Identity by descent and association analysis of dichotomous traits based on large pedigrees

The goals of our analysis were to map functional loci, which contribute to the case-control status of a trait of interest, using large pedigrees. We used logistic regression fitted with the generalized estimation equation to test associations between a dichotomous phenotype and all genotyped common and rare single-nucleotide polymorphisms. In addition to the association study, we also developed and applied a simple and fast identical-by-descent-based test to identify loci that were shared among affected individuals more often than expected by chance. Among the top significant loci, we assessed the statistical power and the false discovery rate of both methods. We also demonstrated that family-based studies, compared with the standard population-based association studies, have great values and advantages for the discovery of multiple rare causal variants

A comparison between microsatellite and single-nucleotide polymorphism markers with respect to two measures of information content

Using the Genetic Analysis Workshop 14 (GAW14) simulated dataset, we compare microsatellite and single-nucleotide polymorphism (SNP) markers in terms of two measures of information content, the traditional entropy-based information content measure, and a new "relative information" measure. Both attempt to measure the amount of information contained in the markers about the identity-by-descent (IBD) sharing among relatives. The performance of the two information measures are compared based on their variability and ability to predict change in the LOD score (ΔLOD) as map density increases for SNP markers. Although in a linked region, LOD scores are correlated with measures of information, we observe that none of the measures predict the LOD score itself very well. In an unlinked region, the LOD score is not related to either measures of information. The information content of microsatellite markers with 7.5-cM spacing is slightly higher than that of SNP markers with 3-cM spacing. At these map densities, microsatellites are found to be uniformly more informative than SNPs irrespective of their level of heterozygosity. For SNPs, we found that as the level of heterozygosity increases, the information content increases. As reported in all other previous studies, we also found that high-density SNPs have higher information content compared to low-density microsatellites. Performance of both the two information measures considered here are similar, but the relative information measure predicts ΔLOD as marker density increases better than the traditional entropy-based information measure

Pathway-based analysis using reduced gene subsets in genome-wide association studies

<p>Abstract</p> <p>Background</p> <p>Single Nucleotide Polymorphism (SNP) analysis only captures a small proportion of associated genetic variants in Genome-Wide Association Studies (GWAS) partly due to small marginal effects. Pathway level analysis incorporating prior biological information offers another way to analyze GWAS's of complex diseases, and promises to reveal the mechanisms leading to complex diseases. Biologically defined pathways are typically comprised of numerous genes. If only a subset of genes in the pathways is associated with disease then a joint analysis including all individual genes would result in a loss of power. To address this issue, we propose a pathway-based method that allows us to test for joint effects by using a pre-selected gene subset. In the proposed approach, each gene is considered as the basic unit, which reduces the number of genetic variants considered and hence reduces the degrees of freedom in the joint analysis. The proposed approach also can be used to investigate the joint effect of several genes in a candidate gene study.</p> <p>Results</p> <p>We applied this new method to a published GWAS of psoriasis and identified 6 biologically plausible pathways, after adjustment for multiple testing. The pathways identified in our analysis overlap with those reported in previous studies. Further, using simulations across a range of gene numbers and effect sizes, we demonstrate that the proposed approach enjoys higher power than several other approaches to detect associated pathways.</p> <p>Conclusions</p> <p>The proposed method could increase the power to discover susceptibility pathways and to identify associated genes using GWAS. In our analysis of genome-wide psoriasis data, we have identified a number of relevant pathways for psoriasis.</p

Mixtures of Regression Models for Time-Course Gene Expression Data: Evaluation of Initialization and Random Effects

Finite mixture models are routinely applied to time course microarray data. Due to the complexity and size of this type of data the choice of good starting values plays an important role. So far initialization strategies have only been investigated for data from a mixture of multivariate normal distributions. In this work several initialization procedures are evaluated for mixtures of regression models with and without random effects in an extensive simulation study on different artificial datasets. Finally these procedures are also applied to a real dataset from E. coli

Combined genotype and haplotype tests for region-based association studies

10.1186/1471-2164-14-569BMC Genomics141-BGME

Genetic and environmental influences on fruit and vegetable consumption and depression in older adults

Background: Prior work suggests that higher fruit and vegetable consumption may protect against depression in older adults. Better understanding of the influence of genetic and environmental factors on fruit and vegetable intakes may lead to the design of more effective dietary strategies to increase intakes. In turn this may reduce the occurrence of depression in older adults. Objectives: The primary aim of this study is to estimate the genetic and environmental influences on the consumption of fruit and vegetables in older adults. The secondary aim is an exploratory analysis into possible shared genetic influences on fruit and vegetable intakes and depression. Methods: Analysis of observational data from 374 twins (67.1% female; 208 monozygotic (MZ); 166 dizygotic (DZ)) aged ≥ 65 years drawn from the Older Australian Twins Study. Dietary data were obtained using a validated food frequency questionnaire and depressive symptoms were measured using the 15-item short form Geriatric Depression Scale. The contribution of genetic and environmental influences on fruit and vegetable intake were estimated by comparing MZ and DZ twin intakes using structural equation modelling. A tri-variate twin model was used to estimate the genetic and environmental correlation between total fruit and vegetable intakes and depression. Results: In this study, vegetable intake was moderately influenced by genetics (0.39 95%CI 0.22, 0.54). Heritability was highest for brassica vegetables (0.40 95%CI 0.24, 0.54). Overall fruit intake was not significantly heritable. No significant genetic correlations were detected between fruit and vegetable intake and depressive symptoms. Conclusions: Vegetable consumption, particularly bitter tasting brassica vegetables, was significantly influenced by genetics, although environmental influences were also apparent. Consumption of fruit was only influenced by the environment, with no genetic influence detected, suggesting strategies targeting the food environment may be particularly effective for encouraging fruit consumption

The influence of rs53576 polymorphism in the oxytocin receptor (OXTR) gene on empathy in healthy adults by subtype and ethnicity: a systematic review and meta-analysis

Empathy is essential for navigating complex social environments. Prior work has shown associations between rs53576, a single nucleotide polymorphism (SNP) located in the oxytocin receptor gene (OXTR), and generalized empathy. We undertook a systematic review and meta-analysis to assess the effects of rs53576 on subdomains of empathy, specifically cognitive empathy (CE) and affective empathy (AE), in healthy adults. Twenty cohorts of 8933 participants aged 18-98 were identified, including data from the Sydney Memory and Ageing Study, a cohort of older community adults. Meta-analyses found G homozygotes had greater generalized empathic abilities only in young to middle-aged adults. While meta-analyses of empathy subdomains yielded no significant overall effects, there were differential effects based on ethnicity. G homozygotes were associated with greater CE abilities in Asian cohorts (standardized mean difference; SMD: 0.09 [2.8·10-3-0.18]), and greater AE performance in European cohorts [SMD: 0.12 (0.04-0.21)]. The current literature highlights a need for further work that distinguishes between genetic and ethnocultural effects and explores effects of advanced age on this relationship

Molecular analysis of CHX10 and MFRP in Chinese subjects with primary angle closure glaucoma and short axial length eyes

Molecular Vision141313-131