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.

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.

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.

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.

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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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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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.

Influence of COMT (rs4680) and OPRM1 (rs1799971) on Cancer Pain, Opioid Dose, and Adverse Effects.

Background: The influence of pharmacogenomics on opioid response, particularly with COMT (rs4680) and OPRM1 (rs1799971) variants, has been studied individually and in combination. However, most studies are in a noncancer context and not all their possible variant combinations have been examined. Objectives: This study examined COMT (rs4680) and OPRM1 (rs1799971), and their allele combinations, in advanced cancer to examine associations with pain scores, opioid dose, and adverse effects. Setting/Subjects: This multicenter prospective cohort study recruited patients receiving opioids for advanced cancer pain in Melbourne, Australia. Clinical data (demographics, opioids), validated instruments (pain and adverse effects), and blood (DNA) were collected. Descriptive analyses were used. Univariate and multivariate logistic regression analyses were used to evaluate associations between clinical outcomes (opioid dose, pain, adverse effects) and genotypes of interest. Results: Fifty-four participants were recruited to the study. Those with COMT A allele required lower opioid doses [130 mg (interquartile range [IQR] 67.5,230) versus 180 mg (IQR 55,322.5), p = 0.047] and experienced greater adverse effects [sickness response aOR (adjusted odds ratio) 7.1 (95% CI 1.51,33.41), p = 0.01]. Those with the COMT GG/OPRM1 G allele combination required higher opioid doses [322.5 mg (IQR 264,360) versus 125 mg (65,225), (p = 0.04)]. Those with COMT AG/OPRM1 AA experienced higher average pain [aOR 1.55 (95% CI 1.03, 2.33), p = 0.04] and moderate-severe nausea [aOR 5.47 (95% CI 1.35, 22.21), p = 0.02] but reduced drowsiness [aOR 0.25 (95% CI 0.06, 1.02), p = 0.05]. Conclusions: Patients with cancer with the COMT alternate (A) allele have greater sickness response adverse effects, which may be responsible for the lower opioid doses observed. Significant results of two new COMT/OPRM1 genotype combinations are presented that have not previously been studied, with plausible phenotype descriptions suggested.

Evaluation of pharmacogenetic automated clinical decision support for clopidogrel.

Aim: Clopidogrel requires CYP2C19 activation to have antiplatelet effects. Pharmacogenetic testing to identify patients with impaired CYP2C19 function can be coupled with clinical decision support (CDS) alerts to guide antiplatelet prescribing. We evaluated the impact of alerts on clopidogrel prescribing.Materials & methods: We retrospectively analyzed data for 866 patients in which CYP2C19-clopidogrel CDS was deployed at a single healthcare system during 2015-2023.Results: Analyses included 2,288 alerts. CDS acceptance rates increased from 24% in 2015 to 63% in 2023 (p < 0.05). Adjusted analyses also showed higher acceptance rates when clopidogrel had been ordered for a percutaneous intervention (OR: 28.7, p < 0.001) and when cardiologists responded to alerts (OR: 2.11, p = 0.001).Conclusion: CDS for CYP2C19-clopidogrel was effective in reducing potential drug-gene interactions. Its influence varied by clinician specialty and medication indications.

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Clinical effects of CYP2D6 phenoconversion in patients with psychosis.

BACKGROUND: Pharmacogenetics is considered a promising avenue for improving treatment outcomes, yet evidence arguing for the use of pharmacogenetics in the treatment of psychotic disorders is mixed and clinical usefulness is under debate. Many patients with psychosis use multiple medications, which can alter the metabolic capacity of CYP enzymes, a process called phenoconversion. In clinical studies, treatment outcomes of drugs for psychosis management may have been influenced by phenoconversion. AIM: Here we evaluate the impact and predictive value of CYP2D6 phenoconversion in patients with psychotic disorders under pharmacological treatment. METHOD: Phenoconversion-corrected phenotype was determined by accounting for inhibitor strength. Phenoconversion-corrected and genotype-predicted phenotypes were compared in association with side effects, subjective well-being and symptom severity. RESULTS: Phenoconversion led to a large increase in poor metabolizers (PMs; 17-82, 16% of sample), due to concomitant use of the serotonin reuptake inhibitors fluoxetine and paroxetine. Neither CYP2D6-predicted nor phenoconversion-corrected phenotype was robustly associated with outcome measures. Risperidone, however, was most affected by the CYP2D6 genotype. CONCLUSION: Polypharmacy and phenoconversion were prevalent and accounted for a significant increase in PMs. CYP2D6 may play a limited role in side effects, symptoms and well-being measures. However, due to the high frequency of occurrence, phenoconversion should be considered in future clinical trials.

Implementation of a pharmacist-guided pharmacogenomics dosing service at a rural NCI-designated comprehensive cancer center.

INTRODUCTION: The goal of pharmacogenetic testing is to identify genetic variants with significant implications on drug safety and efficacy. Several professional organizations and institutions have demonstrated the value of pharmacist involvement in the implementation of pharmacogenomic services. Therefore, we aimed to establish a pharmacist-guided model for interpretation of pharmacogenetic results for all oncology patients seen at the Dartmouth Cancer Center (DCC) in Lebanon, NH. METHODS: A pilot of a pharmacist-guided pharmacogenomics dosing service was implemented at the DCC. Pharmacy services included review of results from a next generation sequencing panel for DPYD, TPMT, NUDT15, and UGT1A1 variants. The pharmacist wrote a note in the electronic health record (EHR) detailing actionable drug-gene interactions and drug-dosing guidance, which was then routed to the treating oncologist. Outcomes collected included highlighting actionable mutations and defining pharmacist interventions. In addition, time spent formulating and documenting patient-specific drug-dosing recommendations was collected. RESULTS: From February 2024 through May 2024, a total of 71 patients with pharmacogenetic results, provided by the clinical molecular laboratory at Dartmouth Health, were reviewed by the pharmacist. The majority of patients tested were diagnosed with a malignancy of gastrointestinal origin. Twenty-one patients were found to have actionable variants in at least one of the four genes evaluated, and five of the 21 identified patients had active treatment plans for which dose changes were then implemented. CONCLUSIONS: Implementation of a pharmacist-guided pharmacogenomics based dosing service aided in optimizing drug therapy and has positioned Dartmouth Health for further expansion of pharmacogenomics and personalized patient care.

Personalized medicine and opioid use disorder.

Opioid use disorder (OUD) is a major public health problem affecting millions of people worldwide. Although OUD is a chronic and relapsing disorder, a variety of pharmacological and non-pharmacological interventions are available. Medication-assisted treatment of OUD generally relies on competition for opioid receptors against the addictive substance. The mechanisms of this competition are to block or inactivate the opioid receptor or activate the receptor with a substance that is intermittent or long acting. Methadone and buprenorphine are two United States Food and Drug Administration-approved medications that have long-term positive effects on the health of opioid-dependent individuals. Although clinical studies of drugs generally demonstrate efficacy in thousands of people and toxicity is excluded, it cannot be predicted whether the given drug will cause side effects in one of the patients at the treatment dose. Individual differences can be explained by many biological and environmental factors. Variations in genes encoding drug metabolism or cellular drug targets significantly explain the variability in drug response between individuals. Therefore, for the effects of candidate genes to be accepted and included in individual treatment protocols, it is important to repeat studies on individuals of different ethnic backgrounds and prove a similar effect.

The Additive Effect of Combinations of FSH Receptor Gene Variants in Ovarian Response to Stimulation.

To analyze whether combinations of polymorphisms within FSHR gene influence ovarian response (OR) to stimulation. A multicenter prospective cohort study was conducted from 11/2016-06/2019 in Europe and Asia including predicted normo-responders under 38y. Patients underwent ovarian stimulation using fixed-dose 150 IU rFSH in a GnRH antagonist protocol. FSHR variants rs6165, rs6166 and rs1394205 were genotyped and combined in diplotypes. OR was compared following multivariable regression. rs6165/rs6166 genotype AG/AG exhibited more hypo-response (33.1% vs. 24%,adjOR 1.77 [95%CI 1.08-2.90]) and lower Follicle to Oocyte Index (FOI) compared with other diplotypes (EMD -11.72 [95%CI -20.89;-2.55]). Genotype GG/AA showed less hypo-response (19.1% vs. 31%, adjOR 0.48 [95%CI 0.24-0.96]), while AA/AA had higher FOI (EMD 20.04 [95%CI 4.51;35.56]). Concerning rs6165/rs1394205, less oocytes (EMD -1.99 [95%CI -3.57;-0.42]) and lower FOI (EMD -12.07 [95%CI -23.09;-1.05]) were retrieved with genotype AG/AG and higher FORT with genotype AA/AG (EMD 17.88 [95%CI 3.77;31.98]). Regarding rs6166/rs1394205, less hypo-response (16.3% vs. 29.5%,adjOR 0.42 [95%CI 0.19-0.97]), more oocytes (EMD 3.45 [95%CI 1.57;5.34]) and higher FOI (EMD 17.57 [95%CI 4.41;30.73) were found with genotype AA/GG. Genotype AA/AG presented higher FORT (EMD 13.47 [95%CI 2.51,24.42]), while more hypo-response (56.3% vs. 26.4%,adjOR 6.30 [95%CI 1.88;21.08]) and lower FOI (EMD -23.51 [95%CI -45.04;-1.97]) was reported with AG/AA. In accordance with our previous studies, FSHR polymorphisms have a statistically significant impact on OR, both individually and in association. However, only rs6166/rs1394205 genotype AA/GG seems to have a clinically significant effect, with a decrease in the prevalence of hypo-response, higher oocyte yield and increase in FOI.

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.

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.

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.

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.

Long-read sequencing of CYP2D6 may improve psychotropic prescribing and treatment outcomes: A systematic review and meta-analysis.

BACKGROUND: The enzyme expression (i.e. phenotype) of the Cytochrome P450 2D6 (CYP2D6) gene is highly relevant to the metabolism of psychotropic medications, and therefore to precision medicine (i.e. personalised prescribing). AIMS: This review aims to assess the improvement in CYP2D6 phenotyping sensitivity (IPS) and accuracy (IPA) offered by long-read sequencing (LRS), a new genetic testing technology. METHODS: Human DNA samples that underwent LRS genotyping of CYP2D6 in published, peer-reviewed clinical research were eligible for inclusion. A systematic literature search was conducted until 30 September 2023. CYP2D6 genotypes were translated into phenotypes using the international consensus method. IPS was the percentage of non-normal LRS CYP2D6 phenotypes undetectable with FDA-approved testing (AmpliChip). IPA was the percentage of LRS CYP2D6 phenotypes mischaracterised by non-LRS genetic tests (for samples with LRS and non-LRS data). RESULTS: Six studies and 1411 samples were included. In a meta-analysis of four studies, IPS was 10% overall (95% CI = (2, 18); n = 1385), 20% amongst Oceanians (95% CI = (17, 23); n = 582) and 2% amongst Europeans (95% CI = (1, 4); n = 803). IPA was 4% in a large European cohort (95% CI = (2, 7); n = 567). When LRS was used selectively (e.g. for novel or complex CYP2D6 genotypes), very high figures were observed for IPS (e.g. 88%; 95% CI = (72, 100); n = 17; country = Japan) and IPA (e.g. 76%; 95% CI = (55, 98); n = 17; country = Japan). CONCLUSIONS: LRS improves CYP2D6 phenotyping compared to established genetic tests, particularly amongst Oceanian and Japanese individuals, and those with novel or complex genotypes. LRS may therefore assist in optimising personalised prescribing of psychotropic medications. Further research is needed to determine associated clinical benefits, such as increased medication safety and efficacy.