Genetic risk factors for drug-induced long QT syndrome: findings from a large real-world case-control study.

Aim: Drug-induced long QT syndrome (diLQTS), an adverse effect of many drugs, can lead to sudden cardiac death. Candidate genetic variants in cardiac ion channels have been associated with diLQTS, but several limitations of previous studies hamper clinical utility. Materials & methods: Thus, the purpose of this study was to assess the associations of KCNE1-D85N, KCNE2-I57T and SCN5A-G615E with diLQTS in a large observational case-control study (6,083 self-reported white patients treated with 27 different high-risk QT-prolonging medications; 12.0% with diLQTS). Results: KCNE1-D85N significantly associated with diLQTS (adjusted odds ratio: 2.24 [95% CI: 1.35-3.58]; p = 0.001). Given low minor allele frequencies, the study had insufficient power to analyze KCNE2-I57T and SCN5A-G615E. Conclusion: KCNE1-D85N is a risk factor for diLQTS that should be considered in future clinical practice guidelines.

Some medications can lead to a condition called drug-induced long QT syndrome (diLQTS), which can be a serious abnormal heart rhythm in some patients. In our research, we explored three specific changes in DNA related to the electrical function of the heart (KCNE1-D85N, KCNE2-I57T, SCN5A-G615E) and their link to diLQTS. Our study revealed a connection between KCNE1-D85N and diLQTS. This study emphasized the importance of including KCNE1-D85N in the medical guidelines to help identify patients at risk of diLQTS. We were unable to identify the connection of KCNE2-I57T and SCN5A-G615E with diLQTS, due to a low number of carriers in the study.

Risk scores for major bleeding from direct oral anticoagulants: comparing predictive performance in patients with atrial fibrillation.

Background: Despite direct oral anticoagulants (DOACs) being safer than warfarin for stroke prevention in atrial fibrillation (AF), major bleeding concerns persist. Most bleeding risk scores predate DOAC approval. Objectives: This study aimed to compare the Age, history of Bleeding, and non-bleeding related Hospitalisation [ABH] score's performance-derived for DOAC-treated patients-with those of 5 other scores (Anticoagulation and Risk Factors in Atrial Fibrillation [ATRIA], Hypertension, Abnormal renal/liver function, Stroke, Bleeding history or predisposition, Labile international normalized ratio, Elderly [>65 years], Drugs/alcohol concomitantly [HAS-BLED], Hepatic, Hepatic or Renal Disease, Ethanol Abuse, Malignancy, Older Age, Reduced Platelet Count or Function, Re-Bleeding, Hypertension, Anemia, Genetic Factors, Excessive Fall Risk and Stroke [HEMORR2HAGES], Outcomes Registry for Better Informed Treatment of Atrial Fibrillation [ORBIT-AF], and Congestive heart failure, Hypertension, Age ≥75 [doubled], Diabetes, Stroke [doubled]-Vascular disease, Age 65-74, Sex category [CHA2DS2-VASc]) in predicting DOAC-related major bleeding in patients with AF. Methods: In this retrospective study of 2364 patients with nonvalvular AF on rivaroxaban or apixaban (median age, 68.3 years; 32.1% women), International Society on Thrombosis and Haemostasis-defined major bleeding (incidence, 4.1%; n = 97) was analyzed. C-statistics from time-dependent receiver operating characteristic (ROC) curves for continuous risk scores were the primary comparison metric, but other metrics, such as decision curves, were also compared. Results: At 100 days, C-statistics were highest for ORBIT-AF and ATRIA (0.62 and 0.61, respectively, with other scores having an area under the ROC curve of <0.60); some significant differences favored ORBIT-AF. At 1100 days, C-statistics remained highest for ORBIT-AF and ATRIA (0.62 and 0.61, respectively, with other scores having an area under the ROC curve of <0.60 again), and ORBIT-AF had significantly higher C-statistics than those for all other risk scores (P < .05), except for ATRIA. At 2100 days, all C-statistics were <0.60 with no significant differences. Decision curves showed the greatest net benefit for ORBIT-AF and ATRIA at 100 days and for ATRIA at 1100 days, with no discernible net benefit for any of the scores at 2100 days. Conclusion: ORBIT-AF and ATRIA provided the best bleeding risk prediction within the first 1100 days. None of the 6 bleeding risk scores provided predictive benefit over 2100 days of DOAC treatment.

Genome-Wide Association Study of Beta-Blocker Survival Benefit in Black and White Patients with Heart Failure with Reduced Ejection Fraction.

In patients with heart failure with reduced ejection fraction (HFrEF), individual responses to beta-blockers vary. Candidate gene pharmacogenetic studies yielded significant but inconsistent results, and they may have missed important associations. Our objective was to use an unbiased genome-wide association study (GWAS) to identify loci influencing beta-blocker survival benefit in HFrEF patients. Genetic variant × beta-blocker exposure interactions were tested in Cox proportional hazards models for all-cause mortality stratified by self-identified race. The models were adjusted for clinical risk factors and propensity scores. A prospective HFrEF registry (469 black and 459 white patients) was used for discovery, and linkage disequilibrium (LD) clumped variants with a beta-blocker interaction of p < 5 × 10-5, were tested for Bonferroni-corrected validation in a multicenter HFrEF clinical trial (288 black and 579 white patients). A total of 229 and 18 variants in black and white HFrEF patients, respectively, had interactions with beta-blocker exposure at p < 5 × 10-5 upon discovery. After LD-clumping, 100 variants and 4 variants in the black and white patients, respectively, remained for validation but none reached statistical significance. In conclusion, genetic variants of potential interest were identified in a discovery-based GWAS of beta-blocker survival benefit in HFrEF patients, but none were validated in an independent dataset. Larger cohorts or alternative approaches, such as polygenic scores, are needed.

Common Variants on FGD5 Increase Hazard of Mortality or Rehospitalization in Patients With Heart Failure From the ASCEND-HF Trial.

BACKGROUND: Heart failure remains a global health burden, and patients hospitalized are particularly at risk, but genetic associates for subsequent death or rehospitalization are still lacking. METHODS: The genetic substudy of the ASCEND-HF trial (Acute Study of Clinical Effectiveness of Nesiritide in Decompensated Heart Failure) was used to perform genome-wide association study and transethnic meta-analysis. The overall trial included the patients of self-reported European ancestry (n=2173) and African ancestry (n=507). The end point was death or heart failure rehospitalization within 180 days. Cox models adjusted for 11 a priori predictors of rehospitalization and 5 genetic principal components were used to test the association between single-nucleotide polymorphisms and outcome. Summary statistics from the 2 populations were combined via meta-analysis with the significance threshold considered P<5×10-8. RESULTS: Common variants (rs2342882 and rs35850039 in complete linkage disequilibrium) located in FGD5 were significantly associated with the primary outcome in both ancestry groups (European Americans: hazard ratio [HR], 1.38; P=2.42×10-6; African ancestry: HR, 1.51; P=4.43×10-3; HR in meta-analysis, 1.41; P=4.25×10-8). FGD5 encodes a regulator of VEGF (vascular endothelial growth factor)-mediated angiogenesis, and in silico investigation revealed several previous genome-wide association study hits in this gene, among which rs748431 was associated with our outcome (HR, 1.20; meta P<0.01). Sensitivity analysis proved FGD5 common variants survival association did not appear to operate via coronary artery disease or nesiritide treatment (P>0.05); and the signal was still significant when changing the censoring time from 180 to 30 days (HR, 1.39; P=1.59×10-5). CONCLUSIONS: In this multiethnic genome-wide association study of ASCEND-HF, single-nucleotide polymorphisms in FGD5 were associated with increased risk of death or rehospitalization. Additional investigation is required to examine biological mechanisms and whether FGD5 could be a therapeutic target. REGISTRATION: URL: https://www. CLINICALTRIALS: gov; Unique identifier: NCT00475852.

An Introductory Tutorial on Cardiovascular Pharmacogenetics for Healthcare Providers.

Pharmacogenetics can improve clinical outcomes by reducing adverse drug effects and enhancing therapeutic efficacy for commonly used drugs that treat a wide range of cardiovascular diseases. One of the major barriers to the clinical implementation of cardiovascular pharmacogenetics is limited education on this field for current healthcare providers and students. The abundance of pharmacogenetic literature underscores its promise, but it can also be challenging to learn such a wealth of information. Moreover, current clinical recommendations for cardiovascular pharmacogenetics can be confusing because they are outdated, incomplete, or inconsistent. A myriad of misconceptions about the promise and feasibility of cardiovascular pharmacogenetics among healthcare providers also has halted clinical implementation. Therefore, the main goal of this tutorial is to provide introductory education on the use of cardiovascular pharmacogenetics in clinical practice. The target audience is any healthcare provider (or student) with patients that use or have indications for cardiovascular drugs. This tutorial is organized into the following 6 steps: (1) understand basic concepts in pharmacogenetics; (2) gain foundational knowledge of cardiovascular pharmacogenetics; (3) learn the different organizations that release cardiovascular pharmacogenetic guidelines and recommendations; (4) know the current cardiovascular drugs/drug classes to focus on clinically and the supporting evidence; (5) discuss an example patient case of cardiovascular pharmacogenetics; and (6) develop an appreciation for emerging areas in cardiovascular pharmacogenetics. Ultimately, improved education among healthcare providers on cardiovascular pharmacogenetics will lead to a greater understanding for its potential in improving outcomes for a leading cause of morbidity and mortality.

Evaluation of a New Aptamer-Based Array for Soluble Suppressor of Tumorgenicity (ST2) and N-terminal Pro-B-Type Natriuretic Peptide (NTproBNP) in Heart Failure Patients.

BACKGROUND: Recent advances in multi-marker platforms offer faster data generation, but the fidelity of these methods compared to the ELISA is not established. We tested the correlation and predictive performance of SOMAscan vs. ELISA methods for NTproBNP and ST2. METHODS: Patients ≥ 18 years with heart failure and ejection fraction < 50% were enrolled. We tested the correlation between SOMA and ELISA for each biomarker and their association with outcomes. RESULTS: There was good correlation of SOMA vs. ELISA for ST2 (ρ = 0.71) and excellent correlation for NTproBNP (ρ = 0.94). The two versions of both markers were not significantly different regarding survival association. The two ST2 assays and NTproBNP assays were similarly associated with all-cause mortality and cardiovascular mortality. These associations remained statistically significant when adjusted for MAGGIC risk score (all p < 0.05). CONCLUSION: SOMAscan quantifications of ST2 and NTproBNP correlate to ELISA versions and carry similar prognosis.

Pharmacogenetics of Antiplatelet Therapy.

Antiplatelet therapy is used in the treatment of patients with acute coronary syndromes, stroke, and those undergoing percutaneous coronary intervention. Clopidogrel is the most widely used antiplatelet P2Y12 inhibitor in clinical practice. Genetic variation in CYP2C19 may influence its enzymatic activity, resulting in individuals who are carriers of loss-of-function CYP2C19 alleles and thus have reduced active clopidogrel metabolites, high on-treatment platelet reactivity, and increased ischemic risk. Prospective studies have examined the utility of CYP2C19 genetic testing to guide antiplatelet therapy, and more recently published meta-analyses suggest that pharmacogenetics represents a key treatment strategy to individualize antiplatelet therapy. Rapid genetic tests, including bedside genotyping platforms that are validated and have high reproducibility, are available to guide selection of P2Y12 inhibitors in clinical practice. The aim of this review is to provide an overview of the background and rationale for the role of a guided antiplatelet approach to enhance patient care.

Eight pharmacokinetic genetic variants are not associated with the risk of bleeding from direct oral anticoagulants in non-valvular atrial fibrillation patients.

Background: Atrial fibrillation (AF) is the leading cause of ischemic stroke and treatment has focused on reducing this risk through anticoagulation. Direct Oral Anticoagulants (DOACs) are the first-line guideline-recommended therapy since they are as effective and overall safer than warfarin in preventing AF-related stroke. Although patients bleed less from DOACs compared to warfarin, bleeding remains the primary safety concern with this therapy. Hypothesis: Genetic variants known to modify the function of metabolic enzymes or transporters involved in the pharmacokinetics (PK) of DOACs could increase the risk of bleeding. Aim: To assess the association of eight, functional PK-related single nucleotide variants (SNVs) in five genes (ABCB1, ABCG2, CYP2J2, CYP3A4, CYP3A5) with the risk of bleeding from DOACs in non-valvular AF patients. Methods: A retrospective cohort study was carried out with 2,364 self-identified white non-valvular AF patients treated with either rivaroxaban or apixaban. Genotyping was performed with Illumina Infinium CoreExome v12.1 bead arrays by the Michigan Genomics Initiative biobank. The primary endpoint was a composite of major and clinically relevant non-major bleeding. Cox proportional hazards regression with time-varying analysis assessed the association of the eight PK-related SNVs with the risk of bleeding from DOACs in unadjusted and covariate-adjusted models. The pre-specified primary analysis was the covariate-adjusted, additive genetic models. Six tests were performed in the primary analysis as three SNVs are in the same haplotype, and thus p-values below the Bonferroni-corrected level of 8.33e-3 were considered statistically significant. Results: In the primary analysis, none of the SNVs met the Bonferroni-corrected level of statistical significance (all p > 0.1). In exploratory analyses with other genetic models, the ABCB1 (rs4148732) GG genotype tended to be associated with the risk of bleeding from rivaroxaban [HR: 1.391 (95%CI: 1.019-1.900); p = 0.038] but not from apixaban (p = 0.487). Conclusion: Eight functional PK-related genetic variants were not significantly associated with bleeding from either rivaroxaban or apixaban in more than 2,000 AF self-identified white outpatients.

Association of Valproic Acid Use With Post-Myocardial Infarction Heart Failure Development: A Meta-Analysis of Two Retrospective Case-Control Studies.

BACKGROUND: Despite advances in treatments, myocardial infarction (MI) remains a significant cause of morbidity and mortality worldwide. Our team has previously shown that valproic acid (VPA) is cardio-protective when administered to rats post-MI. The aim of this study was to investigate the association of VPA use with post-MI heart failure (HF) development in humans. METHODS: This study was a random effects meta-analysis of two retrospective case-control studies collected from electronic health record (Michigan Medicine) and claims data (OptumInsight). Cases with an active prescription for VPA at the time of their MI were matched 1:4 to controls not taking VPA at the time of their MI by multiple demographic and clinical characteristics. The primary outcome, time-to-HF development, was analyzed using the Fine-Gray competing risks model of any VPA prescription versus no VPA prescription. An exploratory analysis was conducted to evaluate the association of different VPA doses (≥1000 mg/day vs <1000 mg/day vs 0 mg/day VPA). RESULTS: In total, the datasets included 1313 patients (249 cases and 1064 controls). In the meta-analysis, any dose of VPA during an MI tended to be protective against incident HF post-MI (HR = 0.87; 95% CI = 0.72-1.01). However, when stratified by dose, high-dose VPA (≥1000 mg/day) significantly associated with 30% reduction in risk for HF post-MI (HR = 0.70; 95% CI = 0.49-0.91), whereas low-dose VPA (<1000 mg/day) did not (HR = 0.95; 95% CI = 0.78-1.13). CONCLUSION: VPA doses ≥1000 mg/day may provide post-MI cardio-protection resulting in a reduced incidence of HF.

Polygenic Risk Scores for Cardiovascular Disease: A Scientific Statement From the American Heart Association.

Cardiovascular disease is the leading contributor to years lost due to disability or premature death among adults. Current efforts focus on risk prediction and risk factor mitigation' which have been recognized for the past half-century. However, despite advances, risk prediction remains imprecise with persistently high rates of incident cardiovascular disease. Genetic characterization has been proposed as an approach to enable earlier and potentially tailored prevention. Rare mendelian pathogenic variants predisposing to cardiometabolic conditions have long been known to contribute to disease risk in some families. However, twin and familial aggregation studies imply that diverse cardiovascular conditions are heritable in the general population. Significant technological and methodological advances since the Human Genome Project are facilitating population-based comprehensive genetic profiling at decreasing costs. Genome-wide association studies from such endeavors continue to elucidate causal mechanisms for cardiovascular diseases. Systematic cataloging for cardiovascular risk alleles also enabled the development of polygenic risk scores. Genetic profiling is becoming widespread in large-scale research, including in health care-associated biobanks, randomized controlled trials, and direct-to-consumer profiling in tens of millions of people. Thus, individuals and their physicians are increasingly presented with polygenic risk scores for cardiovascular conditions in clinical encounters. In this scientific statement, we review the contemporary science, clinical considerations, and future challenges for polygenic risk scores for cardiovascular diseases. We selected 5 cardiometabolic diseases (coronary artery disease, hypercholesterolemia, type 2 diabetes, atrial fibrillation, and venous thromboembolic disease) and response to drug therapy and offer provisional guidance to health care professionals, researchers, policymakers, and patients.

The genetics of drug-induced QT prolongation: evaluating the evidence for pharmacodynamic variants.

Drug-induced long QT syndrome (diLQTS) is an adverse effect of many commonly prescribed drugs, and it can increase the risk for lethal ventricular arrhythmias. Genetic variants in pharmacodynamic genes have been associated with diLQTS, but the strength of the evidence for each of those variants has not yet been evaluated. Therefore, the purpose of this review was to evaluate the strength of the evidence for pharmacodynamic genetic variants associated with diLQTS using a novel, semiquantitative scoring system modified from the approach used for congenital LQTS. KCNE1-D85N and KCNE2-T8A had definitive and strong evidence for diLQTS, respectively. The high level of evidence for these variants supports current consideration as risk factors for patients that will be prescribed a QT-prolonging drug.

Coenzyme Q10 supplementation for the treatment of statin-associated muscle symptoms.

Aim: To determine the association of coenzyme Q10 (CoQ10) use with the resolution of statin-associated muscle symptoms (SAMS). Patients & methods: Retrospective analysis of a large, multicenter survey study of SAMS (total n = 511; n = 64 CoQ10 users). Univariate and multivariate logistic regression models assessed the association between CoQ10 use and the resolution of SAMS. Results: The frequency of SAMS resolution was similar between CoQ10 users and non-users (25% vs 31%, respectively; unadjusted odds ratio [OR]: 0.75 [95% CI: 0.41-1.38]; p = 0.357). Similarly, CoQ10 use was not significantly associated with the resolution of SAMS in multivariable models adjusted for SAMS risk factors (OR: 0.84 [95% CI: 0.45-1.55]; p = 0.568) or adjusted for significant differences among CoQ10 users and non-users (OR: 0.82 [95% CI: 0.45-1.51]; p = 0.522). Conclusion: CoQ10 was not significantly associated with the resolution of SAMS.

Statins are medications that help lower cholesterol and treat cardiovascular disease, but muscle pain is the most common side effect of statins. Statins decrease the body's levels of coenzyme Q10 (CoQ10), and thus taking CoQ10 supplements (which are widely available over the counter in pharmacies) may help treat the muscle side effects from statins. However, the results of previous studies are not clear whether CoQ10 is effective for treating statin-associated muscle symptoms. Therefore, the purpose of this study was to analyze whether the use of CoQ10 supplements improved statin-associated muscle side effects in a large group of individuals. When the authors compared the survey responses of 64 CoQ10 users versus those of 447 non-CoQ10 users with statin-associated muscle symptoms, CoQ10 supplements did not improve their muscle symptoms.

The Clinical Pharmacogenetics Implementation Consortium Guideline for SLCO1B1, ABCG2, and CYP2C9 genotypes and Statin-Associated Musculoskeletal Symptoms.

Statins reduce cholesterol, prevent cardiovascular disease, and are among the most commonly prescribed medications in the world. Statin-associated musculoskeletal symptoms (SAMS) impact statin adherence and ultimately can impede the long-term effectiveness of statin therapy. There are several identified pharmacogenetic variants that impact statin disposition and adverse events during statin therapy. SLCO1B1 encodes a transporter (SLCO1B1; alternative names include OATP1B1 or OATP-C) that facilitates the hepatic uptake of all statins. ABCG2 encodes an efflux transporter (BCRP) that modulates the absorption and disposition of rosuvastatin. CYP2C9 encodes a phase I drug metabolizing enzyme responsible for the oxidation of some statins. Genetic variation in each of these genes alters systemic exposure to statins (i.e., simvastatin, rosuvastatin, pravastatin, pitavastatin, atorvastatin, fluvastatin, lovastatin), which can increase the risk for SAMS. We summarize the literature supporting these associations and provide therapeutic recommendations for statins based on SLCO1B1, ABCG2, and CYP2C9 genotype with the goal of improving the overall safety, adherence, and effectiveness of statin therapy. This document replaces the 2012 and 2014 Clinical Pharmacogenetics Implementation Consortium (CPIC) guidelines for SLCO1B1 and simvastatin-induced myopathy.

Clinical Pharmacogenetics Implementation Consortium Guideline for CYP2C19 Genotype and Clopidogrel Therapy: 2022 Update.

CYP2C19 catalyzes the bioactivation of the antiplatelet prodrug clopidogrel, and CYP2C19 genotype impacts clopidogrel active metabolite formation. CYP2C19 intermediate and poor metabolizers who receive clopidogrel experience reduced platelet inhibition and increased risk for major adverse cardiovascular and cerebrovascular events. This guideline is an update to the 2013 Clinical Pharmacogenetics Implementation Consortium (CPIC) guideline for the use of clopidogrel based on CYP2C19 genotype and includes expanded indications for CYP2C19 genotype-guided antiplatelet therapy, increased strength of recommendation for CYP2C19 intermediate metabolizers, updated CYP2C19 genotype to phenotype translation, and evidence from an expanded literature review (updates at www.cpicpgx.org).

Comparison of clinical pharmacogenetic recommendations across therapeutic areas.

OBJECTIVES: Evaluations from pharmacogenetics implementation programs at major US medical centers have reported variability in the clinical adoption of pharmacogenetics across therapeutic areas. A potential cause for this variability may involve therapeutic area-specific differences in published pharmacogenetics recommendations to clinicians. To date, however, the potential for differences in clinical pharmacogenetics recommendations by therapeutic areas from prominent US guidance sources has not been assessed. Accordingly, our objective was to comprehensively compare essential elements from clinical pharmacogenetics recommendations contained within Clinical Pharmacogenetics Implementation Consortium guidelines, US Food and Drug Administration drug labels and clinical practice guidelines from US professional medical organizations across therapeutic areas. METHODS: We analyzed clinical pharmacogenetics recommendation elements within Clinical Pharmacogenetics Implementation Consortium guidelines, US Food and Drug Administration drug labels and professional clinical practice guidelines through 05/24/19. RESULTS: We identified 606 unique clinical pharmacogenetics recommendations, with the most recommendations involving oncology (217 recommendations), hematology (79), psychiatry (65), cardiovascular (43) and anesthetic (37) medications. Within our analyses, we observed considerable variability across therapeutic areas within the following essential pharmacogenetics recommendation elements: the recommended clinical management strategy; the relevant genetic biomarkers; the organizations providing pharmacogenetics recommendations; whether routine genetic screening was recommended; and the time since recommendations were published. CONCLUSIONS: On the basis of our results, we infer that observed differences in clinical pharmacogenetics recommendations across therapeutic areas may result from specific factors associated with individual disease states, the associated genetic biomarkers, and the characteristics of the organizations providing recommendations.

Survival Association of Angiotensin Inhibitors in Heart Failure With Reduced Ejection Fraction: Comparisons Using Self-Identified Race and Genomic Ancestry.

BACKGROUND: It remains unclear whether there is a racial disparity in the response to angiotensin inhibitors in patients with heart failure with reduced ejection fraction (HFrEF) and whether the role of genomic ancestry plays a part. Therefore, we compared survival rates associated with angiotensin inhibitors in patients with HFrEF by self-identified race and proportion of West African genomic ancestry. METHODS: Three datasets totaling 1153 and 1480 self-identified Black and White patients, respectively, with HFrEF were meta-analyzed (random effects model) for race-based analyses. One dataset had genomic data for ancestry analyses (416 and 369 self-identified Black and White patients, respectively). Cox proportional hazards regression, adjusted for propensity scores, assessed the association of angiotensin inhibitor exposure with all-cause mortality by self-identified race or proportion of West African genomic ancestry. RESULTS: In meta-analysis of self-identified race, adjusted hazard ratios (95% CI) for exposure to angiotensin inhibitors were similar in self-identified Black and White patients with HFrEF: 0.52 (0.31-0.85) P = 0.006 and 0.54 (0.42-0.71) P = 0.001, respectively. Results were similar when the proportion of West African genomic ancestry was > 80% or < 5%: 0.66 (0.34-1.25) P = 0.200 and 0.56 (0.26-1.23) P = 0.147, respectively. CONCLUSIONS: Among self-identified Black and White patients with HFrEF, reduction in all-cause mortality associated with exposure to angiotensin inhibitors was similar regardless of self-identified race or proportion of West African genomic ancestry.

The need to shift pharmacogenetic research from candidate gene to genome-wide association studies.

The primary research approach in pharmacogenetics has been candidate gene association studies (CGAS), but pharmacogenomic genome-wide association studies (GWAS) are becoming more common. We are now at a critical juncture when the results of those two research approaches, CGAS and GWAS, can be compared in pharmacogenetics. We analyzed publicly available databases of pharmacogenetic CGAS and GWAS (i.e., the Pharmacogenomics Knowledgebase [PharmGKB®] and the NHGRI-EBI GWAS catalog) and the vast majority of variants (98%) and genes (94%) discovered in pharmacogenomic GWAS were novel (i.e., not previously studied CGAS). Therefore, pharmacogenetic researchers are not selecting the right candidate genes in the vast majority of CGAS, highlighting a need to shift pharmacogenetic research efforts from CGAS to GWAS.

Comparative performance of the two pooled cohort equations for predicting atherosclerotic cardiovascular disease.

BACKGROUND AND AIMS: Multivariable algorithms have been developed to predict the risk of atherosclerotic cardiovascular disease (ASCVD) to identify high-risk patients. Shortly after the introduction of the AHA/ACC Pooled Cohort Equations (PCE), a systematic overestimation of risk was identified. As such, a revised PCE was proposed to more accurately assess ASCVD risk. This study aims to compare the accuracy of both PCE in predicting ASCVD risk within a large, real-world patient sample in the US. METHODS: This retrospective cohort study identified 20,843 patients aged between 40 and 75 years with no previous ASCVD in an academic healthcare system. Model fit, calibration, and discrimination were compared between PCE using Bayesian Information Criterion (BIC), Hosmer-Lemeshow test, area under the ROC curves (AUC), Brier score, and precision-recall analysis. In addition, we examined race and sex subgroups for effect modification. RESULTS: Both PCE showed poor calibration (Hosmer-Lemeshow χ2 > 20; p < 0.05) and discrimination (AUC<0.7). The lack of improvement in discrimination of the revised PCE (AUC: 0.677 vs 0.679; p = 0.357) was confirmed with the AUC precision-recall curves (AUCPR: 0.0717 vs 0.0698). In contrast, the AHA/ACC PCE showed a strong positive risk prediction (ΔBIC>10) compared to the revised PCE, although calibration curves had overlapped. CONCLUSIONS: In this single center analysis, both PCE had poor calibration and discrimination of ASCVD risk in a large, real-world patient sample followed up for over 2 years. There was no evidence of improvement in the accuracy of the revised PCE in assessing the risk of ASCVD in relation to the AHA/ACC PCE.