Identification of key genes and regulatory networks involved in the Comorbidity of atrial fibrillation and chronic obstructive pulmonary disease

识别与心房颤动和慢性阻塞性肺疾病合并症相关的关键基因和调控网络

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Abstract

BACKGROUND: The underlying molecular processes of atrial fibrillation (AF) and chronic obstructive pulmonary disease (COPD) are frequently linked to increased morbidity and mortality when they co-occur. However, their underlying molecular mechanisms are questioned due to their incomplete analysis. OBJECTIVE: This study aimed to identify common differentially expressed genes (DEGs) in AF and COPD patients and investigate their potential biological functions and pathways. We hope to complement and update previous research through clearer figure presentation and different bioinformatic analysis methods with different datasets. METHODS: We used statistical analysis to identify DEGs in the expression profiles of AF and COPD patients using datasets from the Gene Expression Omnibus database. To ascertain whether the common DEGs were functionally enriched, Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway analyses were used. In addition, we generated protein‒protein interaction networks and identified significant hub genes. Furthermore, the hub genes were used to analyze transcription factor (TF)-gene interactions and TF-miRNA coregulatory networks, and their expression levels were validated in additional datasets. RESULTS: We identified a total of 15 DEGs that were upregulated, whereas 36 were downregulated in AF and COPD patients. The DEGs were commonly expressed in both AF and COPD patients, with functional enrichment analysis revealing their involvement in metabolic processes and neuron-to-neuron synapses. We identified significant hub genes, including TGM2, ITPR1, CHL1, ALDOC, RPS3, FBLN2, NDUFS2, ITGA5, CTNNB1, RBP1, CLSTN2, FABP5, EPHA4, LDHA, and HNRNPL, and analyzed their coexpression and biological functions. TF-gene interaction and TF-miRNA coregulatory network analyses revealed the regulatory relationships of the hub genes. Additional datasets were analyzed to validate hub gene expression, and ALDOC, HNRNPL, and NDUFS2 displayed similar processes in AF and COPD patients. CONCLUSIONS: In our study, we demonstrate that metabolic processes and neuron-to-neuron synaptic connections may contribute to the cooccurrence of AF and COPD. The identified hub genes and regulatory networks may act as potential biomarkers and therapeutic targets for these diseases.

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