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An integrative genomics approach to infer causal associations between gene expression and disease.

ABSTRACT: A key goal of biomedical research is to elucidate the complex network of gene interactions underlying complex traits such as common human diseases. Here we detail a multistep procedure for identifying potential key drivers of complex traits that integrates DNA-variation and gene-expression data with other complex trait data in segregating mouse populations. Ordering gene expression traits relative to one another and relative to other complex traits is achieved by systematically testing whether variations in DNA that lead to variations in relative transcript abundances statistically support an independent, causative or reactive function relative to the complex traits under consideration. We show that this approach can predict transcriptional responses to single gene-perturbation experiments using gene-expression data in the context of a segregating mouse population. We also demonstrate the utility of this approach by identifying and experimentally validating the involvement of three new genes in susceptibility to obesity.

SUBMITTER: Schadt EE

PROVIDER: S-EPMC2841396 | biostudies-literature | 2005 Jul

REPOSITORIES: biostudies-literature

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An integrative genomics approach to infer causal associations between gene expression and disease.

Schadt Eric E EE Lamb John J Yang Xia X Zhu Jun J Edwards Steve S Guhathakurta Debraj D Sieberts Solveig K SK Monks Stephanie S Reitman Marc M Zhang Chunsheng C Lum Pek Yee PY Leonardson Amy A Thieringer Rolf R Metzger Joseph M JM Yang Liming L Castle John J Zhu Haoyuan H Kash Shera F SF Drake Thomas A TA Sachs Alan A Lusis Aldons J AJ

Nature genetics 20050619 7

A key goal of biomedical research is to elucidate the complex network of gene interactions underlying complex traits such as common human diseases. Here we detail a multistep procedure for identifying potential key drivers of complex traits that integrates DNA-variation and gene-expression data with other complex trait data in segregating mouse populations. Ordering gene expression traits relative to one another and relative to other complex traits is achieved by systematically testing whether v ...[more]

PMID: 15965475

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An integrative genomics approach to infer causal associations between gene expression and disease.

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An integrative genomics approach to infer causal associations between gene expression and disease.

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