Inflammation and Immunological Disarrays Are Associated with Acute Exercise in Type 2 Diabetes

Vahid Mansouri,Reza Vafaee, Mahsa Mohammadi Maram,Fatemeh Bandarian,Parisa Sarabi,Farideh Razi,Zahra Razzaghi,Majid Rezaei Tavirani, Hassan Karimi,Mostafa Rezaei-Tavirani

Journal of Diabetes & Metabolic Disorders（2024）

Shahid Beheshti University of Medical Sciences | Tehran University of Medical Sciences | Iran University of Medical Sciences

Cited 0|Views24

Abstract

Objective:Type 2 diabetes (T2D) is the most common metabolic disorder that is associated with insulin resistance. The aim of the present study is to discover details of the molecular mechanism of exercise on control or progress of diabetic condition in patients via network analysis. Methods:Gene expression profiles of patients with T2D before and after doing exercise are retrieved from Gene Expression Omnibus (GEO) and are pre-evaluated by the GEO2R program. Data are studied based on expression values, regulatory relationships between the differentially expressed genes (DEGs), gene ontology analyses, and protein-protein interaction PPI network analysis. Results:A number of 118 significant DEGs were identified and classified based on fold change (FC) values as most dysregulated genes and dysregulated individuals. Action map analysis revealed that 18 DEGs appeared as the critical genes. Gene ontology analysis showed that 24 DEGs are connected to at least four pathways. JUN, IL6, IL1B, PTGS2, FOS, MYC, ATF3, CXCL8, EGR1, EGR2, NR4A1, PLK3, TTN, and UCP3 were identified as central DEGs. Conclusion:Finally; JUN, IL6, IL1B, PTGS2, FOS, ATF3, CXCL8, EGR1, and EGR2 were introduced as the critical targeted genes by exercise. Since the critical genes after exercise are upregulated and mostly are known as the risk factors of T2D, it can be concluded that unsuitable exercise can develop diabetic conditions in patients. Acute exercise-induced inflammation and immune disturbances seem to be associated with the development of T2D in patients.

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Key words

Exercise,Type 2 diabetes,Gene ontology,Network analysis,Action map

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