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. 2023 Oct 23;24(20):15471.
doi: 10.3390/ijms242015471.

Pharmacogenomic Landscape of Ivermectin and Selective Antioxidants: Exploring Gene Interplay in the Context of Long COVID

Ying-Fei Yang  1 , Sher Singh  2
Affiliations

Pharmacogenomic Landscape of Ivermectin and Selective Antioxidants: Exploring Gene Interplay in the Context of Long COVID

Ying-Fei Yang et al. Int J Mol Sci. .

Abstract

COVID-19 pandemic has caused widespread panic and fear among the global population. As such, repurposing drugs are being used as viable therapeutic options due to the limited effective treatments for Long COVID symptoms. Ivermectin is one of the emerging repurposed drugs that has been shown effective to have antiviral effects in clinical trials. In addition, antioxidant compounds are also gaining attention due to their capabilities of reducing inflammation and severity of symptoms. Due to the absence of knowledge in pharmacogenomics and modes of actions in the human body for these compounds, this study aims to provide a pharmacogenomic profile for the combination of ivermectin and six selected antioxidants (epigallocatechin gallate (EGCG), curcumin, sesamin, anthocyanins, quercetin, and N-acetylcysteine (NAC)) as potentially effective regimens for long COVID symptoms. Results showed that there were 12 interacting genes found among the ivermectin, 6 antioxidants, and COVID-19. For network pharmacology, the 12 common interacting genes/proteins had the highest associations with Pertussis pathway, AGE-RAGE signaling pathway in diabetic complications, and colorectal cancer in the Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses. Disease analyses also revealed that the top three relevant diseases with COVID-19 infections were diabetes mellitus, ischemia, reperfusion injury. We also identified 6 potential target microRNAs (miRNAs) of the 12 commonly curated genes used as molecular biomarkers for COVID-19 treatments. The established pharmacogenomic network, disease analyses, and identified miRNAs could facilitate developments of effective regimens for chronic sequelae of COVID-19 especially in this post-pandemic era. However, further studies and clinical trials are needed to substantiate the effectiveness and dosages for COVID-19 treatments.

Keywords: antioxidant compounds; disease analyses; ivermectin; long COVID; network pharmacology; pharmacogenomics.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
The chemical structures of (a) ivermectin and the six investigated antioxidants including (b) curcumin, (c) sesamin, (d) anthocyanins, (e) epigallocatechin gallate (EGCG), (f) quercetin, and (g) N-acetylcysteine (NAC). Chemical structures were visualized using SwissBioisostere (http://www.swissbioisostere.ch/ (accessed on 27 August 2023)) [13] from Canonical SMILES.
Figure 2
Figure 2
Venn diagram of the interacting genes between (A) ivermectin and COVID-19, or (B) the six investigated antioxidants and COVID-19.
Figure 3
Figure 3
Gene ontology analyses of (A) biological process (BP), where circle size and color indicate the number of occurrences of GO terms in the secreted gene set annotation list, (B) cellular component (CC), and (C) molecular function (MF) scatterplot. (D) Ontology enrichment clustering network. Cluster annotations are shown in color code.
Figure 3
Figure 3
Gene ontology analyses of (A) biological process (BP), where circle size and color indicate the number of occurrences of GO terms in the secreted gene set annotation list, (B) cellular component (CC), and (C) molecular function (MF) scatterplot. (D) Ontology enrichment clustering network. Cluster annotations are shown in color code.
Figure 4
Figure 4
(A) KEGG pathway enrichment analysis for the target 12 genes. The gene ratios refer to the ratio of enriched genes to all target genes, and counts refer to the number of enriched genes. KEGG pathway analyses for the (B) Pertussis pathway (hsa05133) and (C) AGE-RAGE signaling pathway in diabetic complications (hsa04933).
Figure 4
Figure 4
(A) KEGG pathway enrichment analysis for the target 12 genes. The gene ratios refer to the ratio of enriched genes to all target genes, and counts refer to the number of enriched genes. KEGG pathway analyses for the (B) Pertussis pathway (hsa05133) and (C) AGE-RAGE signaling pathway in diabetic complications (hsa04933).
Figure 4
Figure 4
(A) KEGG pathway enrichment analysis for the target 12 genes. The gene ratios refer to the ratio of enriched genes to all target genes, and counts refer to the number of enriched genes. KEGG pathway analyses for the (B) Pertussis pathway (hsa05133) and (C) AGE-RAGE signaling pathway in diabetic complications (hsa04933).
Figure 5
Figure 5
The PPI networks of the 12 common curated genes/proteins generated from the databases of (A) STRING and (B) GeneMANIA.
Figure 6
Figure 6
(A) Disease analysis and (B) the gene–disease network of ivermectin and the 6 investigated antioxidants and COVID-19.
Figure 6
Figure 6
(A) Disease analysis and (B) the gene–disease network of ivermectin and the 6 investigated antioxidants and COVID-19.
Figure 7
Figure 7
Potential targets of miRNAs to the 12 common curated genes.
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