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

doi:10.1172/jci.insight.144392

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. CarrRamachandran S. Vasan, Martin G. Larson, J. Gustav Smith, Thomas J. Wang, Qiong Yang, Robert E. Gerszten

Research output: Contribution to journal › Article › peer-review

22 Scopus citations

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.

Original language	English (US)
Article number	e144392
Journal	JCI Insight
Volume	6
Issue number	5
DOIs	https://doi.org/10.1172/jci.insight.144392
State	Published - Mar 8 2021
Externally published	Yes

ASJC Scopus subject areas

General Medicine

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Ngo, D., Benson, M. D., Long, J. Z., Chen, Z. Z., Wang, R., Nath, A. K., Keyes, M. J., Shen, D., Sinha, S., Kuhn, E., Morningstar, J. E., Shi, X., Peterson, B. D., Chan, C., Katz, D. H., Tahir, U. A., Farrell, L. A., Melander, O., Mosley, J. D., ... Gerszten, R. E. (2021). Proteomic profiling reveals biomarkers and pathways in type 2 diabetes risk. JCI Insight, 6(5), Article e144392. https://doi.org/10.1172/jci.insight.144392

Ngo, D, Benson, MD, Long, JZ, Chen, ZZ, Wang, R, Nath, AK, Keyes, MJ, Shen, D, Sinha, S, Kuhn, E, Morningstar, JE, Shi, X, Peterson, BD, Chan, C, Katz, DH, Tahir, UA, Farrell, LA, Melander, O, Mosley, JD, Carr, SA, Vasan, RS, Larson, MG, Gustav Smith, J, Wang, TJ, Yang, Q & Gerszten, RE 2021, 'Proteomic profiling reveals biomarkers and pathways in type 2 diabetes risk', JCI Insight, vol. 6, no. 5, e144392. https://doi.org/10.1172/jci.insight.144392

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title = "Proteomic profiling reveals biomarkers and pathways in type 2 diabetes risk",

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.",

author = "Debby Ngo and Benson, {Mark D.} and Long, {Jonathan Z.} and Chen, {Zsu Zsu} and Ruiqi Wang and Nath, {Anjali K.} and Keyes, {Michelle J.} and Dongxiao Shen and Sumita Sinha and Eric Kuhn and Morningstar, {Jordan E.} and Xu Shi and Peterson, {Bennet D.} and Christopher Chan and Katz, {Daniel H.} and Tahir, {Usman A.} and Farrell, {Laurie A.} and Olle Melander and Mosley, {Jonathan D.} and Carr, {Steven A.} and Vasan, {Ramachandran S.} and Larson, {Martin G.} and {Gustav Smith}, J. and Wang, {Thomas J.} and Qiong Yang and Gerszten, {Robert E.}",

note = "Publisher Copyright: Copyright: {\textcopyright} 2021, Ngo et al.",

year = "2021",

month = mar,

day = "8",

doi = "10.1172/jci.insight.144392",

language = "English (US)",

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AU - Ngo, Debby

AU - Benson, Mark D.

AU - Long, Jonathan Z.

AU - Chen, Zsu Zsu

AU - Wang, Ruiqi

AU - Nath, Anjali K.

AU - Keyes, Michelle J.

AU - Shen, Dongxiao

AU - Sinha, Sumita

AU - Kuhn, Eric

AU - Morningstar, Jordan E.

AU - Shi, Xu

AU - Peterson, Bennet D.

AU - Chan, Christopher

AU - Katz, Daniel H.

AU - Tahir, Usman A.

AU - Farrell, Laurie A.

AU - Melander, Olle

AU - Mosley, Jonathan D.

AU - Carr, Steven A.

AU - Vasan, Ramachandran S.

AU - Larson, Martin G.

AU - Gustav Smith, J.

AU - Wang, Thomas J.

AU - Yang, Qiong

AU - Gerszten, Robert E.

PY - 2021/3/8

Y1 - 2021/3/8

N2 - 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.

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Proteomic profiling reveals biomarkers and pathways in type 2 diabetes risk

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