Pharmacogenomic Insights: The Role of CYP2D6 Allelic Variants in Drug Metabolism Among COVID-19 Patients With Comorbidities

Abstract

Background/Aim

Drug metabolism and thus drug efficacy can be affected by individual differences in cytochrome P450 2D6 enzyme (CYP2D6) due to genetic polymorphism in its gene. In this study, we aimed to investigate CYP2D6 allelic variants in drug metabolism among patients with COVID-19 with comorbidities.

Patients and Methods

This prospective case-control study, approved by the Pamukkale University Ethics Committee, investigated CYP2D6 polymorphisms (*4, *5, *7, *10) and COVID-19 outcomes in the Emergency Department between April and June 2020. Genomic DNA was extracted from whole blood, and genotyping was performed by polymerase chain reaction followed by sequencing on the ABI PRISM 7700 platform. Statistical analyses, including Student's t-test, Mann-Whitney U-test, chi-square test, and Fisher's exact test, were performed for laboratory and clinical data comparing between wild-type and heterozygous variants, and significance was determined as p<0.05. Data visualization was performed using SankeyMATIC, STATA 16.1 SE, and GraphPad Prism 5.0.

Results

Among the 99 patients, 71 were identified as having one or more comorbid conditions. Comorbidity analysis showed that the absence of comorbidities was most common in CYP2D6*4 (38.46%), *5 (40%), and *7 (29.63%) heterozygotes, while hypertension and diabetes were also common. CYP2D6*10 heterozygotes (n=3) presented with cardiovascular diseases, osteomalacia, and arrhythmia. In particular, CYP2D6*5 heterozygotes had significantly lower lymphocyte counts. A trend toward differences was observed for hemoglobin in CYP2D6*4 and platelet count for CYP2D6*5 and CYP2D6*10, but these were not statistically significant.

Conclusion

This study highlights the diverse clinical profiles of COVID-19 patients with different CYP2D*6 variants, particularly the association between CYP2D6*5 heterozygosity and a reduced lymphocyte count.

Introduction

Focusing on COVID-19 patients with comorbidities in this study was essential, not only for clinical reasons but also due to pharmacogenetics. Patients with multiple diseases are often taking various medications, which raises the likelihood of drug-drug interactions and the occurrence of different therapeutic outcomes, especially if genetic polymorphisms, like those of the gene encoding cytochrome P450 2D6 enzyme (CYP2D6), influence drug metabolism (1,2). Understanding the mechanism of action of enzymes resulting from genetic variants such as CYP2D6 *4, *5, *7 and *10 allows evaluation of their effects on the pharmacokinetics of commonly used drugs, including antivirals, corticosteroids, and antidepressants (3,4). It has been observed that hypertension, diabetes, and cardiovascular disease, among other comorbid conditions, are the main reasons for severe symptoms of COVID-19 that lead to a higher number of hospitalizations and deaths (5). Hence, accurate and personalized pharmacotherapy is very important in this scenario. The use of pharmacogenomic testing should be part of the decision-making process in treating these patients as this would allow for a personalized drug selection and dosage pattern that would lead to the least side-effects and the highest therapeutic effect (6,7). Since polymorphisms such as CYP2D6 *4 and *10 are common in different populations and have been found to be associated with poor drug response or increased toxicity, their determination becomes important in patients with comorbidities in the context of precision medicine (8,9).

CYP2D6 is a well-known drug-metabolizing enzyme in humans, and is a central member of the P450 cytochrome superfamily, which is a large family involved in the synthesis and metabolism of many drugs. Approximately 25% of drugs are subjected to this kind of metabolism, including antipsychotics, antidepressants, and drugs like those that are used to manage pain or heart diseases (4,10). These drug-metabolizing enzymes are generally regulated through their genetic variants, the activity of which varies between individuals. Among such variations, the alleles CYP2D6 *4, *5, *7, and *10 are those that ultimately lead to a difference in the patient's ability to metabolize medicines, so they are classified either as poor, intermediate, extensive, or ultra-rapid metabolizers (3). The *4 and *5 alleles of CYP2D6 are the most important because they are non-functional variants that are among the most common ones found in several populations (4,11). These polymorphisms may drastically hinder the drug metabolism of those drugs that are CYP2D6-substrate, thus drugs in plasma could either be elevated to concentrations which could give rise to adverse effects, or it could be that dose escalation is needed to achieve efficacy (1). In fact, the CYP2D6*10 allele, which is mostly spread in East Asian populations, is connected with lowered enzymatic activity as well as intermediate metabolizer status (12,13). Similarly, the CYP2D6*7 allele that is a splice variant leading to decreased enzyme function, has been found more and more over the years in old people and in aged persons with different pathological conditions, i.e., a demographic that is highly represented in the COVID-19 patient population (2). Comorbidities related to genetic mutations have a notable impact during the COVID-19 pandemic, since such patients usually undergo a complicated pharmacotherapy treatment, thus the possibility of drug interactions and variable therapeutic outcomes rises considerably (1,5,6).

Comprehensive consideration of pharmacogenomics is essential; clinicians should assess relevant polymorphisms when prescribing treatments to maximize therapeutic efficacy and minimize adverse reactions. The existence of these alleles may modify the pharmacokinetics of antiviral drugs and the pharmacodynamics of the adjuvants used in COVID-19 management, and treatment protocols might be altered by the presence of genetic variations. CYP2D6 polymorphisms may greatly affect the combined pharmacological activity of steroids, specifically dexa-methasone; the treatment of COVID-19, such as with antivirals like remdesivir; and the therapy of the patient with different supportive measures (3,14,15). Moreover, as the incidence of comorbidities increases alongside the severity of COVID-19, understanding the mechanisms by which CYP2D6 alleles influence drug-drug interactions is becoming increasingly critical. The more personalized the medicine, the greater the chance of avoiding side-effects, and the more likely it is that the drug will work. Moreover, pharmacogenetic tests incorporated in clinical setups would also help to adapt the treatment to the specific patient and cater to their needs. The interaction between pharmacogenomics and clinical pathways is emerging as a pressing issue, requiring the delivery of protocols and guidelines leading to appropriately adapted treatments for COVID-19 (2,16).

Alleles such as CYP2D6*4, which produce a non-functional enzyme due to a point mutation, and CYP2D6*5, which involves a gene deletion that entirely eliminates CYP2D6 enzymatic activity, show considerable frequency variation across different populations (17). These inter-population differences may influence the pharmacological management of COVID-19 and may potentially help prevent the onset or exacerbation of comorbidities, such as hypertension, diabetes, and depression. Some studies have suggested that a significant proportion of patients with chronic diseases may also carry these alleles, which adds additional implications for the successful treatment of the disease (17). In this study, we aimed to investigate the distribution of CYP2D6 allelic variants and their impact on drug metabolism among patients with COVID-19 with comorbidities.

Patients and Methods

Study type. The present study was a prospective case-control study, and the required approval was obtained from the Ethics Committee of Pamukkale University prior to the study (no. 60116787-020/26598).

Study population. The present study included patients who were admitted between April 2020 and June 2020 to the COVID-19 pandemic outpatient clinic of the Emergency Department. Eligible patients either presented with symptoms of upper respiratory tract infection and pneumonia, were asymptomatic but tested positive for COVID-19 via polymerase chain reaction (PCR) during contact tracing, or were referred to the Emergency Department for further examination and treatment. After being provided with detailed information about the study, written informed consent was obtained from all participants. Patients without any comorbidity data were excluded from the analyses.

Genotyping. Extraction of genomic DNA from whole blood was performed using a commercial kit (High Pure PCR Template Preparation Kit, Roche Diagnostics, Mannheim, Germany^®). DNA samples were quantified and stored at −20˚C until further analysis. Genomic DNA was amplified by PCR using primers for the specific variants studied. The genotype analyses for the CYP2D6 *4, *5, *7, and *10 alleles were performed with PCR by sequencing on an ABI PRISM 7700 Sequence System (Applied Biosystems, Foster City, CA, USA). The primers used for PCR and DNA sequencing are presented in Table I (18).

Table I. Primer sequences for alleles of cytochrome P450 2D6 (CYP2D6) gene studied.

F: Forward; R: reverse.

Statistical analysis. Descriptive values of quantitative continuous variables (such as age) were examined with standard descriptive statistical methods (mean, standard deviation, min-max level). Categorical variables were examined using their frequencies and percentages in the population. Evaluation of quantitative measurements was made using Student’s t-test or Mann-Whitney U-test according to the distribution properties of the data. Comparisons of categorical variables were made with chi-square or Fischer’s exact test according to the status of the case distributions. Statistical significance was accepted as p<0.05. Diagrams were created using SankeyMATIC (available at: https://sankeymatic.com). Statistical analyses and visualization of data were performed in STATA 16.1 SE (StataCorp LLC, College Station, TX, USA) and visualized with GraphPad Prism 5.0 (GraphPad Software Inc., San Diego, CA, USA) software.

Results

Descriptive information. Characteristics of 99 COVID-19 PCR-positive patients, describing their age, fever, oxygen saturation (SpO₂), systolic and diastolic blood pressure, and Pneumonia Patient Outcomes Research Team (PORT) score (19) were determined. The average age of the patients was 50.12 years (± standard deviation of 20.11 years), ranging from 18 to 88 years. Additionally, the mean body temperature was 36.91±0.66˚C, with temperatures varying between 36˚C and 39.7˚C. The average SpO₂ was 94.79±4.80%, with a range from 70% to 100%. Systolic blood pressure averaged 124.59±23.29 mmHg, ranging from 60 to 200 mmHg, while diastolic blood pressure averaged 75.65±12.92 mmHg, with a range from 30 to 123 mmHg. Lastly, the PORT score, available for 94 patients, was a mean of 68.35±43.74, ranging from 8 to 197.

Among patients heterozygous for the CYP2D6*5 variant, the absence of comorbidities was again the most frequent, representing 40% of this group. However, hypertension was also a prominent comorbidity, affecting 20% of these patients. Other comorbidities, such as diabetes, coronary artery disease (CAD) with hypertension, and nasopharyngeal conditions, were present at lower frequencies.

The CYP2D6*7 heterozygous group exhibited a wide array of comorbidities. Similar to the other variants, the absence of comorbidities was the most common feature, observed in 29.63% of patients. However, a notable proportion of patients presented with hypertension combined with CAD (14.81%), asthma (11.11%), or hypertension alone (11.11%). Finally, the CYP2D6*10 heterozygous group (n=3) had cardiovascular diseases, osteomalacia, and arrhythmia.

Comorbidity information. Table II and Figure 1 present the cohort of patients heterozygous for the CYP2D6 allelic variants; a diverse range of comorbidities was observed. Notably, the most prevalent group was the absence of any comorbidity, accounting for 38.46% of those with CYP2D6*4 variant. However, a significant proportion of patients with CYP2D6*4 presented with hypertension (11.54%) or diabetes (7.69%), indicating a substantial association with these chronic conditions. Additionally, various other comorbidities, including Alzheimer's disease, asthma, CAD with renal failure, epilepsy, and multiple myeloma, were each observed in single cases.

Table II. Comorbidities of the COVID-19-positive patient group included in the study.

CAD: Cardiovascular disease; NA: not available; SCC: Squamous cell carcinoma.

Figure 1.

Sankey diagram of distribution of comorbidities in the COVID-19-positive patient group included in the study according to cytochrome P450 2D6 (CYP2D6) polymorphism. The number of patients with each comorbidity who were heterozygous or wild type for each allele are given.

Laboratory information. Comparisons of patients' laboratory data by CYP26 allelic variants with wild-type and heterozygous status are presented at Table III. There were 73 patients with wild-type CYP2D6 and 26 heterozygotes with the CYP2D6*4 allele variant. The mean white blood cell (WBC) counts were 9.82±5.29 10⁹/l for individuals with wild type and 10.59±6.61 10⁹/l for heterozygotes, with a p-value of 0.976, indicating no significant difference. Hemoglobin levels were a mean of 13.67±2.06 10⁹/l for individuals with wild type and 12.75±2.71 10⁹/l for heterozygotes, with a p-value of 0.078. Similarly, neutrophil, lymphocyte, platelet and monocyte, CRP, urea, creatinine, D-dimer, and ferritin levels did not display statistically significant differences between the two groups.

Table III. Comparison of patients' laboratory data and cytochrome P450 2D6 (CYP2D6) allelic variants (wild type and heterozygote status).

CRP: C-Reactive protein; WBC: white blood cells. ^aMann–Whitney U-test, ^bchi-squared test.

In the CYP2D6*5 variant analysis, the mean WBC counts were 10.11±5.49 10⁹/l for individuals with wild type (n=83) and 9.68±6.77 10⁹/l for the heterozygotes (n=15), with a p-value of 0.563, presenting no significant difference. However, lymphocyte counts showed a statistically significant difference (p=0.026), with the heterozygous group having a mean of 1.44±0.92 10⁹/l compared to 2.02±0.94 10⁹/l for the wild type. Other parameters did not show significant differences.

In the CYP2D6*7 variant analysis, the mean WBC counts were 10.27±5.53 10⁹/L for the wild type (n=72) and 9.37±5.98 10⁹/l for the heterozygotes (n=27), with a p-value of 0.160, indicating no significant difference. Other parameters did not show statistically significant differences.

Lastly, in the CYP2D6*10 variant analysis, the mean WBC counts were 10.06±5.66 10⁹/l for the wild type (n=96) and 8.90±5.79 10⁹/l for the heterozygotes (n=3), with a p-value of 0.662, indicating no significant difference. Other parameters did not show significant differences. However, due to the small sample size (n=3) of the heterozygote group, the statistical power is limited.

Discussion

The CYP2D6*4 and CYP2D6*5 alleles significantly affect the metabolism of medications such as antidepressants, beta-blockers, and some antiviral drugs, including those used in COVID-19 therapy. For instance, venlafaxine, is an anti-anxiety and antidepressant medication that is detoxified by CYP2D6. But in patients with CYP2D6 variants that lead to poor activity of the enzyme, the drug may reach a level that implies more side-effects or toxicity (20,21). Moreover, therapies with drugs such as hydroxychloroquine and dexamethasone, which both have a highly variable pharmacodynamic profile in the presence of comorbidities, may trigger negative developments in patients that are poor metabolizers due to CYP2D6 polymorphism.

This alteration of the therapeutic effectiveness of drugs by CYP2D6*4 and CYP2D6*5 gene polymorphisms is an aspect of treatment that should be considered, given the use of numerous medications for COVID-19 therapy. There is much variability between individuals, where those who are fast metabolizers (ultra-rapid metabolizers) can break down drugs very fast, thus rendering them useless, while poor metabolizers may face greater exposure to drugs and thus suffer from side-effects (1,2). This large degree of variability makes it necessary to take a closer look at prescribing, especially for patients who simultaneously suffer from other health complications that would add to the struggle of adhering to the recommended dosage.

Using multiple medications in the case of patients with COVID-19 with comorbidities significantly complicates the clinical implications of CYP2D6 allelic polymorphisms (6). It is recommended that health service providers determine the best options for treatment strategies, and the task of education on the advantages of genotype-based dosing should start with them. Changes in therapeutic measures can include the closer scrutiny of plasma drug levels, the selection of alternative medications that do not depend on metabolism via CYP2D6, or the initiation of discussions on genetic testing prior to the commencement of treatment.

Ultimately, the influence of variations in the CYP2D6 gene, especially *5, on drug metabolism highlights the necessity for individualized medical interventions in treating patients with COVID-19. The scientific evidence is quite robust: the CYP2D6*5 allele, which is a complete gene deletion, leads to the production of a non-functional enzyme, thereby defining the carriers as poor metabolizers. This condition considerably hampers the clearance of a wide range of drugs, including those used for the treatment of COVID-19, i.e., antivirals, corticosteroids, and psychotropic agents. Consequently, patients with the *5 allele are more likely to suffer from drug overdosing, adverse drug reactions, and even therapeutic failure, which further highlights the importance of genotype-guided, personalized treatment strategies (1,3,22).

Understanding the genetic background can provide a solution to the effects of COVID-19 in coexistence with other diseases. The considerable polymorphic characteristics of the CYP2D6 gene include the *7 and *10 alleles, which mostly dictate pharmacokinetics in certain populations. The presence of these alleles among individuals suffering from coexisting diseases such as CAD and arrhythmia can be important for the metabolism of drugs and overall therapy outcome. The CYP2D6*7 allele is a splicing variant that significantly reduces enzymatic activity. As a result, the metabolism of drugs is negatively affected, especially those with low bioavailability, or they are rapidly eliminated, for instance, cardiovascular agents like beta-blockers. Patients with CAD or arrhythmias, who are usually on polypharmacy, are at the greatest risk of side-effects when enzyme activity of CYP2D6 is lowered because of genetic polymorphisms. Consequently, interactions between drugs and an insufficient treatment response lead to a higher frequency of adverse events (5,23).

Conversely, the CYP2D6*10 allele displays variable activity, which causes some carriers to be classified as intermediate metabolizers. Research suggests that this allele is most commonly found in Asian populations (12), which indicates that there are significant ethnic differences in the frequency of this allele among patients. This intermediate activity may contribute to changes in the response to prescribed drugs such as anticoagulants and antiviral therapies for comorbid conditions in patients with COVID-19. For instance, the effectiveness of the analgesic codeine, which is commonly administered for pain control, in patients with a *10 allele can be compromised, thus leading to treatment failure and the need for dose adjustments (4,6).

The existence of these alleles in the context of COVID-19 complicates treatment selection. Different studies have related severe COVID-19 instances to the presence of CAD and arrhythmias, as well as reports of overwhelmed immune systems and inflammation issues. The management of COVID-19 with standard therapies such as corticosteroids or antivirals, which are substrates for CYP2D6, necessitates a detailed understanding of allelic distributions to ensure the effectiveness of these therapies. Clinicians should, therefore, pay heightened attention to a detailed assessment of pharmacogenomic profiles prior to commencing treatment since patients homozygous for *7 or heterozygous for *10 ones may respond in an unpredictable manner to commonly used drugs (5,14).

Fundamentally, a personalized medicine approach is essential for managing the complicated relationship between CYP2D6 gene variations and drug metabolism in patients with COVID-19 with heart comorbidities. The implementation of pharmacogenetic tests might enable the identification of individuals who would benefit from modified doses or alternative therapies that do not involve CYP2D6 metabolism. This personalized approach is crucial not only from a safety point of view but also to maximize the efficacy of treatment and improve the results of patients who are already at a higher risk of serious complications from both COVID-19 and their co-existing diseases. Specific polymorphisms such as CYP2D6 *4, *5, *7, and *10 can mark the difference between a responsive and a non-responsive patient to the drug therapy, which is very crucial for COVID-19 patients with comorbid conditions. The clinical implications of these variants are significant, particularly when considering possible drug-drug interactions, which not only can worsen the patient's health but can also complicate treatment (22).

The CYP2D6* 4 allele is responsible for the low expression of this enzyme. As a result, CYP2D6 substrates can build up with time. This is especially worrisome for patients taking antidepressants or opioids, which may cause an increased incidence of adverse effects such as respiratory depression due to elevated plasma levels, especially in the case of COVID-19 treatment (1). This is where it becomes critical that several drugs prescribed to patients should be CYP2D6 metabolized in order to prevent better or worse therapeutic outcomes than targeting non-CYP2D6 pathways (24,25). In contrast, patients with alleles causing very rapid metabolization, like CYP2D6*10, might face problems because some medications will be ineffective without their initial metabolic activation through CYP2D6, or can be cleared too quickly, leading to the therapeutic effect being diminished, so higher doses or drugs which are less CYP2D6 metabolism-sensitive would be needed (10,26). Drugs such as remdesivir and dexamethasone, used for COVID-19, may require a fine-tuning of dosage according to genomic variation so that they work effectively (15,24). Thus, these problems must be considered when deciding on treatment drugs for people with the relevant polymorphisms, thus demonstrating the need for an approach that utilizes precision medicine in disease treatment pathways.

Alongside, the coexistence of disorders such as hypertension, diabetes, and respiratory diseases in COVID-19 individuals leads to the dependence on multiple medications. The diversity of drug-drug interactions is deepened further by considering pharmacogenetics tied to CYP2D6. For instance, when treating with beta-blockers or selective serotonin reuptake inhibitors (the pro-drugs of which are mainly metabolized by CYP2D6), there is a likelihood of pharmacokinetics and pharmacodynamics being altered in patients already susceptible due to prior health issues (6,27). The clinician must focus on pharmacogenetics testing to check drug selection reduces the influence of the drug on the clinical picture of the patients; in particular, they need to adjust dosages.

It is very important to determine the CYP2D6 polymorphism frequencies in patients with COVID-19 to improve therapeutic effects and reduce adverse therapy and drug reactions. By utilizing pharmacogenetic tests in their clinical decision-making, health professionals can provide more personalized and efficacious treatments, especially among patients with multi-morbidities. Ongoing studies must bring out the details of these genetic variants to optimize clinical protocols and improve patient outcomes in terms of COVID-19 and its various comorbidities. Commercially, pharmacogenomic tests shine a light on the unique nature of medical treatment individualization that is necessary in the context of complex and multifaceted diseases such as COVID-19, especially in patients with comorbidities.

To avoid adverse events in patients with COVID-19, practitioners need to be aware of the influence of CYP2D6 allelic distribution on therapy decisions. To that end, health systems need to make policies that facilitate the usage of pharmacogenetic tests in regular practices (3,5). They must create an atmosphere where precision medicine is not a fancy clinical wish but rather a fundamental aspect of patient management. When a thorough integration of precision medicine is finally realized, it is likely that clinical results will improve. The reduced occurrence of drug-related reactions along with the improved management of patients who have to cope with COVID-19, as well as comorbid conditions, are now aiding modern medicine. The use of pharmacogenomic tests for the design of therapeutic schemes and the correlation of test results with various conditions allows discrimination in selecting a secure treatment for the population that is most prone to adverse drug responses. The distribution profiles of CYP2D6*4, *5, *7, and *10 in the context of patients infected with COVID-19, especially those with comorbidities, necessitates a unified understanding of individual genetic diversity and its clinical consequences. Several case studies provide many examples of how these genetic variations influence the metabolism of medications and treatment outcomes. The results were not generalized but are highly relevant for some groups of patients (1,26,28).

A key study by Nguyen et al. involved a cohort of 150 patients with COVID-19, of whom 40% had comorbidities such as hypertension, diabetes, and chronic respiratory conditions (7). Notably, 25% of those tested were found to have the CYP2D6*4 allele, and it was concluded there was a major connection between this pharmacogenomic marker and altered drug metabolism of patients, particularly with regard to opioid and antidepressant therapies (28). In particular, in patients with comorbidities who were positive for the CYP2D6*4 allele presented very limited activation of the drug, which necessitated adjustments for those drugs with a Vmax of CYP2D6 and a potency that would have required a level of conversion to the active form that was obviously higher, the net effect being a two-fold greater plasma concentration of the drug and a high frequency of adverse drug reactions. In parallel, Dieter et al. researched the distribution of CYP2D6*10 among a varied group of patients, showing a worrying frequency of 30% in patients with cardiovascular diseases (8,13,28). The research confirmed a robust correlation between CYP2D6*10 and the reduced breakdown of beta blockers and antidepressants, which are commonly prescribed to regulate symptoms and treatment of patients suffering from COVID-19. The risk to those who are carriers of this allele was insufficient therapeutic concentrations, which resulted in the inadequate control of the severity of symptoms and complications of COVID-19 (29).

More statistics can be obtained when examining combined allelic frequencies within the cohorts stratified by multiple comorbid conditions. It was found that the presence of the CYP2D6*5 allele, leading to gene deletion, was prevalent in 15% of critical patients. This genetic factor is the basic one that must be considered if the pharmacokinetics of antiretroviral therapies utilized for COVID-19 management in patients with comorbidities are to be studied. The likelihood of these patients facing ineffective therapy due to the lack of enzyme activity shows that a personalized medicine approach is of paramount significance (30). The point of convergence between pharmacogenetics and the event of COVID-19 on the other hand is the most urgent necessity of including the expeditious resolution of the gene detection in the standard of care for the people who were affected by the virus. The integration of this process not only promotes a proactive therapeutic adjustment, but it also provides patients with the way to avoid the unintentional aggravation of the comorbid conditions. The existing literature strongly indicates that comprehension and the modulation of the CYP2D6 polymorphisms are the key ingredients for optimal therapeutic pharmacology for the individuals who have COVID-19 and the diverse pathology in their health problems (31).

The distribution models of alleles in various racial and ethnic groups necessitate a structured approach when prescribing drugs, particularly those that are metabolized by CYP2D6. The impact that these pharmacogenetic issues have in the clinic is remarkable. The selection and the dosage of the drug vary not only according to the pathology but also considering the possibility of its side-effects before making the decision to fine-tune the therapy. As comorbidity creates a complex therapeutic environment for patients suffering from COVID-19, paying regard to genetic variability has the potential to preclude threatening drug-drug interactions and boost general management strategies (30,32).

Concerning directions for future research, it is crucial to conduct a large number of studies to provide evidence for the associations between CYP2D6 polymorphisms and drug metabolism in various cohorts. These studies should focus on the elucidation of the interplay between genetic factors and comorbid states, together with the pharmacokinetics of drugs used during COVID-19 therapy. Moreover, longitudinal studies will be invaluable in understanding the contribution of genetic variations to long-term outcomes and recovery of patients with COVID-19 (5).

The creation of a scientific database comprising the frequencies of CYP2D6 alleles and the related clinical results will permit the integration of pharmacogenomic data into clinical practice to the full extent by the clinicians. Improvement of genomic-based medicine will lead to point-of-care tests, which will permit the fast assessment of the CYP2D6 genotype of a patient before starting drug therapy. This will help clinicians in the customization of therapeutic plans, thus giving patients the chance to decide wisely in choosing therapies (32).

One of the limitations of this study is the incomplete availability of comorbidity data for all participants. Although a total of 99 COVID-19-positive patients were initially included, only 71 had complete and usable comorbidity information and were thus eligible for downstream genotype-comorbidity association analyses. The exclusion of 28 patients due to missing clinical data may have introduced selection bias and limited the generalizability of the findings. Nevertheless, the study provides a valuable and timely contribution by being among the first to explore the pharmacogenomic landscape of CYP2D6 variants in the context of COVID-19. The integration of genetic and clinical data, even with partial information, represents a meaningful step towards more personalized approaches to infectious disease management. Future studies with more comprehensive and systematically recorded clinical information are warranted to validate and expand upon these promising findings.

Additionally, as the landscape of COVID-19 and its management continues to be in flux, the place of pharmacogenomics will become established in public health policy and clinical guidelines. This study not only helps to clarify the distribution of CYP2D6 alleles, but may also enable more proactive health systems to be developed to deal with the complexities of the drug metabolism in patients with multiple health issues. The integration of these research-led activities will deepen the knowledge base and enhance the quality of care and services. Therefore, it is essential to take advantage of the opportunities presented by personalized medicine for optimum treatment outcomes.

Conflicts of Interest

The Authors declare that they have no conflicts of interest.

Authors’ Contributions

Conception: Aylin Köseler. Study design: Aylin Köseler. Funding: Aylin Köseler. Materials: Mert Özen. Data collection and processing: Mert Özen, Alten Oskay, İbrahim Türkçüer, Atakan Yılmaz, Murat Seyit, Yasemin Adalı, Vefa Çakmak and Aylin Köseler. Composition: Yasemin Adalı and Aylin Köseler. Clinical review: Ibrahim Türkçüer, Aylin Köseler.

Artificial Intelligence (AI) Disclosure

No artificial intelligence (AI) tools, including large language models or machine-learning software, were used in the preparation, analysis, or presentation of this manuscript.