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AMIA Summits Transl Sci Proc. 2012; 2012: 35–41.
Published online Mar 19, 2012.
PMCID: PMC3392070
Coanalysis of GWAS with eQTLs reveals disease-tissue associations
Hyunseok Peter Kang, M.D.,1 Alex A. Morgan, Ph.D.,1 Rong Chen, Ph.D.,1 Eric E. Schadt, Ph.D.,2 and Atul J. Butte, M.D, Ph.D.1
1 Division of Systems Medicine, Department of Pediatrics, Stanford University School of Medicine, Stanford, CA
2 Department of Genetics and Genome Sciences, Mount Sinai School of Medicine, New York, NY
Abstract
Expression quantitative trait loci (eQTL), or genetic variants associated with changes in gene expression, have the potential to assist in interpreting results of genome-wide association studies (GWAS). eQTLs also have varying degrees of tissue specificity. By correlating the statistical significance of eQTLs mapped in various tissue types to their odds ratios reported in a large GWAS by the Wellcome Trust Case Control Consortium (WTCCC), we discovered that there is a significant association between diseases studied genetically and their relevant tissues. This suggests that eQTL data sets can be used to determine tissues that play a role in the pathogenesis of a disease, thereby highlighting these tissue types for further post-GWAS functional studies.
Articles from AMIA Summits on Translational Science Proceedings are provided here courtesy of
American Medical Informatics Association