Abstract
BackgroundType 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.MethodsThe 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.ResultsA 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.ConclusionsThis 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.
Highlights
Type 2 diabetes mellitus (T2DM) is a complex multifactorial disease with a high prevalence worldwide
One possible reason for this failure may be the multifactorial nature of T2DM, which results in different groups of molecular mechanisms, all leading to insulin resistance
We studied gene expression profiles of human skeletal muscle from healthy and newly diagnosed diabetic patients with two goals: 1) To identify a set of genes whose expression patterns can discriminate T2DM individuals from healthy ones using a machinelearning approach; and 2) To examine the potential existence of molecular subtypes based on the gene expression profile of diabetic individuals
Summary
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. Impaired insulin secretion by pancreatic β-cells is the main cause of T2DM. This usually happens due to having a background of reduced sensitivity to insulin in target tissues [1]. Better prognostic signatures and therapeutic targets necessitate a better understanding of the molecular mechanisms underlying insulin resistance in skeletal muscle. One possible reason for this failure may be the multifactorial nature of T2DM, which results in different groups of molecular mechanisms, all leading to insulin resistance. Precision medicine for each group may, help develop more effective treatments for T2DM
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