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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...
Autores principales: | , , , , , , , , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Society for Clinical Investigation
2021
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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. |
format | Online Article Text |
id | pubmed-8021115 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | American Society for Clinical Investigation |
record_format | MEDLINE/PubMed |
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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