Pharmacogenomics最新文献

Determining variant TPMT alleles to predict patient response to thiopurine therapy represents one of the first successful implementations of pharmacogenomics in clinical practice. However, despite the TPMT-adjusted thiopurine dosing, some TPMT wild-type patients still exhibit toxicity at standard doses. Over the past decade, the pharmacogene NUDT15 has emerged as a significant co-modulator of thiopurine therapy. Initially, NUDT15 was considered important predominantly in Asian populations, but recent studies have highlighted its relevance in European populations as well.To evaluate the pharmacogenetic significance of NUDT15 in the Slovenian population, we sequenced extended regions of exon 1 and exon 3 in 109 healthy individuals and 37 patients with acute lymphoblastic leukemia.We identified eight variants, including one with established clinical significance (allele *3) and one extremely rare variant (Chr13 at 48045861; GRCh38, NC_000013.11). The frequencies of most previously described variants in both the general population and in the ALL cohort were consistent with those reported in other European populations, except for rs45465203, which was less frequent in the Slovenian population. None of the variants, except for NUDT15*3, were associated with cumulative thiopurine doses in ALL patients. However, these variants warrant further investigation in larger ALL cohorts.

Artificial Intelligence (AI) and Machine Learning (ML) are revolutionizing various scientific and clinical disciplines including pharmacogenomics (PGx) by enabling the analysis of complex datasets and the development of predictive models. The integration of AI and ML with PGx has the potential to provide more precise, data-driven insights into new drug targets, drug efficacy, drug selection, and risk of adverse events. While significant effort to develop and validate these tools remain, ongoing advancements in AI technologies, coupled with improvements in data quality and depth is anticipated to drive the transition of these tools into clinical practice and delivery of individualized treatments and improved patient outcomes. The successful development and integration of AI-assisted PGx tools will require careful consideration of ethical, legal, and social issues (ELSI) in research and clinical practice. This paper explores the intersection of PGx with AI, highlighting current research and potential clinical applications, and ELSI including privacy, oversight, patient and provider knowledge and acceptance, and the impact on patient-provider relationship and new roles.

Tweetable abstract Update on the genetic variants with the highest level of Pharmacogenomics Knowledge Base evidence for their association with toxicity and efficacy in response to the most commonly used disease-modifying antirheumatic drugs for the treatment of rheumatoid arthritis.

Calcineurin inhibitors (CNIs) are the mainstay of immunosuppression in kidney transplantation. Interpatient variability in the disposition of calcineurin inhibitors is a well-researched phenomenon and has a well-established genetic contribution. There is great diversity in the makeup of African genomes, but very little is known about the pharmacogenetics of CNIs and transplant outcomes. This review focuses on genetic variants of calcineurin inhibitors' metabolizing enzymes (CYP3A4, CYP3A5), related molecules (POR, PPARA) and membrane transporters involved in the metabolism of calcineurin inhibitors. Given the genetic diversity across the African continent, it is imperative to generate pharmacogenetic data, especially in the era of personalized medicine and emphasizes the need for studies specific to African populations. The study of allelic variants in populations where they have greater frequencies will help answer questions regarding their impact. We aim to fill the knowledge gaps by reviewing existing research and highlighting areas where African research can contribute.

Aim: The study aimed to examine the association of two selected candidate SNPs rs2242480 (CYP3A4) and rs1045642 (ABCB1) with metabolic ratio of plasma norfentanyl to fentanyl concentrations in patients undergoing major breast surgeries.

Methods: The retrospective cross-sectional study was done in 257 female patients. DNA extraction, genotyping of selected SNPs, and drug levels measurement were employed.

Results: A total of 257 female patients were recruited with no loss to follow up. There was no significant association between the two mentioned SNPs and the metabolic ratio (p value > 0.05). As an exploratory analysis, there was a moderately significant negative correlation between metabolic ratio and pupillary constriction to fentanyl (r = -0.27; p < 0.001). There was also a weak but significant positive correlation between metabolic ratio and time for first analgesia in the postoperative period (r = 0.17; p = 0.01).

Conclusion: There was no significant association with the selected candidate SNPs in CYP3A4 and ABCB1 genes and metabolic ratio of norfentanyl to fentanyl in South Indian patients undergoing major breast surgery.

Aim: To investigate the association of DNA methylation, genetic polymorphisms and mRNA level of aminolevulinate synthase 1 (ALAS1) with antituberculosis drug-induced liver injury (AT-DILI) risk.Methods: Based on a 1:1 matched case-control study with 182 cases and 182 controls, one CpG island and three single nucleotide polymorphisms (SNPs) were detected. ALAS1 mRNA level was detected in 34 samples.Results: Patients with methylation status were at high risk of AT-DILI (odds ratio: 1.567, 95% CI: 1.015-2.421, p = 0.043) and SNP rs352169 was associated with AT-DILI risk (GA vs. GG, odds ratio: 1.770, 95% CI: 1.101-2.847, p = 0.019). ALAS1 mRNA level in the cases was significantly lower than that in the controls (0.75 ± 0.34 vs. 1.00 ± 0.42, p = 0.021).Conclusion: The methylation status and SNP rs352169 of ALAS1 were associated with AT-DILI risk.

This study aims to use machine learning model to predict laboratory aspirin resistance (AR) in Chinese stroke patients by incorporating patient characteristics and single nucleotide polymorphisms of GP1BA and LTC4S. 2405 patients were analyzed to measure the Mutation frequency of GP1BA rs6065 and LTC4S rs730012. 112 patients with first-stroke arteriostenosis were prospectively enrolled to establish machine learning model. GP1BA rs6065 mutation frequency is 5.26% and LTC4S rs730012 is 14.78%. GP1BA rs6065 CT patients have more sensitivity to aspirin than CC genotype. Simple linear regression identified significant associations with age, smoking, HDL and GP1BA rs6065. Random forest (RF) and extreme gradient boosting (XGBoost) demonstrated predictive capabilities for AR. Findings suggest pre-identifying GP1BA rs6065 could optimize aspirin treatment, enabling personalized care and future research avenues.

Background: Our objective was to explore the pharmacogenetic impact of three known functional variants in drug target genes and determine whether they can explain the inter-individual variation in therapeutic response.

Methods: In a post hoc analysis of data from randomized controlled clinical trials of chiglitazar, we genotyped 481 Chinese patients with T2DM and investigated the association of variants in PPAR genes with the therapeutic outcome separated by dose using linear regression.

Results: rs1800234, a gain-of-function variant of PPARA, had a dose-dependent pharmacogenetic impact on the therapeutic response to chiglitazar. The C allele was significantly associated with reduced therapeutic response in the 48 mg group, while no significant association was observed in the 32 mg group. In addition, in patients without the C allele, patients treated with 48 mg chiglitazar had a better therapeutic response than those treated with 32 mg chiglitazar. To the contrary, in patients with the C allele, patients treated with 48 mg chiglitazar had a worse therapeutic response than those treated with 32 mg of chiglitazar.

Conclusion: The PPARA variant rs1800234 had a dose-dependent pharmacogenetic impact on the therapeutic response to chiglitazar. It could help explain the absence of a dose effect of chiglitazar and serve as a potential biomarker for the chosen dose of chiglitazar in the future. In addition, our study provided important reference for the design and clinical application of multi-target drugs.

Aim: Successful treatment with tacrolimus to prevent graft versus host disease (GVHD) and minimize tacrolimus-related toxicities among allogeneic hematopoietic cell transplantation (alloHCT) recipients is contingent upon quickly achieving and maintaining concentrations within a narrow therapeutic range. The primary objective was to investigate associations between CYP3A4, CYP3A5 or ABCB1 genotype and the proportion of patients that attained an initial tacrolimus goal concentration following initiation of intravenous (iv.) and conversion to oral administration. Materials & methods: We retrospectively evaluated 86 patients who underwent HLA-matched (8/8) related donor alloHCT and were prescribed a tacrolimus-based regimen for GVHD prophylaxis. Results & conclusion: The findings of the present study suggests that CYP3A5 genotype may impact attainment of initial therapeutic tacrolimus concentrations with oral administration in alloHCT recipients.

An increasing number of economic evaluations are published annually investigating the economic effectiveness of pharmacogenomic (PGx) testing. This work was designed to provide a comprehensive summary of the available utility methods used in cost-effectiveness/cost-utility analysis studies of PGx interventions. A comprehensive review was conducted to identify economic analysis studies using a utility valuation method for PGx testing. A total of 82 studies met the inclusion criteria. A majority of studies were from the USA and used the EuroQol-5D questionnaire, as the utility valuation method. Cardiovascular disorders was the most studied therapeutic area while discrete-choice studies mainly focused on patients' willingness to undergo PGx testing. Future research in applying other methodologies in PGx economic evaluation studies would improve the current research environment and provide better results.