to normalization of tumor markers predicts outcome in poor-prognosis nonseminomatous germ cell tumors.

PubMed

Fizazi, Karim; Culine, Stéphane; Kramar, Andrew; Amato, Robert J; Bouzy, Jeannine; Chen, Isan; Droz, Jean-Pierre; Logothetis, Christopher J

2004-10-01

The prognostic relevance of the rate of decline of serum alpha-fetoprotein (AFP) and human chorionic gonadotropin (HCG) during the first 3 weeks of chemotherapy for nonseminomatous germ cell tumors (NSGCT) was studied in the context of the International Germ Cell Cancer Collaborative Group (IGCCCG) classification. Data from 653 patients prospectively recruited in clinical trials were studied. Tumor markers were obtained before chemotherapy and 3 weeks later. Decline rates were calculated using a logarithmic formula and expressed as a predicted time to normalization (TTN). A favorable TTN was defined when both AFP and HCG had a favorable decline rate, including cases with normal values. The median follow-up was 50 months (range, 2 to 151 months). Tumor decline rate expressed as a predicted TTN was associated with both progression-free survival (PFS; P <.0001) and overall survival (OS; P <.0001). The 4-year PFS rates were 64% and 38% in patients from the poor-prognosis group who had a favorable and an unfavorable TTN, respectively. The 4-year OS rates were 83% and 58%, respectively. This effect was independent from the initial tumor marker values, the primary tumor site, and the presence of nonpulmonary visceral metastases: tumor marker decline rate remained a strong predictor for both PFS (hazard ratio = 2.5; P =.01) and OS (hazard ratio = 4.6; P =.002) in patients from the IGCCCG poor-prognosis group in multivariate analysis. Early predicted time to tumor marker normalization is an independent prognostic factor in patients with poor-prognosis NSGCT and may be a useful tool in the therapeutic management of these patients.

Mitigating Errors in External Respiratory Surrogate-Based Models of Tumor Position

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

Malinowski, Kathleen T.; Fischell Department of Bioengineering, University of Maryland, College Park, MD; McAvoy, Thomas J.

2012-04-01

Purpose: To investigate the effect of tumor site, measurement precision, tumor-surrogate correlation, training data selection, model design, and interpatient and interfraction variations on the accuracy of external marker-based models of tumor position. Methods and Materials: Cyberknife Synchrony system log files comprising synchronously acquired positions of external markers and the tumor from 167 treatment fractions were analyzed. The accuracy of Synchrony, ordinary-least-squares regression, and partial-least-squares regression models for predicting the tumor position from the external markers was evaluated. The quantity and timing of the data used to build the predictive model were varied. The effects of tumor-surrogate correlation and the precisionmore » in both the tumor and the external surrogate position measurements were explored by adding noise to the data. Results: The tumor position prediction errors increased during the duration of a fraction. Increasing the training data quantities did not always lead to more accurate models. Adding uncorrelated noise to the external marker-based inputs degraded the tumor-surrogate correlation models by 16% for partial-least-squares and 57% for ordinary-least-squares. External marker and tumor position measurement errors led to tumor position prediction changes 0.3-3.6 times the magnitude of the measurement errors, varying widely with model algorithm. The tumor position prediction errors were significantly associated with the patient index but not with the fraction index or tumor site. Partial-least-squares was as accurate as Synchrony and more accurate than ordinary-least-squares. Conclusions: The accuracy of surrogate-based inferential models of tumor position was affected by all the investigated factors, except for the tumor site and fraction index.« less

Machine learning classification with confidence: application of transductive conformal predictors to MRI-based diagnostic and prognostic markers in depression.

PubMed

Nouretdinov, Ilia; Costafreda, Sergi G; Gammerman, Alexander; Chervonenkis, Alexey; Vovk, Vladimir; Vapnik, Vladimir; Fu, Cynthia H Y

2011-05-15

There is rapidly accumulating evidence that the application of machine learning classification to neuroimaging measurements may be valuable for the development of diagnostic and prognostic prediction tools in psychiatry. However, current methods do not produce a measure of the reliability of the predictions. Knowing the risk of the error associated with a given prediction is essential for the development of neuroimaging-based clinical tools. We propose a general probabilistic classification method to produce measures of confidence for magnetic resonance imaging (MRI) data. We describe the application of transductive conformal predictor (TCP) to MRI images. TCP generates the most likely prediction and a valid measure of confidence, as well as the set of all possible predictions for a given confidence level. We present the theoretical motivation for TCP, and we have applied TCP to structural and functional MRI data in patients and healthy controls to investigate diagnostic and prognostic prediction in depression. We verify that TCP predictions are as accurate as those obtained with more standard machine learning methods, such as support vector machine, while providing the additional benefit of a valid measure of confidence for each prediction. Copyright © 2010 Elsevier Inc. All rights reserved.

Algorithms for selecting informative marker panels for population assignment.

PubMed

Rosenberg, Noah A

2005-11-01

Given a set of potential source populations, genotypes of an individual of unknown origin at a collection of markers can be used to predict the correct source population of the individual. For improved efficiency, informative markers can be chosen from a larger set of markers to maximize the accuracy of this prediction. However, selecting the loci that are individually most informative does not necessarily produce the optimal panel. Here, using genotypes from eight species--carp, cat, chicken, dog, fly, grayling, human, and maize--this univariate accumulation procedure is compared to new multivariate "greedy" and "maximin" algorithms for choosing marker panels. The procedures generally suggest similar panels, although the greedy method often recommends inclusion of loci that are not chosen by the other algorithms. In seven of the eight species, when applied to five or more markers, all methods achieve at least 94% assignment accuracy on simulated individuals, with one species--dog--producing this level of accuracy with only three markers, and the eighth species--human--requiring approximately 13-16 markers. The new algorithms produce substantial improvements over use of randomly selected markers; where differences among the methods are noticeable, the greedy algorithm leads to slightly higher probabilities of correct assignment. Although none of the approaches necessarily chooses the panel with optimal performance, the algorithms all likely select panels with performance near enough to the maximum that they all are suitable for practical use.

A Comparison Between Genotyping-by-sequencing and Array-based Scoring of SNPs for Genomic Prediction Accuracy in Winter Wheat

USDA-ARS?s Scientific Manuscript database

The utilization of DNA molecular markers in plant breeding to maximize selection response via marker assisted selection (MAS) and genomic selection (GS) has the potential to revolutionize plant breeding. A key factor affecting GS applicability is the choice of molecular marker platform. Genotypying-...

Reliability increases from combining 50,000- and 777,000-marker genotypes from four countries

USDA-ARS?s Scientific Manuscript database

Genomic predictions were compared on U.S. scale after combining 50,000 (50K) and 777,000 (HD) marker genotypes across countries. The genotyped Holsteins included 161,341 animals with five marker densities including 1,510 with HD. Imputation was more accurate with FImpute than with findhap across the...

Multiple Biomarker Panels for Early Detection of Breast Cancer in Peripheral Blood

PubMed Central

Zhang, Fan; Deng, Youping; Drabier, Renee

2013-01-01

Detecting breast cancer at early stages can be challenging. Traditional mammography and tissue microarray that have been studied for early breast cancer detection and prediction have many drawbacks. Therefore, there is a need for more reliable diagnostic tools for early detection of breast cancer due to a number of factors and challenges. In the paper, we presented a five-marker panel approach based on SVM for early detection of breast cancer in peripheral blood and show how to use SVM to model the classification and prediction problem of early detection of breast cancer in peripheral blood. We found that the five-marker panel can improve the prediction performance (area under curve) in the testing data set from 0.5826 to 0.7879. Further pathway analysis showed that the top four five-marker panels are associated with signaling, steroid hormones, metabolism, immune system, and hemostasis, which are consistent with previous findings. Our prediction model can serve as a general model for multibiomarker panel discovery in early detection of other cancers. PMID:24371830

Multiple biomarker panels for early detection of breast cancer in peripheral blood.

PubMed

Zhang, Fan; Deng, Youping; Drabier, Renee

2013-01-01

Detecting breast cancer at early stages can be challenging. Traditional mammography and tissue microarray that have been studied for early breast cancer detection and prediction have many drawbacks. Therefore, there is a need for more reliable diagnostic tools for early detection of breast cancer due to a number of factors and challenges. In the paper, we presented a five-marker panel approach based on SVM for early detection of breast cancer in peripheral blood and show how to use SVM to model the classification and prediction problem of early detection of breast cancer in peripheral blood. We found that the five-marker panel can improve the prediction performance (area under curve) in the testing data set from 0.5826 to 0.7879. Further pathway analysis showed that the top four five-marker panels are associated with signaling, steroid hormones, metabolism, immune system, and hemostasis, which are consistent with previous findings. Our prediction model can serve as a general model for multibiomarker panel discovery in early detection of other cancers.

Biomarker in Cisplatin-Based Chemotherapy for Urinary Bladder Cancer.

PubMed

Ecke, Thorsten H

2015-01-01

The treatment of metastasized bladder cancer has been evolving during recent years. Cisplatin based chemotherapy combinations are still gold standard in the treatment of advanced and metastasized bladder cancer. But new therapies are approaching. Based to this fact biological markers will become more important for decisions in bladder cancer treatment. A systematic MEDLINE search of the key words "cisplatin", "bladder cancer", "DNA marker", "protein marker", "methylation biomarker", "predictive marker", "prognostic marker" has been made. This review aims to highlight the most relevant clinical and experimental studies investigating markers for metastasized transitional carcinoma of the urothelium treated by cisplatin based regimens.

Mechanical function of the heart and its alteration during myocardial ischemia and infarction. Specific reference to coronary atherosclerosis.

PubMed

Swan, H J

1979-12-01

Altered regional mechanical myocardial performance is an early, sensitive marker of myocardial ischemia, and can be estimated in man with reasonable accuracy. Identification, localization and quantification of abnormalities in mechanical performance can be used to predict the presence of coronary artery disease. Testing techniques that have little or no effect on diagnostic efficiency must be replaced with more sensitive indicators of ischemia. If experimental data are validated by findings in human subjects, accurate identification of regional wall motion changes during test conditions should prove to be a powerful marker of ischemia. To be of value, a diagnostic test must strongly increase the frequency of identification of subjects with a high probabilty for the presence of coronary artery disease in an otherwise low-prevalence population, and of those with known disease who are at the highest risk for complications including myocardial infarction or death.

[Serum anticholinergic activity: relationship with clinical symptoms in Alzheimer's disease and proposal of new biological marker].

PubMed

Hori, Koji; Konishi, Kimiko; Hachisu, Mitsugu

2011-06-01

We reviewed the importance of measuring serum anticholinergic activity (SAA) in patients with Alzheimer's disease (AD). Since Tune and Coyle reported a simple method for assessing SAA using radioreceptor-binding assay, SAA is assumed to be the cumulative activity of parent medications and their metabolites and its relationship with delirium and cognitive functions has been debated. However, we evaluated the SAA in AD patients and SAA was correlated with prescription of antipsychotic medications, cognitive dysfunctions, severity of AD and psychotic symptoms, especially, with delusion and diurnal rhythm disturbance. From these results, we should not only pay attention to avoiding the prescription of medications with anticholinergic activity but also we speculated that AA appeared endogenously in AD and accelerated AD pathology. Moreover, there might be the possibility that SAA has predictive value for assessing the progressiveness of AD and as a biological marker for AD.

A Population Genetics Model of Marker-Assisted Selection

PubMed Central

Luo, Z. W.; Thompson, R.; Woolliams, J. A.

1997-01-01

A deterministic two-loci model was developed to predict genetic response to marker-assisted selection (MAS) in one generation and in multiple generations. Formulas were derived to relate linkage disequilibrium in a population to the proportion of additive genetic variance used by MAS, and in turn to an extra improvement in genetic response over phenotypic selection. Predictions of the response were compared to those predicted by using an infinite-loci model and the factors affecting efficiency of MAS were examined. Theoretical analyses of the present study revealed the nonlinearity between the selection intensity and genetic response in MAS. In addition to the heritability of the trait and the proportion of the marker-associated genetic variance, the frequencies of the selectively favorable alleles at the two loci, one marker and one quantitative trait locus, were found to play an important role in determining both the short- and long-term efficiencies of MAS. The evolution of linkage disequilibrium and thus the genetic response over several generations were predicted theoretically and examined by simulation. MAS dissipated the disequilibrium more quickly than drift alone. In some cases studied, the rate of dissipation was as large as that to be expected in the circumstance where the true recombination fraction was increased by three times and selection was absent. PMID:9215918

Clinical utility of endocrine markers predicting myocardial siderosis in transfusion dependent thalassemia major.

PubMed

Ehsan, Lubaina; Rashid, Mariam; Alvi, Najveen; Awais, Khadija; Nadeem, Omair; Asghar, Aleezay; Sajjad, Fatimah; Fatima, Malika; Qidwai, Asim; Hussain, Shabneez; Hasan, Erum; Brown, Nick; Altaf, Sadaf; Hasan, Babar; Kirmani, Salman

2018-06-12

Endocrinopathy due to iron overload is the most common morbidity whereas myocardial siderosis causing toxic cardiomyopathy is the leading cause of mortality among patients with transfusion dependent thalassemia major (TDTM). If detected early, this can be treated with aggressive chelation. T2* cardiac magnetic resonance imaging (CMR) guided chelation protocols are now the gold standard but have limited availability in low and middle-income countries. We hypothesized that markers of endocrine dysfunction would correlate with T2* CMR and can be used to predict the severity of myocardial siderosis and guide chelation therapy. We undertook a multicenter retrospective study of 280 patients with TDTM to assess the prevalence of endocrinopathies and the predictive value of a number of individual and composite markers of endocrinopathy with T2* CMR. The prevalence of hypogonadism, stunting, hypoparathyroidism, and hypothyroidism was 82%, 69%, 40%, and 30%, respectively. The sensitivity of hypogonadism and stunting predicting severe myocardial siderosis was 90% and 80%, respectively. We conclude that clinical markers of endocrine dysfunction, especially hypogonadism (positive likelihood ratio [LR+] = 1.4, 95% confidence interval [CI] = 1.0-1.9; positive predictive value [PPV] = 77%, 95% CI = 70-82; negative predictive value [NPV] = 57%, 95% CI = 34-77] and stunting (LR+ = 1.3, 95% CI = 1.1-1.6; PPV = 64%, 95% CI = 60-69; NPV = 55%, 95% CI = 45-64) in TDTM can predict severe myocardial siderosis and can potentially guide chelation therapy, especially where access to T2* CMR is limited. © 2018 Wiley Periodicals, Inc.

Graphical assessment of incremental value of novel markers in prediction models: From statistical to decision analytical perspectives.

PubMed

Steyerberg, Ewout W; Vedder, Moniek M; Leening, Maarten J G; Postmus, Douwe; D'Agostino, Ralph B; Van Calster, Ben; Pencina, Michael J

2015-07-01

New markers may improve prediction of diagnostic and prognostic outcomes. We aimed to review options for graphical display and summary measures to assess the predictive value of markers over standard, readily available predictors. We illustrated various approaches using previously published data on 3264 participants from the Framingham Heart Study, where 183 developed coronary heart disease (10-year risk 5.6%). We considered performance measures for the incremental value of adding HDL cholesterol to a prediction model. An initial assessment may consider statistical significance (HR = 0.65, 95% confidence interval 0.53 to 0.80; likelihood ratio p < 0.001), and distributions of predicted risks (densities or box plots) with various summary measures. A range of decision thresholds is considered in predictiveness and receiver operating characteristic curves, where the area under the curve (AUC) increased from 0.762 to 0.774 by adding HDL. We can furthermore focus on reclassification of participants with and without an event in a reclassification graph, with the continuous net reclassification improvement (NRI) as a summary measure. When we focus on one particular decision threshold, the changes in sensitivity and specificity are central. We propose a net reclassification risk graph, which allows us to focus on the number of reclassified persons and their event rates. Summary measures include the binary AUC, the two-category NRI, and decision analytic variants such as the net benefit (NB). Various graphs and summary measures can be used to assess the incremental predictive value of a marker. Important insights for impact on decision making are provided by a simple graph for the net reclassification risk. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Age and Vascular Burden Determinants of Cortical Hemodynamics Underlying Verbal Fluency.

PubMed

Heinzel, Sebastian; Metzger, Florian G; Ehlis, Ann-Christine; Korell, Robert; Alboji, Ahmed; Haeussinger, Florian B; Wurster, Isabel; Brockmann, Kathrin; Suenkel, Ulrike; Eschweiler, Gerhard W; Maetzler, Walter; Berg, Daniela; Fallgatter, Andreas J

2015-01-01

Aging processes and several vascular burden factors have been shown to increase the risk of dementia including Alzheimer's disease. While pathological alterations in dementia precede diagnosis by many years, reorganization of brain processing might temporarily delay cognitive decline. We hypothesized that in healthy elderly individuals both age-related neural and vascular factors known to be related to the development of dementia impact functional cortical hemodynamics during increased cognitive demands. Vascular burden factors and cortical functional hemodynamics during verbal fluency were assessed in 1052 non-demented elderly individuals (51 to 83 years; cross-sectional data of the longitudinal TREND study) using functional near-infrared spectroscopy (fNIRS). The prediction of functional hemodynamic responses by age in multiple regressions and the impact of single and cumulative vascular burden factors including hypertension, diabetes, obesity, smoking and atherosclerosis were investigated. Replicating and extending previous findings we could show that increasing age predicted functional hemodynamics to be increased in right prefrontal and bilateral parietal cortex, and decreased in bilateral inferior frontal junction during phonological fluency. Cumulative vascular burden factors, with hypertension in particular, decreased left inferior frontal junction hemodynamic responses during phonological fluency. However, age and vascular burden factors showed no statistical interaction on functional hemodynamics. Based on these findings, one might hypothesize that increased fronto-parietal processing may represent age-related compensatory reorganization during increased cognitive demands. Vascular burden factors, such as hypertension, may contribute to regional cerebral hypoperfusion. These neural and vascular hemodynamic determinants should be investigated longitudinally and combined with other markers to advance the prediction of future cognitive decline and dementia.

Evaluation of 7 serum biomarkers and uterine artery Doppler ultrasound for first-trimester prediction of preeclampsia: a systematic review.

PubMed

Kuc, Sylwia; Wortelboer, Esther J; van Rijn, Bas B; Franx, Arie; Visser, Gerard H A; Schielen, Peter C J I

2011-04-01

Preeclampsia (PE) affects 1% to 2% of pregnant women and is a leading cause of maternal and perinatal morbidity and mortality worldwide. The clinical syndrome of PE arises in the second half of pregnancy. However, many underlying factors including defective placentation may already be apparent in the first and early second trimester in many patients. In clinical practice, there is currently no reliable screening method in the first trimester of pregnancy with sufficient accuracy to identify women at high risk to develop PE. Early identification of high-risk pregnancy may facilitate the development of new strategies for antenatal surveillance or prevention and thus improve maternal and perinatal outcome. The aim of this systematic review was to study the literature on the predictive potential of first-trimester serum markers and of uterine artery Doppler velocity waveform assessment (Ut-A Doppler). Literature on the 7 most studied serum markers (ADAM12, fβ-hCG, Inhibin A, Activin A, PP13, PlGF, and PAPP-A) and Ut-A Doppler was primarily selected. In the selected literature, a combination of these markers was analyzed, and where relevant, the value of maternal characteristics was added. Measurements of serum markers and Ut-A Doppler were performed between week 8 + 0 and 14 + 0 GA. Low levels of PP13, PlGF, and PAPP-A and elevated level of Inhibin A have been found to be significantly associated with the development of PE later in pregnancy. The detection rates of single markers, fixed at 10% false-positive rate, in the prediction of early-onset PE were relatively low, and ranged from 22% to 83%. Detection rates for combinations of multiple markers varied between 38% and 100%. Therefore, a combination of multiple markers yields high detection rates and is promising to identify patients at high risk of developing PE. However, large scale prospective studies are required to evaluate the power of this integrated approach in clinical practice. Obstetricians and Gynecologists, Family physicians Learning Objectives: After completion of this article, the reader should be better able to appraise the recent literature on the development of preeclampsia in the first-trimester, evaluate the predictive value of first-trimester markers and use first-trimester markers, either individually or in combination, to assess the risk of preeclampsia.

How to predict clinical relapse in inflammatory bowel disease patients

PubMed Central

Liverani, Elisa; Scaioli, Eleonora; Digby, Richard John; Bellanova, Matteo; Belluzzi, Andrea

2016-01-01

Inflammatory bowel diseases have a natural course characterized by alternating periods of remission and relapse. Disease flares occur in a random way and are currently unpredictable for the most part. Predictors of benign or unfavourable clinical course are required to facilitate treatment decisions and to avoid overtreatment. The present article provides a literature review of the current evidence on the main clinical, genetic, endoscopic, histologic, serologic and fecal markers to predict aggressiveness of inflammatory bowel disease and discuss their prognostic role, both in Crohn’s disease and ulcerative colitis. No single marker seems to be reliable alone as a flare predictor, even in light of promising evidence regarding the role of fecal markers, in particular fecal calprotectin, which has reported good results recently. In order to improve our daily clinical practice, validated prognostic scores should be elaborated, integrating clinical and biological markers of prognosis. Finally, we propose an algorithm considering clinical history and biological markers to intercept patients with high risk of clinical relapse. PMID:26811644

EGFR Gene Amplification and KRAS Mutation Predict Response to Combination Targeted Therapy in Metastatic Colorectal Cancer.

PubMed

Khan, Sajid A; Zeng, Zhaoshi; Shia, Jinru; Paty, Philip B

2017-07-01

Genetic variability in KRAS and EGFR predicts response to cetuximab in irinotecan refractory colorectal cancer. Whether these markers or others remain predictive in combination biologic therapies including bevacizumab is unknown. We identified predictive biomarkers from patients with irinotecan refractory metastatic colorectal cancer treated with cetuximab plus bevacizumab. Patients who received cetuximab plus bevacizumab for irinotecan refractory colorectal cancer in either of two Phase II trials conducted were identified. Tumor tissue was available for 33 patients. Genomic DNA was extracted and used for mutational analysis of KRAS, BRAF, and p53 genes. Fluorescence in situ hybridization was performed to assess EGFR copy number. The status of single genes and various combinations were tested for association with response. Seven of 33 patients responded to treatment. KRAS mutations were found in 14/33 cases, and 0 responded to treatment (p = 0.01). EGFR gene amplification was seen in 3/33 of tumors and in every case was associated with response to treatment (p < 0.001). TP53 and BRAF mutations were found in 18/33 and 0/33 tumors, respectively, and there were no associations with response to either gene. EGFR gene amplification and KRAS mutations are predictive markers for patients receiving combination biologic therapy of cetuximab plus bevacizumab for metastatic colorectal cancer. One marker or the other is present in the tumor of half of all patients allowing treatment response to be predicted with a high degree of certainty. The role for molecular markers in combination biologic therapy seems promising.

Resting lateralized activity predicts the cortical response and appraisal of emotions: an fNIRS study.

PubMed

Balconi, Michela; Grippa, Elisabetta; Vanutelli, Maria Elide

2015-12-01

This study explored the effect of lateralized left-right resting brain activity on prefrontal cortical responsiveness to emotional cues and on the explicit appraisal (stimulus evaluation) of emotions based on their valence. Indeed subjective responses to different emotional stimuli should be predicted by brain resting activity and should be lateralized and valence-related (positive vs negative valence). A hemodynamic measure was considered (functional near-infrared spectroscopy). Indeed hemodynamic resting activity and brain response to emotional cues were registered when subjects (N = 19) viewed emotional positive vs negative stimuli (IAPS). Lateralized index response during resting state, LI (lateralized index) during emotional processing and self-assessment manikin rating were considered. Regression analysis showed the significant predictive effect of resting activity (more left or right lateralized) on both brain response and appraisal of emotional cues based on stimuli valence. Moreover, significant effects were found as a function of valence (more right response to negative stimuli; more left response to positive stimuli) during emotion processing. Therefore, resting state may be considered a predictive marker of the successive cortical responsiveness to emotions. The significance of resting condition for emotional behavior was discussed. © The Author (2015). Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

Can quantity of amniotic fluid reliably predict postnatal renal function in boys with posterior urethral valves: a decision curve analysis.

PubMed

Harper, Luke; Waubant, Alice; Vignes, Julien; Amat, Sara; Dobremez, Eric; Lefevre, Yan; Ferdynus, Cyril

2017-09-01

Prenatal management of male fetuses with suspected posterior urethral valves depends on reliable markers for postnatal long-term renal function. Whether ultrasound parameters, including the presence or absence of oligohydramnios, are reliable remains the subject of debate. We decided to evaluate the reliability of quantity of amniotic fluid to predict postnatal renal function using decision curve analysis (DCA), a method for evaluating the clinical utility of a diagnostic test. We analyzed retrospectively 51 male fetuses born with prenatally suspected posterior urethral valves between 2009 and 2012. We studied the relationship between quantity of amniotic fluid on prenatal ultrasound and the nadir creatinine during the first year of life as a proxy of postnatal renal function using DCA. Twelve fetuses presented with prenatal oligohydramnios. Thirty-one children had a normal nadir creatinine, of which one had prenatal oligohydramnios (3.2%). Thirteen had a nadir creatinine between 35 and 75 μmol/L, of which four had prenatal oligohydramnios (30.8%). Seven had a nadir creatinine >75 μmol/L, all of them had prenatal oligohydramnios. In this retrospective study, DCA confirms the relationship between prenatal quantity of amniotic fluid volume and postnatal renal function. © 2017 John Wiley & Sons, Ltd. © 2017 John Wiley & Sons, Ltd.

Gut Microbiome Function Predicts Response to Anti-integrin Biologic Therapy in Inflammatory Bowel Diseases.

PubMed

Ananthakrishnan, Ashwin N; Luo, Chengwei; Yajnik, Vijay; Khalili, Hamed; Garber, John J; Stevens, Betsy W; Cleland, Thomas; Xavier, Ramnik J

2017-05-10

The gut microbiome plays a central role in inflammatory bowel diseases (IBDs) pathogenesis and propagation. To determine whether the gut microbiome may predict responses to IBD therapy, we conducted a prospective study with Crohn's disease (CD) or ulcerative colitis (UC) patients initiating anti-integrin therapy (vedolizumab). Disease activity and stool metagenomes at baseline, and weeks 14, 30, and 54 after therapy initiation were assessed. Community α-diversity was significantly higher, and Roseburia inulinivorans and a Burkholderiales species were more abundant at baseline among CD patients achieving week 14 remission. Several significant associations were identified with microbial function; 13 pathways including branched chain amino acid synthesis were significantly enriched in baseline samples from CD patients achieving remission. A neural network algorithm, vedoNet, incorporating microbiome and clinical data, provided highest classifying power for clinical remission. We hypothesize that the trajectory of early microbiome changes may be a marker of response to IBD treatment. Copyright © 2017 Elsevier Inc. All rights reserved.

The Changing Nature of Adolescent Friendships Longitudinal Links With Early Adolescent Ego Development

PubMed Central

Marsh, Penny; Allen, Joseph P.; Ho, Martin; Porter, Maryfrances; McFarland, F. Christy

2008-01-01

Although success in managing evolving peer relationships is linked to critical adolescent outcomes, little is known about the specific factors that lead to success or failure in peer relationship development across adolescence. This longitudinal study examines the role of adolescents’ level of ego development as a predictor of the future course of several facets of friendship development in early adolescence. Ego development was assessed in a community sample of adolescents at age 13. Several facets of adolescent friendship were also assessed at 13 and then reassessed 1 year later, including adolescent intimate behavior during a supportive interaction with their best friends, adolescent reports of psychological security in their friendships, and peer-rated popularity. As predicted, ego development not only explained concurrent levels of peer functioning but also predicted markers of change over time in each of the assessed domains of peer functioning. Implications for ego development in increasing our understanding of individual differences in adolescent friendship development are discussed. PMID:18548124

Baseline series fragrance markers fail to predict contact allergy.

PubMed

Mann, Jack; McFadden, John P; White, Jonathan M L; White, Ian R; Banerjee, Piu

2014-05-01

Negative patch test results with fragrance allergy markers in the European baseline series do not always predict a negative reaction to individual fragrance substances. To determine the frequencies of positive test reactions to the 26 fragrance substances for which labelling is mandatory in the EU, and how effectively reactions to fragrance markers in the baseline series predict positive reactions to the fragrance substances that are labelled. The records of 1951 eczema patients, routinely tested with the labelled fragrance substances and with an extended European baseline series in 2011 and 2012, were retrospectively reviewed. Two hundred and eighty-one (14.4%) (71.2% females) reacted to one or more allergens from the labelled-fragrance substance series and/or a fragrance marker from the European baseline series. The allergens that were positive with the greatest frequencies were cinnamyl alcohol (48; 2.46%), Evernia furfuracea (44; 2.26%), and isoeugenol (40; 2.05%). Of the 203 patients who reacted to any of the 26 fragrances in the labelled-fragrance substance series, only 117 (57.6%) also reacted to a fragrance marker in the baseline series. One hundred and seven (52.7%) reacted to either fragrance mix I or fragrance mix II, 28 (13.8%) reacted to Myroxylon pereirae, and 13 (6.4%) reacted to hydroxyisohexyl 3-cyclohexene carboxaldehyde. These findings confirm that the standard fragrance markers fail to identify patients with contact allergies to the 26 fragrances. © 2014 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Support Vector Hazards Machine: A Counting Process Framework for Learning Risk Scores for Censored Outcomes.

PubMed

Wang, Yuanjia; Chen, Tianle; Zeng, Donglin

2016-01-01

Learning risk scores to predict dichotomous or continuous outcomes using machine learning approaches has been studied extensively. However, how to learn risk scores for time-to-event outcomes subject to right censoring has received little attention until recently. Existing approaches rely on inverse probability weighting or rank-based regression, which may be inefficient. In this paper, we develop a new support vector hazards machine (SVHM) approach to predict censored outcomes. Our method is based on predicting the counting process associated with the time-to-event outcomes among subjects at risk via a series of support vector machines. Introducing counting processes to represent time-to-event data leads to a connection between support vector machines in supervised learning and hazards regression in standard survival analysis. To account for different at risk populations at observed event times, a time-varying offset is used in estimating risk scores. The resulting optimization is a convex quadratic programming problem that can easily incorporate non-linearity using kernel trick. We demonstrate an interesting link from the profiled empirical risk function of SVHM to the Cox partial likelihood. We then formally show that SVHM is optimal in discriminating covariate-specific hazard function from population average hazard function, and establish the consistency and learning rate of the predicted risk using the estimated risk scores. Simulation studies show improved prediction accuracy of the event times using SVHM compared to existing machine learning methods and standard conventional approaches. Finally, we analyze two real world biomedical study data where we use clinical markers and neuroimaging biomarkers to predict age-at-onset of a disease, and demonstrate superiority of SVHM in distinguishing high risk versus low risk subjects.

Common Marker Genes Identified from Various Sample Types for Systemic Lupus Erythematosus.

PubMed

Bing, Peng-Fei; Xia, Wei; Wang, Lan; Zhang, Yong-Hong; Lei, Shu-Feng; Deng, Fei-Yan

2016-01-01

Systemic lupus erythematosus (SLE) is a complex auto-immune disease. Gene expression studies have been conducted to identify SLE-related genes in various types of samples. It is unknown whether there are common marker genes significant for SLE but independent of sample types, which may have potentials for follow-up translational research. The aim of this study is to identify common marker genes across various sample types for SLE. Based on four public microarray gene expression datasets for SLE covering three representative types of blood-born samples (monocyte; peripheral blood mononuclear cell, PBMC; whole blood), we utilized three statistics (fold-change, FC; t-test p value; false discovery rate adjusted p value) to scrutinize genes simultaneously regulated with SLE across various sample types. For common marker genes, we conducted the Gene Ontology enrichment analysis and Protein-Protein Interaction analysis to gain insights into their functions. We identified 10 common marker genes associated with SLE (IFI6, IFI27, IFI44L, OAS1, OAS2, EIF2AK2, PLSCR1, STAT1, RNASE2, and GSTO1). Significant up-regulation of IFI6, IFI27, and IFI44L with SLE was observed in all the studied sample types, though the FC was most striking in monocyte, compared with PBMC and whole blood (8.82-251.66 vs. 3.73-74.05 vs. 1.19-1.87). Eight of the above 10 genes, except RNASE2 and GSTO1, interact with each other and with known SLE susceptibility genes, participate in immune response, RNA and protein catabolism, and cell death. Our data suggest that there exist common marker genes across various sample types for SLE. The 10 common marker genes, identified herein, deserve follow-up studies to dissert their potentials as diagnostic or therapeutic markers to predict SLE or treatment response.

Candidate Markers Associated with the Probability of Future Pulmonary Exacerbations in Cystic Fibrosis Patients

PubMed Central

Wojewodka, Gabriella; De Sanctis, Juan B.; Bernier, Joanie; Bérubé, Julie; Ahlgren, Heather G.; Gruber, Jim; Landry, Jennifer; Lands, Larry C.; Nguyen, Dao; Rousseau, Simon; Benedetti, Andrea; Matouk, Elias; Radzioch, Danuta

2014-01-01

Introduction Pulmonary exacerbations (PEs) cause significant morbidity and can severely impact disease progression in cystic fibrosis (CF) lung disease, especially in patients who suffer from recurrent PEs. The assessments able to predict a future PE or a recurrent PE are limited. We hypothesized that combining clinical, molecular and patient reported data could identify patients who are at risk of PE. Methods We prospectively followed a cohort of 53 adult CF patients for 24 months. Baseline values for spirometry, clinical status using the Matouk Disease Score, quality of life (QOL), inflammatory markers (C-reactive protein (CRP), interleukins (IL)-1β, -6, -8, -10, macrophage inflammatory protein (MIP)-1β, tumor necrosis factor (TNF) and vascular endothelial growth factor (VEGF)), polyunsaturated fatty acids and lipid peroxidation in blood plasma were collected for all patients during periods of stable disease, and patients were monitored for PE requiring PO/IV antibiotic treatment. Additionally, we closely followed 13 patients during PEs collecting longitudinal data on changes in markers from baseline values. We assessed whether any markers were predictors of future PE at baseline and after antibiotic treatment. Results Out of 53 patients, 37 experienced PEs during our study period. At baseline, we found that low lung function, clinical scoring and QOL values were associated with increased risk of PE events. PEs were associated with increased inflammatory markers at Day 1, and these biomarkers improved with treatment. The imbalance in arachidonic acid and docosahexaenoic acid levels improved with treatment which coincided with reductions in lipid peroxidation. High levels of inflammatory markers CRP and IL-8 were associated with an early re-exacerbation. Conclusion Our results demonstrate that worse clinical and QOL assessments during stable disease are potential markers associated with a higher risk of future PEs, while higher levels of inflammatory markers at the end of antibiotic treatment may be associated with early re-exacerbation. PMID:24533110

Genome-wide association analysis of bacterial cold water disease resistance in rainbow trout reveals the potential of a hybrid approach between genomic selection and marker assisted selection

USDA-ARS?s Scientific Manuscript database

Genomic selection (GS) simultaneously incorporates dense SNP marker genotypes with phenotypic data from related animals to predict animal-specific genomic breeding value (GEBV), which circumvents the need to measure the disease phenotype in potential breeders. Marker assisted selection (MAS) involv...

Combined Screening for Early Detection of Pre-Eclampsia

PubMed Central

Park, Hee Jin; Shim, Sung Shin; Cha, Dong Hyun

2015-01-01

Although the precise pathophysiology of pre-eclampsia remains unknown, this condition continues to be a major cause of maternal and fetal mortality. Early prediction of pre-eclampsia would allow for timely initiation of preventive therapy. A combination of biophysical and biochemical markers are superior to other tests for early prediction of the development of pre-eclampsia. Apart from the use of parameters in first-trimester aneuploidy screening, cell-free fetal DNA quantification is emerging as a promising marker for prediction of pre-eclampsia. This article reviews the current research of the most important strategies for prediction of pre-eclampsia, including the use of maternal risk factors, mean maternal arterial pressure, ultrasound parameters, and biomarkers. PMID:26247944

The Identification of Novel Diagnostic Marker Genes for the Detection of Beer Spoiling Pediococcus damnosus Strains Using the BlAst Diagnostic Gene findEr

PubMed Central

Schmid, Jonas; Zehe, Anja; Vogel, Rudi F.

2016-01-01

As the number of bacterial genomes increases dramatically, the demand for easy to use tools with transparent functionality and comprehensible output for applied comparative genomics grows as well. We present BlAst Diagnostic Gene findEr (BADGE), a tool for the rapid prediction of diagnostic marker genes (DMGs) for the differentiation of bacterial groups (e.g. pathogenic / nonpathogenic). DMG identification settings can be modified easily and installing and running BADGE does not require specific bioinformatics skills. During the BADGE run the user is informed step by step about the DMG finding process, thus making it easy to evaluate the impact of chosen settings and options. On the basis of an example with relevance for beer brewing, being one of the oldest biotechnological processes known, we show a straightforward procedure, from phenotyping, genome sequencing, assembly and annotation, up to a discriminant marker gene PCR assay, making comparative genomics a means to an end. The value and the functionality of BADGE were thoroughly examined, resulting in the successful identification and validation of an outstanding novel DMG (fabZ) for the discrimination of harmless and harmful contaminations of Pediococcus damnosus, which can be applied for spoilage risk determination in breweries. Concomitantly, we present and compare five complete P. damnosus genomes sequenced in this study, finding that the ability to produce the unwanted, spoilage associated off-flavor diacetyl is a plasmid encoded trait in this important beer spoiling species. PMID:27028007

Improved age determination of blood and teeth samples using a selected set of DNA methylation markers

PubMed Central

Kamalandua, Aubeline

2015-01-01

Age estimation from DNA methylation markers has seen an exponential growth of interest, not in the least from forensic scientists. The current published assays, however, can still be improved by lowering the number of markers in the assay and by providing more accurate models to predict chronological age. From the published literature we selected 4 age-associated genes (ASPA, PDE4C, ELOVL2, and EDARADD) and determined CpG methylation levels from 206 blood samples of both deceased and living individuals (age range: 0–91 years). This data was subsequently used to compare prediction accuracy with both linear and non-linear regression models. A quadratic regression model in which the methylation levels of ELOVL2 were squared showed the highest accuracy with a Mean Absolute Deviation (MAD) between chronological age and predicted age of 3.75 years and an adjusted R2 of 0.95. No difference in accuracy was observed for samples obtained either from living and deceased individuals or between the 2 genders. In addition, 29 teeth from different individuals (age range: 19–70 years) were analyzed using the same set of markers resulting in a MAD of 4.86 years and an adjusted R2 of 0.74. Cross validation of the results obtained from blood samples demonstrated the robustness and reproducibility of the assay. In conclusion, the set of 4 CpG DNA methylation markers is capable of producing highly accurate age predictions for blood samples from deceased and living individuals PMID:26280308

Effectiveness of Genomic Prediction of Maize Hybrid Performance in Different Breeding Populations and Environments

PubMed Central

Windhausen, Vanessa S.; Atlin, Gary N.; Hickey, John M.; Crossa, Jose; Jannink, Jean-Luc; Sorrells, Mark E.; Raman, Babu; Cairns, Jill E.; Tarekegne, Amsal; Semagn, Kassa; Beyene, Yoseph; Grudloyma, Pichet; Technow, Frank; Riedelsheimer, Christian; Melchinger, Albrecht E.

2012-01-01

Genomic prediction is expected to considerably increase genetic gains by increasing selection intensity and accelerating the breeding cycle. In this study, marker effects estimated in 255 diverse maize (Zea mays L.) hybrids were used to predict grain yield, anthesis date, and anthesis-silking interval within the diversity panel and testcross progenies of 30 F2-derived lines from each of five populations. Although up to 25% of the genetic variance could be explained by cross validation within the diversity panel, the prediction of testcross performance of F2-derived lines using marker effects estimated in the diversity panel was on average zero. Hybrids in the diversity panel could be grouped into eight breeding populations differing in mean performance. When performance was predicted separately for each breeding population on the basis of marker effects estimated in the other populations, predictive ability was low (i.e., 0.12 for grain yield). These results suggest that prediction resulted mostly from differences in mean performance of the breeding populations and less from the relationship between the training and validation sets or linkage disequilibrium with causal variants underlying the predicted traits. Potential uses for genomic prediction in maize hybrid breeding are discussed emphasizing the need of (1) a clear definition of the breeding scenario in which genomic prediction should be applied (i.e., prediction among or within populations), (2) a detailed analysis of the population structure before performing cross validation, and (3) larger training sets with strong genetic relationship to the validation set. PMID:23173094

Mapping QTL for popping expansion volume in popcorn with simple sequence repeat markers.

PubMed

Lu, H-J; Bernardo, R; Ohm, H W

2003-02-01

Popping expansion volume is the most important quality trait in popcorn ( Zea mays L.), but its genetics is not well understood. The objectives of this study were to map quantitative trait loci (QTLs) responsible for popping expansion volume in a popcorn x dent corn cross, and to compare the predicted efficiencies of phenotypic selection, marker-based selection, and marker-assisted selection for popping expansion volume. Of 259 simple sequence repeat (SSR) primer pairs screened, 83 pairs were polymorphic between the H123 (dent corn) and AG19 (popcorn) parental inbreds. Popping test data were obtained for 160 S(1) families developed from the [AG19(H123 x AG19)] BC(1) population. The heritability ( h(2)) for popping expansion volume on an S(1) family mean basis was 0.73. The presence of the gametophyte factor Ga1(s) in popcorn complicates the analysis of popcorn x dent corn crosses. But, from a practical perspective, the linkage between a favorable QTL allele and Ga1(s) in popcorn will lead to selection for the favorable QTL allele. Four QTLs, on chromosomes 1S, 3S, 5S and 5L, jointly explained 45% of the phenotypic variation. Marker-based selection for popping expansion volume would require less time and work than phenotypic selection. But due to the high h(2) of popping expansion volume, marker-based selection was predicted to be only 92% as efficient as phenotypic selection. Marker-assisted selection, which comprises index selection on phenotypic and marker scores, was predicted to be 106% as efficient as phenotypic selection. Overall, our results suggest that phenotypic selection will remain the preferred method for selection in popcorn x dent corn crosses.

Gut Microbiota Markers in Obese Adolescent and Adult Patients: Age-Dependent Differential Patterns.

PubMed

Del Chierico, Federica; Abbatini, Francesca; Russo, Alessandra; Quagliariello, Andrea; Reddel, Sofia; Capoccia, Danila; Caccamo, Romina; Ginanni Corradini, Stefano; Nobili, Valerio; De Peppo, Francesco; Dallapiccola, Bruno; Leonetti, Frida; Silecchia, Gianfranco; Putignani, Lorenza

2018-01-01

Obesity levels, especially in children, have dramatically increased over the last few decades. Recently, several studies highlighted the involvement of gut microbiota in the pathophysiology of obesity. We investigated the composition of gut microbiota in obese adolescents and adults compared to age-matched normal weight (NW) volunteers in order to assemble age- and obesity-related microbiota profiles. The composition of gut microbiota was analyzed by 16S rRNA-based metagenomics. Ecological representations of microbial communities were computed, and univariate, multivariate, and correlation analyses performed on bacterial profiles. The prediction of metagenome functional content from 16S rRNA gene surveys was carried out. Ecological analyses revealed a dissimilarity among the subgroups, and resultant microbiota profiles differed between obese adolescents and adults. Using statistical analyses, we assigned, as microbial markers, Faecalibacterium prausnitzii and Actinomyces to the microbiota of obese adolescents, and Parabacteroides , Rikenellaceae, Bacteroides caccae , Barnesiellaceae, and Oscillospira to the microbiota of NW adolescents. The predicted metabolic profiles resulted different in adolescent groups. Particularly, biosynthesis of primary bile acid and steroid acids, metabolism of fructose, mannose, galactose, butanoate, and pentose phosphate and glycolysis/gluconeogenesis were for the majority associated to obese, while biosynthesis and metabolism of glycan, biosynthesis of secondary bile acid, metabolism of steroid hormone and lipoic acid were associated to NW adolescents. Our study revealed unique features of gut microbiota in terms of ecological patterns, microbial composition and metabolism in obese patients. The assignment of novel obesity bacterial markers may open avenues for the development of patient-tailored treatments dependent on age-related microbiota profiles.

Leptin and insulin growth factor 1: diagnostic markers of the refeeding syndrome and mortality.

PubMed

Elnenaei, Manal O; Alaghband-Zadeh, Jamshid; Sherwood, Roy; Awara, Mahmoud A; Moniz, Caje; le Roux, Carel W

2011-09-01

Refeeding syndrome is difficult to diagnose since the guidelines for identifying those at risk are largely based on subjective clinical parameters and there are no predictive biochemical markers. We examined the suitability of insulin-like growth factor 1 (IGF1) and leptin as markers to identify patients at risk of the refeeding syndrome before initiation of parenteral nutrition (PN). A total of thirty-five consecutive patients referred for commencement of PN were included. Serum leptin and IGF1 were measured before starting PN. Electrolytes, liver and renal function tests were conducted before and daily for 1 week after initiating PN. The primary outcome was a decrease in phosphate 12-36 h after initiating PN. 'Refeeding index' (RI) was defined as leptin × IGF1 divided by 2800 to produce a ratio of 1·0 in patients who are well nourished. RI had better sensitivity (78 %; 95 % CI 40, 97 %) and specificity (78 %; 95 % CI 40, 97 %) with a likelihood ratio of 3·4, at a cut-off value of 0·19 for predicting a ≥ 30 % decrease in phosphate concentration within 12-36 h after starting PN, compared with IGF1 or leptin alone. However, IGF1 was a better predictor of mortality than either leptin or the RI. The present study is the first to derive and test the 'RI', and find that it is a sensitive and specific predictor of the refeeding syndrome in hospitalised patients before starting PN.

Accuracy of Predicted Genomic Breeding Values in Purebred and Crossbred Pigs.

PubMed

Hidalgo, André M; Bastiaansen, John W M; Lopes, Marcos S; Harlizius, Barbara; Groenen, Martien A M; de Koning, Dirk-Jan

2015-05-26

Genomic selection has been widely implemented in dairy cattle breeding when the aim is to improve performance of purebred animals. In pigs, however, the final product is a crossbred animal. This may affect the efficiency of methods that are currently implemented for dairy cattle. Therefore, the objective of this study was to determine the accuracy of predicted breeding values in crossbred pigs using purebred genomic and phenotypic data. A second objective was to compare the predictive ability of SNPs when training is done in either single or multiple populations for four traits: age at first insemination (AFI); total number of piglets born (TNB); litter birth weight (LBW); and litter variation (LVR). We performed marker-based and pedigree-based predictions. Within-population predictions for the four traits ranged from 0.21 to 0.72. Multi-population prediction yielded accuracies ranging from 0.18 to 0.67. Predictions across purebred populations as well as predicting genetic merit of crossbreds from their purebred parental lines for AFI performed poorly (not significantly different from zero). In contrast, accuracies of across-population predictions and accuracies of purebred to crossbred predictions for LBW and LVR ranged from 0.08 to 0.31 and 0.11 to 0.31, respectively. Accuracy for TNB was zero for across-population prediction, whereas for purebred to crossbred prediction it ranged from 0.08 to 0.22. In general, marker-based outperformed pedigree-based prediction across populations and traits. However, in some cases pedigree-based prediction performed similarly or outperformed marker-based prediction. There was predictive ability when purebred populations were used to predict crossbred genetic merit using an additive model in the populations studied. AFI was the only exception, indicating that predictive ability depends largely on the genetic correlation between PB and CB performance, which was 0.31 for AFI. Multi-population prediction was no better than within-population prediction for the purebred validation set. Accuracy of prediction was very trait-dependent. Copyright © 2015 Hidalgo et al.

From genomics to functional markers in the era of next-generation sequencing.

PubMed

Salgotra, R K; Gupta, B B; Stewart, C N

2014-03-01

The availability of complete genome sequences, along with other genomic resources for Arabidopsis, rice, pigeon pea, soybean and other crops, has revolutionized our understanding of the genetic make-up of plants. Next-generation DNA sequencing (NGS) has facilitated single nucleotide polymorphism discovery in plants. Functionally-characterized sequences can be identified and functional markers (FMs) for important traits can be developed at an ever-increasing ease. FMs are derived from sequence polymorphisms found in allelic variants of a functional gene. Linkage disequilibrium-based association mapping and homologous recombinants have been developed for identification of "perfect" markers for their use in crop improvement practices. Compared with many other molecular markers, FMs derived from the functionally characterized sequence genes using NGS techniques and their use provide opportunities to develop high-yielding plant genotypes resistant to various stresses at a fast pace.

Title: Freshwater phytoplankton responses to global warming.

PubMed

Wagner, Heiko; Fanesi, Andrea; Wilhelm, Christian

2016-09-20

Global warming alters species composition and function of freshwater ecosystems. However, the impact of temperature on primary productivity is not sufficiently understood and water quality models need to be improved in order to assess the quantitative and qualitative changes of aquatic communities. On the basis of experimental data, we demonstrate that the commonly used photosynthetic and water chemistry parameters alone are not sufficient for modeling phytoplankton growth under changing temperature regimes. We present some new aspects of the acclimation process with respect to temperature and how contrasting responses may be explained by a more complete physiological knowledge of the energy flow from photons to new biomass. We further suggest including additional bio-markers/traits for algal growth such as carbon allocation patterns to increase the explanatory power of such models. Although carbon allocation patterns are promising and functional cellular traits for growth prediction under different nutrient and light conditions, their predictive power still waits to be tested with respect to temperature. A great challenge for the near future will be the prediction of primary production efficiencies under the global change scenario using a uniform model for phytoplankton assemblages. Copyright © 2016 Elsevier GmbH. All rights reserved.

Functionally Relevant Microsatellite Markers From Chickpea Transcription Factor Genes for Efficient Genotyping Applications and Trait Association Mapping

PubMed Central

Kujur, Alice; Bajaj, Deepak; Saxena, Maneesha S.; Tripathi, Shailesh; Upadhyaya, Hari D.; Gowda, C.L.L.; Singh, Sube; Jain, Mukesh; Tyagi, Akhilesh K.; Parida, Swarup K.

2013-01-01

We developed 1108 transcription factor gene-derived microsatellite (TFGMS) and 161 transcription factor functional domain-associated microsatellite (TFFDMS) markers from 707 TFs of chickpea. The robust amplification efficiency (96.5%) and high intra-specific polymorphic potential (34%) detected by markers suggest their immense utilities in efficient large-scale genotyping applications, including construction of both physical and functional transcript maps and understanding population structure. Candidate gene-based association analysis revealed strong genetic association of TFFDMS markers with three major seed and pod traits. Further, TFGMS markers in the 5′ untranslated regions of TF genes showing differential expression during seed development had higher trait association potential. The significance of TFFDMS markers was demonstrated by correlating their allelic variation with amino acid sequence expansion/contraction in the functional domain and alteration of secondary protein structure encoded by genes. The seed weight-associated markers were validated through traditional bi-parental genetic mapping. The determination of gene-specific linkage disequilibrium (LD) patterns in desi and kabuli based on single nucleotide polymorphism-microsatellite marker haplotypes revealed extended LD decay, enhanced LD resolution and trait association potential of genes. The evolutionary history of a strong seed-size/weight-associated TF based on natural variation and haplotype sharing among desi, kabuli and wild unravelled useful information having implication for seed-size trait evolution during chickpea domestication. PMID:23633531

Tools for outcome prediction in patients with community acquired pneumonia.

PubMed

Khan, Faheem; Owens, Mark B; Restrepo, Marcos; Povoa, Pedro; Martin-Loeches, Ignacio

2017-02-01

Community-acquired pneumonia (CAP) is one of the most common causes of mortality world-wide. The mortality rate of patients with CAP is influenced by the severity of the disease, treatment failure and the requirement for hospitalization and/or intensive care unit (ICU) management, all of which may be predicted by biomarkers and clinical scoring systems. Areas covered: We review the recent literature examining the efficacy of established and newly-developed clinical scores, biological and inflammatory markers such as C-Reactive protein (CRP), procalcitonin (PCT) and Interleukin-6 (IL-6), whether used alone or in conjunction with clinical severity scores to assess the severity of CAP, predict treatment failure, guide acute in-hospital or ICU admission and predict mortality. Expert commentary: The early prediction of treatment failure using clinical scores and biomarkers plays a developing role in improving survival of patients with CAP by identifying high-risk patients requiring hospitalization or ICU admission; and may enable more efficient allocation of resources. However, it is likely that combinations of scoring systems and biomarkers will be of greater use than individual markers. Further larger studies are needed to corroborate the additive value of these markers to clinical prediction scores to provide a safer and more effective assessment tool for clinicians.

Short-term effects of air pollution, markers of endothelial activation, and coagulation to predict major adverse cardiovascular events in patients with acute coronary syndrome: insights from AIRACOS study.

PubMed

Dominguez-Rodriguez, Alberto; Abreu-Gonzalez, Pedro; Rodríguez, Sergio; Avanzas, Pablo; Juarez-Prera, Ruben A

2017-07-01

The aim of this study was to determine whether markers of inflammation and coagulation are associated with short-term particulate matter exposure and predict major adverse cardiovascular events at 360 d in patients with acute coronary syndrome (ACS). We included 307 consecutive patients, and assessed the average concentrations of data on atmospheric pollution in ambient air and meteorological variables from 1 d up to 7 d prior to admission. In patients with ACS, the markers of endothelial activation and coagulation, but not black carbon exposure, are associated with major adverse cardiovascular events at one-year follow-up.

Neuropsychological and socio-occupational functioning in young psychiatric outpatients: a longitudinal investigation.

PubMed

Lee, Rico S C; Hermens, Daniel F; Redoblado-Hodge, M Antoinette; Naismith, Sharon L; Porter, Melanie A; Kaur, Manreena; White, Django; Scott, Elizabeth M; Hickie, Ian B

2013-01-01

Clinical symptoms and neuropsychological deficits are longitudinally associated with functional outcome in chronic psychiatric cohorts. The current study extended these findings to young and early-course psychiatric outpatients, with the aim of identifying cognitive markers that predict later socio-occupational functioning. At baseline, 183 young psychiatric outpatients were assessed. Ninety-three returned for follow-up (M = 21.6 years old; SD = 4.5) with an average re-assessment interval of 21.6 months (SD = 7.0), and primary diagnoses of major depressive disorder (n = 34), bipolar disorder (n = 29), or psychosis (n = 30). The primary outcome measure was cross-validated with various other functional measures and structural equation modelling was used to map out the interrelationships between predictors and later functional outcome. Good socio-occupational functioning at follow-up was associated with better quality of life, less disability, current employment and being in a romantic relationship. The final structural equation model explained 47.5% of the variability in functional outcome at follow-up, with baseline neuropsychological functioning (a composite of memory, working memory and attentional switching) the best independent predictor of later functional outcome. Notably, depressive and negative symptoms were only associated with functioning cross-sectionally. Diagnosis at follow-up was not associated with functional outcome. Neuropsychological functioning was the single best predictor of later socio-occupational outcome among young psychiatric outpatients. Therefore, framing psychiatric disorders along a neuropsychological continuum is likely to be more useful in predicting functional trajectory than traditional symptom-based classification systems. The current findings also have implications for early intervention utilising cognitive remediation approaches.

Low Necroptosis Process Predicts Poor Treatment Outcome of Human Papillomavirus Positive Cervical Cancers by Decreasing Tumor-Associated Macrophages M1 Polarization.

PubMed

Li, Lin; Yu, Song; Zang, Chunyi

2018-01-01

The aim of this study was to assess the functions of the necroptosis process on the prognosis of high-risk human papillomavirus (HR-HPV)-related cervical cancer. PCR and western blotting were used to demonstrate the expression of the necroptosis marker, mixed lineage kinase domain-like protein (MLKL), in whole blood and peripheral blood mononuclears (PBMCs) of 89 cervical cancer patients and 15 healthy volunteers. Necroptosis levels and M1 polarization were determined in tumor co-cultured macrophages. We found that MLKL expressions were significantly increased in cervical cancer patients in both whole blood and PBMC samples compared to the expressions in the healthy controls. Low MLKL expression was significantly associated with decreased survival rate in overall survival and disease-free survival. Co-culture cervical cancer cells decrease the necroptosis process of macrophage, together with the proinflammatory factors (M1 markers) downregulation, and this negative regulation was exacerbated in HPV-positive cases. Necroptosis enhancer RIPK3 overexpression showed reversed regulation of these M1 markers, suggesting that co-culture cervical cancer cells decrease the macrophage M1 polarization partly through necroptosis downregulation. Our study revealed that necroptosis process could be a relevant marker for the determination of the prognosis in cervical cancer patients, which might be because of its role in regulating macrophage polarization. © 2018 S. Karger AG, Basel.

The expression ratio of Map7/B2M is prognostic for survival in patients with stage II colon cancer.

PubMed

Blum, Craig; Graham, Amanda; Yousefzadeh, Matt; Shrout, Jessica; Benjamin, Katie; Krishna, Murli; Hoda, Raza; Hoda, Rana; Cole, David J; Garrett-Mayer, Elizabeth; Reed, Carolyn; Wallace, Michael; Mitas, Michael

2008-09-01

Colorectal cancer (CRC) is the second most frequent cause of cancer-related death in the United States. To determine whether certain molecular markers might be prognostic for survival, we measured by quantitative real-time RT-PCR the expression levels of 15 previously studied genes that are known to be up-regulated or down-regulated in the progression of epithelial cancers. The tumor samples were extracted from formalin-fixed paraffin-embedded primary tissues derived from patients with Stage II CRC who developed disease recurrence within two years (n=10), or were disease-free for at least 4 years (n=12). We were able to determine, by AUC curve analysis, that the ratio of microtubule associated protein 7 (Map7)/B2M was predictive of outcome in our sample set. Further, using Kaplan-Meier survival analysis, we observed significantly different curves as a function of marker positivity for the Map7/B2M (p=0.0001; HR=11) expression ratio. This suggests that the expression ratio of Map7/B2M may serve as a valuable prognostic marker in patients with Stage II colon cancer, and potentially guide therapeutic decision making.

The expression ratio of Map7/B2M is prognostic for survival in patients with stage II colon cancer

PubMed Central

BLUM, CRAIG; GRAHAM, AMANDA; YOUSEFZADEH, MATT; SHROUT, JESSICA; BENJAMIN, KATIE; KRISHNA, MURLI; HODA, RAZA; HODA, RANA; COLE, DAVID J.; GARRETT-MAYER, ELIZABETH; REED, CAROLYN; WALLACE, MICHAEL; MITAS, MICHAEL

2012-01-01

Colorectal cancer (CRC) is the second most frequent cause of cancer-related death in the United States. To determine whether certain molecular markers might be prognostic for survival, we measured by quantitative real-time RT-PCR the expression levels of 15 previously studied genes that are known to be up-regulated or down-regulated in the progression of epithelial cancers. The tumor samples were extracted from formalin-fixed paraffin-embedded primary tissues derived from patients with Stage II CRC who developed disease recurrence within two years (n=10), or were disease-free for at least 4 years (n=12). We were able to determine, by AUC curve analysis, that the ratio of microtubule associated protein 7 (Map7)/B2M was predictive of outcome in our sample set. Further, using Kaplan-Meier survival analysis, we observed significantly different curves as a function of marker positivity for the Map7/B2M (p=0.0001; HR=11) expression ratio. This suggests that the expression ratio of Map7/B2M may serve as a valuable prognostic marker in patients with Stage II colon cancer, and potentially guide therapeutic decision making. PMID:18695889

Salivary biomarkers of neural hypervigilance in trauma-exposed women.

PubMed

Yoon, Seungyeon A; Weierich, Mariann R

2016-01-01

More than half of all adults will be exposed to a traumatic event at some point in their lives, yet we do not yet have reliable biomarkers to help predict who experiences trauma-related symptoms in response to exposure. We tested the utility of salivary cortisol and salivary alpha amylase as markers of (1) neural reactivity to negative affective information and (2) neural hypervigilance in the absence of threat. 20 women (mean age 23.6 +/- 5.8 years) with a history of trauma exposure. Salivary cortisol and alpha amylase reactivity were measured in response to a trauma reminder during a clinical interview. Neural reactivity to novel and familiar affective scenes was measured in a later session using functional magnetic resonance imaging. Salivary alpha amylase, but not cortisol, increased in response to the trauma reminder. Salivary alpha amylase reactivity was associated with neural reactivity in the salience network in response to novel negative scenes and neural hypervigilance as indexed by reactivity to novel neutral scenes. Salivary alpha amylase might serve as a more reliable marker of trauma-related reactivity to negative affective information, and also as a marker of hypervigilance in the absence of threatening information. Copyright © 2015 Elsevier Ltd. All rights reserved.

Predictors of preterm birth in patients with mild systemic lupus erythematosus.

PubMed

Clowse, Megan E B; Wallace, Daniel J; Weisman, Michael; James, Andra; Criscione-Schreiber, Lisa G; Pisetsky, David S

2013-09-01

While increased disease activity is the best predictor of preterm birth in women with systemic lupus erythematosus (SLE), even women with low disease activity are at increased risk of this complication. Biomarkers that would identify at-risk pregnancies could allow interventions to prevent preterm birth. Measures of SLE activity, inflammation, placental health and renal function between 20 and 28 weeks gestation (mid-gestation) were correlated to preterm birth and gestational age at delivery in a prospective cohort of pregnant women with SLE. Of the 40 pregnancies in 39 women, all with mild-moderate SLE disease, 9 (23.7%) of the 38 live births were delivered preterm. Low C4 was the only marker of SLE activity associated with younger gestational age at delivery. Elevated ferritin and lower oestradiol correlated with younger gestational age at delivery. Renal function remained normal during all pregnancies at mid-gestation and did not correlate with preterm birth. Higher serum uric acid, however, correlated with younger gestational age at delivery. In women with SLE with mild-moderate disease activity, ferritin, oestradiol and uric acid levels at mid-gestation may predict preterm birth. These markers may prove to be clinically useful in identifying pregnancies at particularly high risk for adverse outcomes.

Disgust elevates core body temperature and up-regulates certain oral immune markers.

PubMed

Stevenson, Richard J; Hodgson, Deborah; Oaten, Megan J; Moussavi, Mahta; Langberg, Rebekah; Case, Trevor I; Barouei, Javad

2012-10-01

Recent findings suggest that disgust can activate particular aspects of the immune system. In this study we examine whether disgust can also elevate core body temperature (BT), a further feature of an immune response to disease. In addition, we also examined whether food based disgust--a core eliciting stimulus--may be a more potent immune stimulus than non-food based disgust. Healthy males were randomly assigned to view one of four sets of images--food disgust, non-food disgust, food control and negative emotion control. Measures of BT, salivary immune and related markers, and self-report data, were collected before, and at two time points after image viewing. Disgust elevated BT relative to the negative emotion control condition, as did food images. Different mechanisms appeared to account for these effects on BT, with higher initial levels of Tumor Necrosis Factor alpha (TNF-a) and disgust, predictive of BT increases in the disgust conditions. Disgust also increased TNF-a, and albumin levels, relative to the control conditions. Type of disgust exerted little effect. These findings further support the idea that disgust impacts upon immune function, and that disgust serves primarily a disease avoidance function. Copyright © 2012 Elsevier Ltd. All rights reserved.

Early Markers of Autism Spectrum Disorders in Infants and Toddlers Prospectively Identified in the Social Attention and Communication Study

ERIC Educational Resources Information Center

Barbaro, Josephine; Dissanayake, Cheryl

2013-01-01

The Social Attention and Communication Study involved the successful implementation of developmental surveillance of the early markers of autism spectrum disorders in a community-based setting. The objective in the current study was to determine the most discriminating and predictive markers of autism spectrum disorders used in the Social…

BBD Reference Set Application: Jeffery Marks-Duke (2015) — EDRN Public Portal

Cancer.gov

We propose a pre-validation study for markers that could predict the likelihood of invasive breast cancer following a tissue diagnosis of benign breast pathology (any diagnosis that is less severe than carcinoma in situ). The study is designed to test the utility of a series of markers that were shown to have some predictive value by immunohistochemical staining in other cohorts. These markers include the proliferation associated antigen KI-67, EZH2, PTGS2 (COX2), ALDH1, CDKN2A (p16), HYAL1, MMP1, CEACAM6, and TP53. In addition, we propose analyzing two markers that comprise part of the DCIS Oncotype panel, GSTM1 and progesterone receptor (PR). The study will occur in two EDRN clinical validation center (CVC) laboratories, namely Duke and University of Kansas, and utilize specimens from Northwestern University and Geisinger Health System that have been identified and are either already sectioned or waiting to be sectioned. Results will be scored and returned to the DMCC to determine whether any of the markers or combinations of these markers may have sufficient value to proceed to a second stage validation with large numbers of samples from Geisenger Health Systems and the Henry Ford Hospital.

Disorganized Symptoms Predicted Worse Functioning Outcome in Schizophrenia Patients with Established Illness.

PubMed

Ortiz, Bruno Bertolucci; Gadelha, Ary; Higuchi, Cinthia Hiroko; Noto, Cristiano; Medeiros, Daiane; Pitta, José Cássio do Nascimento; de Araújo Filho, Gerardo Maria; Hallak, Jaime Eduardo Cecílio; Bressan, Rodrigo Affonseca

Most patients with schizophrenia will have subsequent relapses of the disorder, with continuous impairments in functioning. However, evidence is lacking on how symptoms influence functioning at different phases of the disease. This study aims to investigate the relationship between symptom dimensions and functioning at different phases: acute exacerbation, nonremission and remission. Patients with schizophrenia were grouped into acutely ill (n=89), not remitted (n=89), and remitted (n=69). Three exploratory stepwise linear regression analyses were performed for each phase of schizophrenia, in which the five PANSS factors and demographic variables were entered as the independent variables and the total Global Assessment of Functioning Scale (GAF) score was entered as the dependent variable. An additional exploratory stepwise logistic regression analysis was performed to predict subsequent remission at discharge in the inpatient population. The Disorganized factor was the most significant predictor for acutely ill patients (p<0.001), while the Hostility factor was the most significant for not-remitted patients and the Negative factor was the most significant for remitted patients (p=0.001 and p<0.001, respectively). In the logistic regression, the Disorganized factor score presented a significant negative association with remission (p=0.007). Higher disorganization symptoms showed the greatest impact in functioning at acute phase, and prevented patients from achieving remission, suggesting it may be a marker of symptom severity and worse outcome in schizophrenia.

Quality of Life and School Absenteeism in Children With Chronic Illness.

PubMed

Emerson, Natacha D; Distelberg, Brian; Morrell, Holly E R; Williams-Reade, Jackie; Tapanes, Daniel; Montgomery, Susanne

2016-08-01

Children and adolescents with a chronic illness (CI) tend to demonstrate diminished physical and social functioning, which contribute to school attendance issues. We investigated the role of social and physical functioning in reducing school absenteeism in children participating in Mastering Each New Direction (MEND), a family-based psychosocial intervention for youths with CI. Forty-eight children and adolescents with a CI (70.8% female, M age = 14.922, SD = 2.143) and their parent(s) completed a health-related quality of life (HRQOL) measure pre- and postintervention. Using multiple mediation, we examined whether parent- and child-rated physical and social HRQOL mediated the relationship between school attendance before and after MEND. Once the mediational model was not supported, we investigated whether HRQOL moderated the relationship between missed school days pre- and postintervention. Neither physical nor social functioning mediated or moderated the relationship between missed school days pre- and postintervention. Instead, higher parent-rated physical functioning directly predicted decreased number of missed school days, while lower parent-rated social and child-rated physical functioning predicted increased missed school days. Parent-perceived HRQOL may have a direct effect on health-related behaviors such as school attendance. Future research should determine whether gains in parent-rated QOL are maintained in the long term and whether these continue to impact markers of functional well-being. © The Author(s) 2015.

De novo RNA-seq and functional annotation of Ornithonyssus bacoti.

PubMed

Niu, DongLing; Wang, RuiLing; Zhao, YaE; Yang, Rui; Hu, Li

2018-06-01

Ornithonyssus bacoti (Hirst) (Acari: Macronyssidae) is a vector and reservoir of pathogens causing serious infectious diseases, such as epidemic hemorrhagic fever, endemic typhus, tularemia, and leptospirosis. Its genome and transcriptome data are lacking in public databases. In this study, total RNA was extracted from live O. bacoti to conduct RNA-seq, functional annotation, coding domain sequence (CDS) prediction and simple sequence repeats (SSRs) detection. The results showed that 65.8 million clean reads were generated and assembled into 72,185 unigenes, of which 49.4% were annotated by seven functional databases. 23,121 unigenes were annotated and assigned to 457 species by non-redundant protein sequence database. The BLAST top-two hit species were Metaseiulus occidentalis and Ixodes scapularis. The procedure detected 12,426 SSRs, of which tri- and di-nucleotides were the most abundant types and the representative motifs were AAT/ATT and AC/GT. 26,936 CDS were predicted with a mean length of 711 bp. 87 unigenes of 30 functional genes, which are usually involved in stress responses, drug resistance, movement, metabolism and allergy, were further identified by bioinformatics methods. The unigenes putatively encoding cytochrome P450 proteins were further analyzed phylogenetically. In conclusion, this study completed the RNA-seq and functional annotation of O. bacoti successfully, which provides reliable molecular data for its future studies of gene function and molecular markers.

‘Alzheimer’s Progression Score’: Development of a Biomarker Summary Outcome for AD Prevention Trials

PubMed Central

Leoutsakos, J.-M.; Gross, A.L.; Jones, R.N.; Albert, M.S.; Breitner, J.C.S.

2017-01-01

BACKGROUND Alzheimer’s disease (AD) prevention research requires methods for measurement of disease progression not yet revealed by symptoms. Preferably, such measurement should encompass multiple disease markers. OBJECTIVES Evaluate an item response theory (IRT) model-based latent variable Alzheimer Progression Score (APS) that uses multi-modal disease markers to estimate pre-clinical disease progression. DESIGN Estimate APS scores in the BIOCARD observational study, and in the parallel PREVENT-AD Cohort and its sister INTREPAD placebo-controlled prevention trial. Use BIOCARD data to evaluate whether baseline and early APS trajectory predict later progression to MCI/dementia. Similarly, use longitudinal PREVENT-AD data to assess test measurement invariance over time. Further, assess portability of the PREVENT-AD IRT model to baseline INTREPAD data, and explore model changes when CSF markers are added or withdrawn. SETTING BIOCARD was established in 1995 and participants were followed up to 20 years in Baltimore, USA. The PREVENT-AD and INTREPAD trial cohorts were established between 2011–2015 in Montreal, Canada, using nearly identical entry criteria to enroll high-risk cognitively normal persons aged 60+ then followed for several years. PARTICIPANTS 349 cognitively normal, primarily middle-aged participants in BIOCARD, 125 high-risk participants aged 60+ in PREVENT-AD, and 217 similar subjects in INTREPAD. 106 INTREPAD participants donated up to four serial CSF samples. MEASUREMENTS Global cognitive assessment and multiple structural, functional, and diffusion MRI metrics, sensori-neural tests, and CSF concentrations of tau, Aβ42 and their ratio. RESULTS Both baseline values and early slope of APS scores in BIOCARD predicted later progression to MCI or AD. Presence of CSF variables strongly improved such prediction. A similarly derived APS in PREVENT-AD showed measurement invariance over time and portability to the parallel INTREPAD sample. CONCLUSIONS An IRT-based APS can summarize multimodal information to provide a longitudinal measure of pre-clinical AD progression, and holds promise as an outcome for AD prevention trials. PMID:29034223

'Alzheimer's Progression Score': Development of a Biomarker Summary Outcome for AD Prevention Trials.

PubMed

Leoutsakos, J-M; Gross, A L; Jones, R N; Albert, M S; Breitner, J C S

2016-01-01

Alzheimer's disease (AD) prevention research requires methods for measurement of disease progression not yet revealed by symptoms. Preferably, such measurement should encompass multiple disease markers. Evaluate an item response theory (IRT) model-based latent variable Alzheimer Progression Score (APS) that uses multi-modal disease markers to estimate pre-clinical disease progression. Estimate APS scores in the BIOCARD observational study, and in the parallel PREVENT-AD Cohort and its sister INTREPAD placebo-controlled prevention trial. Use BIOCARD data to evaluate whether baseline and early APS trajectory predict later progression to MCI/dementia. Similarly, use longitudinal PREVENT-AD data to assess test measurement invariance over time. Further, assess portability of the PREVENT-AD IRT model to baseline INTREPAD data, and explore model changes when CSF markers are added or withdrawn. BIOCARD was established in 1995 and participants were followed up to 20 years in Baltimore, USA. The PREVENT-AD and INTREPAD trial cohorts were established between 2011-2015 in Montreal, Canada, using nearly identical entry criteria to enroll high-risk cognitively normal persons aged 60+ then followed for several years. 349 cognitively normal, primarily middle-aged participants in BIOCARD, 125 high-risk participants aged 60+ in PREVENT-AD, and 217 similar subjects in INTREPAD. 106 INTREPAD participants donated up to four serial CSF samples. Global cognitive assessment and multiple structural, functional, and diffusion MRI metrics, sensori-neural tests, and CSF concentrations of tau, Aβ42 and their ratio. Both baseline values and early slope of APS scores in BIOCARD predicted later progression to MCI or AD. Presence of CSF variables strongly improved such prediction. A similarly derived APS in PREVENT-AD showed measurement invariance over time and portability to the parallel INTREPAD sample. An IRT-based APS can summarize multimodal information to provide a longitudinal measure of pre-clinical AD progression, and holds promise as an outcome for AD prevention trials.

Prognostic implications of surrogate markers of atherosclerosis in low to intermediate risk patients with Type 2 Diabetes

PubMed Central

2012-01-01

Background Type 2 diabetes mellitus (T2DM) patients are at increased risk of developing cardiovascular events. Unfortunately traditional risk assessment scores, including the Framingham Risk Score (FRS), have only modest accuracy in cardiovascular risk prediction in these patients. Methods We sought to determine the prognostic values of different non-invasive markers of atherosclerosis, including brachial artery endothelial function, carotid artery atheroma burden, ankle-brachial index, arterial stiffness and computed tomography coronary artery calcium score (CACS) in 151 T2DM Chinese patients that were identified low-intermediate risk from the FRS recalibrated for Chinese (<20% risk in 10 years). Patients were prospectively followed-up and presence of atherosclerotic events documented for a mean duration of 61 ± 16 months. Results A total of 17 atherosclerotic events in 16 patients (11%) occurred during the follow-up period. The mean FRS of the study population was 5.0 ± 4.6% and area under curve (AUC) from receiver operating characteristic curve analysis for prediction of atherosclerotic events was 0.59 ± 0.07 (P = 0.21). Among different vascular assessments, CACS > 40 had the best prognostic value (AUC 0.81 ± 0.06, P < 0.01) and offered significantly better accuracy in prediction compared with FRS (P = 0.038 for AUC comparisons). Combination of FRS with CACS or other surrogate vascular markers did not further improve the prognostic values over CACS alone. Multivariate Cox regression analysis identified CACS > 40 as an independent predictor of atherosclerotic events in T2DM patients (Hazards Ratio 27.11, 95% Confidence Interval 3.36-218.81, P = 0.002). Conclusions In T2DM patients identified as low-intermediate risk by the FRS, a raised CACS > 40 was an independent predictor for atherosclerotic events. PMID:22900680

Enhanced sensitivity of CpG island search and primer design based on predicted CpG island position.

PubMed

Park, Hyun-Chul; Ahn, Eu-Ree; Jung, Ju Yeon; Park, Ji-Hye; Lee, Jee Won; Lim, Si-Keun; Kim, Won

2018-05-01

DNA methylation has important biological roles, such as gene expression regulation, as well as practical applications in forensics, such as in body fluid identification and age estimation. DNA methylation often occurs in the CpG site, and methylation within the CpG islands affects various cellular functions and is related to tissue-specific identification. Several programs have been developed to identify CpG islands; however, the size, location, and number of predicted CpG islands are not identical due to different search algorithms. In addition, they only provide structural information for predicted CpG islands without experimental information, such as primer design. We developed an analysis pipeline package, CpGPNP, to integrate CpG island prediction and primer design. CpGPNP predicts CpG islands more accurately and sensitively than other programs, and designs primers easily based on the predicted CpG island locations. The primer design function included standard, bisulfite, and methylation-specific PCR to identify the methylation of particular CpG sites. In this study, we performed CpG island prediction on all chromosomes and compared CpG island search performance of CpGPNP with other CpG island prediction programs. In addition, we compared the position of primers designed for a specific region within the predicted CpG island using other bisulfite PCR primer programs. The primers designed by CpGPNP were used to experimentally verify the amplification of the target region of markers for body fluid identification and age estimation. CpGPNP is freely available at http://forensicdna.kr/cpgpnp/. Copyright © 2018 Elsevier B.V. All rights reserved.

Fluctuations in [11C]SB207145 PET Binding Associated with Change in Threat-Related Amygdala Reactivity in Humans

PubMed Central

Fisher, Patrick MacDonald; Haahr, Mette Ewers; Jensen, Christian Gaden; Frokjaer, Vibe Gedsoe; Siebner, Hartwig Roman; Knudsen, Gitte Moos

2015-01-01

Serotonin critically affects the neural processing of emotionally salient stimuli, including indices of threat; however, how alterations in serotonin signaling contribute to changes in brain function is not well understood. Recently, we showed in a placebo-controlled study of 32 healthy males that brain serotonin 4 receptor (5-HT4) binding, assessed with [11C]SB207145 PET, was sensitive to a 3-week intervention with the selective serotonin reuptake inhibitor fluoxetine, supporting it as an in vivo model for fluctuations in central serotonin levels. Participants also underwent functional magnetic resonance imaging while performing a gender discrimination task of fearful, angry, and neutral faces. This offered a unique opportunity to evaluate whether individual fluctuations in central serotonin levels, indexed by change in [11C]SB207145 binding, predicted changes in threat-related reactivity (ie, fear and angry vs neutral faces) within a corticolimbic circuit including the amygdala and medial prefrontal and anterior cingulate cortex. We observed a significant association such that decreased brain-wide [11C]SB207145 binding (ie, increased brain serotonin levels) was associated with lower threat-related amygdala reactivity, whereas intervention group status did not predict change in corticolimbic reactivity. This suggests that in the healthy brain, interindividual responses to pharmacologically induced and spontaneously occurring fluctuations in [11C]SB207145 binding, a putative marker of brain serotonin levels, affect amygdala reactivity to threat. Our finding also supports that change in brain [11C]SB207145 binding may be a relevant marker for evaluating neurobiological mechanisms underlying sensitivity to threat and serotonin signaling. PMID:25560201

High expression of AFAP1-AS1 is associated with poor survival and short-term recurrence in pancreatic ductal adenocarcinoma.

PubMed

Ye, Yibiao; Chen, Jie; Zhou, Yu; Fu, Zhiqiang; Zhou, Quanbo; Wang, YingXue; Gao, Wenchao; Zheng, ShangYou; Zhao, Xiaohui; Chen, Tao; Chen, Rufu

2015-04-30

Pancreatic ductal adenocarcinoma (PDAC) is still a lethal malignancy. Long noncoding RNAs (lncRNAs) have been shown to play a critical role in cancer development and progression. Here we identified overexpression of the lncRNA AFAP1-AS1 in PDAC patients and evaluated its prognostic and functional relevance. The global lncRNA expression profile in PDAC was measured by lncRNA microarray. Expression of AFAP1-AS1 was evaluated by reverse-transcriptase quantitative polymerase chain reaction (RT-qPCR) in 90 PDAC tissue samples and adjacent normal tissues. The impact of AFAP1-AS1 expression on cell proliferation, migration, and invasion were evaluated in vitro using knockdown and ectopic expression strategies. Microarray analysis revealed that up-regulation of AFAP1-AS1 expression in PDAC tissues compared with normal adjacent tissues, which was confirmed by RT-qPCR in 69/90 cases (76.7%). Its overexpression was associated with lymph node metastasis, perineural invasion, and poor survival. When using AFAP1-AS1 as a prognostic marker, the areas under ROC curves were 0.8669 and 0.9370 for predicting tumor progression within 6 months and 1 year, respectively. In vitro functional experiments involving knockdown of AFAP1-AS1 resulted in attenuated PDAC cell proliferation, migration, and invasion. Ectopic expression of AFAP1-AS1 promoted cell proliferation, migration, and invasion. AFAP1-AS1 is a potential novel prognostic marker to predict the clinical outcome of PDAC patients after surgery and may be a rational target for therapy.

Respiration Traits as Novel Markers for Plant Robustness Under the Threat of Climate Change: A Protocol for Validation.

PubMed

Arnholdt-Schmitt, Birgit

2017-01-01

Respiration traits allow calculating temperature-dependent carbon use efficiency and prediction of growth rates. This protocol aims (1) to enable validation of respiration traits as non-DNA biomarkers for breeding on robust plants in support of sustainable and healthy plant production; (2) to provide an efficient, novel way to identify and predict functionality of DNA-based markers (genes, polymorphisms, edited genes, transgenes, genomes, and hologenomes), and (3) to directly help farmers select robust material appropriate for a specified region. The protocol is based on applying isothermal calorespirometry and consists of four steps: plant tissue preparation, calorespirometry measurements, data processing, and final validation through massive field-based data.The methodology can serve selection and improvement for a wide range of crops. Several of them are currently being tested in the author's lab. Among them are important cereals, such as wheat, barley, and rye, and diverse vegetables. However, it is critical that the protocol for measuring respiration traits be well adjusted to the plant species by considering deep knowledge on the specific physiology and functional cell biology behind the final target trait for production. Here, Daucus carota L. is chosen as an advanced example to demonstrate critical species-specific steps for protocol development. Carrot is an important global vegetable that is grown worldwide and in all climate regions (moderate, subtropical, and tropical). Recently, this species is also used in my lab as a model for studies on alternative oxidase (AOX) gene diversity and evolutionary dynamics in interaction with endophytes.

Value of 18F-FDG PET/CT Combined With Tumor Markers in the Evaluation of Ascites.

PubMed

Han, Na; Sun, Xun; Qin, Chunxia; Hassan Bakari, Khamis; Wu, Zhijian; Zhang, Yongxue; Lan, Xiaoli

2018-05-01

The purpose of this study is to investigate the value of 18 F-FDG PET/CT combined with assessment of tumor markers in serum or ascites for the diagnosing and determining the prognosis of benign and malignant ascites. Patients with ascites of unknown cause who underwent evaluation with FDG PET/CT were included in this retrospective study. The maximum standardized uptake value (SUV max ) and levels of the tumor markers carbohydrate antigen-125 (CA-125) and carcinoembryonic antigen (CEA) in serum and ascites were recorded. The diagnostic values of FDG PET/CT, CEA and CA-125 levels in serum or ascites, and the combination of imaging plus tumor marker assessment were evaluated. Factors that were predictive of survival were also analyzed. A total of 177 patients were included. Malignant ascites was eventually diagnosed in 104 patients, and benign ascites was diagnosed in the remaining 73 patients. With the use of FDG PET/CT, 44 patients (42.3%) were found to have primary tumors. The sensitivity, specificity, and accuracy of FDG PET/CT were 92.3%, 83.6%, and 88.7%, respectively. CA-125 levels in serum and ascites showed much better sensitivity than did CEA levels, but they showed significantly lower specificity. If the combination of tumor markers and FDG PET/CT was analyzed, the sensitivity, specificity, and accuracy of tumor markers in serum were 96.6%, 78.1%, and 88.7%, and those of tumor markers in ascites were 97.7%, 80.0%, and 90.4%, respectively. Sex may be an important factor affecting survival time (hazard ratio, 0.471; p = 0.004), but age, CEA level, and FDG PET/CT findings could not predict survival. FDG PET/CT combined with assessment of tumor markers, especially CEA, increased the efficacy of diagnosis of ascites of unknown causes. Male sex conferred a poorer prognosis, whereas age, CEA level, and FDG uptake had no predictive significance in patients with malignant ascites.

Predictive value of cell-surface markers in infections in critically ill patients: protocol for an observational study (ImmuNe FailurE in Critical Therapy (INFECT) Study)

PubMed Central

Shankar-Hari, Manu; Weir, Christopher J; Rennie, Jillian; Antonelli, Jean; Rossi, Adriano G; Warner, Noel; Keenan, Jim; Wang, Alice; Brown, K Alun; Lewis, Sion; Mare, Tracey; Simpson, A John; Hulme, Gillian; Dimmick, Ian; Walsh, Timothy S

2016-01-01

Introduction Critically ill patients are at high risk of nosocomial infections, with between 20% and 40% of patients admitted to the intensive care unit (ICU) acquiring infections. These infections result in increased antibiotic use, and are associated with morbidity and mortality. Although critical illness is classically associated with hyperinflammation, the high rates of nosocomial infection argue for an importance of effect of impaired immunity. Our group recently demonstrated that a combination of 3 measures of immune cell function (namely neutrophil CD88, monocyte HLA-DR and % regulatory T cells) identified a patient population with a 2.4–5-fold greater risk for susceptibility to nosocomial infections. Methods and analysis This is a prospective, observational study to determine whether previously identified markers of susceptibility to nosocomial infection can be validated in a multicentre population, as well as testing several novel markers which may improve the risk of nosocomial infection prediction. Blood samples from critically ill patients (those admitted to the ICU for at least 48 hours and requiring mechanical ventilation alone or support of 2 or more organ systems) are taken and undergo whole blood staining for a range of immune cell surface markers. These samples undergo analysis on a standardised flow cytometry platform. Patients are followed up to determine whether they develop nosocomial infection. Infections need to meet strict prespecified criteria based on international guidelines; where these criteria are not met, an adjudication panel of experienced intensivists is asked to rule on the presence of infection. Secondary outcomes will be death from severe infection (sepsis) and change in organ failure. Ethics and dissemination Ethical approval including the involvement of adults lacking capacity has been obtained from respective English and Scottish Ethics Committees. Results will be disseminated through presentations at scientific meetings and publications in peer-reviewed journals. Trial registration number NCT02186522; Pre-results. PMID:27431901

"Anti-Mullerian Hormone: Marker for Ovarian Response in Controlled Ovarian Stimulation for IVF Patients": A First Pilot Study in the Indian Population.

PubMed

Singh, Neeta; Malik, Ekta; Banerjee, Ayan; Chosdol, Kunzang; Sreenivas, V; Mittal, Suneeta

2013-08-01

To measure the levels of early follicular phase Anti-Mullerian hormone (AMH) in Indian patients of IVF and to evaluate the AMH as a predictive marker of ovarian response in assisted reproductive technology outcome. Sixty women (age 25-40 years) selected for in vitro fertilization treatment were included in this study. Analysis of day-2 serum samples was done for the AMH, FSH, Inhibin B, and LH by ELISA kit methods. USG was done for the antral follicle count (AFC) and oocytes' retrieval. Hormone parameters were compared and correlated with the oocytes' retrieval count and the AFC. The discriminant analysis was done to compare relevance of different parameters for predicting ovarian response. The Anti-Mullerian hormone showed a significant correlation with the oocytes' retrieval after ovulation induction for IVF (r = 0.648, p < 0.0001) and no correlation was seen with serum FSH, LH, and Inhibin. Serum AMH levels show 80 % sensitivity and 80 % specificity in predicting poor ovarian response. There is a significant correlation between day-2 serum AMH levels and the oocytes' retrieval count in women undergoing ovulation induction for IVF, and the AMH is a good marker as the negative predictive values for the success of ART. There is no correlation found between other hormonal ovarian reserve markers and the oocytes' retrieval count.

Predicting impending death: inconsistency in speed is a selective and early marker.

PubMed

Macdonald, Stuart W S; Hultsch, David F; Dixon, Roger A

2008-09-01

Among older adults, deficits in both level and variability of speeded performance are linked to neurological impairment. This study examined whether and when speed (rate), speed (inconsistency), and traditional accuracy-based markers of cognitive performance foreshadow terminal decline and impending death. Victoria Longitudinal Study data spanning 12 years (5 waves) of measurement were assembled for 707 adults aged 59 to 95 years. Whereas 442 survivors completed all waves and relevant measures, 265 decedents participated on at least 1 occasion and subsequently died. Four main results were observed. First, Cox regressions evaluating the 3 cognitive predictors of mortality replicated previous results for cognitive accuracy predictors. Second, level (rate) of speeded performance predicted survival independent of demographic indicators, cardiovascular health, and cognitive performance level. Third, inconsistency in speed predicted survival independent of all influences combined. Fourth, follow-up random-effects models revealed increases in inconsistency in speed per year closer to death, with advancing age further moderating the accelerated growth. Hierarchical prediction patterns support the view that inconsistency in speed is an early behavioral marker of neurological dysfunction associated with impending death. (c) 2008 APA, all rights reserved

Predicting Impending Death: Inconsistency in Speed is a Selective and Early Marker

PubMed Central

MacDonald, Stuart W.S.; Hultsch, David F.; Dixon, Roger A.

2008-01-01

Among older adults, deficits in both level and variability of speeded performance are linked to neurological impairment. This study examined whether and when speed (rate), speed (inconsistency), and traditional accuracy-based markers of cognitive performance foreshadow terminal decline and impending death. Victoria Longitudinal Study data spanning 12 years (5 waves) of measurement were assembled for 707 adults aged 59 to 95 years. Whereas 442 survivors completed all waves and relevant measures, 265 decedents participated on at least one occasion and subsequently died. Four main results were observed. First, Cox regressions evaluating the three cognitive predictors of mortality replicated previous results for cognitive accuracy predictors. Second, level (rate) of speeded performance predicted survival independent of demographic indicators, cardiovascular health, and cognitive performance level. Third, inconsistency in speed predicted survival independent of all influences combined. Fourth, follow-up random-effects models revealed increases in inconsistency in speed per year closer to death, with advancing age further moderating the accelerated growth. Hierarchical prediction patterns support the view that inconsistency in speed is an early behavioral marker of neurological dysfunction associated with impending death. PMID:18808249

Individualization of controlled ovarian stimulation in vitro fertilization using ovarian reserve markers.

PubMed

Grisendi, Valentina; La Marca, Antonio

2017-06-01

In assisted reproduction technologies (ART) the controlled ovarian stimulation (COS) therapy is the starting point from which a good oocytes retrieval depends. Treatment individualization is based on ovarian response prediction, which largely depends on a woman's ovarian reserve. Anti-Müllerian hormone (AMH) and antral follicle count (AFC) are considered the most accurate and reliable markers of ovarian reserve. A literature search was carried out for studies that addressed the ability of AMH and AFC to predict poor and/or excessive ovarian response in IVF cycles. According to the predicted response to ovarian stimulation (poor- normal- or high-response) is today possible not only to personalize pre-treatment counseling with the couple, but also to individualize the ovarian stimulation protocol, choosing among GnRH-agonists or antagonists for endogenous follicle-stimulating hormone (FSH) suppression and formulating the FSH starting dose most adequate for the single patients. In this review we discuss how to choose the best COS therapy for the single patient, on the basis of the markers-guided ovarian response prediction.

Lung function and airway obstruction: associations with circulating markers of cardiac function and incident heart failure in older men—the British Regional Heart Study

PubMed Central

Wannamethee, S Goya; Shaper, A Gerald; Papacosta, Olia; Lennon, Lucy; Welsh, Paul; Whincup, Peter H

2016-01-01

Aims The association between lung function and cardiac markers and heart failure (HF) has been little studied in the general older population. We have examined the association between lung function and airway obstruction with cardiac markers N-terminal pro-brain natriuretic peptide (NT-proBNP) and cardiac troponin T (cTnT) and risk of incident HF in older men. Methods and results Prospective study of 3242 men aged 60–79 years without prevalent HF or myocardial infarction followed up for an average period of 13 years, in whom 211 incident HF cases occurred. Incident HF was examined in relation to % predicted FEV1 and FVC. The Global Initiative on Obstructive Lung Diseases spirometry criteria were used to define airway obstruction. Reduced FEV1, but not FVC in the normal range, was significantly associated with increased risk of HF after adjustment for established HF risk factors including inflammation. The adjusted HRs comparing men in the 6–24th percentile with the highest quartile were 1.91 (1.24 to 2.94) and 1.30 (0.86 to 1.96) for FEV1 and FVC, respectively. FEV1 and FVC were inversely associated with NT-proBNP and cTnT, although the association between FEV1 and incident HF remained after adjustment for NT-proBNP and cTnT. Compared with normal subjects (FEV1/FVC ≥0.70 and FVC≥80%), moderate or severe (FEV1/FVC <0.70 and FEV1 <80%) airflow obstruction was independently associated with HF ((adjusted relative risk 1.59 (1.08 to 2.33)). Airflow restriction (FEV1/FVC ≥0.70 and FVC <80%) was not independently associated with HF. Conclusions Reduced FEV1 reflecting airflow obstruction is associated with cardiac dysfunction and increased risk of incident HF in older men. PMID:26811343

Understanding the Mysterious M2 Macrophage through Activation Markers and Effector Mechanisms

PubMed Central

Rőszer, Tamás

2015-01-01

The alternatively activated or M2 macrophages are immune cells with high phenotypic heterogeneity and are governing functions at the interface of immunity, tissue homeostasis, metabolism, and endocrine signaling. Today the M2 macrophages are identified based on the expression pattern of a set of M2 markers. These markers are transmembrane glycoproteins, scavenger receptors, enzymes, growth factors, hormones, cytokines, and cytokine receptors with diverse and often yet unexplored functions. This review discusses whether these M2 markers can be reliably used to identify M2 macrophages and define their functional subdivisions. Also, it provides an update on the novel signals of the tissue environment and the neuroendocrine system which shape the M2 activation. The possible evolutionary roots of the M2 macrophage functions are also discussed. PMID:26089604

Neutrophil-to-lymphocyte ratio as a predictor of worsening renal function in diabetic patients (3-year follow-up study).

PubMed

Azab, Basem; Daoud, Jacques; Naeem, Fahad Ben; Nasr, Rabih; Ross, Jennifer; Ghimire, Pratima; Siddiqui, Ayesha; Azzi, Nadine; Rihana, Nancy; Abdallah, Marie; Azzi, Nassif; Patel, Parishram; Kleiner, Morton; El-Sayegh, Suzanne

2012-01-01

Previous studies have demonstrated the role of inflammation in diabetic nephropathy (DN). Neutrophil to lymphocyte ratio (NLR) rather than other white cell parameters was found to be a useful inflammatory marker to predict adverse outcomes in medical and surgical conditions. Nevertheless, the value of NLR in predicting DN has not been elucidated. An observational study included 338 diabetic patients, who were followed at our clinic between 2007 and 2009. We arranged our patients into tertiles according to their 2007 NLR. The primary outcome was continuous decrease of GFR >12 mL/min between 2007 and 2009 with the last GFR <60 mL/min. The lowest NLR tertile had fewer patients (2.7%) with primary outcome (i.e., worsening renal function) compared with middle and highest NLR tertiles, which had more patients with primary outcomes (8.7% and 11.5%, respectively) with a significant p-value 0.0164. When other potential confounders were individually analyzed with NLR tertile, the NLR tertiles remained a significant predictor of poor GFR outcome in the presence of other variables (hemoglobin A1C, systolic blood pressure, diastolic blood pressure, age, and congestive heart failure with p-values 0.018, 0.019, 0.017, 0.033, and 0.022, respectively). NLR predicted the worsening of the renal function in diabetic patients. Further studies are needed to confirm this result.

Nestin is essential for zebrafish brain and eye development through control of progenitor cell apoptosis.

PubMed

Chen, Hua-Ling; Yuh, Chiou-Hwa; Wu, Kenneth K

2010-02-19

Nestin is expressed in neural progenitor cells (NPC) of developing brain. Despite its wide use as an NPC marker, the function of nestin in embryo development is unclear. As nestin is conserved in zebrafish and its predicted sequence is clustered with the mammalian nestin orthologue, we used zebrafish as a model to investigate its role in embryogenesis. Injection of nestin morpholino (MO) into fertilized eggs induced time- and dose-dependent brain and eye developmental defects. Nestin morphants exhibited characteristic morphological changes including small head, small eyes and hydrocephalus. Histological examinations show reduced hind- and mid-brain size, dilated ventricle, poorly organized retina and underdeveloped lens. Injection of control nestin MO did not induce brain or eye changes. Nestin MO injection reduced expression of ascl1b (achaete-scute complex-like 1b), a marker of NPCs, without affecting its distribution. Nestin MO did not influence Elavl3/4 (Embryonic lethal, abnormal vision, Drosophila-like 3/4) (a neuronal marker), or otx2 (a midbrain neuronal marker), but severely perturbed cranial motor nerve development and axon distribution. To determine whether the developmental defects are due to excessive NPC apoptosis and/or reduced NPC proliferation, we analyzed apoptosis by TUNEL assay and acridine orange staining and proliferation by BrdU incorporation, pcna and mcm5 expressions. Excessive apoptosis was noted in hindbrain and midbrain cells. Apoptotic signals were colocalized with ascl1b. Proliferation markers were not significantly altered by nestin MO. These results suggest that nestin is essential for zebrafish brain and eye development probably through control of progenitor cell apoptosis.

Adult Attachment Interview Discourse Patterns Predict Metabolic Syndrome in Midlife

PubMed Central

Davis, Cynthia R.; Usher, Nicole; Dearing, Eric; Barkai, Ayelet R.; Crowell-Doom, Cindy; Mantzoros, Christos S.; Crowell, Judith A.

2017-01-01

Objective Adult attachment discourse patterns and current family relationship quality were examined as predictors of health behaviors and number of Metabolic Syndrome (MetS) criteria met. Methods A sample of 215 White/European American and Black/African American adults, aged 35 to 55, were examined cross-sectionally. Discourse was assessed with the Adult Attachment Interview (AAI), specifically: 1) coherence, a marker of attachment security, 2) unresolved trauma/loss, a marker of disorganized and distorted cognition related to trauma, and 3) idealization, the tendency to minimize the impact of stressful experiences. Health behaviors of diet, exercise, smoking and alcohol use were also assessed, as were adverse childhood experiences, current depressive symptoms and relationship functioning. MetS includes hypertension, hyperglycemia, high triglycerides, low HDL cholesterol, and obesity. Results Using path analysis and accounting for childhood adversity and depressive symptoms, AAI coherence and unresolved trauma or loss were directly linked to number of MetS criteria met (β = −.22 and .21 respectively). Idealization was indirectly linked to MetS through poor diet (β = −.26 and −.36 respectively), predicting 21% of the variance in number of MetS criteria met. Conclusions Attachment representations related to stress appraisal and care-seeking behaviors appear to serve as cognitive mechanisms increasing risk of MetS. PMID:25264975

From neural signatures of emotional modulation to social cognition: individual differences in healthy volunteers and psychiatric participants

PubMed Central

Aguado, Jaume; Baez, Sandra; Huepe, David; Lopez, Vladimir; Ortega, Rodrigo; Sigman, Mariano; Mikulan, Ezequiel; Lischinsky, Alicia; Torrente, Fernando; Cetkovich, Marcelo; Torralva, Teresa; Bekinschtein, Tristan; Manes, Facundo

2014-01-01

It is commonly assumed that early emotional signals provide relevant information for social cognition tasks. The goal of this study was to test the association between (a) cortical markers of face emotional processing and (b) social-cognitive measures, and also to build a model which can predict this association (a and b) in healthy volunteers as well as in different groups of psychiatric patients. Thus, we investigated the early cortical processing of emotional stimuli (N170, using a face and word valence task) and their relationship with the social-cognitive profiles (SCPs, indexed by measures of theory of mind, fluid intelligence, speed processing and executive functions). Group comparisons and individual differences were assessed among schizophrenia (SCZ) patients and their relatives, individuals with attention deficit hyperactivity disorder (ADHD), individuals with euthymic bipolar disorder (BD) and healthy participants (educational level, handedness, age and gender matched). Our results provide evidence of emotional N170 impairments in the affected groups (SCZ and relatives, ADHD and BD) as well as subtle group differences. Importantly, cortical processing of emotional stimuli predicted the SCP, as evidenced by a structural equation model analysis. This is the first study to report an association model of brain markers of emotional processing and SCP. PMID:23685775

Filtering genetic variants and placing informative priors based on putative biological function.

PubMed

Friedrichs, Stefanie; Malzahn, Dörthe; Pugh, Elizabeth W; Almeida, Marcio; Liu, Xiao Qing; Bailey, Julia N

2016-02-03

High-density genetic marker data, especially sequence data, imply an immense multiple testing burden. This can be ameliorated by filtering genetic variants, exploiting or accounting for correlations between variants, jointly testing variants, and by incorporating informative priors. Priors can be based on biological knowledge or predicted variant function, or even be used to integrate gene expression or other omics data. Based on Genetic Analysis Workshop (GAW) 19 data, this article discusses diversity and usefulness of functional variant scores provided, for example, by PolyPhen2, SIFT, or RegulomeDB annotations. Incorporating functional scores into variant filters or weights and adjusting the significance level for correlations between variants yielded significant associations with blood pressure traits in a large family study of Mexican Americans (GAW19 data set). Marker rs218966 in gene PHF14 and rs9836027 in MAP4 significantly associated with hypertension; additionally, rare variants in SNUPN significantly associated with systolic blood pressure. Variant weights strongly influenced the power of kernel methods and burden tests. Apart from variant weights in test statistics, prior weights may also be used when combining test statistics or to informatively weight p values while controlling false discovery rate (FDR). Indeed, power improved when gene expression data for FDR-controlled informative weighting of association test p values of genes was used. Finally, approaches exploiting variant correlations included identity-by-descent mapping and the optimal strategy for joint testing rare and common variants, which was observed to depend on linkage disequilibrium structure.

PTEN Loss Does Not Predict for Response to RAD001 (Everolimus) in a Glioblastoma Orthotopic Xenograft Test Panel

PubMed Central

Yang, Lin; Clarke, Michelle J.; Carlson, Brett L.; Mladek, Ann C.; Schroeder, Mark A.; Decker, Paul; Wu, Wenting; Kitange, Gaspar J.; Grogan, Patrick T.; Goble, Jennie M.; Uhm, Joon; Galanis, Evanthia; Giannini, Caterina; Lane, Heidi A.; James, C. David; Sarkaria, Jann N.

2014-01-01

Purpose Hyperactivation of the phosphatidylinositol 3-kinase/Akt signaling through disruption of PTEN function is common in glioblastoma multiforme, and these genetic changes are predicted to enhance sensitivity to mammalian target of rapamycin (mTOR) inhibitors such as RAD001 (everolimus). Experimental Design To test whether PTEN loss could be used as a predictive marker for mTOR inhibitor sensitivity, the response of 17 serially transplantable glioblastoma multiforme xenografts was evaluated in an orthotopic therapy evaluation model. Of these 17 xenograft lines, 7 have either genomic deletion or mutation of PTEN. Results Consistent with activation of Akt signaling, there was a good correlation between loss of PTEN function and elevated levels of Akt phosphorylation. However, of the 7 lines with disrupted PTEN function, only 1 tumor line (GBM10) was significantly sensitive to RAD001 therapy (25% prolongation in median survival), whereas1 of 10 xenograft lines with wild-type PTEN was significantly sensitive to RAD001 (GS22; 34% prolongation in survival). Relative to placebo, 5 days of RAD001 treatment was associated with a marked 66% reduction in the MIB1 proliferation index in the sensitive GBM10 line (deleted PTEN) compared with a 25% and 7% reduction in MIB1 labeling index in the insensitive GBM14 (mutant PTEN) and GBM15 (wild-type PTEN) lines, respectively. Consistent with a cytostatic antitumor effect, bioluminescent imaging of luciferase-transduced intracranial GBM10 xenografts showed slowed tumor growth without significant tumor regression during RAD001 therapy. Conclusion These data suggest that loss of PTEN function is insufficient to adequately predict responsiveness to mTOR inhibitors in glioblastoma multiforme. PMID:18559622

Pretransplant thymic function predicts acute rejection in antithymocyte globulin-treated renal transplant recipients.

PubMed

Bamoulid, Jamal; Courivaud, Cécile; Crepin, Thomas; Carron, Clémence; Gaiffe, Emilie; Roubiou, Caroline; Laheurte, Caroline; Moulin, Bruno; Frimat, Luc; Rieu, Philippe; Mousson, Christiane; Durrbach, Antoine; Heng, Anne-Elisabeth; Rebibou, Jean-Michel; Saas, Philippe; Ducloux, Didier

2016-05-01

Lack of clear identification of patients at high risk of acute rejection hampers the ability to individualize immunosuppressive therapy. Here we studied whether thymic function may predict acute rejection in antithymocyte globulin (ATG)-treated renal transplant recipients in 482 patients prospectively studied during the first year post-transplant of which 86 patients experienced acute rejection. Only CD45RA(+)CD31(+)CD4(+) T cell (recent thymic emigrant [RTE]) frequency (RTE%) was marginally associated with acute rejection in the whole population. This T-cell subset accounts for 26% of CD4(+) T cells. Pretransplant RTE% was significantly associated with acute rejection in ATG-treated patients (hazard ratio, 1.04; 95% confidence interval, 1.01-1.08) for each increased percent in RTE/CD4(+) T cells), but not in anti-CD25 monoclonal (αCD25 mAb)-treated patients. Acute rejection was significantly more frequent in ATG-treated patients with high pretransplant RTE% (31.2% vs. 16.4%) or absolute number of RTE/mm(3) (31.7 vs. 16.1). This difference was not found in αCD25 monclonal antibody-treated patients. Highest values of both RTE% (>31%, hazard ratio, 2.50; 95% confidence interval, 1.09-5.74) and RTE/mm(3) (>200/mm(3), hazard ratio, 3.71; 95% confidence interval, 1.59-8.70) were predictive of acute rejection in ATG-treated patients but not in patients having received αCD25 monoclonal antibody). Results were confirmed in a retrospective cohort using T-cell receptor excision circle levels as a marker of thymic function. Thus, pretransplant thymic function predicts acute rejection in ATG-treated patients. Copyright © 2016 International Society of Nephrology. Published by Elsevier Inc. All rights reserved.

Exploring the genetic architecture and improving genomic prediction accuracy for mastitis and milk production traits in dairy cattle by mapping variants to hepatic transcriptomic regions responsive to intra-mammary infection.

PubMed

Fang, Lingzhao; Sahana, Goutam; Ma, Peipei; Su, Guosheng; Yu, Ying; Zhang, Shengli; Lund, Mogens Sandø; Sørensen, Peter

2017-05-12

A better understanding of the genetic architecture of complex traits can contribute to improve genomic prediction. We hypothesized that genomic variants associated with mastitis and milk production traits in dairy cattle are enriched in hepatic transcriptomic regions that are responsive to intra-mammary infection (IMI). Genomic markers [e.g. single nucleotide polymorphisms (SNPs)] from those regions, if included, may improve the predictive ability of a genomic model. We applied a genomic feature best linear unbiased prediction model (GFBLUP) to implement the above strategy by considering the hepatic transcriptomic regions responsive to IMI as genomic features. GFBLUP, an extension of GBLUP, includes a separate genomic effect of SNPs within a genomic feature, and allows differential weighting of the individual marker relationships in the prediction equation. Since GFBLUP is computationally intensive, we investigated whether a SNP set test could be a computationally fast way to preselect predictive genomic features. The SNP set test assesses the association between a genomic feature and a trait based on single-SNP genome-wide association studies. We applied these two approaches to mastitis and milk production traits (milk, fat and protein yield) in Holstein (HOL, n = 5056) and Jersey (JER, n = 1231) cattle. We observed that a majority of genomic features were enriched in genomic variants that were associated with mastitis and milk production traits. Compared to GBLUP, the accuracy of genomic prediction with GFBLUP was marginally improved (3.2 to 3.9%) in within-breed prediction. The highest increase (164.4%) in prediction accuracy was observed in across-breed prediction. The significance of genomic features based on the SNP set test were correlated with changes in prediction accuracy of GFBLUP (P < 0.05). GFBLUP provides a framework for integrating multiple layers of biological knowledge to provide novel insights into the biological basis of complex traits, and to improve the accuracy of genomic prediction. The SNP set test might be used as a first-step to improve GFBLUP models. Approaches like GFBLUP and SNP set test will become increasingly useful, as the functional annotations of genomes keep accumulating for a range of species and traits.

Molecular Markers for Breast Cancer: Prediction on Tumor Behavior

PubMed Central

Banin Hirata, Bruna Karina; Oda, Julie Massayo Maeda; Losi Guembarovski, Roberta; Ariza, Carolina Batista; de Oliveira, Carlos Eduardo Coral; Watanabe, Maria Angelica Ehara

2014-01-01

Breast cancer is one of the most common cancers with greater than 1,300,000 cases and 450,000 deaths each year worldwide. The development of breast cancer involves a progression through intermediate stages until the invasive carcinoma and finally into metastatic disease. Given the variability in clinical progression, the identification of markers that could predict the tumor behavior is particularly important in breast cancer. The determination of tumor markers is a useful tool for clinical management in cancer patients, assisting in diagnostic, staging, evaluation of therapeutic response, detection of recurrence and metastasis, and development of new treatment modalities. In this context, this review aims to discuss the main tumor markers in breast carcinogenesis. The most well-established breast molecular markers with prognostic and/or therapeutic value like hormone receptors, HER-2 oncogene, Ki-67, and p53 proteins, and the genes for hereditary breast cancer will be presented. Furthermore, this review shows the new molecular targets in breast cancer: CXCR4, caveolin, miRNA, and FOXP3, as promising candidates for future development of effective and targeted therapies, also with lower toxicity. PMID:24591761

The research on endothelial function in women and men at risk for cardiovascular disease (REWARD) study: methodology

PubMed Central

2011-01-01

Background Endothelial function has been shown to be a highly sensitive marker for the overall cardiovascular risk of an individual. Furthermore, there is evidence of important sex differences in endothelial function that may underlie the differential presentation of cardiovascular disease (CVD) in women relative to men. As such, measuring endothelial function may have sex-specific prognostic value for the prediction of CVD events, thus improving risk stratification for the overall prediction of CVD in both men and women. The primary objective of this study is to assess the clinical utility of the forearm hyperaemic reactivity (FHR) test (a proxy measure of endothelial function) for the prediction of CVD events in men vs. women using a novel, noninvasive nuclear medicine -based approach. It is hypothesised that: 1) endothelial dysfunction will be a significant predictor of 5-year CVD events independent of baseline stress test results, clinical, demographic, and psychological variables in both men and women; and 2) endothelial dysfunction will be a better predictor of 5-year CVD events in women compared to men. Methods/Design A total of 1972 patients (812 men and 1160 women) undergoing a dipyridamole stress testing were recruited. Medical history, CVD risk factors, health behaviours, psychological status, and gender identity were assessed via structured interview or self-report questionnaires at baseline. In addition, FHR was assessed, as well as levels of sex hormones via blood draw. Patients will be followed for 5 years to assess major CVD events (cardiac mortality, non-fatal MI, revascularization procedures, and cerebrovascular events). Discussion This is the first study to determine the extent and nature of any sex differences in the ability of endothelial function to predict CVD events. We believe the results of this study will provide data that will better inform the choice of diagnostic tests in men and women and bring the quality of risk stratification in women on par with that of men. PMID:21831309

Bidirectional Prospective Associations Between Cardiac Autonomic Activity and Inflammatory Markers.

PubMed

Hu, Mandy Xian; Lamers, Femke; Neijts, Melanie; Willemsen, Gonneke; de Geus, Eco J C; Penninx, Brenda W J H

2018-06-01

Autonomic nervous system (ANS) imbalance has been cross-sectionally associated with inflammatory processes. Longitudinal studies are needed to shed light on the nature of this relationship. We examined cross-sectional and bidirectional prospective associations between cardiac autonomic measures and inflammatory markers. Analyses were conducted with baseline (n = 2823), 2-year (n = 2099), and 6-year (n = 1774) data from the Netherlands Study of Depression and Anxiety. To compare the pattern of results, prospective analyses with ANS (during sleep, leisure time, and work) and inflammation were conducted in two data sets from the Netherlands Twin Register measured for 4.9 years (n = 356) and 5.4 years (n = 472). Autonomic nervous system measures were heart rate (HR) and respiratory sinus arrhythmia (RSA). Inflammatory markers were C-reactive protein (CRP) and interleukin (IL)-6. The Netherlands Study of Depression and Anxiety results showed that higher HR and lower RSA were cross-sectionally significantly associated with higher inflammatory levels. Higher HR predicted higher levels of CRP (B = .065, p < .001) and IL-6 (B = .036, p = .014) at follow-up. Higher CRP levels predicted lower RSA (B = -.024, p = .048) at follow-up. The Netherlands Twin Register results confirmed that higher HR was associated with higher CRP and IL-6 levels 4.9 years later. Higher IL-6 levels predicted higher HR and lower RSA at follow-up. Autonomic imbalance is associated with higher levels of inflammation. Independent data from two studies converge in evidence that higher HR predicts subsequent higher levels of CRP and IL-6. Inflammatory markers may also predict future ANS activity, but evidence for this was less consistent.

Advantages and limitations of multiple-trait genomic prediction for Fusarium head blight severity in hybrid wheat (Triticum aestivum L.).

PubMed

Schulthess, Albert W; Zhao, Yusheng; Longin, C Friedrich H; Reif, Jochen C

2018-03-01

Predictabilities for wheat hybrids less related to the estimation set were improved by shifting from single- to multiple-trait genomic prediction of Fusarium head blight severity. Breeding for improved Fusarium head blight resistance (FHBr) of wheat is a very laborious and expensive task. FHBr complexity is mainly due to its highly polygenic nature and because FHB severity (FHBs) is greatly influenced by the environment. Associated traits plant height and heading date may provide additional information related to FHBr, but this is ignored in single-trait genomic prediction (STGP). The aim of our study was to explore the benefits in predictabilities of multiple-trait genomic prediction (MTGP) over STGP of target trait FHBs in a population of 1604 wheat hybrids using information on 17,372 single nucleotide polymorphism markers along with indicator traits plant height and heading date. The additive inheritance of FHBs allowed accurate hybrid performance predictions using information on general combining abilities or average performance of both parents without the need of markers. Information on molecular markers and indicator trait(s) improved FHBs predictabilities for hybrids less related to the estimation set. Indicator traits must be observed on the predicted individuals to benefit from MTGP. Magnitudes of genetic and phenotypic correlations along with improvements in predictabilities made plant height a better indicator trait for FHBs than heading date. Thus, MTGP having only plant height as indicator trait already maximized FHBs predictabilities. Provided a good indicator trait was available, MTGP could reduce the impacts of genotype environment [Formula: see text] interaction on STGP for hybrids less related to the estimation set.

CCL3L1-CCR5 genotype improves the assessment of AIDS Risk in HIV-1-infected individuals.

PubMed

Kulkarni, Hemant; Agan, Brian K; Marconi, Vincent C; O'Connell, Robert J; Camargo, Jose F; He, Weijing; Delmar, Judith; Phelps, Kenneth R; Crawford, George; Clark, Robert A; Dolan, Matthew J; Ahuja, Sunil K

2008-09-08

Whether vexing clinical decision-making dilemmas can be partly addressed by recent advances in genomics is unclear. For example, when to initiate highly active antiretroviral therapy (HAART) during HIV-1 infection remains a clinical dilemma. This decision relies heavily on assessing AIDS risk based on the CD4+ T cell count and plasma viral load. However, the trajectories of these two laboratory markers are influenced, in part, by polymorphisms in CCR5, the major HIV coreceptor, and the gene copy number of CCL3L1, a potent CCR5 ligand and HIV-suppressive chemokine. Therefore, we determined whether accounting for both genetic and laboratory markers provided an improved means of assessing AIDS risk. In a prospective, single-site, ethnically-mixed cohort of 1,132 HIV-positive subjects, we determined the AIDS risk conveyed by the laboratory and genetic markers separately and in combination. Subjects were assigned to a low, moderate or high genetic risk group (GRG) based on variations in CCL3L1 and CCR5. The predictive value of the CCL3L1-CCR5 GRGs, as estimated by likelihood ratios, was equivalent to that of the laboratory markers. GRG status also predicted AIDS development when the laboratory markers conveyed a contrary risk. Additionally, in two separate and large groups of HIV+ subjects from a natural history cohort, the results from additive risk-scoring systems and classification and regression tree (CART) analysis revealed that the laboratory and CCL3L1-CCR5 genetic markers together provided more prognostic information than either marker alone. Furthermore, GRGs independently predicted the time interval from seroconversion to CD4+ cell count thresholds used to guide HAART initiation. The combination of the laboratory and genetic markers captures a broader spectrum of AIDS risk than either marker alone. By tracking a unique aspect of AIDS risk distinct from that captured by the laboratory parameters, CCL3L1-CCR5 genotypes may have utility in HIV clinical management. These findings illustrate how genomic information might be applied to achieve practical benefits of personalized medicine.

Clinical implications of omics and systems medicine: focus on predictive and individualized treatment.

PubMed

Benson, M

2016-03-01

Many patients with common diseases do not respond to treatment. This is a key challenge to modern health care, which causes both suffering and enormous costs. One important reason for the lack of treatment response is that common diseases are associated with altered interactions between thousands of genes, in combinations that differ between subgroups of patients who do or do not respond to a given treatment. Such subgroups, or even distinct disease entities, have been described recently in asthma, diabetes, autoimmune diseases and cancer. High-throughput techniques (omics) allow identification and characterization of such subgroups or entities. This may have important clinical implications, such as identification of diagnostic markers for individualized medicine, as well as new therapeutic targets for patients who do not respond to existing drugs. For example, whole-genome sequencing may be applied to more accurately guide treatment of neurodevelopmental diseases, or to identify drugs specifically targeting mutated genes in cancer. A study published in 2015 showed that 28% of hepatocellular carcinomas contained mutated genes that potentially could be targeted by drugs already approved by the US Food and Drug Administration. A translational study, which is described in detail, showed how combined omics, computational, functional and clinical studies could identify and validate a novel diagnostic and therapeutic candidate gene in allergy. Another important clinical implication is the identification of potential diagnostic markers and therapeutic targets for predictive and preventative medicine. By combining computational and experimental methods, early disease regulators may be identified and potentially used to predict and treat disease before it becomes symptomatic. Systems medicine is an emerging discipline, which may contribute to such developments through combining omics with computational, functional and clinical studies. The aims of this review are to provide a brief introduction to systems medicine and discuss how it may contribute to the clinical implementation of individualized treatment, using clinically relevant examples. © 2015 The Association for the Publication of the Journal of Internal Medicine.

Catechol-O-Methyltransferase Val158Met Polymorphism Associates with Individual Differences in Sleep Physiologic Responses to Chronic Sleep Loss

PubMed Central

Goel, Namni; Banks, Siobhan; Lin, Ling; Mignot, Emmanuel; Dinges, David F.

2011-01-01

Background The COMT Val158Met polymorphism modulates cortical dopaminergic catabolism, and predicts individual differences in prefrontal executive functioning in healthy adults and schizophrenic patients, and associates with EEG differences during sleep loss. We assessed whether the COMT Val158Met polymorphism was a novel marker in healthy adults of differential vulnerability to chronic partial sleep deprivation (PSD), a condition distinct from total sleep loss and one experienced by millions on a daily and persistent basis. Methodology/Principal Findings 20 Met/Met, 64 Val/Met, and 45 Val/Val subjects participated in a protocol of two baseline 10h time in bed (TIB) nights followed by five consecutive 4 h TIB nights. Met/Met subjects showed differentially steeper declines in non-REM EEG slow-wave energy (SWE)—the putative homeostatic marker of sleep drive—during PSD, despite comparable baseline SWE declines. Val/Val subjects showed differentially smaller increases in slow-wave sleep and smaller reductions in stage 2 sleep during PSD, and had more stage 1 sleep across nights and a shorter baseline REM sleep latency. The genotypes, however, did not differ in performance across various executive function and cognitive tasks and showed comparable increases in subjective and physiological sleepiness in response to chronic sleep loss. Met/Met genotypic and Met allelic frequencies were higher in whites than African Americans. Conclusions/Significance The COMT Val158Met polymorphism may be a genetic biomarker for predicting individual differences in sleep physiology—but not in cognitive and executive functioning—resulting from sleep loss in a healthy, racially-diverse adult population of men and women. Beyond healthy sleepers, our results may also provide insight for predicting sleep loss responses in patients with schizophrenia and other psychiatric disorders, since these groups repeatedly experience chronically-curtailed sleep and demonstrate COMT-related treatment responses and risk factors for symptom exacerbation. PMID:22216231

Prediction of Response to Sorafenib in Hepatocellular Carcinoma: A Putative Marker Panel by Multiple Reaction Monitoring-Mass Spectrometry (MRM-MS).

PubMed

Kim, Hyunsoo; Yu, Su Jong; Yeo, Injun; Cho, Young Youn; Lee, Dong Hyeon; Cho, Yuri; Cho, Eun Ju; Lee, Jeong-Hoon; Kim, Yoon Jun; Lee, Sungyoung; Jun, Jongsoo; Park, Taesung; Yoon, Jung-Hwan; Kim, Youngsoo

2017-07-01

Sorafenib is the only standard treatment for unresectable hepatocellular carcinoma (HCC), but it provides modest survival benefits over placebo, necessitating predictive biomarkers of the response to sorafenib. Serum samples were obtained from 115 consecutive patients with HCC before sorafenib treatment and analyzed by multiple reaction monitoring-mass spectrometry (MRM-MS) and ELISA to quantify candidate biomarkers. We verified a triple-marker panel to be predictive of the response to sorafenib by MRM-MS, comprising CD5 antigen-like (CD5L), immunoglobulin J (IGJ), and galectin-3-binding protein (LGALS3BP), in HCC patients. This panel was a significant predictor (AUROC > 0.950) of the response to sorafenib treatment, having the best cut-off value (0.4) by multivariate analysis. In the training set, patients who exceeded this cut-off value had significantly better overall survival (median, 21.4 months) than those with lower values (median, 8.6 months; p = 0.001). Further, a value that was lower than this cutoff was an independent predictor of poor overall survival [hazard ratio (HR), 2.728; 95% confidence interval (CI), 1.312-5.672; p = 0.007] and remained an independent predictive factor of rapid progression (HR, 2.631; 95% CI, 1.448-4.780; p = 0.002). When applied to the independent validation set, levels of the cut-off value for triple-marker panel maintained their prognostic value for poor clinical outcomes. On the contrast, the triple-marker panel was not a prognostic factor for patients who were treated with transarterial chemoembolization (TACE). The discriminatory signature of a triple-marker panel provides new insights into targeted proteomic biomarkers for individualized sorafenib therapy. © 2017 by The American Society for Biochemistry and Molecular Biology, Inc.

Evaluation of the Value of d-Dimer, P-Selectin, and Platelet Count for Prediction of Portal Vein Thrombosis After Devascularization.

PubMed

Fei, Yang; Zong, Guang-Quan; Chen, Jian; Liu, Ren-Min

2016-07-01

To evaluate the value of d-dimer, P-selectin, and platelet count in patients with cirrhotic portal hypertension (PHT) for prediction of portal vein thrombosis (PVT) after devascularization. A total of 137 patients with cirrhotic PHT who undergone devascularization from January 2012 to April 2014 were retrospectively reviewed, all of them were divided into 2 groups (PVT group and non-PVT group) by Doppler ultrasonography (DU) examination. The level of d-dimer, P-selectin, and platelet count was tested during the perioperative period. In all, 38 (27.7%) patients were found to have PVT by DU examination postoperatively. In contrast to the non-PVT group, the level of d-dimer, P-selectin, and platelet count in the PVT group was much higher significantly at 1, 3, and 7 days after devascularization. (P < .05). However, in the 15 days after surgery, the difference in P-selectin between the 2 groups was not significant (P = .260). It was shown that the highest sensitivity of the 3 markers for PVT was d-dimer, the highest specificity belonged to P-selectin. The area under receiver-operating characteristic (ROC) curve of P-selectin was the biggest of the 3 markers. When the 3 markers were combined to be used to diagnose PVT, the sensitivity was increased to 0.907, with a slight drop of specificity to 0.693, the area under the ROC curve was 0.927. The level of d-dimer, P-selectin, and platelet count might be good candidate predictive markers for PVT in patients with cirrhotic PHT after devascularization. The combined test of the 3 markers can increase the value of prediction. © The Author(s) 2015.

A Usage-Based Approach to Early-Discourse Pragmatic Functions of the Japanese Subject Markers "wa" and "ga"

ERIC Educational Resources Information Center

Uno, Mariko

2016-01-01

This study investigates the emergence and development of the discourse-pragmatic functions of the Japanese subject markers "wa" and "ga" from a usage-based perspective (Tomasello, 2000). The use of each marker in longitudinal speech data for four Japanese children from 1;0 to 3;1 and their parents available in the CHILDES…

Tumor Cell-Free DNA Copy Number Instability Predicts Therapeutic Response to Immunotherapy.

PubMed

Weiss, Glen J; Beck, Julia; Braun, Donald P; Bornemann-Kolatzki, Kristen; Barilla, Heather; Cubello, Rhiannon; Quan, Walter; Sangal, Ashish; Khemka, Vivek; Waypa, Jordan; Mitchell, William M; Urnovitz, Howard; Schütz, Ekkehard

2017-09-01

Purpose: Chromosomal instability is a fundamental property of cancer, which can be quantified by next-generation sequencing (NGS) from plasma/serum-derived cell-free DNA (cfDNA). We hypothesized that cfDNA could be used as a real-time surrogate for imaging analysis of disease status as a function of response to immunotherapy and as a more reliable tool than tumor biomarkers. Experimental Design: Plasma cfDNA sequences from 56 patients with diverse advanced cancers were prospectively collected and analyzed in a single-blind study for copy number variations, expressed as a quantitative chromosomal number instability (CNI) score versus 126 noncancer controls in a training set of 23 and a blinded validation set of 33. Tumor biomarker concentrations and a surrogate marker for T regulatory cells (Tregs) were comparatively analyzed. Results: Elevated CNI scores were observed in 51 of 56 patients prior to therapy. The blinded validation cohort provided an overall prediction accuracy of 83% (25/30) and a positive predictive value of CNI score for progression of 92% (11/12). The combination of CNI score before cycle (Cy) 2 and 3 yielded a correct prediction for progression in all 13 patients. The CNI score also correctly identified cases of pseudo-tumor progression from hyperprogression. Before Cy2 and Cy3, there was no significant correlation for protein tumor markers, total cfDNA, or surrogate Tregs. Conclusions: Chromosomal instability quantification in plasma cfDNA can serve as an early indicator of response to immunotherapy. The method has the potential to reduce health care costs and disease burden for cancer patients following further validation. Clin Cancer Res; 23(17); 5074-81. ©2017 AACR . ©2017 American Association for Cancer Research.

Comprehensive lipid analysis: a powerful metanomic tool for predictive and diagnostic medicine.

PubMed

Watkins, S M

2000-09-01

The power and accuracy of predictive diagnostics stand to improve dramatically as a result of lipid metanomics. The high definition of data obtained with this approach allows multiple rather than single metabolites to be used in markers for a group. Since as many as 40 fatty acids are quantified from each lipid class, and up to 15 lipid classes can be quantified easily, more than 600 individual lipid metabolites can be measured routinely for each sample. Because these analyses are comprehensive, only the most appropriate and unique metabolites are selected for their predictive value. Thus, comprehensive lipid analysis promises to greatly improve predictive diagnostics for phenotypes that directly or peripherally involve lipids. A broader and possibly more exciting aspect of this technology is the generation of metabolic profiles that are not simply markers for disease, but metabolic maps that can be used to identify specific genes or activities that cause or influence the disease state. Metanomics is, in essence, functional genomics from metabolite analysis. By defining the metabolic basis for phenotype, researchers and clinicians will have an extraordinary opportunity to understand and treat disease. Much in the same way that gene chips allow researchers to observe the complex expression response to a stimulus, metanomics will enable researchers to observe the complex metabolic interplay responsible for defining phenotype. By extending this approach beyond the observation of individual dysregulations, medicine will begin to profile not single diseases, but health. As health is the proper balance of all vital metabolic pathways, comprehensive or metanomic analysis lends itself very well to identifying the metabolite distributions necessary for optimum health. Comprehensive and quantitative analysis of lipids would provide this degree of diagnostic power to researchers and clinicians interested in mining metabolic profiles for biological meaning.

AucPR: an AUC-based approach using penalized regression for disease prediction with high-dimensional omics data.

PubMed

Yu, Wenbao; Park, Taesung

2014-01-01

It is common to get an optimal combination of markers for disease classification and prediction when multiple markers are available. Many approaches based on the area under the receiver operating characteristic curve (AUC) have been proposed. Existing works based on AUC in a high-dimensional context depend mainly on a non-parametric, smooth approximation of AUC, with no work using a parametric AUC-based approach, for high-dimensional data. We propose an AUC-based approach using penalized regression (AucPR), which is a parametric method used for obtaining a linear combination for maximizing the AUC. To obtain the AUC maximizer in a high-dimensional context, we transform a classical parametric AUC maximizer, which is used in a low-dimensional context, into a regression framework and thus, apply the penalization regression approach directly. Two kinds of penalization, lasso and elastic net, are considered. The parametric approach can avoid some of the difficulties of a conventional non-parametric AUC-based approach, such as the lack of an appropriate concave objective function and a prudent choice of the smoothing parameter. We apply the proposed AucPR for gene selection and classification using four real microarray and synthetic data. Through numerical studies, AucPR is shown to perform better than the penalized logistic regression and the nonparametric AUC-based method, in the sense of AUC and sensitivity for a given specificity, particularly when there are many correlated genes. We propose a powerful parametric and easily-implementable linear classifier AucPR, for gene selection and disease prediction for high-dimensional data. AucPR is recommended for its good prediction performance. Beside gene expression microarray data, AucPR can be applied to other types of high-dimensional omics data, such as miRNA and protein data.

A novel neural-inspired learning algorithm with application to clinical risk prediction.

PubMed

Tay, Darwin; Poh, Chueh Loo; Kitney, Richard I

2015-04-01

Clinical risk prediction - the estimation of the likelihood an individual is at risk of a disease - is a coveted and exigent clinical task, and a cornerstone to the recommendation of life saving management strategies. This is especially important for individuals at risk of cardiovascular disease (CVD) given the fact that it is the leading causes of death in many developed counties. To this end, we introduce a novel learning algorithm - a key factor that influences the performance of machine learning-based prediction models - and utilities it to develop CVD risk prediction tool. This novel neural-inspired algorithm, called the Artificial Neural Cell System for classification (ANCSc), is inspired by mechanisms that develop the brain and empowering it with capabilities such as information processing/storage and recall, decision making and initiating actions on external environment. Specifically, we exploit on 3 natural neural mechanisms responsible for developing and enriching the brain - namely neurogenesis, neuroplasticity via nurturing and apoptosis - when implementing ANCSc algorithm. Benchmark testing was conducted using the Honolulu Heart Program (HHP) dataset and results are juxtaposed with 2 other algorithms - i.e. Support Vector Machine (SVM) and Evolutionary Data-Conscious Artificial Immune Recognition System (EDC-AIRS). Empirical experiments indicate that ANCSc algorithm (statistically) outperforms both SVM and EDC-AIRS algorithms. Key clinical markers identified by ANCSc algorithm include risk factors related to diet/lifestyle, pulmonary function, personal/family/medical history, blood data, blood pressure, and electrocardiography. These clinical markers, in general, are also found to be clinically significant - providing a promising avenue for identifying potential cardiovascular risk factors to be evaluated in clinical trials. Copyright © 2015 Elsevier Inc. All rights reserved.

Genomic prediction using phenotypes from pedigreed lines with no marker data

USDA-ARS?s Scientific Manuscript database

Until now genomic prediction in plant breeding has only used information from individuals that have been genotyped. In practice, information from non-genotyped relatives of genotyped individuals can be used to improve the genomic prediction accuracy. Single-step genomic prediction integrates all the...

Molecular markers of carcinogenesis for risk stratification of individuals with colorectal polyps: a case-control study.

PubMed

Gupta, Samir; Sun, Han; Yi, Sang; Storm, Joy; Xiao, Guanghua; Balasubramanian, Bijal A; Zhang, Song; Ashfaq, Raheela; Rockey, Don C

2014-10-01

Risk stratification using number, size, and histology of colorectal adenomas is currently suboptimal for identifying patients at increased risk for future colorectal cancer. We hypothesized that molecular markers of carcinogenesis in adenomas, measured via immunohistochemistry, may help identify high-risk patients. To test this hypothesis, we conducted a retrospective, 1:1 matched case-control study (n = 216; 46% female) in which cases were patients with colorectal cancer and synchronous adenoma and controls were patients with adenoma but no colorectal cancer at baseline or within 5 years of follow-up. In phase I of analyses, we compared expression of molecular markers of carcinogenesis in case and control adenomas, blind to case status. In phase II of analyses, patients were randomly divided into independent training and validation groups to develop a model for predicting case status. We found that seven markers [p53, p21, Cox-2, β-catenin (BCAT), DNA-dependent protein kinase (DNApkcs), survivin, and O6-methylguanine-DNA methyltransferase (MGMT)] were significantly associated with case status on unadjusted analyses, as well as analyses adjusted for age and advanced adenoma status (P < 0.01 for at least one marker component). When applied to the validation set, a predictive model using these seven markers showed substantial accuracy for identifying cases [area under the receiver operation characteristic curve (AUC), 0.83; 95% confidence interval (CI), 0.74-0.92]. A parsimonious model using three markers performed similarly to the seven-marker model (AUC, 0.84). In summary, we found that molecular markers of carcinogenesis distinguished adenomas from patients with and without colorectal cancer. Furthermore, we speculate that prospective studies using molecular markers to identify individuals with polyps at risk for future neoplasia are warranted. ©2014 American Association for Cancer Research.

A comparison of prognostic significance of strong ion gap (SIG) with other acid-base markers in the critically ill: a cohort study.

PubMed

Ho, Kwok M; Lan, Norris S H; Williams, Teresa A; Harahsheh, Yusra; Chapman, Andrew R; Dobb, Geoffrey J; Magder, Sheldon

2016-01-01

This cohort study compared the prognostic significance of strong ion gap (SIG) with other acid-base markers in the critically ill. The relationships between SIG, lactate, anion gap (AG), anion gap albumin-corrected (AG-corrected), base excess or strong ion difference-effective (SIDe), all obtained within the first hour of intensive care unit (ICU) admission, and the hospital mortality of 6878 patients were analysed. The prognostic significance of each acid-base marker, both alone and in combination with the Admission Mortality Prediction Model (MPM0 III) predicted mortality, were assessed by the area under the receiver operating characteristic curve (AUROC). Of the 6878 patients included in the study, 924 patients (13.4 %) died after ICU admission. Except for plasma chloride concentrations, all acid-base markers were significantly different between the survivors and non-survivors. SIG (with lactate: AUROC 0.631, confidence interval [CI] 0.611-0.652; without lactate: AUROC 0.521, 95 % CI 0.500-0.542) only had a modest ability to predict hospital mortality, and this was no better than using lactate concentration alone (AUROC 0.701, 95 % 0.682-0.721). Adding AG-corrected or SIG to a combination of lactate and MPM0 III predicted risks also did not substantially improve the latter's ability to differentiate between survivors and non-survivors. Arterial lactate concentrations explained about 11 % of the variability in the observed mortality, and it was more important than SIG (0.6 %) and SIDe (0.9 %) in predicting hospital mortality after adjusting for MPM0 III predicted risks. Lactate remained as the strongest predictor for mortality in a sensitivity multivariate analysis, allowing for non-linearity of all acid-base markers. The prognostic significance of SIG was modest and inferior to arterial lactate concentration for the critically ill. Lactate concentration should always be considered regardless whether physiological, base excess or physical-chemical approach is used to interpret acid-base disturbances in critically ill patients.

ADM3, TFF3 and LGALS3 are discriminative molecular markers in fine-needle aspiration biopsies of benign and malignant thyroid tumours

PubMed Central

Karger, S; Krause, K; Gutknecht, M; Schierle, K; Graf, D; Steinert, F; Dralle, H; Führer, D

2012-01-01

Background: Previously, we reported a six-marker gene set, which allowed a molecular discrimination of benign and malignant thyroid tumours. Now, we evaluated these markers in fine-needle aspiration biopsies (FNAB) in a prospective, independent series of thyroid tumours with proven histological outcome. Methods: Quantitative RT–PCR was performed (ADM3, HGD1, LGALS3, PLAB, TFF3, TG) in the needle wash-out of 156 FNAB of follicular adenoma (FA), adenomatous nodules, follicular and papillary thyroid cancers (TC) and normal thyroid tissues (NT). Results: Significant expression differences were found for TFF3, HGD1, ADM3 and LGALS3 in FNAB of TC compared with benign thyroid nodules and NT. Using two-marker gene sets, a specific FNAB distinction of benign and malignant tumours was achieved with negative predictive values (NPV) up to 0.78 and positive predictive values (PPV) up to 0.84. Two FNAB marker gene combinations (ADM3/TFF3; ADM3/ACTB) allowed the distinction of FA and malignant follicular neoplasia with NPV up to 0.94 and PPV up to 0.86. Conclusion: We demonstrate that molecular FNAB diagnosis of benign and malignant thyroid tumours including follicular neoplasia is possible with recently identified marker gene combinations. We propose multi-centre FNAB studies on these markers to bring this promising diagnostic tool closer to clinical practice. PMID:22223087

Inflammatory Markers and Preeclampsia: A Systematic Review.

PubMed

Black, Kathleen Darrah; Horowitz, June Andrews

Preeclampsia (PE), a serious and variable pregnancy complication affecting 5%-10% of the obstetric population, has an undetermined etiology, yet inflammation is concomitant with its development, particularly in relation to endothelial dysfunction. The purpose of this systematic review was to examine the published evidence concerning an association between PE and inflammatory markers for their usefulness in the prediction or early identification of women with PE in antepartum clinical settings. In this systematic review, we used the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. The Cumulative Index for Nursing and Allied Health and MEDLINE/OVID were the electronic databases used for identifying published articles. We placed no time limit on the publication year. The search generated 798 articles. After removing duplicates, screening abstracts, and conducting full-text reviews, we retained 73 articles and examined 57 unique markers. This review shows that C-reactive protein and the cytokines, specifically the proinflammatory markers IL-6, IL-8, and tumor necrosis factor alpha, garner the most support as potential inflammatory markers for clinical surveillance of PE, particularly during the second and third trimesters. Based on this review, we cannot recommend any single inflammatory marker for routine clinical use to predict/identify PE onset or progression. Research is recommended to examine a combination panel of these four inflammatory markers both with and without clinical risk factors toward the goal of translation to practice.

Functional Analysis and Marker Development of TaCRT-D Gene in Common Wheat (Triticum aestivum L.).

PubMed

Wang, Jiping; Li, Runzhi; Mao, Xinguo; Jing, Ruilian

2017-01-01

Calreticulin (CRT), an endoplasmic reticulum (ER)-localized Ca 2+ -binding/buffering protein, is highly conserved and extensively expressed in animal and plant cells. To understand the function of CRTs in wheat ( Triticum aestivum L.), particularly their roles in stress tolerance, we cloned the full-length genomic sequence of the TaCRT-D isoform from D genome of common hexaploid wheat, and characterized its function by transgenic Arabidopsis system. TaCRT-D exhibited different expression patterns in wheat seedling under different abiotic stresses. Transgenic Arabidopsis plants overexpressing ORF of TaCRT-D displayed more tolerance to drought, cold, salt, mannitol, and other abiotic stresses at both seed germination and seedling stages, compared with the wild-type controls. Furthermore, DNA polymorphism analysis and gene mapping were employed to develop the functional markers of this gene for marker-assistant selection in wheat breeding program. One SNP, S440 (T→C) was detected at the TaCRT-D locus by genotyping a wheat recombinant inbred line (RIL) population (114 lines) developed from Opata 85 × W7984. The TaCRT-D was then fine mapped between markers Xgwm645 and Xgwm664 on chromosome 3DL, corresponding to genetic distances of 3.5 and 4.4 cM, respectively, using the RIL population and Chinese Spring nulli-tetrasomic lines. Finally, the genome-specific and allele-specific markers were developed for the TaCRT-D gene. These findings indicate that TaCRT-D function importantly in plant stress responses, providing a gene target for genetic engineering to increase plant stress tolerance and the functional markers of TaCRT-D for marker-assistant selection in wheat breeding.

Functional Analysis and Marker Development of TaCRT-D Gene in Common Wheat (Triticum aestivum L.)

PubMed Central

Wang, Jiping; Li, Runzhi; Mao, Xinguo; Jing, Ruilian

2017-01-01

Calreticulin (CRT), an endoplasmic reticulum (ER)-localized Ca2+-binding/buffering protein, is highly conserved and extensively expressed in animal and plant cells. To understand the function of CRTs in wheat (Triticum aestivum L.), particularly their roles in stress tolerance, we cloned the full-length genomic sequence of the TaCRT-D isoform from D genome of common hexaploid wheat, and characterized its function by transgenic Arabidopsis system. TaCRT-D exhibited different expression patterns in wheat seedling under different abiotic stresses. Transgenic Arabidopsis plants overexpressing ORF of TaCRT-D displayed more tolerance to drought, cold, salt, mannitol, and other abiotic stresses at both seed germination and seedling stages, compared with the wild-type controls. Furthermore, DNA polymorphism analysis and gene mapping were employed to develop the functional markers of this gene for marker-assistant selection in wheat breeding program. One SNP, S440 (T→C) was detected at the TaCRT-D locus by genotyping a wheat recombinant inbred line (RIL) population (114 lines) developed from Opata 85 × W7984. The TaCRT-D was then fine mapped between markers Xgwm645 and Xgwm664 on chromosome 3DL, corresponding to genetic distances of 3.5 and 4.4 cM, respectively, using the RIL population and Chinese Spring nulli-tetrasomic lines. Finally, the genome-specific and allele-specific markers were developed for the TaCRT-D gene. These findings indicate that TaCRT-D function importantly in plant stress responses, providing a gene target for genetic engineering to increase plant stress tolerance and the functional markers of TaCRT-D for marker-assistant selection in wheat breeding. PMID:28955354

Whole genome de novo sequencing and genome annotation of the world popular cultivated edible mushroom, Lentinula edodes.

PubMed

Shim, Donghwan; Park, Sin-Gi; Kim, Kangmin; Bae, Wonsil; Lee, Gir Won; Ha, Byeong-Suk; Ro, Hyeon-Su; Kim, Myungkil; Ryoo, Rhim; Rhee, Sung-Keun; Nou, Ill-Sup; Koo, Chang-Duck; Hong, Chang Pyo; Ryu, Hojin

2016-04-10

Lentinula edodes, the popular shiitake mushroom, is one of the most important cultivated edible mushrooms. It is used as a food and for medicinal purposes. Here, we present the 46.1 Mb draft genome of L. edodes, comprising 13,028 predicted gene models. The genome assembly consists of 31 scaffolds. Gene annotation provides key information about various signaling pathways and secondary metabolites. This genomic information should help establish the molecular genetic markers for MAS/MAB and increase our understanding of the genome structure and function. Copyright © 2016 Elsevier B.V. All rights reserved.

Inferential modeling and predictive feedback control in real-time motion compensation using the treatment couch during radiotherapy

NASA Astrophysics Data System (ADS)

Qiu, Peng; D'Souza, Warren D.; McAvoy, Thomas J.; Liu, K. J. Ray

2007-09-01

Tumor motion induced by respiration presents a challenge to the reliable delivery of conformal radiation treatments. Real-time motion compensation represents the technologically most challenging clinical solution but has the potential to overcome the limitations of existing methods. The performance of a real-time couch-based motion compensation system is mainly dependent on two aspects: the ability to infer the internal anatomical position and the performance of the feedback control system. In this paper, we propose two novel methods for the two aspects respectively, and then combine the proposed methods into one system. To accurately estimate the internal tumor position, we present partial-least squares (PLS) regression to predict the position of the diaphragm using skin-based motion surrogates. Four radio-opaque markers were placed on the abdomen of patients who underwent fluoroscopic imaging of the diaphragm. The coordinates of the markers served as input variables and the position of the diaphragm served as the output variable. PLS resulted in lower prediction errors compared with standard multiple linear regression (MLR). The performance of the feedback control system depends on the system dynamics and dead time (delay between the initiation and execution of the control action). While the dynamics of the system can be inverted in a feedback control system, the dead time cannot be inverted. To overcome the dead time of the system, we propose a predictive feedback control system by incorporating forward prediction using least-mean-square (LMS) and recursive least square (RLS) filtering into the couch-based control system. Motion data were obtained using a skin-based marker. The proposed predictive feedback control system was benchmarked against pure feedback control (no forward prediction) and resulted in a significant performance gain. Finally, we combined the PLS inference model and the predictive feedback control to evaluate the overall performance of the feedback control system. Our results show that, with the tumor motion unknown but inferred by skin-based markers through the PLS model, the predictive feedback control system was able to effectively compensate intra-fraction motion.

An in vitro study of the accuracy of a new protocol for planning distraction osteogenesis of the mandible.

PubMed

Gateno, J; Allen, M E; Teichgraeber, J F; Messersmith, M L

2000-09-01

The purpose of this study was to determine the in vitro accuracy of a new protocol for distraction osteogenesis of the mandible that involves a planning process and a surgical technique. An experimental design was developed to simulate distraction osteogenesis on stereolithographic models of patients with craniofacial deformities. All patients had previously undergone 3-dimensional computerized scans of the craniofacial skeleton. The data from these scans were used to generate stereolithographic models. Before the fabrication of the models, the computed tomography (CT) data were manipulated to add a series of rulers and markers to the models. The 3-dimensional computerized scans were also used as the basis of the planning process. They were imported into an animation software (3D-Studio Max; Discreet, Montreal, Canada), and a virtual distractor was built and installed on the model, and the osteotomies and distraction processes were simulated. Finally, a recipe for sequencing the linear and angular changes of the distractor were calculated. A surgical technique was developed to facilitate the precise installation of the distractor as indicated in the presurgical plan. The transfer of information regarding pin position and orientation from the computer model to the patient was accomplished by creating a surgical template. This template was designed in the computer and fabricated by use of stereolithography. Mock surgery was performed on the stereolithographic models, and the results were compared with those predicted by the computer. The difference between the actual position and the predicted position was recorded. On the X-axis, the difference between the predicted position for the condylar marker and the actual position of the marker on the stereolithographic models was 0.6 +/- 1.1 mm. On the Y-axis, the difference between the predicted position for the condylar marker and the actual position of the marker on the stereolithographic models was -0.9 +/- 2.6. On the Z-axis, the difference between the predicted position for the condylar marker and the actual position of the marker on the stereolithographic models was 0.04 +/- 0.8 mm. There was excellent correlation between the predicted and the actual measurements for the X, Y, and Z axes: 0.98, 0.93, and 0.98, respectively. The results indicate that the combination of this planning process and surgical technique was very accurate. This in vitro study is the first step in determining the clinical usefulness of this protocol. If the results of this study are validated in clinical practice, this protocol will allow clinicians to improve the clinical outcomes of patients treated with distraction osteogenesis.

Effect of Co-segregating Markers on High-Density Genetic Maps and Prediction of Map Expansion Using Machine Learning Algorithms.

PubMed

N'Diaye, Amidou; Haile, Jemanesh K; Fowler, D Brian; Ammar, Karim; Pozniak, Curtis J

2017-01-01

Advances in sequencing and genotyping methods have enable cost-effective production of high throughput single nucleotide polymorphism (SNP) markers, making them the choice for linkage mapping. As a result, many laboratories have developed high-throughput SNP assays and built high-density genetic maps. However, the number of markers may, by orders of magnitude, exceed the resolution of recombination for a given population size so that only a minority of markers can accurately be ordered. Another issue attached to the so-called 'large p, small n' problem is that high-density genetic maps inevitably result in many markers clustering at the same position (co-segregating markers). While there are a number of related papers, none have addressed the impact of co-segregating markers on genetic maps. In the present study, we investigated the effects of co-segregating markers on high-density genetic map length and marker order using empirical data from two populations of wheat, Mohawk × Cocorit (durum wheat) and Norstar × Cappelle Desprez (bread wheat). The maps of both populations consisted of 85% co-segregating markers. Our study clearly showed that excess of co-segregating markers can lead to map expansion, but has little effect on markers order. To estimate the inflation factor (IF), we generated a total of 24,473 linkage maps (8,203 maps for Mohawk × Cocorit and 16,270 maps for Norstar × Cappelle Desprez). Using seven machine learning algorithms, we were able to predict with an accuracy of 0.7 the map expansion due to the proportion of co-segregating markers. For example in Mohawk × Cocorit, with 10 and 80% co-segregating markers the length of the map inflated by 4.5 and 16.6%, respectively. Similarly, the map of Norstar × Cappelle Desprez expanded by 3.8 and 11.7% with 10 and 80% co-segregating markers. With the increasing number of markers on SNP-chips, the proportion of co-segregating markers in high-density maps will continue to increase making map expansion unavoidable. Therefore, we suggest developers improve linkage mapping algorithms for efficient analysis of high-throughput data. This study outlines a practical strategy to estimate the IF due to the proportion of co-segregating markers and outlines a method to scale the length of the map accordingly.

Effect of Co-segregating Markers on High-Density Genetic Maps and Prediction of Map Expansion Using Machine Learning Algorithms

PubMed Central

N’Diaye, Amidou; Haile, Jemanesh K.; Fowler, D. Brian; Ammar, Karim; Pozniak, Curtis J.

2017-01-01

Advances in sequencing and genotyping methods have enable cost-effective production of high throughput single nucleotide polymorphism (SNP) markers, making them the choice for linkage mapping. As a result, many laboratories have developed high-throughput SNP assays and built high-density genetic maps. However, the number of markers may, by orders of magnitude, exceed the resolution of recombination for a given population size so that only a minority of markers can accurately be ordered. Another issue attached to the so-called ‘large p, small n’ problem is that high-density genetic maps inevitably result in many markers clustering at the same position (co-segregating markers). While there are a number of related papers, none have addressed the impact of co-segregating markers on genetic maps. In the present study, we investigated the effects of co-segregating markers on high-density genetic map length and marker order using empirical data from two populations of wheat, Mohawk × Cocorit (durum wheat) and Norstar × Cappelle Desprez (bread wheat). The maps of both populations consisted of 85% co-segregating markers. Our study clearly showed that excess of co-segregating markers can lead to map expansion, but has little effect on markers order. To estimate the inflation factor (IF), we generated a total of 24,473 linkage maps (8,203 maps for Mohawk × Cocorit and 16,270 maps for Norstar × Cappelle Desprez). Using seven machine learning algorithms, we were able to predict with an accuracy of 0.7 the map expansion due to the proportion of co-segregating markers. For example in Mohawk × Cocorit, with 10 and 80% co-segregating markers the length of the map inflated by 4.5 and 16.6%, respectively. Similarly, the map of Norstar × Cappelle Desprez expanded by 3.8 and 11.7% with 10 and 80% co-segregating markers. With the increasing number of markers on SNP-chips, the proportion of co-segregating markers in high-density maps will continue to increase making map expansion unavoidable. Therefore, we suggest developers improve linkage mapping algorithms for efficient analysis of high-throughput data. This study outlines a practical strategy to estimate the IF due to the proportion of co-segregating markers and outlines a method to scale the length of the map accordingly. PMID:28878789

Dynamic range of frontoparietal functional modulation is associated with working memory capacity limitations in older adults.

PubMed

Hakun, Jonathan G; Johnson, Nathan F

2017-11-01

Older adults tend to over-activate regions throughout frontoparietal cortices and exhibit a reduced range of functional modulation during WM task performance compared to younger adults. While recent evidence suggests that reduced functional modulation is associated with poorer task performance, it remains unclear whether reduced range of modulation is indicative of general WM capacity-limitations. In the current study, we examined whether the range of functional modulation observed over multiple levels of WM task difficulty (N-Back) predicts in-scanner task performance and out-of-scanner psychometric estimates of WM capacity. Within our sample (60-77years of age), age was negatively associated with frontoparietal modulation range. Individuals with greater modulation range exhibited more accurate N-Back performance. In addition, despite a lack of significant relationships between N-Back and complex span task performance, range of frontoparietal modulation during the N-Back significantly predicted domain-general estimates of WM capacity. Consistent with previous cross-sectional findings, older individuals with less modulation range exhibited greater activation at the lowest level of task difficulty but less activation at the highest levels of task difficulty. Our results are largely consistent with existing theories of neurocognitive aging (e.g. CRUNCH) but focus attention on dynamic range of functional modulation asa novel marker of WM capacity-limitations in older adults. Copyright © 2017 Elsevier Inc. All rights reserved.

UNC-18 Promotes Both the Anterograde Trafficking and Synaptic Function of Syntaxin

PubMed Central

McEwen, Jason M.

2008-01-01

The SM protein UNC-18 has been proposed to regulate several aspects of secretion, including synaptic vesicle docking, priming, and fusion. Here, we show that UNC-18 has a chaperone function in neurons, promoting anterograde transport of the plasma membrane soluble N-ethylmaleimide-sensitive factor attachment protein receptor (SNARE) protein Syntaxin-1. In unc-18 mutants, UNC-64 (Caenorhabditis elegans Syntaxin-1) accumulates in neuronal cell bodies. Colocalization studies and analysis of carbohydrate modifications both suggest that this accumulation occurs in the endoplasmic reticulum. This trafficking defect is specific for UNC-64 Syntaxin-1, because 14 other SNARE proteins and two active zone markers were unaffected. UNC-18 binds to Syntaxin through at least two mechanisms: binding to closed Syntaxin, or to the N terminus of Syntaxin. It is unclear which of these binding modes mediates UNC-18 function in neurons. The chaperone function of UNC-18 was eliminated in double mutants predicted to disrupt both modes of Syntaxin binding, but it was unaffected in single mutants. By contrast, mutations predicted to disrupt UNC-18 binding to the N terminus of Syntaxin caused significant defects in locomotion behavior and responsiveness to cholinesterase inhibitors. Collectively, these results demonstrate the UNC-18 acts as a molecular chaperone for Syntaxin transport in neurons and that the two modes of UNC-18 binding to Syntaxin are involved in different aspects of UNC-18 function. PMID:18596236

Functions of Discourse Markers "Ano and Sono" in Written Dialogue.

ERIC Educational Resources Information Center

Fujita, Yasuko

Through examination of the discourse markers "ano" and "sono" in Japanese, this paper explores how these linguistic devices function differently in conversation. The focus of this analysis is the mental and social functions through which a speaker attempts to achieve an interpersonal rapport with a listener. In particular, the…

Association of Kidney Function and Albuminuria With Prevalent and Incident Hypertension: The Atherosclerosis Risk in Communities (ARIC) Study

PubMed Central

Huang, Minxuan; Matsushita, Kunihiro; Sang, Yingying; Ballew, Shoshana H.; Astor, Brad C.; Coresh, Josef

2014-01-01

Background Decreased kidney function and kidney damage may predate hypertension, but only a few studies have investigated both types of markers simultaneously, and these studies have obtained conflicting results. Study Design Cross-sectional for prevalent and prospective observational study for incident hypertension. Setting & Participants 9,593 participants from the Atherosclerosis Risk in Communities (ARIC) Study, aged 53-75 years during 1996-1998. Predictors Several markers of kidney function (estimated glomerular filtration rate [eGFR] using serum creatinine and/or cystatin C and two novel markers [β-trace protein and β2-microglobulin]) and one marker of kidney damage (urinary albumin-creatinine ratio [ACR]). Every kidney marker was categorized by its quintiles (top quintile as a reference for eGFRs and bottom quintile for the rest). Outcomes Prevalent and incident hypertension. Measurements Prevalence and HRs of hypertension based on modified Poisson regression and Cox proportional hazards models, respectively. Results There were 4,378 participants (45.6%) with prevalent hypertension at baseline and 2,175 incident hypertension cases during a median follow-up of 9.8 years. While all five kidney function markers were significantly associated with prevalent hypertension, prevalent hypertension was most notably associated with higher ACR (adjusted prevalence ratio, 1.60 [95% CI, 1.50-1.71] for the highest vs lowest ACR quintile). Similarly, ACR was consistently associated with incident hypertension in all models tested (adjusted HR, 1.28 [95% CI, 1.10-1.49] for top quintile), while kidney function markers demonstrated significant associations in some, but not all, models. Even mildly increased ACR (9.14-14.0 mg/g) was significantly associated with incident hypertension. Limitations Self-reported use of antihypertensive medication for defining incident hypertension, single assessment of kidney markers, and relatively narrow age range. Conclusions Although all kidney markers were associated with prevalent hypertension, only elevated albuminuria was consistently associated with incident hypertension, suggesting that kidney damage is more closely related to hypertension than moderate reduction in overall kidney function. PMID:25151408

How to personalize ovarian stimulation in clinical practice.

PubMed

Sighinolfi, Giovanna; Grisendi, Valentina; La Marca, Antonio

2017-09-01

Controlled ovarian stimulation (COS) in in vitro fertilization (IVF) cycles is the starting point from which couple's prognosis depends. Individualization in follicle-stimulating hormone (FSH) starting dose and protocol used is based on ovarian response prediction, which depends on ovarian reserve. Anti-Müllerian hormone levels and the antral follicle count are considered the most accurate and reliable markers of ovarian reserve. A literature search was performed for studies that addressed the ability of ovarian reserve markers to predict poor and high ovarian response in assisted reproductive technology cycles. According to the predicted response to ovarian stimulation (poor- normal- or high- response), it is possible to counsel couples before treatment about the prognosis, and also to individualize ovarian stimulation protocols, choosing among GnRH-agonists or antagonists for endogenous FSH suppression, and the FSH starting dose in order to decrease the risk of cycle cancellation and ovarian hyperstimulation syndrome. In this review we discuss how to choose the best COS therapy, based on ovarian reserve markers, in order to enhance chances in IVF.

Circulating tumour DNA methylation markers for diagnosis and prognosis of hepatocellular carcinoma

NASA Astrophysics Data System (ADS)

Xu, Rui-Hua; Wei, Wei; Krawczyk, Michal; Wang, Wenqiu; Luo, Huiyan; Flagg, Ken; Yi, Shaohua; Shi, William; Quan, Qingli; Li, Kang; Zheng, Lianghong; Zhang, Heng; Caughey, Bennett A.; Zhao, Qi; Hou, Jiayi; Zhang, Runze; Xu, Yanxin; Cai, Huimin; Li, Gen; Hou, Rui; Zhong, Zheng; Lin, Danni; Fu, Xin; Zhu, Jie; Duan, Yaou; Yu, Meixing; Ying, Binwu; Zhang, Wengeng; Wang, Juan; Zhang, Edward; Zhang, Charlotte; Li, Oulan; Guo, Rongping; Carter, Hannah; Zhu, Jian-Kang; Hao, Xiaoke; Zhang, Kang

2017-11-01

An effective blood-based method for the diagnosis and prognosis of hepatocellular carcinoma (HCC) has not yet been developed. Circulating tumour DNA (ctDNA) carrying cancer-specific genetic and epigenetic aberrations may enable a noninvasive `liquid biopsy' for diagnosis and monitoring of cancer. Here, we identified an HCC-specific methylation marker panel by comparing HCC tissue and normal blood leukocytes and showed that methylation profiles of HCC tumour DNA and matched plasma ctDNA are highly correlated. Using cfDNA samples from a large cohort of 1,098 HCC patients and 835 normal controls, we constructed a diagnostic prediction model that showed high diagnostic specificity and sensitivity (P < 0.001) and was highly correlated with tumour burden, treatment response, and stage. Additionally, we constructed a prognostic prediction model that effectively predicted prognosis and survival (P < 0.001). Together, these findings demonstrate in a large clinical cohort the utility of ctDNA methylation markers in the diagnosis, surveillance, and prognosis of HCC.

Is hepcidin a new cardiovascular risk marker in polycystic ovary syndrome?

PubMed

Gözdemir, Elif; Kaygusuz, Ikbal; Kafalı, Hasan

2013-01-01

Polycystic ovary syndrome (PCOS) is associated with reproductive and metabolic abnormalities and carries a number of cardiovascular risk factors. Low-grade chronic inflammation has been thought to play a role in the pathogenesis of atherosclerosis and PCOS patients have an increased rate of subclinical inflammation. In the present study, considering the major role that hepcidin plays in the regulation of iron metabolism and as an inflammatory marker, we investigated hepcidin in PCOS patients and its role in predicting cardiovascular disease (CVD) development. Forty patients with PCOS and 40 age- and body mass index-matched healthy controls were included in the study. Iron metabolites, insulin resistance (IR), inflammatory markers and hepcidin levels were analyzed. IR parameters, inflammatory markers, iron parameters and hepcidin levels were similar between the PCOS and control groups. While the inflammatory markers were significantly high in the overweight and obese PCOS subgroup, the hepcidin levels were also high but this elevation was not statistically significant. Obesity is the principle mechanism of chronic inflammation and IR in PCOS patients. C-reactive protein and interleukin-6 should be used to predict and follow the risk of CVD development in PCOS cases. Hepcidin may be used as an additional marker in the follow-up of PCOS patients in the future. Copyright © 2013 S. Karger AG, Basel.

Review of commonly used clinical pathology parameters for general gastrointestinal disease with emphasis on small animals.

PubMed

Steiner, Jörg M

2014-01-01

A wide variety of markers are available to assess the function and pathology of the gastrointestinal (GI) tract. This review describes some of these markers with special emphasis given to markers used in dogs and cats. Small intestinal disease can be confirmed and localized by the measurement of serum concentrations of folate and cobalamin. Fecal α1-proteinase inhibitor concentration can increase in individuals with excessive GI protein loss. A wide variety of inflammatory markers are available for a variety of species that can be used to assess the inflammatory activity of various types of inflammatory cells in the GI tract, although most of these markers assess neutrophilic inflammation, such as neutrophil elastase, calprotectin, or S100A12. N-methylhistamine can serve as a marker of mast cell infiltration. Markers for lymphocytic or eosinophilic inflammation are currently under investigation. Exocrine pancreatic function can be assessed by measurement of serum concentrations of pancreatic lipase immunoreactivity (PLI) and trypsin-like immunoreactivity (TLI). Serum PLI concentration is increased in individuals with pancreatitis and has been shown to be highly specific for exocrine pancreatic function and sensitive for pancreatitis. Serum TLI concentration is severely decreased in individuals with exocrine pancreatic insufficiency.

Introduction: circadian rhythm and its disruption: impact on reproductive function.

PubMed

Casper, Robert F; Gladanac, Bojana

2014-08-01

Almost all forms of life have predictable daily or circadian rhythms in molecular, endocrine, and behavioral functions. In mammals, a central pacemaker located in the suprachiasmatic nuclei coordinates the timing of these rhythms. Daily light exposure that affects the retina of the eye directly influences this area, which is required to align endogenous processes to the appropriate time of day. The present "Views and Reviews" articles discuss the influence of circadian rhythms, especially nightly secretion of melatonin, on reproductive function and parturition. In addition, an examination is made of problems that arise from recurrent circadian rhythm disruption associated with changes in light exposure patterns common to modern day society. Finally, a possible solution to prevent disruptions in circadian phase markers by filtering out short wavelengths from nocturnal light is reviewed. Copyright © 2014 American Society for Reproductive Medicine. Published by Elsevier Inc. All rights reserved.

Improvement of marker-based predictability of Apparent Amylose Content in japonica rice through GBSSI allele mining

PubMed Central

2014-01-01

Background Apparent Amylose Content (AAC), regulated by the Waxy gene, represents the key determinant of rice cooking properties. In occidental countries high AAC rice represents the most requested market class but the availability of molecular markers allowing specific selection of high AAC varieties is limited. Results In this study, the effectiveness of available molecular markers in predicting AAC was evaluated in a collection of 127 rice accessions (125 japonica ssp. and 2 indica ssp.) characterized by AAC values from glutinous to 26%. The analyses highlighted the presence of several different allelic patterns identifiable by a few molecular markers, and two of them, i.e., the SNPs at intron1 and exon 6, were able to explain a maximum of 79.5% of AAC variation. However, the available molecular markers haplotypes did not provide tools for predicting accessions with AAC higher than 24.5%. To identify additional polymorphisms, the re-sequencing of the Waxy gene and 1kbp of the putative upstream regulatory region was performed in 21 genotypes representing all the AAC classes identified. Several previously un-characterized SNPs were identified and four of them were used to develop dCAPS markers. Conclusions The addition of the SNPs newly identified slightly increased the AAC explained variation and allowed the identification of a haplotype almost unequivocally associated to AAC higher than 24.5%. Haplotypes at the waxy locus were also associated to grain length and length/width (L/W) ratio. In particular, the SNP at the first intron, which identifies the Wx a and Wx b alleles, was associated with differences in the width of the grain, the L/W ratio and the length of the kernel, most likely as a result of human selection. PMID:24383761

Sudden cardiac death and pump failure death prediction in chronic heart failure by combining ECG and clinical markers in an integrated risk model

PubMed Central

Orini, Michele; Mincholé, Ana; Monasterio, Violeta; Cygankiewicz, Iwona; Bayés de Luna, Antonio; Martínez, Juan Pablo

2017-01-01

Background Sudden cardiac death (SCD) and pump failure death (PFD) are common endpoints in chronic heart failure (CHF) patients, but prevention strategies are different. Currently used tools to specifically predict these endpoints are limited. We developed risk models to specifically assess SCD and PFD risk in CHF by combining ECG markers and clinical variables. Methods The relation of clinical and ECG markers with SCD and PFD risk was assessed in 597 patients enrolled in the MUSIC (MUerte Súbita en Insuficiencia Cardiaca) study. ECG indices included: turbulence slope (TS), reflecting autonomic dysfunction; T-wave alternans (TWA), reflecting ventricular repolarization instability; and T-peak-to-end restitution (ΔαTpe) and T-wave morphology restitution (TMR), both reflecting changes in dispersion of repolarization due to heart rate changes. Standard clinical indices were also included. Results The indices with the greatest SCD prognostic impact were gender, New York Heart Association (NYHA) class, left ventricular ejection fraction, TWA, ΔαTpe and TMR. For PFD, the indices were diabetes, NYHA class, ΔαTpe and TS. Using a model with only clinical variables, the hazard ratios (HRs) for SCD and PFD for patients in the high-risk group (fifth quintile of risk score) with respect to patients in the low-risk group (first and second quintiles of risk score) were both greater than 4. HRs for SCD and PFD increased to 9 and 11 when using a model including only ECG markers, and to 14 and 13, when combining clinical and ECG markers. Conclusion The inclusion of ECG markers capturing complementary pro-arrhythmic and pump failure mechanisms into risk models based only on standard clinical variables substantially improves prediction of SCD and PFD in CHF patients. PMID:29020031

Sudden cardiac death and pump failure death prediction in chronic heart failure by combining ECG and clinical markers in an integrated risk model.

PubMed

Ramírez, Julia; Orini, Michele; Mincholé, Ana; Monasterio, Violeta; Cygankiewicz, Iwona; Bayés de Luna, Antonio; Martínez, Juan Pablo; Laguna, Pablo; Pueyo, Esther

2017-01-01

Sudden cardiac death (SCD) and pump failure death (PFD) are common endpoints in chronic heart failure (CHF) patients, but prevention strategies are different. Currently used tools to specifically predict these endpoints are limited. We developed risk models to specifically assess SCD and PFD risk in CHF by combining ECG markers and clinical variables. The relation of clinical and ECG markers with SCD and PFD risk was assessed in 597 patients enrolled in the MUSIC (MUerte Súbita en Insuficiencia Cardiaca) study. ECG indices included: turbulence slope (TS), reflecting autonomic dysfunction; T-wave alternans (TWA), reflecting ventricular repolarization instability; and T-peak-to-end restitution (ΔαTpe) and T-wave morphology restitution (TMR), both reflecting changes in dispersion of repolarization due to heart rate changes. Standard clinical indices were also included. The indices with the greatest SCD prognostic impact were gender, New York Heart Association (NYHA) class, left ventricular ejection fraction, TWA, ΔαTpe and TMR. For PFD, the indices were diabetes, NYHA class, ΔαTpe and TS. Using a model with only clinical variables, the hazard ratios (HRs) for SCD and PFD for patients in the high-risk group (fifth quintile of risk score) with respect to patients in the low-risk group (first and second quintiles of risk score) were both greater than 4. HRs for SCD and PFD increased to 9 and 11 when using a model including only ECG markers, and to 14 and 13, when combining clinical and ECG markers. The inclusion of ECG markers capturing complementary pro-arrhythmic and pump failure mechanisms into risk models based only on standard clinical variables substantially improves prediction of SCD and PFD in CHF patients.

Individual classification of ADHD patients by integrating multiscale neuroimaging markers and advanced pattern recognition techniques

PubMed Central

Cheng, Wei; Ji, Xiaoxi; Zhang, Jie; Feng, Jianfeng

2012-01-01

Accurate classification or prediction of the brain state across individual subject, i.e., healthy, or with brain disorders, is generally a more difficult task than merely finding group differences. The former must be approached with highly informative and sensitive biomarkers as well as effective pattern classification/feature selection approaches. In this paper, we propose a systematic methodology to discriminate attention deficit hyperactivity disorder (ADHD) patients from healthy controls on the individual level. Multiple neuroimaging markers that are proved to be sensitive features are identified, which include multiscale characteristics extracted from blood oxygenation level dependent (BOLD) signals, such as regional homogeneity (ReHo) and amplitude of low-frequency fluctuations. Functional connectivity derived from Pearson, partial, and spatial correlation is also utilized to reflect the abnormal patterns of functional integration, or, dysconnectivity syndromes in the brain. These neuroimaging markers are calculated on either voxel or regional level. Advanced feature selection approach is then designed, including a brain-wise association study (BWAS). Using identified features and proper feature integration, a support vector machine (SVM) classifier can achieve a cross-validated classification accuracy of 76.15% across individuals from a large dataset consisting of 141 healthy controls and 98 ADHD patients, with the sensitivity being 63.27% and the specificity being 85.11%. Our results show that the most discriminative features for classification are primarily associated with the frontal and cerebellar regions. The proposed methodology is expected to improve clinical diagnosis and evaluation of treatment for ADHD patient, and to have wider applications in diagnosis of general neuropsychiatric disorders. PMID:22888314

Genomic selection accuracies within and between environments and small breeding groups in white spruce.

PubMed

Beaulieu, Jean; Doerksen, Trevor K; MacKay, John; Rainville, André; Bousquet, Jean

2014-12-02

Genomic selection (GS) may improve selection response over conventional pedigree-based selection if markers capture more detailed information than pedigrees in recently domesticated tree species and/or make it more cost effective. Genomic prediction accuracies using 1748 trees and 6932 SNPs representative of as many distinct gene loci were determined for growth and wood traits in white spruce, within and between environments and breeding groups (BG), each with an effective size of Ne ≈ 20. Marker subsets were also tested. Model fits and/or cross-validation (CV) prediction accuracies for ridge regression (RR) and the least absolute shrinkage and selection operator models approached those of pedigree-based models. With strong relatedness between CV sets, prediction accuracies for RR within environment and BG were high for wood (r = 0.71-0.79) and moderately high for growth (r = 0.52-0.69) traits, in line with trends in heritabilities. For both classes of traits, these accuracies achieved between 83% and 92% of those obtained with phenotypes and pedigree information. Prediction into untested environments remained moderately high for wood (r ≥ 0.61) but dropped significantly for growth (r ≥ 0.24) traits, emphasizing the need to phenotype in all test environments and model genotype-by-environment interactions for growth traits. Removing relatedness between CV sets sharply decreased prediction accuracies for all traits and subpopulations, falling near zero between BGs with no known shared ancestry. For marker subsets, similar patterns were observed but with lower prediction accuracies. Given the need for high relatedness between CV sets to obtain good prediction accuracies, we recommend to build GS models for prediction within the same breeding population only. Breeding groups could be merged to build genomic prediction models as long as the total effective population size does not exceed 50 individuals in order to obtain high prediction accuracy such as that obtained in the present study. A number of markers limited to a few hundred would not negatively impact prediction accuracies, but these could decrease more rapidly over generations. The most promising short-term approach for genomic selection would likely be the selection of superior individuals within large full-sib families vegetatively propagated to implement multiclonal forestry.

Expression of anger and ill health in two cultures: an examination of inflammation and cardiovascular risk.

PubMed

Kitayama, Shinobu; Park, Jiyoung; Boylan, Jennifer Morozink; Miyamoto, Yuri; Levine, Cynthia S; Markus, Hazel Rose; Karasawa, Mayumi; Coe, Christopher L; Kawakami, Norito; Love, Gayle D; Ryff, Carol D

2015-02-01

Expression of anger is associated with biological health risk (BHR) in Western cultures. However, recent evidence documenting culturally divergent functions of the expression of anger suggests that its link with BHR may be moderated by culture. To test this prediction, we examined large probability samples of both Japanese and Americans using multiple measures of BHR, including pro-inflammatory markers (interleukin-6 and C-reactive protein) and indices of cardiovascular malfunction (systolic blood pressure and ratio of total to HDL cholesterol). We found that the link between greater expression of anger and increased BHR was robust for Americans. As predicted, however, this association was diametrically reversed for Japanese, among whom greater expression of anger predicted reduced BHR. These patterns were unique to the expressive facet of anger and remained after we controlled for age, gender, health status, health behaviors, social status, and reported experience of negative emotions. Implications for sociocultural modulation of bio-physiological responses are discussed. © The Author(s) 2015.

Anger Expression and Ill-Health in Two Cultures: An Examination of Inflammation and Cardiovascular Risk

PubMed Central

Kitayama, Shinobu; Park, Jiyoung; Boylan, Jennifer Morozink; Miyamoto, Yuri; Levine, Cynthia S.; Markus, Hazel Rose; Karasawa, Mayumi; Coe, Christopher L.; Kawakami, Norito; Love, Gayle D.; Ryff, Carol D.

2014-01-01

Expression of anger is associated with biological health risk (BHR) in Western cultures. However, recent evidence documenting culturally divergent functions of anger expression suggests that the link between anger expression and BHR may be moderated by culture. To test this prediction, we examined large probability samples of both Japanese and Americans with multiple measures of BHR including pro-inflammatory markers (Interleukin-6 and C-reactive protein) and indices of cardiovascular malfunction (systolic blood pressure and Total/HDL cholesterol ratio). We found that the positive link between anger expression and increased BHR was robust for Americans. As predicted, however, this association was diametrically reversed for Japanese, with anger expression predicting reduced BHR. The pattern was unique to the expressive facet of anger and remained after controlling for age, gender, health status, health behaviors, social status, and reported experience of negative emotions. Implications for socio-cultural modulation of bio-physiological responses are discussed. PMID:25564521

Associability-modulated loss learning is increased in posttraumatic stress disorder

PubMed Central

Brown, Vanessa M; Zhu, Lusha; Wang, John M; Frueh, B Christopher

2018-01-01

Disproportionate reactions to unexpected stimuli in the environment are a cardinal symptom of posttraumatic stress disorder (PTSD). Here, we test whether these heightened responses are associated with disruptions in distinct components of reinforcement learning. Specifically, using functional neuroimaging, a loss-learning task, and a computational model-based approach, we assessed the mechanistic hypothesis that overreactions to stimuli in PTSD arise from anomalous gating of attention during learning (i.e., associability). Behavioral choices of combat-deployed veterans with and without PTSD were fit to a reinforcement learning model, generating trial-by-trial prediction errors (signaling unexpected outcomes) and associability values (signaling attention allocation to the unexpected outcomes). Neural substrates of associability value and behavioral parameter estimates of associability updating, but not prediction error, increased with PTSD during loss learning. Moreover, the interaction of PTSD severity with neural markers of associability value predicted behavioral choices. These results indicate that increased attention-based learning may underlie aspects of PTSD and suggest potential neuromechanistic treatment targets. PMID:29313489

Neural and computational processes underlying dynamic changes in self-esteem

PubMed Central

Rutledge, Robb B; Moutoussis, Michael; Dolan, Raymond J

2017-01-01

Self-esteem is shaped by the appraisals we receive from others. Here, we characterize neural and computational mechanisms underlying this form of social influence. We introduce a computational model that captures fluctuations in self-esteem engendered by prediction errors that quantify the difference between expected and received social feedback. Using functional MRI, we show these social prediction errors correlate with activity in ventral striatum/subgenual anterior cingulate cortex, while updates in self-esteem resulting from these errors co-varied with activity in ventromedial prefrontal cortex (vmPFC). We linked computational parameters to psychiatric symptoms using canonical correlation analysis to identify an ‘interpersonal vulnerability’ dimension. Vulnerability modulated the expression of prediction error responses in anterior insula and insula-vmPFC connectivity during self-esteem updates. Our findings indicate that updating of self-evaluative beliefs relies on learning mechanisms akin to those used in learning about others. Enhanced insula-vmPFC connectivity during updating of those beliefs may represent a marker for psychiatric vulnerability. PMID:29061228

Neural and computational processes underlying dynamic changes in self-esteem.

PubMed

Will, Geert-Jan; Rutledge, Robb B; Moutoussis, Michael; Dolan, Raymond J

2017-10-24

Self-esteem is shaped by the appraisals we receive from others. Here, we characterize neural and computational mechanisms underlying this form of social influence. We introduce a computational model that captures fluctuations in self-esteem engendered by prediction errors that quantify the difference between expected and received social feedback. Using functional MRI, we show these social prediction errors correlate with activity in ventral striatum/subgenual anterior cingulate cortex, while updates in self-esteem resulting from these errors co-varied with activity in ventromedial prefrontal cortex (vmPFC). We linked computational parameters to psychiatric symptoms using canonical correlation analysis to identify an 'interpersonal vulnerability' dimension. Vulnerability modulated the expression of prediction error responses in anterior insula and insula-vmPFC connectivity during self-esteem updates. Our findings indicate that updating of self-evaluative beliefs relies on learning mechanisms akin to those used in learning about others. Enhanced insula-vmPFC connectivity during updating of those beliefs may represent a marker for psychiatric vulnerability.

The vacuole system is a significant intracellular pathway for longitudinal solute transport in basidiomycete fungi.

PubMed

Darrah, P R; Tlalka, M; Ashford, A; Watkinson, S C; Fricker, M D

2006-07-01

Mycelial fungi have a growth form which is unique among multicellular organisms. The data presented here suggest that they have developed a unique solution to internal solute translocation involving a complex, extended vacuole. In all filamentous fungi examined, this extended vacuole forms an interconnected network, dynamically linked by tubules, which has been hypothesized to act as an internal distribution system. We have tested this hypothesis directly by quantifying solute movement within the organelle by photobleaching a fluorescent vacuolar marker. Predictive simulation models were then used to determine the transport characteristics over extended length scales. This modeling showed that the vacuolar organelle forms a functionally important, bidirectional diffusive transport pathway over distances of millimeters to centimeters. Flux through the pathway is regulated by the dynamic tubular connections involving homotypic fusion and fission. There is also a strongly predicted interaction among vacuolar organization, predicted diffusion transport distances, and the architecture of the branching colony margin.

Implementation of a computer-aided detection tool for quantification of intracranial radiologic markers on brain CT images

NASA Astrophysics Data System (ADS)

Aghaei, Faranak; Ross, Stephen R.; Wang, Yunzhi; Wu, Dee H.; Cornwell, Benjamin O.; Ray, Bappaditya; Zheng, Bin

2017-03-01

Aneurysmal subarachnoid hemorrhage (aSAH) is a form of hemorrhagic stroke that affects middle-aged individuals and associated with significant morbidity and/or mortality especially those presenting with higher clinical and radiologic grades at the time of admission. Previous studies suggested that blood extravasated after aneurysmal rupture was a potentially clinical prognosis factor. But all such studies used qualitative scales to predict prognosis. The purpose of this study is to develop and test a new interactive computer-aided detection (CAD) tool to detect, segment and quantify brain hemorrhage and ventricular cerebrospinal fluid on non-contrasted brain CT images. First, CAD segments brain skull using a multilayer region growing algorithm with adaptively adjusted thresholds. Second, CAD assigns pixels inside the segmented brain region into one of three classes namely, normal brain tissue, blood and fluid. Third, to avoid "black-box" approach and increase accuracy in quantification of these two image markers using CT images with large noise variation in different cases, a graphic User Interface (GUI) was implemented and allows users to visually examine segmentation results. If a user likes to correct any errors (i.e., deleting clinically irrelevant blood or fluid regions, or fill in the holes inside the relevant blood or fluid regions), he/she can manually define the region and select a corresponding correction function. CAD will automatically perform correction and update the computed data. The new CAD tool is now being used in clinical and research settings to estimate various quantitatively radiological parameters/markers to determine radiological severity of aSAH at presentation and correlate the estimations with various homeostatic/metabolic derangements and predict clinical outcome.

Beta-blockers influence the short-term and long-term prognostic information of natriuretic peptides and catecholamines in chronic heart failure independent from specific agents.

PubMed

Frankenstein, Lutz; Nelles, Manfred; Slavutsky, Maxim; Schellberg, Dieter; Doesch, Andreas; Katus, Hugo; Remppis, Andrew; Zugck, Christian

2007-10-01

In chronic heart failure (CHF), the physiologic effects of natriuretic peptides and catecholamines are interdependent. Furthermore, reports state an agent-dependent effect of individual beta-blockers on biomarkers. Data on the short-term and long-term predictive power comparing these biomarkers as well as accounting for the influence of beta-blocker treatment both on the marker or the resultant prognostic information are scarce. We included 513 consecutive patients with systolic CHF, measured atrial natriuretic peptide (ANP), N-terminal prohormone brain natriuretic peptide (NTproBNP), noradrenaline, and adrenaline, and monitored them for 90 +/- 25 months. Death or the combination of death and cardiac transplantation at 1 year, 5 years, and overall follow-up were considered end points. Compared with patients not taking beta-blockers, patients taking beta-blockers had significantly lower levels of catecholamines but not natriuretic peptides. Only for adrenaline was the amount of this effect related to the specific beta-blocker chosen. Receiver operating characteristic curves demonstrated superior prognostic accuracy for NTproBNP both at the 1- and 5-year follow-up compared with ANP, noradrenaline, and adrenaline. In multivariate analysis including established risk markers (New York Heart Association functional class, left ventricular ejection fraction, peak oxygen uptake, and 6-minute walk test), of all neurohumoral parameters, only NTproBNP remained an independent predictor for both end points. Long-term beta-blocker therapy is associated with decreased levels of plasma catecholamines but not natriuretic peptides. This effect is independent from the actual beta-blocker chosen for natriuretic peptides and noradrenaline. In multivariate analysis, both for short-term and long-term prediction of mortality or the combined end point of death and cardiac transplantation, only NTproBNP remained independent from established clinical risk markers.

The significance and predictive value of free light chains in the urine of patients with chronic inflammatory rheumatic disease.

PubMed

Bramlage, Carsten Paul; Froelich, Britta; Wallbach, Manuel; Minguet, Joan; Grupp, Clemens; Deutsch, Cornelia; Bramlage, Peter; Koziolek, Michael; Müller, Gerhard Anton

2016-12-01

In patients with rheumatic diseases, reliable markers for determining disease activity are scarce. One potential parameter is the level of immunoglobulin free light chains (FLCs), which is known to be elevated in the blood of patients with certain rheumatic diseases. Few studies have quantified FLCs in urine, a convenient source of test sample, in patients with different rheumatic diseases. We carried out a retrospective analysis of patients with rheumatic disease attending the University hospital of Goettingen, Germany. Subjects were included if they had urine levels of both κ and λ FLCs available and did not have myeloma. Data regarding systemic inflammation and kidney function were recorded, and FLC levels were correlated with inflammatory markers. Of the 382 patients with rheumatic disease, 40.1 % had chronic polyarthritis, 21.2 % connective tissue disease, 18.6 % spondyloarthritis and 15.7 % vasculitis. Elevated levels of κ FLCs were found for 84 % of patients and elevated λ for 52.7 %. For the patients with rheumatoid arthritis, FLCs correlated with C-reactive protein (κ, r = 0.368, p < 0.001; λ, r = 0.398, p < 0.001) and erythrocyte sedimentation rate (κ, r = 0.692, p < 0.001; λ, r = 0.612, p < 0.001). Patients being treated with rituximab displayed FLC levels similar to those of the reference group. There were clear elevations in both κ and λ FLCs in patients with rheumatic disease, but not in κ/λ ratio. The correlation between FLCs and inflammatory markers in patients with rheumatoid arthritis demonstrates their potential for predicting disease activity.

Combined panel of serum human tissue kallikreins and CA-125 for the detection of epithelial ovarian cancer.

PubMed

Koh, Stephen Chee Liang; Huak, Chan Yiong; Lutan, Delfi; Marpuang, Johny; Ketut, Suwiyoga; Budiana, Nyoma Gede; Saleh, Agustria Zainu; Aziz, Mohamad Farid; Winarto, Hariyono; Pradjatmo, Heru; Hoan, Nguyen Khac Han; Thanh, Pham Viet; Choolani, Mahesh

2012-07-01

To determine the predictive accuracy of the combined panels of serum human tissue kallikreins (hKs) and CA-125 for the detection of epithelial ovarian cancer. Serum specimens collected from 5 Indonesian centers and 1 Vietnamese center were analyzed for CA-125, hK6, and hK10 levels. A total of 375 specimens from patients presenting with ovarian tumors, which include 156 benign cysts, 172 epithelial ovarian cancers (stage I/II, n=72; stage III/IV, n=100), 36 germ cell tumors and 11 borderline tumors, were included in the study analysis. Receiver operating characteristic analysis were performed to determine the cutoffs for age, CA-125, hK6, and hK10. Sensitivity, specificity, negative, and positive predictive values were determined for various combinations of the biomarkers. The levels of hK6 and hK10 were significantly elevated in ovarian cancer cases compared to benign cysts. Combination of 3 markers, age/CA-125/hk6 or CA-125/hk6/hk10, showed improved specificity (100%) and positive predictive value (100%) for prediction of ovarian cancer, when compared to the performance of single markers having 80-92% specificity and 74-87% positive predictive value. Four-marker combination, age/CA-125/hK6/hK10 also showed 100% specificity and 100% positive predictive value, although it demonstrated low sensitivity (11.9%) and negative predictive value (52.8%). The combination of human tissue kallikreins and CA-125 showed potential for improving prediction of epithelial ovarian cancer in patients presenting with ovarian tumors.

Meta-analysis of the predictive value of DNA aneuploidy in malignant transformation of oral potentially malignant disorders.

PubMed

Alaizari, Nader A; Sperandio, Marcelo; Odell, Edward W; Peruzzo, Daiane; Al-Maweri, Sadeq A

2018-02-01

DNA aneuploidy is an imbalance of chromosomal DNA content that has been highlighted as a predictor of biological behavior and risk of malignant transformation. To date, DNA aneuploidy in oral potentially malignant diseases (OPMD) has been shown to correlate strongly with severe dysplasia and high-risk lesions that appeared non-dysplastic can be identified by ploidy analysis. Nevertheless, the prognostic value of DNA aneuploidy in predicting malignant transformation of OPMD remains to be validated. The aim of this meta-analysis was to assess the role of DNA aneuploidy in predicting malignant transformation in OPMD. The questions addressed were (i) Is DNA aneuploidy a useful marker to predict malignant transformation in OPMD? (ii) Is DNA diploidy a useful negative marker of malignant transformation in OPMD? These questions were addressed using the PECO method. Five studies assessing aneuploidy as a risk marker of malignant change were pooled into the meta-analysis. Aneuploidy was found to be associated with a 3.12-fold increased risk to progress into cancer (RR=3.12, 95% CI 1.86-5.24). Based on the five studies meta-analyzed, "no malignant progression" was more likely to occur in DNA diploid OPMD by 82% when compared to aneuploidy (RR=0.18, 95% CI 0.08-0.41). In conclusion, aneuploidy is a useful marker of malignant transformation in OPMD, although a diploid result should be interpreted with caution. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Perturbed threat monitoring following a traumatic event predicts risk for post-traumatic stress disorder.

PubMed

Naim, R; Wald, I; Lior, A; Pine, D S; Fox, N A; Sheppes, G; Halpern, P; Bar-Haim, Y

2014-07-01

Post-traumatic stress disorder (PTSD) is a chronic and difficult to treat psychiatric disorder. Objective, performance-based diagnostic markers that uniquely index risk for PTSD above and beyond subjective self-report markers could inform attempts to improve prevention and early intervention. We evaluated the predictive value of threat-related attention bias measured immediately after a potentially traumatic event, as a risk marker for PTSD at a 3-month follow-up. We measured the predictive contribution of attentional threat bias above and beyond that of the more established marker of risk for PTSD, self-reported psychological dissociation. Dissociation symptoms and threat-related attention bias were measured in 577 motor vehicle accident (MVA) survivors (mean age = 35.02 years, 356 males) within 24 h of admission to an emergency department (ED) of a large urban hospital. PTSD symptoms were assessed at a 3-month follow-up using the Clinician-Administered PTSD Scale (CAPS). Self-reported dissociation symptoms significantly accounted for 16% of the variance in PTSD at follow-up, and attention bias toward threat significantly accounted for an additional 4% of the variance in PTSD. Threat-related attention bias can be reliably measured in the context of a hospital ED and significantly predicts risk for later PTSD. Possible mechanisms underlying the association between threat bias following a potentially traumatic event and risk for PTSD are discussed. The potential application of an attention bias modification treatment (ABMT) tailored to reduce risk for PTSD is suggested.

Relative value of diverse brain MRI and blood-based biomarkers for predicting cognitive decline in the elderly

NASA Astrophysics Data System (ADS)

Madsen, Sarah K.; Ver Steeg, Greg; Daianu, Madelaine; Mezher, Adam; Jahanshad, Neda; Nir, Talia M.; Hua, Xue; Gutman, Boris A.; Galstyan, Aram; Thompson, Paul M.

2016-03-01

Cognitive decline accompanies many debilitating illnesses, including Alzheimer's disease (AD). In old age, brain tissue loss also occurs along with cognitive decline. Although blood tests are easier to perform than brain MRI, few studies compare brain scans to standard blood tests to see which kinds of information best predict future decline. In 504 older adults from the Alzheimer's Disease Neuroimaging Initiative (ADNI), we first used linear regression to assess the relative value of different types of data to predict cognitive decline, including 196 blood panel biomarkers, 249 MRI biomarkers obtained from the FreeSurfer software, demographics, and the AD-risk gene APOE. A subset of MRI biomarkers was the strongest predictor. There was no specific blood marker that increased predictive accuracy on its own, we found that a novel unsupervised learning method, CorEx, captured weak correlations among blood markers, and the resulting clusters offered unique predictive power.

Biological Marker Analysis as Part of the CIBERES-RTIC Cancer-SEPAR Strategic Project on Lung Cancer.

PubMed

Monsó, Eduard; Montuenga, Luis M; Sánchez de Cos, Julio; Villena, Cristina

2015-09-01

The aim of the Clinical and Molecular Staging of Stage I-IIp Lung Cancer Project is to identify molecular variables that improve the prognostic and predictive accuracy of TMN classification in stage I/IIp non-small cell lung cancer (NSCLC). Clinical data and lung tissue, tumor and blood samples will be collected from 3 patient cohorts created for this purpose. The prognostic protein signature will be validated from these samples, and micro-RNA, ALK, Ros1, Pdl-1, and TKT, TKTL1 y G6PD expression will be analyzed. Tissue inflammatory markers and stromal cell markers will also be analyzed. Methylation of p16, DAPK, RASSF1a, APC and CDH13 genes in the tissue samples will be determined, and inflammatory markers in peripheral blood will also be analyzed. Variables that improve the prognostic and predictive accuracy of TNM in NSCLC by molecular staging may be identified from this extensive analytical panel. Copyright © 2014 SEPAR. Published by Elsevier Espana. All rights reserved.

De novo Assembly of the Indo-Pacific Humpback Dolphin Leucocyte Transcriptome to Identify Putative Genes Involved in the Aquatic Adaptation and Immune Response

PubMed Central

Xia, Jia; Yang, Lili; Chen, Jialin; Wu, Yuping; Yi, Meisheng

2013-01-01

Background The Indo-Pacific humpback dolphin (Sousa chinensis), a marine mammal species inhabited in the waters of Southeast Asia, South Africa and Australia, has attracted much attention because of the dramatic decline in population size in the past decades, which raises the concern of extinction. So far, this species is poorly characterized at molecular level due to little sequence information available in public databases. Recent advances in large-scale RNA sequencing provide an efficient approach to generate abundant sequences for functional genomic analyses in the species with un-sequenced genomes. Principal Findings We performed a de novo assembly of the Indo-Pacific humpback dolphin leucocyte transcriptome by Illumina sequencing. 108,751 high quality sequences from 47,840,388 paired-end reads were generated, and 48,868 and 46,587 unigenes were functionally annotated by BLAST search against the NCBI non-redundant and Swiss-Prot protein databases (E-value<10−5), respectively. In total, 16,467 unigenes were clustered into 25 functional categories by searching against the COG database, and BLAST2GO search assigned 37,976 unigenes to 61 GO terms. In addition, 36,345 unigenes were grouped into 258 KEGG pathways. We also identified 9,906 simple sequence repeats and 3,681 putative single nucleotide polymorphisms as potential molecular markers in our assembled sequences. A large number of unigenes were predicted to be involved in immune response, and many genes were predicted to be relevant to adaptive evolution and cetacean-specific traits. Conclusion This study represented the first transcriptome analysis of the Indo-Pacific humpback dolphin, an endangered species. The de novo transcriptome analysis of the unique transcripts will provide valuable sequence information for discovery of new genes, characterization of gene expression, investigation of various pathways and adaptive evolution, as well as identification of genetic markers. PMID:24015242

De novo assembly of the Indo-Pacific humpback dolphin leucocyte transcriptome to identify putative genes involved in the aquatic adaptation and immune response.

PubMed

Gui, Duan; Jia, Kuntong; Xia, Jia; Yang, Lili; Chen, Jialin; Wu, Yuping; Yi, Meisheng

2013-01-01

The Indo-Pacific humpback dolphin (Sousa chinensis), a marine mammal species inhabited in the waters of Southeast Asia, South Africa and Australia, has attracted much attention because of the dramatic decline in population size in the past decades, which raises the concern of extinction. So far, this species is poorly characterized at molecular level due to little sequence information available in public databases. Recent advances in large-scale RNA sequencing provide an efficient approach to generate abundant sequences for functional genomic analyses in the species with un-sequenced genomes. We performed a de novo assembly of the Indo-Pacific humpback dolphin leucocyte transcriptome by Illumina sequencing. 108,751 high quality sequences from 47,840,388 paired-end reads were generated, and 48,868 and 46,587 unigenes were functionally annotated by BLAST search against the NCBI non-redundant and Swiss-Prot protein databases (E-value<10(-5)), respectively. In total, 16,467 unigenes were clustered into 25 functional categories by searching against the COG database, and BLAST2GO search assigned 37,976 unigenes to 61 GO terms. In addition, 36,345 unigenes were grouped into 258 KEGG pathways. We also identified 9,906 simple sequence repeats and 3,681 putative single nucleotide polymorphisms as potential molecular markers in our assembled sequences. A large number of unigenes were predicted to be involved in immune response, and many genes were predicted to be relevant to adaptive evolution and cetacean-specific traits. This study represented the first transcriptome analysis of the Indo-Pacific humpback dolphin, an endangered species. The de novo transcriptome analysis of the unique transcripts will provide valuable sequence information for discovery of new genes, characterization of gene expression, investigation of various pathways and adaptive evolution, as well as identification of genetic markers.

Noninvasive scoring system for significant inflammation related to chronic hepatitis B

NASA Astrophysics Data System (ADS)

Hong, Mei-Zhu; Ye, Linglong; Jin, Li-Xin; Ren, Yan-Dan; Yu, Xiao-Fang; Liu, Xiao-Bin; Zhang, Ru-Mian; Fang, Kuangnan; Pan, Jin-Shui

2017-03-01

Although a liver stiffness measurement-based model can precisely predict significant intrahepatic inflammation, transient elastography is not commonly available in a primary care center. Additionally, high body mass index and bilirubinemia have notable effects on the accuracy of transient elastography. The present study aimed to create a noninvasive scoring system for the prediction of intrahepatic inflammatory activity related to chronic hepatitis B, without the aid of transient elastography. A total of 396 patients with chronic hepatitis B were enrolled in the present study. Liver biopsies were performed, liver histology was scored using the Scheuer scoring system, and serum markers and liver function were investigated. Inflammatory activity scoring models were constructed for both hepatitis B envelope antigen (+) and hepatitis B envelope antigen (-) patients. The sensitivity, specificity, positive predictive value, negative predictive value, and area under the curve were 86.00%, 84.80%, 62.32%, 95.39%, and 0.9219, respectively, in the hepatitis B envelope antigen (+) group and 91.89%, 89.86%, 70.83%, 97.64%, and 0.9691, respectively, in the hepatitis B envelope antigen (-) group. Significant inflammation related to chronic hepatitis B can be predicted with satisfactory accuracy by using our logistic regression-based scoring system.

Prediction of Poor Ovarian response by Biochemical and Biophysical Markers: A Logistic Regression Model.

PubMed

Jaiswar, S P; Natu, S M; Sujata; Sankhwar, P L; Manjari, Gupta

2015-12-01

To study correlation between ovarian reserve with biophysical markers (antral follicle count and ovarian volume) and biochemical markers (S. FSH, S. Inhibin B, and S. AMH) and use these markers to predict poor ovarian response to ovarian induction. This is a prospective observational study. One hundred infertile women attending the Obst & Gynae Dept, KGMU were recruited. Blood samples were collected on day 2/day 3 for assessment of S. FSH, S. Inhibin B, and S. AMH and TVS were done for antral follicle count and ovarian volume. Clomephene citrate 100 mg 1OD was given from day 2 to 6, and patients were followed up with serial USG measurements. The numbers of dominant follicles (> or = 14 mm) at the time of hCG administration were counted. Patients with <3 follicles in the 1st cycle were subjected to the 2nd cycle of clomephene 100 mg 1OD from day 2 to day 6 with Inj HMG 150 IU given i.m. starting from day 8 and every alternate day until at least one leading follicle attained ≥18 mm. Development of <3 follicles at end of the 2nd cycle was considered as poor response. Univariate analyses showed that s. inhibin B presented the highest (ROCAUC = 0.862) discriminating potential for predicting poor ovarian response, In multivariate logistic regression model, the variables age, FSH, AMH, INHIBIN B, and AFC remained significant, and the resulting model showed a predicted accuracy of 84.4 %. A derived multimarker computation by a logistic regression model for predicting poor ovarian response was obtained through this study. Thus, potential poor responders could be identified easily, and appropriate ovarian stimulation protocol could be devised for such pts.

Can one blood draw replace transrectal ultrasonography-estimated prostate volume to predict prostate cancer risk?

PubMed

Carlsson, Sigrid V; Peltola, Mari T; Sjoberg, Daniel; Schröder, Fritz H; Hugosson, Jonas; Pettersson, Kim; Scardino, Peter T; Vickers, Andrew J; Lilja, Hans; Roobol, Monique J

2013-09-01

To explore whether a panel of kallikrein markers in blood: total, free and intact prostate-specific antigen (PSA) and kallikrein-related peptidase 2, could be used as a non-invasive alternative for predicting prostate cancer on biopsy in a screening setting. The study cohort comprised previously unscreened men who underwent sextant biopsy owing to elevated PSA (≥3 ng/mL) in two different centres of the European Randomized Study of Screening for Prostate Cancer, Rotterdam (n = 2914) and Göteborg (n = 740). A statistical model, based on kallikrein markers, was compared with one based on established clinical factors for the prediction of biopsy outcome. The clinical tests were found to be no better than blood markers, with an area under the curve in favour of the blood measurements of 0.766 vs. 0.763 in Rotterdam and 0.809 vs. 0.774 in Göteborg. Adding digital rectal examination (DRE) or DRE plus transrectal ultrasonography (TRUS) volume to the markers improved discrimination, although the increases were small. Results were similar for predicting high-grade cancer. There was a strong correlation between the blood measurements and TRUS-estimated prostate volume (Spearman's correlation 0.60 in Rotterdam and 0.57 in Göteborg). In previously unscreened men, each with indication for biopsy, a statistical model based on kallikrein levels was similar to a clinical model in predicting prostate cancer in a screening setting, outside the day-to-day clinical practice. Whether a clinical approach can be replaced by laboratory analyses or used in combination with decision models (nomograms) is a clinical judgment that may vary from clinician to clinician depending on how they weigh the different advantages and disadvantages (harms, costs, time, invasiveness) of both approaches. © 2013 BJU International.

Mixed Model Methods for Genomic Prediction and Variance Component Estimation of Additive and Dominance Effects Using SNP Markers

PubMed Central

Da, Yang; Wang, Chunkao; Wang, Shengwen; Hu, Guo

2014-01-01

We established a genomic model of quantitative trait with genomic additive and dominance relationships that parallels the traditional quantitative genetics model, which partitions a genotypic value as breeding value plus dominance deviation and calculates additive and dominance relationships using pedigree information. Based on this genomic model, two sets of computationally complementary but mathematically identical mixed model methods were developed for genomic best linear unbiased prediction (GBLUP) and genomic restricted maximum likelihood estimation (GREML) of additive and dominance effects using SNP markers. These two sets are referred to as the CE and QM sets, where the CE set was designed for large numbers of markers and the QM set was designed for large numbers of individuals. GBLUP and associated accuracy formulations for individuals in training and validation data sets were derived for breeding values, dominance deviations and genotypic values. Simulation study showed that GREML and GBLUP generally were able to capture small additive and dominance effects that each accounted for 0.00005–0.0003 of the phenotypic variance and GREML was able to differentiate true additive and dominance heritability levels. GBLUP of the total genetic value as the summation of additive and dominance effects had higher prediction accuracy than either additive or dominance GBLUP, causal variants had the highest accuracy of GREML and GBLUP, and predicted accuracies were in agreement with observed accuracies. Genomic additive and dominance relationship matrices using SNP markers were consistent with theoretical expectations. The GREML and GBLUP methods can be an effective tool for assessing the type and magnitude of genetic effects affecting a phenotype and for predicting the total genetic value at the whole genome level. PMID:24498162

Mixed model methods for genomic prediction and variance component estimation of additive and dominance effects using SNP markers.

PubMed

Da, Yang; Wang, Chunkao; Wang, Shengwen; Hu, Guo

2014-01-01

We established a genomic model of quantitative trait with genomic additive and dominance relationships that parallels the traditional quantitative genetics model, which partitions a genotypic value as breeding value plus dominance deviation and calculates additive and dominance relationships using pedigree information. Based on this genomic model, two sets of computationally complementary but mathematically identical mixed model methods were developed for genomic best linear unbiased prediction (GBLUP) and genomic restricted maximum likelihood estimation (GREML) of additive and dominance effects using SNP markers. These two sets are referred to as the CE and QM sets, where the CE set was designed for large numbers of markers and the QM set was designed for large numbers of individuals. GBLUP and associated accuracy formulations for individuals in training and validation data sets were derived for breeding values, dominance deviations and genotypic values. Simulation study showed that GREML and GBLUP generally were able to capture small additive and dominance effects that each accounted for 0.00005-0.0003 of the phenotypic variance and GREML was able to differentiate true additive and dominance heritability levels. GBLUP of the total genetic value as the summation of additive and dominance effects had higher prediction accuracy than either additive or dominance GBLUP, causal variants had the highest accuracy of GREML and GBLUP, and predicted accuracies were in agreement with observed accuracies. Genomic additive and dominance relationship matrices using SNP markers were consistent with theoretical expectations. The GREML and GBLUP methods can be an effective tool for assessing the type and magnitude of genetic effects affecting a phenotype and for predicting the total genetic value at the whole genome level.

Distinguishing prognostic and predictive biomarkers: An information theoretic approach.

PubMed

Sechidis, Konstantinos; Papangelou, Konstantinos; Metcalfe, Paul D; Svensson, David; Weatherall, James; Brown, Gavin

2018-05-02

The identification of biomarkers to support decision-making is central to personalised medicine, in both clinical and research scenarios. The challenge can be seen in two halves: identifying predictive markers, which guide the development/use of tailored therapies; and identifying prognostic markers, which guide other aspects of care and clinical trial planning, i.e. prognostic markers can be considered as covariates for stratification. Mistakenly assuming a biomarker to be predictive, when it is in fact largely prognostic (and vice-versa) is highly undesirable, and can result in financial, ethical and personal consequences. We present a framework for data-driven ranking of biomarkers on their prognostic/predictive strength, using a novel information theoretic method. This approach provides a natural algebra to discuss and quantify the individual predictive and prognostic strength, in a self-consistent mathematical framework. Our contribution is a novel procedure, INFO+, which naturally distinguishes the prognostic vs predictive role of each biomarker and handles higher order interactions. In a comprehensive empirical evaluation INFO+ outperforms more complex methods, most notably when noise factors dominate, and biomarkers are likely to be falsely identified as predictive, when in fact they are just strongly prognostic. Furthermore, we show that our methods can be 1-3 orders of magnitude faster than competitors, making it useful for biomarker discovery in 'big data' scenarios. Finally, we apply our methods to identify predictive biomarkers on two real clinical trials, and introduce a new graphical representation that provides greater insight into the prognostic and predictive strength of each biomarker. R implementations of the suggested methods are available at https://github.com/sechidis. konstantinos.sechidis@manchester.ac.uk. Supplementary data are available at Bioinformatics online.

Intermediate Volume on Computed Tomography Imaging Defines a Fibrotic Compartment that Predicts Glomerular Filtration Rate Decline in Autosomal Dominant Polycystic Kidney Disease Patients

PubMed Central

Caroli, Anna; Antiga, Luca; Conti, Sara; Sonzogni, Aurelio; Fasolini, Giorgio; Ondei, Patrizia; Perico, Norberto; Remuzzi, Giuseppe; Remuzzi, Andrea

2011-01-01

Total kidney and cyst volumes have been used to quantify disease progression in autosomal dominant polycystic kidney disease (ADPKD), but a causal relationship with progression to renal failure has not been demonstrated. Advanced image processing recently allowed to quantify extracystic tissue, and to identify an additional tissue component named “intermediate,” appearing hypoenhanced on contrast-enhanced computed tomography (CT). The aim of this study is to provide a histological characterization of intermediate volume, investigate its relation with renal function, and provide preliminary evidence of its role in long-term prediction of functional loss. Three ADPKD patients underwent contrast-enhanced CT scans before nephrectomy. Histological samples of intermediate volume were drawn from the excised kidneys, and stained with hematoxylin and eosin and with saturated picrosirius solution for histological analysis. Intermediate volume showed major structural changes, characterized by tubular dilation and atrophy, microcysts, inflammatory cell infiltrate, vascular sclerosis, and extended peritubular interstitial fibrosis. A significant correlation (r = −0.69, P < 0.001) between relative intermediate volume and baseline renal function was found in 21 ADPKD patients. Long-term prediction of renal functional loss was investigated in an independent cohort of 13 ADPKD patients, followed for 3 to 8 years. Intermediate volume, but not total kidney or cyst volume, significantly correlated with glomerular filtration rate decline (r = −0.79, P < 0.005). These findings suggest that intermediate volume may represent a suitable surrogate marker of ADPKD progression and a novel therapeutic target. PMID:21683674

The 19q12 bladder cancer GWAS signal: association with cyclin E function and aggressive disease

PubMed Central

Fu, Yi-Ping; Kohaar, Indu; Moore, Lee E.; Lenz, Petra; Figueroa, Jonine D.; Tang, Wei; Porter-Gill, Patricia; Chatterjee, Nilanjan; Scott-Johnson, Alexandra; Garcia-Closas, Montserrat; Muchmore, Brian; Baris, Dalsu; Paquin, Ashley; Ylaya, Kris; Schwenn, Molly; Apolo, Andrea B.; Karagas, Margaret R.; Tarway, McAnthony; Johnson, Alison; Mumy, Adam; Schned, Alan; Guedez, Liliana; Jones, Michael A.; Kida, Masatoshi; Monawar Hosain, GM; Malats, Nuria; Kogevinas, Manolis; Tardon, Adonina; Serra, Consol; Carrato, Alfredo; Garcia-Closas, Reina; Lloreta, Josep; Wu, Xifeng; Purdue, Mark; Andriole, Gerald L.; Grubb, Robert L.; Black, Amanda; Landi, Maria T.; Caporaso, Neil E.; Vineis, Paolo; Siddiq, Afshan; Bueno-de-Mesquita, H. Bas; Trichopoulos, Dimitrios; Ljungberg, Börje; Severi, Gianluca; Weiderpass, Elisabete; Krogh, Vittorio; Dorronsoro, Miren; Travis, Ruth C.; Tjønneland, Anne; Brennan, Paul; Chang-Claude, Jenny; Riboli, Elio; Prescott, Jennifer; Chen, Constance; De Vivo, Immaculata; Govannucci, Edward; Hunter, David; Kraft, Peter; Lindstrom, Sara; Gapstur, Susan M.; Jacobs, Eric J.; Diver, W. Ryan; Albanes, Demetrius; Weinstein, Stephanie J.; Virtamo, Jarmo; Kooperberg, Charles; Hohensee, Chancellor; Rodabough, Rebecca J.; Cortessis, Victoria K.; Conti, David V.; Gago-Dominguez, Manuela; Stern, Mariana C.; Pike, Malcolm C.; Van Den Berg, David; Yuan, Jian-Min; Haiman, Christopher A.; Cussenot, Olivier; Cancel-Tassin, Geraldine; Roupret, Morgan; Comperat, Eva; Porru, Stefano; Carta, Angela; Pavanello, Sofia; Arici, Cecilia; Mastrangelo, Giuseppe; Grossman, H. Barton; Wang, Zhaoming; Deng, Xiang; Chung, Charles C.; Hutchinson, Amy; Burdette, Laurie; Wheeler, William; Fraumeni, Joseph; Chanock, Stephen J.; Hewitt, Stephen M.; Silverman, Debra T.; Rothman, Nathaniel; Prokunina-Olsson, Ludmila

2014-01-01

A genome-wide association study (GWAS) of bladder cancer identified a genetic marker rs8102137 within the 19q12 region as a novel susceptibility variant. This marker is located upstream of the CCNE1 gene, which encodes cyclin E, a cell cycle protein. We performed genetic fine mapping analysis of the CCNE1 region using data from two bladder cancer GWAS (5,942 cases and 10,857 controls). We found that the original GWAS marker rs8102137 represents a group of 47 linked SNPs (with r2≥0.7) associated with increased bladder cancer risk. From this group we selected a functional promoter variant rs7257330, which showed strong allele-specific binding of nuclear proteins in several cell lines. In both GWAS, rs7257330 was associated only with aggressive bladder cancer, with a combined per-allele odds ratio (OR) =1.18 (95%CI=1.09-1.27, p=4.67×10−5 vs. OR =1.01 (95%CI=0.93-1.10, p=0.79) for non-aggressive disease, with p=0.0015 for case-only analysis. Cyclin E protein expression analyzed in 265 bladder tumors was increased in aggressive tumors (p=0.013) and, independently, with each rs7257330-A risk allele (ptrend=0.024). Over-expression of recombinant cyclin E in cell lines caused significant acceleration of cell cycle. In conclusion, we defined the 19q12 signal as the first GWAS signal specific for aggressive bladder cancer. Molecular mechanisms of this genetic association may be related to cyclin E over-expression and alteration of cell cycle in carriers of CCNE1 risk variants. In combination with established bladder cancer risk factors and other somatic and germline genetic markers, the CCNE1 variants could be useful for inclusion into bladder cancer risk prediction models. PMID:25320178

CerealsDB 3.0: expansion of resources and data integration.

PubMed

Wilkinson, Paul A; Winfield, Mark O; Barker, Gary L A; Tyrrell, Simon; Bian, Xingdong; Allen, Alexandra M; Burridge, Amanda; Coghill, Jane A; Waterfall, Christy; Caccamo, Mario; Davey, Robert P; Edwards, Keith J

2016-06-24

The increase in human populations around the world has put pressure on resources, and as a consequence food security has become an important challenge for the 21st century. Wheat (Triticum aestivum) is one of the most important crops in human and livestock diets, and the development of wheat varieties that produce higher yields, combined with increased resistance to pests and resilience to changes in climate, has meant that wheat breeding has become an important focus of scientific research. In an attempt to facilitate these improvements in wheat, plant breeders have employed molecular tools to help them identify genes for important agronomic traits that can be bred into new varieties. Modern molecular techniques have ensured that the rapid and inexpensive characterisation of SNP markers and their validation with modern genotyping methods has produced a valuable resource that can be used in marker assisted selection. CerealsDB was created as a means of quickly disseminating this information to breeders and researchers around the globe. CerealsDB version 3.0 is an online resource that contains a wide range of genomic datasets for wheat that will assist plant breeders and scientists to select the most appropriate markers for use in marker assisted selection. CerealsDB includes a database which currently contains in excess of a million putative varietal SNPs, of which several hundreds of thousands have been experimentally validated. In addition, CerealsDB also contains new data on functional SNPs predicted to have a major effect on protein function and we have constructed a web service to encourage data integration and high-throughput programmatic access. CerealsDB is an open access website that hosts information on SNPs that are considered useful for both plant breeders and research scientists. The recent inclusion of web services designed to federate genomic data resources allows the information on CerealsDB to be more fully integrated with the WheatIS network and other biological databases.

Genome-wide generation and use of informative intron-spanning and intron-length polymorphism markers for high-throughput genetic analysis in rice

PubMed Central

Badoni, Saurabh; Das, Sweta; Sayal, Yogesh K.; Gopalakrishnan, S.; Singh, Ashok K.; Rao, Atmakuri R.; Agarwal, Pinky; Parida, Swarup K.; Tyagi, Akhilesh K.

2016-01-01

We developed genome-wide 84634 ISM (intron-spanning marker) and 16510 InDel-fragment length polymorphism-based ILP (intron-length polymorphism) markers from genes physically mapped on 12 rice chromosomes. These genic markers revealed much higher amplification-efficiency (80%) and polymorphic-potential (66%) among rice accessions even by a cost-effective agarose gel-based assay. A wider level of functional molecular diversity (17–79%) and well-defined precise admixed genetic structure was assayed by 3052 genome-wide markers in a structured population of indica, japonica, aromatic and wild rice. Six major grain weight QTLs (11.9–21.6% phenotypic variation explained) were mapped on five rice chromosomes of a high-density (inter-marker distance: 0.98 cM) genetic linkage map (IR 64 x Sonasal) anchored with 2785 known/candidate gene-derived ISM and ILP markers. The designing of multiple ISM and ILP markers (2 to 4 markers/gene) in an individual gene will broaden the user-preference to select suitable primer combination for efficient assaying of functional allelic variation/diversity and realistic estimation of differential gene expression profiles among rice accessions. The genomic information generated in our study is made publicly accessible through a user-friendly web-resource, “Oryza ISM-ILP marker” database. The known/candidate gene-derived ISM and ILP markers can be enormously deployed to identify functionally relevant trait-associated molecular tags by optimal-resource expenses, leading towards genomics-assisted crop improvement in rice. PMID:27032371

Dynamic hub load predicts cognitive decline after resective neurosurgery.

PubMed

Carbo, Ellen W S; Hillebrand, Arjan; van Dellen, Edwin; Tewarie, Prejaas; de Witt Hamer, Philip C; Baayen, Johannes C; Klein, Martin; Geurts, Jeroen J G; Reijneveld, Jaap C; Stam, Cornelis J; Douw, Linda

2017-02-07

Resective neurosurgery carries the risk of postoperative cognitive deterioration. The concept of 'hub (over)load', caused by (over)use of the most important brain regions, has been theoretically postulated in relation to symptomatology and neurological disease course, but lacks experimental confirmation. We investigated functional hub load and postsurgical cognitive deterioration in patients undergoing lesion resection. Patients (n = 28) underwent resting-state magnetoencephalography and neuropsychological assessments preoperatively and 1-year after lesion resection. We calculated stationary hub load score (SHub) indicating to what extent brain regions linked different subsystems; high SHub indicates larger processing pressure on hub regions. Dynamic hub load score (DHub) assessed its variability over time; low values, particularly in combination with high SHub values, indicate increased load, because of consistently high usage of hub regions. Hypothetically, increased SHub and decreased DHub relate to hub overload and thus poorer/deteriorating cognition. Between time points, deteriorating verbal memory performance correlated with decreasing upper alpha DHub. Moreover, preoperatively low DHub values accurately predicted declining verbal memory performance. In summary, dynamic hub load relates to cognitive functioning in patients undergoing lesion resection: postoperative cognitive decline can be tracked and even predicted using dynamic hub load, suggesting it may be used as a prognostic marker for tailored treatment planning.

Fetal alcohol spectrum disorders: gene-environment interactions, predictive biomarkers, and the relationship between structural alterations in the brain and functional outcomes.

PubMed

Reynolds, James N; Weinberg, Joanne; Clarren, Sterling; Beaulieu, Christian; Rasmussen, Carmen; Kobor, Michael; Dube, Marie-Pierre; Goldowitz, Daniel

2011-03-01

Prenatal alcohol exposure is a major, preventable cause of behavioral and cognitive deficits in children. Despite extensive research, a unique neurobehavioral profile for children affected by prenatal alcohol exposure remains elusive. A fundamental question that must be addressed is how genetic and environmental factors interact with gestational alcohol exposure to produce neurobehavioral and neurobiological deficits in children. The core objectives of the NeuroDevNet team in fetal alcohol spectrum disorders is to create an integrated research program of basic and clinical investigations that will (1) identify genetic and epigenetic modifications that may be predictive of the neurobehavioral and neurobiological dysfunctions in offspring induced by gestational alcohol exposure and (2) determine the relationship between structural alterations in the brain induced by gestational alcohol exposure and functional outcomes in offspring. The overarching hypothesis to be tested is that neurobehavioral and neurobiological dysfunctions induced by gestational alcohol exposure are correlated with the genetic background of the affected child and/or epigenetic modifications in gene expression. The identification of genetic and/or epigenetic markers that are predictive of the severity of behavioral and cognitive deficits in children affected by gestational alcohol exposure will have a profound impact on our ability to identify children at risk. Copyright © 2011 Elsevier Inc. All rights reserved.

Fetal Alcohol Spectrum Disorders: Gene-Environment Interactions, Predictive Biomarkers, and the Relationship Between Structural Alterations in the Brain and Functional Outcomes

PubMed Central

Reynolds, James N.; Weinberg, Joanne; Clarren, Sterling; Beaulieu, Christian; Rasmussen, Carmen; Kobor, Michael; Dube, Marie-Pierre; Goldowitz, Daniel

2016-01-01

Prenatal alcohol exposure is a major, preventable cause of behavioral and cognitive deficits in children. Despite extensive research, a unique neurobehavioral profile for children affected by prenatal alcohol exposure remains elusive. A fundamental question that must be addressed is how genetic and environmental factors interact with gestational alcohol exposure to produce neurobehavioral and neurobiological deficits in children. The core objectives of the NeuroDevNet team in fetal alcohol spectrum disorders is to create an integrated research program of basic and clinical investigations that will (1) identify genetic and epigenetic modifications that may be predictive of the neurobehavioral and neurobiological dysfunctions in offspring induced by gestational alcohol exposure and (2) determine the relationship between structural alterations in the brain induced by gestational alcohol exposure and functional outcomes in offspring. The overarching hypothesis to be tested is that neurobehavioral and neurobiological dysfunctions induced by gestational alcohol exposure are correlated with the genetic background of the affected child and/or epigenetic modifications in gene expression. The identification of genetic and/or epigenetic markers that are predictive of the severity of behavioral and cognitive deficits in children affected by gestational alcohol exposure will have a profound impact on our ability to identify children at risk. PMID:21575841

Endothelial dysfunction, vascular disease and stroke: the ARTICO study.

PubMed

Roquer, J; Segura, T; Serena, J; Castillo, J

2009-01-01

Endothelial dysfunction is a fundamental step in the atherosclerotic disease process. Its presence is a risk factor for the development of clinical events, and may represent a marker of atherothrombotic burden. Also, endothelial dysfunction contributes to enhanced plaque vulnerability, may trigger plaque rupture, and favors thrombus formation. The assessment of endothelial vasomotion is a useful marker of atherosclerotic vascular disease. There are different methods to assess endothelial function: endothelium-dependent vasodilatation brachial flow-mediated dilation, cerebrovascular reactivity to L-arginine, and the determination of some biomarkers such as microalbuminuria, platelet function, and C-reactive protein. Endothelial dysfunction has been observed in stroke patients and has been related to stroke physiopathology, stroke subtypes, clinical severity and outcome. Resting ankle-brachial index (ABI) is also considered an indicator of generalized atherosclerosis, and a low ABI is associated with an increase in stroke incidence in the elderly. Despite all these data, there are no studies analyzing the predictive value of ABI for new cardiovascular events in patients after suffering an acute ischemic stroke. ARTICO is an ongoing prospective, observational, multicenter study being performed in 50 Spanish hospitals. The aim of the ARTICO study is to evaluate the prognostic value of a pathological ABI (

Comparison of MeHg-induced toxicogenomic responses across in vivo and in vitro models used in developmental toxicology.

PubMed

Robinson, Joshua F; Theunissen, Peter T; van Dartel, Dorien A M; Pennings, Jeroen L; Faustman, Elaine M; Piersma, Aldert H

2011-09-01

Toxicogenomic evaluations may improve toxicity prediction of in vitro-based developmental models, such as whole embryo culture (WEC) and embryonic stem cells (ESC), by providing a robust mechanistic marker which can be linked with responses associated with developmental toxicity in vivo. While promising in theory, toxicogenomic comparisons between in vivo and in vitro models are complex due to inherent differences in model characteristics and experimental design. Determining factors which influence these global comparisons are critical in the identification of reliable mechanistic-based markers of developmental toxicity. In this study, we compared available toxicogenomic data assessing the impact of the known teratogen, methylmercury (MeHg) across a diverse set of in vitro and in vivo models to investigate the impact of experimental variables (i.e. model, dose, time) on our comparative assessments. We evaluated common and unique aspects at both the functional (Gene Ontology) and gene level of MeHg-induced response. At the functional level, we observed stronger similarity in MeHg-response between mouse embryos exposed in utero (2 studies), ESC, and WEC as compared to liver, brain and mouse embryonic fibroblast MeHg studies. These findings were strongly correlated to the presence of a MeHg-induced developmentally related gene signature. In addition, we identified specific MeHg-induced gene expression alterations associated with developmental signaling and heart development across WEC, ESC and in vivo systems. However, the significance of overlap between studies was highly dependent on traditional experimental variables (i.e. dose, time). In summary, we identify promising examples of unique gene expression responses which show in vitro-in vivo similarities supporting the relevance of in vitro developmental models for predicting in vivo developmental toxicity. Copyright © 2011 Elsevier Inc. All rights reserved.

Smad4/Fascin index is highly prognostic in patients with diffuse type EBV-associated gastric cancer.

PubMed

Son, Byoung Kwan; Kim, Dong-Hoon; Min, Kyueng-Whan; Kim, Eun-Kyung; Kwon, Mi Jung

2018-04-01

Gastric cancer is a heterogeneous disorder for which predicting clinical outcomes is challenging, although various biomarkers have been suggested. The Smad4 and Fascin proteins are known prognostic indicators of different types of malignancy. Smad4 primarily functions as a key regulator of tumor suppression, whereas Fascin exhibits oncogenic function by enhancing tumor infiltration. A combined marker based on these opposing roles may improve prognostic accuracy in gastric cancer. Smad4 and Fascin expression was assessed in tissue microarrays obtained from 285 primary gastric adenocarcinoma, 201 normal tissue, and 51 metastatic adenocarcinoma samples. A Smad4/Fascin index based on the relative expression of each protein was divided into low- and high-expression groups using receiver operating characteristic curves. We compared normal tissue, primary adenocarcinoma, and metastatic adenocarcinoma in Smad4 and Fascin expression and the differences in clinicopathological findings between low Smad4/Fascin and high Smad4/Fascin expression in gastric adenocarcinoma. High Smad4/Fascin expression was significantly associated with worse outcomes, such as old age, advanced T and N category, large tumor size, high histological grade, lymphatic and vascular invasion, and presence of Epstein-Barr virus (EBV) (all p < 0.05). Univariate and multivariate analyses revealed a significant relationship between disease-free or overall survival and Smad4/Fascin index in diffuse-type or EBV-associated gastric cancer (all p < 0.05). A dual marker system using Smad4 and Fascin may be a reliable indicator for predicting clinical outcomes in patients with diffuse-type or EBV-associated gastric cancer. Copyright © 2018 Elsevier GmbH. All rights reserved.

Pre- and Posttransplant IgA Anti-Fab Antibodies to Predict Long-term Kidney Graft Survival.

PubMed

Amirzargar, M A; Amirzargar, A; Basiri, A; Hajilooi, M; Roshanaei, G; Rajabi, G; Solgi, G

2015-05-01

Immunologic factors are reliable markers for allograft monitoring, because of their seminal role in rejection process. One of these factors is the immunoglobulin (Ig)A anti-Fab of the IgG antibody. This study aimed to evaluate the predictive value of pre- and posttransplant levels of this marker for kidney allograft function and survival. Sera samples of 59 living unrelated donor kidney recipients were collected before and after transplantation (days 7, 14, and 30) and investigated for IgA anti-Fab of IgG antibody levels using enzyme-linked immunosorbent assay in relation with allograft outcome. Among 59 patients, 15 cases (25%) including 10 with acute rejection and 5 with chronic rejection episodes showed graft failure during a mean of 5 years of follow-up. High posttransplant levels of IgA anti-Fab antibodies were observed more frequently in patients with stable graft function (SGF) compared with patients with graft failure (P = 2 × 10(-6)). None of patients with acute or chronic rejection episodes had high levels of IgA anti-Fab antibodies at day 30 posttransplant compared with the SGF group (P = 10(-6) and P = .01, respectively). In addition, high levels of IgA anti-Fab antibody correlated with lesser concentration of serum creatinine at 1 month posttransplantation (P = .01). Five-year graft survival was associated with high levels of pre- and posttransplant IgA anti-Fab antibodies (P = .02 and P = .003, respectively). Our findings indicate the protective effect of higher levels of IgA anti-Fab antibodies regarding to kidney allograft outcomes and long-term graft survival. Copyright © 2015 Elsevier Inc. All rights reserved.

SMA-MAP: a plasma protein panel for spinal muscular atrophy.

PubMed

Kobayashi, Dione T; Shi, Jing; Stephen, Laurie; Ballard, Karri L; Dewey, Ruth; Mapes, James; Chung, Brett; McCarthy, Kathleen; Swoboda, Kathryn J; Crawford, Thomas O; Li, Rebecca; Plasterer, Thomas; Joyce, Cynthia; Chung, Wendy K; Kaufmann, Petra; Darras, Basil T; Finkel, Richard S; Sproule, Douglas M; Martens, William B; McDermott, Michael P; De Vivo, Darryl C; Walker, Michael G; Chen, Karen S

2013-01-01

Spinal Muscular Atrophy (SMA) presents challenges in (i) monitoring disease activity and predicting progression, (ii) designing trials that allow rapid assessment of candidate therapies, and (iii) understanding molecular causes and consequences of the disease. Validated biomarkers of SMA motor and non-motor function would offer utility in addressing these challenges. Our objectives were (i) to discover additional markers from the Biomarkers for SMA (BforSMA) study using an immunoassay platform, and (ii) to validate the putative biomarkers in an independent cohort of SMA patients collected from a multi-site natural history study (NHS). BforSMA study plasma samples (N = 129) were analyzed by immunoassay to identify new analytes correlating to SMA motor function. These immunoassays included the strongest candidate biomarkers identified previously by chromatography. We selected 35 biomarkers to validate in an independent cohort SMA type 1, 2, and 3 samples (N = 158) from an SMA NHS. The putative biomarkers were tested for association to multiple motor scales and to pulmonary function, neurophysiology, strength, and quality of life measures. We implemented a Tobit model to predict SMA motor function scores. 12 of the 35 putative SMA biomarkers were significantly associated (p<0.05) with motor function, with a 13(th) analyte being nearly significant. Several other analytes associated with non-motor SMA outcome measures. From these 35 biomarkers, 27 analytes were selected for inclusion in a commercial panel (SMA-MAP) for association with motor and other functional measures. Discovery and validation using independent cohorts yielded a set of SMA biomarkers significantly associated with motor function and other measures of SMA disease activity. A commercial SMA-MAP biomarker panel was generated for further testing in other SMA collections and interventional trials. Future work includes evaluating the panel in other neuromuscular diseases, for pharmacodynamic responsiveness to experimental SMA therapies, and for predicting functional changes over time in SMA patients.

Changes in social functioning and circulating oxytocin and vasopressin following the migration to a new country.

PubMed

Gouin, Jean-Philippe; Pournajafi-Nazarloo, Hossein; Carter, C Sue

2015-02-01

Prior studies have reported associations between plasma oxytocin and vasopressin and markers of social functioning. However, because most human studies have used cross-sectional designs, it is unclear whether plasma oxytocin and vasopressin influences social functioning or whether social functioning modulates the production and peripheral release of these peptides. In order to address this question, we followed individuals who experienced major changes in social functioning subsequent to the migration to a new country. In this study, 59 new international students were recruited shortly after arrival in the host country and reassessed 2 and 5 months later. At each assessment participants provided information on their current social functioning and blood samples for oxytocin and vasopressin analysis. Results indicated that changes in social functioning were not related to changes in plasma oxytocin. Instead, baseline oxytocin predicted changes in social relationship satisfaction, social support, and loneliness over time. In contrast, plasma vasopressin changed as a function of social integration. Baseline vasopressin was not related to changes in social functioning over time. These results emphasize the different roles of plasma oxytocin and vasopressin in responses to changes in social functioning in humans. Copyright © 2014 Elsevier Inc. All rights reserved.

Dissociation, shame, complex PTSD, child maltreatment and intimate relationship self-concept in dissociative disorder, chronic PTSD and mixed psychiatric groups.

PubMed

Dorahy, Martin J; Middleton, Warwick; Seager, Lenaire; McGurrin, Patrick; Williams, Mary; Chambers, Ron

2015-02-01

Whilst a growing body of research has examined dissociation and other psychiatric symptoms in severe dissociative disorders (DDs), there has been no systematic examination of shame and sense of self in relationships in DDs. Chronic child abuse often associated with severe DDs, like dissociative identity disorder, is likely to heighten shame and relationship concerns. This study investigated complex posttraumatic stress disorder (PTSD), borderline and Schneiderian symptoms, dissociation, shame, child abuse, and various markers of self in relationships (e.g., relationship esteem, relationship depression, fear of relationships). Participants were assessed via clinical interview with psychometrically sound questionnaires. They fell into three diagnostic groups, dissociative disorder (n=39; primarily dissociative identity disorder), chronic PTSD (Chr-PTSD; n=13) or mixed psychiatric presentations (MP; n=21; primarily mood and anxiety disorders). All participants had a history of child abuse and/or neglect, and the groups did not differ on age and gender. The DD group was higher on nearly all measured variables than the MP group, and had more severe dissociative, borderline and Schneiderian symptoms than the Chr-PTSD sample. Shame and complex PTSD symptoms fell marginally short of predicting reductions in relationship esteem, pathological dissociative symptoms predicted increased relationship depression, and complex PTSD symptoms predicted fear of relationships. The representativeness of the samples was unknown. Severe psychiatric symptoms differentiate DDs from chronic PTSD, while dissociation and shame have a meaningful impact on specific markers of relationship functioning in psychiatric patients with a history of child abuse and neglect. Copyright © 2014 Elsevier B.V. All rights reserved.

Hippocampal perfusion predicts impending neurodegeneration in REM sleep behavior disorder.

PubMed

Dang-Vu, Thien Thanh; Gagnon, Jean-François; Vendette, Mélanie; Soucy, Jean-Paul; Postuma, Ronald B; Montplaisir, Jacques

2012-12-11

Patients with idiopathic REM sleep behavior disorder (IRBD) are at risk for developing Parkinson disease (PD) and dementia with Lewy bodies (DLB). We aimed to identify functional brain imaging patterns predicting the emergence of PD and DLB in patients with IRBD, using SPECT with (99m)Tc-ethylene cysteinate dimer (ECD). Twenty patients with IRBD were scanned at baseline during wakefulness using (99m)Tc-ECD SPECT. After a follow-up of 3 years on average, patients were divided into 2 groups according to whether or not they developed defined neurodegenerative disease (PD, DLB). SPECT data analysis comparing regional cerebral blood flow (rCBF) between groups assessed whether specific brain perfusion patterns were associated with subsequent clinical evolution. Regression analysis between rCBF and clinical markers of neurodegeneration (motor, color vision, olfaction) looked for neural structures involved in this process. Of the 20 patients with IRBD recruited for this study, 10 converted to PD or DLB during the follow-up. rCBF at baseline was increased in the hippocampus of patients who would later convert compared with those who would not (p < 0.05 corrected). Hippocampal perfusion was correlated with motor and color vision scores across all IRBD patients. (99m)Tc-ECD SPECT identifies patients with IRBD at risk for conversion to other neurodegenerative disorders such as PD or DLB; disease progression in IRBD is predicted by abnormal perfusion in the hippocampus at baseline. Perfusion within this structure is correlated with clinical markers of neurodegeneration, further suggesting its involvement in the development of presumed synucleinopathies.

Preoperative Molecular Markers in Thyroid Nodules.

PubMed

Sahli, Zeyad T; Smith, Philip W; Umbricht, Christopher B; Zeiger, Martha A

2018-01-01

The need for distinguishing benign from malignant thyroid nodules has led to the pursuit of differentiating molecular markers. The most common molecular tests in clinical use are Afirma ® Gene Expression Classifier (GEC) and Thyroseq ® V2. Despite the rapidly developing field of molecular markers, several limitations exist. These challenges include the recent introduction of the histopathological diagnosis "Non-Invasive Follicular Thyroid neoplasm with Papillary-like nuclear features", the correlation of genetic mutations within both benign and malignant pathologic diagnoses, the lack of follow-up of molecular marker negative nodules, and the cost-effectiveness of molecular markers. In this manuscript, we review the current published literature surrounding the diagnostic value of Afirma ® GEC and Thyroseq ® V2. Among Afirma ® GEC studies, sensitivity (Se), specificity (Sp), positive predictive value (PPV), and negative predictive value (NPV) ranged from 75 to 100%, 5 to 53%, 13 to 100%, and 20 to 100%, respectively. Among Thyroseq ® V2 studies, Se, Sp, PPV, and NPV ranged from 40 to 100%, 56 to 93%, 13 to 90%, and 48 to 97%, respectively. We also discuss current challenges to Afirma ® GEC and Thyroseq ® V2 utility and clinical application, and preview the future directions of these rapidly developing technologies.

Plant Comparative and Functional Genomics

DOE PAGES

Yang, Xiaohan; Leebens-Mack, Jim; Chen, Feng; ...

2015-01-01

Plants form the foundation for our global ecosystem and are essential for environmental and human health. An increasing number of available plant genomes and tractable experimental systems, comparative and functional plant genomics research is greatly expanding our knowledge of the molecular basis of economically and nutritionally important traits in crop plants. Inferences drawn from comparative genomics are motivating experimental investigations of gene function and gene interactions. In this special issue aims to highlight recent advances made in comparative and functional genomics research in plants. Nine original research articles in this special issue cover five important topics: (1) transcription factor genemore » families relevant to abiotic stress tolerance; (2) plant secondary metabolism; (3) transcriptomebased markers for quantitative trait locus; (4) epigenetic modifications in plant-microbe interactions; and (5) computational prediction of protein-protein interactions. Finally, we studied the plant species in these articles which include model species as well as nonmodel plant species of economic importance (e.g., food crops and medicinal plants).« less

Plant Comparative and Functional Genomics

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

Yang, Xiaohan; Leebens-Mack, Jim; Chen, Feng

Plants form the foundation for our global ecosystem and are essential for environmental and human health. An increasing number of available plant genomes and tractable experimental systems, comparative and functional plant genomics research is greatly expanding our knowledge of the molecular basis of economically and nutritionally important traits in crop plants. Inferences drawn from comparative genomics are motivating experimental investigations of gene function and gene interactions. In this special issue aims to highlight recent advances made in comparative and functional genomics research in plants. Nine original research articles in this special issue cover five important topics: (1) transcription factor genemore » families relevant to abiotic stress tolerance; (2) plant secondary metabolism; (3) transcriptomebased markers for quantitative trait locus; (4) epigenetic modifications in plant-microbe interactions; and (5) computational prediction of protein-protein interactions. Finally, we studied the plant species in these articles which include model species as well as nonmodel plant species of economic importance (e.g., food crops and medicinal plants).« less

Sparse Bayesian Learning for Identifying Imaging Biomarkers in AD Prediction

PubMed Central

Shen, Li; Qi, Yuan; Kim, Sungeun; Nho, Kwangsik; Wan, Jing; Risacher, Shannon L.; Saykin, Andrew J.

2010-01-01

We apply sparse Bayesian learning methods, automatic relevance determination (ARD) and predictive ARD (PARD), to Alzheimer’s disease (AD) classification to make accurate prediction and identify critical imaging markers relevant to AD at the same time. ARD is one of the most successful Bayesian feature selection methods. PARD is a powerful Bayesian feature selection method, and provides sparse models that is easy to interpret. PARD selects the model with the best estimate of the predictive performance instead of choosing the one with the largest marginal model likelihood. Comparative study with support vector machine (SVM) shows that ARD/PARD in general outperform SVM in terms of prediction accuracy. Additional comparison with surface-based general linear model (GLM) analysis shows that regions with strongest signals are identified by both GLM and ARD/PARD. While GLM P-map returns significant regions all over the cortex, ARD/PARD provide a small number of relevant and meaningful imaging markers with predictive power, including both cortical and subcortical measures. PMID:20879451

A priori Prediction of Neoadjuvant Chemotherapy Response and Survival in Breast Cancer Patients using Quantitative Ultrasound

PubMed Central

Tadayyon, Hadi; Sannachi, Lakshmanan; Gangeh, Mehrdad J.; Kim, Christina; Ghandi, Sonal; Trudeau, Maureen; Pritchard, Kathleen; Tran, William T.; Slodkowska, Elzbieta; Sadeghi-Naini, Ali; Czarnota, Gregory J.

2017-01-01

Quantitative ultrasound (QUS) can probe tissue structure and analyze tumour characteristics. Using a 6-MHz ultrasound system, radiofrequency data were acquired from 56 locally advanced breast cancer patients prior to their neoadjuvant chemotherapy (NAC) and QUS texture features were computed from regions of interest in tumour cores and their margins as potential predictive and prognostic indicators. Breast tumour molecular features were also collected and used for analysis. A multiparametric QUS model was constructed, which demonstrated a response prediction accuracy of 88% and ability to predict patient 5-year survival rates (p = 0.01). QUS features demonstrated superior performance in comparison to molecular markers and the combination of QUS and molecular markers did not improve response prediction. This study demonstrates, for the first time, that non-invasive QUS features in the core and margin of breast tumours can indicate breast cancer response to neoadjuvant chemotherapy (NAC) and predict five-year recurrence-free survival. PMID:28401902

A priori Prediction of Neoadjuvant Chemotherapy Response and Survival in Breast Cancer Patients using Quantitative Ultrasound.

PubMed

Tadayyon, Hadi; Sannachi, Lakshmanan; Gangeh, Mehrdad J; Kim, Christina; Ghandi, Sonal; Trudeau, Maureen; Pritchard, Kathleen; Tran, William T; Slodkowska, Elzbieta; Sadeghi-Naini, Ali; Czarnota, Gregory J

2017-04-12

Quantitative ultrasound (QUS) can probe tissue structure and analyze tumour characteristics. Using a 6-MHz ultrasound system, radiofrequency data were acquired from 56 locally advanced breast cancer patients prior to their neoadjuvant chemotherapy (NAC) and QUS texture features were computed from regions of interest in tumour cores and their margins as potential predictive and prognostic indicators. Breast tumour molecular features were also collected and used for analysis. A multiparametric QUS model was constructed, which demonstrated a response prediction accuracy of 88% and ability to predict patient 5-year survival rates (p = 0.01). QUS features demonstrated superior performance in comparison to molecular markers and the combination of QUS and molecular markers did not improve response prediction. This study demonstrates, for the first time, that non-invasive QUS features in the core and margin of breast tumours can indicate breast cancer response to neoadjuvant chemotherapy (NAC) and predict five-year recurrence-free survival.