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Proteomic profiling reveals biomarkers and pathways in type 2 diabetes risk

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 (T...

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Autores principales: Ngo, Debby, Benson, Mark D., Long, Jonathan Z., Chen, Zsu-Zsu, Wang, Ruiqi, Nath, Anjali K., Keyes, Michelle J., Shen, Dongxiao, Sinha, Sumita, Kuhn, Eric, Morningstar, Jordan E., Shi, Xu, Peterson, Bennet D., Chan, Christopher, Katz, Daniel H., Tahir, Usman A., Farrell, Laurie A., Melander, Olle, Mosley, Jonathan D., Carr, Steven A., Vasan, Ramachandran S., Larson, Martin G., Smith, J. Gustav, Wang, Thomas J., Yang, Qiong, Gerszten, Robert E.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Society for Clinical Investigation 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8021115/
https://www.ncbi.nlm.nih.gov/pubmed/33591955
http://dx.doi.org/10.1172/jci.insight.144392
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author Ngo, Debby
Benson, Mark D.
Long, Jonathan Z.
Chen, Zsu-Zsu
Wang, Ruiqi
Nath, Anjali K.
Keyes, Michelle J.
Shen, Dongxiao
Sinha, Sumita
Kuhn, Eric
Morningstar, Jordan E.
Shi, Xu
Peterson, Bennet D.
Chan, Christopher
Katz, Daniel H.
Tahir, Usman A.
Farrell, Laurie A.
Melander, Olle
Mosley, Jonathan D.
Carr, Steven A.
Vasan, Ramachandran S.
Larson, Martin G.
Smith, J. Gustav
Wang, Thomas J.
Yang, Qiong
Gerszten, Robert E.
author_facet Ngo, Debby
Benson, Mark D.
Long, Jonathan Z.
Chen, Zsu-Zsu
Wang, Ruiqi
Nath, Anjali K.
Keyes, Michelle J.
Shen, Dongxiao
Sinha, Sumita
Kuhn, Eric
Morningstar, Jordan E.
Shi, Xu
Peterson, Bennet D.
Chan, Christopher
Katz, Daniel H.
Tahir, Usman A.
Farrell, Laurie A.
Melander, Olle
Mosley, Jonathan D.
Carr, Steven A.
Vasan, Ramachandran S.
Larson, Martin G.
Smith, J. Gustav
Wang, Thomas J.
Yang, Qiong
Gerszten, Robert E.
author_sort Ngo, Debby
collection PubMed
description 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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spelling pubmed-80211152021-04-08 Proteomic profiling reveals biomarkers and pathways in type 2 diabetes risk Ngo, Debby Benson, Mark D. Long, Jonathan Z. Chen, Zsu-Zsu Wang, Ruiqi Nath, Anjali K. Keyes, Michelle J. Shen, Dongxiao Sinha, Sumita Kuhn, Eric Morningstar, Jordan E. Shi, Xu Peterson, Bennet D. Chan, Christopher Katz, Daniel H. Tahir, Usman A. Farrell, Laurie A. Melander, Olle Mosley, Jonathan D. Carr, Steven A. Vasan, Ramachandran S. Larson, Martin G. Smith, J. Gustav Wang, Thomas J. Yang, Qiong Gerszten, Robert E. JCI Insight Research Article 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. American Society for Clinical Investigation 2021-03-08 /pmc/articles/PMC8021115/ /pubmed/33591955 http://dx.doi.org/10.1172/jci.insight.144392 Text en © 2021 Ngo et al. http://creativecommons.org/licenses/by/4.0/ This work is licensed under the Creative Commons Attribution 4.0 International License. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Research Article
Ngo, Debby
Benson, Mark D.
Long, Jonathan Z.
Chen, Zsu-Zsu
Wang, Ruiqi
Nath, Anjali K.
Keyes, Michelle J.
Shen, Dongxiao
Sinha, Sumita
Kuhn, Eric
Morningstar, Jordan E.
Shi, Xu
Peterson, Bennet D.
Chan, Christopher
Katz, Daniel H.
Tahir, Usman A.
Farrell, Laurie A.
Melander, Olle
Mosley, Jonathan D.
Carr, Steven A.
Vasan, Ramachandran S.
Larson, Martin G.
Smith, J. Gustav
Wang, Thomas J.
Yang, Qiong
Gerszten, Robert E.
Proteomic profiling reveals biomarkers and pathways in type 2 diabetes risk
title Proteomic profiling reveals biomarkers and pathways in type 2 diabetes risk
title_full Proteomic profiling reveals biomarkers and pathways in type 2 diabetes risk
title_fullStr Proteomic profiling reveals biomarkers and pathways in type 2 diabetes risk
title_full_unstemmed Proteomic profiling reveals biomarkers and pathways in type 2 diabetes risk
title_short Proteomic profiling reveals biomarkers and pathways in type 2 diabetes risk
title_sort proteomic profiling reveals biomarkers and pathways in type 2 diabetes risk
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8021115/
https://www.ncbi.nlm.nih.gov/pubmed/33591955
http://dx.doi.org/10.1172/jci.insight.144392
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