(M1230-03-20) Pathological and Demographic Determinants of SARS-CoV-2-mediated Dysregulation of Drug Processing Pathways

Purpose: Several preclinical and clinical studies have shown that SARS-CoV-2 infection affects drug processing pathways and systemic drug concentrations [1–6]. Although the role of different SARS-CoV-2 variants, angiotensin II (AngII)-mediated NF-κB activation, age, sex, and infection site on COVID-19 severity and outcomes are well-established [7–12], their corresponding influence on SARS-CoV-2-mediated dysregulation of drug processing genes, including drug metabolizing enzymes and membrane transporters remain unknown. This study investigates how different SARS-CoV-2 variants, AngII administration, infection site, age, and sex influence SARS-CoV-2-mediated dysregulation of drug processing pathways and their underlying molecular mechanisms.

Methods: The influence of six different SARS-CoV-2 variants— B.1.1.7, D614G, Delta, BA.1, BA.2, and P.1 on the mRNA expression of 36 genes associated with drug metabolism and transport, inflammation, anti-inflammation, and transcriptional regulation of drug processing pathways were investigated in nasal turbinate and lung tissues of 21 male and 21 female Syrian golden hamsters. Additionally, the study evaluated the effect of AngII and D614G variant, both alone and in combination, on these genes of interest in the lung tissues of 23 male and 23 female Syrian golden hamsters aged four and seven months.

Results: SARS-CoV-2 variants induced a balanced immune response in the nasal turbinate (Figure 1) but triggered a hyperinflammatory state in the lung tissue of Syrian golden hamsters (Figure 2). Hence, more drug metabolizing enzymes, membrane transporters, and transcriptional regulators were dysregulated in the lung tissues compared to the nasal turbinates (Figures 1 and 2). For example, only CYP2E1 and FMO5 were dysregulated in the nasal turbinates (Figure 1), whereas AKR1A1, CYP2E1, GSTM3, NAT1, SLCO2B1, and SLC29A1 were dysregulated in the lung tissues (Figure 2). Interestingly, the P.1, D614G, and Delta variants were key contributors to this dysregulation in both nasal turbinates and lung tissues (Figures 1 and 2). Aging but not AngII administration potentiated D614G-mediated dysregulation of eight drug processing genes, two inflammatory genes, and five transcriptional regulatory genes (Figure 3). There was also a sex-dependent dysregulation of NAT2 by the D614G variant (p < 0.05). Finally, pairwise gene expression association analysis identified potential biomarkers for predicting SARS-CoV-2-mediated dysregulation of drug processing genes based on SARS-CoV-2 variants, infection site, age, and sex. For instance, in D614G-infected hamster lung tissues, IL1B expression is strongly negatively correlated with SLCO2B1 (r = -0.835) and GSTM3 (r = -0.884), whereas IL6 expression is strongly inversely correlated with NAT1 (r = -0.841) and CYP2E1 (r = -0.886) expression in the Delta-infected hamster lung tissues. On the contrary, in the nasal turbinates, CYP2E1 expression is strongly negatively correlated with NFKB1 expression (r = -0.861) following Delta infection, while FMO5 expression shows a very strong positive correlation with TNFA (r = 0.975), IL1B (r = 0.966), IL6 (r = 0.927), and IL10 (r = 0.904). Interestingly, lung PPARG expression is strongly inversely correlated with NAT2 expression (r = -0.700) in female hamsters compared to males. On the other hand, HIF1A expression is strongly positively correlated with SLCO2B1 (r = 0.840), CYP1B1 (r = 0.727), and SLC28A3 (r = 0.698) in seven-month-old hamsters compared to four-month-olds, while CYP1B1 expression is positively correlated with ABCG2 (r = 0.733), ABCC1 (r = 0.555), and AKR1A1 (r = 0.510)  in the older hamsters.

Conclusion: This study has shown for the first time the pathological and demographic factors that influence SARS-CoV-2-mediated dysregulation of drug processing genes, highlighting potential predictors of disease-drug interactions in the COVID-19 patient population. SARS-CoV-2 infection differentially elicits an immune response in Syrian golden hamsters' nasal turbinate and lung tissues. These immunopathological differences eventually culminate in more profound dysregulation of drug processing genes in the lung tissue compared to the nasal turbinates, suggesting that the site of infection impacts SARS-CoV-2-mediated dysregulation of drug processing genes. Out of the six investigated SARS-CoV-2 variants, P.1, D614G, and Delta variants played the most significant role in the dysregulation of drug processing genes, indicating the role of pathogenic variants in differentially modulating SARS-CoV-2-mediated dysregulation of drug processing genes. Older hamsters were more susceptible to SARS-CoV-2-mediated dysregulation of drug processing genes, suggesting that age is a potential risk factor for disease-drug interactions. Similarly, the preferential upregulation of NAT2 in males compared to females by D614G variant infection not only highlights sex as a potential risk factor for disease-drug interactions but also suggests potential disease-sex-gene-drug interactions because of the correlation between NAT2 genetic polymorphisms and anti-tuberculosis drug-induced liver injury, mostly involving NAT2 slow acetylators. The limited effect of AngII administration suggests that the renin-angiotensin-aldosterone pathway does not play a role in the SARS-CoV-2-mediated dysregulation of drug processing genes in the lung tissues of Syrian golden hamsters. Finally, potential biomarkers of SARS-CoV-2-mediated dysregulation of drug processing genes based on pathogenic variants, infection site, age, and sex were discovered. They could be useful for identifying patients that are at risk of COVID-19-drug interactions.

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Acknowledgements: This research is supported by funding from the Canadian Institutes of Health Research [Fund #514798] and the Leslie Dan Faculty of Pharmacy, University of Toronto [Fund #511794]. Chukwunonso Kingsley Nwabufo is a recipient of the Canadian Institutes of Health Research Doctoral Scholarship, Canadian Institutes of Health Research Doctoral Scholarship—Michael Smith Foreign Study Supplements Award, Ontario Graduate Scholarship, Pfizer Canada Graduate Fellowship, and Leslie Dan Faculty of Pharmacy Dean's Fellowship. Chukwunonso Kingsley Nwabufo was a former employee of Gilead Sciences and was involved in the development of remdesivir and lenacapavir. Chukwunonso Kingsley Nwabufo is employed by OneDrug Inc. The author does not have any conflicting interests associated with this research. Drs Samira Mubareka, Slava Epelman, Andra Banete, as well as Crystal Kantores are appreciated for their help with the SARS-CoV-2 infected hamster samples.All Syrian golden hamster studies were conducted in accordance with the animal user protocols # 20012669 (SARS-CoV-2 variants and sex difference studies in lung and nasal turbinate tissues) and # 20012663 ( AngII, D614G, and AngII + D614G, age, and sex difference studies in lung tissues), both approved by the Animal Care Committee at the University of Toronto, and in compliance with the guidelines of the Canadian Council on Animal Care.


Figure 1. Comparative analysis of selected genes associated with inflammation, anti-inflammation, transcriptional regulation, drug metabolism, and membrane transport in nasal turbinates from male and female Syrian golden hamsters, both with and without SARS-CoV-2 variants infection. A total of 42 male and female Syrian golden hamsters were randomly assigned into one of seven groups: mock, B.1.1.7, D614G, Delta, BA.1, BA.2, and P.1, with each group consisting of three males and three female hamsters. The hamsters were intranasally inoculated with 20 μL of either 10^4 TCID50 of the specific SARS-CoV-2 variant corresponding to the animal group or DMEM to the mock group, and necropsies were performed 3 dpi. Total RNA was extracted from the harvested hamster lung tissues and nasal turbinates, and the nCounter analysis system (NanoString Technologies, Seattle, WA) was used to conduct gene expression assay for 42 Syrian golden hamsters genes of interest (11 drug metabolizing enzymes, 12 membrane drug transporters, eight transcriptional regulators, four inflammatory markers, one anti-inflammatory marker, and six housekeeping genes). Thereafter, differential gene expression analysis was performed using nSolver® 4.0 software and the Advanced Analysis 2.0 package (NanoString Technologies, Seattle, WA) for the following 21 comparisons: each variant was compared individually to the mock baseline, and inter-variant comparisons included: D614G vs B.1.1.7, Delta vs B.1.1.7, BA.1 vs B.1.1.7, BA.2 vs B.1.1.7, P.1 vs B.1.1.7, Delta vs D614G, BA.1 vs D614G, BA.2 vs D614G, P.1 vs D614G, BA.1 vs Delta, BA.2 vs Delta, P.1 vs Delta, BA.2 vs BA.1, P.1 vs BA.1, and P.1 vs BA.2. The results are displayed in a box plot generated using GraphPad Prism (version 8.0 for Microsoft Windows, GraphPad Software, San Diego, CA, USA). The box represents the interquartile range, which spans from the first to the third quartile, while the whiskers extend to the minimum and maximum values. The line inside the box represents the median. Adjusted p-values are indicated as follows: *, P < 0.05; **, P < 0.01; ***, P < 0.001; ****, P < 0.0001.


Figure 2. Comparative analysis of selected genes associated with inflammation, anti-inflammation, transcriptional regulation, drug metabolism, and membrane transport in lung tissues from male and female Syrian golden hamsters, both with and without SARS-CoV-2 variants infection. A total of 42 male and female Syrian golden hamsters were randomly assigned into one of seven groups: mock, B.1.1.7, D614G, Delta, BA.1, BA.2, and P.1, with each group consisting of three males and three female hamsters. The hamsters were intranasally inoculated with 20 μL of either 10^4 TCID50 of the specific SARS-CoV-2 variant corresponding to the animal group or DMEM to the mock group, and necropsies were performed 3 dpi. Total RNA was extracted from the harvested hamster lung tissues and nasal turbinates, and the nCounter analysis system (NanoString Technologies, Seattle, WA) was used to conduct gene expression assay for 42 Syrian golden hamsters genes of interest (11 drug metabolizing enzymes, 12 membrane drug transporters, eight transcriptional regulators, four inflammatory markers, one anti-inflammatory marker, and six housekeeping genes). Thereafter, differential gene expression analysis was performed using nSolver® 4.0 software and the Advanced Analysis 2.0 package (NanoString Technologies, Seattle, WA) for the following 21 comparisons: each variant was compared individually to the mock baseline, and inter-variant comparisons included: D614G vs B.1.1.7, Delta vs B.1.1.7, BA.1 vs B.1.1.7, BA.2 vs B.1.1.7, P.1 vs B.1.1.7, Delta vs D614G, BA.1 vs D614G, BA.2 vs D614G, P.1 vs D614G, BA.1 vs Delta, BA.2 vs Delta, P.1 vs Delta, BA.2 vs BA.1, P.1 vs BA.1, and P.1 vs BA.2. The results are displayed in a box plot generated using GraphPad Prism (version 8.0 for Microsoft Windows, GraphPad Software, San Diego, CA, USA). The box represents the interquartile range, which spans from the first to the third quartile, while the whiskers extend to the minimum and maximum values. The line inside the box represents the median. Adjusted p-values are indicated as follows: *, P < 0.05; **, P < 0.01; ***, P < 0.001; ****, P < 0.0001.


Figure 3. Age-based comparative analysis of genes associated with inflammation, anti-inflammation, transcriptional regulation, drug metabolism, and membrane transport in lung tissues from male and female Syrian golden hamsters, both with and without treatments. A total of 46 male and female Syrian golden hamsters were housed until four or seven months old. Each age group was divided into four subgroups: mock, AngII, D614G, and AngII + D614G, with each subgroup consisting of three males and three females (except the seven-month-old mock group, which had two males and two females). The mock group underwent mock surgery on day 1, was inoculated with 100 µL DMEM on day 28, and euthanized on day 42. The D614G group was similarly treated but inoculated with 100 µL of 10^5 TCID50 D614G variant on day 28. Both AngII and AngII + D614G groups received implanted pumps delivering AngII (0.125 mg/kg/day) on day 1, and on day 28, were inoculated with 100 µL DMEM (AngII) or 100 µL 10^5 TCID50 D614G variant (AngII + D614G), followed by euthanasia on day 42. Total RNA was extracted from the harvested hamster lung tissues and the nCounter analysis system (NanoString Technologies, Seattle, WA) was used to conduct gene expression assay for 42 Syrian golden hamster genes of interest (11 drug metabolizing enzymes, 12 membrane drug transporters, eight transcriptional regulators, four inflammatory markers, one anti-inflammatory marker, and six housekeeping genes). Thereafter, differential gene expression analysis was performed using nSolver® 4.0 software and the Advanced Analysis 2.0 package (NanoString Technologies, Seattle, WA). The age-based differential gene expression comparisons were performed as follows: mock 7 months vs mock 4 months, AngII 7 months vs AngII 4 months, D614G 7 months vs D614G 4 months, and AngII + D614G 7 months vs AngII + D614G 4 months. Adjusted p-values are indicated as follows: *, P < 0.05; **, P < 0.01; ***, P < 0.001; ****, P < 0.0001.