Demonstration of the impact of COVID-19 on metabolic associated fatty liver disease by bioinformatics and system biology approach

Tengda Huang, Dawei Zheng, Yujia Song, Hongyuan Pan, Guoteng Qiu, Yuchu Xiang, Zichen Wang, Fang Wang

Research output: Contribution to journalArticlepeer-review

2 Scopus citations

Abstract

Background: Severe coronavirus disease 2019 (COVID-19) has caused a great threat to human health. Metabolic associated fatty liver disease (MAFLD) is a liver disease with a high prevalence rate. Previous studies indicated that MAFLD led to increased mortality and severe case rates of COVID-19 patients, but its mechanism remains unclear. Methods: This study analyzed the transcriptional profiles of COVID-19 and MAFLD patients and their respective healthy controls from the perspectives of bioinformatics and systems biology to explore the underlying molecular mechanisms between the 2 diseases. Specifically, gene expression profiles of COVID-19 and MAFLD patients were acquired from the gene expression omnibus datasets and screened shared differentially expressed genes (DEGs). Gene ontology and pathway function enrichment analysis were performed for common DEGs to reveal the regulatory relationship between the 2 diseases. Besides, the hub genes were extracted by constructing a protein-protein interaction network of shared DEGs. Based on these hub genes, we conducted regulatory network analysis of microRNA/transcription factors-genes and gene - disease relationship and predicted potential drugs for the treatment of COVID-19 and MAFLD. Results: A total of 3734 and 589 DEGs were screened from the transcriptome data of MAFLD (GSE183229) and COVID-19 (GSE196822), respectively, and 80 common DEGs were identified between COVID-19 and MAFLD. Functional enrichment analysis revealed that the shared DEGs were involved in inflammatory reaction, immune response and metabolic regulation. In addition, 10 hub genes including SERPINE1, IL1RN, THBS1, TNFAIP6, GADD45B, TNFRSF12A, PLA2G7, PTGES, PTX3 and GADD45G were identified. From the interaction network analysis, 41 transcription factors and 151 micro-RNAs were found to be the regulatory signals. Some mental, Inflammatory, liver diseases were found to be most related with the hub genes. Importantly, parthenolide, luteolin, apigenin and MS-275 have shown possibility as therapeutic agents against COVID-19 and MAFLD. Conclusion: This study reveals the potential common pathogenesis between MAFLD and COVID-19, providing novel clues for future research and treatment of MAFLD and severe acute respiratory syndrome coronavirus 2 infection.

Original languageEnglish
Pages (from-to)E34570
JournalMedicine (United States)
Volume102
Issue number35
DOIs
StatePublished - 1 Sep 2023
Externally publishedYes

Keywords

  • COVID-19
  • differentially expressed genes
  • drug molecules
  • MAFLD
  • protein-protein interaction

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