While COVID-19 liver injuries have been reported in various studies, concerns are raised about disease-drug reactions in COVID-19 patients. In this study, we examined the hypothesis of gene-disease interactions in an in-silico model of gene expression to seek changes in cytochrome P450 genes. The Gene Expression Omnibus dataset of the liver autopsy in deceased COVID-19 patients (GSE150316) was used in this study. Non-alcoholic fatty liver biopsies were used as the control (GSE167523). Besides, gene expression analysis was performed using the DESeq/EdgeR method. The GO databases were used, and the paths were set at p<0.05. The drug-gene interaction database (DGIdb) was searched for interactions. According to the results, 5,147 genes were downregulated, and 5,122 genes were upregulated in SARS-CoV-2 compared to healthy livers. Compared to the cytochromes, 34 cytochromes were downregulated, while 4 cytochromes were upregulated among the detected differentially expressed genes (DEG). The drug-gene interaction database (DGIdb) provided a list of medications with potential interactions with COVID-19 as well as metacetamol, phenethyl isocyanate, amodiaquine, spironolactone, amiloride, acenocoumarol, clopidogrel, phenprocoumon, trimipramine, phenazepam, etc. Besides, dietary compounds of isoflavones, valerian, and coumarin, as well as caffeine metabolism were shown to have possible interactions with COVID-19 disease. Our study showed that expression levels of cytochrome P450 genes could get altered following COVID-19. In addition, a drug-disease interaction list is recommended to be used for evaluations in clinical considerations in further studies.
Drug-disease interactions of differentially expressed genes in COVID-19 liver samples: an in-silico analysis