Analysis of the current situation of pharmacogenomics in terms of educational and healthcare needs in Egypt and Lebanon.

Pharmacogenomics (PGx) is a practice that investigates the link between genetic differences and drug response in patients. This can improve treatment effectiveness and reduce harmful side effects. However, has yet to be adequately realized in developing nations. Three surveys were conducted between November 2022 to March 2023 in Egypt and Lebanon. The first survey assessed availability of PGx testing in different healthcare facilities; the second one assessed knowledge, interest and attitude toward learning about PGx among pharmacists and physicians; and the third one assessed interest in providing PGx education at academic levels. In Egypt, a few of the surveyed healthcare facilities are conducting some form of pharmacogenetic testing. In Lebanon, very few germline pharmacogenomic tests are offered in Greater Beirut's leading hospitals, and no other testing was recorded. PGx education attracts considerable interest, with 34.3% of pharmacists very interested and 48.8% interested. Similarly, 24.8% of total physicians were very interested while 44.8% were interested. Academic professionals in the surveyed institutions in both countries agreed on the need for educational programs in PGx and 78.2% agreed that there were good opportunities for implementing PGx testing. These findings clearly indicate the need to develop and implement educational programs in PGx in the Middle-East.

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Advancing pharmacogenomic research in US Hmong populations: prevalence of key single nucleotide variations in California Hmong.

Introduction: In collaboration with the Minnesota Hmong community, we have previously discovered significant differences in allele frequencies for key Single Nucleotide Variations (SNVs) within Very Important Pharmacogenes (VIPs) between Hmong and East Asians. Recognizing the potential clinical implications of these observed differences, we sought to validate these observations in a Hmong cohort residing in California, the state with the largest Hmong population in the US. Robust validation of these differences would affect motivation for clinicians treating individuals who identify as Hmong to consider pharmacogenomic (PGx) testing as a means to improve clinical decision making when using therapeutic agents in this unique population. Method: Guided by California Hmong community leaders and utilizing the basic approach of community-based participatory research, demographic, clinical information and a buccal swab was obtained from Hmong adults residing in California. A commercial PGx testing panel was performed on these samples and specific allele frequencies of interest were compared between California and Minnesota Hmong. Allele frequency differences between California Hmong, East Asians and Europeans, were also compared. Return-of-PGx-results and presentations of group data were made to members of the Hmong along with PGx educational sessions to help interpret the observations. Results: In 118 California Hmong who completed the study, the allele frequencies for SNV's were similar to previous Minnesota Hmong results. Furthermore, out of the 18 SNVs that were not previously reported in Hmong, allele frequencies were statistically different in 38% (7/18) of SNVs comparing California Hmong to East Asians, and in 77.8% (14/18) SNVs comparing California Hmong to Europeans. Conclusion: These results validate the original study's findings that Hmong people living in different US locations have similar allele frequencies for key PGx genes. Further, for many of these PGx genes, their allele frequencies are significantly different compared to either East Asians or Europeans. Clinicians should consider these important differences when prescribing medications for people who identify as Hmong.

Drug Metabolizing Enzymes: An Exclusive Guide into Latest Research in Pharmaco-genetic Dynamics in Arab Countries.

Drug metabolizing enzymes play a crucial role in the pharmacokinetics and pharmacodynamics of therapeutic drugs, influencing their efficacy and safety. This review explores the impact of genetic polymorphisms in drug-metabolizing genes on drug response within Arab populations. We examine the genetic diversity specific to Arab countries, focusing on the variations in key drug-metabolizing enzymes such as CYP450, GST, and UGT families. The review highlights recent research on polymorphisms in these genes and their implications for drug metabolism, including variations in allele frequencies and their effects on therapeutic outcomes. Additionally, the paper discusses how these genetic variations contribute to the variability in drug response and adverse drug reactions among individuals in Arab populations. By synthesizing current findings, this review aims to provide a comprehensive understanding of the pharmacogenetic landscape in Arab countries and offer insights into personalized medicine approaches tailored to genetic profiles. The findings underscore the importance of incorporating pharmacogenetic data into clinical practice to enhance drug efficacy and minimize adverse effects, ultimately paving the way for more effective and individualized treatment strategies in the region.

Effects of genetic and clinical factors on thiopurine drugs pharmacokinetics in Tunisian patients.

Aim: Thiopurine drugs are used in the treatment of various diseases including inflammatory bowel disease. Thiopurine-S-methyltransferase (TPMT) and inosine triphosphate pyrophosphatase (ITPA) are the crucial enzymes involved in thiopurines metabolism. The present study aims to investigate in Tunisian patients, the influence of genetic and nongenetic factors on thiopurine drugs pharmacokinetics.Experimental approach: We have included patients having received thiopurine drugs and have undergone 6-thioguanine nucleotides (6-TGN) concentration monitoring. The identification of TPMT and ITPA polymorphisms was performed using the polymerase chain reaction-restriction fragment length polymorphism method. The impact of both genetic and nongenetic factors on the variability of the 6-TGN C/D ratio was analyzed through a stepwise multiple regression model.Key results: One hundred and twenty-three patients were included in the study. For TPMT, the most frequent variant allele was TPMT*3B (3.3%). For ITPA, the predominant polymorphism was the c.IVS2 + 21A> C (7%). We have demonstrated that only gender, the TPMT*3A and TPMT*3C alleles are significantly involved on the variability of thiopurines pharmacokinetics.Conclusion: Our study is the first to evaluate, in African patients, the impact of both genetic and nongenetic factors on the thiopurine drugs pharmacokinetics. Considering the narrow therapeutic range of these drugs, TPMT genotyping combined with 6-TGN blood concentration monitoring may enhance their efficacy and safety.

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Identifying genetic variants associated with side effects of antidepressant treatment: A systematic review.

Major Depressive Disorder (MDD) is one of the most prevalent neurobiological disorders globally. Antidepressant medications are the first-line treatment for managing symptoms. However, over time, pharmacotherapy has been linked to several challenges, primarily due to the wide array of side effects that often reduce patient adherence to treatment. The literature suggests that these side effects may be influenced by polymorphisms in genes related to the pharmacokinetics and pharmacodynamics of antidepressants. Thus, this systematic review aimed to identify studies that investigated the association between genetic variants and side effects resulting from antidepressant treatment in individuals with MDD. Original articles indexed in the electronic databases Cochrane Library, EMBASE, MEDLINE via PubMed, and Scopus were identified. A total of 55 studies were included in the review, and data regarding the outcomes of interest were extracted. Due to the exploratory nature of the review, a narrative/descriptive synthesis of the results was performed. The risk of bias was evaluated using the Joanna Briggs Institute's tools, tailored to the design of each study. Polymorphisms in 35 genes were statistically associated with the development of side effects. A subsequent Protein-Protein Interaction Network analysis helped elucidate the key biological pathways involved in antidepressant side effects, with a view toward exploring the potential application of pharmacogenetic markers in clinical practice.

Pharmacogenetic analysis of structural variation in the 1000 genomes project using whole genome sequences.

While significant strides have been made in understanding pharmacogenetics (PGx) and gene-drug interactions, there remains limited characterization of population-level PGx variation. This study aims to comprehensively profile global star alleles (haplotype patterns) and phenotype frequencies in 58 pharmacogenes associated with drug absorption, distribution, metabolism, and excretion. PyPGx, a star-allele calling tool, was employed to identify star alleles within high-coverage whole genome sequencing (WGS) data from the 1000 Genomes Project (N = 2504; 26 global populations). This process involved detecting structural variants (SVs), such as gene deletions, duplications, hybrids, as well as single nucleotide variants and insertion-deletion variants. The majority of our PyPGx calls for star alleles and phenotype frequencies aligned with the Pharmacogenomics Knowledge Base, although notable population-specific frequencies differed at least twofold. Validation efforts confirmed known SVs while uncovering several novel SVs currently undefined as star alleles. Additionally, we identified 210 small nucleotide variants associated with severe functional consequences that are not defined as star alleles. The study serves as a valuable resource, providing updated population-level star allele and phenotype frequencies while incorporating SVs. It also highlights the burgeoning potential of cost-effective WGS for PGx genotyping, offering invaluable insights to improve tailored drug therapies across diverse populations.

Innovation in cancer pharmacotherapy through integrative consideration of germline and tumor genomes.

Precision cancer medicine is widely established, and numerous molecularly targeted drugs for various tumor entities are approved or in development. Personalized pharmacotherapy in oncology has so far been based primarily on tumor characteristics, e.g., somatic mutations. However, the response to drug treatment also depends on pharmacological processes summarized under the term ADME (absorption, distribution, metabolism, and excretion). Variations in ADME genes have been the subject of intensive research for more than five decades, considering individual patients' genetic makeup, referred to as pharmacogenomics (PGx). The combined impact of a patient's tumor and germline genome is only partially understood and often not adequately considered in cancer therapy. This may be attributed, in part, to the lack of methods for combined analysis of both data layers. Optimized personalized cancer therapies should, therefore, aim to integrate molecular information about the tumor and the germline, taking into account existing PGx guidelines for drug therapy. Moreover, such strategies should provide the opportunity to consider genetic variants of previously unknown functional significance. Bioinformatic analysis methods and corresponding algorithms for data interpretation need to be developed to consider PGx data in interdisciplinary molecular tumor boards, where cancer patients are discussed to provide evidence-based recommendations for clinical management based on individual tumor profiles. Significance Statement The era of personalized oncology has seen the emergence of drugs tailored to genetic variants associated with cancer biology. However, full potential of targeted therapy remains untapped due to the predominant focus on acquired tumor-specific alterations. Optimized cancer care must integrate tumor and patient genomes, guided by pharmacogenomic principles. An essential prerequisite for realizing truly personalized drug treatment of cancer patients is the development of bioinformatic tools for comprehensive analysis of all data layers generated in modern precision oncology programs.

Serotonin transporter 5-HTTLPR polymorphism and escitalopram treatment response in patients with major depressive disorder.

BACKGROUND: There is no doubt that genetic factors have the potential to predict the therapeutic outcomes of antidepressants in patients with major depressive disorder (MDD). This study investigated the association between genetic variants involved in serotonin signaling and brain-derived neurotrophic factor (BDNF) with the response to escitalopram treatment in patients with MDD. We focused on examining the influence of 5-HTTLPR (ins/del), HTR2A rs9316233, BDNF rs962369, CYP2C19 and CYP2D6 on the clinical response to escitalopram. METHODS: The patients were recruited from outpatient psychiatric clinics in Kosice between 2020 and 2022. Patients received escitalopram for 12 weeks at a fixed dose of 10 mg daily. Clinical assessment was done at baseline and after 4, 8, and 12 weeks using the 21-item Hamilton Depression Rating Scale (HAMD-21). RESULTS: At the end of week 12, 57 (65%) patients were defined as responders to escitalopram treatment, while 31 (35%) patients were non-responders. Genotyping revealed that carriers of the short allele (S) of 5-HTTLPR exhibit a significantly lower therapeutic response to escitalopram measured by HAMD-21 than the long allele (L) carriers (p = 0.01). Adjusting for CYP2C19 and CYP2D6 metabolizer genotypes did not modify the observed relationship between 5-HTTLPR and treatment response. No significant associations were found for HTR2A rs9316233 or BDNF rs962369 variants and the treatment response. CONCLUSIONS: These findings underscore the utility of 5-HTTLPR genotyping in guiding escitalopram therapy for MDD patients. Further research with larger cohorts is warranted to validate these results and elucidate additional genetic determinants of antidepressant efficacy.

Barriers and facilitators of the use of clinical informatics resources to facilitate pharmacogenomic implementation in resource-limited settings.

Objective: Understand perceived barriers to and facilitators of using clinical informatics applications for pharmacogenomic (PGx) implementation in resource-limited settings. Materials and Methods: We conducted a qualitative research study using a semi-structured interview guide informed by the Consolidated Framework for Implementation Research (CFIR). Interview questions assessed CFIR contextual determinants related to: electronic health record (EHR) infrastructure; clinical informatics personnel and resources; EHR integration of PGx test results; PGx clinical decision support (CDS) tools; institutional resources; and partner receptivity. Transcripts were coded and analyzed to identify themes. Results: We interviewed 24 clinical informaticists and executive leaders working in rural or underserved health care settings in Montana (n = 15) and Colorado (n = 9) and identified three major themes: (1) EHR infrastructure limitations, (2) insufficient supporting resources, and (3) unique contextual considerations for resource-limited settings. EHR infrastructure limitations included limited agency related to EHR build and interoperability concerns. Theme 1 highlighted challenges associated with integrating structured data into the EHR and inadequate vendor support. Theme 2 included limited familiarity with PGx across the care team, cost concerns, and allocation of non-financial resources. Theme 3 highlighted perceptions about the clinical utility of PGx within rural and underrepresented populations. Potential facilitators, such as being able to act nimbly, were found to coexist among the reported barriers. Discussion and Conclusion: Our results provide insight into the clinical informatics infrastructure in resource-limited settings and identify unique considerations for clinical informatics-facilitated PGx implementation. Future efforts in these settings should consider innovative partnerships and strategies to leverage facilitators and minimize barriers associated with integrating PGx CDS applications.

Dopamine Transporter and CYP2D6 Gene Relationships with Attention-Deficit/Hyperactivity Disorder Treatment Response in the Methylphenidate and Atomoxetine Crossover Study.

Background: Few biological or clinical predictors guide medication selection and/or dosing for attention-deficit/hyperactivity disorder (ADHD). Accumulating data suggest that genetic factors may contribute to clinically relevant pharmacodynamic (e.g., dopamine transporter-SLC6A3 also commonly known as DAT1) or pharmacokinetic (e.g., the drug metabolizing enzyme Cytochrome P450 2D6 CYP2D6) effects of methylphenidate (stimulant) and atomoxetine (non-stimulant), which are commonly prescribed medications. This is the first study of youth with ADHD exposed to both medications examining the clinical relevance of genetic variation on treatment response. Methods: Genetic variations in DAT1 and CYP2D6 were examined to determine how they modified time relationships with changes in ADHD symptoms over a 4-week period in 199 youth participating in a double-blind crossover study following a stepped titration dose optimization protocol. Results: Our results identified trends in the modification effect from CYP2D6 phenotype and the time-response relationship between ADHD total symptoms for both medications (atomoxetine [ATX]: p = 0.058, Methylphenidate [MPH]: p = 0.044). There was also a trend for the DAT1 3' untranslated region (UTR) variable number of tandem repeat (VNTR) genotype to modify dose relationships with ADHD-RS total scores for atomoxetine (p = 0.029). Participants with DAT1 9/10 repeat genotypes had a more rapid dose-response to ATX compared to 10/10, while those with 9/9 genotypes did not respond as doses were increased. Regardless of genotype, ADHD symptoms and doses were similar across CYP2D6 metabolizer groups after 4 weeks of treatment. Conclusions: Most children with ADHD who were CYP2D6 normal metabolizers or had DAT1 10/10 or 9/10 genotypes responded well to both medications. While we observed some statistically significant effects of CYP2D6 and DAT1 with treatment response over time, our data indicate that genotyping for clinical purposes may have limited utility to guide treatment decisions for ATX or MPH because both medications were generally effective in the studied cohort after 3 weeks of titration to higher doses. The potential DAT1 association with ATX treatment is a novel finding, consistent with prior reports suggesting an association of the DAT1 in 9/9 genotypes with lower responsive rates to treatment at low and moderate doses.

Population pharmacokinetics of tacrolimus whole blood and peripheral blood mononuclear cell concentrations in stable kidney-transplanted patients.

AIM: Therapeutic drug monitoring of tacrolimus based on whole blood drug concentrations is routinely performed. The concentration of tacrolimus in peripheral blood mononuclear cells (PMBCs) is likely to better reflect drug exposure at the treatment target site. We aimed to describe the relationship between tacrolimus whole blood and PBMC concentrations, and the influence of patient characteristics on this relationship by developing a population pharmacokinetic model. METHODS: We prospectively enrolled 63 stable adult kidney-transplanted patients and collected dense (12-h, n = 18) or sparse (4-h, n = 45) pharmacokinetic profiles of tacrolimus. PBMCs were isolated from whole blood (Ficoll density gradient centrifugation), and drug concentrations in whole blood and PBMCs were analysed using liquid chromatography-mass spectrometry. Patient genotype (CYP3A4/5, ABCB1, NR1I2) was assessed with PCR. Population pharmacokinetic modelling and statistical evaluation was performed using NONMEM. RESULTS: Tacrolimus whole blood concentrations were well described using a two-compartment pharmacokinetic model with a lag-time and first-order absorption and elimination. Tacrolimus PBMC concentrations were best estimated from whole blood concentrations with the use of a scaling factor, the ratio of whole blood to PBMC concentrations (RC:PBMC), which was the extent of tacrolimus distribution into PBMC. CYP3A5*1 non-expressors and NR1I2-25 385T allele expressors demonstrated higher RC:PBMC ratios of 42.4% and 60.7%, respectively. CONCLUSION: Tacrolimus PBMC concentration could not be accurately predicted from whole blood concentrations and covariates because of significant residual unexplained variability in the distribution of tacrolimus into PBMCs and may need to be measured directly if required for future studies.

An integrated sampling strategy for therapeutic mycophenolic acid monitoring in lung transplant recipients.

BACKGROUND: Mycophenolic Acid (MPA) is the most used anti-proliferative in lung transplantation, but its pharmacokinetic (PK) variability has precluded therapeutic drug monitoring. Both genetic and clinical factors have been implicated in MPA variability. This study aimed to integrate genetic and clinical factors with PK measurements to quantify MPA exposure. METHODS: We performed 12-hour pharmacokinetic analysis on 60 adult lung transplant recipients maintained on MPA for immunosuppression. We genotyped a SLCO1B3 polymorphisms previously associated MPA metabolism and collected relevant clinical data. We calculated area under the curve (AUC0-12) and performed univariate linear regression analysis to evaluate its association with genetic, clinical, and pharmacokinetic variables. We performed lasso regression analysis to create final AUC estimation tools. RESULTS: PK-only measurements obtained 2, 3, and 8 hours after MPA administration (C2, C3, and C8) were strongly associated with MPA AUC0-12 (R267%, 67% and 68% respectively). Clinical and genetic factors associated with MPA AUC0-12 included the MPA dose (p = 0.001), transplant diagnosis (p = 0.015), SLCO1B3 genotype (p = 0.049), and body surface area (p = 0.050). The best integrated single-sampling strategy included C2 and achieved an R2 value of 80%. The best integrated limited-sampling strategy included C0, C0.25, and C2 and achieved an R2 value of 90%. CONCLUSIONS: An integrated limited sampling strategy (LSS) for MPA allows increased accuracy in prediction of MPA AUC0-12 compared to PK-only modeling. Validation of this model will allow for clinically feasible MPA therapeutic drug monitoring and help advance precision management of MPA.

An exploratory analysis of associations of genetic variation with the efficacy of tocilizumab in severe COVID-19 patients. A pharmacogenetic study based on next-generation sequencing.

Background: In the context of the cytokine storm the takes place in severe COVID-19 patients, the Interleukin 6 (IL6) pathway emerges as one of the key pathways involved in the pathogenesis of this hyperinflammatory state. The strategy of blocking the inflammatory storm by targeting the IL6 is a promising therapy to mitigate mortality. The use of Tocilizumab was recommended by the World Health Organization (WHO) to treat severe COVID-19 patients. However, the efficacy of Tocilizumab is variable. We hypothesize that the genetic background could be behind the efficacy of Tocilizumab in terms of mortality. Methods: We performed a targeted-next generation sequencing of 287 genes, of which 264 belong to a community panel of ThermoFisher for the study of genetic causes of primary immunodeficiency disorders, and 23 additional genes mostly related to inflammation, not included in the original community panel. This panel was sequenced in an initial cohort of 425 COVID-19 patients, of which 232 were treated with Tocilizumab and standard therapy, and 193 with standard therapy only. Selected genetic variants were genotyped by single base extension in additional 245 patients (95 treated with Tocilizumab and 150 non-treated with Tocilizumab). Appropriate statistical analyses and internal validation, including logistic regression models, with the interaction between Tocilizumab and genetic variants, were applied to assess the impact of these genetic variants in the efficacy of Tocilizumab in terms of mortality. Results: Age (p < 0.001) and cardiovascular disease (p < 0.001) are risk factors for mortality in COVID-19 patients. The presence of GG and TT genotypes at IL10Rß (rs2834167) and IL1ß (rs1143633) genes significantly associates with a reduced risk of mortality in patients treated with Tocilizumab (OR = 0.111; 95%CI = 0.015-0.829; p = 0.010 and OR = 0.378; 95%CI = 0.154-0.924; p = 0.028 respectively). The presence of CC genotype at IL1RN (rs2234679) significantly associates with an increased risk of mortality, but only in patients not treated with Tocilizumab (OR = 3.200; 95%CI = 1.512-6.771; p = 0.002). Exhaustive internal validation using a bootstrap method (B = 500 replicates) validated the accuracy of the predictive models. Conclusion: We developed a series of predictive models based on three genotypes in genes with a strong implication in the etiopathogenesis of COVID-19 disease capable of predicting the risk of mortality in patients treated with Tocilizumab.

Association of SCN1A Polymorphisms rs3812718 and rs2298771 with Epilepsy.

Background/Objectives: Epilepsy is a brain disease with both environmental and genetic inputs. Ion channel dysfunction seems to be of great significance for abnormal neuronal behavior during epileptic seizures. Within neurons, the voltage-gated sodium channels are crucial proteins contributing to the initiation and propagation of action potentials. The voltage-gated sodium channel α subunit 1 (SCN1A) gene encodes for the α subunit of a voltage-gated ion channel. The aim of the study was to investigate the relation of two common SCN1A variants, i.e., rs3812718 and rs2298771, with distinct epileptic phenotypes in a South-Eastern European population. Methods: DNA was extracted from 214 unrelated participants with focal onset, focal to bilateral tonic-clonic, or generalized onset epileptic seizures and genotyped using real-time PCR (LightSNiP assays) followed by melting curve analysis. Statistical analysis of the results was performed using IBM SPSS Statistics software (version 29.0 for Windows). Results: Genotype frequency distribution analysis indicated an association for the A-allele-containing genotypes of both rs3812718 and rs2298771 polymorphisms of SCN1A with generalized onset seizures and focal to bilateral tonic-clonic seizures versus focal onset seizures. Conclusions: Consequently, the study provides evidence that supports a potential association of the investigated SCN1A polymorphisms with distinct seizure subtype susceptibility in South-Eastern Europeans.

Targeting Calcitriol Metabolism in Acute Vitamin D Toxicity-A Comprehensive Review and Clinical Insight.

High-dose vitamin D supplementation is common in the general population, but unsupervised high-dose supplementation in vitamin D-replete individuals poses a risk of severe toxicity. Susceptibility to vitamin D toxicity shows a significant inter-individual variability that may in part be explained by genetic predispositions (i.e., CYP24A1 polymorphism). The classic manifestation of vitamin D toxicity is hypercalcemia, which may be refractory to conventional therapy. Its causes include the endogenous overaction of 1α-hydroxylase, monogenic alterations affecting vitamin D metabolizing enzymes and exogenous vitamin D intoxication. In this manuscript, we include a literature review of potential pharmacological interventions targeting calcitriol metabolism to treat vitamin D intoxication and present a case of severe, exogenous vitamin D intoxication responding to systemic corticosteroids after the failure of conventional therapy. Systemic glucocorticoids alleviate acute hypercalcemia by inhibiting enteric calcium absorption and increasing the degradation of vitamin D metabolites but may cause adverse effects. Inhibitors of 1α-hydroxylase (keto/fluconazole) and inducers of CYP3A4 (rifampicin) may be considered steroid-sparing alternatives for the treatment of vitamin D intoxication.

Unidentified CYP2D6 genotype does not affect pharmacological treatment for patients with first episode psychosis.

BACKGROUND: Research on the pharmacogenetic influence of hepatic CYP450 enzyme 2D6 (CYP2D6) on metabolism of drugs for psychosis and associated outcome has been inconclusive. Some results suggest increased risk of adverse reactions in poor and intermediate metabolizers, while others find no relationship. However, retrospective designs may fail to account for the long-term pharmacological treatment of patients. Previous studies found that clinicians adapted risperidone dose successfully without knowledge of patient CYP2D6 phenotype. AIM: Here, we aimed to replicate the results of those studies in a Dutch cohort of patients with psychosis (N = 418) on pharmacological treatment. METHOD: We compared chlorpromazine-equivalent dose between CYP2D6 metabolizer phenotypes and investigated which factors were associated with dosage. This was repeated in two smaller subsets; patients prescribed pharmacogenetics-actionable drugs according to published guidelines, and risperidone-only as done previously. RESULTS: We found no relationship between chlorpromazine-equivalent dose and phenotype in any sample (complete sample: p = 0.3, actionable-subset: p = 0.82, risperidone-only: p = 0.34). Only clozapine dose was weakly associated with CYP2D6 phenotype (p = 0.03). CONCLUSION: Clinicians were thus not intuitively adapting dose to CYP2D6 activity in this sample, nor was CYP2D6 activity associated with prescribed dose. Although the previous studies could not be replicated, this study may provide support for existing and future pharmacogenetic research.

Addressing the Ethnicity Gap in Catechol O-Methyl Transferase Inhibitor Trials in Parkinson's Disease: A Review of Available Global Data.

Catechol-O-methyltransferase inhibitors (COMT-Is) have significantly improved the quality of life and symptom management for those at advanced stages of Parkinson's Disease (PD). Given that PD is one of the fastest-growing neurodegenerative diseases worldwide, there is a need to establish a clear framework for the systematic distribution of COMT-Is, considering inter-individual and intra-individual variations in patient response. One major barrier to this is the underrepresentation of ethnic minority participants in clinical trials investigating COMT-Is. To investigate this, we performed a narrative review. We searched PubMed for clinical trials investigating COMT-Is in patients with PD and examined the ethnic diversity of cohorts. A total of 63 articles were identified, with 34 trials found to match our inclusion criteria. Among the 34 trials meeting our inclusion criteria, only 8 reported participants' ethnic backgrounds. Our findings reveal a consistent underrepresentation of ethnic minority groups in trials investigating COMT-Is in PD cohorts-a trend that reflects broader concerns across clinical research. In this review, we explore potential reasons for the underrepresentation of ethnic minorities in clinical trials and propose strategies to address this issue.

An Investigational Study on the Role of CYP2D6, CYP3A4 and UGTs Genetic Variation on Fesoterodine Pharmacokinetics in Young Healthy Volunteers.

Introduction: Fesoterodine is one of the most widely used antimuscarinic drugs to treat an overactive bladder. Fesoterodine is extensively hydrolyzed by esterases to 5-hydroxymethyl tolterodine (5-HMT), the major active metabolite. CYP2D6 and CYP3A4 mainly metabolize 5-HMT and are, therefore, the primary pharmacogenetic candidate biomarkers. Materials and Methods: This is a candidate gene study designed to investigate the effects of 120 polymorphisms in 33 genes (including the CYP, COMT, UGT, NAT2, and CES enzymes, ABC and SLC transporters, and 5-HT receptors) on fesoterodine pharmacokinetics and their safety in 39 healthy volunteers from three bioequivalence trials. Results: An association between 5-HMT exposure (dose/weight corrected area under the curve (AUC/DW) and dose/weight corrected maximum plasma concentration (Cmax/DW)), elimination (terminal half-life (T1/2) and the total drug clearance adjusted for bioavailability (Cl/F)), and CYP2D6 activity was observed. Poor/intermediate metabolizers (PMs/IMs) had higher 5-HMT AUC/DW (1.5-fold) and Cmax/DW (1.4-fold) values than the normal metabolizers (NMs); in addition, the normal metabolizers (NMs) had higher 5-HMT AUC/DW (1.7-fold) and Cmax/DW (1.3-fold) values than the ultrarapid metabolizers (UMs). Lower 5-HMT exposure and higher T1/2 were observed for the CYP3A4 IMs compared to the NMs, contrary to our expectations. Conclusions: CYP2D6 might have a more important role than CYP3A4 in fesoterodine pharmacokinetics, and its phenotype might be a better predictor of variation in its pharmacokinetics. An association was observed between different genetic variants of different genes of the UGT family and AUC, Cmax, and CL/F of 5-HMT, which should be confirmed in other studies.

Insights into Asparaginase Allergic Responses: Exploring Pharmacogenetic Influences.

Acute lymphoblastic leukemia represents the most prevalent childhood cancer. Modern chemotherapy has significantly improved outcomes, achieving EFS rates of 80% and OS rates nearing 90% in developed nations, while in developing regions, rates remain below 50%, highlighting disparities, and this difference is due to several factors. Genetic variability plays a role in these drug response disparities, presenting single-nucleotide variations (SNVs). Pharmacogenetic research aims to pinpoint these SNVs early in treatment to predict specific drug responses effectively. This review aims to explore advancements in pharmacogenetics associated with asparaginase (ASNase). ASNase plays a crucial role in the treatment of ALL and is available in three formulations: E. coli, Erwinia, and PEG ASNase. ASNase therapy presents challenges due to adverse effects, like hypersensitivity reactions. Identifying predictive markers for hypersensitivity development beforehand is crucial for optimizing treatments. Several pharmacogenetic studies have investigated the association between SNVs and the risk of hypersensitivity. Key genes include GRIA1, NFATC2, CNTO3, ARHGAP28, MYBBP1A, and HLA. Studies have highlighted associations between SNVs within these genes and hypersensitivity reactions. Notably, most pharmacogenetic investigations of hypersensitivity have focused on patients treated with E. coli, emphasizing the need for broader exploration across different formulations. Future research investigating these variants holds promise for advancing our understanding of ASNase's pharmacogenetics.

Distribution of CYP3A4 and CYP3A5 Polymorphisms and Genotype Combination Implicated in Tacrolimus Metabolism.

INTRODUCTION: Human cytochrome P450 (CYP), particularly CYP3A4 and CYP3A5 is mainly responsible for the metabolism of several drugs including tacrolimus. Significant interracial/interethnic variation in the expression and function of CYP3A5 and CYP3A4 is caused by Single Nucleotide Polymorphisms (SNPs) of genes encoding these proteins. AIM: The present study investigated the genetic polymorphisms CYP3A4*1B, CYP3A4*22, and CYP3A5*3 in the Tunisian population. METHODS: We included in this study, Tunisian healthy subjects and renal transplant recipients receiving tacrolimus. CYP3A4 and CYP3A5 genotyping were performed using polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP). According to the genotypic combination of the three CYP polymorphisms, we have identified for the first time four metabolizers statuses: slow metabolizers (SM), intermediate metabolizers (IM), high metabolizers (HM), and extensive metabolizers (EM). RESULTS: A total of 101 renal transplant patients and 102 healthy subjects were included. Our results showed that the predominant alleles in the Tunisian population are a wild type of CYP3A4*1B (0.87), likewise CYP3A4*22 (0.975) and CYP3A5*3 (0.82). The genotype frequencies of CYP3A4*1B, CYP3A4*22, and CYP3A5*3 were found to be 3.9%, 0.0%, and 69.5%, respectively. Also, we found a significant linkage disequilibrium between CYP3A4*1B and CYP3A5*3. We approved that the IM is the predominant phenotype in our population with 124 patients followed by and EM with 41 patients, HM in 29 patients and SM in 9 patients. These results showed that Tunisians are most similar to Caucasians. CONCLUSION: The genetic background of these enzymes CYP3A4*1B, CYP3A4*22, and CYP3A5*3 in this study are important in the prescription of personalized medicine.