Platelet Proteomic Profiling Identifies Novel Protein Drivers of Cardiovascular Complications in Type 2 Diabetes: A Multi-Method Consensus Investigation

This study presents a multi-method systems biology pipeline for platelet proteomic biomarker discovery in type 2 diabetes mellitus (T2DM)-associated cardiovascular disease. Quantitative platelet proteomics data from 24 healthy controls and 23 T2DM patients (1,925 proteins after quality filtering) were analysed using four independent discovery methods: differential expression analysis with 10,000-permutation validation, pre-ranked Gene Set Enrichment Analysis (GSEA) against KEGG 2021, silhouette-optimised K-means protein clustering, and principal component analysis (PCA) top-loader extraction. Multi-method consensus integration identified 63 candidate biomarker proteins, with angiotensinogen (AGT) and CD14 reaching three-method high-confidence designation. The consensus protein set showed significantly larger effect sizes than single-method proteins (Mann–Whitney p = 0.001), formed a fully connected protein–protein interaction network (52 nodes, 129 edges, STRING enrichment p < 0.001), and was enriched for 121 biological processes including complement activation, haemostasis, and immune regulation. GSEA identified complement and coagulation cascades as the most significantly enriched pathway (NES = 2.38, FDR < 0.001). These hypothesis-generating findings provide a methodological framework for biomarker discovery in underpowered proteomic cohorts and a foundation for prospective clinical validation of platelet-mediated cardiovascular pathology in T2DM.