Type 2 diabetes mellitus is a heterogeneous disease with broader metabolic perturbation beyond hyperglycemia, resulting in varied prognoses. Additionally, patients are at risk of complications such as diabetic kidney disease (DKD), which often remains asymptomatic in early stages. Metabolomics offers a comprehensive assessment of metabolic dysregulation, surpassing conventional biomarkers like glucose and creatinine. In this case-control study, we used mass spectrometry coupled to liquid (LCMS) and gas chromatography (GCMS) to profile metabolites from the whole blood samples from a cohort of Asian Indians belonging to three groups: non-diabetic, Type 2 diabetes, and DKD.  We identified 290 metabolites using LCMS and GCMS, of which 26 and 20 metabolites were significantly associated with type 2 diabetes and DKD, respectively, after false discovery rate correction. Clustering analyses revealed two distinct subgroups within the type 2 diabetes group, with nine metabolites linked to disease severity. Additionally, seven metabolites exhibited progressive changes from non-diabetic to type 2 diabetes to DKD, suggesting potential prognostic markers for DKD. Our study highlights the role of metabolome profiling for patient stratification and early diagnosis of DKD in Indian patients with type 2 diabetes.

Type 2 diabetes mellitus is a heterogeneous disease with broader metabolic perturbation beyond hyperglycemia, resulting in varied prognoses. Additionally, patients are at risk of complications such as diabetic kidney disease (DKD), which often remains asymptomatic in early stages. Metabolomics offers a comprehensive assessment of metabolic dysregulation, surpassing conventional biomarkers like glucose and creatinine. In this case-control study, we used mass spectrometry coupled to liquid (LCMS) and gas chromatography (GCMS) to profile metabolites from the whole blood samples from a cohort of Asian Indians belonging to three groups: non-diabetic, Type 2 diabetes, and DKD.  We identified 290 metabolites using LCMS and GCMS, of which 26 and 20 metabolites were significantly associated with type 2 diabetes and DKD, respectively, after false discovery rate correction. Clustering analyses revealed two distinct subgroups within the type 2 diabetes group, with nine metabolites linked to disease severity. Additionally, seven metabolites exhibited progressive changes from non-diabetic to type 2 diabetes to DKD, suggesting potential prognostic markers for DKD. Our study highlights the role of metabolome profiling for patient stratification and early diagnosis of DKD in Indian patients with type 2 diabetes.