Association between CYP2D6 genotype and treatment effectiveness and safety in 99 hospitalized patients with major depressive disorder - a retrospective cohort study

Association between CYP2D6 genotype and treatment effectiveness and safety in 99 hospitalized patients with major depressive disorder - a retrospective cohort study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Association between CYP2D6 genotype and treatment effectiveness and safety in 99 hospitalized patients with major depressive disorder - a retrospective cohort study Marin Jukić, Aleksandra Petković Ćurčin, Aleksandra Jeremić, Danilo Joković, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7234296/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 9 You are reading this latest preprint version Abstract Cytochrome P450 2D6 (CYP2D6) is a polymorphic enzyme that affects antidepressant metabolism. This retrospective hospital-based cohort study investigated the association between CYP2D6 genotype and treatment outcomes in 99 hospitalized patients with major depressive disorder (MDD) in Belgrade, Serbia. Patients were classified as poor (PM, n = 5), intermediate (IM, n = 30), or normal metabolizers (NM, n = 64). Effectiveness and tolerability were assessed from admission to discharge (approximately four weeks). Effectiveness was measured using the reduction in Hamilton Depression Rating Scale (HAM-D) score, while tolerability was measured using the Toronto Side Effects Scale (TSES). Compared with NMs, HAM-D score reductions were 5.1 and 9.5 points lower, while TSES scores were 0.8 and 2.3 points higher in IMs and PMs, respectively, with higher prevalence of CNS and gastrointestinal side effects among IMs and PMs. Reduced CYP2D6 activity was associated with poorer antidepressant treatment outcomes supporting the potential clinical utility of CYP2D6 genotyping for treatment individualization. Health sciences/Diseases/Psychiatric disorders/Depression Health sciences/Risk factors Biological sciences/Genetics/Genotype Figures Figure 1 Figure 2 1. INTRODUCTION Depressive disorders lead to the disability of more than 280 million individuals [ 1 , 2 ], while two thirds of suicide victims are depressed at the time of their death [ 3 ]. Numerous major depressive disorder (MDD) patients experience treatment failure due to lack of effectiveness or intolerable side effects [ 4 , 5 , 6 ]. Since the development of new antidepressant drugs is very slow, there is an urgent need for personalization of treatment with currently available antidepressants, for example, by utilization of pharmacogenomic information in therapeutic decision making protocols [ 7 ]. Despite the evidence that pharmacogenomic-guided approach improves antidepressant treatment outcomes [ 8 , 9 , 10 , 11 , 12 ], the effect sizes are still not sufficiently convincing and they vary among sources due to inconsistencies in cohorts analyzed and study settings. Consequently, further clinical research focused on specific gene-drug interactions and adequate characterization of clinically impactful and actionable pharmacogenetic associations is needed to facilitate the implementation of meaningful pharmacogenetic testing into clinical practice. Cytochrome P450 2D6 (CYP2D6) and 2C19 (CYP2C19) are polymorphic enzymes that metabolizes the majority of commonly prescribed antidepressants [ 13 , 14 ]. Functional genetic variants of CYP2D6 and CYP2C19 are highly prevalent and they cause the significant inter-individual variability in enzymatic capacity. Patients are usually categorized as poor metabolizers (PMs), intermediate metabolizers (IMs), normal (or extensive) metabolizers (NMs) and ultra-rapid metabolizers (UMs) based on CYP2C19 and CYP2D6 genotype [ 15 , 16 ]. The patients with decreased enzymatic activity (i.e., PMs and IMs) are considered to be at high risk for overdose and intolerable adverse drug reactions, while UMs are considered to be at high risk of subtherapeutic drug levels and inadequate treatment response. As both mentioned risks affect antidepressant treatment successfulness [ 17 , 18 ], the knowledge of CYP2C19 and CYP2D6 genotype can potentially be useful for clinicians in helping them with selection of appropriate antidepressant drugs and their dosage. Our previous work showed that CYP2C19 slow metabolizer phenotype is associated with lower antidepressant efficacy and tolerability [ 19 ]. Related to the association between CYP2D6 genotype and the effectiveness and tolerability of antidepressants that has been extensively studied, results remain inconsistent [ 20 ]. Many studies advocate the importance of matching the choice of antidepressant with CYP2D6 metabolizer status, while the CYP2D6 enzymatic capacity, as determined by genetic variation, has been associated with differences in antidepressant effectiveness [ 21 , 22 , 23 ] and tolerability [ 22 , 24 , 25 ]. Next, CYP2D6 PMs were at five times higher risk to switch their antidepressants [ 26 , 27 , 28 ] or discontinue treatment compared to NMs [ 29 , 30 ]. However, there are many other adequately powered studies that failed to observe significant association between CYP2D6 phenotype and antidepressant treatment effectiveness [ 31 , 32 , 33 ] or tolerability [ 32 , 33 , 34 ]. Currently, guidelines published by various expert groups, such as the Clinical Pharmacogenetics Implementation Consortium (CPIC), the Dutch Pharmacogenetics Working Group (DPWG), and the US Food and Drug Administration (FDA) provide the instructions to clinicians on how to use CYP2D6 genotype to personalize antidepressant treatment. However, discrepancies between these recommendations are still apparent, underlining the lack of certainty about how CYP2D6 genotype needs to be used to maximize antidepressant treatment successfulness [ 17 , 35 , 36 , 37 ]. This naturalistic retrospective cohort study aimed to investigate the association of CYP2D6 genotype with antidepressant treatment effectiveness and safety in patients hospitalized due to major depressive disorder. 2. MATERIAL AND METHODS This naturalistic hospital-based retrospective cohort study was conducted between May 2016 and January 2018 at the Department of Psychiatry of the Military Medical Academy in Belgrade, Serbia. This naturalistic retrospective cohort study complied with the principles of the Declaration of Helsinki (1997). The protocol was approved by the Ethics Committee of the Military Medical Academy in Belgrade on March 29, 2016, and all participants signed written informed consent before being subjected to the study protocol and included in the data analysis. 2.1. Study participants and exposures Patients were eligible for inclusion if they had been (1) diagnosed with MDD, (2) receiving stable treatment with one or two antidepressants, and (3) hospitalized in a tertiary care facility due to the severity of their depression symptoms. MINI 5.0.0. interview (Mini International Neuropsychiatric Interview) [ 38 ] was used as a screening tool; exclusion criteria included (1) age under 18 or over 65 years, (2) a Mini Mental State Examination (MMSE) score below 24 at enrollment, (3) less than eight years of formal education, and (4) a diagnosis of mental retardation according to ICD-10 criteria. There were no restrictions on the choice of antidepressants or dosage. To enable dose comparisons, antidepressant doses were converted to fluoxetine equivalents [ 39 ]. Patients were clinically assessed at three predefined time points: (1) At the beginning of the study (visit 0, V0) after hospital admission, (2) during interim assessment (visit 1, V1), two weeks after hospitalization, and (3) during final assessment (Visit 2, V2) on discharge from hospital (4–6 weeks after admission). CYP2D6 genotyping and categorization in to CYP2D6 metabolizer groups for subsequent analysis was performed retrospectively after completion of the study and consequently, the investigators who rated the psychometric scales were blinded for CYP2D6 genotype. The study cohort had previously been genotyped for CYP2C19 as part of the previous study [ 19 ]. 2.2. CYP2D6 genotyping Peripheral blood samples were collected in EDTA tubes and stored at − 20°C until DNA isolation. DNA was isolated from the collected blood samples using the PureLink Genomic DNA Mini Kit (Invitrogen, USA). The integrity of the isolated DNA samples was assessed by 1% agarose gel electrophoresis, and the concentration and purity were determined using the Gene Quant spectrophotometer (Pharmacia LKB, Stockholm, Sweden). CYP2D6 genotyping was performed with the commercially available TaqMan SNP Genotyping Assays (Applied Biosystems) on a 7500 Real-Time PCR System (Applied Biosystems, Foster City, CA, USA) using the allele discrimination method to genotype the polymorphisms. Patients were genotyped for common (1% or higher incidence) non-functional alleles ( CYP2D6Nonf ), including CYP2D6*3 (rs35742686), CYP2D6*4 (rs3892097), CYP2D6*6 (rs5030655) and for common alleles associated with decreased enzymatic capacity ( CYP2D6Decr ), including CYP2D6*9 (rs5030656), CYP2D6*10 (rs1065852) and CYP2D6*41 (rs28371725) alleles. Rare alleles in this population, such as CYP2D6*17 (< 0.5%) [ 40 ], were not included in the analysis. Gene copy number variation was assessed to detect deletions or multiplications of entire genes according to the manufacturer’s protocol (Assay ID: Hs00010001_cn; Thermo Fisher Scientific, Waltham, MA). If no variant alleles were detected, the allele was considered to be associated with normal metabolic activity ( CYP2D6Norm ). Patients were categorized based on their genotype-predicted enzymatic activity; homozygous carriers of the CYP2D6Norm allele were classified as normal metabolizers (NM) and served as the reference group and homozygous carriers of CYP2D6Nonf alleles ( CYP2D6*3 , CYP2D6*4 , CYP2D6*6 ) were classified as poor metabolizers (PM). Patients who carried less than two CYP2D6Norm alleles, but who were not PMs, were classified as intermediate metabolizers (IM). The presence of multiple CYP2D6Norm gene copies would result in classification of ultra-rapid metabolizers (UM); however, no such patients were found in this cohort. Three heterozygous individuals carried three copies of the CYP2D6 gene, but due to uncertainty as to which allele was duplicated, we could not unequivocally confirm their metabolizer status and they were therefore excluded from the analysis. 2.3. Clinical measurements and study outcomes At V0, structured questionnaires were administered to collect the data on (1) socio-demographic status, (2) medical history of depression, (3) prescribed antidepressant regimens and dosages, (4) substance abuse history, and (5) concurrent medications. MMSE scores were recorded at each visit to monitor potential cognitive impairment that could potentially confound study outcomes. Depression symptom severity was evaluated by psychiatrists using the 21-item Hamilton Depression Rating Scale (HAMD) [ 41 ] complemented with Clinical Global Impression (CGI) scales for disease severity (CGI-S) and treatment improvement (CGI-I) [ 42 ]. Additionally, the 21-item Beck Depression Inventory-IA [ 43 ] was utilized as a patient self-reported measure of symptom severity and treatment response. Assessments were performed at all visits, except in case of CGI-I score, which was not applicable at V0. Treatment effectiveness was quantified by a decrease in symptom severity from baseline measured by HAMD and BDI-IA, with the reduction of HAMD score as the primary outcome. In addition to the absolute reduction in scores, relative changes from baseline were also analyzed to account for confounding factor induced by inter-individual differences in baseline depressive symptom intensity. Next, response incidence analyzed separately as a categorical outcome and was measured as the proportion of patients with a 50% or greater reduction in HAMD and BDI-IA scores. Finally, absolute CGI-S and CGI-I scores at V1 and V2 were compared across metabolizer groups. Treatment tolerability was assessed at V1 and V2 using the Toronto Side-Effects Scale (TSES) [ 44 ] complemented with the Clinical Global Impression - Efficacy Index (CGI-E) [ 42 ].. The TSES evaluated the frequency and severity of adverse effects categorized into three domains: central nervous system (CNS) effects, gastrointestinal (GI) disturbances, and sexual dysfunction (SF). Composite intensity scores were calculated by multiplying frequency and severity ratings and average intensity scores were compared between groups for overall side-effect burden and for each domain separately. An intensity score of 1 indicated the absence of adverse drug reactions, while scores ranging from 2 to 25 reflected increasing severity [ 44 ]. Absolute side-effect frequencies were also extracted from TSES scores and compared across groups. Additionally, CGI-E was calculated at V1 and V2 as the ratio of clinical benefit to side-effect burden and was used as a secondary outcome of treatment tolerability. 2.4. Statistical data analysis The statistical analyses were performed using SPSS Statistics 20 software (IBM, USA). This sample size was calculated to detect a difference of three HAMD points, which corresponds to minimally clinically observable effect between groups [ 45 ] with a statistical power of 85% [ 46 ]. For between-group comparisons, the normality of the data was tested using the Shapiro-Wilk test. Socio-demographic and medical history data were compared using one-way ANOVA if the data was normally distributed or by the Kruskal-Wallis test if they were not. Fisher’s exact test was used for the statistical evaluation of between-group differences in categorical variables. Absolute HAMD and BDI-IA values were compared using repeated-measures ANOVA to assess changes between visits in the different CYP2D6 metabolizer groups. Between-group comparisons of HAMD at each visit were further assessed using analysis of covariance (ANCOVA), with Tukey post-hoc test for between-group comparison. Additionally, relative changes in HAMD and BDI-IA scores normalized by respective baseline values were compared using ANCOVA with Tukey post-hoc tests, while differences in absolute incidence of adverse events and HAMD response rates were evaluated using the binary logistic regression. Covariates in both models were the age, gender, baseline diagnosis, episode duration, and fluoxetine-equivalent dose because all these factors have been shown to influence the effectiveness of antidepressant treatment [ 47 , 48 , 49 ]. BDI-IA response rates. TSES intensity scores, MMSE scores, and CGI scores were compared between groups using the Kruskal-Wallis test, with Mann-Whitney U tests for post hoc comparisons. In addition to the primary analysis focusing on CYP2D6, combined analyses considering both CYP2D6 and CYP2C19 metabolizer status were performed using the same statistical methods to assess treatment effectiveness and tolerability. FDR correction of p -values was applied whenever multiple comparisons were performed, all tests were two-sided tests, and corrected p -values lower than 0.05 were interpreted as statistically significant difference. Importantly, 19 of the 99 patients included were treated with antidepressants that are not considered CYP2D6 enzyme substrates [ 14 ], but were still included because much is still unclear about the metabolism of antidepressants and because some direct or indirect effects of CYP2D6 genotype cannot be excluded. However, a sensitivity analysis was performed to determine whether the study results are different after the exclusion of patients not treated with the antidepressants that are proven CYP2D6 substrates. 3. RESULTS Study results were reported in accordance with STROBE statement guidelines for cohort studies (Table S1 ) [ 50 ]. 3.1. Patient baseline characteristics Of the 115 eligible patients, 102 patients agreed to participate in the study and completed the protocol, while three patients were excluded due to in conclusive CYP2D6 genotyping. Based on CYP2D6 genotype, patients were categorized into 64 normal metabolizers (NMs), 30 intermediate metabolizers (IMs), and 5 poor metabolizers (PMs). All patients were of Caucasian descent, with a slight predominance of males. No significant differences were observed in demographic variables, including age, sex distribution, education level, employment status, marital status, and substance abuse, including alcohol consumption, smoking, or psychoactive substance use. PMs had a significantly longer history of depression than both NMs and IMs—by 8 and 10.5 years, respectively. IMs had longer hospitalization compared to NMs by 8 days. At admission, the median HAMD and BDI-IA scores for the entire cohort were 33 and 35, respectively. While HAMD scores did not significantly differ between groups, BDI-IA scores did, with IMs showing a 9-point higher median compared to NMs. The most frequently prescribed antidepressants were escitalopram (20), trazodone (14), mirtazapine (11), sertraline (11), venlafaxine (10), clomipramine (7), tianeptine (6). Median otal antidepressant dose, converted to fluoxetine equivalents, was 32 mg/day for the entire cohortand did not significantly differ between groups. All baseline values of the study cohort and study groups are shown in detail in Table 1 . Table 1 Population characteristics. Demographics Total NM IM PM Statistics n = 99 n = 64 n = 30 n = 5 Sex (Male/Female) 56/43 35/29 19/11 2/3 p > 0.1 Age (years) 47 (11) 46 (11) 48 (6.7) 50 (7.3) p > 0.1 Education (Elementary/Highschool/University) 11/58/30 7/36/21 3/18/9 1/4/0 p > 0.1 Employment (Unemployed/Employed/Retired) 37/40/22 22/12/30 12/9/9 3/1/1 p > 0.1 Marital status (Married/Unmarried) 60/39 38/26 17/13 5/0 p > 0.1 Substance abuse Alcohol (nof users) 27 19 8 0 p > 0.1 Smoking (nof users) 45 28 15 2 p > 0.1 Psychoactive substances (nof users) 0 0 0 0 p > 0.1 Depression medical history Duration of depression (Years) 5.0(1.0–10) 4.5(1.0–9.5) b 7.0(2.0–12) b 15(12–23) a p = 0.007 Duration of currentepisode (Months) 2.0(1.0–3.0) 2.0(1.0–3.0) 2.5(1.0–6.0) 3.0(2.0–7.5) p > 0.1 First time hospitalized (n) 41 26 15 0 p > 0.1 Duration of hospitalization (days) 24(21–32) 22(21–39) a 30.5(23–38) b 32(26–52) a,b p = 0.009 Total antidepressant dose ( Fluoxetine equivalent mg ) 32(19–44) 32(15–40) 32(20–46) 40(19–51) p > 0.1 HAMD score at admission 33(28–35) 32(28–35) 30(33–36) 27(30–40) p > 0.1 BDI-IA score at admission 35(30–45) 33.5(29–39) a 42(30–49) b 37 (30–48) a,b p = 0.036 Depression diagnosis (Mild or Moderate/Severe/Severe with psychosis) 14/65/20 11/42/11 3/20/7 0/3/2 p > 0.1 CYP2D6 genotype Wt/Wt n = 64 Wt/*3, n = 2 Wt/*4, n = 12 Wt/*6, n = 2 Wt/*9, n = 2 Wt/*41, n = 7 Wt/*5, n = 3 *9/*5, n = 1 *4/*41, n = 1 *4/*4, n = 4 *3/*3, n = 1 3.2. Association between CYP2D6 genotype and treatment effectiveness and tolerability To evaluate whether treatment effectiveness was associated with CYP2D6 genotype, we compared the reduction in depression symptom severity across CYP2D6 genotype-defined metabolizer groups. Compared to NMs, IMs and PMs exhibited 5.1 and 9.5 points lower HAM-D score reductions (Fig. 1 A) and higher CGI-I scores at V2 (Table 2 ), reflecting less clinician-reported improvement. Similarly, BDI-IA scores improved over time and differed between the groups at both follow-up visits (Fig. 1 B). IMs had 4.6 points lower BDI-IA scores reduction compared to NMs, whereas the difference was not observed between PMs and NMs. In terms of relative symptom reduction, HAMD score decrease was lower by 17% and 34% in IMs and PMs compared to NMs, respectively (Fig. 1 C), while BDI-IA scores decrease was lower by 19% and 28% in IMs and PMs, respectively (Fig. 1 D). Based on HAMD, response rates were lower by 48% in IMs compared with NMs (Fig. 1 E) and based on BDI-IA, response rates were lower by 51% in IMs compared with NMs (Fig. 1 F). Altogether, treatment effectiveness was substantially lower in CYP2D6 intermediate and poor metabolizers, compared with normal metabolizers. Table 2 MMSE and CGI scores in patients with different CYP2D6 metabolizer status . Clinical scale NM IM PM n = 64 n = 30 n = 5 V0 30(28–30) 30(27.8–30) p = 0.530 28(25.5–29.5) p = 0.085 MMSE V1 30(29–30) 30(27.5–30) p = 0.098 29.0(25.5–30) p = 0.093 V2 30(30–30) 30(29–30) p = 0.014 29(26–30) p = 0.014 V0 5(5–6) 6(5–6) p = 0.288 6(5.5–6.5) p = 0.938 CGI-S V1 4(4–5) 5(4–5) p = 0.149 5(4.5–6) p = 0.056 V2 3(3–4) 4(3–4) p = 0.036 4(3–5) p = 0.117 V0 7(6–7) 7(6–7) p = 0.938 7(6.5–7) p = 0.436 CGI-I V1 2(2–2) 2(2–3) p < 0.0001 3(2–5) p = 0.003 V2 2(1–2) 2(2–2) p < 0.0001 2(2–4) p = 0.004 CGI-E V1 3(3–3) 2.5(2–3) p = 0.012 1(1–2.2) p = 0.001 V2 3(3–4) 3(2–3) p < 0.0001 1.5(1.2–2.5) p = 0.001 To evaluate whether antidepressant treatment tolerability was associated with CYP2D6 genotype, we compared the severity of adverse drug reactions (ADRs) between CYP2D6 genotype-defined subgroups. At V2, IMs and PMs exhibited 0.8 and 2.3 higher median TSES intensity scores compared to NMs, respectively (Fig. 2 A). For CNS-related ADRs (Fig. 2 B), IMs and PMs showed 0.6 and 1.3 higher intensity scores compared with NMs, respectively, for GI-related ADRs (Fig. 2 C), IMs and PMs exhibited 0.4 and 1.3 higher median intensity scores compared with NMs, respectively, whereas intensity of SF-related adverse drug reactions were not different between CYP2D6 metabolizer groups (Fig. 2 D). Additionally, compared with NMs, IMs and PMs exhibited significantly lower effectiveness-to-tolerability ratios at V2, as measured by CGI-E scores (Table 2 ), indicating worse overall treatment tolerability. Altogether, treatment tolerability was worse in CYP2D6 intermediate and poor metabolizer groups compared with normal metabolizers. 3.3. Sensitivity analysis Decision to exclude patients not treated with CYP2D6 substrate drugs did not meaningfully change the magnitudes or the significance levels of the between-group changes in the treatment effectiveness and tolerability readouts. The sensitivity analysis is presented in full detail in the supplement (Table S3-S4). In addition, detailed results of the composite analysis of CYP2D6 and CYP2C19 metabolic capacities and their association with clinical outcomes are provided in Supplement (Table S5). 4. DISCUSSION The results indicate that slower CYP2D6 metabolism in this cohort of hospitalized patients suffering from MDD contributed to worse antidepressant treatment outcomes compared with normal CYP2D6 metabolizers. Worse effectiveness was observed in assessment by both clinician-rated (HAMD, CGI-I, CGI-S) and patient-rated (BDI-IA) psychometry assessment tools, while worse tolerability was observed in both TSES scores and CGI-E effectiveness/tolerability ratios. These results are concordant with previously published reports indicating worse effectiveness [ 21 , 22 51 ] and tolerability [ 22 , 24 , 25 ] of antidepressant treatment in patients with genetically-encoded lower CYP2D6 enzymatic capacity. However, these results are in contrast with other reports that failed to observe association between CYP2D6 genotype and antidepressant treatment outcomes [ 31 , 32 , 33 , 34 ]. Moreover, a supplementary composite analysis incorporating both CYP2D6 and CYP2C19 genotypes demonstrated that patients with reduced function of both enzymes exhibited the poorest treatment outcomes and the highest overall burden of adverse drug reactions. The obtained results advocate the usefulness of preemptive CYP2D6 and CYP2C19 genotyping because they indicate that knowing whether a patient is PM or IM may be useful for clinicians to predict outcomes and to adequately select drugs, dosage, and treatment strategies to minimize the risk of treatment failure. Indeed, well replicated results indicate that PMs are at increased risk of in tolerable adverse drug reactions even under standard dosing, which often leads to drug discontinuation before the benefits can be achieved [ 22 , 24 , 25 ]. Consequently, dose adjustments or alternative medications in CYP2D6 PMs are recommended across relevant clinical guidelines for numerous antidepressant drugs [ 36 , 52 ]. However, most of the guidelines focus only on PMs and overlook the significance of IMs, despite the evident differences in antidepressant blood levels between IMs and NMs [ 53 ]. While the clinical significance of being an IM is likely more subtle than being a PM, according to this and other studies [ 54 ], IMs also require different treatment and dosing strategies, especially when the drug has a narrow therapeutic window [ 23 , 55 ]. An additional challenge to establish informative guidelines for IMs is the lack of a clear definition for the CYP2D6 IM phenotype, as different authors tend to use different categorization criteria, which is not the case for PMs, who are clearly defined by the presence of two non-functional alleles i.e. the complete absence of the active CYP2D6 enzyme [ 17 , 56 , 57 ]. In addition, one less likely, but plausible explanation for the observed results concerns the considerable presence of CYP2D6 in the brain, which means that local metabolism of antidepressants may be affected by CYP2D6 genotype [ 58 ]. Reduced CYP2D6 activity may be associated with altered intracerebral levels of antidepressants or their metabolites independent of blood levels, which may lead to altered therapeutic response or increased adverse drug reactions, potentially due to different effects on neurotransmitter homeostasis in the brain. In conclusion, the observed association between slower CYP2D6 and CYP2C19 metabolism and poor treatment outcomes suggests the potential benefits of using preemptive CYP2C19/CYP2D6 genotyping as part of the standard treatment routine. In theory, the ability to identify PMs and IMs prior to initiating treatment could provide clinicians with useful information to better individualize therapy, reduce adverse effects, and improve the successfulness of antidepressant therapy. These results are particularly useful when considering hospitalized patients suffering from depression, like the cohort analyzed here, where there is less margin for error and more at stake in case of suboptimal treatment. Importantly however, studies with prospective design, preemptive CYP2D6 and CYP2C19 genotyping, and examination of pharmacokinetic parameters are still needed to unequivocally demonstrate the usefulness of knowing CYP2D6 and CYP2C19 genotype in terms of improving antidepressant treatment successfulness. 4.1. Limitations The main limitation is lack of availability of pharmacokinetic data meaning that it was not possible to directly link CYP2D6 genotype to drug concentration in the blood. Next, due to the small number of PMs in the cohort, all statistical comparisons related to this category should be interpreted with caution and as preliminary findings. In addition, the patients were already receiving antidepressant therapy at the time of study enrollment, so it was not possible to take treatment duration or history into consideration, which may have influenced clinical outcomes. Furthermore, while concomitant use of multiple antidepressants reflects the usual situation in clinical settings, it further complicates the interpretation of results due the interference between CYP2D6 gene–drug and drug-drug interactions. Finally, numerous factors limit the generalizability of the results obtained to general population because: ( 1 ) the cohort did not include UMs, ( 2 ) the cohort consisted primarily of military personnel and consequently the sample was predominantly male which does not represent the general population, in which there is usually higher incidence of depression in women among depressed patients, ( 3 ) all patients had relatively severe depression that required hospitalization, ( 4 ) the cohort included only Caucasian participants. Declarations FUNDING Funding source had no role in study design; in the collection, analysis, and interpretation of data; in the writing of the report; and in the decision to submit the article for publication. COMPETING INTERESTS Marin Jukić is a cofounder and executive director of TDM health. All other authors declare no competing interest. Funding for this study was provided by the 6066800/PsyCise from the Science Fund of the Republic of Serbia PROMIS program to the corresponding author Dr Jukić and by the MFVMA/05/20–22 grant from the University of Defense, Belgrade, Serbia to Zvezdana Stojanović. The authors would like to thank the clinical staff of the Military Medical Academy for their assistance with sample collection and the patients who participated in the study. AUTHOR CONTRIBUTIONS Aleksandra Petković Ćurčin: Methodology, Conceptualization, Investigation, Writing – review & editing, Project administration. Aleksandra Jeremić: Writing – original draft, Writing – review & editing, Visualization. Danilo Joković: Methodology, Resources, Investigation, Data curation, Writing – review & editing. Danilo Joković: Methodology, Investigation Gordana Šupić: Methodology, Investigation, Writing – review & editing. Filip Milosavljević: Writing – review & editing. 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Evaluation of the CYP2D6 Haplotype Activity Scores Based on Metabolic Ratios of 4,700 Patients Treated With Three Different CYP2D6 Substrates. Clin Pharma and Therapeutics 2021; 110: 750–758. Stingl JC, Brockmöller J, Viviani R. Genetic variability of drug-metabolizing enzymes: the dual impact on psychiatric therapy and regulation of brain function. Mol Psychiatry 2013; 18: 273–287. Additional Declarations Yes there is potential conflict of interest. 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16:23:47","extension":"html","order_by":13,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":169732,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-7234296/v1/7aba6aad4d956079d1c12576.html"},{"id":92734503,"identity":"26d73a21-f8eb-494f-bbff-1b3d62eb7b53","added_by":"auto","created_at":"2025-10-03 16:23:46","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":89399,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eAssociation between antidepressant treatment effectiveness and \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eCYP2D6 \u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003egenotype\u003c/strong\u003e. (\u003cstrong\u003eA\u003c/strong\u003e) At V2, PMs showed a 9.5 points smaller absolute HAMD decrease compared to NMs [95% CI: 3.5–16, \u003cem\u003ep\u003c/em\u003e = 0.001], while IMs had a 5.1 points smaller decrease [95% CI: 2.3–8.0, \u003cem\u003ep\u003c/em\u003e\u0026lt; 0.001]. (\u003cstrong\u003eB\u003c/strong\u003e) A repeated measures ANOVA revealed a significant main effect of visit on BDI-IA scores (\u003cem\u003ep\u003c/em\u003e\u0026lt; 0.001), indicating a general reduction in symptoms over time. Additionally, a significant main effect of metabolizer group was observed (p \u0026lt; 0.001), indicating that average BDI-IA scores differed between CYP2D6 metabolizer category. At V2, IMs had a 4.6 points lower absolute BDI-IA decrease compared to NMs [95% CI: 4.1–13, p \u0026lt; 0.001]. No significant differences were observed between PMs and NMs. (\u003cstrong\u003eC\u003c/strong\u003e) At V1, PMs and IMs showed a 16% [1.1-31%, \u003cem\u003ep\u003c/em\u003e = 0.031] and 9.3% [2.2-16%, \u003cem\u003ep\u003c/em\u003e = 0.006] smaller decrease in HAMD scores compared to NMs, respectively. At V2, PMs had a 34% [18-49%, \u003cem\u003ep \u003c/em\u003e\u0026lt; 0.001] lower absolute decrease compared to NMs, while IMs showed a 17% [10%-25%, \u003cem\u003ep\u003c/em\u003e\u0026lt; 0.001] lower decrease. PMs also had a 16% [0.2-32%, \u003cem\u003ep\u003c/em\u003e = 0.046] smaller decrease than IMs. (\u003cstrong\u003eD\u003c/strong\u003e) Concerning BDI-IA score changes At V1, IMs had a 11% [0.7-21%, \u003cem\u003ep\u003c/em\u003e = 0.034] smaller decrease in BDI-IA scores compared to NMs, while no significant differences were found between PMs and NMs or PMs and IMs. At V2, IMs had a 19% [11-28%, \u003cem\u003ep\u003c/em\u003e\u0026lt; 0.001] smaller decrease than NMs, while PMs had a 28% [9.2-46%, \u003cem\u003ep\u003c/em\u003e= 0.001] smaller decrease. (\u003cstrong\u003eE\u003c/strong\u003e) Response rate was defined as proportion of patients with HAMD score reduction of 50% or higher from V0 to V2. IMs had 48% [28-67%, \u003cem\u003ep \u003c/em\u003e= 0.010] lower response rate, compared with NMs; (\u003cstrong\u003eF\u003c/strong\u003e) Response rates differed significantly across CYP2D6 metabolizer groups (\u003cem\u003ep\u003c/em\u003e\u0026lt; 0.001) and response was achieved in 54/64 NMs, 10/30 IMs, and none of five PMs. Covariates in ANCOVA models and logistic regression included age, sex, diagnosis at V0, episode duration, and fluoxetine-equivalent dose. \u003cem\u003eHAMD: Hamilton Depression Rating Scale; BDI-IA: Beck depression inventory; NM: Normal CYP2D6 metabolizer; IM – Intermediate metabolizers; PM: Poor CYP2D6 metabolizer; V0: hospital admission; V1: 2 weeks after the admission; V2: 4–6 weeks after the hospital admission.*p\u0026lt;0.05, ** p\u0026lt;0.01, *** p\u0026lt;0.001, whiskers represent CI 95%\u003c/em\u003e\u003c/p\u003e","description":"","filename":"Figure1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7234296/v1/3954e5b9fa5b29d490884c30.jpg"},{"id":92735736,"identity":"20645a74-d406-4ed7-bc46-e158a10e566c","added_by":"auto","created_at":"2025-10-03 16:31:50","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":67829,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eAssociation between antidepressant treatment tolerability and \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eCYP2D6 \u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003egenotype.\u003c/strong\u003e (\u003cstrong\u003eA\u003c/strong\u003e) At V2, median intensity scores for all adverse reactions combined were significantly higher in both IMs: 3.1 [IQR:2.1–3.9, \u003cem\u003ep\u003c/em\u003e = 0.007]) and PM: 4.6 [IQR: 3.3–5.3, \u003cem\u003ep\u003c/em\u003e = 0.002], compared with NMs: 2.3 [IQR: 1.8–3.1]. (\u003cstrong\u003eB\u003c/strong\u003e) Median intensity scores for CNS-related adverse reactions were also higher in both IMs: 2.5 [IQR: 1.8–3.2, \u003cem\u003ep\u003c/em\u003e = 0.001] and PMs: 3.2 [IQR: 2.6–4.8, \u003cem\u003ep\u003c/em\u003e = 0.004], compared to NMs: 1.9 [IQR: 1.5–2.2]. (\u003cstrong\u003eC\u003c/strong\u003e) Similarly, both IMs:2.0 [IQR: 1.5–2.8, \u003cem\u003ep\u003c/em\u003e = 0.008] and PMs: 2.9 [IQR: 2.4–3.4, \u003cem\u003ep\u003c/em\u003e = 0.002] exhibited higher median intensity scores for GI-related adverse reactions compared to NMs: 1.6 [IQR: 1.3–2.1]. (\u003cstrong\u003eD\u003c/strong\u003e) However, for SF-related adverse reactions, differences between NMs: 3.8 [IQR: 2.7–6.0], IMs: 5.7 [IQR: 3.7–7.8], and PMs: 9.0 [IQR: 3.5–9.0] did not reach statistical significance (\u003cem\u003ep\u003c/em\u003e = 0.093) \u003cem\u003eCNS - central nervous system; GI - gastrointestinal; SF - sexual function; TSES – Toronto Side-Effects Scale; NM: Normal CYP2D6 metabolizer; IM – Intermediate CYP2D6 metabolizer; PM: Poor CYP2D6 metabolizer; V2: 4–6 weeks after the hospital admission; IQR – interquartile range.*p\u0026lt;0.05, ** p\u0026lt;0.01, *** p\u0026lt;0.001, Boxes represent interquartile range, whiskers represent minimum and maximum and dots represent outliers.\u003c/em\u003e\u003c/p\u003e","description":"","filename":"Figure2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7234296/v1/7ce194a0b69a5854be8da6bb.jpg"},{"id":92735793,"identity":"3badd4c4-cdce-477c-90de-26b693e3953a","added_by":"auto","created_at":"2025-10-03 16:31:56","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1184748,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7234296/v1/a7d38198-340f-484a-bde2-3b183ad60f32.pdf"},{"id":92734555,"identity":"a0ad4dc3-56b4-48b7-970c-c4dc2e792fb8","added_by":"auto","created_at":"2025-10-03 16:23:48","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":41282,"visible":true,"origin":"","legend":"Supplementary material","description":"","filename":"SUPPLEMENTARYMATERIAL.docx","url":"https://assets-eu.researchsquare.com/files/rs-7234296/v1/f58f7895792d31c532146071.docx"}],"financialInterests":"\u003cb\u003eYes\u003c/b\u003e there is potential conflict of interest.","formattedTitle":"Association between CYP2D6 genotype and treatment effectiveness and safety in 99 hospitalized patients with major depressive disorder - a retrospective cohort study","fulltext":[{"header":"1. INTRODUCTION","content":"\u003cp\u003eDepressive disorders lead to the disability of more than 280\u0026nbsp;million individuals [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e], while two thirds of suicide victims are depressed at the time of their death [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Numerous major depressive disorder (MDD) patients experience treatment failure due to lack of effectiveness or intolerable side effects [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Since the development of new antidepressant drugs is very slow, there is an urgent need for personalization of treatment with currently available antidepressants, for example, by utilization of pharmacogenomic information in therapeutic decision making protocols [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Despite the evidence that pharmacogenomic-guided approach improves antidepressant treatment outcomes [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e], the effect sizes are still not sufficiently convincing and they vary among sources due to inconsistencies in cohorts analyzed and study settings. Consequently, further clinical research focused on specific gene-drug interactions and adequate characterization of clinically impactful and actionable pharmacogenetic associations is needed to facilitate the implementation of meaningful pharmacogenetic testing into clinical practice.\u003c/p\u003e\u003cp\u003eCytochrome P450 2D6 (CYP2D6) and 2C19 (CYP2C19) are polymorphic enzymes that metabolizes the majority of commonly prescribed antidepressants [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Functional genetic variants of \u003cem\u003eCYP2D6\u003c/em\u003e and \u003cem\u003eCYP2C19\u003c/em\u003e are highly prevalent and they cause the significant inter-individual variability in enzymatic capacity. Patients are usually categorized as poor metabolizers (PMs), intermediate metabolizers (IMs), normal (or extensive) metabolizers (NMs) and ultra-rapid metabolizers (UMs) based on \u003cem\u003eCYP2C19\u003c/em\u003e and \u003cem\u003eCYP2D6\u003c/em\u003e genotype [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. The patients with decreased enzymatic activity (i.e., PMs and IMs) are considered to be at high risk for overdose and intolerable adverse drug reactions, while UMs are considered to be at high risk of subtherapeutic drug levels and inadequate treatment response. As both mentioned risks affect antidepressant treatment successfulness [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e], the knowledge of \u003cem\u003eCYP2C19\u003c/em\u003e and \u003cem\u003eCYP2D6\u003c/em\u003e genotype can potentially be useful for clinicians in helping them with selection of appropriate antidepressant drugs and their dosage. Our previous work showed that CYP2C19 slow metabolizer phenotype is associated with lower antidepressant efficacy and tolerability [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. Related to the association between \u003cem\u003eCYP2D6\u003c/em\u003e genotype and the effectiveness and tolerability of antidepressants that has been extensively studied, results remain inconsistent [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. Many studies advocate the importance of matching the choice of antidepressant with \u003cem\u003eCYP2D6\u003c/em\u003e metabolizer status, while the CYP2D6 enzymatic capacity, as determined by genetic variation, has been associated with differences in antidepressant effectiveness [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e] and tolerability [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. Next, \u003cem\u003eCYP2D6\u003c/em\u003e PMs were at five times higher risk to switch their antidepressants [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e] or discontinue treatment compared to NMs [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. However, there are many other adequately powered studies that failed to observe significant association between \u003cem\u003eCYP2D6\u003c/em\u003e phenotype and antidepressant treatment effectiveness [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e] or tolerability [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eCurrently, guidelines published by various expert groups, such as the Clinical Pharmacogenetics Implementation Consortium (CPIC), the Dutch Pharmacogenetics Working Group (DPWG), and the US Food and Drug Administration (FDA) provide the instructions to clinicians on how to use \u003cem\u003eCYP2D6\u003c/em\u003e genotype to personalize antidepressant treatment. However, discrepancies between these recommendations are still apparent, underlining the lack of certainty about how \u003cem\u003eCYP2D6\u003c/em\u003e genotype needs to be used to maximize antidepressant treatment successfulness [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. This naturalistic retrospective cohort study aimed to investigate the association of \u003cem\u003eCYP2D6\u003c/em\u003e genotype with antidepressant treatment effectiveness and safety in patients hospitalized due to major depressive disorder.\u003c/p\u003e"},{"header":"2. MATERIAL AND METHODS","content":"\u003cp\u003eThis naturalistic hospital-based retrospective cohort study was conducted between May 2016 and January 2018 at the Department of Psychiatry of the Military Medical Academy in Belgrade, Serbia. This naturalistic retrospective cohort study complied with the principles of the Declaration of Helsinki (1997). The protocol was approved by the Ethics Committee of the Military Medical Academy in Belgrade on March 29, 2016, and all participants signed written informed consent before being subjected to the study protocol and included in the data analysis.\u003c/p\u003e\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003e2.1. Study participants and exposures\u003c/h2\u003e\u003cp\u003ePatients were eligible for inclusion if they had been (1) diagnosed with MDD, (2) receiving stable treatment with one or two antidepressants, and (3) hospitalized in a tertiary care facility due to the severity of their depression symptoms. MINI 5.0.0. interview (Mini International Neuropsychiatric Interview) [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e] was used as a screening tool; exclusion criteria included (1) age under 18 or over 65 years, (2) a Mini Mental State Examination (MMSE) score below 24 at enrollment, (3) less than eight years of formal education, and (4) a diagnosis of mental retardation according to ICD-10 criteria. There were no restrictions on the choice of antidepressants or dosage. To enable dose comparisons, antidepressant doses were converted to fluoxetine equivalents [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. Patients were clinically assessed at three predefined time points: (1) At the beginning of the study (visit 0, V0) after hospital admission, (2) during interim assessment (visit 1, V1), two weeks after hospitalization, and (3) during final assessment (Visit 2, V2) on discharge from hospital (4\u0026ndash;6 weeks after admission). \u003cem\u003eCYP2D6\u003c/em\u003e genotyping and categorization in to \u003cem\u003eCYP2D6\u003c/em\u003e metabolizer groups for subsequent analysis was performed retrospectively after completion of the study and consequently, the investigators who rated the psychometric scales were blinded for \u003cem\u003eCYP2D6\u003c/em\u003e genotype. The study cohort had previously been genotyped for \u003cem\u003eCYP2C19\u003c/em\u003e as part of the previous study [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e].\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\u003ch2\u003e2.2. \u003cem\u003eCYP2D6\u003c/em\u003e genotyping\u003c/h2\u003e\u003cp\u003ePeripheral blood samples were collected in EDTA tubes and stored at \u0026minus;\u0026thinsp;20\u0026deg;C until DNA isolation. DNA was isolated from the collected blood samples using the PureLink Genomic DNA Mini Kit (Invitrogen, USA). The integrity of the isolated DNA samples was assessed by 1% agarose gel electrophoresis, and the concentration and purity were determined using the Gene Quant spectrophotometer (Pharmacia LKB, Stockholm, Sweden). CYP2D6 genotyping was performed with the commercially available TaqMan SNP Genotyping Assays (Applied Biosystems) on a 7500 Real-Time PCR System (Applied Biosystems, Foster City, CA, USA) using the allele discrimination method to genotype the polymorphisms. Patients were genotyped for common (1% or higher incidence) non-functional alleles (\u003cem\u003eCYP2D6Nonf\u003c/em\u003e), including \u003cem\u003eCYP2D6*3\u003c/em\u003e (rs35742686), \u003cem\u003eCYP2D6*4\u003c/em\u003e (rs3892097), \u003cem\u003eCYP2D6*6\u003c/em\u003e (rs5030655) and for common alleles associated with decreased enzymatic capacity (\u003cem\u003eCYP2D6Decr\u003c/em\u003e), including \u003cem\u003eCYP2D6*9\u003c/em\u003e (rs5030656), \u003cem\u003eCYP2D6*10\u003c/em\u003e (rs1065852) and \u003cem\u003eCYP2D6*41\u003c/em\u003e (rs28371725) alleles. Rare alleles in this population, such as \u003cem\u003eCYP2D6*17\u003c/em\u003e (\u0026lt;\u0026thinsp;0.5%) [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e], were not included in the analysis. Gene copy number variation was assessed to detect deletions or multiplications of entire genes according to the manufacturer\u0026rsquo;s protocol (Assay ID: Hs00010001_cn; Thermo Fisher Scientific, Waltham, MA). If no variant alleles were detected, the allele was considered to be associated with normal metabolic activity (\u003cem\u003eCYP2D6Norm\u003c/em\u003e). Patients were categorized based on their genotype-predicted enzymatic activity; homozygous carriers of the \u003cem\u003eCYP2D6Norm\u003c/em\u003e allele were classified as normal metabolizers (NM) and served as the reference group and homozygous carriers of \u003cem\u003eCYP2D6Nonf\u003c/em\u003e alleles (\u003cem\u003eCYP2D6*3\u003c/em\u003e, \u003cem\u003eCYP2D6*4\u003c/em\u003e, \u003cem\u003eCYP2D6*6\u003c/em\u003e) were classified as poor metabolizers (PM). Patients who carried less than two \u003cem\u003eCYP2D6Norm\u003c/em\u003e alleles, but who were not PMs, were classified as intermediate metabolizers (IM). The presence of multiple \u003cem\u003eCYP2D6Norm\u003c/em\u003e gene copies would result in classification of ultra-rapid metabolizers (UM); however, no such patients were found in this cohort. Three heterozygous individuals carried three copies of the \u003cem\u003eCYP2D6\u003c/em\u003e gene, but due to uncertainty as to which allele was duplicated, we could not unequivocally confirm their metabolizer status and they were therefore excluded from the analysis.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\u003ch2\u003e2.3. Clinical measurements and study outcomes\u003c/h2\u003e\u003cp\u003eAt V0, structured questionnaires were administered to collect the data on (1) socio-demographic status, (2) medical history of depression, (3) prescribed antidepressant regimens and dosages, (4) substance abuse history, and (5) concurrent medications. MMSE scores were recorded at each visit to monitor potential cognitive impairment that could potentially confound study outcomes. Depression symptom severity was evaluated by psychiatrists using the 21-item Hamilton Depression Rating Scale (HAMD) [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e] complemented with Clinical Global Impression (CGI) scales for disease severity (CGI-S) and treatment improvement (CGI-I) [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]. Additionally, the 21-item Beck Depression Inventory-IA [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e] was utilized as a patient self-reported measure of symptom severity and treatment response. Assessments were performed at all visits, except in case of CGI-I score, which was not applicable at V0. Treatment effectiveness was quantified by a decrease in symptom severity from baseline measured by HAMD and BDI-IA, with the reduction of HAMD score as the primary outcome. In addition to the absolute reduction in scores, relative changes from baseline were also analyzed to account for confounding factor induced by inter-individual differences in baseline depressive symptom intensity. Next, response incidence analyzed separately as a categorical outcome and was measured as the proportion of patients with a 50% or greater reduction in HAMD and BDI-IA scores. Finally, absolute CGI-S and CGI-I scores at V1 and V2 were compared across metabolizer groups.\u003c/p\u003e\u003cp\u003eTreatment tolerability was assessed at V1 and V2 using the Toronto Side-Effects Scale (TSES) [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e] complemented with the Clinical Global Impression - Efficacy Index (CGI-E) [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e].. The TSES evaluated the frequency and severity of adverse effects categorized into three domains: central nervous system (CNS) effects, gastrointestinal (GI) disturbances, and sexual dysfunction (SF). Composite intensity scores were calculated by multiplying frequency and severity ratings and average intensity scores were compared between groups for overall side-effect burden and for each domain separately. An intensity score of 1 indicated the absence of adverse drug reactions, while scores ranging from 2 to 25 reflected increasing severity [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e]. Absolute side-effect frequencies were also extracted from TSES scores and compared across groups. Additionally, CGI-E was calculated at V1 and V2 as the ratio of clinical benefit to side-effect burden and was used as a secondary outcome of treatment tolerability.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\u003ch2\u003e2.4. Statistical data analysis\u003c/h2\u003e\u003cp\u003eThe statistical analyses were performed using SPSS Statistics 20 software (IBM, USA). This sample size was calculated to detect a difference of three HAMD points, which corresponds to minimally clinically observable effect between groups [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e] with a statistical power of 85% [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e]. For between-group comparisons, the normality of the data was tested using the Shapiro-Wilk test. Socio-demographic and medical history data were compared using one-way ANOVA if the data was normally distributed or by the Kruskal-Wallis test if they were not. Fisher\u0026rsquo;s exact test was used for the statistical evaluation of between-group differences in categorical variables. Absolute HAMD and BDI-IA values were compared using repeated-measures ANOVA to assess changes between visits in the different \u003cem\u003eCYP2D6\u003c/em\u003e metabolizer groups. Between-group comparisons of HAMD at each visit were further assessed using analysis of covariance (ANCOVA), with Tukey post-hoc test for between-group comparison. Additionally, relative changes in HAMD and BDI-IA scores normalized by respective baseline values were compared using ANCOVA with Tukey post-hoc tests, while differences in absolute incidence of adverse events and HAMD response rates were evaluated using the binary logistic regression. Covariates in both models were the age, gender, baseline diagnosis, episode duration, and fluoxetine-equivalent dose because all these factors have been shown to influence the effectiveness of antidepressant treatment [\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e, \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e, \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e]. BDI-IA response rates. TSES intensity scores, MMSE scores, and CGI scores were compared between groups using the Kruskal-Wallis test, with Mann-Whitney U tests for \u003cem\u003epost hoc\u003c/em\u003e comparisons. In addition to the primary analysis focusing on CYP2D6, combined analyses considering both CYP2D6 and CYP2C19 metabolizer status were performed using the same statistical methods to assess treatment effectiveness and tolerability.\u003c/p\u003e\u003cp\u003eFDR correction of \u003cem\u003ep\u003c/em\u003e-values was applied whenever multiple comparisons were performed, all tests were two-sided tests, and corrected \u003cem\u003ep\u003c/em\u003e-values lower than 0.05 were interpreted as statistically significant difference. Importantly, 19 of the 99 patients included were treated with antidepressants that are not considered \u003cem\u003eCYP2D6\u003c/em\u003e enzyme substrates [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e], but were still included because much is still unclear about the metabolism of antidepressants and because some direct or indirect effects of \u003cem\u003eCYP2D6\u003c/em\u003e genotype cannot be excluded. However, a sensitivity analysis was performed to determine whether the study results are different after the exclusion of patients not treated with the antidepressants that are proven \u003cem\u003eCYP2D6\u003c/em\u003e substrates.\u003c/p\u003e\u003c/div\u003e"},{"header":"3. RESULTS","content":"\u003cp\u003eStudy results were reported in accordance with STROBE statement guidelines for cohort studies (Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e) [\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e].\u003c/p\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003e3.1. Patient baseline characteristics\u003c/h2\u003e\u003cp\u003eOf the 115 eligible patients, 102 patients agreed to participate in the study and completed the protocol, while three patients were excluded due to in conclusive \u003cem\u003eCYP2D6\u003c/em\u003e genotyping. Based on \u003cem\u003eCYP2D6\u003c/em\u003e genotype, patients were categorized into 64 normal metabolizers (NMs), 30 intermediate metabolizers (IMs), and 5 poor metabolizers (PMs). All patients were of Caucasian descent, with a slight predominance of males. No significant differences were observed in demographic variables, including age, sex distribution, education level, employment status, marital status, and substance abuse, including alcohol consumption, smoking, or psychoactive substance use. PMs had a significantly longer history of depression than both NMs and IMs\u0026mdash;by 8 and 10.5 years, respectively. IMs had longer hospitalization compared to NMs by 8 days. At admission, the median HAMD and BDI-IA scores for the entire cohort were 33 and 35, respectively. While HAMD scores did not significantly differ between groups, BDI-IA scores did, with IMs showing a 9-point higher median compared to NMs. The most frequently prescribed antidepressants were escitalopram (20), trazodone (14), mirtazapine (11), sertraline (11), venlafaxine (10), clomipramine (7), tianeptine (6). Median otal antidepressant dose, converted to fluoxetine equivalents, was 32 mg/day for the entire cohortand did not significantly differ between groups. All baseline values of the study cohort and study groups are shown in detail in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003ePopulation characteristics.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"6\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDemographics\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTotal\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eNM\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eIM\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003ePM\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eStatistics\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;99\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;64\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;30\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSex \u003cem\u003e(Male/Female)\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e56/43\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e35/29\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e19/11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2/3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cem\u003ep\u0026thinsp;\u0026gt;\u0026thinsp;0.1\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAge \u003cem\u003e(years)\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e47 (11)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e46 (11)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e48 (6.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e50 (7.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cem\u003ep\u0026thinsp;\u0026gt;\u0026thinsp;0.1\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEducation \u003cem\u003e(Elementary/Highschool/University)\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e11/58/30\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e7/36/21\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3/18/9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1/4/0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cem\u003ep\u0026thinsp;\u0026gt;\u0026thinsp;0.1\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEmployment \u003cem\u003e(Unemployed/Employed/Retired)\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e37/40/22\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e22/12/30\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e12/9/9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e3/1/1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cem\u003ep\u0026thinsp;\u0026gt;\u0026thinsp;0.1\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMarital status \u003cem\u003e(Married/Unmarried)\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e60/39\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e38/26\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e17/13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e5/0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cem\u003ep\u0026thinsp;\u0026gt;\u0026thinsp;0.1\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eSubstance abuse\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAlcohol \u003cem\u003e(nof users)\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e27\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e19\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cem\u003ep\u0026thinsp;\u0026gt;\u0026thinsp;0.1\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSmoking \u003cem\u003e(nof users)\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e45\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e28\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e15\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cem\u003ep\u0026thinsp;\u0026gt;\u0026thinsp;0.1\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePsychoactive substances \u003cem\u003e(nof users)\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cem\u003ep\u0026thinsp;\u0026gt;\u0026thinsp;0.1\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eDepression medical history\u003c/b\u003e\u003c/p\u003e\u003cp\u003eDuration of depression\u003cem\u003e(Years)\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e5.0(1.0\u0026ndash;10)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4.5(1.0\u0026ndash;9.5)\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e7.0(2.0\u0026ndash;12)\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e15(12\u0026ndash;23)\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003ep\u003c/b\u003e\u0026thinsp;=\u0026thinsp;\u003cb\u003e0.007\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDuration of currentepisode\u003cem\u003e(Months)\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2.0(1.0\u0026ndash;3.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2.0(1.0\u0026ndash;3.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2.5(1.0\u0026ndash;6.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e3.0(2.0\u0026ndash;7.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cem\u003ep\u0026thinsp;\u0026gt;\u0026thinsp;0.1\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFirst time hospitalized\u003cem\u003e(n)\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e41\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e26\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e15\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cem\u003ep\u0026thinsp;\u0026gt;\u0026thinsp;0.1\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDuration of hospitalization\u003cem\u003e(days)\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e24(21\u0026ndash;32)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e22(21\u0026ndash;39)\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e30.5(23\u0026ndash;38)\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e32(26\u0026ndash;52)\u003csup\u003ea,b\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003ep\u003c/b\u003e\u0026thinsp;\u003cb\u003e=\u003c/b\u003e\u0026thinsp;\u003cb\u003e0.009\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTotal antidepressant dose\u003c/p\u003e\u003cp\u003e(\u003cem\u003eFluoxetine equivalent mg\u003c/em\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e32(19\u0026ndash;44)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e32(15\u0026ndash;40)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e32(20\u0026ndash;46)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e40(19\u0026ndash;51)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cem\u003ep\u0026thinsp;\u0026gt;\u0026thinsp;0.1\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHAMD score at admission\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e33(28\u0026ndash;35)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e32(28\u0026ndash;35)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e30(33\u0026ndash;36)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e27(30\u0026ndash;40)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cem\u003ep\u0026thinsp;\u0026gt;\u0026thinsp;0.1\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBDI-IA score at admission\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e35(30\u0026ndash;45)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e33.5(29\u0026ndash;39)\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e42(30\u0026ndash;49)\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e37 (30\u0026ndash;48)\u003csup\u003ea,b\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003ep\u003c/b\u003e\u0026thinsp;\u003cb\u003e=\u003c/b\u003e\u0026thinsp;\u003cb\u003e0.036\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDepression diagnosis\u003c/p\u003e\u003cp\u003e\u003cem\u003e(Mild or Moderate/Severe/Severe with psychosis)\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e14/65/20\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e11/42/11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3/20/7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0/3/2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cem\u003ep\u0026thinsp;\u0026gt;\u0026thinsp;0.1\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eCYP2D6\u003c/b\u003e \u003cb\u003egenotype\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cem\u003eWt/Wt\u003c/em\u003e\u003c/p\u003e\u003cp\u003e\u003cem\u003en\u0026thinsp;=\u0026thinsp;64\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cem\u003eWt/*3, n\u0026thinsp;=\u0026thinsp;2\u003c/em\u003e\u003c/p\u003e\u003cp\u003e\u003cem\u003eWt/*4, n\u0026thinsp;=\u0026thinsp;12\u003c/em\u003e\u003c/p\u003e\u003cp\u003e\u003cem\u003eWt/*6, n\u0026thinsp;=\u0026thinsp;2\u003c/em\u003e\u003c/p\u003e\u003cp\u003e\u003cem\u003eWt/*9, n\u0026thinsp;=\u0026thinsp;2\u003c/em\u003e\u003c/p\u003e\u003cp\u003e\u003cem\u003eWt/*41, n\u0026thinsp;=\u0026thinsp;7\u003c/em\u003e\u003c/p\u003e\u003cp\u003e\u003cem\u003eWt/*5, n\u0026thinsp;=\u0026thinsp;3\u003c/em\u003e\u003c/p\u003e\u003cp\u003e\u003cem\u003e*9/*5, n\u0026thinsp;=\u0026thinsp;1\u003c/em\u003e\u003c/p\u003e\u003cp\u003e\u003cem\u003e*4/*41, n\u0026thinsp;=\u0026thinsp;1\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cem\u003e*4/*4, n\u0026thinsp;=\u0026thinsp;4\u003c/em\u003e\u003c/p\u003e\u003cp\u003e\u003cem\u003e*3/*3, n\u0026thinsp;=\u0026thinsp;1\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\u003ch2\u003e3.2. Association between CYP2D6 genotype and treatment effectiveness and tolerability\u003c/h2\u003e\u003cp\u003eTo evaluate whether treatment effectiveness was associated with \u003cem\u003eCYP2D6\u003c/em\u003e genotype, we compared the reduction in depression symptom severity across \u003cem\u003eCYP2D6\u003c/em\u003e genotype-defined metabolizer groups. Compared to NMs, IMs and PMs exhibited 5.1 and 9.5 points lower HAM-D score reductions (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA) and higher CGI-I scores at V2 (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e), reflecting less clinician-reported improvement. Similarly, BDI-IA scores improved over time and differed between the groups at both follow-up visits (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB). IMs had 4.6 points lower BDI-IA scores reduction compared to NMs, whereas the difference was not observed between PMs and NMs. In terms of relative symptom reduction, HAMD score decrease was lower by 17% and 34% in IMs and PMs compared to NMs, respectively (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eC), while BDI-IA scores decrease was lower by 19% and 28% in IMs and PMs, respectively (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eD). Based on HAMD, response rates were lower by 48% in IMs compared with NMs (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eE) and based on BDI-IA, response rates were lower by 51% in IMs compared with NMs (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eF). Altogether, treatment effectiveness was substantially lower in CYP2D6 intermediate and poor metabolizers, compared with normal metabolizers.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003e\u003cb\u003eMMSE and CGI scores in patients with different\u003c/b\u003e \u003cb\u003eCYP2D6\u003c/b\u003e \u003cb\u003emetabolizer status\u003c/b\u003e.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eClinical scale\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eNM\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eIM\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003ePM\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;64\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;30\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;5\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eV0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e30(28\u0026ndash;30)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e30(27.8\u0026ndash;30)\u003c/p\u003e\u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;\u003cem\u003e0.530\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e28(25.5\u0026ndash;29.5)\u003c/p\u003e\u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;\u003cem\u003e0.085\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eMMSE\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eV1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e30(29\u0026ndash;30)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e30(27.5\u0026ndash;30)\u003c/p\u003e\u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;\u003cem\u003e0.098\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e29.0(25.5\u0026ndash;30)\u003c/p\u003e\u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;\u003cem\u003e0.093\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eV2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e30(30\u0026ndash;30)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e30(29\u0026ndash;30)\u003c/p\u003e\u003cp\u003e\u003cb\u003ep\u003c/b\u003e\u0026thinsp;\u003cb\u003e=\u003c/b\u003e\u0026thinsp;\u003cb\u003e0.014\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e29(26\u0026ndash;30)\u003c/p\u003e\u003cp\u003e\u003cb\u003ep\u003c/b\u003e\u0026thinsp;\u003cb\u003e=\u003c/b\u003e\u0026thinsp;\u003cb\u003e0.014\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eV0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5(5\u0026ndash;6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e6(5\u0026ndash;6)\u003c/p\u003e\u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;\u003cem\u003e0.288\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e6(5.5\u0026ndash;6.5)\u003c/p\u003e\u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;\u003cem\u003e0.938\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eCGI-S\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eV1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4(4\u0026ndash;5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e5(4\u0026ndash;5)\u003c/p\u003e\u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;\u003cem\u003e0.149\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e5(4.5\u0026ndash;6)\u003c/p\u003e\u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;\u003cem\u003e0.056\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eV2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3(3\u0026ndash;4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e4(3\u0026ndash;4)\u003c/p\u003e\u003cp\u003e\u003cb\u003ep\u0026thinsp;=\u0026thinsp;0.036\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e4(3\u0026ndash;5)\u003c/p\u003e\u003cp\u003e\u003cem\u003ep\u0026thinsp;=\u0026thinsp;0.117\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eV0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e7(6\u0026ndash;7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e7(6\u0026ndash;7)\u003c/p\u003e\u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;\u003cem\u003e0.938\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e7(6.5\u0026ndash;7)\u003c/p\u003e\u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;\u003cem\u003e0.436\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eCGI-I\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eV1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2(2\u0026ndash;2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2(2\u0026ndash;3)\u003c/p\u003e\u003cp\u003e\u003cb\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.0001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e3(2\u0026ndash;5)\u003c/p\u003e\u003cp\u003e\u003cb\u003ep\u003c/b\u003e\u0026thinsp;=\u0026thinsp;\u003cb\u003e0.003\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eV2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2(1\u0026ndash;2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2(2\u0026ndash;2)\u003c/p\u003e\u003cp\u003e\u003cb\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.0001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2(2\u0026ndash;4)\u003c/p\u003e\u003cp\u003e\u003cb\u003ep\u003c/b\u003e\u0026thinsp;=\u0026thinsp;\u003cb\u003e0.004\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eCGI-E\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eV1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3(3\u0026ndash;3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2.5(2\u0026ndash;3)\u003c/p\u003e\u003cp\u003e\u003cb\u003ep\u0026thinsp;=\u0026thinsp;0.012\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1(1\u0026ndash;2.2)\u003c/p\u003e\u003cp\u003e\u003cb\u003ep\u003c/b\u003e\u0026thinsp;=\u0026thinsp;\u003cb\u003e0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eV2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3(3\u0026ndash;4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3(2\u0026ndash;3)\u003c/p\u003e\u003cp\u003e\u003cb\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.0001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.5(1.2\u0026ndash;2.5)\u003c/p\u003e\u003cp\u003e\u003cb\u003ep\u003c/b\u003e\u0026thinsp;=\u0026thinsp;\u003cb\u003e0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eTo evaluate whether antidepressant treatment tolerability was associated with \u003cem\u003eCYP2D6\u003c/em\u003e genotype, we compared the severity of adverse drug reactions (ADRs) between \u003cem\u003eCYP2D6\u003c/em\u003e genotype-defined subgroups. At V2, IMs and PMs exhibited 0.8 and 2.3 higher median TSES intensity scores compared to NMs, respectively (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA). For CNS-related ADRs (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB), IMs and PMs showed 0.6 and 1.3 higher intensity scores compared with NMs, respectively, for GI-related ADRs (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eC), IMs and PMs exhibited 0.4 and 1.3 higher median intensity scores compared with NMs, respectively, whereas intensity of SF-related adverse drug reactions were not different between \u003cem\u003eCYP2D6\u003c/em\u003e metabolizer groups (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eD). Additionally, compared with NMs, IMs and PMs exhibited significantly lower effectiveness-to-tolerability ratios at V2, as measured by CGI-E scores (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e), indicating worse overall treatment tolerability. Altogether, treatment tolerability was worse in \u003cem\u003eCYP2D6\u003c/em\u003e intermediate and poor metabolizer groups compared with normal metabolizers.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\u003ch2\u003e3.3. Sensitivity analysis\u003c/h2\u003e\u003cp\u003eDecision to exclude patients not treated with CYP2D6 substrate drugs did not meaningfully change the magnitudes or the significance levels of the between-group changes in the treatment effectiveness and tolerability readouts. The sensitivity analysis is presented in full detail in the supplement (Table S3-S4). In addition, detailed results of the composite analysis of CYP2D6 and CYP2C19 metabolic capacities and their association with clinical outcomes are provided in Supplement (Table S5).\u003c/p\u003e\u003c/div\u003e"},{"header":"4. DISCUSSION","content":"\u003cp\u003eThe results indicate that slower \u003cem\u003eCYP2D6\u003c/em\u003e metabolism in this cohort of hospitalized patients suffering from MDD contributed to worse antidepressant treatment outcomes compared with normal \u003cem\u003eCYP2D6\u003c/em\u003e metabolizers. Worse effectiveness was observed in assessment by both clinician-rated (HAMD, CGI-I, CGI-S) and patient-rated (BDI-IA) psychometry assessment tools, while worse tolerability was observed in both TSES scores and CGI-E effectiveness/tolerability ratios. These results are concordant with previously published reports indicating worse effectiveness [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e]\u003c/p\u003e\u003cp\u003eand tolerability [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e] of antidepressant treatment in patients with genetically-encoded lower \u003cem\u003eCYP2D6\u003c/em\u003e enzymatic capacity. However, these results are in contrast with other reports that failed to observe association between \u003cem\u003eCYP2D6\u003c/em\u003e genotype and antidepressant treatment outcomes [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. Moreover, a supplementary composite analysis incorporating both \u003cem\u003eCYP2D6\u003c/em\u003e and \u003cem\u003eCYP2C19\u003c/em\u003e genotypes demonstrated that patients with reduced function of both enzymes exhibited the poorest treatment outcomes and the highest overall burden of adverse drug reactions.\u003c/p\u003e\u003cp\u003eThe obtained results advocate the usefulness of preemptive \u003cem\u003eCYP2D6\u003c/em\u003e and \u003cem\u003eCYP2C19\u003c/em\u003e genotyping because they indicate that knowing whether a patient is PM or IM may be useful for clinicians to predict outcomes and to adequately select drugs, dosage, and treatment strategies to minimize the risk of treatment failure. Indeed, well replicated results indicate that PMs are at increased risk of in tolerable adverse drug reactions even under standard dosing, which often leads to drug discontinuation before the benefits can be achieved [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. Consequently, dose adjustments or alternative medications in \u003cem\u003eCYP2D6\u003c/em\u003e PMs are recommended across relevant clinical guidelines for numerous antidepressant drugs [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e, \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e]. However, most of the guidelines focus only on PMs and overlook the significance of IMs, despite the evident differences in antidepressant blood levels between IMs and NMs [\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e]. While the clinical significance of being an IM is likely more subtle than being a PM, according to this and other studies [\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e], IMs also require different treatment and dosing strategies, especially when the drug has a narrow therapeutic window [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e]. An additional challenge to establish informative guidelines for IMs is the lack of a clear definition for the \u003cem\u003eCYP2D6\u003c/em\u003e IM phenotype, as different authors tend to use different categorization criteria, which is not the case for PMs, who are clearly defined by the presence of two non-functional alleles i.e. the complete absence of the active \u003cem\u003eCYP2D6\u003c/em\u003e enzyme [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e, \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eIn addition, one less likely, but plausible explanation for the observed results concerns the considerable presence of \u003cem\u003eCYP2D6\u003c/em\u003e in the brain, which means that local metabolism of antidepressants may be affected by \u003cem\u003eCYP2D6\u003c/em\u003e genotype [\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e]. Reduced \u003cem\u003eCYP2D6\u003c/em\u003e activity may be associated with altered intracerebral levels of antidepressants or their metabolites independent of blood levels, which may lead to altered therapeutic response or increased adverse drug reactions, potentially due to different effects on neurotransmitter homeostasis in the brain.\u003c/p\u003e\u003cp\u003eIn conclusion, the observed association between slower \u003cem\u003eCYP2D6\u003c/em\u003e and CYP2C19 metabolism and poor treatment outcomes suggests the potential benefits of using preemptive \u003cem\u003eCYP2C19/CYP2D6\u003c/em\u003e genotyping as part of the standard treatment routine. In theory, the ability to identify PMs and IMs prior to initiating treatment could provide clinicians with useful information to better individualize therapy, reduce adverse effects, and improve the successfulness of antidepressant therapy. These results are particularly useful when considering hospitalized patients suffering from depression, like the cohort analyzed here, where there is less margin for error and more at stake in case of suboptimal treatment. Importantly however, studies with prospective design, preemptive \u003cem\u003eCYP2D6\u003c/em\u003e and \u003cem\u003eCYP2C19\u003c/em\u003e genotyping, and examination of pharmacokinetic parameters are still needed to unequivocally demonstrate the usefulness of knowing \u003cem\u003eCYP2D6\u003c/em\u003e and \u003cem\u003eCYP2C19\u003c/em\u003e genotype in terms of improving antidepressant treatment successfulness.\u003c/p\u003e\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003e4.1. Limitations\u003c/h2\u003e\u003cp\u003eThe main limitation is lack of availability of pharmacokinetic data meaning that it was not possible to directly link \u003cem\u003eCYP2D6\u003c/em\u003e genotype to drug concentration in the blood. Next, due to the small number of PMs in the cohort, all statistical comparisons related to this category should be interpreted with caution and as preliminary findings. In addition, the patients were already receiving antidepressant therapy at the time of study enrollment, so it was not possible to take treatment duration or history into consideration, which may have influenced clinical outcomes. Furthermore, while concomitant use of multiple antidepressants reflects the usual situation in clinical settings, it further complicates the interpretation of results due the interference between \u003cem\u003eCYP2D6\u003c/em\u003e gene\u0026ndash;drug and drug-drug interactions. Finally, numerous factors limit the generalizability of the results obtained to general population because: (\u003cb\u003e1\u003c/b\u003e) the cohort did not include UMs, (\u003cb\u003e2\u003c/b\u003e) the cohort consisted primarily of military personnel and consequently the sample was predominantly male which does not represent the general population, in which there is usually higher incidence of depression in women among depressed patients, (\u003cb\u003e3\u003c/b\u003e) all patients had relatively severe depression that required hospitalization, (\u003cb\u003e4\u003c/b\u003e) the cohort included only Caucasian participants.\u003c/p\u003e\u003c/div\u003e"},{"header":"Declarations","content":"\u003ch2\u003eFUNDING\u003c/h2\u003e\u003cp\u003eFunding source had no role in study design; in the collection, analysis, and interpretation of data; in the writing of the report; and in the decision to submit the article for publication.\u003c/p\u003e\u003ch2\u003eCOMPETING INTERESTS\u003c/h2\u003e\u003cp\u003eMarin Jukić is a cofounder and executive director of TDM health. All other authors declare no competing interest.\u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e\u003cp\u003e for this study was provided by the 6066800/PsyCise from the Science Fund of the Republic of Serbia PROMIS program to the corresponding author Dr Jukić and by the MFVMA/05/20\u0026ndash;22 grant from the University of Defense, Belgrade, Serbia to Zvezdana Stojanović. The authors would like to thank the clinical staff of the Military Medical Academy for their assistance with sample collection and the patients who participated in the study.\u003c/p\u003e\u003ch2\u003eAUTHOR CONTRIBUTIONS\u003c/h2\u003e\u003cp\u003eAleksandra Petković Ćurčin: Methodology, Conceptualization, Investigation, Writing \u0026ndash; review \u0026amp; editing, Project administration. Aleksandra Jeremić: Writing \u0026ndash; original draft, Writing \u0026ndash; review \u0026amp; editing, Visualization. Danilo Joković: Methodology, Resources, Investigation, Data curation, Writing \u0026ndash; review \u0026amp; editing. Danilo Joković: Methodology, Investigation Gordana Šupić: Methodology, Investigation, Writing \u0026ndash; review \u0026amp; editing. Filip Milosavljević: Writing \u0026ndash; review \u0026amp; editing. Zvezdana Stojanović: Methodology, Resources, Investigation, Writing\u0026ndash; review \u0026amp; editing, Funding acquisition. Marin M. Jukić: Conceptualization, Resources, Writing \u0026ndash; review \u0026amp; editing, Funding acquisition.\u003c/p\u003e\u003ch2\u003eDATA AVAILABILITY\u003c/h2\u003e\u003cp\u003eThe datasets generated during and/or analysed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col start=\"1\" type=\"1\"\u003e\n\u003cli\u003eVos T, Lim SS, Abbafati C, Abbas KM, Abbasi M, Abbasifard M et al. 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Impact of pharmacogenomics on clinical outcomes in major depressive disorder in the GUIDED trial: A large, patient- and rater-blinded, randomized, controlled study. Journal of Psychiatric Research 2019; 111: 59\u0026ndash;67.\u003c/li\u003e\n\u003cli\u003eArnone D, Omar O, Arora T, \u0026Ouml;stlundh L, Ramaraj R, Javaid S et al. Effectiveness of pharmacogenomic tests including CYP2D6 and CYP2C19 genomic variants for guiding the treatment of depressive disorders: Systematic review and meta-analysis of randomised controlled trials. Neuroscience \u0026amp; Biobehavioral Reviews 2023; 144: 104965.\u003c/li\u003e\n\u003cli\u003eBrown LC, Stanton JD, Bharthi K, Maruf AA, M\u0026uuml;ller DJ, Bousman CA. Pharmacogenomic Testing and Depressive Symptom Remission: A Systematic Review and Meta‐Analysis of Prospective, Controlled Clinical Trials. Clin Pharma and Therapeutics 2022; 112: 1303\u0026ndash;1317.\u003c/li\u003e\n\u003cli\u003eBunka M, Wong G, Kim D, Edwards L, Austin J, Doyle-Waters MM et al. Evaluating treatment outcomes in pharmacogenomic-guided care for major depression: A rapid review and meta-analysis. Psychiatry Research 2023; 321: 115102.\u003c/li\u003e\n\u003cli\u003eMilosavljević F, Molden ProfE, Ingelman-Sundberg ProfM, Jukić AssocProfMM. Current level of evidence for improvement of antidepressant efficacy and tolerability by pharmacogenomic-guided treatment: A Systematic review and meta-analysis of randomized controlled clinical trials. European Neuropsychopharmacology 2024; 81: 43\u0026ndash;52.\u003c/li\u003e\n\u003cli\u003eWang X, Wang C, Zhang Y, An Z. Effect of pharmacogenomics testing guiding on clinical outcomes in major depressive disorder: a systematic review and meta-analysis of RCT. 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Clinical Impact of Functional CYP2C19 and CYP2D6 Gene Variants on Treatment with Antidepressants in Young People with Depression: A Danish Cohort Study. Pharmaceuticals 2022; 15: 870.\u003c/li\u003e\n\u003cli\u003eGex-Fabry M, Eap CB, Oneda B, Gervasoni N, Aubry J-M, Bondolfi G et al. CYP2D6 and ABCB1 Genetic Variability: Influence on Paroxetine Plasma Level and Therapeutic Response. Therapeutic Drug Monitoring 2008; 30: 474\u0026ndash;482.\u003c/li\u003e\n\u003cli\u003eMurphy GM, Kremer C, Rodrigues HE, Schatzberg AF. Pharmacogenetics of Antidepressant Medication Intolerance. AJP 2003; 160: 1830\u0026ndash;1835.\u003c/li\u003e\n\u003cli\u003ePeters EJ, Slager SL, Kraft JB, Jenkins GD, Reinalda MS, McGrath PJ et al. Pharmacokinetic Genes Do Not Influence Response or Tolerance to Citalopram in the STAR*D Sample. PLoS ONE 2008; 3: e1872.\u003c/li\u003e\n\u003cli\u003eRoberts RL, Mulder RT, Joyce PR, Luty SE, Kennedy MA. No evidence of increased adverse drug reactions in cytochrome P450 CYP2D6 poor metabolizers treated with fluoxetine or nortriptyline. Human Psychopharmacology 2004; 19: 17\u0026ndash;23.\u003c/li\u003e\n\u003cli\u003eConrado DJ, Rogers HL, Zineh I, Pacanowski MA. Consistency of Drug\u0026ndash;Drug and Gene\u0026ndash;Drug Interaction Information in US FDA-Approved Drug Labels. Pharmacogenomics 2013; 14: 215\u0026ndash;223.\u003c/li\u003e\n\u003cli\u003eHicks J, Sangkuhl K, Swen J, Ellingrod V, M\u0026uuml;ller D, Shimoda K et al. Clinical pharmacogenetics implementation consortium guideline (CPIC) for CYP2D6 and CYP2C19 genotypes and dosing of tricyclic antidepressants: 2016 update. Clin Pharma and Therapeutics 2017; 102: 37\u0026ndash;44.\u003c/li\u003e\n\u003cli\u003eSwen JJ, Nijenhuis M, De Boer A, Grandia L, Maitland-van Der Zee AH, Mulder H et al. Pharmacogenetics: From Bench to Byte\u0026mdash; An Update of Guidelines. Clin Pharmacol Ther 2011; 89: 662\u0026ndash;673.\u003c/li\u003e\n\u003cli\u003eSheehan DV, Lecrubier Y, Sheehan KH, Amorim P, Janavs J, Weiller E et al. The Mini-International Neuropsychiatric Interview (M.I.N.I.): the development and validation of a structured diagnostic psychiatric interview for DSM-IV and ICD-10. J Clin Psychiatry 1998; 59 Suppl 20: 22-33;quiz 34-57.\u003c/li\u003e\n\u003cli\u003eHayasaka Y, Purgato M, Magni LR, Ogawa Y, Takeshima N, Cipriani A et al. Dose equivalents of antidepressants: Evidence-based recommendations from randomized controlled trials. Journal of Affective Disorders 2015; 180: 179\u0026ndash;184.\u003c/li\u003e\n\u003cli\u003eKane M. CYP2D6 Overview: Allele and Phenotype Frequencies. In: Medical Genetics Summaries [Internet]. National Center for Biotechnology Information (US), 2025https://www.ncbi.nlm.nih.gov/books/NBK574601/ (accessed 23 June2025).\u003c/li\u003e\n\u003cli\u003eHamilton M. A RATING SCALE FOR DEPRESSION. Journal of Neurology, Neurosurgery \u0026amp; Psychiatry 1960; 23: 56\u0026ndash;62.\u003c/li\u003e\n\u003cli\u003eGuy W. ECDEU Assessment Manual for Psychopharmacology: Revised Edition. Rockville, MD: US Department of Health, Education, and Welfare, Public Health Service, Alcohol, Drug Abuse, and Mental Health Administration, National Institute of Mental Health, Psychopharmacology Research Branch, Division of Extramural Research Programs; 1976.\u003c/li\u003e\n\u003cli\u003eBeck AT, Steer RA, Ball R, Ranieri WF. Comparison of Beck Depression Inventories-IA and-II in Psychiatric Outpatients. Journal of Personality Assessment 1996; 67: 588\u0026ndash;597.\u003c/li\u003e\n\u003cli\u003eVanderkooy J, Ken Nedy SNH, Bagby RMC. Antidepressant Side Effects in Depression Patients Treated in a Naturalistic Setting: A Study of Bupropion, Moclobemide, Paroxetine, Sertraline, and Venlafaxine. 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Depress Anxiety 2012; 29: 340\u0026ndash;354.\u003c/li\u003e\n\u003cli\u003eJain FA, Hunter AM, Brooks JO, Leuchter AF. PREDICTIVE SOCIOECONOMIC AND CLINICAL PROFILES OF ANTIDEPRESSANT RESPONSE AND REMISSION: Research Article: Profiles of Antidepressant Treatment Outcome. Depress Anxiety 2013; 30: 624\u0026ndash;630.\u003c/li\u003e\n\u003cli\u003eVon Elm E, Altman DG, Egger M, Pocock SJ, G\u0026oslash;tzsche PC, Vandenbroucke JP. The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement: guidelines for reporting observational studies. Journal of Clinical Epidemiology 2008; 61: 344\u0026ndash;349.\u003c/li\u003e\n\u003cli\u003eMaciaszek J, Pawłowski T, Hadryś T, Machowska M, Wiela-Hojeńska A, Misiak B. The Impact of the CYP2D6 and CYP1A2 Gene Polymorphisms on Response to Duloxetine in Patients with Major Depression. IJMS 2023; 24: 13459.\u003c/li\u003e\n\u003cli\u003eBousman CA, Stevenson JM, Ramsey LB, Sangkuhl K, Hicks JK, Strawn JR et al. 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Impact of CYP2D6 on Venlafaxine Metabolism in Trinidadian Patients with Major Depressive Disorder. Pharmacogenomics 2018; 19: 197\u0026ndash;212.\u003c/li\u003e\n\u003cli\u003eCaudle KE, Sangkuhl K, Whirl‐Carrillo M, Swen JJ, Haidar CE, Klein TE et al. Standardizing CYP 2D6 Genotype to Phenotype Translation: Consensus Recommendations from the Clinical Pharmacogenetics Implementation Consortium and Dutch Pharmacogenetics Working Group. Clinical Translational Sci 2020; 13: 116\u0026ndash;124.\u003c/li\u003e\n\u003cli\u003eJukić MM, Smith RL, Molden E, Ingelman‐Sundberg M. Evaluation of the CYP2D6 Haplotype Activity Scores Based on Metabolic Ratios of 4,700 Patients Treated With Three Different CYP2D6 Substrates. Clin Pharma and Therapeutics 2021; 110: 750\u0026ndash;758.\u003c/li\u003e\n\u003cli\u003eStingl JC, Brockm\u0026ouml;ller J, Viviani R. Genetic variability of drug-metabolizing enzymes: the dual impact on psychiatric therapy and regulation of brain function. Mol Psychiatry 2013; 18: 273\u0026ndash;287.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"the-pharmacogenomics-journal","isNatureJournal":false,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"tpj","sideBox":"Learn more about [The Pharmacogenomics Journal](http://www.nature.com/tpj/)","snPcode":"41397","submissionUrl":"https://mts-tpj.nature.com/cgi-bin/main.plex","title":"The Pharmacogenomics Journal","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"Nature AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-7234296/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7234296/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eCytochrome P450 2D6 (CYP2D6) is a polymorphic enzyme that affects antidepressant metabolism. This retrospective hospital-based cohort study investigated the association between \u003cem\u003eCYP2D6\u003c/em\u003e genotype and treatment outcomes in 99 hospitalized patients with major depressive disorder (MDD) in Belgrade, Serbia. Patients were classified as poor (PM, n\u0026thinsp;=\u0026thinsp;5), intermediate (IM, n\u0026thinsp;=\u0026thinsp;30), or normal metabolizers (NM, n\u0026thinsp;=\u0026thinsp;64). Effectiveness and tolerability were assessed from admission to discharge (approximately four weeks). Effectiveness was measured using the reduction in Hamilton Depression Rating Scale (HAM-D) score, while tolerability was measured using the Toronto Side Effects Scale (TSES). Compared with NMs, HAM-D score reductions were 5.1 and 9.5 points lower, while TSES scores were 0.8 and 2.3 points higher in IMs and PMs, respectively, with higher prevalence of CNS and gastrointestinal side effects among IMs and PMs. Reduced CYP2D6 activity was associated with poorer antidepressant treatment outcomes supporting the potential clinical utility of \u003cem\u003eCYP2D6\u003c/em\u003e genotyping for treatment individualization.\u003c/p\u003e","manuscriptTitle":"Association between CYP2D6 genotype and treatment effectiveness and safety in 99 hospitalized patients with major depressive disorder - a retrospective cohort study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-10-03 16:23:21","doi":"10.21203/rs.3.rs-7234296/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"revise","date":"2025-10-06T15:02:45+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"This content is not available.","date":"2025-10-05T12:36:42+00:00","index":1,"fulltext":"This content is not available."},{"type":"editorInvitedReview","content":"This content is not available.","date":"2025-10-03T15:58:54+00:00","index":2,"fulltext":"This content is not available."},{"type":"reviewerAgreed","content":"This content is not available.","date":"2025-09-22T14:29:06+00:00","index":2,"fulltext":"This content is not available."},{"type":"reviewerAgreed","content":"This content is not available.","date":"2025-09-22T04:38:51+00:00","index":1,"fulltext":"This content is not available."},{"type":"reviewersInvited","content":"","date":"2025-09-22T04:24:48+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-07-29T10:59:17+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-07-28T13:14:12+00:00","index":"","fulltext":""},{"type":"submitted","content":"The Pharmacogenomics Journal","date":"2025-07-28T13:14:11+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"the-pharmacogenomics-journal","isNatureJournal":false,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"tpj","sideBox":"Learn more about [The Pharmacogenomics Journal](http://www.nature.com/tpj/)","snPcode":"41397","submissionUrl":"https://mts-tpj.nature.com/cgi-bin/main.plex","title":"The Pharmacogenomics Journal","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"Nature AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"c25bc24b-1702-4aa5-aebd-7c2fbf8a9d4f","owner":[],"postedDate":"October 3rd, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[{"id":55086555,"name":"Health sciences/Diseases/Psychiatric disorders/Depression"},{"id":55086556,"name":"Health sciences/Risk factors"},{"id":55086557,"name":"Biological sciences/Genetics/Genotype"}],"tags":[],"updatedAt":"2026-05-13T13:50:16+00:00","versionOfRecord":[],"versionCreatedAt":"2025-10-03 16:23:21","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7234296","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7234296","identity":"rs-7234296","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}