Common- and rare-variant genetic architecture of heart failure across the allele frequency spectrum.

Heart failure (HF) is a complex trait, influenced by environmental and genetic factors, that affects over 30 million individuals worldwide. Historically, the genetics of HF have been studied in Mendelian forms of disease, where rare genetic variants have been linked to familial cardiomyopathies. More recently, genome-wide association studies (GWAS) have successfully identified common genetic variants associated with risk of HF. However, the relative importance of genetic variants across the allele-frequency spectrum remains incompletely characterized. Here, we report the results of common- and rare-variant association studies of all-cause heart failure, applying recently developed methods to quantify the heritability of HF attributable to different classes of genetic variation. We combine GWAS data across multiple populations including 207,346 individuals with HF and 2,151,210 without, identifying 176 risk loci at genome-wide significance (p < 5×10-8). Signals at newly identified common-variant loci include coding variants in Mendelian cardiomyopathy genes (MYBPC3, BAG3), as well as regulators of lipoprotein (LPL) and glucose metabolism (GIPR, GLP1R), and are enriched in cardiac, muscle, nerve, and vascular tissues, as well as myocyte and adipocyte cell types. Gene burden studies across three biobanks (PMBB, UKB, AOU) including 27,208 individuals with HF and 349,126 without uncover exome-wide significant (p < 3.15×10-6) associations for HF and rare predicted loss-of-function (pLoF) variants in TTN, MYBPC3, FLNC, and BAG3. Total burden heritability of rare coding variants (2.2%, 95% CI 0.99-3.5%) is highly concentrated in a small set of Mendelian cardiomyopathy genes, and is lower than heritability attributable to common variants (4.3%, 95% CI 3.9-4.7%) which is more diffusely spread throughout the genome. Finally, we demonstrate that common-variant background, in the form of a polygenic risk score (PRS), significantly modifies the risk of HF among carriers of pathogenic truncating variants in the Mendelian cardiomyopathy gene TTN. These findings suggest a significant polygenic component to HF exists that is not captured by current clinical genetic testing.

A multi-ancestry polygenic risk score improves risk prediction for coronary artery disease.

Identification of individuals at highest risk of coronary artery disease (CAD)-ideally before onset-remains an important public health need. Prior studies have developed genome-wide polygenic scores to enable risk stratification, reflecting the substantial inherited component to CAD risk. Here we develop a new and significantly improved polygenic score for CAD, termed GPSMult, that incorporates genome-wide association data across five ancestries for CAD (>269,000 cases and >1,178,000 controls) and ten CAD risk factors. GPSMult strongly associated with prevalent CAD (odds ratio per standard deviation 2.14, 95% confidence interval 2.10-2.19, P < 0.001) in UK Biobank participants of European ancestry, identifying 20.0% of the population with 3-fold increased risk and conversely 13.9% with 3-fold decreased risk as compared with those in the middle quintile. GPSMult was also associated with incident CAD events (hazard ratio per standard deviation 1.73, 95% confidence interval 1.70-1.76, P < 0.001), identifying 3% of healthy individuals with risk of future CAD events equivalent to those with existing disease and significantly improving risk discrimination and reclassification. Across multiethnic, external validation datasets inclusive of 33,096, 124,467, 16,433 and 16,874 participants of African, European, Hispanic and South Asian ancestry, respectively, GPSMult demonstrated increased strength of associations across all ancestries and outperformed all available previously published CAD polygenic scores. These data contribute a new GPSMult for CAD to the field and provide a generalizable framework for how large-scale integration of genetic association data for CAD and related traits from diverse populations can meaningfully improve polygenic risk prediction.

Genome-wide association study of thoracic aortic aneurysm and dissection in the Million Veteran Program.

The current understanding of the genetic determinants of thoracic aortic aneurysms and dissections (TAAD) has largely been informed through studies of rare, Mendelian forms of disease. Here, we conducted a genome-wide association study (GWAS) of TAAD, testing ~25 million DNA sequence variants in 8,626 participants with and 453,043 participants without TAAD in the Million Veteran Program, with replication in an independent sample of 4,459 individuals with and 512,463 without TAAD from six cohorts. We identified 21 TAAD risk loci, 17 of which have not been previously reported. We leverage multiple downstream analytic methods to identify causal TAAD risk genes and cell types and provide human genetic evidence that TAAD is a non-atherosclerotic aortic disorder distinct from other forms of vascular disease. Our results demonstrate that the genetic architecture of TAAD mirrors that of other complex traits and that it is not solely inherited through protein-altering variants of large effect size.

Genome-wide association meta-analysis of spontaneous coronary artery dissection identifies risk variants and genes related to artery integrity and tissue-mediated coagulation.

Spontaneous coronary artery dissection (SCAD) is an understudied cause of myocardial infarction primarily affecting women. It is not known to what extent SCAD is genetically distinct from other cardiovascular diseases, including atherosclerotic coronary artery disease (CAD). Here we present a genome-wide association meta-analysis (1,917 cases and 9,292 controls) identifying 16 risk loci for SCAD. Integrative functional annotations prioritized genes that are likely to be regulated in vascular smooth muscle cells and artery fibroblasts and implicated in extracellular matrix biology. One locus containing the tissue factor gene F3, which is involved in blood coagulation cascade initiation, appears to be specific for SCAD risk. Several associated variants have diametrically opposite associations with CAD, suggesting that shared biological processes contribute to both diseases, but through different mechanisms. We also infer a causal role for high blood pressure in SCAD. Our findings provide novel pathophysiological insights involving arterial integrity and tissue-mediated coagulation in SCAD and set the stage for future specific therapeutics and preventions.

Clinical and genetic associations of deep learning-derived cardiac magnetic resonance-based left ventricular mass.

Left ventricular mass is a risk marker for cardiovascular events, and may indicate an underlying cardiomyopathy. Cardiac magnetic resonance is the gold-standard for left ventricular mass estimation, but is challenging to obtain at scale. Here, we use deep learning to enable genome-wide association study of cardiac magnetic resonance-derived left ventricular mass indexed to body surface area within 43,230 UK Biobank participants. We identify 12 genome-wide associations (1 known at TTN and 11 novel for left ventricular mass), implicating genes previously associated with cardiac contractility and cardiomyopathy. Cardiac magnetic resonance-derived indexed left ventricular mass is associated with incident dilated and hypertrophic cardiomyopathies, and implantable cardioverter-defibrillator implant. An indexed left ventricular mass polygenic risk score ≥90th percentile is also associated with incident implantable cardioverter-defibrillator implant in separate UK Biobank (hazard ratio 1.22, 95% CI 1.05-1.44) and Mass General Brigham (hazard ratio 1.75, 95% CI 1.12-2.74) samples. Here, we perform a genome-wide association study of cardiac magnetic resonance-derived indexed left ventricular mass to identify 11 novel variants and demonstrate that cardiac magnetic resonance-derived and genetically predicted indexed left ventricular mass are associated with incident cardiomyopathy.

Predictive Utility of a Coronary Artery Disease Polygenic Risk Score in Primary Prevention.

Importance: The clinical utility of polygenic risk scores (PRS) for coronary artery disease (CAD) has not yet been established. Objective: To investigate the ability of a CAD PRS to potentially guide statin initiation in primary prevention after accounting for age and clinical risk. Design, Setting, and Participants: This was a longitudinal cohort study with enrollment starting on January 1, 2006, and ending on December 31, 2010, with data updated to mid-2021, using data from the UK Biobank, a long-term population study of UK citizens. A replication analysis was performed in Biobank Japan. The analysis included all patients without a history of CAD and who were not taking lipid-lowering therapy. Data were analyzed from January 1 to June 30, 2022. Exposures: Polygenic risk for CAD was defined as low (bottom 20%), intermediate, and high (top 20%) using a CAD PRS including 241 genome-wide significant single-nucleotide variations (SNVs). The pooled cohort equations were used to estimate 10-year atherosclerotic cardiovascular disease (ASCVD) risk and classify individuals as low (<5%), borderline (5-<7.5%), intermediate (7.5-<20%), or high risk (≥20%). Main Outcomes and Measures: Myocardial infarction (MI) and ASCVD events (defined as incident clinical CAD [including MI], stroke, or CV death). Results: A total of 330 201 patients (median [IQR] age, 57 [40-74] years; 189 107 female individuals [57%]) were included from the UK Biobank. Over the 10-year follow-up, 4454 individuals had an MI. The CAD PRS was significantly associated with the risk of MI in all age groups but had significantly stronger risk prediction at younger ages (age <50 years: hazard ratio [HR] per 1 SD of PRS, 1.72; 95% CI, 1.56-1.89; age 50-60 years: HR, 1.46; 95% CI, 1.38-1.53; age >60 years: HR, 1.42; 95% CI, 1.37-1.48; P for interaction <.001). In patients younger than 50 years, those with high PRS had a 3- to 4-fold increased associated risk of MI compared with those in the low PRS category. A significant interaction between CAD PRS and age was replicated in Biobank Japan. When CAD PRS testing was added to the clinical ASCVD risk score in individuals younger than 50 years, 591 of 4373 patients (20%) with borderline risk were risk stratified into intermediate risk, warranting initiation of statin therapy and 3198 of 7477 patients (20%) with both borderline or intermediate risk were stratified as low risk, thus not warranting therapy. Conclusions and Relevance: Results of this cohort study suggest that the predictive ability of a CAD PRS was greater in younger individuals and can be used to better identify patients with borderline and intermediate clinical risk who should initiate statin therapy.

Discovery and systematic characterization of risk variants and genes for coronary artery disease in over a million participants.

The discovery of genetic loci associated with complex diseases has outpaced the elucidation of mechanisms of disease pathogenesis. Here we conducted a genome-wide association study (GWAS) for coronary artery disease (CAD) comprising 181,522 cases among 1,165,690 participants of predominantly European ancestry. We detected 241 associations, including 30 new loci. Cross-ancestry meta-analysis with a Japanese GWAS yielded 38 additional new loci. We prioritized likely causal variants using functionally informed fine-mapping, yielding 42 associations with less than five variants in the 95% credible set. Similarity-based clustering suggested roles for early developmental processes, cell cycle signaling and vascular cell migration and proliferation in the pathogenesis of CAD. We prioritized 220 candidate causal genes, combining eight complementary approaches, including 123 supported by three or more approaches. Using CRISPR-Cas9, we experimentally validated the effect of an enhancer in MYO9B, which appears to mediate CAD risk by regulating vascular cell motility. Our analysis identifies and systematically characterizes >250 risk loci for CAD to inform experimental interrogation of putative causal mechanisms for CAD.

Genome-wide association and multi-trait analyses characterize the common genetic architecture of heart failure.

Heart failure is a leading cause of cardiovascular morbidity and mortality. However, the contribution of common genetic variation to heart failure risk has not been fully elucidated, particularly in comparison to other common cardiometabolic traits. We report a multi-ancestry genome-wide association study meta-analysis of all-cause heart failure including up to 115,150 cases and 1,550,331 controls of diverse genetic ancestry, identifying 47 risk loci. We also perform multivariate genome-wide association studies that integrate heart failure with related cardiac magnetic resonance imaging endophenotypes, identifying 61 risk loci. Gene-prioritization analyses including colocalization and transcriptome-wide association studies identify known and previously unreported candidate cardiomyopathy genes and cellular processes, which we validate in gene-expression profiling of failing and healthy human hearts. Colocalization, gene expression profiling, and Mendelian randomization provide convergent evidence for the roles of BCKDHA and circulating branch-chain amino acids in heart failure and cardiac structure. Finally, proteome-wide Mendelian randomization identifies 9 circulating proteins associated with heart failure or quantitative imaging traits. These analyses highlight similarities and differences among heart failure and associated cardiovascular imaging endophenotypes, implicate common genetic variation in the pathogenesis of heart failure, and identify circulating proteins that may represent cardiomyopathy treatment targets.

Rare and Common Genetic Variation Underlying the Risk of Hypertrophic Cardiomyopathy in a National Biobank.

Importance: Hypertrophic cardiomyopathy (HCM) is a leading cause of sudden cardiac death in young people. Although rare genetic variants are well-established contributors to HCM risk, common genetic variants have recently been implicated in disease pathogenesis. Objective: To assess the contributions of rare and common genetic variation to risk of HCM in the general population. Design, Setting, and Participants: This cohort study of the UK Biobank (data from 2006-2010) and the Mass General Brigham Biobank (2010-2019) assessed the relative and joint contributions of rare genetic variants and a common variant (polygenic) score to risk of HCM. Both rare and common variant predictors were then evaluated in the context of relevant clinical risk factors. Data analysis was conducted from May 2021 to February 2022. Exposures: Pathogenic rare variants, common-variant (polygenic) score, and clinical risk factors. Main Outcomes and Measures: Risk of HCM. Results: The primary study population comprised 184 511 individuals from the UK Biobank. Mean (SD) age was 56 (8) years, 83 690 (45%) of participants were men, and 204 (0.1%) participants had HCM. Of 51 genes included in clinical genetic testing panels for HCM, pathogenic or likely pathogenic variants in 14 core genes (designated by the American College of Medical Genetics and Genomics [ACMG]) were associated with 55-fold higher odds (95% CI, 35-83) of HCM, while those in the remaining 37 non-ACMG genes were not significantly associated with HCM (OR, 1.8; 95% CI, 0.6-4.0). ClinVar pathogenic or likely pathogenic mutations in MYBPC3 (OR, 72; 95% CI, 39-124) and MYH7 (OR, 61; 95% CI, 26-121) were strongly associated with HCM, as were loss-of-function variants in ALPK3 (OR, 13; 95% CI, 4.4-28). A polygenic score was strongly associated with HCM (OR per SD increase in score, 1.6; 95% CI, 1.4-1.8), with concordant results in the Mass General Brigham Biobank. Genetic factors enhanced clinical risk prediction for HCM: addition of rare variant carrier status and the polygenic score to clinical risk factors (obesity, hypertension, atrial fibrillation, and coronary artery disease) improved the area under the receiver operator characteristic curve from 0.71 (95% CI, 0.65-0.77) to 0.82 (95% CI, 0.77-0.87). Conclusions and Relevance: Both rare and common genetic variants contribute substantially to HCM susceptibility in the general population and improve HCM risk prediction beyond that achieved with clinical factors.

Association of Pathogenic DNA Variants Predisposing to Cardiomyopathy With Cardiovascular Disease Outcomes and All-Cause Mortality.

Importance: Pathogenic variants associated with inherited cardiomyopathy are recognized as important and clinically actionable when identified, leading some clinicians to recommend population-wide genomic screening. Objective: To determine the prevalence and clinical importance of pathogenic variants associated with inherited cardiomyopathy within the context of contemporary clinical care. Design, Setting, and Participants: This was a genetic association study of participants in Atherosclerosis in Risk Communities (ARIC), recruited from 1987 to 1989, with median follow-up of 27 years, and the UK Biobank, recruited from 2006 to 2010, with median follow-up of 10 years. ARIC participants were recruited from 4 sites across the US. UK Biobank participants were recruited from 22 sites across the UK. Participants in the US were of African and European ancestry; those in the UK were of African, East Asian, South Asian, and European ancestry. Statistical analyses were performed between August 1, 2021, and February 9, 2022. Exposures: Rare genetic variants predisposing to inherited cardiomyopathy. Main Outcomes and Measures: Pathogenicity of observed DNA sequence variants in sequenced exomes of 13 genes (ACTC1, FLNC, GLA, LMNA, MYBPC3, MYH7, MYL2, MYL3, PRKAG2, TNNI3, TNNT2, TPM1, and TTN) associated with inherited cardiomyopathies were classified by a blinded clinical geneticist per American College of Medical Genetics recommendations. Incidence of all-cause mortality, heart failure, and atrial fibrillation were determined. Cardiac magnetic resonance imaging, echocardiography, and electrocardiogram measures were assessed in a subset of participants. Results: A total of 9667 ARIC participants (mean [SD] age, 54.0 [5.7] years; 4232 women [43.8%]; 2658 African [27.5%] and 7009 European [72.5%] ancestry) and 49 744 UK Biobank participants (mean [SD] age, 57.1 [8.0] years; 27 142 women [54.5%]; 1006 African [2.0%], 173 East Asian [0.3%], 939 South Asian [1.9%], and 46 449 European [93.4%] European ancestry) were included in the study. Of those, 59 participants (0.61%) in ARIC and 364 participants (0.73%) in UK Biobank harbored an actionable pathogenic or likely pathogenic variant associated with dilated or hypertrophic cardiomyopathy. Carriers of these variants were not reliably identifiable by imaging. However, the presence of these variants was associated with increased risk of heart failure (hazard ratio [HR], 1.7; 95% CI, 1.1-2.8), atrial fibrillation (HR, 2.9; 95% CI, 1.9-4.5), and all-cause mortality (HR, 1.5; 95% CI, 1.1-2.2) in ARIC. Similar risk patterns were observed in the UK Biobank. Conclusions and Relevance: Results of this genetic association study suggest that approximately 0.7% of study participants harbored a pathogenic variant associated with inherited cardiomyopathy. These variant carriers would be challenging to identify within clinical practice without genetic testing but are at increased risk for cardiovascular disease and all-cause mortality.

Genome-wide and phenome-wide analysis of ideal cardiovascular health in the VA Million Veteran Program.

BACKGROUND: Genetic studies may help identify causal pathways; therefore, we sought to identify genetic determinants of ideal CVH and their association with CVD outcomes in the multi-population Veteran Administration Million Veteran Program. METHODS: An ideal health score (IHS) was calculated from 3 clinical factors (blood pressure, total cholesterol, and blood glucose levels) and 3 behavioral factors (smoking status, physical activity, and BMI), ascertained at baseline. Multi-population genome-wide association study (GWAS) was performed on IHS and binary ideal health using linear and logistic regression, respectively. Using the genome-wide significant SNPs from the IHS GWAS, we created a weighted IHS polygenic risk score (PRSIHS) which was used (i) to conduct a phenome-wide association study (PheWAS) of associations between PRSIHS and ICD-9 phenotypes and (ii) to further test for associations with mortality and selected CVD outcomes using logistic and Cox regression and, as an instrumental variable, in Mendelian Randomization. RESULTS: The discovery and replication cohorts consisted of 142,404 (119,129 European American (EUR); 16,495 African American (AFR)), and 45,766 (37,646 EUR; 5,366 AFR) participants, respectively. The mean age was 65.8 years (SD = 11.2) and 92.7% were male. Overall, 4.2% exhibited ideal CVH based on the clinical and behavioral factors. In the multi-population meta-analysis, variants at 17 loci were associated with IHS and each had known GWAS associations with multiple components of the IHS. PheWAS analysis in 456,026 participants showed that increased PRSIHS was associated with a lower odds ratio for many CVD outcomes and risk factors. Both IHS and PRSIHS measures of ideal CVH were associated with significantly less CVD outcomes and CVD mortality. CONCLUSION: A set of high interest genetic variants contribute to the presence of ideal CVH in a multi-ethnic cohort of US Veterans. Genetically influenced ideal CVH is associated with lower odds of CVD outcomes and mortality.

Association of Habitual Alcohol Intake With Risk of Cardiovascular Disease.

Importance: Observational studies have consistently proposed cardiovascular benefits associated with light alcohol consumption, while recent genetic analyses (ie, mendelian randomization studies) have suggested a possible causal link between alcohol intake and increased risk of cardiovascular disease. However, traditional approaches to genetic epidemiology assume a linear association and thus have not fully evaluated dose-response estimates of risk across different levels of alcohol intake. Objectives: To assess the association of habitual alcohol intake with cardiovascular disease risk and to evaluate the direction and relative magnitude of cardiovascular risk associated with different amounts of alcohol consumption. Design, Setting, and Participants: This cohort study used the UK Biobank (2006-2010, follow-up until 2016) to examine confounding in epidemiologic associations between alcohol intake and cardiovascular diseases. Using both traditional (ie, linear) and nonlinear mendelian randomization, potential associations between alcohol consumption and cardiovascular diseases (eg, hypertension and coronary artery disease) as well as corresponding association shapes were assessed. Data analysis was conducted from July 2019 to January 2022. Exposures: Genetic predisposition to alcohol intake. Main Outcomes and Measures: The association between alcohol consumption and cardiovascular diseases, including hypertension, coronary artery disease, myocardial infarction, stroke, heart failure, and atrial fibrillation. Results: This study included 371 463 participants (mean [SD] age, 57.0 [7.9] years; 172 400 [46%] men), who consumed a mean (SD) 9.2 (10.6) standard drinks per week. Overall, 121 708 participants (33%) had hypertension. Light to moderate alcohol consumption was associated with healthier lifestyle factors, adjustment for which attenuated the cardioprotective epidemiologic associations with modest intake. In linear mendelian randomization analyses, a 1-SD increase in genetically predicted alcohol consumption was associated with 1.3-fold (95% CI, 1.2-1.4) higher risk of hypertension (P < .001) and 1.4-fold (95% CI, 1.1-1.8) higher risk of coronary artery disease (P = .006). Nonlinear mendelian randomization analyses suggested nonlinear associations between alcohol consumption and both hypertension and coronary artery disease: light alcohol intake was associated with minimal increases in cardiovascular risk, whereas heavier consumption was associated with exponential increases in risk of both clinical and subclinical cardiovascular disease. Conclusions and Relevance: In this cohort study, coincident, favorable lifestyle factors attenuated the observational benefits of modest alcohol intake. Genetic epidemiology suggested that alcohol consumption of all amounts was associated with increased cardiovascular risk, but marked risk differences exist across levels of intake, including those accepted by current national guidelines.

Association of the Interaction Between Familial Hypercholesterolemia Variants and Adherence to a Healthy Lifestyle With Risk of Coronary Artery Disease.

Importance: Familial hypercholesterolemia variants impair clearance of cholesterol from the circulation and increase risk of coronary artery disease (CAD). The extent to which adherence to a healthy lifestyle is associated with a lower risk of CAD in carriers and noncarriers of variants warrants further study. Objective: To assess the association of the interaction between familial hypercholesterolemia variants and adherence to a healthy lifestyle with risk of CAD. Design, Setting, and Participants: This cross-sectional study used 2 independent data sets with gene sequencing and lifestyle data from the UK Biobank: a case-control study of 4896 cases and 5279 controls and a cohort study of 39 920 participants. Participants were recruited from 22 sites across the UK between March 21, 2006, and October 1, 2010. The case-control study included participants with CAD and controls at enrollment. The cohort study used a convenience sample of individuals with available gene sequencing data. Statistical analysis was performed from April 2, 2019, to January 20, 2022. Exposures: Pathogenic or likely pathogenic DNA variants classified by a clinical laboratory geneticist and adherence to a healthy lifestyle based on a 4-point scoring system (1 point for each of the following: healthy diet, regular exercise, not smoking, and absence of obesity). Main Outcomes and Measures: Coronary artery disease, defined as myocardial infarction in the case-control study, and myocardial infarction, ischemic heart disease, or coronary revascularization procedure in the cohort study. Results: The case-control study included 10 175 participants (6828 men [67.1%]; mean [SD] age, 58.6 [7.2] years), and the cohort study included 39 920 participants (18 802 men [47.1%]; mean [SD] age at the end of follow-up, 66.4 [8.0] years). A variant was identified in 35 of 4896 cases (0.7%) and 12 of 5279 controls (0.2%), corresponding to an odds ratio of 3.0 (95% CI, 1.6-5.9), and a variant was identified in 108 individuals (0.3%) in the cohort study, in which the hazard ratio for CAD was 3.8 (95% CI, 2.5-5.8). However, this risk appeared to vary according to lifestyle categories in both carriers and noncarriers of familial hypercholesterolemia variants, without a significant interaction between carrier status and lifestyle (odds ratio, 1.2 [95% CI, 0.6-2.5]; P = .62). Among carriers, a favorable lifestyle conferred 86% lower risk of CAD compared with an unfavorable lifestyle (hazard ratio, 0.14 [95% CI, 0.04-0.41]). The estimated risk of CAD by the age of 75 years varied according to lifestyle, ranging from 10.2% among noncarriers with a favorable lifestyle to 24.0% among noncarriers with an unfavorable lifestyle and ranging from 34.5% among carriers with a favorable lifestyle to 66.2% among carriers with an unfavorable lifestyle. Conclusions and Relevance: This study suggests that, among carriers and noncarriers of a familial hypercholesterolemia variant, significant gradients in risk of CAD are noted according to adherence to a healthy lifestyle pattern. Similar to the general population, individuals who carry familial hypercholesterolemia variants are likely to benefit from lifestyle interventions to reduce their risk of CAD.

Analysis of rare genetic variation underlying cardiometabolic diseases and traits among 200,000 individuals in the UK Biobank.

Cardiometabolic diseases are the leading cause of death worldwide. Despite a known genetic component, our understanding of these diseases remains incomplete. Here, we analyzed the contribution of rare variants to 57 diseases and 26 cardiometabolic traits, using data from 200,337 UK Biobank participants with whole-exome sequencing. We identified 57 gene-based associations, with broad replication of novel signals in Geisinger MyCode. There was a striking risk associated with mutations in known Mendelian disease genes, including MYBPC3, LDLR, GCK, PKD1 and TTN. Many genes showed independent convergence of rare and common variant evidence, including an association between GIGYF1 and type 2 diabetes. We identified several large effect associations for height and 18 unique genes associated with blood lipid or glucose levels. Finally, we found that between 1.0% and 2.4% of participants carried rare potentially pathogenic variants for cardiometabolic disorders. These findings may facilitate studies aimed at therapeutics and screening of these common disorders.