Candidate Causal Regulatory Effects by Integration of Expression QTLs with Complex Trait Genetic Associations

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Candidate Causal Regulatory Effects by Integration of Expression QTLs with Complex Trait Genetic Associations

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dc.contributor.author Nica, Alexandra C.
dc.contributor.author Montgomery, Stephen B.
dc.contributor.author Dimas, Antigone S.
dc.contributor.author Beazley, Claude
dc.contributor.author Barroso, Inês
dc.contributor.author Dermitzakis, Emmanouil T.
dc.contributor.author Gibson, Greg
dc.contributor.author Stranger, Barbara Elaine
dc.date.accessioned 2010-12-09T14:52:41Z
dc.date.issued 2010
dc.identifier.citation Nica, Alexandra C., Stephen B. Montgomery, Antigone S. Dimas, Barbara E. Stranger, Claude Beazley, Inês Barroso, and Emmanouil T. Dermitzakis. 2010. Candidate causal regulatory effects by integration of expression QTLs with complex trait genetic associations. PLoS Genetics 6(4): e1000895. en_US
dc.identifier.issn 1553-7390 en_US
dc.identifier.issn 1553-7404 en_US
dc.identifier.uri http://nrs.harvard.edu/urn-3:HUL.InstRepos:4621600
dc.description.abstract The recent success of genome-wide association studies (GWAS) is now followed by the challenge to determine how the reported susceptibility variants mediate complex traits and diseases. Expression quantitative trait loci (eQTLs) have been implicated in disease associations through overlaps between eQTLs and GWAS signals. However, the abundance of eQTLs and the strong correlation structure (LD) in the genome make it likely that some of these overlaps are coincidental and not driven by the same functional variants. In the present study, we propose an empirical methodology, which we call Regulatory Trait Concordance (RTC) that accounts for local LD structure and integrates eQTLs and GWAS results in order to reveal the subset of association signals that are due to cis eQTLs. We simulate genomic regions of various LD patterns with both a single or two causal variants and show that our score outperforms SNP correlation metrics, be they statistical (r2) or historical (D'). Following the observation of a significant abundance of regulatory signals among currently published GWAS loci, we apply our method with the goal to prioritize relevant genes for each of the respective complex traits. We detect several potential disease-causing regulatory effects, with a strong enrichment for immunity-related conditions, consistent with the nature of the cell line tested (LCLs). Furthermore, we present an extension of the method in trans, where interrogating the whole genome for downstream effects of the disease variant can be informative regarding its unknown primary biological effect. We conclude that integrating cellular phenotype associations with organismal complex traits will facilitate the biological interpretation of the genetic effects on these traits. en_US
dc.language.iso en_US en_US
dc.publisher Public Library of Science en_US
dc.relation.isversionof doi:10.1371/journal.pgen.1000895 en_US
dc.relation.hasversion http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2848550/pdf/ en_US
dash.license LAA
dc.subject genetics and genomics en_US
dc.subject complex traits en_US
dc.subject genetics of disease en_US
dc.subject gene expression en_US
dc.title Candidate Causal Regulatory Effects by Integration of Expression QTLs with Complex Trait Genetic Associations en_US
dc.type Journal Article en_US
dc.description.version Version of Record en_US
dc.relation.journal PLoS Genetics en_US
dash.depositing.author Stranger, Barbara Elaine
dc.date.available 2010-12-09T14:52:41Z
dash.affiliation.other HMS^Medicine-Brigham and Women's Hospital en_US

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