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.

CYP2C19 Genetic Testing for Oral P2Y12 Inhibitor Therapy: A Scientific Statement From the American Heart Association.

There is significant variability in the efficacy and safety of oral P2Y12 inhibitors, which are used to prevent ischemic outcomes in common diseases such as coronary and peripheral arterial disease and stroke. Clopidogrel, a prodrug, is the most used oral P2Y12 inhibitor and is activated primarily after being metabolized by a highly polymorphic hepatic cytochrome CYP2C219 enzyme. Loss-of-function genetic variants in CYP2C219 are common, can result in decreased active metabolite levels and increased on-treatment platelet aggregation, and are associated with increased ischemic events on clopidogrel therapy. Such patients can be identified by CYP2C19 genetic testing and can be treated with alternative therapy. Conversely, universal use of potent oral P2Y12 inhibitors such as ticagrelor or prasugrel, which are not dependent on CYP2C19 for activation, has been recommended but can result in increased bleeding. Recent clinical trials and meta-analyses have demonstrated that a precision medicine approach in which loss-of-function carriers are prescribed ticagrelor or prasugrel and noncarriers are prescribed clopidogrel results in reducing ischemic events without increasing bleeding risk. The evidence to date supports CYP2C19 genetic testing before oral P2Y12 inhibitors are prescribed in patients with acute coronary syndromes or percutaneous coronary intervention. Clinical implementation of such genetic testing will depend on among multiple factors: rapid availability of results or adoption of the concept of performing preemptive genetic testing, provision of easy-to-understand results with therapeutic recommendations, and seamless integration in the electronic health record.

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.

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.

Pharmacogenetic study in gastric cancer patients treated with adjuvant fluorouracil/leucovorin or epirubicin/cisplatin/fluorouracil before and after chemoradiation on CALGB 80101 (Alliance).

There is a lack of pharmacogenetic predictors of outcome in gastric cancer patients. The aim of this study was to assess previously identified candidate genes associated with 5-fluorouracil (5-FU), cisplatin, or epirubicin toxicity or response in a cohort of resected gastric cancer patients treated on CALGB (Alliance) 80101. Gastric or gastroesophageal cancer patients randomized to adjuvant 5-FU/leucovorin or epirubicin/cisplatin/5-FU before and after 5-FU chemoradiation were genotyped for single nucleotide polymorphisms (SNPs) in GSTP1 (rs1695), ERCC1 (rs11615 and rs3212986), XRCC1 (rs25487), UGT2B7 (rs7439366) and the 28 base-pair tandem repeats in TYMS (rs34743033). Logistic regression and log rank tests were used to assess the association between each SNP and incidence of grade 3/4 neutropenia and leukopenia, overall (OS) and progression-free survival (PFS), respectively. Toxicity endpoint analyses were adjusted for the treatment arm, while OS and PFS were also adjusted for performance status, sex, age, lymph node involvement, and primary tumor site and size. Of 281 subjects with successful genotyping results and available clinical (toxicity and efficacy) data, 166 self-reported non-Hispanic White patients were included in the final analysis. There was a lack of evidence of an association among any SNPs tested with grade 3/4 neutropenia and leukopenia or OS and PFS. Age, lymph node involvement, and primary tumor size were significantly associated with OS and PFS. This study failed to confirm results of previous gastric cancer pharmacogenetic studies.

Fewer patients receive recommendations for pharmacotherapy in primary prevention using the 2018 atherosclerotic cardiovascular disease risk estimator.

Shortly after the introduction of the 2013 original Pooled Cohort Equation (PCE), an overestimation of risk was suggested. As such, the updated 2018 PCE was developed to more accurately assess atherosclerotic cardiovascular disease (ASCVD) risk in the population. Hence, this study aims to compare drug prescribing recommendations in a large, real-world patient population, depending on which PCE is used to estimate 10-year ASCVD risk. This retrospective cohort study identified 20,843 patients aged between 40 and 75 years with no previous ASCVD. The 10-year ASCVD risk score was assessed by using both PCE. Patients were assigned to the four risk categories according to the 2018 ACC/AHA guideline. The percentage of patients qualifying for guideline-recommended primary prevention with statins and/or anti-hypertensives were compared between both PCE. Risk reclassification occurred in 26.7% of patients overall (n = 5571), of which 98.1% (n = 5466) were assigned to lower risk categories with the updated PCE. Non-diabetic (14.0%) patients no longer met the threshold for recommending statins as primary prevention with the updated PCE. Likewise, 13.8% of patients with stage I hypertension no longer met the threshold for recommending antihypertensive drugs with the updated PCE. In conclusion, risk reclassification occurred among 26.7% of patients overall, mostly due to lower risk categories assigned by the updated PCE. Up to 14.0% of patients no longer met the threshold for recommending statin therapy and/or antihypertensive drugs by using the updated PCE. These findings suggest that using the updated PCE could translate into fewer patients receiving pharmacotherapy for ASCVD primary prevention.

Association of SLCO1B1 c.521T>C (rs4149056) with discontinuation of atorvastatin due to statin-associated muscle symptoms.

The most common adverse drug reaction from statins are statin-associated muscle symptoms (SAMS), characterized by myopathy (weakness), myalgia (muscle pain), and commonly elevation in serum creatine kinase. All statins are substrates of the organic anion transporter 1B1 (OATP1B1; gene: SLCO1B1), albeit to different degrees. A genetic polymorphism in SLCO1B1, c.521T>C (rs4149056), markedly decreases OATP1B1 function. The literature is currently unclear as to whether SLCO1B1 c.521T>C is significantly associated with discontinuation of atorvastatin specifically due to SAMS. Our hypothesis was that individuals carrying the SLCO1B1 decreased function 521C allele are more likely to discontinue atorvastatin due to SAMS. This was a retrospective analysis of survey data from 379 Caucasians genotyped for rs4149056 and treated with atorvastatin for at least 12 months. Crude and multivariable logistic regression, adjusted for established risk factors for SAMS, determined the association of SLCO1B1 c.521T>C with discontinuation of atorvastatin due to SAMS (SLCO1B1 521T-homozygotes vs. 521C-carriers). The sample was 51% male, with a mean age of 57 years (SD = 11). Sixty-one percent of participants reported discontinuing atorvastatin due to SAMS, and 32% overall carried the 521C allele. SLCO1B1 521C-carrier status was not a significant predictor of atorvastatin discontinuation in any model: crude OR = 1.07; 95% CI, 0.68-1.66; P = 0.78 and adjusted OR = 1.07; 95% CI, 0.68-1.69; P = 0.76. The results were similar in a sub-group of participants treated with higher doses of atorvastatin (>20 mg). In summary, SLCO1B1 c.521T>C was not significantly associated with discontinuation of atorvastatin therapy due to SAMS.

Clinical features related to statin-associated muscle symptoms.

INTRODUCTION: Statins reduce cardiovascular disease risk and are generally well tolerated, yet up to 0.5% of statin-treated patients develop incapacitating muscle symptoms including rhabdomyolysis. Our objective was to identify clinical factors related to statin-associated muscle symptoms (SAMS). METHODS: Clinical and laboratory characteristics were evaluated in 748 statin-treated Caucasians (634 with SAMS and 114 statin-tolerant controls). Information was collected on statin type, concomitant drug therapies, muscle symptom history, comorbidities, and family history. Logistic regression was used to identify associations. RESULTS: Individuals with SAMS were 3.6 times (odds ratio [OR] 3.60, 95% confidence interval [CI] 2.08-6.22) more likely than statin-tolerant controls to have a family history of heart disease. Additional associations included obesity (OR 3.08, 95% CI 1.18, 8.05), hypertension (OR 2.24, 95% CI 1.33, 3.77), smoking (OR 2.08, 95% CI 1.16, 3.74), and statin type. DISCUSSION: Careful medical monitoring of statin-treated patients with the associated coexisting conditions may ultimately reduce muscle symptoms and lead to improved compliance. Muscle Nerve 59:537-537, 2019.

Association of Regulatory Genetic Variants for Protein Kinase Cα with Mortality and Drug Efficacy in Patients with Heart Failure.

PURPOSE: Protein kinase C alpha (gene: PRKCA) is a key regulator of cardiac contractility. Two genetic variants have recently been discovered to regulate PRKCA expression in failing human heart tissue (rs9909004 [T → C] and rs9303504 [C → G]). The association of those variants with clinical outcomes in patients with heart failure (HF), and their interaction with HF drug efficacy, is unknown. METHODS: Patients with HF in a prospective registry starting in 2007 were genotyped by whole genome array (n = 951). The primary outcome was all-cause mortality. Cox proportional hazards models adjusted for established clinical risk factors and genomic ancestry tested the independent association of rs9909004 or rs9303504 and the variant interactions with cornerstone HF pharmacotherapies (beta-blockers or angiotensin-converting enzyme inhibitors/angiotensin receptor blockers) in additive genetic models. RESULTS: The minor allele of rs9909004, but not of rs9303504, was independently associated with a decreased risk for all-cause mortality: adjusted HR = 0.81 (95% CI = 0.67-0.98), p = 0.032. The variants did not significantly interact with mortality benefit associated with cornerstone HF pharmacotherapies (p > 0.1 for all). CONCLUSIONS: A recently discovered cardiac-specific regulatory variant for PRKCA (rs9909004) was independently associated with a decreased risk for all-cause mortality in patients with HF. The variant did not interact with mortality benefit associated with cornerstone HF pharmacotherapies.

Germline genetic variants with implications for disease risk and therapeutic outcomes.

Genetic testing has multiple clinical applications including disease risk assessment, diagnosis, and pharmacogenomics. Pharmacogenomics can be utilized to predict whether a pharmacologic therapy will be effective or to identify patients at risk for treatment-related toxicity. Although genetic tests are typically ordered for a distinct clinical purpose, the genetic variants that are found may have additional implications for either disease or pharmacology. This review will address multiple examples of germline genetic variants that are informative for both disease and pharmacogenomics. The discussed relationships are diverse. Some of the agents are targeted for the disease-causing genetic variant, while others, although not targeted therapies, have implications for the disease they are used to treat. It is also possible that the disease implications of a genetic variant are unrelated to the pharmacogenomic implications. Some of these examples are considered clinically actionable pharmacogenes, with evidence-based, pharmacologic treatment recommendations, while others are still investigative as areas for additional research. It is important that clinicians are aware of both the disease and pharmacogenomic associations of these germline genetic variants to ensure patients are receiving comprehensive personalized care.

CYP2D6 Genetic Variation and Beta-Blocker Maintenance Dose in Patients with Heart Failure.

PURPOSE: This study examined whether a CYP2D6 polymorphism (CYP2D6*4) was related to beta-blocker maintenance dose in patients with heart failure. METHODS: Logistic regression modeling was utilized in a retrospective chart-review analysis of heart-failure patients (60% Male, 90% of European descent) to assess whether CYP2D6*4 (non-functional CYP2D6 allele present in 1 of 5 individuals of European descent) is associated with maintenance dose of carvedilol (n = 65) or metoprolol (n = 33). RESULTS: CYP2D6*4 was associated with lower maintenance dose of metoprolol (OR 0.13 [95% CI 0.02-0.75] p = 0.023), and a trend was observed between CYP2D6*4 and higher maintenance dose of carvedilol (OR 2.94 [95% CI 0.84-10.30] p = 0.093). None of the patients that carried CYP2D6*4 achieved the recommended target dose of metoprolol (200 mg/day). CONCLUSION: Consistent with the role of CYP2D6 in the metabolism of metoprolol, the tolerated maintenance dose of metoprolol was lower in CYP2D6*4 carriers compared to non-carriers. Consistent with the role of CYP2D6 in activation of carvedilol, tolerated maintenance dose of carvedilol was higher in CYP2D6*4 carriers compared to non-carriers. Further investigation is warranted to ascertain the potential of CYP2D6 as a potential predictive biomarker of beta-blocker maintenance dose in heart failure patients.

Individual and Combined Associations of Genetic Variants in CYP3A4, CYP3A5, and SLCO1B1 With Simvastatin and Simvastatin Acid Plasma Concentrations.

Our objective was to evaluate the associations of genetic variants affecting simvastatin (SV) and simvastatin acid (SVA) metabolism [the gene encoding cytochrome P450, family 3, subfamily A, polypeptide 4 (CYP3A4)*22 and the gene encoding cytochrome P450, family 3, subfamily A, polypeptide 5 (CYP3A5)*3] and transport [the gene encoding solute carrier organic anion transporter family member 1B1 (SLCO1B1) T521C] with 12-hour plasma SV and SVA concentrations. The variants were genotyped, and the concentrations were quantified by high performance liquid chromatography-tandem mass spectrometry in 646 participants of the Cholesterol and Pharmacogenetics clinical trial of 40 mg/d SV for 6 weeks. The genetic variants were tested for association with 12-hour plasma SV, SVA, or the SVA/SV ratio using general linear models. CYP3A5*3 was not significantly associated with 12-hour plasma SV or SVA concentration. CYP3A4*1/*22 participants had 58% higher 12-hour plasma SV concentration compared with CYP3A4*1/*1 participants (P = 0.006). SLCO1B1 521T/C and 521C/C participants had 71% (P < 0.001) and 248% (P < 0.001) higher 12-hour plasma SVA compared with SLCO1B1 521T/T participants, respectively. CYP3A4 and SLCO1B1 genotypes combined categorized participants into low (<1), intermediate (≈1), and high (>1) SVA/SV ratio groups (P = 0.001). In conclusion, CYP3A4*22 and SLCO1B1 521C were significantly associated with increased 12-hour plasma SV and SVA concentrations, respectively. CYP3A5*3 was not significantly associated with 12-hour plasma SV or SVA concentrations. The combination of CYP3A4*22 and SLCO1B1 521C was significantly associated with SVA/SV ratio, which may translate into different clinical SV risk/benefit profiles.

CYP3A4*22 and CYP3A5*3 are associated with increased levels of plasma simvastatin concentrations in the cholesterol and pharmacogenetics study cohort.

OBJECTIVE: Simvastatin is primarily metabolized by CYP3A4. A combined CYP3A4/5 genotype classification, combining the decrease-of-function CYP3A4*22 and the loss-of-function CYP3A5*3, has recently been reported. We aim to determine whether CYP3A4*22 and CYP3A5*3 alleles are associated with increased plasma concentrations of simvastatin lactone (SV) and simvastatin acid (SVA). This is the first report evaluating associations between in-vivo simvastatin concentrations and CYP3A4*22, alone or in a combined CYP3A4/5 genotype-defined classification. PARTICIPANTS AND METHODS: Genotypes and simvastatin concentrations were determined for 830 participants (555 Whites and 275 African-Americans) in the Cholesterol and Pharmacogenomics clinical trial with 40 mg/day simvastatin for 6 weeks. Concentrations were determined in 12-h postdose samples. Associations between simvastatin concentrations and CYP3A4*22 and CYP3A5*3 alleles were tested separately and in a combined CYP3A4/5 genotype-defined classification system. RESULTS: In Whites, CYP3A4*22 carriers (n=42) had 14% higher SVA (P=0.04) and 20% higher SV (P=0.06) compared with noncarriers (n=513). CYP3A5*3 allele status was not significantly associated with SV or SVA in Whites. In African-Americans, CYP3A4*22 carriers (n=8) had 170% higher SV (P<0.01) than noncarriers (n=267), but no significant difference was detected for SVA. African-American CYP3A5 nonexpressors (n=28) had 33% higher SV (P=0.02) than CYP3A5 expressors (n=247), but no significant difference was detected for SVA. For both races, SV appeared to decrease across the rank-ordered combined CYP3A4/5 genotype-defined groups (poor, intermediate, and extensive metabolizers); however, similar trends were not observed for SVA. CONCLUSION: Genetic variation in CYP3A4 was associated with plasma simvastatin concentrations in self-reported Whites. Genetic variations in CYP3A4 and CYP3A5 were associated with plasma simvastatin concentrations in self-reported African-Americans.

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.

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.

Genetic drivers of human plasma metabolites that determine mortality in heart failure patients with reduced ejection fraction.

Background: Heart failure with reduced ejection fraction (HFrEF) remains a significant public health issue, with the disease advancing despite neurohormonal antagonism. Energetic dysfunction is a likely contributor to residual disease progression, and we have previously reported a strong association of plasma metabolite profiles with survival among patients with HFrEF. However, the genetic and biologic mechanisms that underlie the metabolite-survival association in HFrEF were uncertain. Methods and results: We performed genetic mapping of the key metabolite parameters, followed by mediation analyses of metabolites and genotypes on survival, and genetic pathway analyses. Patients with HFrEF (n = 1,003) in the Henry Ford Pharmacogenomic Registry (HFPGR; 500 self-reported Black/African race patients [AA], 503 self-reported White/European race patients [EA], and 249 deaths over a median of 2.7 years) with genome-wide genotyping and targeted metabolomic profiling of plasma were included. We tested genome-wide association (GWA) of single nucleotide polymorphisms (SNPs) with the prognostic metabolite profile (PMP) and its components; first stratified by race, and then combined via meta-analysis for the entire cohort. Seven independent loci were identified as GWA significant hits in AA patients (3 for PMP and 4 for individual metabolites), one of which was also significant in the entire cohort (rs944469). No genome wide significant hits were found in White/EA patients. Among these SNPs, only rs35792152, (a hit for 3.HBA) tended to be associated with mortality in standard survival analysis (HR = 1.436, p = 0.052). The mediation analyses indicated several significant associations between SNPs, metabolites, and mortality in AA patients. Functional annotation mapping (FUMA) implicated inflammation, DNA metabolic, and mRNA splicing processes. Conclusions: GWAS of key metabolites and survival along with FUMA pathway analysis revealed new candidate genes which unveiled molecular pathways that contribute to HF disease progression via metabolic and energetic abnormalities.

Clinical Pharmacogenetics Implementation Consortium Guideline (CPIC) for CYP2D6, ADRB1, ADRB2, ADRA2C, GRK4, and GRK5 Genotypes and Beta-Blocker Therapy.

Beta-blockers are widely used medications for a variety of indications, including heart failure, myocardial infarction, cardiac arrhythmias, and hypertension. Genetic variability in pharmacokinetic (e.g., CYP2D6) and pharmacodynamic (e.g., ADRB1, ADRB2, ADRA2C, GRK4, GRK5) genes have been studied in relation to beta-blocker exposure and response. We searched and summarized the strength of the evidence linking beta-blocker exposure and response with the six genes listed above. The level of evidence was high for associations between CYP2D6 genetic variation and both metoprolol exposure and heart rate response. Evidence indicates that CYP2D6 poor metabolizers experience clinically significant greater exposure and lower heart rate in response to metoprolol compared with those who are not poor metabolizers. Therefore, we provide therapeutic recommendations regarding genetically predicted CYP2D6 metabolizer status and metoprolol therapy. However, there was insufficient evidence to make therapeutic recommendations for CYP2D6 and other beta-blockers or for any beta-blocker and the other five genes evaluated (updates at www.cpicpgx.org).

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.