Illuminating diabetes via multi-omics: Unraveling disease mechanisms and advancing personalized therapy

Table 2 Translational insights from multi-omics studies in diabetes

Focus/theme	Key multi-omics finding	Potential clinical application
T1DM: Early autoimmune risk assessment	Genomics/epigenomics highlight HLA variants & methylation changes; Metabolomics reveals pro-inflammatory signatures	Identifying high-risk individuals for early intervention[1-3]
T2DM: Insulin resistance & metabolic overload	Elevated BCAAs/lipids from metabolomics [5,8,23,30-38]; Transcriptomics pinpoints insulin signaling defects [24,25]	Improved patient stratification; Tailored dietary or pharmacological interventions targeting dysregulated pathways
GDM: Pregnancy-specific biomarkers & interventions	Metabolomics + microbiomics [10,12-15] reveal distinct lipid/bile acid profiles, gut flora changes	Early screening of at-risk mothers; Nutritional or probiotic therapies to minimize fetal impact
Diabetic complications (DKD, DR)	Proteomics + metabolomics identify inflammation/fibrosis [17-20]; Single-cell multi-omics links endothelial dysfunction to hyperglycemia	Risk stratification for DKD, DR; Earlier monitoring and targeted therapy

BCAAs: Branched-chain amino acids; HLA: Human leukocyte antigen; DKD: Diabetic kidney disease; DR: Diabetic retinopathy; T1DM: Type 1 diabetes mellitus; T2DM: Type 2 diabetes mellitus; GDM: Gestational diabetes mellitus; HLA: Human leukocyte antigen.