Unraveling the molecular heterogeneity in type 2 diabetes: a potential subtype discovery followed by metabolic modeling

Abstract

Background: Type 2 diabetes mellitus (T2DM) is a complex multifactorial disease with a high prevalence worldwide. Insulin resistance and impaired insulin secretion are the two major abnormalities in the pathogenesis of T2DM. Skeletal muscle is responsible for over 75% of the glucose uptake and plays a critical role in T2DM. Here, we sought to provide a better understanding of the abnormalities in this tissue. Methods: The muscle gene expression patterns were explored in healthy and newly diagnosed T2DM individuals using supervised and unsupervised classification approaches. Moreover, the potential of subtyping T2DM patients was evaluated based on the gene expression patterns. Results: A machine-learning technique was applied to identify a set of genes whose expression patterns could discriminate diabetic subjects from healthy ones. A gene set comprising of 26 genes was found that was able to distinguish healthy from diabetic individuals with 94% accuracy. In addition, three distinct clusters of diabetic patients with different dysregulated genes and metabolic pathways were identified. Conclusions: This study indicates that T2DM is triggered by different cellular/molecular mechanisms, and it can be categorized into different subtypes. Subtyping of T2DM patients in combination with their real clinical profiles will provide a better understanding of the abnormalities in each group and more effective therapeutic approaches in the future.

A novel diabetes typology: towards precision diabetology from pathogenesis to treatment

“…An extension of phenotyping including not only multiple omics data (e.g. genomics, metabolomics, proteomics, transcriptomics) but also deep molecular and physiological phenotyping using wearable devices may help to provide further insight and to refine the subtyping of diabetes [10,[60][61][62] • Individual responses to diet and exercise vary between individuals [63,64]. It is not known to what extent this individuality is also related to different pathomechanisms that characterise the novel diabetes subgroups…”

Circulating microRNAs as clinically useful biomarkers for Type 2 Diabetes Mellitus: miRNomics from bench to bedside

“…This strategy allowed the identification of three T2D patients subgroups based on the expression pattern of skeletal muscle genes. 15 The rapid development of advanced and cost-effective -omics platforms (genomics, proteomics, transcriptomics and small RNAomics) and the creation of multicentric consortia, favored the adoption of multiomics approaches to identify a potential combination of molecular and clinical parameters to stratify insulinresistant and T2D patients. 16 For example, Huang et al adopted a multiomics approach based on clinical features, proteomic, cytokines profile, microbiome and RNA-seq in order to identify 17 parameters able to distinguish insulin resistant (IR) and insulin sensitive subjects.…”