Blood metabolome profiling for patient stratification and assessment of disease severity among Asian Indian patients with Type 2 diabetes mellitus

Abstract

Abstract Introduction: Type 2 diabetes mellitus is a heterogeneous disease with broader metabolic perturbation beyond hyperglycemia, resulting in varied prognoses. Clustering analyses using clinical features have identified at least four sub-types with differing disease progression among patients with type 2 diabetes. Additionally, patients are at risk of developing complications such as diabetic kidney disease (DKD), the early stages of which are clinically silent. Metabolomics offers a comprehensive understanding of the underlying metabolic intricacies, beyond conventional clinical markers such as glucose and creatinine. Objective: We aimed to identify significant metabolites that can help in patient stratification and early assessment of DKD in Indian patients with type 2 diabetes. Methods: 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. Results: We identified 290 unique metabolites using both LCMS and GCMS, of which 26 and 20 metabolites were significantly associated with Type 2 diabetes and DKD, respectively, after p-value correction for false discovery rate. K-means and hierarchical clustering revealed two distinct sub-groups within the type 2 diabetes group with nine significant metabolites indicating differences in disease severity. Furthermore, seven metabolites showed progressive changes from non-diabetic to type 2 diabetes to DKD. Conclusion: Metabolome profiling has the potential to be used for patient stratification and early diagnosis of DKD in Indian patients with type 2 diabetes in Asian Indians, towards facilitating personalized treatment with timely intervention.