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Proteomic profiling reveals novel biomarkers and pathways in yype 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 and Kuhn, Eric , et al. (2021) In JCI Insight 6(5).
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 two large longitudinal cohorts (n=2,839) followed for up to 16 years. We leveraged proteomic, metabolomic, genetic and clinical data from humans to nominate one specific candidate to test for potential causal relationships in model systems. Our studies identified functional effects of aminoacylase 1 (ACY1), a top... (More)

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 two large longitudinal cohorts (n=2,839) followed for up to 16 years. We leveraged proteomic, metabolomic, genetic and clinical data from humans to nominate one 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. Further, 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 novel disease markers and potential pathways in T2DM, we provide publicly available data to be leveraged for new insights about gene function and disease pathogenesis in the context of human metabolism. .

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organization
publishing date
type
Contribution to journal
publication status
published
subject
in
JCI Insight
volume
6
issue
5
publisher
The American Society for Clinical Investigation
external identifiers
  • pmid:33591955
  • scopus:85102455279
ISSN
2379-3708
DOI
10.1172/jci.insight.144392
language
English
LU publication?
yes
id
385d32da-20ab-4362-8a8f-8b4e4ddbfa08
date added to LUP
2021-02-24 10:23:18
date last changed
2024-06-13 07:28:42
@article{385d32da-20ab-4362-8a8f-8b4e4ddbfa08,
  abstract     = {{<p>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 two large longitudinal cohorts (n=2,839) followed for up to 16 years. We leveraged proteomic, metabolomic, genetic and clinical data from humans to nominate one 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. Further, 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 novel disease markers and potential pathways in T2DM, we provide publicly available data to be leveraged for new insights about gene function and disease pathogenesis in the context of human metabolism. .</p>}},
  author       = {{Ngo, Debby and Benson, Mark D and Long, Jonathan Z and Chen, Zsu-Zsu and Wang, Ruiqi and Nath, Anjali K and Keyes, Michelle J and Shen, Dongxiao and Sinha, Sumita and Kuhn, Eric and Morningstar, Jordan E and Shi, Xu and Peterson, Bennet D and Chan, Christopher and Katz, Daniel H and Tahir, Usman A and Farrell, Laurie A and Melander, Olle and Mosley, Jonathan D and Carr, Steven A and Vasan, Ramachandran S and Larson, Martin G and Smith, J Gustav and Wang, Thomas J and Yang, Qiong and Gerszten, Robert E}},
  issn         = {{2379-3708}},
  language     = {{eng}},
  month        = {{02}},
  number       = {{5}},
  publisher    = {{The American Society for Clinical Investigation}},
  series       = {{JCI Insight}},
  title        = {{Proteomic profiling reveals novel biomarkers and pathways in yype 2 diabetes risk}},
  url          = {{http://dx.doi.org/10.1172/jci.insight.144392}},
  doi          = {{10.1172/jci.insight.144392}},
  volume       = {{6}},
  year         = {{2021}},
}