Analysis of the Comorbidity and Biological Mechanism Between COVID-19 and Type 2 Diabetes
This article investigates the interaction mechanism between coronavirus disease 2019(COVID-19)and type 2 diabetes(T2D)using transcriptome data,and aiming to identify potential functional modules for the treatment of these diseases.The study collected 10 gene expression profiles datasets from the Gene Expression Omnibus(GEO)database,divided them into training and validation sets in a 4∶6 ratio and enrichment analysis of differentially expressed genes(DEGs)and modular analysis of protein-protein interactions(PPI)were conducted to identify Key genes and protein modules related to COVID-19 and T2D.43 shared DEGs across tissues were found,and 5 Key genes(HSP90AA1,SRC,EGFR,MAPK3,CDK1)were identified,with CDK1 exhibiting the highest network connectivity.Performance evaluation using six machine learning algorithms,including XGBoost,revealed the potential value of Key genes in diagnosing COVID-19 and T2D.Experimental validation through qPCR confirmed the expression differences of these Key genes in the PBMCs of COVID-19 patients and the normal control group.Additionally,the study identified six potential functional modules of the PPI network using a module partitioning algorithm,which were mainly associated with carbohydrate and lipid metabolism and cell replication.Finally,the study established a miRNA-TF-mRNA regulatory network and identified TP53 and NFIC as hub transcription factors regulating the transcription of shared genes.Overall,this study analyzed the shared expression characteristics,biological pathways,and regulatory factors between COVID-19 and T2D,and explored the complex interactions between genes in transcription and translation,providing new ideas for the treatment of these diseases in the future.
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