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Published on: April 7, 2023
Investigating the molecular mechanisms between type 1 diabetes and mild cognitive impairment using bioinformatics
Dongxu Yue1, Runze Wang1, Yanli Zhao1
1Department of Pathology and Pathophysiology, Faculty of Basic Medical Sciences, Kunming Medical University, Kunming, PR China.
Abstract:
The immune system is involved in the development and progression of several diseases. Type 1 diabetes mellitus (T1DM), an autoimmune disorder, influences the progression of several other conditions; however, the link between T1DM and mild cognitive impairment (MCI) remains unclear. This study investigated the underlying immune response mechanisms that contribute to the development and progression of T1DM and MCI. Microarray datasets for MCI (GSE63060) and T1DM (GSE30208) were retrieved from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) were identified using the limma package. To explore the functional implications of these DEGs, Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses were conducted using ClusterProfiler. Protein-protein interaction networks for the DEGs were constructed using the STRING database and visualized using Cytoscape. The Molecular Complex Detection algorithm was used to analyze DEGs. Immune cell infiltration in patients with T1DM and MCI was analyzed using the xCell method. Gene set enrichment analysis was used to gain in-depth insights into the functional characteristics of T1DM and MCI. Immune-related genes were obtained from the GeneCards and ImmPort databases. Machine learning algorithms were used to identify potential hub genes associated with immunity for T1DM and MCI diagnosis, and the diagnostic value was assessed using the receiver operating characteristic curve. The identified genes were validated using quantitative polymerase chain reaction. In the T1DM and MCI datasets, 610 DEGs showed consistent trends, of which 232 and 378 were upregulated and downregulated, respectively. Immune response analysis revealed significant changes in the immune cells associated with MCI and T1DM. Using immune-related genes, DEGs, and machine learning techniques, we identified CD3D in the MCI and T1DM groups. We observed a gradual decline in the cognitive function of mice with T1DM as the disease progressed. CD3D expression increased with increasing disease severity; CD3D primarily affected CD4+ T cells. This study revealed a complex interaction between T1DM and MCI, providing novel insights into the intricate relationship between immune dysregulation and cognitive impairment and expanding our understanding of these two interconnected disorders. These findings will facilitate the development of therapeutic interventions and identification of potential therapeutic targets.
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