Androgen receptor-mediated pharmacogenomic expression quantitative trait loci: implications for breast cancer response to AR-targeting therapy.

BACKGROUND: Endocrine therapy is the most important treatment modality of breast cancer patients whose tumors express the estrogen receptor α (ERα). The androgen receptor (AR) is also expressed in the vast majority (80-90%) of ERα-positive tumors. AR-targeting drugs are not used in clinical practice, but have been evaluated in multiple trials and preclinical studies. METHODS: We performed a genome-wide study to identify hormone/drug-induced single nucleotide polymorphism (SNP) genotype - dependent gene-expression, known as PGx-eQTL, mediated by either an AR agonist (dihydrotestosterone) or a partial antagonist (enzalutamide), utilizing a previously well characterized lymphoblastic cell line panel. The association of the identified SNPs-gene pairs with breast cancer phenotypes were then examined using three genome-wide association (GWAS) studies that we have published and other studies from the GWAS catalog. RESULTS: We identified 13 DHT-mediated PGx-eQTL loci and 23 Enz-mediated PGx-eQTL loci that were associated with breast cancer outcomes post ER antagonist or aromatase inhibitors (AI) treatment, or with pharmacodynamic (PD) effects of AIs. An additional 30 loci were found to be associated with cancer risk and sex-hormone binding globulin levels. The top loci involved the genes IDH2 and TMEM9, the expression of which were suppressed by DHT in a PGx-eQTL SNP genotype-dependent manner. Both of these genes were overexpressed in breast cancer and were associated with a poorer prognosis. Therefore, suppression of these genes by AR agonists may benefit patients with minor allele genotypes for these SNPs. CONCLUSIONS: We identified AR-related PGx-eQTL SNP-gene pairs that were associated with risks, outcomes and PD effects of endocrine therapy that may provide potential biomarkers for individualized treatment of breast cancer.

Pharmacogenomics polygenic risk score: Ready or not for prime time?

Pharmacogenomic Polygenic Risk Scores (PRS) have emerged as a tool to address the polygenic nature of pharmacogenetic phenotypes, increasing the potential to predict drug response. Most pharmacogenomic PRS have been extrapolated from disease-associated variants identified by genome wide association studies (GWAS), although some have begun to utilize genetic variants from pharmacogenomic GWAS. As pharmacogenomic PRS hold the promise of enabling precision medicine, including stratified treatment approaches, it is important to assess the opportunities and challenges presented by the current data. This assessment will help determine how pharmacogenomic PRS can be advanced and transitioned into clinical use. In this review, we present a summary of recent evidence, evaluate the current status, and identify several challenges that have impeded the progress of pharmacogenomic PRS. These challenges include the reliance on extrapolations from disease genetics and limitations inherent to pharmacogenomics research such as low sample sizes, phenotyping inconsistencies, among others. We finally propose recommendations to overcome the challenges and facilitate the clinical implementation. These recommendations include standardizing methodologies for phenotyping, enhancing collaborative efforts, developing new statistical methods to capitalize on drug-specific genetic associations for PRS construction. Additional recommendations include enhancing the infrastructure that can integrate genomic data with clinical predictors, along with implementing user-friendly clinical decision tools, and patient education. Ethical and regulatory considerations should address issues related to patient privacy, informed consent and safe use of PRS. Despite these challenges, ongoing research and large-scale collaboration is likely to advance the field and realize the potential of pharmacogenomic PRS.

Drug-induced hepatotoxicity and association with slow acetylation variants NAT2*5 and NAT2*6 in Cameroonian patients with tuberculosis and HIV co-infection.

BACKGROUND: Human immunodeficiency virus (HIV) and tuberculosis (TB) are major contributors to morbidity and mortality in sub-Saharan Africa including Cameroon. Pharmacogenetic variants could serve as predictors of drug-induced hepatotoxicity (DIH), in patients with TB co-infected with HIV. We evaluated the occurrence of DIH and pharmacogenetic variants in Cameroonian patients. METHODS: Treatment-naïve patients with HIV, TB or TB/HIV co-infection were recruited at three hospitals in Cameroon, between September 2018 and November 2019. Appropriate treatment was initiated, and patients followed up for 12 weeks to assess DIH. Pharmacogenetic variants were assessed by allele discrimination TaqMan SNP assays. RESULTS: Of the 141 treatment naïve patients, the overall incidence of DIH was 38% (53/141). The highest incidence of DIH, 52% (32/61), was observed among HIV patients. Of 32 pharmacogenetic variants, the slow acetylation variants NAT2*5 was associated with a decreased risk of DIH (OR: 0.4; 95%CI: 0.17-0.96; p = 0.038), while NAT2*6 was found to be associated with an increased risk of DIH (OR: 4.2; 95%CI: 1.1-15.2; p = 0.017) among patients treated for TB. Up to 15 SNPs differed in ≥ 5% of allele frequencies among African populations, while 25 SNPs differed in ≥ 5% of the allele frequencies among non-African populations, respectively. CONCLUSIONS: DIH is an important clinical problem in African patients with TB and HIV. The NAT2*5 and NAT2*6 variants were found to be associated with DIH in the Cameroonian population. Prior screening for the slow acetylation variants NAT2*5 and NAT2*6 may prevent DIH in TB and HIV-coinfected patients.

Pharmacogenomic Characterization of Childbearing-Aged Individuals With Mood Disorders in a Tertiary Care Perinatal Mental Health Clinic.

Objective: The effectiveness of antidepressant treatment for mood disorders is often limited by either a poor response or the emergence of adverse effects. These complications often necessitate multiple drug trials. This clinical challenge intensifies during pregnancy, when medications must be selected to improve the likelihood of response and optimize reproductive outcomes. We determined the distribution of common pharmacogenetic variants, metabolizer phenotypes, past medication responses, and side effects in childbearing-aged individuals seeking treatment in a tertiary care perinatal mental health clinic.Methods: Sixty treatment-seeking women (based on sex at birth) with DSM-5- defined bipolar disorder (n = 28) or major depressive disorder (n = 32) provided DNA samples and completed psychiatric diagnostic and severity assessments between April 2014 and December 2017. Samples were genotyped for single-nucleotide variants in drug metabolizing enzyme genes of commonly prescribed antidepressants (cytochrome P450 [CYP] 1A2, 2B6, 2C9, 2C19, 2D6, 3A4, and 3A5), and the frequency of normative metabolizer status was compared to reference populations data from Clinical Pharmacogenetics Implementation Consortium (CPIC) guidelines. The Antidepressant Treatment History Form was used to record historic medication trials and side effects.Results: A significantly greater proportion of extensive metabolizers for CYP2B6 was observed in the study population when compared to CPIC population frequency databases in Caucasians (0.64 vs 0.43 [95% CI: 0.49-0.76]; P value = .006) and African Americans (0.71 vs 0.33 [95% CI: 0.29-0.96]; P value = .045). No significant association was found between metabolizer phenotype and the likelihood of a medication side effect.Conclusion: Pharmacogenomic testing may have value for personalized prescribing in individuals capable of or considering pregnancy.

A comprehensive Thai pharmacogenomics database (TPGxD-1): Phenotype prediction and variants identification in 942 whole-genome sequencing data.

Computational methods analyze genomic data to identify genetic variants linked to drug responses, thereby guiding personalized medicine. This study analyzed 942 whole-genome sequences from the Electricity Generating Authority of Thailand (EGAT) cohort to establish a population-specific pharmacogenomic database (TPGxD-1) in the Thai population. Sentieon (version 201808.08) implemented the GATK best workflow practice for variant calling. We then annotated variant call format (VCF) files using Golden Helix VarSeq 2.5.0 and employed Stargazer v2.0.2 for star allele analysis. The analysis of 63 very important pharmacogenes (VIPGx) reveals 85,566 variants, including 13,532 novel discoveries. Notably, we identified 464 known PGx variants and 275 clinically relevant novel variants. The phenotypic prediction of 15 VIPGx demonstrated a varied metabolic profile for the Thai population. Genes like CYP2C9 (9%), CYP3A5 (45.2%), CYP2B6 (9.4%), NUDT15 (15%), CYP2D6 (47%) and CYP2C19 (43%) showed a high number of intermediate metabolizers; CYP3A5 (41%), and CYP2C19 (9.9%) showed more poor metabolizers. CYP1A2 (52.7%) and CYP2B6 (7.6%) were found to have a higher number of ultra-metabolizers. The functional prediction of the remaining 10 VIPGx genes reveals a high frequency of decreased functional alleles in SULT1A1 (12%), NAT2 (84%), and G6PD (12%). SLCO1B1 reports 20% poor functional alleles, while PTGIS (42%), SLCO1B1 (4%), and TPMT (5.96%) showed increased functional alleles. This study discovered new variants and alleles in the 63 VIPGx genes among the Thai population, offering insights into advancing clinical pharmacogenomics (PGx). However, further validation is needed using other computational and genotyping methods.

Pharmacokinetic and neuroimmune pharmacogenetic impacts on slow-release morphine cancer pain control and adverse effects.

The aim was to determine if opioid neuroimmunopharmacology pathway gene polymorphisms alter serum morphine, morphine-3-glucuronide and morphine-6-glucuronide concentration-response relationships in 506 cancer patients receiving controlled-release oral morphine. Morphine-3-glucuronide concentrations (standardised to 11 h post-dose) were higher in patients without pain control (median (interquartile range) 1.2 (0.7-2.3) versus 1.0 (0.5-1.9) µM, P = 0.006), whereas morphine concentrations were higher in patients with cognitive dysfunction (40 (20-81) versus 29 (14-60) nM, P = 0.02). TLR2 rs3804100 variant carriers had reduced odds (adjusted odds ratio (95% confidence interval) 0.42 (0.22-0.82), P = 0.01) of opioid adverse events. IL2 rs2069762 G/G (0.20 (0.06-0.52)), BDNF rs6265 A/A (0.15 (0.02-0.63)) and IL6R rs8192284 carrier (0.55 (0.34-0.90)) genotypes had decreased, and IL6 rs10499563 C/C increased (3.3 (1.2-9.3)), odds of sickness response (P ≤ 0.02). The study has limitations in heterogeneity in doses, sampling times and diagnoses but still suggests that pharmacokinetics and immune genetics co-contribute to morphine pain control and adverse effects in cancer patients.

Predictive role of ITPA genetic variants in thiopurine-related myelotoxicity in Crohn's disease patients.

Thiopurines, an effective therapy for Crohn's disease (CD), often lead to adverse events (AEs). Gene polymorphisms affecting thiopurine metabolism may predict AEs. This retrospective study in CD patients (n = 114) with TPMT activity > 5 Units/Red Blood Cells analyzed TPMT (c.238 G > C, c.460 G > A, c.719 A > G), ITPA (c.94 C > A, IVS2 + 21 A > C), and NUDT15 (c.415 C > T) polymorphisms. All patients received azathioprine (median dose 2.2 mg/kg) with 41.2% experiencing AEs, mainly myelotoxicity (28.1%). No NUDT15 polymorphisms were found, 7% had TPMT, and 31.6% had ITPA polymorphisms. AEs led to therapy modifications in 41.2% of patients. Multivariate analysis identified advanced age (OR 1.046, p = 0.007) and ITPA IVS2 + 21 A > C (OR 3.622, p = 0.015) as independent predictors of AEs. IVS2 + 21 A > C was also associated with myelotoxicity (OR 2.863, p = 0.021). These findings suggest that ITPA IVS2 + 21 A > C polymorphism and advanced age predict AEs during thiopurine therapy for CD with intermediate-normal TPMT activity.

Rationale and design for a pragmatic randomized trial to assess gene-based prescribing for SSRIs in the treatment of depression.

Specific selective serotonin reuptake inhibitors (SSRIs) metabolism is strongly influenced by two pharmacogenes, CYP2D6 and CYP2C19. However, the effectiveness of prospectively using pharmacogenetic variants to select or dose SSRIs for depression is uncertain in routine clinical practice. The objective of this prospective, multicenter, pragmatic randomized controlled trial is to determine the effectiveness of genotype-guided selection and dosing of antidepressants on control of depression in participants who are 8 years or older with ≥3 months of depressive symptoms who require new or revised therapy. Those randomized to the intervention arm undergo pharmacogenetic testing at baseline and receive a pharmacy consult and/or automated clinical decision support intervention based on an actionable phenotype, while those randomized to the control arm have pharmacogenetic testing at the end of 6-months. In both groups, depression and drug tolerability outcomes are assessed at baseline, 1 month, 3 months (primary), and 6 months. The primary end point is defined by change in Patient-Reported Outcomes Measurement Information System (PROMIS) Depression score assessed at 3 months versus baseline. Secondary end points include change inpatient health questionnaire (PHQ-8) measure of depression severity, remission rates defined by PROMIS score < 16, medication adherence, and medication side effects. The primary analysis will compare the PROMIS score difference between trial arms among those with an actionable CYP2D6 or CYP2C19 genetic result or a CYP2D6 drug-drug interaction. The trial has completed accrual of 1461 participants, of which 562 were found to have an actionable phenotype to date, and follow-up will be complete in April of 2024.

CYP2C19 Genotype Is Associated With Adverse Cardiovascular Outcomes in Black Patients Treated With Clopidogrel Undergoing Percutaneous Coronary Intervention.

BACKGROUND: Cytochrome P450 2C19 (CYP2C19) intermediate and poor metabolizer patients exhibit diminished clopidogrel clinical effectiveness after percutaneous coronary intervention (PCI). However, outcome studies to date have lacked racial diversity. Thus, the impact of CYP2C19 genotype on cardiovascular outcomes in patients treated with clopidogrel who identify as Black or African American remains unclear. METHODS AND RESULTS: Adults among 5 institutions who self-identified as Black or African American, underwent PCI and clinical CYP2C19 genotyping, and were treated with clopidogrel were included. Data were abstracted from health records. Major atherothrombotic (composite of death, myocardial infarction, ischemic stroke, stent thrombosis, or revascularization for unstable angina) and bleeding event rates within 1 year after PCI were compared across CYP2C19 metabolizer groups using multivariable Cox regression adjusted for potential confounders and baseline variables meeting a threshold of P<0.10. The population included 567 Black patients treated with clopidogrel (median age, 62 years; 46% women; 70% with an acute coronary syndrome indication for PCI). Major atherothrombotic events rates were significantly higher among clopidogrel-treated intermediate and poor metabolizers (24 of 125 [19.2%]) versus patients treated with clopidogrel without a no function allele (43 of 442 [9.7%]; 35.1 versus 15.9 events per 100 person-years; adjusted hazard ratio, 2.00 [95% CI, 1.20-3.33], P=0.008). Bleeding event rates were low overall (23 of 567 [4.1%]) and did not differ among the metabolizer groups. CONCLUSIONS: Black patients with CYP2C19 intermediate and poor metabolizer phenotypes who are treated with clopidogrel exhibit increased risk of adverse cardiovascular outcomes after PCI in a real-world clinical setting. Bleeding outcomes should be interpreted cautiously. Prospective studies are needed to determine whether genotype-guided use of prasugrel or ticagrelor in intermediate and poor metabolizers improves outcomes in Black patients undergoing PCI.

Prognostic Impact of CYP2C19 Genotypes on Long-Term Clinical Outcomes in Older Patients After Percutaneous Coronary Intervention.

BACKGROUND: Carriers of CYP2C19 loss-of-function alleles have increased adverse events after percutaneous coronary intervention, but limited data are available for older patients. We aimed to evaluate the prognostic impact of CYP2C19 genotypes on clinical outcomes in older patients after percutaneous coronary intervention. METHODS AND RESULTS: The study included 1201 older patients (aged ≥75 years) who underwent percutaneous coronary intervention and received clopidogrel-based dual antiplatelet therapy in South Korea. Patients were grouped on the basis of CYP2C19 genotypes. The primary outcome was 3-year major adverse cardiac events, defined as a composite of cardiac death, myocardial infarction, and stent thrombosis. Older patients were grouped into 3 groups: normal metabolizer (36.6%), intermediate metabolizer (48.1%), and poor metabolizer (15.2%). The occurrence of the primary outcome was significantly different among the groups (3.1, 7.0, and 6.2% in the normal metabolizer, intermediate metabolizer, and poor metabolizer groups, respectively; P=0.02). The incidence rate of all-cause death at 3 years was greater in the intermediate metabolizer and poor metabolizer groups (8.1% and 9.2%, respectively) compared with that in the normal metabolizer group (3.5%, P=0.03) without significant differences in major bleeding. In the multivariable analysis, the intermediate metabolizer and poor metabolizer groups were independent predictors of 3-year clinical outcomes. CONCLUSIONS: In older patients, the presence of any CYP2C19 loss-of-function allele was found to be predictive of a higher incidence of major adverse cardiac events within 3 years following percutaneous coronary intervention. This finding suggests a need for further investigation into an optimal antiplatelet strategy for older patients. REGISTRATION: URL: https://clinicaltrials.gov. Identifier: NCT04734028.

Frequency of pharmacogenomic variants affecting efficacy and safety of anti-cancer drugs in a south Asian population from Sri Lanka.

BACKGROUND: Therapy with anti-cancer drugs remain the cornerstone of treating cancer. The effectiveness and safety of anti-cancer drugs vary significantly among individuals due to genetic factors influencing the drug response and metabolism. Data on the pharmacogenomic variations in Sri Lankans related to anti-cancer therapy is sparse. As current treatment guidelines in Sri Lanka often do not consider local pharmacogenomic variants, this study aimed to explore the diversity of pharmacogenomic variants in the Sri Lankan population to pave the way for personalized treatment approaches and improve patient outcomes. METHODS: Pharmacogenomic data regarding variant-drug pairs of genes CYP2D6, DPYD, NUDT15, EPAS1, and XRCC1 with clinical annotations labelled as evidence levels 1A-2B were obtained from the Pharmacogenomics Knowledgebase database. Their frequencies in Sri Lankans were obtained from an anonymized database that was derived from 541 Sri Lankans who underwent exome sequencing at the Human Genetics Unit, Faculty of Medicine, University of Colombo. Variations in DPYD, NUDT15, and EPAS1 genes are related to increased toxicity to fluoropyrimidines, mercaptopurines, and sorafenib respectively. Variations in CYP2D6 and XRCC1 genes are related to changes in efficacy of tamoxifen and platinum compounds, respectively. Minor allele frequencies of these variants were calculated and compared with other populations. RESULTS: MAFs of rs1065852 c.100 C > T (CYP2D6), rs3918290 c.1905 + 1G > A (DPYD), rs56038477 c.1236G > A (DPYD), rs7557402 c.1035-7 C > G (EPAS1), rs116855232 c.415 C > T (NUDT15*3), and rs25487 c.1196 A > G (XRCC1) were: 12.9% [95%CI:10.9-14.9], 1.5% [95%CI:0.8-2.2], 1.2% [95%CI:0.5-1.8], 37.7% [95%CI:34.8-40.6], 8.3% [95%CI:6.7-10.0], and 64.0% [95%CI:61.1-66.8], respectively. Frequencies of rs1065852 c.100 C > T (CYP2D6), rs7557402 c.1035-7 C > G (EPAS1), and rs25487 (XRCC1) were significantly lower in Sri Lankans, while frequencies of rs116855232 c.415 C > T (NUDT15*3) and rs56038477 c.1236G > A (DPYD) were significantly higher in Sri Lankans when compared to some Western and Asian populations. CONCLUSION: Sri Lankans are likely to show lower toxicity risk with sorafenib (rs7557402 c.84,131 C > G) and, higher toxicity risk with fluoropyrimidines (rs56038477 c.1236G > A) and mercaptopurine (rs116855232 c.415 C > T), and reduced effectiveness with tamoxifen (rs1065852 c.100 C > T) and platinum compounds (rs25487). These findings highlight the potential contribution of these genetic variations to the individual variability in anti-cancer dosage requirements among Sri Lankans.

Gene polymorphism as a cause of hemorrhagic complications in patients with non-valvular atrial fibrillation treated with oral vitamin K-independent anticoagulants.

Atrial fibrillation (AF) accounts for 40% of all cardiac arrhythmias and is associated with a high risk of stroke and systemic thromboembolic complications. Dabigatran, rivaroxaban, apixaban, and edoxaban are direct oral anticoagulants (DOACs) that have been proven to prevent stroke in patients with non-valvular AF. This review summarizes the pharmacokinetics, pharmacodynamics, and drug interactions of DOACs, as well as new data from pharmacogenetic studies of these drugs. This review is aimed at analyzing the scientific literature on the gene polymorphisms involved in the metabolism of DOACs. We searched PubMed, Cochrane, Google Scholar, and CyberLeninka (Russian version) databases with keywords: 'dabigatran', 'apixaban', 'rivaroxaban', 'edoxaban', 'gene polymorphism', 'pharmacogenetics', 'ABCB1', 'CES1', 'SULT1A', 'ABCG2', and 'CYP3A4'. The articles referred for this review include (1) full-text articles; (2) study design with meta-analysis, an observational study in patients taking DOAC; and (3) data on the single-nucleotide polymorphisms and kinetic parameters of DOACs (plasma concentration), or a particular clinical outcome, published in English and Russian languages during the last 10 years. The ages of the patients ranged from 18 to 75 years. Out of 114 reviewed works, 24 were found eligible. As per the available pharmacogenomic data, polymorphisms affecting DOACs are different. This may aid in developing individual approaches to optimize DOAC pharmacotherapy to reduce the risk of hemorrhagic complications. However, large-scale population studies are required to determine the dosage of the new oral anticoagulants based on genotyping. Information on the genetic effects is limited owing to the lack of large-scale studies. Uncovering the mechanisms of the genetic basis of sensitivity to DOACs helps in developing personalized therapy based on patient-specific genetic variants and improves the efficacy and safety of DOACs in the general population.

Gene polymorphism as a cause of hemorrhagic complications in patients with non-valvular atrial fibrillation treated with oral vitamin K-independent anticoagulantsAtrial fibrillation (AF) accounts for 40% of all cardiac arrhythmias and is associated with a high risk of stroke and systemic thromboembolic complications. Dabigatran, rivaroxaban, apixaban, and edoxaban are direct oral anticoagulants (DOACs) that have been proven to prevent stroke in patients with non-valvular AF. This review summarizes the pharmacokinetics, pharmacodynamics, and drug interactions of DOACs, as well as new data from pharmacogenetic studies of these drugs.

APF2: an improved ensemble method for pharmacogenomic variant effect prediction.

Lack of efficacy or adverse drug response are common phenomena in pharmacological therapy causing considerable morbidity and mortality. It is estimated that 20-30% of this variability in drug response stems from variations in genes encoding drug targets or factors involved in drug disposition. Leveraging such pharmacogenomic information for the preemptive identification of patients who would benefit from dose adjustments or alternative medications thus constitutes an important frontier of precision medicine. Computational methods can be used to predict the functional effects of variant of unknown significance. However, their performance on pharmacogenomic variant data has been lackluster. To overcome this limitation, we previously developed an ensemble classifier, termed APF, specifically designed for pharmacogenomic variant prediction. Here, we aimed to further improve predictions by leveraging recent key advances in the prediction of protein folding based on deep neural networks. Benchmarking of 28 variant effect predictors on 530 pharmacogenetic missense variants revealed that structural predictions using AlphaMissense were most specific, whereas APF exhibited the most balanced performance. We then developed a new tool, APF2, by optimizing algorithm parametrization of the top performing algorithms for pharmacogenomic variations and aggregating their predictions into a unified ensemble score. Importantly, APF2 provides quantitative variant effect estimates that correlate well with experimental results (R2 = 0.91, p = 0.003) and predicts the functional impact of pharmacogenomic variants with higher accuracy than previous methods, particularly for clinically relevant variations with actionable pharmacogenomic guidelines. We furthermore demonstrate better performance (92% accuracy) on an independent test set of 146 variants across 61 pharmacogenes not used for model training or validation. Application of APF2 to population-scale sequencing data from over 800,000 individuals revealed drastic ethnogeographic differences with important implications for pharmacotherapy. We thus think that APF2 holds the potential to improve the translation of genetic information into pharmacogenetic recommendations, thereby facilitating the use of Next-Generation Sequencing data for stratified medicine.

Association of Pharmacogenomic Phenotypes in CYP2D6, CYP2C9, CYP2C19, and CYP3A5 on Polypharmacy in Veterans.

The Department of Veterans Affairs (VA) utilizes a pharmacogenomic (PGx) program that analyzes specific "pharmacogenes." This study evaluates the effect that pharmacogenes may have on prevalence of polypharmacy. This retrospective cohort study included patients with VA prescriptions who underwent PGx testing. We quantified prescriptions active or recently expired at the time of PGx testing. We constructed two co-primary polypharmacy (≥10 medications) end points: (i) based on all medications and (ii) requiring that at least one medication was affected by a pharmacogene of interest. Pharmacogenes and actionable phenotypes of interest included poor and ultrarapid metabolizers for CYP2D6, CYP2C9, and CYP2C19 and intermediate and normal metabolizers for CYP3A5. Patients were classified as having 0, 1, and 2+ total phenotypes across all genes. Of the 15,144 patients screened, 13,116 met eligibility criteria. Across phenotype cohorts, there was no significant association with polypharmacy using all medications, number of total medications, or number of medications affected by phenotypes. However, there was a significant difference in patients with polypharmacy prescribed ≥1 medication impacted by PGx across phenotype groups: 2,514/4,949 (51%), 1,349/2,595 (52%), 204/350 (58%) (P = 0.03, OR 1.31, 95% CI 1.02-1.67). The median number of medications affected by PGx phenotypes with ≥1 PGx-impacted medication across phenotype groups was a median of 0 (IQR 0, 0), 0 (IQR 0, 0), and 1 (IQR 0, 1) (P < 0.001). In patients prescribed ≥1 medication impacted by PGx, those with more actionable pharmacogenomic phenotypes were more likely to meet polypharmacy criteria.

SGLT1 and SGLT2 inhibition, circulating metabolites, and cerebral small vessel disease: a mediation Mendelian Randomization study.

BACKGROUND: Sodium-glucose cotransporter 2 (SGLT2) and SGLT1 inhibitors may have additional beneficial metabolic effects on circulating metabolites beyond glucose regulation, which could contribute to a reduction in the burden of cerebral small vessel disease (CSVD). Accordingly, we used Mendelian Randomization (MR) to examine the role of circulating metabolites in mediating SGLT2 and SGLT1 inhibition in CSVD. METHODS: Genetic instruments for SGLT1/2 inhibition were identified as genetic variants, which were both associated with the expression of encoding genes of SGLT1/2 inhibitors and glycated hemoglobin A1c (HbA1c) level. A two-sample two-step MR was used to determine the causal effects of SGLT1/2 inhibition on CSVD manifestations and the mediating effects of 1400 circulating metabolites linking SGLT1/2 inhibition with CSVD manifestations. RESULTS: A lower risk of deep cerebral microbleeds (CMBs) and small vessel stroke (SVS) was linked to genetically predicted SGLT2 inhibition. Better white matter structure integrity was also achieved, as evidenced by decreased mean diffusivity (MD), axial diffusivity (AD), and radial diffusivity (RD), as well as lower deep (DWMH) and periventrivular white matter hyperintensity (PWMH) volume. Inhibiting SGLT2 could also lessen the incidence of severe enlarged perivascular spaces (EPVS) located at white matter, basal ganglia (BG) and hippocampus (HIP). SGLT1 inhibition could preserve white matter integrity, shown as decreased MD of white matter and DWMH volume. The effect of SGLT2 inhibition on SVS and MD of white matter through the concentration of 4-acetamidobutanoate and the cholesterol to oleoyl-linoleoyl-glycerol (18:1 to 18:2) ratio, with a mediated proportion of 30.3% and 35.5% of the total effect, respectively. CONCLUSIONS: SGLT2 and SGLT1 inhibition play protective roles in CSVD development. The SGLT2 inhibition could lower the risk of SVS and improve the integrity of white matter microstructure via modulating the level of 4-acetamidobutanoate and cholesterol metabolism. Further mechanistic and clinical studies research are needed to validate our findings.

A systematic review and meta-analysis of the impacts of germline pharmacogenomics on severe toxicity and symptom burden in adult patients with cancer.

The clinical application of Pharmacogenomics (PGx) has improved patient safety. However, comprehensive PGx testing has not been widely adopted in clinical practice, and significant opportunities exist to further optimize PGx in cancer care. This systematic review and meta-analysis aim to evaluate the safety outcomes of reported PGx-guided strategies (Analysis 1) and identify well-studied emerging pharmacogenomic variants that predict severe toxicity and symptom burden (Analysis 2) in patients with cancer. We searched MEDLINE, EMBASE, CENTRAL, clinicaltrials.gov, and International Clinical Trials Registry Platform from inception to January 2023 for clinical trials or comparative studies evaluating PGx strategies or unconfirmed pharmacogenomic variants. The primary outcomes were severe adverse events (SAE; ≥ grade 3) or symptom burden with pain and vomiting as defined by trial protocols and assessed by trial investigators. We calculated pooled overall relative risk (RR) and 95% confidence interval (95%CI) using random effects models. PROSPERO, registration number CRD42023421277. Of 6811 records screened, six studies were included for Analysis 1, 55 studies for Analysis 2. Meta-analysis 1 (five trials, 1892 participants) showed a lower absolute incidence of SAEs with PGx-guided strategies compared to usual therapy, 16.1% versus 34.0% (RR = 0.72, 95%CI 0.57-0.91, p = 0.006, I2 = 34%). Meta-analyses 2 identified nine medicine(class)-variant pairs of interest across the TYMS, ABCB1, UGT1A1, HLA-DRB1, and OPRM1 genes. Application of PGx significantly reduced rates of SAEs in patients with cancer. Emergent medicine-variant pairs herald further research into the expansion and optimization of PGx to improve systemic anti-cancer and supportive care medicine safety and efficacy.

Impacts of gene variants on drug effects-the foundation of genotype-guided pharmacologic therapy for long QT syndrome and short QT syndrome.

The clinical significance of optimal pharmacotherapy for inherited arrhythmias such as short QT syndrome (SQTS) and long QT syndrome (LQTS) has been increasingly recognised. The advancement of gene technology has opened up new possibilities for identifying genetic variations and investigating the pathophysiological roles and mechanisms of genetic arrhythmias. Numerous variants in various genes have been proven to be causative in genetic arrhythmias. Studies have demonstrated that the effectiveness of certain drugs is specific to the patient or genotype, indicating the important role of gene-variants in drug response. This review aims to summarize the reported data on the impact of different gene-variants on drug response in SQTS and LQTS, as well as discuss the potential mechanisms by which gene-variants alter drug response. These findings may provide valuable information for future studies on the influence of gene variants on drug efficacy and the development of genotype-guided or precision treatment for these diseases.

Polygenic scores for cardiovascular risk factors improve estimation of clinical outcomes in CCB treatment compared to pharmacogenetic variants alone.

Pharmacogenetic variants are associated with clinical outcomes during Calcium Channel Blocker (CCB) treatment, yet whether the effects are modified by genetically predicted clinical risk factors is unknown. We analyzed 32,000 UK Biobank participants treated with dihydropiridine CCBs (mean 5.9 years), including 23 pharmacogenetic variants, and calculated polygenic scores for systolic and diastolic blood pressures, body fat mass, and other patient characteristics. Outcomes included treatment discontinuation and heart failure. Pharmacogenetic variant rs10898815-A (NUMA1) increased discontinuation rates, highest in those with high polygenic scores for fat mass. The RYR3 variant rs877087 T-allele alone modestly increased heart failure risks versus non-carriers (HR:1.13, p = 0.02); in patients with high polygenic scores for fat mass, lean mass, and lipoprotein A, risks were substantially elevated (HR:1.55, p = 4 × 10-5). Incorporating polygenic scores for adiposity and lipoprotein A may improve risk estimates of key clinical outcomes in CCB treatment such as treatment discontinuation and heart failure, compared to pharmacogenetic variants alone.

Influence of pharmacogenomic polymorphisms on allopurinol-induced cutaneous adverse drug reactions in Thai patients.

BACKGROUND: Allopurinol has been causing substantial morbidity and mortality particularly in Asian population by producing cutaneous adverse drug reactions (cADRs). Nonetheless, there are no data describing whether other genetics are a valid marker for prediction of allopurinol-induced cADRs patients in addition to HLA-B*58:01 allele. The goal of this study was to identify suitable single nucleotide polymorphisms (SNPs) for allopurinol induced cADRs among Thai patients. METHODS: We conducted a case-control association study after enrolling 57 Thai patients with allopurinol induced cADRs and 101 allopurinol-tolerant controls. The genetic biomarkers and associated SNPs located on chromosome 6p21 were examined by TaqMan® SNP genotyping assays in both the cases and the controls. RESULTS: Out of fifteen SNPs in nine genes, we found four combined SNPs (rs3099844 of HCP5, rs9263726 of PSORS1C1, rs9263733 of POLR2LP, and rs9263745 of CCHCR1) were significantly associated with allopurinol-induced cADRs compared to the tolerant controls (OR 73.2; 95% CI 24.2-266.8; P = 1.9 × 10- 24). The overall sensitivity, specificity, positive predictive value and negative predictive value of these combinations were 84%, 94%, 9%, and 100%, respectively. However, the variant alleles of these SNP combinations were detected in 89.5% (51/57) of the cases. Moreover, the HLA-B*58:01 allele was observed in 86.0% of patients with allopurinol-induced cADRs, but only in 4.0% of tolerant controls (OR: 137.2; 95% CI: 38.3-670.5 and p-value = 1.7 × 10- 27). CONCLUSIONS: Thus, this research confirms the association between the specific HLA-B*58:01 allele and all phenotypes of allopurinol-induced cADRs in Thais. Furthermore, there was found the combined four SNPs (rs3099844, rs9263726, rs9263733, and rs9263745) could be used as alternative novel biomarkers for predicting cADRs in patients taking allopurinol.