Cardiovascular Pharmacogenomics: Does It Matter If You're Black or White?

Research on genetic variant characteristics in ADME genes based on whole-exome sequencing in the Han Chinese population

BACKGROUND

Genetic variants in absorption, distribution, metabolism, and excretion (ADME) genes affect drug efficacy and side effects. Whole-exome sequencing (WES) effectively identifies these variants. Findings from Western populations may not apply to the Han Chinese population due to ethnic differences.

OBJECTIVE

This study aimed to investigate genetic variants, metabolic phenotypes, and drug impacts related to ADME genes in the Han Chinese population using WES data.

METHODS

ADME genes and drug profiles were sourced from multiple databases. WES data were collected from 357 samples at Third Xiangya Hospital and 5,000 samples from the "HuaBiao Project." After WES, fastp was used for quality control; BWA, samtools, and the Picard software were used for comparison, sequencing, and de-duplication; GATK was used for base quality score recalibration; and variant quality score recalibration was carried out after detecting the variants, and the variants were annotated using ANNOVAR. ADME genes and drug profiles were obtained through PharmGKB and other databases, and then all variants in the exonic regions of ADME genes were extracted. The distributional characteristics of these variants, ethnic differences, and metabolic phenotype distribution of important ADME genes, such as CYP2B6, were analyzed. Prediction of deleterious variants of ADME gene employed the ADME gene variant prediction framework, and western blotting and enzyme assays were used to validate the impact of harmful variants.

RESULTS

We integrated 604 ADME genes and 972 drugs. There were 33,925 single nucleotide polymorphisms (SNPs) and 484 insertion-deletions (InDels) in 5,357 Han Chinese WES samples; 88.9 % were rare. Of the SNPs, 60.9 % are new functional mutations in enzyme and transporter genes; InDels also affected these genes. We discovered Chinese-specific variants in key ADME genes and ethnic-specific metabolic phenotypes that could affect drug use. Finally, we screened 3,657 potentially harmful mutations; 45.6 % are novel. Western blotting and enzyme activity assays confirmed several harmful mutations significantly reduced CYP2C19 gene expression and function (P < 0.01).

Implementing differentially pigmented skin models for predicting drug response variability across human ancestries

Persistent racial disparities in health outcomes have catalyzed legislative reforms and heightened scientific focus recently. However, despite the well-documented properties of skin pigments in binding drug compounds, their impact on therapeutic efficacy and adverse drug responses remains insufficiently explored. This perspective examines the intricate relationships between variation in melanin-based skin pigmentation and pharmacokinetics and -dynamics, highlighting the need for considering diversity in skin pigmentation as a variable to advance the equitability of pharmacological interventions. The article provides guidelines on the selection of New Approach Methods (NAMs) to foster inclusive study designs in preclinical drug development pipelines, leading to an improved level of translatability to the clinic.

Toward building a comprehensive human pan-genome: The SEN-GENOME project

The human reference genome (GRCh38), primarily sourced from individuals of European descent, falls short in capturing the vast genetic diversity across global populations. Efforts to diversify the reference genome face challenges in accessibility and representation, exacerbating the scarcity of African genomic data crucial for studying diseases prevalent in these populations. Sherman et al. proposed constructing reference genomes tailored to distinct human sub-populations. Their African Pan-Genome initiative highlighted substantial genetic variation missing from the GRCh38 human reference genome, emphasizing the necessity for population-specific genomes. In response, local initiatives like the Senegalese Genome project (SEN-GENOME) have emerged to document the genomes of historically overlooked populations. SEN-GENOME embodies community-driven decentralized research. With meticulous recruitment criteria and ethical practices, it aims to sequence 1,000 genomes from 31 ethnolinguistic groups, in the fourteen administrative regions of Senegal, fostering local genomic research tailored to the region. The key to SEN-GENOME's success is its commitment to local governance of data, capacity building, and integration with broader pan-genome projects in Africa. Despite the complexities of data harmonization and sharing, our collaborative efforts are aligned with common goals, ensuring steady progress toward a comprehensive human pan-genome. We invite and welcome collaboration with other research entities to achieve this shared vision. In summary, local initiatives such as SEN-GENOME are pivotal in bridging genomic disparities, offering pathways to equitable and inclusive genomic research. Collaborative endeavors guided by a collective vision for human health will propel us toward a more encompassing understanding of the human genome and better health through genomic medicine.

Population-enriched innate immune variants may identify candidate gene targets at the intersection of cancer and cardio-metabolic disease

Both cancer and cardio-metabolic disease disparities exist among specific populations in the US. For example, African Americans experience the highest rates of breast and prostate cancer mortality and the highest incidence of obesity. Native and Hispanic Americans experience the highest rates of liver cancer mortality. At the same time, Pacific Islanders have the highest death rate attributed to type 2 diabetes (T2D), and Asian Americans experience the highest incidence of non-alcoholic fatty liver disease (NAFLD) and cancers induced by infectious agents. Notably, the pathologic progression of both cancer and cardio-metabolic diseases involves innate immunity and mechanisms of inflammation. Innate immunity in individuals is established through genetic inheritance and external stimuli to respond to environmental threats and stresses such as pathogen exposure. Further, individual genomes contain characteristic genetic markers associated with one or more geographic ancestries (ethnic groups), including protective innate immune genetic programming optimized for survival in their corresponding ancestral environment(s). This perspective explores evidence related to our working hypothesis that genetic variations in innate immune genes, particularly those that are commonly found but unevenly distributed between populations, are associated with disparities between populations in both cancer and cardio-metabolic diseases. Identifying conventional and unconventional innate immune genes that fit this profile may provide critical insights into the underlying mechanisms that connect these two families of complex diseases and offer novel targets for precision-based treatment of cancer and/or cardio-metabolic disease.

Functional Roles of Furin in Cardio-Cerebrovascular Diseases

Furin plays a major role in post-translational modification of several biomolecules, including endogenous hormones, growth factors, and cytokines. Recent reports have demonstrated the association of furin and cardio-cerebrovascular diseases (CVDs) in humans. This review describes the possible pathogenic contribution of furin and its substrates in CVDs. Early-stage hypertension and diabetes mellitus show a negative correlation with furin. A reduction in furin might promote hypertension by decreasing maturation of B-type natriuretic peptide (BNP) or by decreasing shedding of membrane (pro)renin receptor (PRR), which facilitates activation of the renin-angiotensin-aldosterone system (RAAS). In diabetes, furin downregulation potentially leads to insulin resistance by reducing maturation of the insulin receptor. In contrast, the progression of other CVDs is associated with an increase in furin, including dyslipidemia, atherosclerosis, ischemic stroke, myocardial infarction (MI), and heart failure. Upregulation of furin might promote maturation of membrane type 1-matrix metalloproteinase (MT1-MMP), which cleaves low-density lipoprotein receptor (LDLR), contributing to dyslipidemia. In atherosclerosis, elevated levels of furin possibly enhance maturation of several substrates related to inflammation, cell proliferation, and extracellular matrix (ECM) deposition and degradation. Neuronal cell death following ischemic stroke has also been shown to involve furin substrates (e.g., MT1-MMP, hepcidin, and hemojuvelin). Moreover, furin and its substrates, including tumor necrosis factor-α (TNF-α), endothelin-1 (ET-1), and transforming growth factor-β1 (TGF-β1), are capable of mediating inflammation, hypertrophy, and fibrosis in MI and heart failure. Taken together, this evidence provides functional significance of furin in CVDs and might suggest a potential novel therapeutic modality for the management of CVDs.

Should secondary pharmacogenomic variants be actively screened and reported when diagnostic genome-wide sequencing is performed in a child?

This white paper was prepared by the Global Alliance for Genomics and Health Regulatory and Ethics Work Stream's Pediatric Task Team to review and provide perspective with respect to ethical, legal, and social issues regarding the return of secondary pharmacogenomic variants in children who have a serious disease or developmental disorder and are undergoing exome or genome sequencing to identify a genetic cause of their condition. We discuss actively searching for and reporting pharmacogenetic/genomic variants in pediatric patients, different methods of returning secondary pharmacogenomic findings to the patient/parents and/or treating clinicians, maintaining these data in the patient's health record over time, decision supports to assist using pharmacogenetic results in future treatment decisions, and sharing information in public databases to improve the clinical interpretation of pharmacogenetic variants identified in other children. We conclude by presenting a series of points to consider for clinicians and policymakers regarding whether, and under what circumstances, routine screening and return of pharmacogenomic variants unrelated to the indications for testing is appropriate in children who are undergoing genome-wide sequencing to assist in the diagnosis of a suspected genetic disease.

Harnessing population diversity: in search of tools of the trade

Big neuroscience datasets are not big small datasets when it comes to quantitative data analysis. Neuroscience has now witnessed the advent of many population cohort studies that deep-profile participants, yielding hundreds of measures, capturing dimensions of each individual's position in the broader society. Indeed, there is a rebalancing from small, strictly selected, and thus homogenized cohorts toward always larger, more representative, and thus diverse cohorts. This shift in cohort composition is prompting the revision of incumbent modeling practices. Major sources of population stratification increasingly overshadow the subtle effects that neuroscientists are typically studying. In our opinion, as we sample individuals from always wider diversity backgrounds, we will require a new stack of quantitative tools to realize diversity-aware modeling. We here take inventory of candidate analytical frameworks. Better incorporating driving factors behind population structure will allow refining our understanding of how brain-behavior relationships depend on human subgroups.

CYP2D6 and CYP2C19 Genes Associated with Tricontinental and Latin American Ancestry of Pe-ruvians

Precision medicine seeks to individualize the dose from the beginning of phar-macological therapy based on the characteristics of each patient, genes involved in the metabolic phenotype, ethnicity or miscegenation, with the purpose to minimize adverse effects and optimize drug efficacy. The objective was to re-view studies that describe the association of the CYP2D6 and CYP2C19 genes with the tricontinental and Latin American ancestry of Peruvians. A biblio-graphic search was carried out in PubMed/Medline and SciELO, with various descriptors in Spanish and English. The results of this review confirm that the ethnic origin of Peruvians is triconti-nental due to European (mainly Spanish), African and Asian migration, in addi-tion to Latin American migration, being 60.2% mixed, 25.8% Amerindian, 5.9% white, 3.6% African descent, 1.2% Chinese and Japanese descent, and 3.3% unspecified. Studies on CYP2C19*3, CYP2D6*2, *3 and *6 have been reported in Peruvians, and the frequency is similar to that studied in Ecuadori-ans and Colombians. The CYP2C19*3, CYP2D6*3, and CYP2D6*6 alleles found in Peruvians are common in Europeans, Africans, and Asians; while CYP2D6*4 in Africans and CYP2D6*2 related to Asians. In some studies, the ethnic/gene association has not been demonstrated; while others have shown a significant association, which is why further investigation is warranted. It is concluded that the studies on CYP2D6 and CYP2C19 genes associated with the tricontinental and Latin American ancestry of Peruvians are little, and ac-cording to what has been investigated, the CYP2C19*3, CYP2D6*2, *3, *4 and *6 alleles have more related to their ancestry.

Modular networks and genomic variation during progression from stable angina pectoris through ischemic cardiomyopathy to chronic heart failure

Background

Analyzing disease–disease relationships plays an important role for understanding etiology, disease classification, and drug repositioning. However, as cardiovascular diseases with causative links, the molecular relationship among stable angina pectoris (SAP), ischemic cardiomyopathy (ICM) and chronic heart failure (CHF) is not clear.

Methods

In this study, by integrating the multi-database data, we constructed paired disease progression modules (PDPMs) to identified relationship among SAP, ICM and CHF based on module reconstruction pairs (MRPs) of K-value calculation (a Euclidean distance optimization by integrating module topology parameters and their weights) methods. Finally, enrichment analysis, literature validation and structural variation (SV) were performed to verify the relationship between the three diseases in PDPMs.

Results

Total 16 PDPMs were found with K > 0.3777 among SAP, ICM and CHF, in which 6 pairs in SAP–ICM, 5 pairs for both ICM–CHF and SAP–CHF. SAP–ICM was the most closely related by having the smallest average K-value (K = 0.3899) while the maximum is SAP–CHF (K = 0.4006). According to the function of the validation gene, inflammatory response were through each stage of SAP–ICM–CHF, while SAP–ICM was uniquely involved in fibrosis, and genes were related in affecting the upstream of PI3K–Akt signaling pathway. 4 of the 11 genes (FLT1, KDR, ANGPT2 and PGF) in SAP–ICM–CHF related to angiogenesis in HIF-1 signaling pathway. Furthermore, we identified 62.96% SVs were protein deletion in SAP–ICM–CHF, and 53.85% SVs were defined as protein replication in SAP–ICM, while ICM–CHF genes were mainly affected by protein deletion.

Conclusion

The PDPMs analysis approach combined with genomic structural variation provides a new avenue for determining target associations contributing to disease progression and reveals that inflammation and angiogenesis may be important links among SAP, ICM and CHF progression.

Pharmacogenomic Biomarkers

Why does the usual dose of medication work for a person while another individual cannot give the expected response to the same drug? On the other hand, how come half of the usual dose of an analgesic relieves an individual’s pain immediately, as another man continue to suffer even after taking double dose? Although a treatment method has been successfully used in majority of the population for many years, why does the same therapy cause serious side effects in another region of the world? Most presently approved therapies are not effective in all patients. For example, 20-40% of patients with depression respond poorly or not at all to antidepressant drug therapy. Many patients are resistant to the effects of antiasthmatics and antiulcer drugs or drug treatment of hyperlipidemia and many other diseases. The reason for all those is basically interindividual differences in genomic structures of people, which are explained in this chapter in terms of the systems and the most frequently used drugs in clinical treatment.

Rates of genetic testing in patients prescribed drugs with pharmacogenomic information in FDA-approved labeling

This study examined rates of genetic testing in two cohorts of publicly insured individuals who have newly prescribed medication with FDA pharmacogenomic labeling guidance. Genetic testing was rare (4.4% and 10.5% in Medicaid and Medicare cohorts, respectively) despite the fact that all participants selected were taking medications that contained pharmacogenomic labeling information. When testing was conducted it was typically done before the initial use of a target medication. Factors that emerged as predictors of the likelihood of undergoing genetic testing included White ethnicity (vs. Black), female gender, and age. Cost analyses indicated higher expenditures in groups receiving genetic testing vs. matched comparators with no genetic testing, as well as disparities between proactively and reactively tested groups (albeit in opposite directions across cohorts). Results are discussed in terms of the possible reasons for the low base rate of testing, mechanisms of increased cost, and barriers to dissemination and implementation of these tests.

Metabolizer phenotype prediction in different Peruvian ethnic groups through CYP2C9 polymorphisms

OBJECTIVES

The CYP2C9 gene have three common alleles, CYP2C9*1, CYP2C9*2 and CYP2C9*3, associated with different homozygous (*1/*1, *2/*2 and *3/*3) and heterozygous (*1/*2 and *1/*3) genotypes, which in turn are related to extensive (gEM), intermediate (gIM) and poor (gPM) metabolizers. Likewise, the inter-ethnic variability was intimately associated with different drug metabolism. Therefore, the aim of the present study was predict the metabolizer phenotypes in different Peruvian ethnic groups from lowland (<2,500 m) and highland (>2,500 m).

METHODS

TaqMan genotyping assays were performed in a group of 174 healthy unrelated Peruvian individuals.

RESULTS

In this study, the allelic comparison between the three eco-regions showed that the CYP2C9*1 was the most common in Andean (96.32%); the *2 was the most frequent in Coast (7.45%, p<0.05). Regarding the *3 was the most common in Amazonian (6.25%, p<0.05). In a corroborative manner, the gEM was the most common in Andean (94.74%), the gIM in Coast (17.02%) and gPM in Amazonian (6.25%) populations.

CONCLUSIONS

Our study provides a valuable source of information about to metabolizer phenotype drugs in different Peruvian ethnic groups. In this way, it could be established suitable genetic-dosage medicaments for various common diseases in these heterogenetic populations.

Pharmacogenomic Biomarkers in US FDA-Approved Drug Labels (2000-2020)

Pharmacogenomics (PGx) is a key subset of precision medicine that relates genomic variation to individual response to pharmacotherapy. We assessed longitudinal trends in US FDA approval of new drugs labeled with PGx information. Drug labels containing PGx information were obtained from Drugs@FDA and guidelines from PharmGKB were used to compare the actionability of PGx information in drug labels across therapeutic areas. The annual proportion of new drug approvals with PGx labeling has increased by nearly threefold from 10.3% (n = 3) in 2000 to 28.2% (n = 11) in 2020. Inclusion of PGx information in drug labels has increased for all clinical areas over the last two decades but most prominently for cancer therapies, which comprise the largest proportion (75.5%) of biomarker–drug pairs for which PGx testing is required. Clinically actionable information was more frequently observed in biomarker–drug pairs associated with cancer drugs compared to those for other therapeutic areas (n = 92 (59.7%) vs. n = 62 (40.3%), p < 0.0051). These results suggest that further evidence is needed to support the clinical adoption of pharmacogenomics in non-cancer therapeutic areas.

Influence of CYP4F2, ApoE, and CYP2A6 gene polymorphisms on the variability of Warfarin dosage requirements and susceptibility to cardiovascular disease in Jordan

Cardiovascular diseases are among the leading causes of death worldwide. Many of those diseases require treatment with warfarin, an anticoagulant that has a large high inter and intra-variability in the required doses. The aim of this study is to find if there are any associations between rs2108622 of CYP4F2, rs7412 and rs405509 of ApoE, and rs1801272 of CYP2A6, and CVD and warfarin dose variability. The selected genes and their polymorphisms are involved in many GWAS associated with cardiovascular disease and variability in warfarin treatment. The study sample consisted of 212 Jordanian Cardiovascular patients and 213 healthy controls. DNA was extracted and the Mass ARRAY™ system was used to genotype four selected SNPs within three genes (CYP4F2, ApoE, and CYP2A6). Only one out of the four selected SNPs (ApoE rs7412 SNP) was found to be associated with the risk of cardiovascular disease. Also, this SNP showed significant differences in warfarin initial doses. CYP2A6 rs1801272 SNP was found to be associated with warfarin sensitivity during the initiation phase of therapy and with warfarin responsiveness and INR measurement during the stabilization phase of therapy. This study improves the current understanding of the high inter and intra-variabilities in response to warfarin, including the variety of dosing requirements and the susceptibility to cardiovascular disease in the Jordanian Arab population. Further study on a larger sample and in different ethnic groups could help in improving our understanding of warfarin's pharmacogenetics and its application in personalized medicine.

Digital Health Applications for Pharmacogenetic Clinical Trials

Digital health (DH) is the use of digital technologies and data analytics to understand health-related behaviors and enhance personalized clinical care. DH is increasingly being used in clinical trials, and an important field that could potentially benefit from incorporating DH into trial design is pharmacogenetics. Prospective pharmacogenetic trials typically compare a standard care arm to a pharmacogenetic-guided therapeutic arm. These trials often require large sample sizes, are challenging to recruit into, lack patient diversity, and can have complicated workflows to deliver therapeutic interventions to both investigators and patients. Importantly, the use of DH technologies could mitigate these challenges and improve pharmacogenetic trial design and operation. Some DH use cases include (1) automatic electronic health record-based patient screening and recruitment; (2) interactive websites for participant engagement; (3) home- and tele-health visits for patient convenience (e.g., samples for lab tests, physical exams, medication administration); (4) healthcare apps to collect patient-reported outcomes, adverse events and concomitant medications, and to deliver therapeutic information to patients; and (5) wearable devices to collect vital signs, electrocardiograms, sleep quality, and other discrete clinical variables. Given that pharmacogenetic trials are inherently challenging to conduct, future pharmacogenetic utility studies should consider implementing DH technologies and trial methodologies into their design and operation.

The Advantages and Challenges of Diversity in Pharmacogenomics: Can Minority Populations Bring Us Closer to Implementation?

Health disparities exist among minorities in the United States, with differences seen in disease prevalence, mortality, and responses to medications. These differences are multifactorial with genetic variation explaining a portion of this variability. Pharmacogenomics aims to find the effect of genetic variations on drug response, with the goal of optimizing drug therapy and development. Although genome-wide association studies have been useful in unbiasedly surveying the genome for genetic drivers of clinically relevant phenotypes, most of these studies have been conducted in mainly participants of European and Asian descent, contributing to a growing health disparity in precision medicine. Diversity is important to pharmacogenomic studies, and there may be real advantages to the use of these complex genomes in pharmacogenomics. In this review we will outline some of the advantages and confounders of pharmacogenomics in minorities, describe the role of genetic variation in pharmacologic pathways, and highlight a number of population-specific findings.

Discovery of novel hepatocyte eQTLs in African Americans

African Americans (AAs) are disproportionately affected by metabolic diseases and adverse drug events, with limited publicly available genomic and transcriptomic data to advance the knowledge of the molecular underpinnings or genetic associations to these diseases or drug response phenotypes. To fill this gap, we obtained 60 primary hepatocyte cultures from AA liver donors for genome-wide mapping of expression quantitative trait loci (eQTL) using LAMatrix. We identified 277 eGenes and 19,770 eQTLs, of which 67 eGenes and 7,415 eQTLs are not observed in the Genotype-Tissue Expression Project (GTEx) liver eQTL analysis. Of the eGenes found in GTEx only 25 share the same lead eQTL. These AA-specific eQTLs are less correlated to GTEx eQTLs. in effect sizes and have larger Fst values compared to eQTLs found in both cohorts (overlapping eQTLs). We assessed the overlap between GWAS variants and their tagging variants with AA hepatocyte eQTLs and demonstrated that AA hepatocyte eQTLs can decrease the number of potential causal variants at GWAS loci. Additionally, we identified 75,002 exon QTLs of which 48.8% are not eQTLs in AA hepatocytes. Our analysis provides the first comprehensive characterization of AA hepatocyte eQTLs and highlights the unique discoveries that are made possible due to the increased genetic diversity within the African ancestry genome.

Hepatocyte gene expression and DNA methylation as ancestry-dependent mechanisms in African Americans

African Americans (AAs) are an admixed population with widely varying proportion of West African ancestry (WAA). Here we report the correlation of WAA to gene expression and DNA methylation in AA-derived hepatocytes, a cell type important in disease and drug response. We perform mediation analysis to test whether methylation is a mediator of the effect of ancestry on expression. GTEx samples and a second cohort are used as validation. One hundred and thirty-one genes are associated with WAA (FDR < 0.10), 28 of which replicate and represent 220 GWAS phenotypes. Among PharmGKB pharmacogenes, VDR, PTGIS, ALDH1A1, CYP2C19, and P2RY1 nominally associate with WAA (p < 0.05). We find 1037 WAA-associated, differentially methylated regions (FDR < 0.05), with hypomethylated genes enriched in drug-response pathways. In conclusion, WAA contributes to variability in hepatocyte expression and DNA methylation with identified genes previously implicated for diseases disproportionately affecting AAs, including cardiovascular (PTGIS, PLAT) and renal (APOL1) disease, and drug response (CYP2C19).

Projected Prevalence of Actionable Pharmacogenetic Variants and Level A Drugs Prescribed Among US Veterans Health Administration Pharmacy Users

IMPORTANCE

Implementation of pharmacogenetic testing to guide drug prescribing has potential to improve drug response and prevent adverse events. Robust data exist for more than 30 gene-drug pairs linking genotype to drug response phenotypes; however, it is unclear which pharmacogenetic tests, if implemented, would provide the greatest utility for a given patient population.

OBJECTIVES

To project the proportion of veterans in the US Veterans Health Administration (VHA) with actionable pharmacogenetic variants and evaluate how testing might be associated with prescribing decisions.

DESIGN, SETTING, AND PARTICIPANTS

This cross-sectional study included veterans who used national VHA pharmacy services from October 1, 2011, to September 30, 2017. Data analyses began April 26, 2018, and were completed February 6, 2019.

EXPOSURES

Receipt of level A drugs based on VHA pharmacy dispensing records.

MAIN OUTCOMES AND MEASURES

Projected prevalence of actionable pharmacogenetic variants among VHA pharmacy users based on variant frequencies from the 1000 Genomes Project and veteran demographic characteristics; incident number of level A prescriptions, and proportion of new level A drug recipients projected to carry an actionable pharmacogenetic variant.

RESULTS

During the study, 7 769 359 veterans (mean [SD] age, 58.1 [17.8] years; 7 021 504 [90.4%] men) used VHA pharmacy services. It was projected that 99% of VHA pharmacy users would carry at least 1 actionable pharmacogenetic variant. Among VHA pharmacy users, 4 259 153 (54.8%) received at least 1 level A drug with 1 188 124 (15.3%) receiving 2 drugs, and 912 189 (11.7%) receiving 3 or more drugs. The most common incident prescriptions during the study were tramadol (923 671 new recipients), simvastatin (533 928 new recipients), citalopram (266 952 new recipients), and warfarin (205 177 new recipients). Gene-drug interactions projected to have substantial clinical impacts in the VHA population include the interaction of SLCO1B1 with simvastatin (1 988 956 veterans [25.6%]), CYP2D6 with tramadol (318 544 veterans [4.1%]), and CYP2C9 or VKORC1 with warfarin (7 163 349 veterans [92.2%]).

CONCLUSIONS AND RELEVANCE

Clinically important pharmacogenetic variants are highly prevalent in the VHA population. Almost all veterans would carry an actionable variant, and more than half of the population had been exposed to a drug affected by these variants. These results suggest that pharmacogenetic testing has the potential to affect pharmacotherapy decisions for commonly prescribed outpatient medications for many veterans.