94 research outputs found
Epistatic effects between two genes in the renin-angiotensin system and systolic blood pressure and coronary artery calcification
Association Between Episodic Memory and Genetic Risk Factors for Alzheimerâs Disease in South Asians from the Longitudinal Aging Study in IndiaâDiagnostic Assessment of Dementia (LASIâDAD)
Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/156473/3/jgs16735-sup-0001-supinfo.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/156473/2/jgs16735_am.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/156473/1/jgs16735.pd
An Empirical Comparison of Metaâanalysis and Megaâanalysis of Individual Participant Data for Identifying GeneâEnvironment Interactions
For analysis of the main effects of SNPs, metaâanalysis of summary results from individual studies has been shown to provide comparable results as âmegaâanalysisâ that jointly analyzes the pooled participant data from the available studies. This fact revolutionized the genetic analysis of complex traits through large GWAS consortia. Investigations of geneâenvironment (GĂE) interactions are on the rise since they can potentially explain a part of the missing heritability and identify individuals at high risk for disease. However, for analysis of geneâenvironment interactions, it is not known whether these methods yield comparable results. In this empirical study, we report that the results from both methods were largely consistent for all four tests; the standard 1 degree of freedom (df) test of main effect only, the 1 df test of the main effect (in the presence of interaction effect), the 1 df test of the interaction effect, and the joint 2 df test of main and interaction effects. They provided similar effect size and standard error estimates, leading to comparable P âvalues. The genomic inflation factors and the number of SNPs with various thresholds were also comparable between the two approaches. Megaâanalysis is not always feasible especially in very large and diverse consortia since pooling of raw data may be limited by the terms of the informed consent. Our study illustrates that metaâanalysis can be an effective approach also for identifying interactions. To our knowledge, this is the first report investigating metaâversus megaâanalyses for interactions.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/106866/1/gepi21800.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/106866/2/gepi21800-sup-0001-SuppMat.pd
Testing crossâphenotype effects of rare variants in longitudinal studies of complex traits
Many gene mapping studies of complex traits have identified genes or variants that influence multiple phenotypes. With the advent of nextâgeneration sequencing technology, there has been substantial interest in identifying rare variants in genes that possess crossâphenotype effects. In the presence of such effects, modeling both the phenotypes and rare variants collectively using multivariate models can achieve higher statistical power compared to univariate methods that either model each phenotype separately or perform separate tests for each variant. Several studies collect phenotypic data over time and using such longitudinal data can further increase the power to detect genetic associations. Although rareâvariant approaches exist for testing crossâphenotype effects at a single time point, there is no analogous method for performing such analyses using longitudinal outcomes. In order to fill this important gap, we propose an extension of Gene Association with Multiple Traits (GAMuT) test, a method for crossâphenotype analysis of rare variants using a framework based on the distance covariance. The approach allows for both binary and continuous phenotypes and can also adjust for covariates. Our simple adjustment to the GAMuT test allows it to handle longitudinal data and to gain power by exploiting temporal correlation. The approach is computationally efficient and applicable on a genomeâwide scale due to the use of a closedâform test whose significance can be evaluated analytically. We use simulated data to demonstrate that our method has favorable power over competing approaches and also apply our approach to exome chip data from the Genetic Epidemiology Network of Arteriopathy.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/144294/1/gepi22121_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/144294/2/gepi22121.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/144294/3/gepi22121-sup-0001-SuppMat.pd
Copy Number Variations Associated With ObesityâRelated Traits in African Americans: A Joint Analysis Between GENOA and HyperGEN
Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/95398/1/oby.2012.162.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/95398/2/oby_2790_sm_oby2012162_coi.pd
Insulin Resistance Exacerbates Genetic Predisposition to Nonalcoholic Fatty Liver Disease in Individuals Without Diabetes
Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/149741/1/hep41353.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/149741/2/hep41353_am.pd
DNA mismatch repair gene MSH6 implicated in determining age at natural menopause
The length of female reproductive lifespan is associated with multiple adverse outcomes, including breast cancer, cardiovascular disease and infertility. The biological processes that govern the timing of the beginning and end of reproductive life are not well understood. Genetic variants are known to contribute to âŒ50% of the variation in both age at menarche and menopause, but to date the known genes explain <15% of the genetic component. We have used genome-wide association in a bivariate meta-analysis of both traits to identify genes involved in determining reproductive lifespan. We observed significant genetic correlation between the two traits using genome-wide complex trait analysis. However, we found no robust statistical evidence for individual variants with an effect on both traits. A novel association with age at menopause was detected for a variant rs1800932 in the mismatch repair gene MSH6 (P = 1.9 Ă 10â9), which was also associated with altered expression levels of MSH6 mRNA in multiple tissues. This study contributes to the growing evidence that DNA repair processes play a key role in ovarian ageing and could be an important therapeutic target for infertilit
Multi-ancestry genome-wide association study accounting for gene-psychosocial factor interactions identifies novel loci for blood pressure traits
Psychological
and social factors are known to influence blood pressure (BP) and risk
of hypertension and associated cardiovascular diseases. To identify
novel BP loci, we carried out genome-wide association meta-analyses of
systolic, diastolic, pulse, and mean arterial BP, taking into account
the interaction effects of genetic variants with three psychosocial
factors: depressive symptoms, anxiety symptoms, and social support.
Analyses were performed using a two-stage design in a sample of up to
128,894 adults from five ancestry groups. In the combined meta-analyses
of stages 1 and 2, we identified 59 loci (p value < 5eâ8), including
nine novel BP loci. The novel associations were observed mostly with
pulse pressure, with fewer observed with mean arterial pressure. Five
novel loci were identified in African ancestry, and all but one showed
patterns of interaction with at least one psychosocial factor.
Functional annotation of the novel loci supports a major role for genes
implicated in the immune response (PLCL2), synaptic function and neurotransmission (LIN7A and PFIA2), as well as genes previously implicated in neuropsychiatric or stress-related disorders (FSTL5 and CHODL).
These findings underscore the importance of considering psychological
and social factors in gene discovery for BP, especially in non-European
populations
DNA mismatch repair gene MSH6 implicated in determining age at natural menopause
notes: PMCID: PMC3976329This is a freely-available open access publication. Please cite the published version which is available via the DOI link in this record.The length of female reproductive lifespan is associated with multiple adverse outcomes, including breast cancer, cardiovascular disease and infertility. The biological processes that govern the timing of the beginning and end of reproductive life are not well understood. Genetic variants are known to contribute to âŒ50% of the variation in both age at menarche and menopause, but to date the known genes explain <15% of the genetic component. We have used genome-wide association in a bivariate meta-analysis of both traits to identify genes involved in determining reproductive lifespan. We observed significant genetic correlation between the two traits using genome-wide complex trait analysis. However, we found no robust statistical evidence for individual variants with an effect on both traits. A novel association with age at menopause was detected for a variant rs1800932 in the mismatch repair gene MSH6 (P = 1.9 Ă 10(-9)), which was also associated with altered expression levels of MSH6 mRNA in multiple tissues. This study contributes to the growing evidence that DNA repair processes play a key role in ovarian ageing and could be an important therapeutic target for infertility.UK Medical Research CouncilWellcome Trus
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