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Pharmacogenomic Polygenic Risk Scores (PRS) have emerged as a tool to address the polygenic nature of pharmacogenetic phenotypes, increasing the potential to predict drug response. Most pharmacogenomic PRS have been extrapolated from disease-associated variants identified by genome wide association studies (GWAS), although some have begun to utilize genetic variants from pharmacogenomic GWAS. As pharmacogenomic PRS hold the promise of enabling precision medicine, including stratified treatment approaches, it is important to assess the opportunities and challenges presented by the current data. This assessment will help determine how pharmacogenomic PRS can be advanced and transitioned into clinical use. In this review, we present a summary of recent evidence, evaluate the current status, and identify several challenges that have impeded the progress of pharmacogenomic PRS. These challenges include the reliance on extrapolations from disease genetics and limitations inherent to pharmacogenomics research such as low sample sizes, phenotyping inconsistencies, among others. We finally propose recommendations to overcome the challenges and facilitate the clinical implementation. These recommendations include standardizing methodologies for phenotyping, enhancing collaborative efforts, developing new statistical methods to capitalize on drug-specific genetic associations for PRS construction. Additional recommendations include enhancing the infrastructure that can integrate genomic data with clinical predictors, along with implementing user-friendly clinical decision tools, and patient education. Ethical and regulatory considerations should address issues related to patient privacy, informed consent and safe use of PRS. Despite these challenges, ongoing research and large-scale collaboration is likely to advance the field and realize the potential of pharmacogenomic PRS., (© 2024 The Author(s). Clinical and Translational Science published by Wiley Periodicals LLC on behalf of American Society for Clinical Pharmacology and Therapeutics.)

There are limited comparison data throughout the dosing interval for generic versus brand metoprolol extended-release (ER) tablets. We compared the pharmacokinetics (PKs) and pharmacodynamics of brand name versus two generic formulations (drugs 1 and 2) of metoprolol ER tablets with different time to maximum concentration (T max ) in adults with hypertension. Participants were randomized to equal drug doses (50-150 mg/day) administered in one of two sequences (brand-drug1-brand-drug2 or brand-drug2-brand-drug1) and completed 24-h PK, digital heart rate (HR), ambulatory blood pressure (BP), and HR studies after taking each formulation for greater than or equal to 7 days. Metoprolol concentrations were determined by liquid chromatography tandem mass spectrometry, with noncompartmental analysis performed to obtain PK parameters in Phoenix WinNonlin. Heart rate variability (HRV) low-to-high frequency ratio was determined per quartile over the 24-h period. Thirty-six participants completed studies with the brand name and at least one generic product. Among 30 participants on the 50 mg dose, the primary PK end points of area under the concentration-time curve and C max were similar between products; T max was 6.1 ± 3.6 for the brand versus 3.5 ± 4.9 for drug 1 (p = 0.019) and 9.6 ± 3.2 for drug 2 (p < 0.001). Among all 36 participants, 24-h BPs and HRs were similar between products. Mean 24-h HRV low-to-high ratio was also similar for drug 1 (2.04 ± 1.35), drug 2 (1.86 ± 1.35), and brand (2.04 ± 1.77), but was more sustained over time for the brand versus drug 1 (drug × quartile interaction p = 0.017). Differences in T max between metoprolol ER products following repeated doses may have implications for drug effects on autonomic balance over the dosing interval., (© 2022 The Authors. Clinical and Translational Science published by Wiley Periodicals LLC on behalf of American Society for Clinical Pharmacology and Therapeutics.)

To date, there has been no genomewide association study (GWAS) from the Middle East and North African (MENA) region to identify genetic variants associated with warfarin dose variability using this approach. In this study, we aimed to conduct the first GWAS of warfarin dose requirements in patients from the MENA region. A total of 132 Qatari (discovery) and 50 Egyptians (replication) were genotyped using Illumina Multi-Ethnic Global BeadChip Array. A GWAS was performed on log-transformed weekly warfarin dose in the studied population, adjusting for clinical characteristics and ancestry. The genomewide signals from the discovery cohort were tested in the Egyptian cohort. A GWAS meta-analysis, including the Qatari and Egyptian cohorts, was also performed and the output from this analysis was used in a gene-based analysis. The discovery analysis in Qatari identified five genomewide single-nucleotide polymorphisms (SNPs) in chromosome 16. These signals were replicated in the Egyptian cohort. Combining the two data through a GWAS meta-analysis strengthened the association in chromosome 16 with VKORC1 rs9934438 being the lead genomewide signal (β = -0.17, 6 × 10 -15 ). Other SNPs were identified in chromosome 10 at a p value less than 1 × 10 -5 . The genetic variants within VKORC1 rs9934438 and CYP2C9 rs4086116 explained 39% and 27% of the variability in the weekly warfarin dose requirement in the Qatari and Egyptians, respectively. This is the first GWAS of warfarin dose variability in the MENA region. It confirms the importance of VKORC1 and CYP2C9 variants in warfarin dose variability among patients from the MENA region., (© 2021 The Authors. Clinical and Translational Science published by Wiley Periodicals LLC on behalf of American Society for Clinical Pharmacology and Therapeutics.)

Populations used to create warfarin dose prediction algorithms largely lacked participants reporting Hispanic or Latino ethnicity. While previous research suggests nonlinear modeling improves warfarin dose prediction, this research has mainly focused on populations with primarily European ancestry. We compare the accuracy of stable warfarin dose prediction using linear and nonlinear machine learning models in a large cohort enriched for US Latinos and Latin Americans (ULLA). Each model was tested using the same variables as published by the International Warfarin Pharmacogenetics Consortium (IWPC) and using an expanded set of variables including ethnicity and warfarin indication. We utilized a multiple linear regression model and three nonlinear regression models: Bayesian Additive Regression Trees, Multivariate Adaptive Regression Splines, and Support Vector Regression. We compared each model's ability to predict stable warfarin dose within 20% of actual stable dose, confirming trained models in a 30% testing dataset with 100 rounds of resampling. In all patients ( n = 7,030), inclusion of additional predictor variables led to a small but significant improvement in prediction of dose relative to the IWPC algorithm (47.8 versus 46.7% in IWPC, p = 1.43 × 10 -15 ). Nonlinear models using IWPC variables did not significantly improve prediction of dose over the linear IWPC algorithm. In ULLA patients alone ( n = 1,734), IWPC performed similarly to all other linear and nonlinear pharmacogenetic algorithms. Our results reinforce the validity of IWPC in a large, ethnically diverse population and suggest that additional variables that capture warfarin dose variability may improve warfarin dose prediction algorithms., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 Steiner, Giles, Patterson, Feng, El Rouby, Claudio, Marcatto, Tavares, Galvez, Calderon-Ospina, Sun, Hutz, Scott, Cavallari, Fonseca-Mendoza, Duconge, Botton, Santos and Karnes.)

We conducted a multi-site investigation of genetic determinants of warfarin dose variability in Latinos from the U.S. and Brazil. Patients from four institutions in the United States (n = 411) and Brazil (n = 663) were genotyped for VKORC1 c.-1639G> A, common CYP2C9 variants, CYP4F2*3, and NQO1*2. Multiple regression analysis was used in the U.S. cohort to test the association between warfarin dose and genotype, adjusting for clinical factors, with further testing in an independent cohort of Brazilians. In the U.S. cohort, VKORC1 and CYP2C9 variants were associated with lower warfarin dose (β = -0.29, P < 2.0 × 10 -16 ; β = -0.21, P = 4.7 × 10 -7 , respectively) whereas CYP4F2 and NQO1 variants were associated with higher dose (β = 0.10, P = 2 × 10 -4 ; β = 0.10, P = 0.01, respectively). Associations with VKORC1 (β = -0.14, P = 2.0 × 10 -16 ), CYP2C9 (β = -0.07, P = 5.6 × 10 -10 ), and CYP4F2 (β = 0.03, P = 3 × 10 -3 ), but not NQO1*2 (β = 0.01, P = 0.30), were replicated in the Brazilians, explaining 43-46% of warfarin dose variability among the cohorts from the U.S. and Brazil, respectively. We identified genetic associations with warfarin dose requirements in the largest cohort of ancestrally diverse, warfarin-treated Latinos from the United States and Brazil to date. We confirmed the association of variants in VKORC1, CYP2C9, and CYP4F2 with warfarin dose in Latinos from the United States and Brazil., (© 2020 The Authors. Clinical and Translational Science published by Wiley Periodicals LLC on behalf of the American Society of Clinical Pharmacology and Therapeutics.)

Importance: Genotype-guided prescribing in pediatrics could prevent adverse drug reactions and improve therapeutic response. Clinical pharmacogenetic implementation guidelines are available for many medications commonly prescribed to children. Frequencies of medication prescription and actionable genotypes (genotypes where a prescribing change may be indicated) inform the potential value of pharmacogenetic implementation., Objective: To assess potential opportunities for genotype-guided prescribing in pediatric populations among multiple health systems by examining the prevalence of prescriptions for each drug with the highest level of evidence (Clinical Pharmacogenetics Implementation Consortium level A) and estimating the prevalence of potential actionable prescribing decisions., Design, Setting, and Participants: This serial cross-sectional study of prescribing prevalences in 16 health systems included electronic health records data from pediatric inpatient and outpatient encounters from January 1, 2011, to December 31, 2017. The health systems included academic medical centers with free-standing children's hospitals and community hospitals that were part of an adult health care system. Participants included approximately 2.9 million patients younger than 21 years observed per year. Data were analyzed from June 5, 2018, to April 14, 2020., Exposures: Prescription of 38 level A medications based on electronic health records., Main Outcomes and Measures: Annual prevalence of level A medication prescribing and estimated actionable exposures, calculated by combining estimated site-year prevalences across sites with each site weighted equally., Results: Data from approximately 2.9 million pediatric patients (median age, 8 [interquartile range, 2-16] years; 50.7% female, 62.3% White) were analyzed for a typical calendar year. The annual prescribing prevalence of at least 1 level A drug ranged from 7987 to 10 629 per 100 000 patients with increasing trends from 2011 to 2014. The most prescribed level A drug was the antiemetic ondansetron (annual prevalence of exposure, 8107 [95% CI, 8077-8137] per 100 000 children). Among commonly prescribed opioids, annual prevalence per 100 000 patients was 295 (95% CI, 273-317) for tramadol, 571 (95% CI, 557-586) for codeine, and 2116 (95% CI, 2097-2135) for oxycodone. The antidepressants citalopram, escitalopram, and amitriptyline were also commonly prescribed (annual prevalence, approximately 250 per 100 000 patients for each). Estimated prevalences of actionable exposures were highest for oxycodone and ondansetron (>300 per 100 000 patients annually). CYP2D6 and CYP2C19 substrates were more frequently prescribed than medications influenced by other genes., Conclusions and Relevance: These findings suggest that opportunities for pharmacogenetic implementation among pediatric patients in the US are abundant. As expected, the greatest opportunity exists with implementing CYP2D6 and CYP2C19 pharmacogenetic guidance for commonly prescribed antiemetics, analgesics, and antidepressants.

Recent CYP2D6 phenotype standardization efforts by CYP2D6 activity score (AS) are based on limited pharmacokinetic (PK) and pharmacodynamic (PD) data. Using data from two independent clinical trials of metoprolol, we compared metoprolol PK and PD across CYP2D6 AS with the goal of determining whether the PK and PD data support the new phenotype classification. S-metoprolol apparent oral clearance (CLo), adjusted for clinical factors, was correlated with CYP2D6 AS (P < 0.001). The natural log of CLo was lower with an AS of 1 (7.6 ± 0.4 mL/minute) vs. 2-2.25 (8.3 ± 0.6 mL/minute; P = 0.012), similar between an AS of 1 and 1.25-1.5 (7.8 ± 0.5 mL/minute; P = 0.702), and lower with an AS of 1.25-1.5 vs. 2-2.25 (P = 0.03). There was also a greater reduction in heart rate with metoprolol among study participants with AS of 1 (-10.8 ± 5.5) vs. 2-2.25 (-7.1 ± 5.6; P < 0.001) and no significant difference between those with an AS of 1 and 1.25-1.5 (-9.2 ± 4.7; P = 0.095). These data highlight linear trends among CYP2D6 AS and metoprolol PK and PD, but inconsistencies with the phenotypes assigned by AS based on the current standards. Overall, this case study with metoprolol suggests that utilizing CYP2D6 AS, instead of collapsing AS into phenotype categories, may be the most precise approach for utilizing CYP2D6 pharmacogenomics in clinical practice., (© 2020 The Authors. CPT: Pharmacometrics & Systems Pharmacology published by Wiley Periodicals LLC on behalf of the American Society for Clinical Pharmacology and Therapeutics.)

Purpose: Genotype-guided antiplatelet therapy is increasingly being incorporated into clinical care. The purpose of this study is to determine the extent to which patients initially genotyped for CYP2C19 to guide antiplatelet therapy were prescribed additional medications affected by CYP2C19., Methods: We assembled a cohort of patients from eight sites performingCYP2C19 genotyping to inform antiplatelet therapy. Medication orders were evaluated from time of genotyping through one year. The primary endpoint was the proportion of patients prescribed two or more CYP2C19 substrates. Secondary endpoints were the proportion of patients with a drug-genotype interaction and time to receiving a CYP2C19 substrate., Results: Nine thousand one hundred ninety-one genotyped patients (17% nonwhite) with a mean age of 68 ± 3 years were evaluated; 4701 (51%) of patients received two or more CYP2C19 substrates and 3835 (42%) of patients had a drug-genotype interaction. The average time between genotyping and CYP2C19 substrate other than antiplatelet therapy was 25 ± 10 days., Conclusions: More than half of patients genotyped in the setting of CYP2C19-guided antiplatelet therapy received another medication impacted by CYP2C19 in the following year. Given that genotype is stable for a patient's lifetime, this finding has implications for cost effectiveness, patient care, and treatment outcomes beyond the indication for which it was originally performed.

We aimed to estimate the utility of panel-based pharmacogenetic testing of patients undergoing percutaneous coronary intervention (PCI). Utilization of Clinical Pharmacogenetic Implementation Consortium (CPIC) level A/B drugs after PCI was estimated in a national sample of IBM MarketScan beneficiaries. Genotype data from University of Florida (UF) patients (n = 211) who underwent PCI were used to project genotype-guided opportunities among MarketScan beneficiaries with at least one (N = 105,547) and five (N = 12,462) years of follow-up data. The actual incidence of genotype-guided prescribing opportunities was determined among UF patients. In MarketScan, 50.0% (52,799/105,547) over 1 year and 68.0% (8,473/12,462) over 5 years had ≥ 1 CPIC A/B drug besides antiplatelet therapy prescribed, with a projected incidence of genotype-guided prescribing opportunities of 39% at 1 year and 52% at 5 years. Genotype-guided prescribing opportunities occurred in 32% of UF patients. Projected and actual incidence of genotype-guided opportunities among two cohorts supports the utility of panel-based testing among patients who underwent PCI., (© 2019 The Authors. Clinical and Translational Science published by Wiley Periodicals, Inc. on behalf of the American Society for Clinical Pharmacology and Therapeutics.)

European Americans (EA) have a better antihypertensive response to β-blockers when compared with African Americans, albeit with some variability. We undertook a genomewide association study to elucidate the underlying genetic determinants in EA contributing to this variability in blood pressure (BP) response. A discovery genomewide association study of change in BP post-metoprolol treatment was performed in EA participants (n = 201) from the Pharmacogenomic Evaluation of Antihypertensive Responses-2 (PEAR-2) study and tested for replication in the atenolol-treated EA from the PEAR study (n = 233). Rs294610 in the FGD5, which encodes for FYVE, RhoGEF and PH Domain Containing 5, (expression quantitative trait loci for FGD5 in the small intestine) was significantly associated with increased diastolic BP response to β-blockers in the PEAR-2 study (P = 3.41 × 10 -6 , β = -2.70) and replicated (P = 0.01, β = -1.17) in the PEAR study. Post-meta-analysis of these studies, an additional single nucleotide polymorphism rs45545233 in the SLC4A1, encoding for Solute Carrier Family 4 Member 1, (expression quantitative trait loci for dual specificity phosphatase 3 in the artery tibial) was identified that was significantly associated with a poor response to β-blockers (P = 3.43 × 10 -6 , β = 4.57) and was replicated in the atenolol add-on cohort (P = 0.007, β = 4.97). We identified variants in FGD5 and SLC4A1, which have been previously cited as candidate genes for hypertension, to be associated with a β-blocker BP response in EA. Further elucidation is warranted of the underlying mechanisms of these variants and genes by which they influence the BP response to β-blockers., (© 2019 The Authors. Clinical and Translational Science published by Wiley Periodicals, Inc. on behalf of the American Society for Clinical Pharmacology and Therapeutics.)

BackgroundThere exists a wide interindividual variability in blood pressure (BP) response to β 1 -blockers. To identify the genetic determinants of this variability, we performed a pharmacogenomic genome-wide meta-analysis of genetic variants influencing β 1 -blocker BP response.Methods and ResultsGenome-wide association analysis for systolic BP and diastolic BP response to β 1 -blockers from 5 randomized clinical trials consisting of 1254 patients with hypertension of European ancestry were combined in meta-analysis and single nucleotide polymorphisms (SNPs) with P<10 -4 were tested for replication in 2 independent randomized clinical trials of β 1 -blocker-treated patients of European ancestry (n=1552). Regions harboring the replicated SNPs were validated in a β 1 -blocker-treated black cohort from 2 randomized clinical trials (n=315). A missense SNP rs28404156 in BST1 was associated with systolic BP response to β 1 -blockers in the discovery meta-analysis (P=9.33×10 -5 , β=-3.21 mm Hg) and replicated at Bonferroni significance (P=1.85×10 -4 , β=-4.86 mm Hg) in the replication meta-analysis with combined meta-analysis approaching genome-wide significance (P=2.18×10 -7 ). This SNP in BST1 is in linkage disequilibrium with several SNPs with putative regulatory functions in nearby genes, including CD38, FBXL5, and FGFBP1, all of which have been implicated in BP regulation. SNPs in this genetic region were also associated with BP response in the black cohort.ConclusionsData from randomized clinical trials of 8 European ancestry and 2 black cohorts support the assumption that BST1 containing locus on chromosome 4 is associated with β 1 -blocker BP response. Given the previous associations of this region with BP, this is a strong candidate region for future functional studies and potential use in precision medicine approaches for BP management and risk prediction.

Resistant hypertension (RHTN), defined as uncontrolled blood pressure (BP) ≥ 140/90 using three or more drugs or controlled BP (<140/90) using four or more drugs, is associated with adverse outcomes, including decline in kidney function. We conducted a genome-wide association analysis in 1194 White and Hispanic participants with hypertension and coronary artery disease from the INternational VErapamil-SR Trandolapril STudy-GENEtic Substudy (INVEST-GENES). Top variants associated with RHTN at p < 10 -4 were tested for replication in 585 White and Hispanic participants with hypertension and subcortical strokes from the Secondary Prevention of Subcortical Strokes GENEtic Substudy (SPS3-GENES). A genetic risk score for RHTN was created by summing the risk alleles of replicated RHTN signals. rs11749255 in MSX2 was associated with RHTN in INVEST (odds ratio (OR) (95% CI) = 1.50 (1.2-1.8), p = 7.3 × 10 -5 ) and replicated in SPS3 (OR = 2.0 (1.4-2.8), p = 4.3 × 10 -5 ), with genome-wide significance in meta-analysis (OR = 1.60 (1.3-1.9), p = 3.8 × 10 -8 ). Other replicated signals were in IFLTD1 and PTPRD. IFLTD1 rs6487504 was associated with RHTN in INVEST (OR = 1.90 (1.4-2.5), p = 1.1 × 10 - 5 ) and SPS3 (OR = 1.70 (1.2-2.5), p = 4 × 10 -3 ). PTPRD rs324498, a previously reported RHTN signal, was among the top signals in INVEST (OR = 1.60 (1.3-2.0), p = 3.4 × 10 - 5 ) and replicated in SPS3 (OR = 1.60 (1.1-2.4), one-sided p = 0.005). Participants with the highest number of risk alleles were at increased risk of RHTN compared to participants with a lower number (p-trend = 1.8 × 10 -15 ). Overall, we identified and replicated associations with RHTN in the MSX2, IFLTD1, and PTPRD regions, and combined these associations to create a genetic risk score.

Recent advances in DNA sequencing technologies are revealing how human genetic variations associate with differential health risks, disease susceptibilities, and drug responses. Such information is now expected to help evaluate individual health risks, design personalized health plans and treat patients with precision. It is still challenging, however, to understand how such genetic variations cause the phenotypic alterations in pathobiologies and treatment response. Human induced pluripotent stem cell (iPSC) technologies are emerging as a promising strategy to fill the knowledge gaps between genetic association studies and underlying molecular mechanisms. Breakthroughs in genome editing technologies and continuous improvement in iPSC differentiation techniques are particularly making this research direction more realistic and practical. Pioneering studies have shown that iPSCs derived from a variety of monogenic diseases can faithfully recapitulate disease phenotypes in vitro when differentiated into disease-relevant cell types. It has been shown possible to partially recapitulate disease phenotypes, even with late onset and polygenic diseases. More recently, iPSCs have been shown to validate effects of disease and treatment-related single nucleotide polymorphisms identified through genome wide association analysis. In this review, we will discuss how iPSC research will further contribute to human health in the coming era of precision medicine. Stem Cells 2017;35:545-550., (© 2017 AlphaMed Press.)

Unlabelled: Studies in hypertension (HTN) pharmacogenomics seek to identify genetic sources of variable antihypertensive drug response. Genetic association studies have detected single-nucleotide polymorphisms (SNPs) that link to drug responses; however, to understand mechanisms underlying how genetic traits alter drug responses, a biological interface is needed. Patient-derived induced pluripotent stem cells (iPSCs) provide a potential source for studying otherwise inaccessible tissues that may be important to antihypertensive drug response. The present study established multiple iPSC lines from an HTN pharmacogenomics cohort. We demonstrated that established HTN iPSCs can robustly and reproducibly differentiate into functional vascular smooth muscle cells (VSMCs), a cell type most relevant to vasculature tone control. Moreover, a sensitive traction force microscopy assay demonstrated that iPSC-derived VSMCs show a quantitative contractile response on physiological stimulus of endothelin-1. Furthermore, the inflammatory chemokine tumor necrosis factor α induced a typical VSMC response in iPSC-derived VSMCs. These studies pave the way for a large research initiative to decode biological significance of identified SNPs in hypertension pharmacogenomics., Significance: Treatment of hypertension remains suboptimal, and a pharmacogenomics approach seeks to identify genetic biomarkers that could be used to guide treatment decisions; however, it is important to understand the biological underpinnings of genetic associations. Mouse models do not accurately recapitulate individual patient responses based on their genetics, and hypertension-relevant cells are difficult to obtain from patients. Induced pluripotent stem cell (iPSC) technology provides a great interface to bring patient cells with their genomic data into the laboratory and to study hypertensive responses. As an initial step, the present study established an iPSC bank from patients with primary hypertension and demonstrated an effective and reproducible method of generating functional vascular smooth muscle cells., (©AlphaMed Press.)