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

Table 1 Representative multi-omics studies across different diabetes subtypes and complications

Dm subtype/focus	Omics approach(s)	Primary objective/key findings	Ref.
T1DM (human cohorts)	Genomics (HLA region); metabolomics (LC-MS); epigenomics (RRBS)	Investigate autoimmune-driven β-cell destruction and identify early T1DM biomarkers	[1-3]
T2DM (human & animal)	Transcriptomics (RNA-Seq); proteomics (LC-MS/MS); metabolomics (NMR)	Elucidate insulin resistance, islet dysfunction; discover novel therapeutic targets	[8,9]
GDM (human studies)	Metabolomics (GC-MS); microbiomics (16S rRNA)	Uncover pregnancy-specific metabolite and microbiome signatures predictive of GDM	[10,12-15]
DKD/DR complications	Proteomics (targeted); metabolomics (untargeted); ML-based integration	Correlate inflammatory and fibrotic biomarkers with organ damage; early detection in both T1DM and T2DM	[17-20]
GI complications	Multi-omics synergy (transcript + metabolite)	Reveal changes in gut motility, microbiome composition, disease progression in T2DM	[25,36,42]
Maternal hyperglycemia	Metabolomics (LC-MS); lipidomics	Assess how hyperglycemia in pregnant sows influences neonatal hepatic metabolism	[43]
Microbiome in T1DM/ T2DM/GDM	Microbiomics (16S rRNA, shotgun metagenomics); Metabolomics (SCFAs)	Examine gut dysbiosis related to insulin resistance, inflammation, and distinct metabolic phenotypes	[62-64]

LC-MS: Liquid chromatography-mass spectrometry; GC-MS: Gas chromatography-mass spectrometry; NMR: Nuclear magnetic resonance; RRBS: Reduced representation bisulfite sequencing; ML: Machine learning; SCFAs: Short-chain fatty acids; T1DM: Type 1 diabetes mellitus; T2DM: Type 2 diabetes mellitus; HLA: Human leukocyte antigen; GDM: Gestational diabetes mellitus; GI: Gastrointestinal; MS: Mass spectrometry; DKD: Diabetic kidney disease; DR: Diabetic retinopathy.

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.