Influence of CYP3A4 and CYP3A5 Genetic Variants on Clinical Outcomes in Methylprednisolone-Treated, Hospitalized COVID-19 Patients in Manaus, Brazil

Influence of CYP3A4 and CYP3A5 Genetic Variants on Clinical Outcomes in Methylprednisolone-Treated, Hospitalized COVID-19 Patients in Manaus, Brazil | Authorea try { document.documentElement.classList.add('js'); } catch (e) { } var _gaq = _gaq || []; _gaq.push(['_setAccount', 'G-8VDV14Y67G']); _gaq.push(['_trackPageview']); (function() { var ga = document.createElement('script'); ga.type = 'text/javascript'; ga.async = true; ga.src = ('https:' == document.location.protocol ? 'https://ssl' : 'http://www') + '.google-analytics.com/ga.js'; var s = document.getElementsByTagName('script')[0]; s.parentNode.insertBefore(ga, s); })(); Skip to main content Preprints Collections Wiley Open Research IET Open Research Ecological Society of Japan All Collections About About Authorea FAQs Contact Us Quick Search anywhere Search for preprint articles, keywords, etc. Search Search ADVANCED SEARCH SCROLL This is a preprint and has not been peer reviewed. Data may be preliminary. 9 April 2026 V1 Latest version Share on Influence of CYP3A4 and CYP3A5 Genetic Variants on Clinical Outcomes in Methylprednisolone-Treated, Hospitalized COVID-19 Patients in Manaus, Brazil Authors : Victor I. Mwangi 0000-0002-2618-3816 , Marielle M. Macêdo , Ana C. Shuan Laco , Vanessa K. C. Godinho , Rebeca L.A. Netto , Bernado M. Silva 0000-0002-5989-1288 , Fernanda Rodrigues-Soares , Fernando Almeida-Val , Marcus Lacerda , Anne C. G. Almeida , and Gisely Melo [email protected] Authors Info & Affiliations https://doi.org/10.22541/au.177571298.89733492/v1 240 views 79 downloads Contents Abstract Information & Authors Metrics & Citations View Options References Figures Tables Media Share Abstract Aims: This study investigated whether common CYP3A4 and CYP3A5 variants are associated with clinical outcomes in hospitalized COVID-19 patients treated with MP in Manaus, Brazil. Methods: A pharmacogenetic analysis was conducted on 100 hospitalized COVID-19 patients enrolled in a randomized, placebo-controlled clinical trial receiving heavy-dose intravenous MP (n = 49) or placebo (n = 51), for five days. CYP3A4 : c.-392G>A (rs2740574, CYP3A4*1.002 ) and CYP3A5 (rs776746 - *3 and rs10264272 - *6 ) variants were genotyped. Associations between genotypes, treatment outcomes, and time to discharge or death were analyzed using χ 2 tests, Kaplan-Meier curves, and Cox regression. Results: Allele frequencies of CYP3A4*1.002 (86%), CYP3A5*3 (70%), and CYP3A5*6 (2%) were within those reported in admixed Latin American populations . Genotype distributions did not differ significantly between treatment groups or outcome categories. Carriers of CYP3A5 wild-type (*1/*1) genotypes had shorter hospital stay (p = 0.012), and this genotype did not influence mortality. Adjusted Cox models showed only sex, comorbidities, and weight predicted discharge likelihood in both CYP3A4 and CYP3A5 models (p<0.05). Conclusion: CYP3A4 and CYP3A5 variants were associated with modest differences in hospital length of stay but did not independently influence survival among MP-treated COVID-19 patients. Host genetic variation in CYP3A-mediated metabolism may contribute to variability in recovery dynamics, although clinical characteristics remained dominant determinants of clinical outcome. 1. Introduction The COVID-19 disease is still active, with 43,500 new cases reported globally at the end of January 2026 1 . Among the most prominent interventions in the clinical management of severe COVID-19, corticosteroids such as dexamethasone and methylprednisolone (MP) were implemented to attenuate the dysregulated inflammatory response 2–4 . The RECOVERY trial provided robust evidence that low-dose dexamethasone (6mg/day for 10 days) significantly reduced mortality in patients requiring supplemental oxygen or mechanical ventilation response 3 . In contrast, MetCOVID trial, which evaluated weight-based dosing of MP (0.5mg/Kg twice daily for 5 days), did not demonstrate mortality benefit, thereby highlighting controversies regarding the efficacy of these corticosteroids 4,5 . Although dexamethasone and MP played central roles in severe COVID-19 management, their relative benefits differed a lot in clinical outcomes 6,7 . These discrepancies may be attributed in part to variations in dosing regimens, timing of administration after illness onset, underlying disease status, and intensity of COVID-19 at the time of treatment 5 . In Brazil and across the world, MP was a key treatment used on severe COVID-19 cases. A critical factor influencing treatment outcomes for methylprednisolone (MP) is the underlying genetic diversity of the patient population 8,9 . Beyond standard treatment variables, inter-individual genetic variation significantly modulates the pharmacological response to glucocorticoid (GC) medications, impacting both therapeutic efficacy and the incidence of adverse effects 10 . Specifically, genetic polymorphisms can alter key components of the GC system, including the glucocorticoid receptor (GR), associated co-chaperones, and the enzymes/transporters responsible for GC metabolism 11 . The improved solubility of MP, a widely available water-soluble sodium succinate ester, facilitates both intravenous and intramuscular delivery. The chemically modified MP is rapidly hydrolyzed in vivo to methylprednisolone, thus improving bioavailability, leading to an immediate peak plasma concentration after intravenous administration. This supports the classification of MP as a prodrug 12 . In the body, the metabolism of MP is primarily mediated by cytochrome P450 (CYP) enzymes, particularly CYP3A4 and CYP3A5 13 . CYP3A4 is expressed predominantly in the liver, and is the most abundant CYP enzyme in the liver (14.5-37%) 14 . It is also abundant in the human intestinal epithelial cells. On the other hand, CYP3A5 is expressed at about 10.6% of CYP3A4 15 . Together, CYP3A4/5 enzymes metabolize between 30-50% of known drugs 16 . Whereas CYP3A4 has a broad substrate specificity, allowing it to metabolize a wide range of structurally diverse compounds, CYP3A5 that is 83% homologous to CYP3A4, has a narrower substrate preference. A study of genetic variants in glucocorticoid-pathway genes among indigenous Amazonian populations showed that their distinct genetic profile may influence the risk of adverse responses to corticosteroid therapy (prednisolone or dexamethasone) in the treatment of acute lymphoblastic leukemia 17 . The impact of CYP genetic polymorphisms on COVID-19 outcomes and corticosteroid treatment remains unexplored. Understanding these genetic variables is critical for improving GC therapy and reducing potential negative effects. Therefore, to address this knowledge gap and inform future approaches to personalized COVID-19 and other acute respiratory distress syndrome (ARDS) therapy, we conducted a pharmacogenetic analysis on our cohort involving COVID-19 patients who had been randomly assigned to receive either high-dose MP or placebo, aiming to determine whether variants in CYP3A4 and CYP3A5 modulate the clinical response to MP. 2. Methods 2.1 Study Design and Participants Participants were drawn from the MetCOVID clinical trial cohort (ClinicalTrials Identifier NCT04343729), which was a phase IIb clinical trial involving hospitalized COVID-19 patients of either sex, aged ≥ 18 years with clinical, epidemiological and/or radiological suspected COVID-19, at a tertiary care facility in Manaus, Brazil 4 . The patients were randomly allocated (1:1 ratio) to receive either intravenous MP sodium succinate (1 mg/kg) or placebo (standard care), daily, for 5 days 4 . Socio-demographic characteristics, clinical data, comorbidities, previous medication used, and treatment outcomes (discharge or death) over a 14-day follow-up period were recorded. Using convenience sampling, 100 hospitalized participants (MP=49, and placebo=51) from the MetCOVID study, with confirmed SARS-CoV-2 infection by PCR and who had completed the 5-day treatment regimen, were included in the current study involving pharmacogenetics analysis. 2.2 DNA extraction, Genotyping and Pharmacogenetic assays Approximately 200μL of whole peripheral blood samples initially collected from the participants and stored at -80 o C were retrieved from the biorepository for DNA extraction and CYP3A4/5 genotyping. Genomic DNA was extracted using the QIAmp® Blood Mini kit (Qiagen, Hilden, Germany), following the manufacturer’s recommendations. A Nano Drop spectrophotometer (Nano Drop Technologies Inc., DE, USA) was used for measuring DNA concentration and purity. Genotyping was performed for CYP3A4*1.002 c.-392G>A (rs2740574) (formerly CYP3A4*1B ), CYP3A5*3 6981A>G (rs776746) and CYP3A5*6 14685G>A (rs10264272). CYP3A4 and CYP3A5 genotyping tests were performed using real-time PCR (7500 Fast Real-Time PCR System), Applied Biosystems, Foster City, CA, USA, and TaqMan® probes, using TaqMan™ Drug Metabolism Genotyping Assay (ThermoFisher scientific®, South San Francisco, CA, USA), following manufacturer instructions. Amplification reactions and cycling parameters were determined according to the manufacturer’s protocols. These targets were selected based on their known functional relevance. The CYP3A4*1.002 variant is associated with increased CYP3A4 activity or expression 18 , while the two CYP3A5 variants are the most common non-functional variants, resulting in a non-functional enzyme 19 . Additionally, previous studies demonstrated a large frequency of these variants, CYP3A5*3 , in the Brazilian Amazon region 20,21 . 2.3 Statistical Analysis Descriptive statistics compared baseline characteristics between groups using t -test or the Wilcoxon – Mann-Whitney test for the mean and standard deviation (SD) or median and interquartile range (IQR) values. Categorical variables were expressed in absolute value (n) and relative frequency (%) and the frequency distribution was tested for significant difference using chi-square or Fisher’s exact tests. Chi-square tests also assessed differences in allele and genotype frequencies. Relative risks (RR) were calculated for treatment effects and genotypic associations. Kaplan Meier survival curves were done for time to outcomes between the CYP3A4/5 variant carriers. The Hardy-Weinberg equilibrium (HWE) was determined with SELOME p-value calculations using the Hardy-Weinberg package in R. In all analyses, p < 0.05 was set as the significance threshold. 2.4 Ethical Considerations This study was approved by the Fundação de Medicina Tropical Dr. Heitor Vieira Dourado (FMT-HVD)’s Ethical Review Committee (CAAE: 80890124.9.0000.0005 / Approval Number: 6.945.835). 3. Results 3.1 Baseline Characteristics Participants had a mean age of 57.6 ± 15.4 years; 68% were male, and most self-reported mixed ethnicity (79%). Most patients (91%) had reported having comorbidities, particularly hypertension (60.4%), obesity (37.4%), and diabetes (29.7%). All participants had reported the use of other medications, but antibiotics (75.0%) and angiotensin-converting enzyme (ACE) inhibitors (47.0%) were frequently used (Table 1). 3.2 CYP3A4 and CYP3A5 Variants Grouped by treatment arms, no significant differences in allele or diplotype frequencies were observed (p > 0.05). CYP3A4 * 1.002 and CYP3A5* 3 were the most common alleles (0.86 and 0.70), while CYP3A5* 6 had the least frequency (0.02). CYP3A4*1.001/*1.002 and CYP3A5 *3/*3 were the most frequent diplotypes (0.72 and 0.52 , respectively). The distribution of the alleles and diplotypes between the treatment arms was comparable (Table 2). All single nucleotide polymorphisms (SNPs) followed Hardy-Weinberg equilibrium when analyzed separately for each group (p>0.05). The distribution of CYP3A4*1.001 between the two outcomes was similar (14.7% vs 11.4%, p=0.57). A similar observation was made for the CYP3A4*1.002 allele, which was marginally more frequent among the deceased than in the discharged (88.6% vs 85.3%, p=0.57). Additionally, CYP3A5*1 was more prevalent among deceased patients compared with discharged patients (15/44, 34.1% vs. 41/156, 26.3%, p=0.31), while CYP3A5*3 was more prevalent among discharged patients than the deceased (111/156, 71.2% vs. 29/44, 65.9%, p=0.50). The CYP3A5*6 allele was detected exclusively in discharged patients (4/156, 2.6%). Overall, no statistically significant differences were observed in allele or diplotype distributions across clinical outcomes (p > 0.05) (Table 3). A comparison of the allele frequencies by treatment groups in either of the outcomes also revealed no remarkable differences between CYP3A4 or CYP3A5 allele/diplotype frequencies (Supplementary Table 1). 3.3 Association between outcome and CYP3A4/5 polymorphisms: Time to outcome and relative risks Using Kaplan-Meier curves, we evaluated the association between CYP3A4 and CYP3A5 diplotype variants and clinical outcomes, specifically time to hospital discharge and time to death (Figure 1). Interestingly, our analysis suggested that patients having the c.-392G>A variant defining CYP3A4*1.002 showed no remarkable difference in hospital stay time (Figure 1A, p = 0.12), nor time to death (Figure 1B, p = 0.75) when compared to wild type individuals ( CYP3A4*1.001/*1.001 ). For CYP3A5 variants, wild-type individuals were discharged significantly earlier than those with the mutated allele (Figure 1C, p = 0.017). In contrast, no significant differences were observed in time to death between mutant and wild-type groups (Figure 1D, p = 0.2). A further relative risk analysis confirmed there was no significant difference in outcomes (discharge/mortality) between variant and wild type carriers (Table 4). Likewise, there were no significant differences observed in the outcomes (discharge/mortality) relative to the diplotype carried (variant or wild type) following the treatments. 3.4 Clinical factors as a predictor of hospital discharge outcomes After adjusting for covariates, neither genotype independently predicted patient discharge or death. In a Cox proportional hazards model evaluating time to hospital discharge with death treated as a censoring event, our analysis suggested that presence of a CYP3A4 variant allele, whether it appears in homozygosity or heterozygosity, was not associated with discharge timing (HR 0.91, 95% CI 0.31–2.68; p = 0.864). Sex (HR 0.21, 95% CI 0.05–0.93; p = 0.040), body weight (HR 0.90, 95% CI 0.82–0.98; p = 0.018), and the presence of comorbidities at admission (HR 0.12, 95% CI 0.03–0.43; p = 0.001) were independently associated with prolonged hospitalization on basis of the CYP3A4 genotype. Age, treatment group, BMI, and time to hospitalization were not significantly associated with discharge outcomes. The overall model was statistically significant (Wald χ² = 24.72, p = 0.0017). Similarly, presence of a CYP3A5 variant allele, either in homozygosity or heterozygosity, was not significantly associated with discharge outcomes (HR 0.54, 95% CI 0.16–1.85; p = 0.328). However, a higher body weight (HR 0.90, 95% CI 0.83–0.99; p = 0.025) and the presence of comorbidities at admission (HR 0.14, 95% CI 0.04–0.53; p = 0.004) were independently associated with prolonged hospitalization among CYP3A5 variant allele carriers. Sex showed a borderline association with discharge timing (HR 0.25, 95% CI 0.06–1.04; p = 0.057), whereas age, treatment group, BMI, and time to hospitalization were not significantly associated with the outcome. The overall model was statistically significant (Wald χ² = 25.04, p = 0.0015) (Table 5). Additionally, an initial comparative analysis revealed a significant difference in outcomes between participants based on weight and BMI. Patients who died had significantly lower average weight [70.2 (13.5) vs 80.3 (20.0) kg] and BMI [25.9 (23.4-28.6) vs 28.5 (25.4-32.7)], than the discharged patients. 4. Discussion This study represents one of the first pharmacogenetic investigations to evaluate the role of CYP3A4 and CYP3A5 genetic variability on clinical outcomes in hospitalized COVID-19 patients after MP therapy in a randomized, placebo-controlled setting in Brazil 4,22 . Conducted in Manaus, an epicenter of the COVID-19 pandemic in the Brazilian Amazon region, this work addresses a critical knowledge gap at the intersection of host genetics, corticosteroid pharmacology, and infectious disease outcomes in an understudied, genetically admixed population. By integrating genotypic data with detailed clinical outcomes, our study provides important context-specific insight into the potential and limitations of pharmacogenetics in optimizing corticosteroid therapy, contributing to the broader global effort to understand determinants of treatment response in severe viral infections. With the lack of a completely effective drug to treat COVID-19, most pharmacotherapeutic interventions used merely relieved symptoms and were applied based on disease severity. Guidelines advocated for the use of antiviral agents (remdesivir, lopinavir/ritonavir, oseltamivir), antibiotics (azithromycin), antiparasitics (chloroquine, hydroxychloroquine, ivermectin), and corticosteroids (dexamethasone, MP) 23 . Corticosteroids were often favored as an intervention in managing ARDS, the major cause of morbidity among the COVID-19 patients 24 . While corticosteroids were widely used in managing COVID-19 because of their anti-inflammatory and immunosuppressive properties, their effectiveness as a treatment option remained controversial because of an inherent variability in drug response 25 . Variation in the rates of desirable outcomes has been influenced by factors such as reason for their use, time of application, interaction with other medications, dosage used, stage of disease severity and even patient genetics 26,27 . Corticosteroid mechanistic and metabolic pathways are complex. The metabolic biotransformation of glucocorticoids, including MP, is primarily hepatic, driven by cytochrome P450 enzymes (specifically CYP3A4, CYP3A5, and CYP3A7), which convert the prodrug methylprednisolone sodium succinate into active methylprednisolone and its metabolites 28 . Production of functional enzymes can thus be influenced by genetics. A review by Takahashi (2020) noted that although many variants have been associated with corticosteroids response and toxicities across multiple disease conditions, including genes involved in metabolizing enzymes (e.g., CYP3A4, CYP3A5, CYP3A7, GSTT1), there was no pharmacogenetic information to guide corticosteroid treatment decisions for ARDS in COVID-19 29 . Alterations in CYP3A enzymes, which regulate corticosteroid biotransformation in vivo , can lead to variations in corticosteroid responses. These alterations may be influenced by a hereditary factor, by environmental factors like BMI, alcohol consumption, and smoking habit/quantity, or due to SNPs in the CYP3A4/5 genes resulting in low enzyme activity 14 . The CYP3A4/5 enzymes, members of the cytochrome P450 3A family, are key in metabolizing MP. Data suggest that CYP3A4 enzyme is the most influential in determining MP clearance, and genetic variations associated with CYP3A4 are strongly associated with reduced drug metabolism. While the CYP3A5*3/*3 genotype results in minimal CYP3A5 enzyme expression and activity, it did not fully explain low MP metabolism in some white North Americans, despite the high prevalence of homozygous CYP3A5*3 in white populations 30 . There are key factors regulating the expression of cytochrome P450 enzymes, including genetic polymorphisms, hormonal and cytokine-mediated pathways, and disease state 31,32 . Importantly, multi-allelic genetic variants, which differ significantly across ethnic groups, define distinct pharmacogenetic phenotypes ranging from poor and intermediate to extensive and ultra-rapid metabolizers 33,34 . The multi-allelic polymorphism nature of CYP3A4/5 genes can lead to a variable CYP3A4/5 enzyme activity profile even within the same ethnic population. For instance, carriers of the CYP3A5*3 allele, such as those with *3/*3 or *3/*6 diplotypes, produce non-functional CYP3A5 enzymes and are therefore classified as poor metabolizers of CYP3A5 substrate drugs. In contrast, individuals who do not carry the CYP3A5*3 allele possess functional enzyme activity and are able to effectively metabolize drugs such as tacrolimus and nifedipine 16,35,36 . From our study, the distribution frequency of CYP3A4/5 variants confirms observations reported elsewhere. CYP3A4*1.002 (-392G>A; rs2740574) is frequently detected in Africans (76.6%). At 14.0%, the CYP3A4*1.002 allelic frequency in this northern Brazil cohort was similar to 10.5-11.3% reported for Latin Americans 37,38 . Likewise, we observed a CYP3A5*6 frequency of 2% in this region, which was within the 1.78-2.31% range reported elsewhere 37,39 . CYP3A5*6 (14690G>A; rs10264272) is considered a nonfunctional allele and is present predominantly in the African American population (7-17%) 40,41 , and occasionally in the white European and Asian populations 40,42,43 . Finally, CYP3A5*3 is reported as prevalent in many populations, and is the most frequent and well-studied variant allele of CYP3A5 . Its frequency varies widely across human populations 44,45 . In our predominantly mixed-race northern Brazil cohort, the estimated CYP3A5*3 allele frequency was 70%. Our findings are slightly lower but comparable to a reported 78.09% for Latino/admixed Americans from Latin America 37,46 . Contrastingly, this allele’s frequency among a white European population is estimated to be 82-95% 42 . The lack of significant associations between CYP3A4 or CYP3A5 allele/diplotype frequencies and patient outcomes (discharged vs. deceased) in our analysis suggests that these genetic variations do not appear to influence the likelihood of patient survival or recovery, with respect to the use of MP. The CYP3A4 gene is located on chromosome 7q22.1, which alleles are known as CYP3A4*1.001 (formerly *1B ) in wild-type individuals 47,48 . CYP3A4 gene codes for the CYP3A4 enzyme that is critical for the metabolism of rivaroxaban, and polymorphisms of the CYP3A4 significantly affect the activity of rivaroxaban 49 . The CYP3A4*1.002 allele (formerly *1A ) is defined by a substitution of an adenine by a guanine in the promoter region of the gene (AF280107.01, -392G>A). This variant is located in the promoter region of the CYP3A4 gene. As a regulatory SNP, it reduces gene expression and consequently decreases enzymatic activity. In the heterozygous state, it is associated with approximately a 20% reduction in rivaroxaban metabolism compared with the wild-type enzyme 49 . Although the CYP3A4*1.001 allele (at rs2740574) is the minor frequent variant and results in standard enzyme activity, it is currently excluded from routine clinical diagnostic panels. Similarly, CYP3A4*1.002 is omitted because its presence across multiple different genetic backgrounds (haplotypes) makes its specific impact difficult to isolate using standard tests 44 . When assessing the influence of CYP3A4/5 variants on time to outcome post-treatment, we found that CYP3A5*1/*1 diplotype was linked to a shorter hospital stay. This suggested that carriers of this variant had favorable response to treatment leading to rapid clinical improvement, possibly driven by faster drug metabolism in the context of high-dose methylprednisolone therapy. Elsewhere, a multiple myeloma study demonstrated that CYP3A5*3/*3 genotypes appeared to be associated with shorter progression-free survival time, despite these carriers reaching higher peak melphalan plasma concentrations compared to non-carriers of CYP3A4*1B (CYP3A4*1.001) and CYP3A5*3 50 . In an different study involving Slovenian COVID-19 patients, the CYP3A4 rs35599367-rs2740574 TA haplotypes were found to be associated with longer hospitalization (p = = 1.138–38.692: p = 0.035), while CG was associated with longer hospitalization (p = <0.001), when compared with the most common CYP3A4 CA haplotype 10 , contrasting with our Kaplan–Meier analysis for the CYP3A4 time to discharge. Thus, taken together, this indicates that the clinical impact of CYP3A4/5 polymorphisms can be highly drug- and context-dependent. The Kaplan–Meier analysis suggested that wild-type CYP3A5 diplotypes may be a potential factor of interest influencing duration of hospital stay following the corticosteroid intervention. A plausible explanation is the presence of functional CYP3A5 enzyme activity in the liver and extrahepatic tissues, which may enhance corticosteroid metabolism. This increased metabolic capacity could optimize drug exposure and ameliorate the inflammation, thereby shortening hospitalization in these patients 41 . Although there was no remarkable difference in the ages of discharged patients, with or without mutated CYP3A4 , we observed that discharged patients with CYP3A4 variants had significant excess body weight compared to those with wildtype CY3A4 . It is possible that this, combined with the diplotype, incites decreased sensitivity to MP that consequently hinders effective reduction of systemic inflammation in this group of patients. However, further pharmacokinetic studies involving overweight patients with mutated CYP3A4 genes are clearly needed to verify and demonstrate a diminished sensitivity to corticosteroids. As for patients with mutated CYP3A5 gene requiring significantly longer time to discharge, this can be attributed to the predominance of the non-functional CYP3A5 enzyme present in this group, arising from the non-functional CYP3A5*3 variant of CYP3A5 19 . We note that in this Brazilian cohort, CYP3A4 and CYP3A5 genetic variants showed limited impact on treatment outcomes following methylprednisolone therapy. Although the CYP3A5 wild-type homozygotes were discharged earlier, these associations were not independent of comorbidities, weight and to an extent patient sex, which consistently predicted recovery likelihood. Previous studies observed that age, gender, daily routines, medication use, and health conditions were other influencing factors of inter-individual variations in CYP3A4/5 activity 51,52 . Additionally, intra-individual differences are mainly due to the generation of variants by SNPs in the corresponding coding regions of CYP3A4/5 . These SNPs subsequently affect the downstream gene processes of transcription, translation, and protein synthesis, affecting the biological expression level of CYP3A4/5 , resulting in differences in the metabolic efficiency of various drugs among individuals 16 . Regarding relative risk of mortality, these findings suggest that, within the limits of this cohort, common functional variants in CYP3A4 and CYP3A5 were not independently associated with mortality risk. Although carriers of CYP3A4*1.001 and CYP3A5*3 and *6 alleles showed slightly higher relative risk estimates compared with wild-type genotypes, there may be limited statistical power. Nonetheless, the consistent direction and magnitude of effect estimates imply that CYP3A4/5 polymorphisms alone are unlikely to be major determinants of clinical outcome in this cohort, perhaps limited by sample size and reduced power. Our findings suggest that clinical factors like weight and presence of underlying comorbidities were important determinants of post-intervention outcomes. In our case, the presence of comorbidities indicated a large disparity in the likelihood of favorable hospital discharge, likely reflecting how these factors, along with others, decline patient immunity and physiological resilience. The variability in MP treatment outcomes observed across COVID-19 studies likely reflects a complex interplay among the CYP3A4/5 polymorphisms studied here, and perhaps with other CYP3A4/5 polymorphisms, patient factors, and potentially COVID-19–induced intestinal and hepatic injury caused by cytokine storm or direct viral cytopathy. Together, these factors may substantially influence drug metabolism and therapeutic efficacy, as well as patient outcomes. This study provides novel pharmacogenetic insights into corticosteroid response among hospitalized COVID-19 patients from an ethnically admixed background by integrating clinical outcomes with CYP3A4 and CYP3A5 genotyping in a randomized, placebo-controlled trial. Several limitations warrant consideration. The relatively small sample size limited statistical power to detect subtle genotype-outcome relationships or effects of rare alleles. Our cohort predates the emergence of the highly infectious Omicron variants; therefore, our findings should be interpreted within the clinical context of earlier SARS-CoV-2 lineages rather than across the full spectrum of variants. Our investigation was confined to only three genetic variants, excluding others that may have contributed to a more comprehensive genetic profile. The absence of pharmacokinetic data precluded direct assessment of genotype-dependent drug metabolism and the generalizability of this finding. Furthermore, the 14-day follow-up period may have been insufficient to capture delayed or long-term outcomes. Despite these limitations, the findings provide insights supporting continued investigation into the potential roles of CYP3A4*1.002 ( formerly CYP3A4*1B ) and CYP3A5*3 . The absence of association with mortality may reflect limited statistical power rather than true absence of pharmacogenetic effect. 5. Conclusion Our findings suggest that although CYP3A4 and CYP3A5 polymorphisms were associated with length of hospital stay in unadjusted analyses, Cox regression analysis revealed that patient weight, sex, and comorbidities are the primary determinants of clinical prognosis. These results indicate that these genotypes alone do not drive outcomes in this cohort; rather, a complex interplay between host genetics, COVID-19 pathology, and environmental factors govern CYP3A-mediated metabolism. Consequently, clinical characteristics, rather than CYP3A4 or CYP3A5 genotype alone, should be prioritized when optimizing methylprednisolone dosing strategies. Larger, multiethnic studies incorporating pharmacokinetic profiling are required to validate these findings and refine personalized corticosteroid protocols in COVID-19, ARDS, and related inflammatory syndromes to better clarify the independent or interacting effects of these variants on clinical outcomes. STUDY HIGHLIGHTS What is already known about this subject? Corticosteroids, including methylprednisolone (MP), are widely used to manage severe COVID-19, but clinical responses vary considerably. MP is primarily metabolized by CYP3A4 and CYP3A5 enzymes, whose genetic polymorphisms can alter drug metabolism and potentially influence treatment outcomes. However, pharmacogenetic evidence guiding corticosteroid use in COVID-19 or ARDS remains limited. What question did this study address? This study investigated whether common functional variants in CYP3A4 (*1.002) and CYP3A5 (*3, *6) are associated with clinical outcomes, specifically hospital discharge time and mortality, among hospitalized, mixed-race Brazilian COVID-19 patients treated with MP. What does this study add? The study found that CYP3A4/5 variants have a limited independent impact on survival in MP-treated patients. While CYP3A5 wild-type carriers had shorter hospital stays, this effect was not independent of clinical covariates. Specifically, sex, comorbidities, and body weight, remained the dominant predictors of discharge likelihood or treatment response. These findings suggest that while host genetics may influence recovery dynamics, routine CYP3A4/5 genotyping may have limited utility in guiding therapy. Emphasis should remain on clinical factors. Future translational efforts should integrate pharmacogenetics with pharmacokinetic data and patient characteristics to better inform personalized corticosteroid therapy. ACKNOWLEDGMENTS We give special thanks to the director and staff of Hospital e Pronto Socorro Delphina Rinaldi Abdel Aziz, Unidade de Pesquisa Clínica Carlos Borborema, and FMT-HVD as well as the participants recruited into the MetCOVID Study for their outstanding support. We also extend our gratitude to the Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) for a Junior Post-doctorate scholarship to author VIM (PDJ 175855/2023-4). Shear Flow Mechanism on the Hyperbottle: Addendum to the Topological Lagrangian Model for Field-Based Unification C. R. Gimarelli (December 25, 2025) \affiliation Independent Researcher DATA AVAILABILITY STATEMENT The datasets generated and/or analyzed during the current study can be requested from the corresponding author, subject to a reasonable access agreement. AUTHOR CONTRIBUTIONS V.I.M., F.F.A.V., F.R.S., A.C.G.A., and G.C.M. wrote the manuscript; V.I.M., and G.C.M. designed the research; V.I.M., M.M.M., A.C.S.L., V.K.C.G., and R.L.A.N. performed the research; V.I.M., B.M.S., and A.C.G.A. analyzed the data; M.V.G.L., and G.C.M. contributed new reagents/analytical tools. PRINCIPAL INVESTIGATOR (PI) STATEMENT The authors confirm that the PI for this paper is Dr. Victor I. Mwangi and he had, together with Dr. Gisele C. Melo, the direct responsibility for the data generated and analyzed, while Dr. Marcus V.G. Lacerda had the direct clinical responsibility for the participants involved. REFERENCES 1. WHO COVID-19 cases | WHO COVID-19 dashboard. (2026).at 2. Mehta, J. et al. Role of Dexamethasone and Methylprednisolone Corticosteroids in Coronavirus Disease 2019 Hospitalized Patients: A Review. Front. Microbiol. 13 , 813358 (2022). 3. RECOVERY Collaborative Group Dexamethasone in Hospitalized Patients with Covid-19. 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Pharmacokinetic interactions between tacrolimus and Wuzhi capsule in liver transplant recipients: Genetic polymorphisms affect the drug interaction. Chem. Biol. Interact. 391 , (2024). TABLES Table 1. Socio-epidemiological characteristics of the treated participants Age in years; mean (SD) 57.6 (15.4) Males (%) 68/100 (68.0%) Ethnicity White 9/100 (9.0%) Mixed 79/100 (79.0%) Black 6/100 (6.0%) Native American 6/100 (6.0%) Weight in kg; median (IQR) 74.2 (65.0 - 86.5) BMI in kg/m 2 ; median (IQR) 28.1 (25.2 - 31.1) Days to admission; mean (SD) 13.1 (9.4) Days to outcome; mean (SD) 9.8 (10.6) Treatments Placebo 51/100 (51%) MP 49/100 (49%) Post-treatment outcome by day 14 Discharged 78/100 (78.0%) Deceased 22/100 (22.0%) Comorbidities No 9/100 (9.0%) Yes 91/100 (91.0%) Chronic heart disease 9/91 (9.9%) Hypertension 55/91 (60.4%) Chronic Pulmonary disease 4/91 (4.4%) Previous Tuberculosis: 3/91 (3.3%) Diabetes 27/91 (29.7%) Obesity 34/91 (37.4%) Smoking habits 4/91 (4.4%) Alcohol use 19/91 (20.9%) Liver Diseases 10/91 (11.0%) Chronic hematologic disease 2/91 (2.2%) Chronic neurological disease 2/91 (2.2%) Rheumatic disorder 13/91 (14.3%) Pre-treatment medication use: 100/100 (100.0%) Ibuprofen (NSAIDs) 4/100 (4.0%) Antibiotics 75/100 (75.0%) Azithromycin 56/72 (77.8%) Bronchodilators 10/100 (10.0%) Angiotensin-converting enzyme (ACE) inhibitors 47/100 (47.0%) Calcium blockers 3/100 (3.0%) Statins 5/100 (5.0%) Legend: SD - standard deviation; IQR - interquartile range; BMI - body mass index; Kg - kilogramme; NSAIDs - non steroid anti-inflammatory drugs. Table 2. Allele frequency in the treatment groups. Gene Allele Allele count Frequency Allele count Frequency Allele count Frequency HWE S p-value CYP3A4 *1.001 28/200 0.14 12 0.122 16 0.157 0.205 0.48 *1.002 172/200 0.86 86 0.878 86 0.843 0.205 0.48 CYP3A5 *1 56/200 0.28 28 0.286 28 0.275 0.620 0.86 *3 140/200 0.70 68 0.694 72 0.706 0.156 0.85 *6 4/200 0.02 2 0.02 2 0.02 1.000 0.97 CYP3A4 Diplotypes ( *1.001/…) *1.001 28/100 0.28 12/49 0.245 16/51 0.314 0.205 0.44 *1.002 72/100 0.72 37/49 0.755 35/51 0.686 CYP3A5 Diplotypes *1/*1 9/100 0.09 4/49 0.082 5/51 0.098 0.169 0.74 *1/*3 35/100 0.35 19/49 0.388 16/51 0.314 *1/*6 3/100 0.03 1/49 0.020 2/51 0.039 *3/*3 52/100 0.52 24/49 0.490 28/51 0.549 *3/*6 1/100 0.01 1/49 0.020 0/51 0.00 Legend : MP -methylprednisolone; 1 P- values were determined by the X 2 test; # These numbers (n) in the alleles, and not diplotypes, refer to the number of chromosomes; HWE S - the Hardy-Weinberg p-value (Exact test with Selome). Table 3. Allele frequency categorized by patient health outcomes. Gene Allele Allele count Frequency Allele count Frequency CYP3A4 *1.001 23 0.147 5 0.114 0.57 *1.002 133 0.853 39 0.886 0.57 CYP3A5 *1 41 0.263 15 0.341 0.31 *3 111 0.712 29 0.659 0.50 *6 4 0.026 0 0.000 0.28 CYP3A4 Diplotypes ( *1.001/…) *1.001 23/78 0.295 5/22 0.227 0.53 *1.002 55/78 0.705 17/22 0.773 CYP3A5 Diplotypes *1/*1 6/78 0.077 3/22 0.136 0.68 *1/*3 26/78 0.333 9/22 0.409 *1/*6 3/78 0.038 0/22 0.000 *3/*3 42/78 0.538 10/22 0.455 *3/*6 1/78 0.013 0/22 0.000 1 P- values were determined by the X 2 test; # These numbers (n) in the gene alleles, and not diplotypes, refer to the number of chromosomes. Table 4. Relative risks on the outcomes associated by mutations in CYP genotype CYP3A4 Wild type allele ( *1.001 ) 23 5 1.08 (0.867, 1.334) 0.5328 Variant allele ( *1.002 ) 55 17 0.93 (0.750, 1.153) 0.5328 CYP3A5 Wild type allele ( *1 ) 6 3 0.84 (0.525, 1.353) 0.3121 Variant allele ( *3 or *6 ) 72 19 1.18 (0.739, 1.906) 0.3121 Diplotypes (CYP3A4 and CYP3A5) ‡ Only wild type in both 2 2 0.34 (0.515, 2.238) 0.2434 Only variants in both 51 16 ‡ Participant having both wild type CYP3A4 and CYP3A5 genotypes ( *1.001/*1.001 with *1/*1 , respectively) or just variants of CYP3A4 and CYP3A5 genotypes (with *1.001/*1.002 with *1/*3 , *3/*3 , *1/*6 or *3/*6 ). Table 5. Cox proportional hazards regression results for CYP3A4 and CYP3A5 genotypes adjusted for demographic and clinical covariates Hazard Ratio (95% CI) VARIABLES CYP3A4 model p-value CYP3A5 model p-value CYP3A4/5 variant # 0.91 (0.31 - 2.68) 0.864 0.54 (0.16 - 1.85) 0.328 Age 0.99 (0.97 - 1.02) 0.689 0.99 (0.97 - 1.02) 0.631 Sex 0.21 (0.05 - 0.93) 0.040 0.25 (0.06 - 1.04) 0.057 Weight 0.90 (0.82 - 0.98) 0.018 0.90 (0.83 - 0.99) 0.025 Treatment (MP) 0.78 (0.33 - 1.86) 0.581 0.78 (0.33 - 1.84) 0.568 Comorbidities present 0.12 (0.03 - 0.43) 0.001 0.14 (0.04 - 0.53) 0.004 BMI 1.16 (0.91 - 1.49) 0.221 1.16 (0.92 - 1.46) 0.221 Days till hospitalization 1.00 (0.94 - 1.07) 0.986 1.01(0.95 - 1.06) 0.834 Legend: # CYP3A4 ( *1.002 ), CYP3A5 (*3, *6 ). FIGURE LEGENDS Figure 1. Kaplan-Meier survival curves for clinical outcomes by CYP3A4 and CYP3A5 gene variants. A and B) Time to hospital discharge and death in CYP3A4, respectively. C and D) Time to hospital discharge and death in CYP3A5, respectively. Numbers at risk are shown below each plot Information & Authors Information Version history V1 Version 1 09 April 2026 Copyright This work is licensed under a Non Exclusive No Reuse License. Authors Affiliations Victor I. Mwangi 0000-0002-2618-3816 Universidade do Estado do Amazonas View all articles by this author Marielle M. Macêdo Universidade do Estado do Amazonas View all articles by this author Ana C. Shuan Laco Universidade do Estado do Amazonas View all articles by this author Vanessa K. C. Godinho Universidade do Estado do Amazonas View all articles by this author Rebeca L.A. Netto Universidade do Estado do Amazonas View all articles by this author Bernado M. Silva 0000-0002-5989-1288 Universidade do Estado do Amazonas View all articles by this author Fernanda Rodrigues-Soares Universidade Federal do Triangulo Mineiro View all articles by this author Fernando Almeida-Val Universidade do Estado do Amazonas View all articles by this author Marcus Lacerda Universidade do Estado do Amazonas View all articles by this author Anne C. G. Almeida Universidade do Estado do Amazonas View all articles by this author Gisely Melo [email protected] Universidade do Estado do Amazonas View all articles by this author Metrics & Citations Metrics Article Usage 240 views 79 downloads .FvxKWukQNSOunydq8rnd { width: 100px; } Citations Download citation Victor I. Mwangi, Marielle M. Macêdo, Ana C. Shuan Laco, et al. Influence of CYP3A4 and CYP3A5 Genetic Variants on Clinical Outcomes in Methylprednisolone-Treated, Hospitalized COVID-19 Patients in Manaus, Brazil. Authorea . 09 April 2026. 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