Pharmacogenetics and genomics最新文献

CYP2D6 is a highly polymorphic gene with clinically important structural variations. Commonly, only exon 9 is assayed on clinical pharmacogenomics panels, as it allows for accurate functional characterization even in the presence of a CYP2D6::CYP2D7 conversion. However, this method does not capture CYP2D7::CYP2D6 (CYP2D6*13) conversions, possibly leading to inaccurate phenotype assignment. The study's purpose was to determine the frequency of structural variations in CYP2D6 utilizing multiple copy number variation (CNV) assay locations to quantify the potential impact on clinical phenotype classification. A retrospective analysis was conducted of de-identified pharmacogenomics data submitted through the Translational Software, Inc. platform. Samples with CYP2D6 CNV data for exon 9 and at least one additional CNV location (5'UTR, exon 1, intron 2, exon 5 or intron 6) were included. CYP2D7::CYP2D6 and CYP2D6::CYP2D7 conversions were classified according to PharmVar nomenclature. The CYP2D6 copies were capped at four total copies to account for assay limitations in detecting more than four copies. A total of 106,474 samples were included for analysis. CYP2D7::CYP2D6 conversions were present in approximately 2.44% of samples, and 5.84% of samples had CYP2D6::CYP2D7 conversions. Many samples did not have a CYP2D7 conversion detected (91.5%; 97,462/106,474). A full gene deletion was detected in 0.15%, and 5.98% had a duplication or multiplication present. This retrospective study underscores the importance of testing more than one CNV site for CYP2D6 . Over 2% of patients were found to have a CYP2D7::CYP2D6 conversion. This translates into potentially misclassified phenotype classification and incongruent clinical recommendations.

The use of genome-wide genotyping arrays in pharmacogenomics (PGx) research and clinical implementation applications is increasing but it is unclear which arrays are best suited for these applications. Here, we conduct a comparative coverage analysis of PGx alleles included on genome-wide genotyping arrays, with an emphasis on alleles in genes with PGx-based prescribing guidelines. Genomic manifest files for seven arrays including the Axiom Precision Medicine Diversity Array (PMDA), Axiom PMDA Plus, Axiom PangenomiX, Axiom PangenomiX Plus, Infinium Global Screening Array, Infinium Global Diversity Array (GDA) and Infinium GDA with enhanced PGx (GDA-PGx) Array, were evaluated for coverage of 523 star alleles across 19 pharmacogenes included in prescribing guidelines developed by the Clinical Pharmacogenetic Implementation Consortium and Dutch Pharmacogenomics Working Group. Specific attention was given to coverage of the Association of Molecular Pathology's Tier 1 and Tier 2 allele sets for CYP2C9, CYP2C19, CYP2D6, CYP3A4, CYP3A5, NUDT15, TPMT and VKORC1 . Coverage of the examined PGx alleles was highest for the Infinium GDA-PGx (88%), Axiom PangenomiX Plus (77%), Axiom PangenomiX (72%) and Axiom PMDA Plus (70%). Three arrays (Infinium GDA-PGx, Axiom PangenomiX Plus and Axiom PMDA Plus) fully covered the Tier 1 alleles and the Axiom PangenomiX array provided full coverage of Tier 2 alleles. In conclusion, PGx allele coverage varied by gene and array. A superior array for all PGx applications was not identified. Future comparative analyses of genotype data produced by these arrays are needed to determine the robustness of the reported coverage estimates.

Objectives: Genetic variation has been a major contributor to interindividual variability of warfarin dosage requirement. The specific genetic factors contributing to warfarin bleeding complications are largely unknown, particularly in Chinese patients. In this study, 896 Chinese patients were enrolled to explore the effect of CYP2C9 and VKORC1 genetic variations on both the efficacy and safety of warfarin therapy.

Methods and results: Univariate analyses unveiled significant associations between two specific single nucleotide polymorphisms rs1057910 in CYP2C9 and rs9923231 in VKORC1 and stable warfarin dosage ( P  < 0.001). Further, employing multivariate logistic regression analysis adjusted for age, sex and height, the investigation revealed that patients harboring at least one variant allele in CYP2C9 exhibited a heightened risk of bleeding events compared to those with the wild-type genotype (odds ratio = 2.16, P  = 0.04). Moreover, a meta-analysis conducted to consolidate findings confirmed the associations of both CYP2C9 (rs1057910) and VKORC1 (rs9923231) with stable warfarin dosage. Notably, CYP2C9 variant genotypes were significantly linked to an increased risk of hemorrhagic complications ( P  < 0.00001), VKORC1 did not demonstrate a similar association.

Conclusion: The associations found between specific genetic variants and both stable warfarin dosage and bleeding risk might be the potential significance of gene detection in optimizing warfarin therapy for improving patient efficacy and safety.

Third-generation aromatase inhibitors (AI) are the standard treatment for patients with hormone receptor positive (HR+) breast cancer. While effective, AI can lead to severe adverse events, including AI-induced musculoskeletal syndrome (AIMSS). Genetic predictors of AIMSS have the potential to personalize AI treatment and improve outcomes. We attempted to replicate results from a previous genome-wide association study that found a lower risk of AIMSS in patients carrying PPP1R14C rs912571 and a higher risk in patients carrying CCDC148 rs79048288. AIMSS data were collected prospectively from patients with HR+ breast cancer prior to starting and after 3 and 6 months of adjuvant AI via the Patient-Reported Outcome Measurement Information System and Functional Assessment of Cancer Therapy-Endocrine Symptom. Germline genotypes for PPP1R14C rs912571 and CCDC148 rs79048288 were tested for a similar association with AIMSS as previously reported via $2 tests. Of the 143 patients with AIMSS and genetics data were included in the analysis. There was no association identified between PPP1R14C rs912571 and AIMSS risk ( P  > 0.05). Patients carrying CCDC148 rs79048288 variant alleles had lower AIMSS incidence in a secondary analysis ( P  = 0.04); however, this was in the opposite direction of the previous finding. The study did not replicate previously reported associations with AIMSS risk for genetic variants in PPP1R14C and CCDC148 and AIMSS risk. Further research is needed to discover and validate genetic predictors of AIMSS that can be used to personalize treatment in patients with HR+ breast cancer.

Objective: We aim to develop a personalized dosing tool for tricyclic antidepressants (TCAs) that integrates CYP2D6 and CYP2C19 gene variants and their effects while also considering the polypharmacy effect.

Methods: The study first adopted a scoring system that assigns weights to each genetic variant. A formula was then developed to compute the effect of both genes' variants on drug dosing. The output of the formula was assessed by a comparison with the clinical pharmacogenetics implementation consortium recommendation. The study also accounts for the effect of the co-administration of inhibitors and inducers on drug metabolism. Accordingly, a user-friendly tool, Clinical Dosing Tool ver.2, was created to assist clinicians in dosing patients on TCAs.

Results: The study provides a comprehensive list of all alleles with corresponding activity values and phenotypes for both enzymes. The tool calculated an updated area under the curve ratio that utilizes the effects of both enzymes' variants for dose adjustment. The tool provided a more accurate individualized dosing that also integrates the polypharmacy effect.

Conclusion: To the best of our knowledge, the literature misses such a tool that provides a numerical adjusted dose based on continuous numerical activity scores for the considered patients' alleles and phenoconversion.

Known genetic variations in dihydropyrimidine dehydrogenase (gene name DPYD ) do not fully predict patients at risk for severe fluoropyrimidine-associated chemotherapy toxicity. Dihydropyrimidinase (gene name DPYS ), the second catabolic enzyme in fluoropyrimidine metabolism, has been noted as a potential determinant of variation in fluoropyrimidine metabolism and response. In this study, we genotyped for DPYS c.-1T>C (rs2959023), c.265-58T>C (rs2669429) and c.541C>T (rs36027551) in a Canadian cohort of 248 patients who were wild type for Clinical Pharmacogenetics Implementation Consortium recommended DPYD variants and had received a standard dose of fluoropyrimidine chemotherapy. None of our patients were found to carry the DPYS c.541C>T variant, while the minor allele frequencies were 63% and 54% for c.-1T>C and c.265-58T>C, respectively. There was no association between DPYS c.-1T>C wild type and heterozygote [odds ratio (OR) (95% confidence interval, CI) = 1.10 (0.51-2.40)] or homozygote variant carriers [OR (95% CI) = 1.22 (0.55-2.70)], or between DPYS c.265-58T>C wild-type patients and heterozygote [OR (95% CI) = 0.93 (0.48-1.80)] or homozygote variant carriers [OR (95% CI) = 0.76 (0.37-1.55)] in terms of fluoropyrimidine-associated toxicity. Therefore, in our cohort of mostly Caucasian Canadians, genetic variations in DPYS do not appear to be a significant contributor to severe fluoropyrimidine-associated toxicity.

Objective: The impact of CYP2C19 genotype on clopidogrel outcomes is one of the most well established pharmacogenetic interactions, supported by robust evidence and recommended by the Food and Drug Administration and clinical pharmacogenetics implementation consortium. However, there is a scarcity of large-scale real-world data on the extent of this pharmacogenetic effect, and clinical testing for the CYP2C19 genotype remains infrequent. This study utilizes the UK Biobank dataset, including 10 365 patients treated with clopidogrel, to offer the largest observational analysis of these pharmacogenetic effects to date.

Methods: Incorporating time-varying drug exposure and repeated clinical outcome, we adopted semiparametric frailty models to detect and quantify exposure-based effects of CYP2C19 (*2,*17) variants and nongenetic factors on the incidence risks of composite outcomes of death or recurrent hospitalizations due to major adverse cardiovascular events (MACE) or hemorrhage in the entire cohort of clopidogrel-treated patients.

Results: Out of the 10 365 clopidogrel-treated patients, 40% (4115) experienced 10 625 MACE events during an average follow-up of 9.23 years. Individuals who received clopidogrel (coverage >25%) with a CYP2C19*2 loss-of-function allele had a 9.4% higher incidence of MACE [incidence rate ratios (IRR), 1.094; 1.044-1.146], but a 15% lower incidence of hemorrhage (IRR, 0.849; 0.712-0.996). These effects were stronger with high clopidogrel exposure. Conversely, the gain-of-function CYP2C19*17 variant was associated with a 5.3% lower incidence of MACE (IRR, 0.947; 0.903-0.983). Notably, there was no evidence of *2 or *17 effects when clopidogrel exposure was low, confirming the presence of a drug-gene interaction.

Conclusion: The impact of CYP2C19 on clinical outcomes in clopidogrel-treated patients is substantial, highlighting the importance of incorporating genotype-based prescribing into clinical practice, regardless of the reason for clopidogrel use or the duration of treatment. Moreover, the methodology introduced in this study can be applied to further real-world investigations of known drug-gene and drug-drug interactions and the discovery of novel interactions.