UNASSIGNED: Precise estimation of a patient\'s drug metabolism capacity is important for antiseizure dose personalization.
UNASSIGNED: To quantify the differences in plasma concentrations for antiseizure drugs associated with variants of genes encoding drug metabolizing enzymes.
UNASSIGNED: PubMed, Clinicaltrialsregister.eu, ClinicalTrials.gov, International Clinical Trials Registry Platform, and CENTRAL databases were screened for studies from January 1, 1990, to September 30, 2023, without language restrictions.
UNASSIGNED: Two reviewers performed independent study screening and assessed the following inclusion criteria: appropriate genotyping was performed, genotype-based categorization into subgroups was possible, and each subgroup contained at least 3 participants.
UNASSIGNED: The Meta-analysis of Observational Studies in Epidemiology (MOOSE) guidelines were followed for data extraction and subsequent quality, validity, and risk-of-bias assessments. The results from the included studies were pooled with random-effect meta-analysis.
UNASSIGNED: Plasma concentrations of antiseizure drugs were quantified with the dose-normalized area under the concentration-time curve, the dose-normalized steady state concentration, or the concentrations after a single dose at standardized dose and sampling time. The ratio of the means was calculated by dividing the mean drug plasma concentrations of carriers and noncarriers of the pharmacogenetic variant.
UNASSIGNED: Data from 98 studies involving 12 543 adult participants treated with phenytoin, valproate, lamotrigine, or carbamazepine were analyzed. Studies were mainly conducted within East Asian (69 studies) or White or European (15 studies) cohorts. Significant increases of plasma concentrations compared with the reference subgroup were observed for phenytoin, by 46% (95% CI, 33%-61%) in CYP2C9 intermediate metabolizers, 20% (95% CI, 17%-30%) in CYP2C19 intermediate metabolizers, and 39% (95% CI, 24%-56%) in CYP2C19 poor metabolizers; for valproate, by 12% (95% CI, 4%-20%) in CYP2C9 intermediate metabolizers, 12% (95% CI, 2%-24%) in CYP2C19 intermediate metabolizers, and 20% (95% CI, 2%-41%) in CYP2C19 poor metabolizers; and for carbamazepine, by 12% (95% CI, 3%-22%) in CYP3A5 poor metabolizers.
UNASSIGNED: This systematic review and meta-analysis found that CYP2C9 and CYP2C19 genotypes encoding low enzymatic capacity were associated with a clinically relevant increase in phenytoin plasma concentrations, several pharmacogenetic variants were associated with statistically significant but only marginally clinically relevant changes in valproate and carbamazepine plasma concentrations, and numerous pharmacogenetic variants were not associated with statistically significant differences in plasma concentrations of antiseizure drugs.

OBJECTIVE: The aim of this article was to perform a narrative review of how pharmacogenetics and pharmacogenomics is being applied in the clinics, especially in Spain.
METHODS: Publications and websites of major interest have been reviewed.
RESULTS: Pharmacogenes and variants used in several hospitals, available methodologies, and the implementation process are discussed.

OBJECTIVE: The aim of this article is to perform a narrative review of how pharmacogenetics and pharmacogenomics is being applied in the clinic, especially in Spain.
METHODS: Publications and websites of major interest have been reviewed.
RESULTS: Pharmacogenes and variants used in several hospitals, available methodologies, and the implementation process are discussed.

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 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.

Ramipril is an angiotensin-converting enzyme inhibitor used for hypertension and heart failure management. To date, scarce literature is available on pharmacogenetic associations affecting ramipril. The goal of this study was to investigate the effect of 120 genetic variants in 34 pharmacogenes (i.e., genes encoding for enzymes like CYPs or UGTs and transporters like ABC or SLC) on ramipril pharmacokinetic variability and adverse drug reaction (ADR) incidence. Twenty-nine healthy volunteers who had participated in a single-dose bioequivalence clinical trial of two formulations of ramipril were recruited. A univariate and multivariate analysis searching for associations between genetic variants and ramipril pharmacokinetics was performed. SLCO1B1 and ABCG2 genotype-informed phenotypes strongly predicted ramipril exposure. Volunteers with the SLCO1B1 decreased function (DF) phenotype presented around 1.7-fold higher dose/weight-corrected area under the curve (AUC/DW) than volunteers with the normal function (NF) phenotype (univariate p-value [puv] < 0.001, multivariate p-value [pmv] < 0.001, β = 0.533, R2 = 0.648). Similarly, volunteers with ABCG2 DF + poor function (PF) phenotypes presented around 1.6-fold higher AUC/DW than those with the NF phenotype (puv = 0.011, pmv < 0.001, β = 0.259, R2 = 0.648). Our results suggest that SLCO1B1 and ABCG2 are important transporters to ramipril pharmacokinetics, and their genetic variation strongly alters its pharmacokinetics. Further studies are required to confirm these associations and their clinical relevance.

暂无摘要。

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.

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.

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.