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作者

Yi Zhou, Chunhua Yang, Jing Zhou, Qiyao Zhang, Xingling Sui, Hongyu Dong, Haidong Zhang, Yue Wang

作者单位

Affiliations ¹ Department of Emergency, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, 250021, China. ² School of Clinical and Basic Medical Sciences, Shandong First Medical University & Shandong Academy of Medical Sciences, Jinan, 250117, China. ³ Medical Experimental Center, Jinan Maternity and Child Care Hospital Affiliated to Shandong First Medical University, Jinan, 250000, China.

刊名

Translational neuroscience

年份

2024

卷号

Vol.15 No.1

页码

20220360

ISSN

2081-3856

关键词

COVID-19 major depressive disorder neuroimmune response neuroinflammation transcriptional and posttranscriptional regulation.

摘要

Introduction: Depression, the leading cause of disability worldwide, is known to be exacerbated by severe acute respiratory syndrome coronavirus 2 infection, worsening coronavirus disease 2019 outcomes. However, the mechanisms and treatments for this comorbidity are not well understood. Methods: This study utilized Gene Expression Omnibus datasets for COVID-19 and depression, combined with protein-protein interaction networks, to identify key genes. Gene ontology and Kyoto Encyclopedia of Genes...更多

Introduction: Depression, the leading cause of disability worldwide, is known to be exacerbated by severe acute respiratory syndrome coronavirus 2 infection, worsening coronavirus disease 2019 outcomes. However, the mechanisms and treatments for this comorbidity are not well understood. Methods: This study utilized Gene Expression Omnibus datasets for COVID-19 and depression, combined with protein-protein interaction networks, to identify key genes. Gene ontology and Kyoto Encyclopedia of Genes and Genomes analyses were performed to understand gene functions. The CIBERSORT algorithm and NetworkAnalyst were used to examine the relationship of immune cell infiltration with gene expression and to predict transcription factors and microRNAs interactions. The Connectivity Map database was used to predict drug interactions with these genes. Results: TRUB1, PLEKHA7, and FABP6 were identified as key genes enriched in pathways related to immune cell function and signaling. Seven TFs and nineteen miRNAs were found to interact with these genes. Nineteen drugs, including atorvastatin and paroxetine, were predicted to be significantly associated with these genes and potential therapeutic agents for COVID-19 and depression. Conclusions: This research provides new insights into the molecular mechanisms of post-COVID-19 depression and suggests potential therapeutic strategies, marking a step forward in understanding and treating this complex comorbidity.收起

文献类型

期刊