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Linking Diabetes Mellitus with Alzheimer's Disease: Bioinformatics Analysis for the Potential Pathways and Characteristic Genes.

Cheng HuangJuyu LuoXueyi WenKeshen Li
Published in: Biochemical genetics (2021)
As the surging epidemics with significant disability, Alzheimer's disease (AD) and type II diabetes mellitus (T2DM) with microvascular complications are widely prevalent, sharing considerable similarities in putative pathomechanism. Despite a spurt of researches on the biology, knowledge about their interactive mechanisms is still rudimentary. Applying bioinformatics ways to explore the differentially co-expressed genes contributes to achieve our objectives to find new therapeutic targets. In this study, we firstly integrated gene expression omnibus datasets (GSE28146 and GSE43950) to identify differentially expressed genes. The enrichment analysis of pivotal genes, like gene ontology and pathway signaling proceeded subsequently. Besides, the related protein-protein interaction (PPI) network was then constructed. To further explain the inner connections, we ended up unearthing the biological significance of valuable targets. As a result, a set of 712, 630, 487, and 997 genes were differentially identified in T2DM with microvascular complications and AD at incipient, moderate, and severe, respectively. The enrichment analysis involving both diseases implicated the dominance of immune system, especially the noteworthy chemokine signaling. Multiple comparisons confirmed that CACNA2D3, NUMB, and IER3 were simultaneously participate in these two conditions, whose respective associations with neurological and endocrine diseases, and regulators including interacting chemicals, transcription factors, and miRNAs were analyzed. Bioinformatics analysis eventually concluded that immune-related biological functions and pathways closely link AD and T2DM with microvascular complications. Further exploration of the regulatory factors about CACNA2D3, NUMB, and IER3 in neuroendocrine field may provide us a promising direction to discover potential strategies for the comorbidity status.
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