Pharmacogenomics最新文献

Background: Green tea extract was tested for the secondary prevention of colorectal adenoma in the placebo-controlled MIRACLE trial. Genome-wide screening on adenoma recurrence was performed in n = 550 participants 3 years after randomization to green tea or placebo intake.

Methods: Single Marker Analysis followed by regression analyses was calculated for all 700.078 markers assuming an additive genetic model and including all covariates from the main MIRACLE trial analysis. The outcome was an adenoma rate at 3-year follow-up colonoscopy comparing participants carrying a genetic variant versus wildtype.

Results: The gene showing the strongest association with the outcome in both, SMA as well as regression analysis, was the organic anion transporter SLCO1A2. In the variant carriers, the adenoma frequency was 41.4% in the green tea group and 35.7% in the placebo group (RR 1.16 [0.81; 1.65] p = 0.61), whereas in the nonvariant carriers, the frequency of reoccurrence was 54.5% in the green tea group and 66.5% in the placebo group (RR 0.82 [0.69; 0.97], p = 0.03).

Conclusion: Individuals with genetic variants in the transporter SLCO1A2 may be protected against colon adenoma irrespective of the green tea intake. In nonvariant carriers of SLCO1A2, green tea was associated with a clear benefit in outcome (18% risk reduction).

Background: Pharmacogenetics uses individuals' genetic profiles to optimize drug treatment and prevent adverse reactions. One strategy to obtain information on pharmacogenes is to reuse sequencing data for a pharmacogenetic passport, providing information preemptively to healthcare professionals for utilization throughout a patient's lifetime.

Aim: To explore stakeholders' perceived barriers and facilitators and future perspectives of implementing a pharmacogenetic passport based on experiences from reusing sequencing data, in a Dutch University Medical Center.

Methods: Semi-structured interviews were conducted among 21 stakeholders. Interviews were analyzed using thematic analysis, and themes were grouped under the constructs of structure, culture, and practice.

Results: Perceived implementation barriers included inadequate data infrastructure, limited knowledge of pharmacogenetics, lack of (visible) guidelines, unequal access, unclear division of tasks and unclear procedures, and other hospital priorities. Perceived facilitators included the ease, efficiency, and affordability to obtain pharmacogenetic test results from reused sequencing data, stakeholders' positive attitudes about patient impacts of a pharmacogenetic passport, and that patient control of their health data is provided.

Conclusion: When considering the implementation of a pharmacogenetic passport, strategies can be developed to diminish barriers and strengthen facilitators. It is important to focus on data infrastructure, (visibility of) guidelines, clear division of tasks, and pharmacogenetic education.

Tuberculosis is the leading cause of death from a single infectious agent globally, with the highest burden in low-and middle-income countries. Successful treatment requires prolonged administration of multiple drugs. The increasing threat of multidrug-resistant tuberculosis has prompted the development of a robust pipeline for new drugs. While generally safe and well tolerated, adverse drug reactions (ADRs) to TB drugs have a considerable impact on treatment outcomes. Pharmacogenetic testing has been implemented for some diseases to identify at-risk individuals and prevent ADRs. For tuberculosis treatment, the use of pharmacogenetic testing to optimize complex regimens and avoid ADRs is appealing, but there has been minimal implementation. To improve the use of pharmacogenetics, understanding both the pharmacology of relevant drugs and population-specific pathophysiology of ADRs are essential. This review highlights the major treatment-limiting ADRs with TB drugs, the current understanding of drug metabolic pathways, ADR pathophysiology, and known pharmacogenetic risk alleles. We highlight research gaps and barriers to meaningful clinical use and implementation of pharmacogenomic testing to prevent adverse reactions to TB drugs.

Pharmacogenomics (PGx) has the potential to revolutionize hypertension management by tailoring antihypertensive therapy based on genetic profiles. Despite significant advances in genomic research, the clinical translation of PGx in hypertension remains challenging due to genetic complexity, variability in drug response, and implementation barriers. This review explores the genetic basis of hypertension, highlighting key pharmacogenomic markers that influence antihypertensive metabolism and efficacy, including CYP2D6, CYP3A4, UMOD, and ACE polymorphisms. We also examine the role of Mendelian randomization, polygenic risk scores in drug development and stratifying hypertension treatment response. While PGx offers opportunities for personalized medicine - such as reducing trial-and-error prescribing and improving adherence - several obstacles hinder its widespread adoption. These include limited clinical actionability, lack of large-scale randomized controlled trials, cost constraints, and concerns about equity and accessibility. Furthermore, drug-gene interactions and phenoconversion add complexity to implementation. Emerging technologies, including artificial intelligence-driven prescribing, microbiome integration, and pharmacoepigenomics, may enhance PGx precision in hypertension management. However, further research, clinical validation, and policy frameworks are necessary before PGx can be routinely incorporated into hypertension care. This review critically evaluates both the promise and limitations of PGx in hypertension, offering insights into the future of precision medicine in cardiovascular health.

Pharmacogenomic variations in genes involved in drug disposition and in drug targets is a major determinant of inter-individual differences in drug response and toxicity. While the effects of common variants are well established, millions of rare variations remain functionally uncharacterized, posing a challenge for the implementation of precision medicine. Recent advances in machine learning (ML) have significantly enhanced the prediction of variant effects by considering DNA as well as protein sequences, as well as their evolutionary conservation and haplotype structures. Emerging deep learning models utilize techniques to capture evolutionary conservation and biophysical properties, and ensemble approaches that integrate multiple predictive models exhibit increased accuracy, robustness, and interpretability. This review explores the current landscape of ML-based variant effect predictors. We discuss key methodological differences and highlight their strengths and limitations for pharmacogenomic applications. We furthermore discuss emerging methodologies for the prediction of substrate-specificity and for consideration of variant epistasis. Combined, these tools improve the functional effect prediction of drug-related variants and offer a viable strategy that could in the foreseeable future translate comprehensive genomic information into pharmacogenetic recommendations.

The development of polygenic risk scores (PRSs), which make use of genetic testing to assess an individual's risk of developing certain diseases or conditions based on collective genetic variant information, can be applied in drug development to enrich clinical trials or predict response to treatment. From querying documents submitted to the Food & Drug Administration, the landscape of use of PRSs across time shows increased use in guiding clinical trials. Of the clinical trial protocols submitted, most were in the therapeutic areas of neurology, radiology (imaging and diagnostic pharmaceuticals), psychiatry, and oncology. Use of PRSs in clinical trials is most frequent in early drug development (phase 1, phase 1/2, or phase 3) and generally supports secondary or exploratory analyses. Additionally, about half of the protocols developed novel PRSs, and the other half used preexisting PRSs. As researchers, regulators, and clinicians aim to understand the results and implications of PRSs in clinical trials, the continued use of PRSs, despite being less common, reinforces the need for further exploration.

Systemic lupus erythematosus (SLE) is a complex autoimmune disease requiring immunosuppressive medications to control symptoms and prevent organ damage. This review explores the influence of genetic polymorphisms on the pharmacokinetics and therapeutic responses of immunosuppressants in SLE. A total of 37 studies were reviewed, focusing on mycophenolic acid, tacrolimus, azathioprine, glucocorticoids, and cyclophosphamide. Genetic variants in UGT1A9, UGT2B7, CYP3A5, ABCB1,ABCC2 and TPMT significantly affect drug metabolism, efficacy, and toxicity. For instance, ABCB1 polymorphisms influence drug transport and bioavailability, impacting tacrolimus and glucocorticoid response, while ABCC2 variants alter MPA clearance, potentially affecting therapeutic outcomes, UGT1A9 and UGT2B7 variants influence mycophenolic acid metabolism, CYP3A5 impacts tacrolimus dosing, TPMT determines azathioprine metabolism, and CYP2C19 and CYP2B6 affect cyclophosphamide processing. These genetic differences can alter treatment effectiveness and risk of adverse effects. However, most pharmacogenetic studies focus on organ transplantation, leaving a critical gap in SLE-specific research, particularly among diverse populations. Addressing this gap is essential to optimizing personalized treatment for SLE. Integrating pharmacogenetics into clinical practice holds great potential to enhance the safety, efficacy, and outcomes of immunosuppressive therapy in SLE. This review highlights the urgent need for further studies to advance precision medicine for SLE patients.

As an emerging health technology, pharmacogenetic (PGx) testing has the capacity to improve medication therapy. However, implementation in medically underserved populations (MUPs) remains limited, which has the potential to increase healthcare disparities. While there is no single accepted definition for MUPs, demographic, socioeconomic, cultural, and geographic factors can lead to reduced access to healthcare, which contributes to disparate health outcomes in these populations. In the case of PGx testing, as MUPs have an increased risk of adverse drug events, have lower numbers of healthcare encounters, and are prescribed more medications which can be guided by PGx testing, additional benefits from PGx testing may occur in MUPs. Study of the acceptability and perceptions of PGx testing in MUPs, as reported in literature, provides support for the development of successful PGx testing implementations. Additionally, a few limited pilot PGx testing implementations in MUPs have assessed feasibility. However, further studies establishing the feasibility and effectiveness of PGx testing implementations in MUPs will enable more widespread PGx testing in those who are medically underserved. Thus, this narrative review explores the impact of medical underservice on health, PGx testing's potential impact on MUPs, and the research and early clinical implementations of PGx in MUPs.

Introduction: Genotype-guided tacrolimus management is not routine in clinical practice despite the availability of Clinical Pharmacogenetics Implementation Consortium dosing guidelines. Prior surveys have evaluated patient and provider perspectives of pharmacogenetics (PGx) in transplant, but limited recent data exists on tacrolimus PGx implementation across United States transplant centers.

Methods: An electronic survey was distributed to transplant pharmacists regarding utilization of tacrolimus PGx, methods of implementing PGx, and barriers to clinical implementation. A survey response was requested for each organ program within the transplant center.

Results: A total of 90 programs from 69 transplant centers (28.1% of active U.S. transplant centers) responded to the survey. Tacrolimus PGx was utilized for patient care in 14 programs (15.6%). There was substantial variability in the implementation methods and application of tacrolimus PGx results among transplant programs. In programs that had not implemented tacrolimus PGx, common barriers for implementation included PGx testing cost and availability and lack of evidence for clinical utility.

Conclusion: Implementation of PGx guided tacrolimus in solid organ transplant centers remains limited with heterogeneity in the implementation approach. Additional research is needed to establish the clinical utility of PGx guided tacrolimus and education on reimbursement and testing resources may help to increase uptake.

Aim: The aim of this study is to find out the effect of SOD1 rs36232792 and SOD2 rs5746136 on the risk of opioid use disorder (OUD).

Methods: Individuals with OUD (n = 101) and controls (n = 104) were included. SOD1 rs36232792 was genotyped by PCR. A novel PCR-RFLP method for SOD2 rs5746136 was optimized.

Results: A significant difference was observed between individuals with OUD and controls in view of the frequency of 'Ins/Del+Del/Del' genotypes of the SOD1 rs36232792 (p = 0.049), but not for SOD2 rs5746136 (p = 0.254). The intensity of anxiety and depressive symptoms was significantly higher in individuals with OUD compared to controls (p = 0.001).

Conclusion: The SOD1 rs36232792 polymorphism could contribute to the risk of OUD in a Turkish population. A novel PCR-RFLP method for SOD2 rs5746136 confirmed by sequencing can be used in a research laboratory without advanced equipment.