Variations in DNA elucidate molecular networks that cause disease

Yanqing Chen, Jun Zhu, Pek Yee Lum, Xia Yang, Shirly Pinto, Douglas J. MacNeil, Chunsheng Zhang, John Lamb, Stephen Edwards, Solveig K. Sieberts, Amy Leonardson, Lawrence W. Castellini, Susanna Wang, Marie France Champy, Bin Zhang, Valur Emilsson, Sudheer Doss, Anatole Ghazalpour, Steve Horvath, Thomas A. DrakeAldons J. Lusis, Eric E. Schadt

Research output: Contribution to journalArticlepeer-review

730 Scopus citations


Identifying variations in DNA that increase susceptibility to disease is one of the primary aims of genetic studies using a forward genetics approach. However, identification of disease-susceptibility genes by means of such studies provides limited functional information on how genes lead to disease. In fact, in most cases there is an absence of functional information altogether, preventing a definitive identification of the susceptibility gene or genes. Here we develop an alternative to the classic forward genetics approach for dissecting complex disease traits where, instead of identifying susceptibility genes directly affected by variations in DNA, we identify gene networks that are perturbed by susceptibility loci and that in turn lead to disease. Application of this method to liver and adipose gene expression data generated from a segregating mouse population results in the identification of a macrophage-enriched network supported as having a causal relationship with disease traits associated with metabolic syndrome. Three genes in this network, lipoprotein lipase (Lpl), lactamase β (Lactb) and protein phosphatase 1-like (Ppm1l), are validated as previously unknown obesity genes, strengthening the association between this network and metabolic disease traits. Our analysis provides direct experimental support that complex traits such as obesity are emergent properties of molecular networks that are modulated by complex genetic loci and environmental factors.

Original languageEnglish
Pages (from-to)429-435
Number of pages7
Issue number7186
StatePublished - 27 Mar 2008
Externally publishedYes


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