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

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.

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