Clinical Application of a Novel Genetic Risk Score for Ischemic Stroke in Patients With Cardiometabolic Disease
Abstract
Background:
Genome-wide association studies have identified single-nucleotide polymorphisms that are associated with an increased risk of stroke. We sought to determine whether a genetic risk score (GRS) could identify subjects at higher risk for ischemic stroke after accounting for traditional clinical risk factors in 5 trials across the spectrum of cardiometabolic disease.
Methods:
Subjects who had consented for genetic testing and who were of European ancestry from the ENGAGE AF-TIMI 48 (Effective Anticoagulation with Factor Xa Next Generation in Atrial Fibrillation), SOLID-TIMI 52 (Stabilization of Plaques Using Darapladib), SAVOR-TIMI 53 (Saxagliptin Assessment of Vascular Outcomes Recorded in Patients with Diabetes Mellitus), PEGASUS-TIMI 54 (Prevention of Cardiovascular Events in Patients With Prior Heart Attack Using Ticagrelor Compared to Placebo on a Background of Aspirin), and FOURIER (Further Cardiovascular Outcomes Research With PCSK9 Inhibition in Patients With Elevated Risk) trials were included in this analysis. A set of 32 single-nucleotide polymorphisms associated with ischemic stroke was used to calculate a GRS in each patient and identify tertiles of genetic risk. A Cox model was used to calculate hazard ratios for ischemic stroke across genetic risk groups, adjusted for clinical risk factors.
Results:
In 51 288 subjects across the 5 trials, a total of 960 subjects had an ischemic stroke over a median follow-up period of 2.5 years. After adjusting for clinical risk factors, a higher GRS was strongly and independently associated with increased risk for ischemic stroke (P trend=0.009). In comparison with individuals in the lowest third of the GRS, individuals in the middle and top tertiles of the GRS had adjusted hazard ratios of 1.15 (95% CI, 0.98–1.36) and 1.24 (95% CI 1.05–1.45) for ischemic stroke, respectively. Stratification into subgroups revealed that the performance of the GRS appeared stronger in the primary prevention cohort with an adjusted hazard ratio for the top versus lowest tertile of 1.27 (95% CI, 1.04–1.53), in comparison with an adjusted hazard ratio of 1.06 (95% CI, 0.81–1.41) in subjects with previous stroke. In an exploratory analysis of patients with atrial fibrillation and CHA2DS2-VASc score of 2, high genetic risk conferred a 4-fold higher risk of stroke and an absolute risk equivalent to those with CHA2DS2-VASc score of 3.
Conclusions:
Across a broad spectrum of subjects with cardiometabolic disease, a 32–single-nucleotide polymorphism GRS was a strong, independent predictor of ischemic stroke. In patients with atrial fibrillation but lower CHA2DS2-VASc scores, the GRS identified patients with risk comparable to those with higher CHA2DS2-VASc scores.
Clinical Perspective
What Is New?
•
This is the first study to show that a genetic risk score remains an independent predictor of ischemic stroke in subjects who are older and have established cardiometabolic disease.
•
The genetic risk score demonstrated stronger risk prediction in subjects without previous stroke and in those with a lower burden of clinical risk factors.
What Are the Clinical Implications?
•
Genetics may help refine stroke prediction in patients at apparent low clinical risk.
•
Further studies should focus on whether patients with atrial fibrillation and CHA2DS2-VASc scores of 0 to 1 but high genetic risk would benefit from anticoagulation therapy.
Introduction
Ischemic stroke, a sudden neurological deficit caused by an interruption of cerebral blood flow, remains a leading cause of morbidity and mortality worldwide.1 Although several traditional risk factors such as hypertension, diabetes, and heart failure exhibit strong associations with ischemic stroke, a substantial proportion of ischemic stroke risk remains unexplained.2–4 Multiple lines of evidence suggest that heritable factors may contribute to the development of ischemic stroke,5,6 with some reports estimating that 30% to 40% of variability in ischemic stroke risk can be explained by genetic variation.7 Over the past decade, advances in molecular genetics have better defined the genetic architecture underlying risk for ischemic stroke, bringing further attention to this underappreciated component of stroke susceptibility.8
Genetic risk scores represent a method of summating an individual’s genetic propensity for a given phenotype and have garnered interest for their potential to improve risk prediction in many common diseases.9–11 Despite promise in other conditions, early attempts at using a genetic risk score (GRS) for ischemic stroke showed limited predictive ability,12–14 possibly because of the fewer number of stroke susceptibility loci identified and the biological heterogeneity of ischemic stroke. In the wake of the MEGASTROKE meta-analysis of genome-wide association studies,15 multiple groups have developed genetic risk scores with increased predictive power.16,17 Whether a GRS can predict ischemic stroke risk across a diverse group of patients with cardiovascular disease, after fully adjusting for clinical risk factors including atrial fibrillation, is still not known.
We sought to determine whether a GRS could identify subjects at higher risk for ischemic stroke after accounting for traditional clinical risk factors in 5 trials across the spectrum of cardiometabolic disease. We quantified the level of risk conferred by each genetic risk tertile, compared the magnitude of risk provided by high genetic risk with that provided by well-established clinical risk factors, and investigated GRS performance across key subgroups. Last, we explored whether genetic risk classification could refine stroke risk prediction in patients with atrial fibrillation, with specific attention to those with lower CHA2DS2-VASc scores in whom high genetic risk might inform the decision about initiating anticoagulation.
Methods
Study Design and Population
We performed a genetic cohort analysis pooling individual patient-level data from 5 cardiovascular clinical trials: ENGAGE AF-TIMI 48 (Effective Anticoagulation with Factor Xa Next Generation in Atrial Fibrillation),18 SOLID-TIMI 52 (Stabilization of Plaques Using Darapladib),19 SAVOR-TIMI 53 (Saxagliptin Assessment of Vascular Outcomes Recorded in Patients with Diabetes Mellitus),20 PEGASUS-TIMI 54 (Prevention of Cardiovascular Events in Patients With Prior Heart Attack Using Ticagrelor Compared to Placebo on a Background of Aspirin),21 and FOURIER (Further Cardiovascular Outcomes Research With PCSK9 Inhibition in Patients With Elevated Risk).22 The study population represents a broad spectrum of cardiovascular disease including established atherosclerosis, previous myocardial infarction, diabetes, and atrial fibrillation. Brief descriptions of each trial are listed in the Appendix in the Data Supplement. Patients who consented for genetic analysis, passed quality control, and were of European ancestry were included. Baseline characteristics for each trial are listed in Table I in the Data Supplement.
Study protocols were approved by the institutional review board or ethics committee at each participating site. All subjects provided written informed consent. We encourage parties interested in collaboration and data sharing to contact the corresponding author directly for further discussions.
Genotyping and Imputation
Methods for genotyping and imputation have previously been published.11 Genotyping was performed using the Illumina Multi-Ethnic Genotyping Array (ENGAGE AF-TIMI 48, SAVOR-TIMI 53, and PEGASUS-TIMI 54), Affymetrix Biobank Array (SOLID-TIMI 52), and Infinium Global Array (FOURIER). Preimputation quality control was performed using PLINK v2.0,23 followed by imputation using the Michigan Imputation server24 and TOPMed Freeze5 reference panel.25 Postimputation quality control was performed, followed by identification of patients with European ancestry using the 1000 Genomes phase 3 v5 reference panel26 and ADMIXTURE tool.27
Genetic Risk Score
The GRS for ischemic stroke was based on all 32 genome-wide associated single-nucleotide polymorphisms (SNPs) from MEGASTROKE,15 listed in Table II in the Data Supplement. In cases where the risk variant was not available, proxy SNPs were used to complete the set of 32 SNPs.28,29 With the use of PLINK v2.0, the GRS was calculated for each patient by multiplying the imputed allelic dosage with the variant-specific weight (β-coefficient for the association between the SNP and ischemic stroke) based on MEGASTROKE,15 and then summing across all variants. Patients were assigned into low, intermediate, and high genetic risk for ischemic stroke based on tertiles.
Clinical End Point and Follow-Up
The end point of interest was ischemic stroke. In each trial, ischemic stroke was formally adjudicated by an independent clinical end point committee blinded to treatment assignment. The median follow-up across trials ranged from 2.2 to 2.9 years.
Statistical Analysis
Individual patient-level data were pooled from the 5 clinical trials. Analyses were performed in the overall genetic cohort, primary versus secondary prevention cohorts, clinical subgroups of interest, the ENGAGE AF-TIMI 48 trial (all with atrial fibrillation), and across a range of CHADSVASc scores in those with and without atrial fibrillation.30 Time-to-event data were used to create Kaplan-Meier curves. Cox proportional hazard models were used to calculate hazard ratios (HRs) for ischemic stroke across genetic risk categories. Schoenfeld residuals were used to test proportional hazards assumptions that were met. Analyses were adjusted for age, sex, genetic ancestry (by principal components 1–5), and clinical comorbidities including hypertension, hyperlipidemia, diabetes, smoking, vascular disease, congestive heart failure, and atrial fibrillation. A trend test was used to assess the difference in ischemic stroke across genetic risk categories. With the use of the components of the Revised Framingham Stroke Risk Score31 and geographic region (given the global nature of these trials) for the base model in the overall cohort, the Harrell C-index was used to determine whether the addition of genetics (genetic risk score and genetic ancestry) improved discrimination between patients who experienced stroke and those who did not. The C-index was also assessed in patients with a CHA2DS2-VASc score of 2, along with the ability of the GRS to reclassify risk using the net reclassification improvement at event rate.32 The 95% confidence interval for net reclassification improvement was calculated by a resampling method. All P values were 2-sided and assessed at a threshold of 0.05.
Results
Study Cohort
Across the 5 trials studied, 51 288 subjects were eligible to be included in this analysis. The average age of the study population was 65.9 years, and 28.3% were female. Most subjects (81.7%) had coronary or peripheral artery disease. Many had traditional clinical risk factors for stroke, including hypertension (82.3%), hyperlipidemia (60.2%), and diabetes (41.9%). A smaller percentage of the cohort had previous transient ischemic attack or stroke (14.0%), were current smokers (18.2%), had atrial fibrillation (28.4%), or had a history of congestive heart failure (29.1%). A total of 960 subjects had an ischemic stroke over a median follow-up of 2.5 years.
Identification of Genetic Risk Groups
Baseline characteristics by genetic risk tertile are shown in the Table. Subjects in the highest tertile of the GRS were more likely to be female, have had a previous stroke, and have comorbidities associated with stroke including hypertension, atrial fibrillation, and congestive heart failure. The relative contribution of each trial to each tertile of genetic risk is listed in Table I in the Data Supplement.
| Characteristics | Low genetic risk | Intermediate genetic risk | High genetic risk | P value |
|---|---|---|---|---|
| Participants | 17 096 | 17 096 | 17 096 | |
| Demographics | ||||
| Age, y | 66.1 (9.2) | 65.9 (9.3) | 65.6 (9.2) | <0.001 |
| 65–74 y | 6521 (38) | 6281 (37) | 6272 (37) | 0.007 |
| ≥75 y | 3306 (19) | 3306 (19) | 3116 (18) | 0.01 |
| Female sex | 4808 (28) | 4722 (28) | 4989 (29) | 0.005 |
| Medical history | ||||
| Hypertension | 13 749 (80) | 14 110 (83) | 14 350 (84) | <0.001 |
| Hyperlipidemia | 10 379 (61) | 10 293 (60) | 10 181 (60) | 0.09 |
| Diabetes | 7367 (43) | 6989 (41) | 7118 (42) | <0.001 |
| Smoking | 3062 (18) | 3118 (18) | 3169 (19) | 0.33 |
| Atrial fibrillation | 4300 (25) | 4721 (28) | 5536 (32) | <0.001 |
| Vascular disease | 14 107 (83) | 14 056 (82) | 13 716 (80) | <0.001 |
| Congestive heart failure | 4494 (26) | 4867 (29) | 5552 (33) | <0.001 |
| Stroke/transient ischemic attack | 2106 (12) | 2453 (14) | 2634 (15) | <0.001 |
Values indicate n (%) or average (standard deviation). P values represent χ2 test for categorical variables and 1-way ANOVA for continuous variables.
Genetic Risk Predicts Ischemic Stroke
The Kaplan-Meier event rates for ischemic stroke at 3 years in the low, intermediate, and high GRS groups were 1.95% (n=272), 2.24% (n=322), and 2.56% (n=366), respectively (Figure 1). After adjusting for clinical risk factors, a higher GRS remained strongly associated with increased risk for ischemic stroke (P trend=0.009). In comparison with patients in the lowest GRS tertile, those in the middle tertile had an adjusted HR of 1.15 (95% CI, 0.98–1.36) for ischemic stroke and those in the top tertile had an adjusted HR of 1.24 (95% CI, 1.05–1.45). The magnitude of risk conferred by a high GRS was comparable to the individual risk provided from smoking, diabetes, or hypertension (Figure I in the Data Supplement). Addition of the GRS to a Cox model of clinical variables from the Revised Framingham Stroke Risk Score plus geographic region did not significantly increase the C-index (0.64 [0.62–0.66] versus 0.65 [0.63–0.66]).
Among subgroups, the performance of the GRS was stronger in the 44 095 subjects without previous stroke (adjusted HR of top tertile versus lowest tertile, 1.27 [95% CI, 1.04–1.53]; Figure 2), with no clear predictive utility in the 7193 subjects with previous stroke (adjusted HR, 1.06 [95% CI, 0.81–1.41]). In addition, risk prediction with the GRS was better in subjects without diabetes (Pinteraction=0.002) or congestive heart failure (Pinteraction=0.04) in comparison with subjects with those conditions (Figure II in the Data Supplement). The GRS demonstrated similar predictive power across subgroups of sex and age, and in those with and without vascular disease and atrial fibrillation.
Exploratory Analysis in ENGAGE AF-TIMI 48
A total of 11 187 patients from the overall cohort were enrolled in ENGAGE AF-TIMI 48, a trial of patients with atrial fibrillation and a CHADS2 score of 2 or higher who were treated with anticoagulation. Of these, 395 (3.5%) had an ischemic stroke over a median follow-up of 2.8 years. Even after adjusting for components of the CHA2DS2-VASc score, patients with a high GRS were at 29% greater risk of ischemic stroke (adjusted HR, 1.29 [95% CI, 1.01–1.64]; P=0.045) than those with a low GRS (Figure III in the Data Supplement). The magnitude of risk was beyond that of multiple components of the CHA2DS2-VASc score such as vascular disease, congestive heart failure, diabetes, and hypertension.
Among this atrial fibrillation cohort, the predictive ability of the GRS was significantly stronger in patients with lower CHA2DS2-VASc scores (P trend=0.04), including a 4-fold increased risk in patients with a CHA2DS2-VASc score of 2 (HR, 3.97 [95% CI, 1.04–15.2]; Figure 3). More specifically, high genetic risk identified one-third of patients with a CHA2DS2-VASc score of 2 who had a risk of ischemic stroke equivalent to patients with a CHA2DS2-VASc score of 3. When the GRS was applied to patients with a CHA2DS2-VASc score of 2, the C-index went from 0.68 (0.58–0.77) to 0.84 (0.77–0.91), and the net reclassification improvement was 0.32 (0.04–0.69), with 33% of those without stroke correctly reclassified to a lower-risk group (Table III in the Data Supplement). A sensitivity analysis in patients without atrial fibrillation from the other 4 trials demonstrated a similar trend of greater prognostic value from the GRS in subjects with fewer risk factors (P trend=0.02; Figure IV in the Data Supplement).
When comparing the degree of risk stratification provided by CHA2DS2-VASc in patients with differing levels of genetic risk, there was a steeper gradient present in patients with lower genetic risk, ranging from a 0.6% rate of stroke in patients with a CHA2DS2-VASc score of 2 to a 5.5% rate of stroke in patients with a CHA2DS2-VASc score >5 (P trend<0.001). In patients with high genetic risk, a more modest increase in absolute stroke risk was observed, ranging from 2.8% in patients with a CHA2DS2-VASc score of 2 to 5.1% in those with scores >5 (P trend=0.01; Figure V in the Data Supplement).
Discussion
With 51 288 patients and 960 incident ischemic strokes, this study represents one of the largest prospective analyses of stroke genetics to date. Such data provide a unique opportunity to study the clinical value of an ischemic stroke GRS at scale and across a diverse patient population. In this study, we demonstrate that a 32-SNP GRS predicts ischemic stroke in patients with a wide range of cardiometabolic diseases, appears to have greater utility in those without previous stroke, and can potentially refine stroke risk in patients with atrial fibrillation and lower CHA2DS2-VASc scores, suggesting a potential role for genetic risk scores in therapeutic decision making.
In patients who are older and have cardiovascular risk factors, it is not clear whether a genetic predisposition still plays a role in ischemic stroke. However, we found that a GRS is a significant and independent predictor of ischemic stroke risk, even in patients with cardiometabolic disease and a median age of 66 years. More precisely, those in the top third of the GRS carried a 24% greater risk of ischemic stroke than those in the lowest third of the GRS. To put this degree of risk into perspective, high genetic risk was similar to the risk provided by several well-established clinical risk factors such as smoking, diabetes, and hypertension in this population. The performance of the GRS was even more robust when applied to patients without diabetes or heart failure and, more broadly, demonstrated stronger risk prediction in patients with a lower burden of clinical risk factors.
Beyond the independent and additive value of genetics in determining ischemic stroke risk, a second question of interest is whether genetics can also identify increased risk for recurrent ischemic stroke. Although only 14% of the overall cohort had previous stroke, this subgroup of subjects accounted for 31% of the ischemic strokes during the follow-up period. We found that the 32-SNP GRS was unable to predict recurrent stroke in this secondary prevention population. Conversely, the predictive value of genetic risk was far stronger in patients without previous stroke. These findings imply that the GRS used in this study may be most useful for stratifying risk for a first-ever stroke. Determining whether primary and secondary strokes have varying genetic drivers will require additional investigation.
Although identifying increased stroke risk from a GRS may be valuable, the low absolute event rates in the general cardiometabolic population limit the ability of the GRS to change clinical practice. However, application of the GRS in patients with atrial fibrillation could be considered to help determine who should receive anticoagulation. We tested whether genetics could enhance stroke risk stratification in an exploratory analysis of the ENGAGE AF-TIMI 48 trial and found that GRS performance was greatest when applied to patients with lower CHA2DS2-VASc scores. Specifically, in patients with a CHA2DS2-VASc score of 2, there was a 4-fold increased risk of stroke in those with high genetic risk. This translated to an absolute stroke risk equivalent to patients with a CHA2DS2-VASc score of 3, identifying a group of patients whose stroke risk is underappreciated.
Patients with a CHA2DS2-VASc score of 1 often present the greatest challenge clinically regarding anticoagulation management, and the addition of genetic risk could provide greater clarity in such situations. Although the ENGAGE AF-TIMI 48 trial had very few patients with low CHA2DS2-VASc scores, and all were on anticoagulation, our findings suggest that high genetic risk confers a multiple fold higher stroke risk that could help guide management. Further studies are needed to validate these findings and ultimately address whether such patients with low CHA2DS2-VASc scores, but high genetic risk would benefit from anticoagulation therapy.
Limitations
Our study has several limitations. First, we specifically studied subjects enrolled in 5 clinical trials across the spectrum of cardiometabolic disease and, therefore, our findings may not be fully applicable to a an unselected general population. In addition, our analysis was limited to subjects who were of European ancestry and had consented to genetic testing. Further data will be required before extrapolating genetic risk prediction to more diverse populations. Regarding our investigation in ENGAGE AF-TIMI 48, the proportion of patients in the trial with lower CHA2DS2-VASc scores was limited. Therefore, the confidence intervals for the magnitude of increased risk in those with a high GRS were wide, and thus our results in this population should be viewed as exploratory. Future research efforts should focus on genotyping other large cohorts of subjects with atrial fibrillation to validate these findings in this subgroup of interest. Last, our study does not explore the biological heterogeneity of stroke and the relative contributions of large-artery atherosclerotic stroke, cardioembolic stroke, and small-vessel stroke to the ischemic stroke phenotype. Although it is likely that each of these stroke subtypes contributed to the overall rates of ischemic stroke found in our study, attempts at genetic risk prediction across subtypes would require deeper stroke phenotyping and would likely be underpowered because of the small number of genetic loci that are known to be associated with each stroke subtype. As such, in this study, we elected to apply a GRS comprising the 32 SNPs that had achieved genome-wide significance for stroke or any ischemic stroke subtype to predict all ischemic stroke. Many of these SNPs are closely associated with blood pressure, hyperlipidemia, coronary artery disease, atrial fibrillation, and venous thromboembolism, suggesting that the GRS used in this study incorporates these various biological mechanisms. We anticipate that further advances in stroke genetics will reveal additional loci that can refine efforts toward genetic risk prediction of stroke subtypes in the future.
Conclusion
Across 5 large clinical trials of subjects with cardiometabolic disease, a 32-SNP GRS was a strong, independent predictor of ischemic stroke. The predictive value of the GRS appeared strongest in subjects without previous stroke and in subjects with fewer clinical risk factors. Moreover, in patients with atrial fibrillation but lower CHA2DS2-VASc scores, the GRS identified patients with risk comparable to those with higher CHA2DS2-VASc scores.
Acknowledgments
Drs Marston and Patel contributed to study design, literature search, statistical analysis, data interpretation, figures, and drafting of the manuscript. Drs Kamanu, Nordio, and Melloni, C. Roselli, and Drs Gurmu and Weng contributed to data preparation, study design, and statistical analysis. Drs Bonaca, Giugliano, Scirica, O’Donoghue, Cannon, Anderson, Bhatt, Steg, Cohen, Storey, Sever, Keech, Raz, Mosenzon, Antman, and Braunwald contributed to data interpretation and critical review of the manuscript. Drs Ellinor, Lubitz, Sabatine, and Ruff contributed to study design, statistical analysis, data interpretation, figures, and critical review of the manuscript. Drs Sabatine and Ruff are the guarantors of this work and, as such, had full access to all the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.
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© 2020 American Heart Association, Inc.
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History
Received: 3 October 2020
Accepted: 11 November 2020
Published online: 13 November 2020
Published in print: 2 February 2021
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Disclosures
Dr Marston reports grant support from the National Institutes of Health and involvement in clinical trials with Amgen, Pfizer, Novartis, and AstraZeneca without personal fees, payments, or increase in salary. Dr Nordio is now employed by Takeda Pharmaceuticals. C. Roselli is supported by a grant from Bayer AG to the Broad Institute focused on the development of therapeutics for cardiovascular disease. Dr Gurmu is now employed at the Food and Drug Administration. Dr Weng reports support from the American Heart Association (18SFRN34110082). Dr Bonaca discloses grant support from Amgen, AstraZeneca, Bayer, Sanofi and consulting fees from Amgen, AstraZeneca, Bayer, Sanofi. Dr Giugliano reports grants from Amgen and Daiichi Sankyo, during the conduct of the study; personal fees from Akcea, American College of Cardiology, Bristol Myers Squibb, CVS Caremark, GlaxoSmithKline, Janssen, Lexicon Merck, Pfizer, and Servier; grants and personal fees from Amarin, Amgen, and Daiichi Sankyo outside the submitted work; and an institutional research grant to the TIMI Study Group at Brigham and Women’s Hospital for research he is not directly involved in from Abbott, Amgen, Aralez, AstraZeneca, Bayer HealthCare Pharmaceuticals, Inc, BRAHMS, Daiichi Sankyo, Eisai, GlaxoSmithKline, Intarcia, Janssen, MedImmune, Merck, Novartis, Pfizer, Poxel, Quark Pharmaceuticals, Roche, Takeda, The Medicines Company, and Zora Biosciences. Dr Scirica reports research grants from AstraZeneca, Eisai, Novartis, and Merck and consulting fees from AstraZeneca, Biogen Idec, Boehringer Ingelheim, Covance, Dr Reddy’s Laboratories, Eisai, Elsevier Practice Update Cardiology, GlaxoSmithKline, Lexicon, Merck, Novo Nordisk, Sanofi, and St Jude’s Medical; and has equity in Health [at] Scale. Dr O’Donoghue reports institutional research grants from Amgen, Janssen, The Medicines Company, Eisai, GlaxoSmithKline, and Astra Zeneca. Dr Cannon reports research grants from Amgen, Boehringer-Ingelheim (BI), Bristol-Myers Squibb (BMS), Daiichi Sankyo, Janssen, Merck, Novo Nordisk, and Pfizer; consulting fees from Aegerion, Alnylam, Amarin, Amgen, Applied Therapeutics, Ascendia, BI, BMS, Corvidia, Eli Lilly, HLS Therapeutics, Innovent, Janssen, Kowa, Merck, Pfizer, Rhoshan, and Sanofi. Dr Anderson reports grants from the National Institutes of Health (R01NS103924, R01NS069763), the American Heart Association (18SFRN34250007), and Massachusetts General Hospital, sponsored research support from Bayer AG, and consulting fees for ApoPharma, Inc. Dr Bhatt discloses the following relationships: Advisory Board: Cardax, CellProthera, Cereno Scientific, Elsevier Practice Update Cardiology, Level Ex, Medscape Cardiology, MyoKardia, PhaseBio, PLx Pharma, Regado Biosciences; Board of Directors: Boston VA Research Institute, Society of Cardiovascular Patient Care, TobeSoft; Chair: American Heart Association Quality Oversight Committee; Data Monitoring Committees: Baim Institute for Clinical Research (formerly Harvard Clinical Research Institute, for the PORTICO trial (Portico Re-sheathable Transcatheter Aortic Valve System US IDE Trial), funded by St. Jude Medical, now Abbott), Cleveland Clinic (including for the ExCEED trial (Efficacy of Secukinumab Compared to Adalimumab in Patients With Psoriatic Arthritis), funded by Edwards), Contego Medical (Chair, PERFORMANCE 2 [Protection Against Emboli During Carotid Artery Stenting Using the Neuroguard IEP System]), Duke Clinical Research Institute, Mayo Clinic, Mount Sinai School of Medicine (for the ENVISAGE trial [Edoxaban Compared to Standard Care After Heart Valve Replacement Using a Catheter in Patients With Atrial Fibrillation], funded by Daiichi Sankyo), Population Health Research Institute; Honoraria: American College of Cardiology (Senior Associate Editor, Clinical Trials and News, ACC.org; Vice-Chair, ACC Accreditation Committee), Baim Institute for Clinical Research (formerly Harvard Clinical Research Institute; RE-DUAL PCI clinical trial (Evaluation of Dual Therapy With Dabigatran vs. Triple Therapy With Warfarin in Patients With AF That Undergo a PCI With Stenting) steering committee funded by Boehringer Ingelheim; AEGIS-II (Study to Investigate CSL112 in Subjects With Acute Coronary Syndrome) executive committee funded by CSL Behring), Belvoir Publications (Editor in Chief, Harvard Heart Letter), Canadian Medical and Surgical Knowledge Translation Research Group (clinical trial steering committees), Duke Clinical Research Institute (clinical trial steering committees, including for the PRONOUNCE trial (A Trial Comparing Cardiovascular Safety of Degarelix Versus Leuprolide in Patients With Advanced Prostate Cancer and Cardiovascular Disease), funded by Ferring Pharmaceuticals), HMP Global (Editor in Chief, Journal of Invasive Cardiology), Journal of the American College of Cardiology (Guest Editor; Associate Editor), K2P (Co-Chair, interdisciplinary curriculum), Level Ex, Medtelligence/ReachMD (CME steering committees), MJH Life Sciences, Population Health Research Institute (for the COMPASS [Rivaroxaban for the Prevention of Major Cardiovascular Events in Coronary or Peripheral Artery Disease] operations committee, publications committee, steering committee, and US national coleader, funded by Bayer), Slack Publications (Chief Medical Editor, Cardiology Today’s Intervention), Society of Cardiovascular Patient Care (Secretary/Treasurer), WebMD (CME steering committees); Other: Clinical Cardiology (Deputy Editor), National Cardiovascular Data Registry (NCDR)-ACTION Registry Steering Committee (Chair), VA CART Research and Publications Committee (Chair); Research Funding: Abbott, Afimmune, Amarin, Amgen, AstraZeneca, Bayer, Boehringer Ingelheim, Bristol-Myers Squibb, Cardax, Chiesi, CSL Behring, Eisai, Ethicon, Ferring Pharmaceuticals, Forest Laboratories, Fractyl, Idorsia, Ironwood, Ischemix, Lexicon, Lilly, Medtronic, MyoKardia, Pfizer, PhaseBio, PLx Pharma, Regeneron, Roche, Sanofi Aventis, Synaptic, The Medicines Company; Royalties: Elsevier (Editor, Cardiovascular Intervention: A Companion to Braunwald’s Heart Disease); Site Co-Investigator: Biotronik, Boston Scientific, CSI, St. Jude Medical (now Abbott), Svelte; Trustee: American College of Cardiology; Unfunded Research: FlowCo, Merck, Novo Nordisk, Takeda. Dr Steg reports research grants from Amarin, Bayer, Sanofi, and Servier; speaking or consulting fees from Amarin, Amgen, AstraZeneca, Bayer/Janssen, Boehringer-Ingelheim, Bristol-Myers-Squibb, Idorsia, Novartis, Novo-Nordisk, Pfizer, Regeneron, Sanofi, and Servier. Dr Cohen discloses honoraria for Speakers Bureau and advisory Boards (moderate) from AstraZeneca. Dr Storey reports research grants, consultancy fees, and honoraria from AstraZeneca; consulting fees and honoraria from Bayer and Bristol Myers Squibb/Pfizer; research grants and consultancy fees from Cytosorbents, GlyCardial Diagnostics, and Thromboserin; consultancy fees from Amgen, Haemonetics, Hengrui, Idorsia, PhaseBio, Portola and Sanofi Aventis; honoraria from Intas Pharmaceuticals and Medscape. Dr Sever reports research grants and honoraria for speakers’ bureau Amgen and Pfizer. Dr Keech reports grants and personal fees from Abbott and Mylan; personal fees from Amgen, AstraZeneca, Pfizer, and Bayer; grants from Sanofi and Novartis, outside the submitted work. Dr Raz received personal fees from AstraZeneca, Bristol Myers Squibb, Boehringer Ingelheim, Concenter BioPharma and Silkim, Eli Lilly, Merck Sharp & Dohme, Novo Nordisk, Orgenesis, Pfizer, Sanofi, SmartZyme Innovation, Panaxia, FutuRx, Insuline Medical, Medial EarlySign, CameraEyes, Exscopia, Dermal Biomics, Johnson & Johnson, Novartis, Teva, GlucoMe, and DarioHealth. Dr Mosenzon reports serving on Advisory Boards for Novo Nordisk, Eli Lilly, Sanofi, Merck Sharp & Dohme, Boehringer Ingelheim, Novartis, AstraZeneca, BOL Pharma; Research grant support through Hadassah Hebrew University Hospital: Novo Nordisk, AstraZeneca and Bristol-Myers Squibb; Speaker’s Bureau: AstraZeneca and Bristol-Myers Squibb, Novo Nordisk, Eli Lilly, Sanofi, Novartis, Merck Sharp & Dohme, Boehringer Ingelheim. Dr Antman reports receiving grant support through his institution from Daiichi Sankyo. Dr Braunwald reports research grants through the Brigham and Women’s Hospital from Astra Zeneca, Daiichi Sankyo, Merck, and Novartis. Consultancies with Amgen, Cardurion, MyoKardia, NovoNordisk, Boehringer-Ingelheim/Lilly, IMMEDIATE, and Verve. Uncompensated consultancies and lectures with The Medicines Company. Dr Ellinor reports grants and personal fees from Bayer AG, personal fees from Novartis and Quest Diagnostics, outside the submitted work. Dr Lubitz is supported by National Institutes of Health grant 1R01HL139731 and American Heart Association 18SFRN34250007. He receives sponsored research support from Bristol Myers Squibb/Pfizer, Bayer AG, Boehringer Ingelheim, Fitbit, and IBM, and has consulted for Bristol Myers Squibb/Pfizer and Bayer AG. Dr Sabatine reports research grant support through Brigham and Women’s Hospital from Amgen, AstraZeneca, Bayer, Daiichi-Sankyo, Eisai, GlaxoSmithKline, Intarcia, Janssen Research and Development, Medicines Company, MedImmune, Merck, Novartis, Pfizer, Poxel, Quark Pharmaceuticals, Takeda; Consulting for Amgen, Anthos Therapeutics, AstraZeneca, Bristol-Myers Squibb, CVS Caremark, DalCor, Dyrnamix, Esperion, IFM Therapeutics, Intarcia, Ionis, Janssen Research and Development, Medicines Company, MedImmune, Merck, Novartis; Dr Sabatine is a member of the TIMI Study Group, which has also received institutional research grant support through Brigham and Women’s Hospital from: Abbott, Aralez, Roche, and Zora Biosciences. Dr Ruff reports grants from Boehringer Ingelheim, Daiichi Sankyo, MedImmune, National Institute of Health; personal fees from Bayer, Bristol Myers Squibb, Boehringer Ingelheim, Daiichi Sankyo, Janssen, MedImmune, Pfizer, Portola, Anthos, outside the submitted work; Dr Ruff is a member of the TIMI Study Group, which has received institutional research grant support through Brigham and Women’s Hospital from: Abbott, Amgen, Aralez, AstraZeneca, Bayer HealthCare Pharmaceuticals, Inc, BRAHMS, Daiichi-Sankyo, Eisai, GlaxoSmithKline, Intarcia, Janssen, MedImmune, Merck, Novartis, Pfizer, Poxel, Quark Pharmaceuticals, Roche, Takeda, The Medicines Company, and Zora Biosciences. The other authors report no disclosures.
Sources of Funding
The trials were funded by Amgen, AstraZeneca, Daiichi Sankyo, and GlaxoSmithKline.
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