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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 E. Morningstar, Xu Shi, Bennet D. Peterson, Christopher Chan, Daniel H. Katz, Usman A. Tahir, Laurie A. Farrell, Olle Melander, Jonathan D. Mosley, Steven A. Carr, Ramachandran S. Vasan, Martin G. Larson, J. Gustav Smith, Thomas J. Wang, Qiong Yang, Robert E. Gerszten
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 E. Morningstar, Xu Shi, Bennet D. Peterson, Christopher Chan, Daniel H. Katz, Usman A. Tahir, Laurie A. Farrell, Olle Melander, Jonathan D. Mosley, Steven A. Carr, Ramachandran S. Vasan, Martin G. Larson, J. Gustav Smith, Thomas J. Wang, Qiong Yang, Robert E. Gerszten
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Research Article Endocrinology

Proteomic profiling reveals biomarkers and pathways in type 2 diabetes risk

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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.

Authors

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 E. Morningstar, Xu Shi, Bennet D. Peterson, Christopher Chan, Daniel H. Katz, Usman A. Tahir, Laurie A. Farrell, Olle Melander, Jonathan D. Mosley, Steven A. Carr, Ramachandran S. Vasan, Martin G. Larson, J. Gustav Smith, Thomas J. Wang, Qiong Yang, Robert E. Gerszten

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Figure 3

The WFIKKN2 rs35300894 SNP is associated with WFIKKN2 plasma protein levels and glucose homeostasis in FHS participants.

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The WFIKKN2 rs35300894 SNP is associated with WFIKKN2 plasma protein lev...
Heterozygous carriers of the low-frequency 286G>A, Val96Met missense substitution within the WFIKKN2 gene compared with GG noncarriers in FHS demonstrated significantly (a) higher levels of WFIKKN2 plasma protein levels (mean 4691 ± 217 RFU versus 3754 ± 43 RFU); (b) lower fasting blood glucose (mean 97.8 ± 0.7 mg/dL versus 101.1 ± 0.3 mg/dL); and (c) lower hemoglobin A1c (HbA1c; mean 5.51% ± 0.02% versus 5.60% ± 0.01%). P values generated from age- and sex-adjusted regression analyses on natural log-transformed and standardized WFIKKN2, fasting blood glucose, and HbA1c values. RFU, relative fluorescence units.

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