Metabolic and proteomic signatures of type 2 diabetes subtypes in an Arab population

Abstract

Background. Type 2 diabetes (T2D) has a heterogeneous etiology which is increasingly recognized to influence the risk of complications and choice of treatment. A data driven cluster analysis in four separate European populations of patients with type 2 diabetes identified four subtypes of severe insulin dependent (SIDD), severe insulin resistant (SIRD), mild obesity-related (MOD), and mild age-related (MARD) (Ahlqvist et al., Lancet Diabetes Endocrinology, 2018). Our aim was to extend this classification to the Arab population of Qatar and characterize the biological processes that differentiate these subtypes in relation to metabolomic and proteomic signatures. Methods. The Ahlqvist et al. subtype clustering approach was applied to 631 individuals with T2D from the Qatar Biobank (QBB) and validated in an independent set of 420 participants from the same population. The association between blood metabolites (n=1,159) and protein levels (n=1,305) with each cluster were established. Findings. The four subtypes of T2D were reproduced and validated in the population of Qatar. Cluster-specific metabolomic and proteomic associations revealed subtype-specific molecular processes. Activation of the complement system with many features of autoimmune diabetes and reduced 1,5-anhydroglucitol (1,5-AG) characterized SIDD, with evidence of impaired insulin signaling in SIRD, elevated leptin and fatty acid binding protein in MOD, whilst MARD appeared to be the healthiest subgroup. Interpretation. We have replicated the four T2D clusters in an Arab population and identified distinct metabolic and proteomic signatures, providing insights into underlying etiology with the potential to deploy subtype-specific treatment options.