Exploring Biomarkers in Type 2 Diabetes Mellitus versus Normoglycemia Identified through High-Throughput Proteomics: A Systematic Review and Meta-Analysis #MMPMID41319215
Garcia-Curras J; Perez-Lois R; L Taboada G; P Pata M
J Proteome Res 2025[Nov]; ? (?): ? PMID41319215show ga
Recent advances in proteomics have enabled the identification of early protein biomarkers and metabolic disturbances associated with type 2 diabetes (T2D), a major global health challenge. This systematic review and meta-analysis synthesize evidence from 27 studies comparing proteomic profiles of individuals with T2D and normoglycemic controls, selected from 2,422 initial records. The QUADOMICS assessment showed good methodological reporting for sample handling and proteomic analysis (>70% of studies), but over 60% lacked information on confounding clinical factors and biomarker validation. A qualitative synthesis focused on 85 recurrently reported proteins (>/=8 studies), which showed strong interconnectivity and were involved in immune response, lipid-protein organization, detoxification, proteolysis, and coagulation, key pathways implicated in T2D. An omics-based meta-analysis identified seven promising protein biomarkers for T2D related to lipid/glucose metabolism (Q12907_LMAN2, P02652_POA2, P07602_PSPA, P09622_DLD); cell binding/adhesion (P12109_COL6A1, P12830_CDH1); and translational regulation and mitochondrial function (P35232_PHB). Random-effects meta-analysis revealed variation in effect sizes across studies for previously highlighted biomarkers, but three of them (P02763_ORM1, P00738_HP, P25311_AZGP1) exhibited considerable consistency. To enhance accessibility and further exploration of findings, we provide the interactive web tool metaMarkersT2D: https://jgcurras.shinyapps.io/metaMarkersT2D/.
J+Proteome+Res 2025 ; ? (?): ?
