Plasma proteomics identifies four candidate biomarkers associated with macrovascular complications in type 2 diabetes: evidence from a clinical cohort and an animal model.

Authors

Nuo Chen, Jingxuan Wang, Xiaojing Yuan, Wan Zhou

Published in

Frontiers in endocrinology. Volume 17. Pages 1955597. Epub Oct 30, 2026.

Abstract

To identify and validate plasma protein biomarkers for T2DM macrovascular complications through proteomic screening, clinical validation, and animal models.
Plasma proteomics (4D-DIA, n = 6/group) was used to screen candidate proteins via differential expression, WGCNA, and PPI analyses. Candidates were validated in an independent clinical cohort (n = 162: 41 healthy controls, 35 T2DM alone, 86 T2DM with macrovascular complications) by ELISA for associations with metabolic parameters and diagnostic performance. A diabetic atherosclerosis mouse model (n = 10/group; C57BL/6J for control and diabetic groups, ApoE-/- for diabetic atherosclerosis, 24 weeks) was used to assess protein/mRNA expression and atherosclerotic lesions by Western blot, RT-qPCR, histology, and immunohistochemistry, with correlations to inflammatory and metabolic markers.
In an exploratory proteomic discovery phase using a very small cohort (n = 6 per group), four candidate proteins were prioritized: adenylosuccinate lyase (ADSL), galectin-3 (LGALS3), mannosyl (α-1,3-)-glycoprotein β-1,2-N-acetylglucosaminyltransferase (MGAT1), and V-set and immunoglobulin domain-containing protein 4 (VSIG4). The four-protein panel showed good discrimination (AUC = 0.961). Adding the panel to a clinical model (age, disease duration, and HbA1c) significantly improved diagnostic performance (ΔAUC = 0.138, P = 0.008; NRI = 0.314; IDI = 0.261), with good calibration and internal stability. Firth penalized logistic regression identified ADSL (OR = 0.327, P = 0.0199) and MGAT1 (OR = 7.435, P = 2.71×10^-6) as independently associated with prevalent macrovascular disease. In animal models, ADSL, LGALS3, and VSIG4 correlated significantly with seven indicators, while MGAT1 correlated significantly with LDL-C, HDL-C, IL-6, and TNF-α after FDR. LGALS3 and VSIG4, though not independent in multivariable analysis, showed consistent upregulation and moderate discriminative ability (AUC = 0.736 and 0.686), supporting biological relevance.
ADSL and MGAT1 were independently associated with prevalent macrovascular complications.LGALS3 and VSIG4 may reflect cumulative metabolic and inflammatory burden rather than a lack of biological relevance; animal studies provide supportive evidence for this hypothesis.The four-protein panel improved diagnostic discrimination over clinical variables alone. These findings are exploratory and based on a small discovery cohort and internal validation; the four proteins are therefore best regarded as candidate diagnostic biomarkers associated with prevalent disease. Prospective external validation is warranted.

PMID:
43031686
Bibliographic data and abstract were imported from PubMed on 14 Nov 2026.

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