Mapping the Genetic Architecture of Gene Expression in Human Liver

作者：Eric E. Schadt, Cliona Molony, Eugene Chudin, K. Hao, Xia Yang, Pek Yee Lum, Andrew Kasarskis, Bin Zhang, Susanna Wang, Christine Suver, Jun Zhu, Joshua Millstein, Solveig K. Sieberts, John Lamb, Debraj GuhaThakurta, Jonathan M.J. Derry, John D. Storey, Iliana Avila-Campillo, Mark J Kruger, Jason M. Johnson, Carol A. Rohl, Atila van Nas, Margarete Mehrabian, Thomas A. Drake, Aldons J. Lusis, Ryan Smith, F. Peter Guengerich, Stephen C. Strom, Erin G. Schuetz, Thomas H. Rushmore, Roger G. Ulrich · 发表于：PLoS Biology · 年份：2008 · DOI：10.1371/journal.pbio.0060107 · 被引用次数：933 · 研究领域：Endoplasmic Reticulum Stress and Disease、Genetic Associations and Epidemiology、Liver Disease Diagnosis and Treatment

Genetic variants that are associated with common human diseases do not lead directly to disease, but instead act on intermediate, molecular phenotypes that in turn induce changes in higher-order disease traits. Therefore, identifying the molecular phenotypes that vary in response to changes in DNA and that also associate with changes in disease traits has the potential to provide the functional information required to not only identify and validate the susceptibility genes that are directly affected by changes in DNA, but also to understand the molecular networks in which such genes operate and how changes in these networks lead to changes in disease traits. Toward that end, we profiled more than 39,000 transcripts and we genotyped 782,476 unique single nucleotide polymorphisms (SNPs) in more than 400 human liver samples to characterize the genetic architecture of gene expression in the human liver, a metabolically active tissue that is important in a number of common human diseases, including obesity, diabetes, and atherosclerosis. This genome-wide association study of gene expression resulted in the detection of more than 6,000 associations between SNP genotypes and liver gene expression traits, where many of the corresponding genes identified have already been implicated in a number of human diseases. The utility of these data for elucidating the causes of common human diseases is demonstrated by integrating them with genotypic and expression data from other human and mous...