Pharmacogenetics and genomics最新文献

Objectives: Pharmacogenomic testing is rapidly becoming the standard of care in treating pediatric acute lymphoblastic leukemia (ALL). Risk classification of ALL can be performed through whole transcriptome sequencing (WTS) of diagnostic tumor samples. We evaluated the feasibility of inferring germline pharmacogenomic genotypes from the tumor transcriptome in ALL.

Methods: Transcriptome and paired tumor-germline genome sequencing data were collected from clinical testing at St. Jude Children's Research Hospital. Genotypes for pharmacogenes that are actionable for medications used in the management of pediatric ALL ( TPMT, NUDT15 , and G6PD ) were determined using a rule-based algorithm from transcriptome data. WTS-derived genotype calls were compared with germline genotypes obtained from whole genome sequencing (WGS) and clinical genotyping assays.

Results: Among 650 patients with ALL, 36 (5.5%) patients had somatic copy number loss on chromosomes 6, 13, or X, where TPMT , NUDT15 , and G6PD are located, respectively. For the remaining 614 patients, WTS provided thiopurine dosing guidance by calling both TPMT and NUDT15 diplotypes in 545 patients (83.8%). For G6PD , accurate genotyping was called for 367 male patients. We observed a greater than 99% concordance between tumor WTS and germline WGS diplotypes for all three genes.

Conclusion: The leukemia transcriptome can be used to provide accurate genotyping calls for select germline pharmacogenes actionable in the treatment of pediatric ALL.

In Canada, access to pharmacogenetic (PGx) testing remains limited, particularly outside of research institutions, and commercial testing is often cost-prohibitive. To address access challenges, several Canadian insurance providers have begun offering PGx test coverage; however, the extent and nature of this coverage remain unclear. This study systematically reviewed publicly available PGx coverage policies from Canadian insurance companies to evaluate eligibility requirements, affiliated laboratories, and clinical actionability of test panels. Ten Canadian insurers were identified with publicly accessible PGx testing policies. Six offered partial reimbursement or discounted pricing to all members, while four restricted full coverage to individuals meeting specific criteria, such as being on disability leave or having a physician's diagnosis. Eligibility requirements varied considerably, with some insurers requiring multiple conditions to be met. Four commercial laboratories were affiliated with insurers, but these labs differed substantially in the number of actionable genes and drugs tested. Our findings highlight substantial heterogeneity in insurer eligibility criteria and affiliate lab test comprehensiveness that may create inequities in access and quality of care. Furthermore, variability in insurance coverage may influence clinicians' willingness to recommend testing and patients' ability to access personalized therapy. These findings underscore the need for standardized PGx testing coverage policies and harmonized testing panels. Collaboration among insurers, researchers, and clinicians is essential to generating Canadian-specific evidence to guide equitable and clinically effective PGx implementation.

Background: Large consortia link variants in SLC22A1 , SLC47A1 , and GLP1R to antidiabetic response, yet few data confirm these effects in small real-world cohorts. We tested whether three common polymorphisms translate into measurable 3-month metabolic changes.

Methods: Twenty-seven Bulgarian adults with type 2 diabetes [BMI ≥ 25 kg/m²; mean glycated hemoglobin (HbA1c): 8.3 ± 0.9%] received metformin XR 2000 mg ( n  = 17) or oral semaglutide 14 mg ( n  = 10). Sanger sequencing identified SLC22A1 rs628031, SLC47A1 rs2252281, and GLP1R rs6923761. Primary endpoints were 3-month changes (Δ) in weight and HbA1c; analysis of variance and ordinary least squares regression assessed genotype and treatment effects, as well as covariate-adjusted linear models of 3-month change (Δ).

Results: Semaglutide produced greater weight loss than metformin [-6.5 ± 3.6 vs. -1.6 ± 2.5 kg; 95% confidence interval (CI) -7.6 to -2.2; P  = 0.001] and larger BMI reduction (-2.0 ± 1.2 vs. -0.3 ± 0.9 kg/m²; P  = 0.001). At an exploratory 10% FDR, only OCT1 rs34130495 dosage was associated with high-density lipoprotein (HDL) change in metformin-treated participants ( β = +0.340 mmol/L per minor allele; P  = 0.0026; q  = 0.063; N  = 16). GLP1R rs6923761 showed nominal trends for weight and BMI change in semaglutide users that did not survive FDR ( P  ≈ 0.06-0.07; q  ≈ 0.29; N  = 10).

Conclusion: Semaglutide outperformed metformin for short-term weight loss. An HDL signal for OCT1 rs34130495 at an exploratory 10% FDR warrants replication. These hypothesis-generating data support the feasibility of genotype-guided studies in local clinical settings.

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.

Background: Cytochrome P450 2D6 (CYP2D6) is a highly polymorphic drug-metabolizing enzyme involved in the metabolism of many clinically important medications. CYP2D6 is affected by genetic variation as well as drug interactions; however, this does not account for all the variability seen in CYP2D6. Previously, a single-nucleotide variant in the nuclear factor 1-B (NFIB), rs28379954 T>C, was linked to increased CYP2D6 activity and metabolism of CYP2D6 substrates. Thus, we investigated the effect of NFIB rs28379954 on the metabolism of CYP2D6 substrates, solanidine and tamoxifen.

Methods: Patients (N = 759) were genotyped for CYP2D6 genetic variants and NFIB rs28379954. Solanidine, tamoxifen, and their metabolites were measured with ultra-HPLC-tandem mass spectrometry.

Results: NFIB rs28379954 genotype (T/T versus T/C) was not associated with metabolism of solanidine to its CYP2D6-generated metabolites, 4-OH-solanidine or SSDA irrespective of CYP2D6 phenotype (poor metabolizer, intermediate metabolizer, or normal metabolizer; P > 0.05). Similarly, the ratio of endoxifen to tamoxifen was not affected by NFIB rs28379954 genotype in any CYP2D6 phenotypic group (P > 0.05). Multivariable linear regression modeling demonstrated that CYP2D6 phenotypes were associated with solanidine metabolic ratios as well endoxifen to tamoxifen ratios. However, the addition of NFIB genotype to the model did not significantly improve the predictability of solanidine or tamoxifen metabolites in plasma.

Conclusion: In conclusion, we did not observe any significant impact of NFIB rs28379954 genetic variation on CYP2D6 activity in vivo, when assessed using tamoxifen or solanidine metabolites as prototypical CYP2D6 substrates.

Objectives: Dyslipidemia is a crucial risk factor for atherosclerotic cardiovascular disease. Although rosuvastatin is widely used, treatment response varies significantly due to genetic variation. This study investigated the pharmacogenomic impact of low-density lipoprotein receptor (LDLR) 3' untranslated region (UTR) variants on rosuvastatin efficacy in a Chinese Han adult cohort with dyslipidemia.

Methods: A cohort of 113 Chinese participants receiving 10 mg rosuvastatin daily was sequenced for LDLR 3'UTR variants. Haploview was used to assess linkage disequilibrium (LD) patterns and haplotype structures. Multivariate regression modeling was employed to assess the influence of genetic variants on therapeutic outcomes.

Results: Seventeen LDLR 3'UTR variants were identified. A crosspopulation comparative assessment revealed significant variation in allele frequencies across distinct ethnic groups. Five variants (rs14158, rs2738466, rs5742911, rs17249057, and rs17249064) were in complete LD ( D ' = 1 and r2  = 1). CHANGE analysis revealed that rosuvastatin efficacy was significantly influenced by rs2738465, rs55903358, rs186461273, and rs751672818, while ANCOVA indicated that baseline triglycerides (TG), high-density lipoprotein cholesterol (HDL-C), and patient age, alongside rs2738467, rs143587805, and rs751672818 significantly impacted treatment response. Given the bias correction properties and well-established efficiency, results derived from ANCOVA were preferred. These findings were first reported, highlighting LDLR variants can be used as predictive markers for precision medicine for rosuvastatin in the Chinese population.

Conclusions: These findings highlight the role of LDLR 3'UTR as a critical pharmacogenomic locus. Our results advance understanding of genetic predictors for personalized statin therapy.

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.

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).