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

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...

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Bibliographic Details
Published in:BMC medical genomics Vol. 13; no. 1; pp. 119 - 12
Main Authors: Khoshnejat, Maryam, Kavousi, Kaveh, Banaei-Moghaddam, Ali Mohammad, Moosavi-Movahedi, Ali Akbar
Format: Journal Article
Language:English
Published: London BioMed Central 24.08.2020
BioMed Central Ltd
Springer Nature B.V
BMC
Subjects:
Accuracy
Analysis
Bioinformatic and algorithmical studies
Biomarkers - analysis
Biomass
Biomedical and Life Sciences
Biomedicine
Case-Control Studies
Chromosomes
Classification
Clustering
Diabetes
Diabetes mellitus (non-insulin dependent)
Diabetes Mellitus, Type 2 - classification
Diabetes Mellitus, Type 2 - genetics
Diabetes Mellitus, Type 2 - metabolism
Diabetes Mellitus, Type 2 - pathology
Diabetics
Discovery and exploration
Enzymes
Feature selection
Flux variability analysis
Gene Expression
Gene Expression Regulation
Genes
Genetic algorithms
Genomes
Glucose
Glucose metabolism
Human Genetics
Humans
Insulin
Insulin - metabolism
Insulin resistance
Insulin secretion
Learning algorithms
Machine learning
Metabolic Networks and Pathways
Metabolic pathways
Metabolism
Metabolites
Microarrays
Molecular modelling
Muscle
Musculoskeletal system
Research Article
Signal Transduction
Skeletal muscle
Subtype
Support vector machines
Transcriptome
Type 2 diabetes
Type 2 diabetes
Metabolic modeling
Classification
Insulin resistance
Muscle
Clustering
Subtype
Flux variability analysis
ISSN:1755-8794, 1755-8794
Online Access:Get full text
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Summary: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.
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ISSN:1755-8794
1755-8794
DOI:10.1186/s12920-020-00767-0