Genome-wide association studies of human and rat BMI converge on synapse, epigenome, and hormone signaling networks
Sarah N. Wright, Brittany S. Leger, Sara Brin Rosenthal, Sophie Liu, Tongqiu Jia, Apurva S. Chitre, Oksana Polesskaya, Katie Holl, Jianjun Gao, Riyan Cheng, Angel Garcia Martinez, Anthony M. George, Alexander F. Gileta, Wenyan Han, Alesa H. Netzley, Christopher P. King, Alexander Lamparelli, Connor D. Martin, Celine L. St. Pierre, Tengfei Wang, Hannah Bimschleger, Jerry B. Richards, Keita Ishiwari, Hao Chen, Shelly B. Flagel, Paul Meyer, Terry E. Robinson, Leah C. Solberg Woods, Jason F. Kreisberg, Trey Ideker, Abraham A. Palmer
Abstract
A vexing observation in genome-wide association studies (GWASs) is that parallel analyses in different species may not identify orthologous genes. Here, we demonstrate that cross-species translation of GWASs can be greatly improved by an analysis of co-localization within molecular networks. Using body mass index (BMI) as an example, we show that the genes associated with BMI in humans lack significant agreement with those identified in rats. However, the networks interconnecting these genes show substantial overlap, highlighting common mechanisms including synaptic signaling, epigenetic modification, and hormonal regulation. Genetic perturbations within these networks cause abnormal BMI phenotypes in mice, too, supporting their broad conservation across mammals. Other mechanisms appear species specific, including carbohydrate biosynthesis (humans) and glycerolipid metabolism (rodents). Finally, network co-localization also identifies cross-species convergence for height/body length. This study advances a general paradigm for determining whether and how phenotypes measured in model species recapitulate human biology.