Pharmacogenetics and genomics最新文献

Background: Dehydroepiandrosterone (DHEA) is considered an endogenous steroid hormone precursor, and 17-ß estradiol (E2) is one of the estrogen steroid hormones. Of the 13 known human cytosolic sulfotransferases (SULTs), SULT2B1a has been shown to be expressed in steroid hormone-responsive tissues such as the prostate, ovary, and placenta, as well as the fetal brain. Previous studies have demonstrated that SULT2B1a is capable of sulfating 3β-hydroxysteroids such as DHEA and pregnenolone. The present study aimed to investigate the effects of human SULT2B1 single-nucleotide polymorphisms (SNPs) on the enzymatic characteristics of SULT2B1a allozymes in mediating the sulfation of DHEA and E2.

Methods: To inspect the effects of SNPs of the SULT2B1 gene on the sulfation of DHEA and E2 by SULT2B1a allozymes, 13 recombinant SULT2B1a allozymes were produced, expressed, and purified using established procedures. Thirteen SULT 2B1a nonsynonymous missense coding SNPs (cSNPs) were selected among numerous identified human SULT 2B1a SNPs by a comprehensive database search. The corresponding cDNAs, packaged in pGEX-2TK expression vector, and encoding the selected 13 SULT2B1a allozymes, have been generated by performing site-directed mutagenesis. These were then bacterially expressed in BL21 E. coli cells and purified using glutathione-Sepharose affinity chromatography. The purified allozymes were tested for their ability to sulfonate DHEA and E2.

Results: In terms of the kinetic parameters, the wild-type SULT2B1a exhibited higher enzyme affinity toward DHEA than with E2. In comparison with the wild-type SULT2B1a, the purified allozymes displayed differential sulfating activities toward DHEA and E2.

Conclusion: Accordingly, these findings indicate an apparent effect of SULT2B1 cSNPs on the sulfating activities of SULT2B1a allozymes toward DHEA and E2, and may provide for a better understanding of the pharmacokinetics of DHEA and E2 in individuals with differing SULT2B1a genotypes.

Objective: The pathogenic mechanisms of antituberculosis drug-induced liver injury (AT-DILI) remain unclear. Isoniazid and rifampicin may lead to hepatic accumulation of protoporphyrin IX in which heme synthesis ferrochelatase (FECH), a key rate-limiting enzyme, potentially plays an important role. This study aimed to investigate the combined effects of FECH gene polymorphisms and promoter methylation on AT-DILI risk in the Eastern Chinese population.

Methods: A 1 : 1 matched case-control study was conducted, detecting one CpG island in the FECH promoter and four single-nucleotide polymorphisms (SNPs). A multivariate conditional logistic regression was used to estimate the association between genotypes and the risk of AT-DILI by the odds ratios (OR) with 95% confidence intervals (CIs). Additive and multiplicative interactions between methylation status and SNPs were further analyzed: additive interactions via the relative excess risk due to interaction (RERI) with 95% CIs, and multiplicative interactions by incorporating methylation-SNP product terms into regression models.

Results: Overall, 182 cases and 182 controls were included. Neither FECH promoter methylation (adjusted OR: 0.978, 95% CI: 0.408-1.560, P  = 0.509) nor the four SNPs showed individual associations with AT-DILI risk ( P  > 0.05). Crossover analyses revealed no significant genotype-methylation interactions ( P  > 0.05). Both additive (rs17063905 RERI: -0.556, P  = 0.691) and multiplicative interaction models (rs17063905, OR: 0.723, P  = 0.615) demonstrated no synergistic effects between methylation and polymorphisms.

Conclusion: This research finds no significant association between FECH promoter methylation status in the CpG island, polymorphisms, or their interactions and the risk of AT-DILI.

Background: Pharmacogenetic testing plays a key role in personalized pharmacotherapy and improving treatment outcomes; however, its benefit in clinical hyperpolypharmacy (≥ 10 chronic drugs) remains uncertain.

Objective: This study assessed the impact of extensive pharmacogenetic testing in hyperpolypharmacy patients. The primary outcome was the number of actionable drug-gene interactions (DGIs) per patient; secondary outcomes included clinical recommendations, clinician adherence, and DGIs with potential for severe adverse events.

Design: This intervention included 100 hyperpolypharmacy inpatients (≥ 10 drugs) from Maasstad Hospital internal ward and Antes psychiatry ward. Eligible patients (≥ 18 years) underwent a 14-gene pharmacogenetic panel test. A multidisciplinary team reviewed drug-gene interactions (DGIs), evaluated medical records, and implemented monitoring or medication adjustments as needed.

Results: An average of 4.7 (interquartile range: 4.0-5.5) actionable variants in the tested pharmacogenes per patient was identified, resulting in at least one DGI in 46% of the patients, with an average of 0.6 DGI per patient. After evaluation by the multidisciplinary team, 12 out of 64 DGIs (19%) led to recommendations for interventions, with an adherence rate of 67%. In 5% of patients, the identified DGI could potentially be associated with a higher risk of hospitalization or mortality.

Conclusion: Systematic pharmacogenetic panel testing in clinical hyperpolypharmacy patients identified at least one DGI in 46% of the patients. Of these DGIs, 19% led to a recommendation for intervention. This study demonstrates that pharmacogenetic panel testing holds the potential to optimize pharmacotherapy in clinical hyperpolypharmacy patients.

Objective: This study examined the impact of glutathione- S -transferase polymorphisms (GSTA1, GSTM1, GSTP1, and GSTT1) on the area under the curve (AUC), clearance, veno-occlusive disease (VOD), and graft-versus-host disease (GvHD) in hematopoietic stem cell transplant (HSCT) patients treated with intravenous busulfan.

Methods: A systematic review was performed on three electronic databases to identify relevant studies. The relative risk and the 95% confidence interval (CI) of the association of different GST polymorphisms with pharmacokinetic and clinical outcomes were reported using the random and fixed effect models. Quality of the studies was assessed using the Newcastle-Ottawa Scale for cohort studies. Heterogeneity between studies and publication bias were also carried out using R software.

Results: Eighteen studies were included in the meta-analysis. GSTA1*A/*B was significantly associated with lower clearance (95% CI: 0.008-1.223, P = 0.048) and higher AUC (95% CI: -374.960 to -56.661, P = 0.008) than the GSTA1*A/*A genotype. GSTA1*B/*B had a higher busulfan AUC than GSTA1*A/*A (95% CI: -403.531 to -89.454, P = 0.002). None of the other genotypes was significantly associated with busulfan pharmacokinetic parameters or the risk of VOD or GvHD.

Conclusion: GSTA1 should be considered as a guide for intravenous busulfan dosing in allogeneic HSCT patients, where patients with the GSTA1*A/*A genotype require a higher dose than GSTA1*B carriers.

Pharmacogenomics (PGx) is a scientific field that aims to understand how an individual's genetic code regulates drug metabolism and response. The response to many anesthetic drugs varies widely among patients due to many factors including, but not limited to, age, gender, and comorbidities. However, PGx contributes to this variability, particularly regarding adverse drug reactions. This review explores the influence of PGx on five commonly used induction agents in anesthesia: propofol, midazolam, ketamine, etomidate, and thiopental. Propofol metabolism is significantly affected by polymorphisms in CYP2B6, CYP2C9, and UGT1A9, influencing both efficacy and toxicity. Midazolam's PGx is mainly mediated by variations in CYP3A4, CYP3A5, and UDP-glucuronosyltransferase enzymes, with implications for sedation depth and drug clearance. Ketamine response is modulated by polymorphisms in metabolic enzymes (e.g. CYP2B6), as well as neurobiological targets such as brain-derived neurotrophic factor and gamma-aminobutyric acid (GABA) receptors, particularly in psychiatric applications. Etomidate shows less studied but emerging PGx associations, including single-nucleotide polymorphisms in GABA receptor subunits and metabolic enzymes, which may affect both sedative depth and cardiovascular stability. Thiopental is a rapid-acting metabolite whose effect stems from GABA-A receptor potentiation; no studies have yet identified specific genetic polymorphisms influencing its action. Overall, PGx provides a promising avenue for tailoring anesthetic management to improve patient safety and outcomes. However, clinical integration remains limited due to practical and infrastructural barriers. This review highlights the potential and current limitations of pharmacogenomic-guided anesthesia, underscoring its relevance in the era of precision medicine.

Background: Major depressive disorder (MDD) and bipolar disorder (BD) are common, disabling conditions. Despite associated morbidity and premature mortality, current treatments have modest efficacy and response to treatment highly variable. Contributing factors to variability in response include influence of common genetic variations in the pharmacokinetic and/or pharmacodynamic action of medications. As such, attention has turned toward the identification of genetic markers that could assist with determining who will respond or not to psychotropic treatment. Results of studies to date are promising but primarily have been small. This study aims to evaluate the efficacy of a pharmacogenetic (PGx)-based decision support tool among adults with MDD and BD.

Methods: This single-site, single (rater) blinded, randomized controlled trial with two arms evaluates the 24-week efficacy of a PGx-based support tool for adults with MDD or BD. Participants are randomized to receive PGx testing or standard prescribing. Participants provide DNA samples at baseline, but only those (including clinicians) randomized to the former receive the results at the start of their study participation. It is not mandatory for clinicians to follow the test recommendations. Remission rate (primary outcome), change in depression symptoms, drop-out rate, medication adherence, and medication side effects (secondary outcomes) are assessed at 4-, 8-, 12-, and 24-week postbaseline by a blinded rater. Analyses will follow an intention-to-treat approach and use mixed models for repeated measures.

Discussion: Treatment response to medication for severe mood disorders is highly variable and less than optimal. This trial will provide evidence as to whether a PGx-based support tool is an efficacious strategy to inform selection and dosing of pharmacotherapy among adults with severe mood disorders. Importantly, it will do so independently and with a larger sample size than previous studies.

Trial registration: This trial is registered under the number ACTRN12621001374853 (11 Oct 2021).

Objective: To characterize the allelic and diplotype variability of TPMT and NUDT15 in pediatric patients with B-cell acute lymphoblastic leukemia from the central-southern region of Mexico.

Methods: Samples from 275 pediatric B-cell acute lymphoblastic leukemia patients were analyzed. Next-generation sequencing was used for TPMT and NUDT15 genotyping. Alleles and diplotypes were assessed according to the Clinical Pharmacogenetics Implementation Consortium guidelines. Their geographic distribution was compared across Mexican states and global populations. In-silico analyses were conducted to assess the structural and functional impact of TPMT variants not associated with star alleles.

Results: The wild-type *1 allele, associated with normal enzymatic activity, was predominant in both genes: TPMT (94.15%) and NUDT15 (90.45%). TPMT showed greater allelic diversity compared with previous studies in Mexican populations. Alleles conferring absent or indeterminate enzymatic activity in TPMT were distributed across six diplotypes (11.62%), with *3A allele (4.73%) and *1/*3A diplotype (9.45%) being the most frequent. Additionally, two unclassified TPMT variants, p.G126A and p.D137Y, were identified. For NUDT15, three non-wild-type diplotypes were observed (19.09%), with the *2 allele (6.74%) and *1*/2 diplotype (13.48%) being the most prevalent.

Conclusion: Approximately 28% of patients carried TPMT and/or NUDT15 variants associated with non-wild-type enzymatic activity, increasing the risk of mercaptopurine-induced myelotoxicity. Preemptive genotyping is essential to reduce toxicity, optimize treatment, and advance precision medicine in this population. Additionally, the two TPMT variants p.G126A and p.D137Y, currently not classified within Clinical Pharmacogenetics Implementation Consortium-defined star alleles, highlight the need for functional validation and potential clinical classification to improve pharmacogenetic interpretation in diverse populations.

Posaconazole is used to treat and prevent invasive fungal infections. Posaconazole metabolism is mediated by the uridine 5'-diphopho-glucuronosyltransferase (UGT) 1A4 enzyme; prior studies have suggested UGT1A4*3 contributes to low posaconazole exposure, while the impact of UGT1A4*2 is unclear. This study aimed to further understand the relationship between posaconazole exposure and UGT1A4 genotypes. Steady-state posaconazole plasma concentrations (PPCs) and demographics of patients who received the oral tablet formulation of posaconazole were collected, retrospectively, regardless of the patient's underlying diagnoses. UGT1A4 genotypes were obtained from the institutional research biorepository. The patients' dose-controlled PPCs, PPCs, and clinical PPC categorizations by institutional prophylaxis and treatment targets were analyzed among UGT1A4 genotypes. Breakthrough infection data were also collected in patients receiving posaconazole prophylaxis. A total of 103 patients were included, with 21 (20.3%) UGT1A4 *1/*3, 76 (73.7%) UGT1A4 *1/*1, and 6 (5.8%) UGT1A4 *1/*2. The dose-controlled PPCs [(ng/ml)/(mg/day)] were 3.63 (2.45-6.92) for UGT1A4 *1/*3, 5.07 (3.04-7.11) for *1/*1, and 4.92 (2.89-6.12) for *1/*2 (P = 0.62). Additionally, no statistically significant differences in median PPC or clinical PPC prophylaxis and treatment classifications were found among UGT1A4 genotypes. One UGT1A4 *1/*3 and two *1/*1 patients experienced possible breakthrough fungal infections. This study did not confirm the previously reported association between UGT1A4*3 and reduced posaconazole exposure and found no association with UGT1A4*2. Further studies are needed to determine the impact of homozygous UGT1A4 variants on posaconazole exposure.

Objective: To investigate the effects of SLCO1B1, apolipoprotein E (APOE) and ABCG2 gene polymorphisms on the lipid-modulating efficacy of rosuvastatin.

Methods: Systematic searches were conducted in PubMed, Cochrane Library, Embase, Web of Science, PharmGKB, CNKI, VIP, and Wanfang databases (from database establishment to 1 March 2025). Studies on the correlation between SLCO1B1, APOE, ABCG2 gene polymorphisms and the lipid-modulating efficacy of rosuvastatin were collected, and meta-analysis was performed using RevMan 5.4 software.

Results: A total of 16 studies involving 6167 patients were included, covering APOE (p.C130R/rs429358, p.R176C/rs741), SLCO1B1 (p.V174A/rs4149056, p.N130D/rs2306283), and ABCG2 (p.Q141K/rs2231142) genes. The results showed that SLCO1B1 [AG+GG vs. AA, mean difference = -4.36, 95% confidence interval (CI): -7.92 to -0.80, P = 0.02], APOE (E2 vs. E3, mean difference = -5.58, 95% CI: -8.04 to -2.51, P < 0.00001] and ABCG2 (CA+AA vs. CC, mean difference = -7.07, 95% CI: -9.47 to -4.68, P < 0.00001) genotypes all significantly affected statin-induced low-density lipoprotein cholesterol (LDL-C) reduction; patients with ABCG2 CA+AA genotype had statistically significant differences in total cholesterol level changes (mean difference = -7.15, 95% CI: -8.78 to -5.53) and triglyceride level changes (mean difference = -7.37, 95% CI: -10.91 to -3.83) (both P < 0.05).

Conclusion: The lipid-lowering efficacy of rosuvastatin (especially the reduction of LDL-C level) is significantly affected by the polymorphisms of SLCO1B1 (c.388A>G), ApoE (c.388T>C, c.526C>T) and ABCG2 (c.421C>A) genes.