Literature DB >> 27863080

Screening for potential serum-based proteomic biomarkers for human type 2 diabetes mellitus using MALDI-TOF MS.

Qiutao Meng1, Siqi Ge2,3, Wenhua Yan1, Ruisheng Li4, Jingtao Dou1, Haibing Wang1, Baoan Wang1, Qingwei Ma5, Yong Zhou2, Manshu Song2, Xinwei Yu2,3, Hao Wang2, Xinghua Yang2, Fen Liu2, Mohamed Ali Alzain2, Yuxiang Yan2, Ling Zhang2, Lijuan Wu2, Feifei Zhao2, Yan He2, Xiuhua Guo2, Feng Chen6, Weizhuo Xu7, Monique Garcia3, Desmond Menon3, Youxin Wang2, Yiming Mu1, Wei Wang2,3.   

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.
© 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Entities:  

Keywords:  MALDI-TOF MS; Predictive models; Serum peptide biomarkers; Type 2 diabetes mellitus

Mesh:

Substances:

Year:  2016        PMID: 27863080     DOI: 10.1002/prca.201600079

Source DB:  PubMed          Journal:  Proteomics Clin Appl        ISSN: 1862-8346            Impact factor:   3.494


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