Proteomic profiling reveals biomarkers and pathways in type 2 diabetes risk
Debby Ngo, Mark D. Benson, Jonathan Z. Long, Zsu‐Zsu Chen, Ruiqi Wang, Anjali K. Nath, Michelle J. Keyes, Dongxiao Shen, Sumita Sinha, Eric Kuhn, Jordan Morningstar, Xu Shi, Bennet Peterson, Christopher T. Chan, Daniel H. Katz, Usman A. Tahir, Laurie Farrell, Olle Melander, Jonathan D. Mosley, Steven A. Carr, Ramachandran S. Vasan, Martin G. Larson, J. G. Smith, Thomas J. Wang, Qiong Yang, Robert E. Gerszten
Abstract
Recent advances in proteomic technologies have made high-throughput profiling of low-abundance proteins in large epidemiological cohorts increasingly feasible. We investigated whether aptamer-based proteomic profiling could identify biomarkers associated with future development of type 2 diabetes (T2DM) beyond known risk factors. We identified dozens of markers with highly significant associations with future T2DM across 2 large longitudinal cohorts (n = 2839) followed for up to 16 years. We leveraged proteomic, metabolomic, genetic, and clinical data from humans to nominate 1 specific candidate to test for potential causal relationships in model systems. Our studies identified functional effects of aminoacylase 1 (ACY1), a top protein association with future T2DM risk, on amino acid metabolism and insulin homeostasis in vitro and in vivo. Furthermore, a loss-of-function variant associated with circulating levels of the biomarker WAP, Kazal, immunoglobulin, Kunitz, and NTR domain-containing protein 2 (WFIKKN2) was, in turn, associated with fasting glucose, hemoglobin A1c, and HOMA-IR measurements in humans. In addition to identifying potentially novel disease markers and pathways in T2DM, we provide publicly available data to be leveraged for insights about gene function and disease pathogenesis in the context of human metabolism.