Screening for potential serum-based proteomic biomarkers for human type 2 diabetes mellitus using MALDI-TOF MS
Authors/Creators
- 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
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
Keywords
[RSTDPub], MALDI-TOF MS, Predictive models, Serum peptide biomarkers, Type 2 diabetes mellitus
Document Type
Journal Article
Date of Publication
2017
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
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Garcia, M. (2018). Impact of Biobanks on Research Outcomes in Rare Diseases：A Systematic Review. Retrieved from http://ro.ecu.edu.au/theses/2110
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
Copyright
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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