Unraveling the Molecular Heterogeneity in type 2 Diabetes: A Potential Subtype Discovery Study Followed by Metabolic Modeling

Abstract

Background Type 2 diabetes mellitus (T2DM) is a complex multifactorial disease with a high prevalence in the world. 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 thus plays a critical role in T2DM. Here, we attempt to provide a better understanding of abnormalities in this tissue. We have explored the muscle gene expression pattern in healthy and newly-diagnosed T2DM individuals using supervised and unsupervised classification along with the discovery of potential subtypes of type 2 diabetes.Results A machine-learning technique applied to identify a pattern of gene expression that could potentially discriminate between normoglycemic and diabetic groups. A gene set comprises of 26 genes identified which was able to discriminate healthy from diabetic individuals with the 94% accuracy after 10-fold stratified cross-validation. In addition, three distinct potential subtypes with different dysregulated genes and metabolic pathways identified in diabetic patients.Conclusion This study implies that it seems the disease has triggered through different cellular/molecular mechanisms. Therefore, subtyping of T2DM patients will provide a better understanding of abnormalities in each group and lead to the recommendation of the appropriate precision therapy for each subtype in the future.