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Song Liu,1,* Xiaojun Cai,1,* Tao Wang,1 Jiwen Xu,2 Weilun Cheng,3 Xuling Wang,1 Gangjie Wei,4 Shuang Yan5 1Endocrinology Department, Traditional Chinese Medicine Academy of Heilongjiang, Harbin, Heilongjiang Province, People’s Republic of China; 2Anatomy, Histology and Embryology Teaching and Research Section, School of Basic Medicine, Heilongjiang University of Chinese Medicine, Harbin, Heilongjiang Province, People’s Republic of China; 3Department of General Surgery, The First Affiliated Hospital of Harbin Medical University, Harbin, Heilongjiang Province, People’s Republic of China; 4Medical Department, Traditional Chinese Medicine Academy of Heilongjiang, Harbin, Heilongjiang Province, People’s Republic of China; 5Department of Endocrinology and Metabolism, The Fourth Affiliated Hospital of Harbin Medical University, Harbin, Heilongjiang Province, People’s Republic of China*These authors contributed equally to this workCorrespondence: Shuang Yan, Email yan8028397483@126.comPurpose: Skeletal muscle insulin resistance (IR) is an important etiology of type 2 diabetes mellitus (T2DM); however, its molecular mechanism is yet to be fully defined. This study attempted to identify the gene expression patterns and molecular disorders in T2DM patients’ skeletal muscle samples.Methods: First, the difference in genetic expression among GSE25462 data was analyzed. Next, PPI network analysis of differential genes was carried out, after which the maladjustment module was identified. Then, an enrichment analysis and gene set enrichment analysis (GSEA) were carried out. Finally, the transcription factors that regulate the modular genes by raid were predicted.Results: Most differentially expressed genes were found to be able to form an interaction network and cluster into 9 modules. These modular genes were shown to possess a significant correlation with immune inflammation and metabolic response. Importantly, the top 15 genes of area under receiver operating characteristic curve (AUC) were identified, and the expression of 10 genes by GSE12643, GSE18732 and GSE29221 was confirmed. The expression and AUC value of ALDH6A1 were then verified according to three sets of data, where ALDH6A1 was found to be negatively correlated with follicular helper T cells. However, among the predicted transcription regulators, HDAC was shown to have a better regulatory effect.Conclusion: The findings highlight that the dysregulation of ALDH6A1 expression in IR of T2DM may serve as a potential therapeutic target. ALDH6A1 is involved in the immune inflammation and metabolic pathways.Keywords: type 2 diabetes mellitus, ALDH6A1, immune inflammatory response, metabolic pathway, HDAC |
