Pharmacogenomics of GPCR Drug Targets.

Natural genetic variation in the human genome is a cause of individual differences in responses to medications and is an underappreciated burden on public health. Although 108 G-protein-coupled receptors (GPCRs) are the targets of 475 (∼34%) Food and Drug Administration (FDA)-approved drugs and account for a global sales volume of over 180 billion US dollars annually, the prevalence of genetic variation among GPCRs targeted by drugs is unknown. By analyzing data from 68,496 individuals, we find that GPCRs targeted by drugs show genetic variation within functional regions such as drug- and effector-binding sites in the human population. We experimentally show that certain variants of µ-opioid and Cholecystokinin-A receptors could lead to altered or adverse drug response. By analyzing UK National Health Service drug prescription and sales data, we suggest that characterizing GPCR variants could increase prescription precision, improving patients' quality of life, and relieve the economic and societal burden due to variable drug responsiveness. VIDEO ABSTRACT.

A second space age spanning omics, platforms and medicine across orbits.

The recent acceleration of commercial, private and multi-national spaceflight has created an unprecedented level of activity in low Earth orbit, concomitant with the largest-ever number of crewed missions entering space and preparations for exploration-class (lasting longer than one year) missions. Such rapid advancement into space from many new companies, countries and space-related entities has enabled a 'second space age'. This era is also poised to leverage, for the first time, modern tools and methods of molecular biology and precision medicine, thus enabling precision aerospace medicine for the crews. The applications of these biomedical technologies and algorithms are diverse, and encompass multi-omic, single-cell and spatial biology tools to investigate human and microbial responses to spaceflight. Additionally, they extend to the development of new imaging techniques, real-time cognitive assessments, physiological monitoring and personalized risk profiles tailored for astronauts. Furthermore, these technologies enable advancements in pharmacogenomics, as well as the identification of novel spaceflight biomarkers and the development of corresponding countermeasures. In this Perspective, we highlight some of the recent biomedical research from the National Aeronautics and Space Administration, Japan Aerospace Exploration Agency, European Space Agency and other space agencies, and detail the entrance of the commercial spaceflight sector (including SpaceX, Blue Origin, Axiom and Sierra Space) into aerospace medicine and space biology, the first aerospace medicine biobank, and various upcoming missions that will utilize these tools to ensure a permanent human presence beyond low Earth orbit, venturing out to other planets and moons.

Cardiovascular Pharmacogenetics: From Discovery of Genetic Association to Clinical Adoption of Derived Test.

Recent breakthroughs in human genetics and in information technologies have markedly expanded our understanding at the molecular level of the response to drugs, i.e., pharmacogenetics (PGx), across therapy areas. This review is restricted to PGx for cardiovascular (CV) drugs. First, we examined the PGx information in the labels approved by regulatory agencies in Europe, Japan, and North America and related recommendations from expert panels. Out of 221 marketed CV drugs, 36 had PGx information in their labels approved by one or more agencies. The level of annotations and recommendations varied markedly between agencies and expert panels. Clopidogrel is the only CV drug with consistent PGx recommendation (i.e., "actionable"). This situation prompted us to dissect the steps from discovery of a PGx association to clinical translation. We found 101 genome-wide association studies that investigated the response to CV drugs or drug classes. These studies reported significant associations for 48 PGx traits mapping to 306 genes. Six of these 306 genes are mentioned in the corresponding PGx labels or recommendations for CV drugs. Genomic analyses also highlighted the wide between-population differences in risk allele frequencies and the individual load of actionable PGx variants. Given the high attrition rate and the long road to clinical translation, additional work is warranted to identify and validate PGx variants for more CV drugs across diverse populations and to demonstrate the utility of PGx testing. To that end, pre-emptive PGx combining genomic profiling with electronic medical records opens unprecedented opportunities to improve healthcare, for CV diseases and beyond. SIGNIFICANCE STATEMENT: Despite spectacular breakthroughs in human molecular genetics and information technologies, consistent evidence supporting PGx testing in the cardiovascular area is limited to a few drugs. Additional work is warranted to discover and validate new PGx markers and demonstrate their utility. Pre-emptive PGx combining genomic profiling with electronic medical records opens unprecedented opportunities to improve healthcare, for CV diseases and beyond.

Frequencies of pharmacogenomic alleles across biogeographic groups in a large-scale biobank.

Pharmacogenomics (PGx) is an integral part of precision medicine and contributes to the maximization of drug efficacy and reduction of adverse drug event risk. Accurate information on PGx allele frequencies improves the implementation of PGx. Nonetheless, curating such information from published allele data is time and resource intensive. The limited number of allelic variants in most studies leads to an underestimation of certain alleles. We applied the Pharmacogenomics Clinical Annotation Tool (PharmCAT) on an integrated 200K UK Biobank genetic dataset (N = 200,044). Based on PharmCAT results, we estimated PGx frequencies (alleles, diplotypes, phenotypes, and activity scores) for 17 pharmacogenes in five biogeographic groups: European, Central/South Asian, East Asian, Afro-Caribbean, and Sub-Saharan African. PGx frequencies were distinct for each biogeographic group. Even biogeographic groups with similar proportions of phenotypes were driven by different sets of dominant PGx alleles. PharmCAT also identified "no-function" alleles that were rare or seldom tested in certain groups by previous studies, e.g., SLCO1B1∗31 in the Afro-Caribbean (3.0%) and Sub-Saharan African (3.9%) groups. Estimated PGx frequencies are disseminated via the PharmGKB (The Pharmacogenomics Knowledgebase: www.pharmgkb.org). We demonstrate that genetic biobanks such as the UK Biobank are a robust resource for estimating PGx frequencies. Improving our understanding of PGx allele and phenotype frequencies provides guidance for future PGx studies and clinical genetic test panel design, and better serves individuals from wider biogeographic backgrounds.

Advancing Pharmacogenomics from Single-Gene to Preemptive Testing.

Pharmacogenomic testing can be an effective tool to enhance medication safety and efficacy. Pharmacogenomically actionable medications are widely used, and approximately 90-95% of individuals have an actionable genotype for at least one pharmacogene. For pharmacogenomic testing to have the greatest impact on medication safety and clinical care, genetic information should be made available at the time of prescribing (preemptive testing). However, the use of preemptive pharmacogenomic testing is associated with some logistical concerns, such as consistent reimbursement, processes for reporting preemptive results over an individual's lifetime, and result portability. Lessons can be learned from institutions that have implemented preemptive pharmacogenomic testing. In this review, we discuss the rationale and best practices for implementing pharmacogenomics preemptively.

A Bayesian approach for investigating the pharmacogenetics of combination antiretroviral therapy in people with HIV.

Combination antiretroviral therapy (ART) with at least three different drugs has become the standard of care for people with HIV (PWH) due to its exceptional effectiveness in viral suppression. However, many ART drugs have been reported to associate with neuropsychiatric adverse effects including depression, especially when certain genetic polymorphisms exist. Pharmacogenetics is an important consideration for administering combination ART as it may influence drug efficacy and increase risk for neuropsychiatric conditions. Large-scale longitudinal HIV databases provide researchers opportunities to investigate the pharmacogenetics of combination ART in a data-driven manner. However, with more than 30 FDA-approved ART drugs, the interplay between the large number of possible ART drug combinations and genetic polymorphisms imposes statistical modeling challenges. We develop a Bayesian approach to examine the longitudinal effects of combination ART and their interactions with genetic polymorphisms on depressive symptoms in PWH. The proposed method utilizes a Gaussian process with a composite kernel function to capture the longitudinal combination ART effects by directly incorporating individuals' treatment histories, and a Bayesian classification and regression tree to account for individual heterogeneity. Through both simulation studies and an application to a dataset from the Women's Interagency HIV Study, we demonstrate the clinical utility of the proposed approach in investigating the pharmacogenetics of combination ART and assisting physicians to make effective individualized treatment decisions that can improve health outcomes for PWH.

Pharmacogenetics in Italy: current landscape and future prospects.

Pharmacogenetics investigates sequence of genes that affect drug response, enabling personalized medication. This approach reduces drug-induced adverse reactions and improves clinical effectiveness, making it a crucial consideration for personalized medical care. Numerous guidelines, drawn by global consortia and scientific organizations, codify genotype-driven administration for over 120 active substances. As the scientific community acknowledges the benefits of genotype-tailored therapy over traditionally agnostic drug administration, the push for its implementation into Italian healthcare system is gaining momentum. This evolution is influenced by several factors, including the improved access to patient genotypes, the sequencing costs decrease, the growing of large-scale genetic studies, the rising popularity of direct-to-consumer pharmacogenetic tests, and the continuous improvement of pharmacogenetic guidelines. Since EMA (European Medicines Agency) and AIFA (Italian Medicines Agency) provide genotype information on drug leaflet without clear and explicit clinical indications for gene testing, the regulation of pharmacogenetic testing is a pressing matter in Italy. In this manuscript, we have reviewed how to overcome the obstacles in implementing pharmacogenetic testing in the clinical practice of the Italian healthcare system. Our particular emphasis has been on germline testing, given the absence of well-defined national directives in contrast to somatic pharmacogenetics.

A qualitative approach to assess the opinion of physicians about the challenges and prospects of pharmacogenomic testing implementation in clinical practice in Greece.

BACKGROUND: Pharmacogenomics (PGx) constitutes an important part of personalized medicine and has several clinical applications. PGx role in clinical practice is known, however, it has not been widely adopted yet. In this study, we aim to investigate the perspectives of Greek physicians regarding the implementation of PGx testing in clinical practice and the key issues associated with it. METHODS: Fourteen interviews were conducted with physicians of various specialties for which PGx applications are available. A semi-structured interview guide was utilized based on the Consolidated Framework for Implementation Research (CFIR) context and the Diffusion of Innovation model. Transcripts were coded independently and compared by two members of the research team. Descriptive statistics were generated using Microsoft Excel. RESULTS: Six main themes emerged: awareness and use of PGx testing; source of information; key stakeholders of the PGx supply chain, their interactions and change agents; clinical benefit and significance of PGx testing; barriers and lack of reimbursement; and recommendations to boost the PGx adoption rate. Most respondents were aware of PGx applications, but only three had already recommended PGx testing. Peer-reviewed journals along with clinical guidelines were regarded as the most used source of information while stakeholders of the PGx supply chain were discussed. PGx was considered that promote patient-centered care, enhance medication clinical effectiveness, decrease the risk of side effects, and reduce healthcare costs. Lack of reimbursement, scarcity of resources, and high PGx cost were the foremost barriers affecting PGx adoption. CONCLUSIONS: It was concluded that if case PGx testing is reimbursed and physicians' training is reinforced, PGx implementation will be boosted and improved shortly.

Frequency of pharmacogenomic variants affecting safety and efficacy of immunomodulators and biologics in a South Asian population from Sri Lanka.

BACKGROUND: Immunomodulators are important for management of autoimmune diseases and hematological malignancies. Significant inter-individual variation in drug response/reactions exists due to genetic polymorphisms. We describe frequency of identified genetic polymorphisms among Sri Lankans. METHODS: Sri Lankan data were obtained from an anonymized database of 670 participants. Data on variants and global distribution of Minor Allele frequency (MAF) of other populations (South Asian, Ashkenazi-Jewish, East-Asian, European-Finnish, European-non-Finnish, Latino-American, African/African-American) were obtained from pharmGKB online database. RESULTS: SLC19A1 (rs1051266) variant had a MAF (95% CI) of 63.3% (60.7-65.9). Other common variants included FCGR3A (rs396991), MTHFR (rs1801133), ITPA (rs1127354), CYP2C9*3 (rs1057910) and NUD15*3 (rs116855232), with MAFs of 35.3% (32.7-37.9), 12.2% (10.4-13.9), 10.9% (9.2-12.6), 9.8% (8.2-11.4), 8.3% (6.8-9.8) respectively. Less commonly present variants included CYP2C9*2 (rs1799853) (2.5%[1.7-3.4]), TPMT*3C (rs1142345) (1.9%[1.1-2.6]), TPMT*3B (rs1800460) (0.2%[0-0.5]), CYP3A5*6 (rs10264272) (0.2%[0-0.4]) and CYP3A4*18 (rs28371759) (0.1%[0-0.2]). The SLC19A1 (rs1051266), NUD15*3 (rs116855232), CYP2C9*3 (rs1057910), FCGR3A (rs396991), and ITPA (rs1127354) showed significantly higher frequencies in Sri Lankans compared to many other populations, exceptions include FCGR3A in Ashkenazi-Jewish and ITPA in East-Asians. Conversely, MTHFR (rs1801133), TPMT*3B (rs1800460), and CYP2C9*2 (rs1799853) were significantly less prevalent among Sri Lankans than in  many other populations. Sri Lankans exhibited lower prevalence of TPMT*3C (rs1142345) compared to European-non-Finnish, Latino-Americans, and African/African-Americans; CYP3A4*18 (rs28371759) compared to East-Asians; and CYP3A5*6 (rs10264272) compared to African/African-Americans and Latino-Americans. CONCLUSION: Sri Lankans exhibit higher frequencies in variants reducing methotrexate efficacy (SLC19A1), increasing azathioprine myelotoxicity (NUDT15), and lower frequencies in variants linked to increased azathioprine toxicity (TPMT*3B, TPMT*3C), reduced tacrolimus efficacy (CYP3A4*18), and methotrexate toxicity risk (MTHFR). Beneficial variants enhancing rituximab efficacy (FCGR3A) are more prevalent, while those reducing tacrolimus dosage (CYP3A5*6) are less common. This highlights need for targeted medication strategies to improve treatment outcomes.

Targeted panel sequencing of pharmacogenes and oncodrivers in colorectal cancer patients reveals genes with prognostic significance.

BACKGROUND: Colorectal cancer is still the second leading cause of cancer-related deaths and thus biomarkers allowing prediction of the resistance of patients to therapy and estimating their prognosis are needed. We designed a panel of 558 genes with pharmacogenomics records related to 5-fluorouracil resistance, genes important for sensitivity to other frequently used drugs, major oncodrivers, and actionable genes. We performed a target enrichment sequencing of DNA from tumors and matched blood samples of patients, and compared the results with patient prognosis stratified by systemic adjuvant chemotherapy. RESULTS: The median number of detected variants per tumor sample was 18.5 with 4 classified as having a high predicted functional effect and 14.5 moderate effect. APC, TP53, and KRAS were the most frequent mutated genes (64%, 59%, and 42% of mutated samples, respectively) followed by FAT4 (23%), FBXW7, and PIK3CA (16% for both). Patients with advanced stage III had more frequently APC, TP53, or KRAS mutations than those in stages I or II. KRAS mutation counts followed an increasing trend with grade (G1 < G2 < G3). The response to adjuvant therapy was worse in carriers of frameshift mutations in APC or 12D variant in KRAS, but none of these oncodrivers had prognostic value. Carriage of somatic mutations in any of the genes ABCA13, ANK2, COL7A1, NAV3, or UNC80 had prognostic relevance for worse overall survival (OS) of all patients. In contrast, mutations in FLG, GLI3, or UNC80 were prognostic in the same direction for patients untreated, and mutations in COL6A3, LRP1B, NAV3, RYR1, RYR3, TCHH, or TENM4 for patients treated with adjuvant therapy. The first association was externally validated. From all germline variants with high or moderate predicted functional effects (median 326 per patient), > 5% frequency and positive Manhattan plot based on 3-year RFS, rs72753407 in NFACS, rs34621071 in ERBB4, and rs2444274 in RIF1 were significantly associated with RFS, OS or both. CONCLUSIONS: The present study identified several putative somatic and germline genetic events with prognostic potential for colorectal cancer that should undergo functional characterization.

Precision medicine for psychotic disorders: objective assessment, risk prediction, and pharmacogenomics.

Psychosis occurs inside the brain, but may have external manifestations (peripheral molecular biomarkers, behaviors) that can be objectively and quantitatively measured. Blood biomarkers that track core psychotic manifestations such as hallucinations and delusions could provide a window into the biology of psychosis, as well as help with diagnosis and treatment. We endeavored to identify objective blood gene expression biomarkers for hallucinations and delusions, using a stepwise discovery, prioritization, validation, and testing in independent cohorts design. We were successful in identifying biomarkers that were predictive of high hallucinations and of high delusions states, and of future psychiatric hospitalizations related to them, more so when personalized by gender and diagnosis. Top biomarkers for hallucinations that survived discovery, prioritization, validation and testing include PPP3CB, DLG1, ENPP2, ZEB2, and RTN4. Top biomarkers for delusions include AUTS2, MACROD2, NR4A2, PDE4D, PDP1, and RORA. The top biological pathways uncovered by our work are glutamatergic synapse for hallucinations, as well as Rap1 signaling for delusions. Some of the biomarkers are targets of existing drugs, of potential utility in pharmacogenomics approaches (matching patients to medications, monitoring response to treatment). The top biomarkers gene expression signatures through bioinformatic analyses suggested a prioritization of existing medications such as clozapine and risperidone, as well as of lithium, fluoxetine, valproate, and the nutraceuticals omega-3 fatty acids and magnesium. Finally, we provide an example of how a personalized laboratory report for doctors would look. Overall, our work provides advances for the improved diagnosis and treatment for schizophrenia and other psychotic disorders.

Going to the negative: genomics for optimized medical prescription.

Personalized medicine promises to advance and improve health by targeting the right medication to the right person at the right time, thus maximizing the proportion of treated patients who achieve an effective response to therapy. This Comment article makes the complementary argument that equally important benefits will derive from negative prediction, namely by identifying those individuals who are either not actually in need of, or unlikely to respond to, a drug. Reduction of unnecessary prescription could conceivably save health-care systems many billions of dollars with very little detrimental impact on outcomes.

A Nanopore Sequencing-based Pharmacogenomic Panel to Personalize Tuberculosis Drug Dosing.

Rationale: Standardized dosing of antitubercular drugs leads to variable plasma drug levels, which are associated with adverse drug reactions, delayed treatment response, and relapse. Mutations in genes affecting drug metabolism explain considerable interindividual pharmacokinetic variability; however, pharmacogenomic assays that predict metabolism of antitubercular drugs have been lacking. Objectives: We sought to develop a Nanopore sequencing panel and validate its performance in patients with active tuberculosis (TB) to personalize treatment dosing. Methods: We developed a Nanopore sequencing panel targeting 15 SNPs in five genes affecting the metabolism of antitubercular drugs. For validation, we sequenced DNA samples (n = 48) from the 1,000 Genomes Project and compared the variant calling accuracy with that of Illumina genome sequencing. We then sequenced DNA samples from patients with active TB (n = 100) from South Africa on a MinION Mk1C and evaluated the relationship between genotypes and pharmacokinetic parameters for isoniazid (INH) and rifampin (RIF). Measurements and Main Results: The pharmacogenomic panel achieved 100% concordance with Illumina sequencing in variant identification for the samples from the 1,000 Genomes Project. In the clinical cohort, coverage was more than 100× for 1,498 of 1,500 (99.8%) amplicons across the 100 samples. Thirty-three percent, 47%, and 20% of participants were identified as slow, intermediate, and rapid INH acetylators, respectively. INH clearance was 2.2 times higher among intermediate acetylators and 3.8 times higher among rapid acetylators, compared with slow acetylators (P < 0.0001). RIF clearance was 17.3% (2.50-29.9) lower in individuals with homozygous AADAC rs1803155 G→A substitutions (P = 0.0015). Conclusions: Targeted sequencing can enable the detection of polymorphisms that influence TB drug metabolism on a low-cost, portable instrument to personalize dosing for TB treatment or prevention.

Androgen receptor-mediated pharmacogenomic expression quantitative trait loci: implications for breast cancer response to AR-targeting therapy.

BACKGROUND: Endocrine therapy is the most important treatment modality of breast cancer patients whose tumors express the estrogen receptor α (ERα). The androgen receptor (AR) is also expressed in the vast majority (80-90%) of ERα-positive tumors. AR-targeting drugs are not used in clinical practice, but have been evaluated in multiple trials and preclinical studies. METHODS: We performed a genome-wide study to identify hormone/drug-induced single nucleotide polymorphism (SNP) genotype - dependent gene-expression, known as PGx-eQTL, mediated by either an AR agonist (dihydrotestosterone) or a partial antagonist (enzalutamide), utilizing a previously well characterized lymphoblastic cell line panel. The association of the identified SNPs-gene pairs with breast cancer phenotypes were then examined using three genome-wide association (GWAS) studies that we have published and other studies from the GWAS catalog. RESULTS: We identified 13 DHT-mediated PGx-eQTL loci and 23 Enz-mediated PGx-eQTL loci that were associated with breast cancer outcomes post ER antagonist or aromatase inhibitors (AI) treatment, or with pharmacodynamic (PD) effects of AIs. An additional 30 loci were found to be associated with cancer risk and sex-hormone binding globulin levels. The top loci involved the genes IDH2 and TMEM9, the expression of which were suppressed by DHT in a PGx-eQTL SNP genotype-dependent manner. Both of these genes were overexpressed in breast cancer and were associated with a poorer prognosis. Therefore, suppression of these genes by AR agonists may benefit patients with minor allele genotypes for these SNPs. CONCLUSIONS: We identified AR-related PGx-eQTL SNP-gene pairs that were associated with risks, outcomes and PD effects of endocrine therapy that may provide potential biomarkers for individualized treatment of breast cancer.

Pharmacogenomic allele coverage of genome-wide genotyping arrays: a comparative analysis.

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.

Healthcare provider and patient perspectives on the implementation of pharmacogenetic-guided treatment in routine clinical practice.

OBJECTIVE: This study aims to understand patient and healthcare provider perspectives on the integration and application of pharmacogenetics (PGx) testing in routine clinical practice. METHODS: Two anonymous online surveys were distributed globally for healthcare providers and patients respectively on the Qualtrics platform (version 3.24). The surveys were distributed through social platforms, email, and posters with QR codes from 27 October 2023 to 7 March 2024. The surveys evaluated participant familiarity with PGx, previous experience with PGx testing, perceived implementation challenges, and opinions on point-of-care (PoC) PGx testing devices. RESULTS: This study collected 78 responses from healthcare providers and 98 responses from patients. The results revealed that 64% of healthcare providers had some level of familiarity with PGx, however, PGx testing in clinical practice was low. The primary challenges identified by healthcare providers included limited access to testing and lack of knowledge on PGx test interpretation. In contrast, 52% of patient respondents were aware of PGx testing, with a significant association between awareness and positive opinions toward PGx. Both healthcare providers and patients recognized the value of PoC PGx testing devices, with 98% of healthcare providers and 71% of patients believing PoC devices would improve the accessibility and implementation of PGx testing. Comparative analysis revealed a statistically significant difference in PGx awareness between healthcare providers and patients, with providers being more informed. CONCLUSION: Improved PGx awareness, training, clinical guidelines, and PoC PGx testing devices may help promote the implementation of PGx-guided treatments in routine clinical practice.

Comparative performance of pharmacogenetics-based warfarin dosing algorithms in Chinese population: use of a pharmacokinetic/pharmacodynamic model to explore dosing regimen through clinical trial simulation.

OBJECTIVE: Warfarin has a narrow therapeutic window and large variability in dosing that are affected by clinical and genetic factors. To help guide the dosing of warfarin, the Clinical Pharmacogenetics Implementation Consortium has recommended the use of pharmacogenetic algorithms, such as the ones developed by the International Warfarin Pharmacogenetics Consortium (IWPC) and by Gage et al. when genotype information is available. METHODS: In this study, simulations were performed in Chinese cohorts to explore how dosing differences between Western (by IWPC and Gage et al.) and Chinese algorithms (by Miao et al.) would mean in terms of anticoagulation effect in clinical trials. We first tried to replicate a published clinical trial comparing genotype-guided dosing to routine clinical dosing in Chinese patients. We then made simulations where Chinese cohorts received daily doses recommended by Gage, IWPC, and Miao algorithms. RESULTS: We found that in simulation conditions where dosing specifications were strictly followed, genotype-guided dosing by IWPC and Lenzini formulae was more likely to overshoot the upper limit of the therapeutic window by day 15, and thus may have a lower % time in therapeutic range (%TTR) than that of clinical dosing group. Also, in comparing Gage, IWPC, and Miao algorithms, we found that the Miao dosing cohort has the highest %TTR and the lowest risk of over-anticoagulation by day 28. CONCLUSION: In summary, our results confirmed that algorithms developed based on data from local patients may be more suitable for achieving therapeutic international normalized ratio window in Chinese population.

Pharmacogenetics to prevent hypersensitivity reactions to antiepileptic drugs: is testing performed when indicated?

Extensive scientific evidence consistently demonstrates the clinical validity and utility of HLA-B*15:02 pre-screening in averting severe cutaneous adverse reactions (SCARs), namely Stevens-Johnson syndrome and toxic epidermal necrolysis, associated with carbamazepine or oxcarbazepine usage. Current practice guidelines and drug labeling actively advocate for pharmacogenetic pre-screening before initiating these antiepileptic drugs (AED), with particular emphasis on patients of Asian descent. However, there is a potential need to strengthen compliance with these recommendations. This retrospective study aimed to describe the pharmacogenetic pre-screening, documentation, and SCARs incidence for patients of Asian ancestry initiated on carbamazepine or oxcarbazepine at a large Northeastern USA healthcare system. Between 1 July 2016 and August 1, 2021, 27 patients with documented Asian heritage in the electronic health record (EHR) were included. The overall rate of HLA-B*15:02 pre-screening before carbamazepine or oxcarbazepine initiation was 4%. None who underwent pharmacogenetic pre-screening carried the associated HLA-B risk allele, and no SCARs were reported. Notably, pharmacogenetic results were not discretely entered into the EHR, and the results were only found as attached documents in the miscellaneous section of the EHR. There remains a significant opportunity for improving HLA-B*15:02 pre-screening for patients starting carbamazepine and oxcarbazepine to prevent SCARs in the USA.

Pharmacogenetic determinants of tenofovir diphosphate and lamivudine triphosphate concentrations in people with HIV/HBV coinfection.

The nucleos(t)ide analogs require phosphorylation to the pharmacologically active anabolites in cells. We investigated the hypothesis that single-nucleotide polymorphisms (SNPs) in genes that encode transporters and phosphodiesterase (PDE) enzymes involved in tenofovir (TFV), disoproxil fumarate (TDF), and lamivudine (3TC) disposition will be associated with concentrations of their phosphate anabolites and virologic response. Individuals with human immunodeficiency virus (HIV) and hepatitis B virus (HBV) coinfection receiving TDF/3TC-containing antiretroviral therapy were enrolled. Steady-state TFV diphosphate (TFV-DP) and 3TC triphosphate (3TC-TP) concentrations in peripheral blood mononuclear cells (PBMCs) and dried blood spot samples were quantified. The relationship between genetic variants and TFV-DP and 3TC-TP concentrations as well as with virologic response were examined using multivariable linear regression. Of the 136 participants (median age 43 years; 63% females), 6.6% had HBV non-suppression, and 7.4% had HIV non-suppression. The multidrug resistance protein 2 (encoded by ABCC2 rs2273697) SNP was associated with 3TC-TP concentrations in PBMCs. The human organic anion transporter-1 (encoded by SLC28A2) rs11854484 SNP was associated with HIV non-suppression, and when evaluated together with SNPs with marginal associations (ABCC2 rs717620 and PDE1C rs30561), participants with two or three variants compared to those with none of these variants had an adjusted odds ratio of 48.3 (confidence interval, 4.3-547.8) for HIV non-suppression. None of the SNPs were associated with HBV non-suppression. Our study identified ABCC2 SNP to be associated with 3TC-TP concentrations in PBMCs. Also, a combination of genetic variants of drug transporters and PDE was associated with HIV non-suppression.

Cost-utility analysis of pharmacogenomics-guided tacrolimus treatment in Austrian kidney transplant recipients participating in the U-PGx PREPARE study.

Chronic kidney disease (CKD) is a global health issue. Kidney failure patients may undergo a kidney transplantation (KTX) and prescribed an immunosuppressant medication i.e., tacrolimus. Tacrolimus' efficacy and toxicity varies among patients. This study investigates the cost-utility of pharmacogenomics (PGx) guided tacrolimus treatment compared to the conventional approach in Austrian patients undergone KTX, participating in the PREPARE UPGx study. Treatment's effectiveness was determined by mean survival, and utility values were based on a Visual Analog Scale score. Incremental Cost-Effectiveness Ratio was also calculated. PGx-guided treatment arm was found to be cost-effective, resulting in reduced cost (3902 euros less), 6% less hospitalization days and lower risk of adverse drug events compared to the control arm. The PGx-guided arm showed a mean 0.900 QALYs (95% CI: 0.862-0.936) versus 0.851 QALYs (95% CI: 0.814-0.885) in the other arm. In conclusion, PGx-guided tacrolimus treatment represents a cost-saving option in the Austrian healthcare setting.