Identification and Analysis of Biomarkers Associated with Lipophagy and Therapeutic Agents for COVID-19

Abstract

Background: Lipids, as a fundamental cell component, play an regulating role in controlling the different cellular biological processes involved in viral infections. A notable feature of coronavirus disease 2019 (COVID-19) is impaired lipid metabolism. The function of lipophagy-related genes in COVID-19 is unknown. The present study aimed to investigate biomarkers and drug targets associated with lipophagy and lipophagy-based therapeutic agents for COVID-19 through bioinformatics analysis. Methods: Lipophagy-related biomarkers for COVID-19 were identified using machine learning algorithms such as random forest, Support Vector Machine-Recursive Feature Elimination, Generalized Linear Model, and Extreme Gradient Boosting in three COVID-19-associated GEO datasets: scRNA-seq (GSE145926) and bulk RNA-seq (GSE183533 and GSE190496). The cMAP database was searched for potential COVID-19 medications. Results: The lipophagy pathway was downregulated, and the lipid droplet formation pathway was upregulated, resulting in impaired lipid metabolism. Seven lipophagy-related genes, including ACADVL, HYOU1, DAP, AUP1, PRXAB2, LSS, and PLIN2, were used as biomarkers and drug targets for COVID-19. Moreover, lipophagy may play a role in COVID-19 pathogenesis. As prospective drugs for treating COVID-19, seven potential downregulators (phenoxybenzamine, helveticoside, lanatoside C, geldanamycin, loperamide, pioglitazone, and trichostatin A) were discovered. These medication candidates showed remarkable binding energies against the seven biomarkers. Conclusions: The lipophagy-related genes ACADVL, HYOU1, DAP, AUP1, PRXAB2, LSS, and PLIN2 can be used as biomarkers and drug targets for COVID-19. Seven potential downregulators of these seven biomarkers may have therapeutic effects for treating COVID-19.

Keywords

• bioinformatics
• lipophagy-related genes
• COVID-19
• lipid metabolism
• therapeutic agents