Screening for potential serum-based proteomic biomarkers for human type 2 diabetes mellitus using MALDI-TOF MS
Authors
Qiutao Meng
Siqi Ge, Edith Cowan UniversityFollow
Wenhua Yan
Ruisheng Li
Jingtao Dou
Haibing Wang
Baoan Wang
Qingwei Ma
Yong Zhou
Manshu Song
Xinwei Yu, Edith Cowan UniversityFollow
Hao Wang
Xinghua Yang
Fen Liu
Mohamed Ali Alzain
Yuxiang Yan
Ling Zhang
Lijuan Wu
Feifei Zhao
Yan He
Xiuhua Guo
Feng Chen
Weizhuo Xu
Monique Garcia, Edith Cowan UniversityFollow
Desmond D. Menon, Edith Cowan UniversityFollow
Youxin Wang
Yiming Mu
Wei Wang, Edith Cowan UniversityFollow
Document Type
Journal Article
Publication Title
Proteomics Clinical Applications
Publisher
Wiley
School
School of Medical and Health Sciences
RAS ID
22713
Funders
National Health and Medical Research Council
Grant Number
NHMRC Number : 1112767
Abstract
Background
Type 2 diabetes mellitus (T2DM) is a complex, pandemic disease contributing towards the global burden of health issues. To date, there are no simple clinical tests for the early detection of T2DM.
Method
To identify potential peptide biomarkers for such applications, 406 sera of T2DM patients (n = 206) and healthy controls (n = 200) are analyzed by using MALDI-TOF MS with a cross-sectional case-control design.
Result
Six peptides (peaks m/z 1452.9, 1692.8, 1946.0, 2115.1, 2211.0 and 4053.6) are identified as candidate biomarkers for T2DM. A diagnostic model constructed with six peptides is able to discriminate T2DM patients from healthy controls, with an accuracy of 82.20%, sensitivity of 82.50%, and specificity of 77.80% in the validation set. Peptide peaks m/z 1452.9 and 1692.8 are identified as fragments of the complement C3f, while peptide peaks m/z 1946.0, 2115.1, and 2211.0 are identified as the fragments of kininogen 1 isoform 1 precursor.
Conclusion
This study reinforces proteomic analyses as a potential technique for defining significant clinical peptide biomarkers, providing a simple and convenient diagnostic model for T2DM in clinical examination.j
DOI
10.1002/prca.201600079
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Ge, S. (2019). Screening of multi-omics biomarkers for Type 2 Diabetes Mellitus among Chinese population. https://ro.ecu.edu.au/theses/2293
Yu, X. (2019). Immunoglobulin G N-glycan profiling as a risk stratification biomarker for type 2 diabetes. Retrieved from https://ro.ecu.edu.au/theses/2199
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Comments
Meng, Q., Ge, S., Yan, W., Li, R., Dou, J., Wang, H., . . . Wang, W. (2017). Screening for potential serum-based proteomic biomarkers for human type 2 diabetes mellitus using MALDI-TOF MS. Proteomics Clinical Applications, 11(3-4), article 1600079. https://doi.org/10.1002/prca.201600079