A Review on Dysregulation of Lipid Metabolism & Ketohenesis in Type 2 Diabetes Mellitus

Abstract

Introduction: Diabetes mellitus (DM) is a metabolic disorder characterised by chronic hyperglycaemia resulting from impaired insulin–glucagon regulation. Type 1 diabetes involves autoimmune β-cell destruction, whereas type 2 diabetes mellitus (T2DM) is primarily associated with insulin resistance and relative insulin deficiency. Advances in metabolomics and immunometabolism have identified metabolites that participate in insulin resistance, inflammation, and metabolic dysregulation.

Aim & Objective: To review the roles of ketogenic and immune metabolism in DM and evaluate their potential as biomarkers for early diagnosis, patient stratification, and personalised therapeutic monitoring.

Materials & Methods: A narrative review of current evidence was undertaken, focusing on metabolomic and immunometabolic studies involving ketone bodies, acylcarnitines, branched-chain amino acids, ceramides, glycine, glutamine, lactate, NAD⁺, immune-cell metabolic pathways, and inflammatory mediators in DM.

Results: Ketone bodies, particularly β-hydroxybutyrate, act as metabolic substrates and signalling molecules influencing oxidative stress, histone deacetylation, and immune-cell function. Alterations in acylcarnitine and other metabolite profiles are associated with insulin resistance and metabolic dysfunction. Immune-cell metabolic reprogramming contributes to chronic low-grade inflammation (metaflammation), particularly in obesity and T2DM. However, clinical translation is limited by insufficient longitudinal human studies, heterogeneous diabetes phenotypes, non-standardised measurement protocols, incomplete multi-omics integration, and limited validation of metabolite-based assays.

Conclusion: Integration of ketogenic and immune-metabolic pathways may provide a systems-level approach to understanding DM pathogenesis. Combined assessment of ketone bodies, acylcarnitines, immune-derived enzymes, and inflammatory mediators may improve early detection, disease stratification, and personalised monitoring beyond conventional glycaemic indices.

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