Integrated analyses of gene expression and genetic association studies in a founder population

Darren A. Cusanovich, Minal Caliskan, Christine Billstrand, Katelyn Michelini, Claudia Chavarria, Sherryl De Leon, Amy Mitrano, Noah Lewellyn, Jack A. Elias, Geoffrey L. Chupp, Roberto M. Lang, Sanjiv J. Shah, Jeanne M. Decara, Yoav Gilad, Carole Ober*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

13 Scopus citations

Abstract

Genome-wide association studies (GWASs) have become a standard tool for dissecting genetic contributions to disease risk. However, these studies typically require extraordinarily large sample sizes to be adequately powered. Strategies that incorporate functional information alongside genetic associations have proved successful in increasing GWAS power. Following this paradigm, we present the results of 20 different genetic association studies for quantitative traits related to complex diseases, conducted in the Hutterites of South Dakota. To boost the power of these association studies, we collected RNA-sequencing data from lymphoblastoid cell lines for 431 Hutterite individuals. We then used Sherlock, a tool that integrates GWAS and expression quantitative trait locus (eQTL) data, to identify weak GWAS signals that are also supported by eQTL data. Using this approach, we found novel associations with quantitative phenotypes related to cardiovascular disease, including carotid intima-media thickness, left atrial volume index, monocyte count and serum YKL-40 levels.

Original languageEnglish (US)
Article numberddw061
Pages (from-to)2104-2112
Number of pages9
JournalHuman molecular genetics
Volume25
Issue number10
DOIs
StatePublished - May 15 2016

ASJC Scopus subject areas

  • Genetics(clinical)
  • Genetics
  • Molecular Biology

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