TY - JOUR
T1 - Identification and validation of genes affecting aortic lesions in mice
AU - Yang, Xia
AU - Peterson, Larry
AU - Thieringer, Rolf
AU - Deignan, Joshua L.
AU - Wang, Xuping
AU - Zhu, Jun
AU - Wang, Susanna
AU - Zhong, Hua
AU - Stepaniants, Serguei
AU - Beaulaurier, John
AU - Wang, I. Ming
AU - Rosa, Ray
AU - Cumiskey, Anne Marie
AU - Luo, Jane Ming Juan
AU - Luo, Qi
AU - Shah, Kashmira
AU - Xiao, Jianying
AU - Nickle, David
AU - Plump, Andrew
AU - Schadt, Eric E.
AU - Lusis, Aldons J.
AU - Lum, Pek Yee
PY - 2010/7/1
Y1 - 2010/7/1
N2 - Atherosclerosis represents the most significant risk factor for coronary artery disease (CAD), the leading cause of death in developed countries. To better understand the pathogenesis of atherosclerosis, we applied a likelihood-based model selection method to infer gene-disease causality relationships for the aortic lesion trait in a segregating mouse population demonstrating a spectrum of susceptibility to developing atherosclerotic lesions. We identified 292 genes that tested causal for aortic lesions from liver and adipose tissues of these mice, and we experimentally validated one of these candidate causal genes, complement component 3a receptor 1 (C3ar1), using a knockout mouse model. We also found that genes identified by this method overlapped with genes progressively regulated in the aortic arches of 2 mouse models of atherosclerosis during atherosclerotic lesion development. By comparing our gene set with findings from public human genome-wide association studies (GWAS) of CAD and related traits, we found that 5 genes identified by our study overlapped with published studies in humans in which they were identified as risk factors for multiple atherosclerosis-related pathologies, including myocardial infarction, serum uric acid levels, mean platelet volume, aortic root size, and heart failure. Candidate causal genes were also found to be enriched with CAD risk polymorphisms identified by the Wellcome Trust Case Control Consortium (WTCCC). Our findings therefore validate the ability of causality testing procedures to provide insights into the mechanisms underlying atherosclerosis development.
AB - Atherosclerosis represents the most significant risk factor for coronary artery disease (CAD), the leading cause of death in developed countries. To better understand the pathogenesis of atherosclerosis, we applied a likelihood-based model selection method to infer gene-disease causality relationships for the aortic lesion trait in a segregating mouse population demonstrating a spectrum of susceptibility to developing atherosclerotic lesions. We identified 292 genes that tested causal for aortic lesions from liver and adipose tissues of these mice, and we experimentally validated one of these candidate causal genes, complement component 3a receptor 1 (C3ar1), using a knockout mouse model. We also found that genes identified by this method overlapped with genes progressively regulated in the aortic arches of 2 mouse models of atherosclerosis during atherosclerotic lesion development. By comparing our gene set with findings from public human genome-wide association studies (GWAS) of CAD and related traits, we found that 5 genes identified by our study overlapped with published studies in humans in which they were identified as risk factors for multiple atherosclerosis-related pathologies, including myocardial infarction, serum uric acid levels, mean platelet volume, aortic root size, and heart failure. Candidate causal genes were also found to be enriched with CAD risk polymorphisms identified by the Wellcome Trust Case Control Consortium (WTCCC). Our findings therefore validate the ability of causality testing procedures to provide insights into the mechanisms underlying atherosclerosis development.
UR - http://www.scopus.com/inward/record.url?scp=77955003279&partnerID=8YFLogxK
U2 - 10.1172/JCI42742
DO - 10.1172/JCI42742
M3 - Article
C2 - 20577049
AN - SCOPUS:77955003279
SN - 0021-9738
VL - 120
SP - 2414
EP - 2422
JO - Journal of Clinical Investigation
JF - Journal of Clinical Investigation
IS - 7
ER -