👤 Patrick T Ellinor

The genetic influences on normal aortic valve function and their impact on aortic stenosis risk are of substantial interest. We used deep learning to measure peak velocity, mean gradient and aortic valve area from magnetic resonance imaging and conducted genome-wide association studies (GWAS) in 59,571 participants in the UK Biobank. Incorporating the aortic valve measurement GWAS with aortic stenosis GWAS using multitrait analysis of GWAS (MTAG), we identified 166 distinct loci (134 with aortic valve traits, 134 with aortic stenosis and 166 unique loci across all GWAS), including PCSK9 and LDLR. The MTAG aortic stenosis PGS was associated with aortic stenosis in All of Us (hazard ratio (HR) = 3.32 for top 5% versus all others, P = 8.8 × 10 Show less

Treatment to lower high levels of low-density lipoprotein cholesterol (LDL-C) reduces incident coronary artery disease (CAD) risk but modestly increases the risk for incident type 2 diabetes (T2D). The extent to which genetic factors across the cholesterol spectrum are associated with incident T2D is not well understood. To investigate the association of genetic predisposition to increased LDL-C levels with incident T2D risk. In this large prospective, population-based cohort study, UK Biobank participants who underwent whole-exome sequencing and genome-wide genotyping were included. Participants were separated into 7 groups with familial hypercholesterolemia (FH), predicted loss of function (pLOF) in APOB or PCSK9 variants, and LDL-C polygenic risk score (PRS) quintiles. Data were collected between 2006 and 2010, with a median follow-up of 13.7 (IQR, 12.9-14.5) years. Data were analyzed from March 1 to November 1, 2024. LDL-C level, LDL-C PRS, FH, or pLOF variant status. Cox proportional hazards regression models adjusted for age, sex, genotyping array, lipid-lowering medication use, and the first 10 genetic principal components were fitted to assess the association between LDL-C genetic factors and incident T2D and CAD risks. Among the 361 082 participants, mean (SD) age was 56.8 (8.0) years, 194 751 (53.9%) were female, and mean (SD) baseline LDL-C level was 138.0 (33.6) mg/dL. During the follow-up period, 22 619 (6.3%) participants developed incident T2D and 17 966 (5.0%) developed incident CAD. The hazard ratio for incident T2D was lowest in the FH group (0.65; 95% CI, 0.54-0.77), while the highest risk was in the pLOF group (1.48; 95% CI, 1.18-1.86). The association between LDL-C PRS and incident T2D was 0.72 (95% CI, 0.66-0.79) for very high LDL-C PRS, 0.87 (95% CI, 0.84-0.90) for high LDL-C PRS, 1.13 (95% CI, 1.09-1.17) for low LDL-C PRS, and 1.26 (95% CI, 1.15-1.38) for very low LDL-C PRS. CAD risk increased directly with the LDL-C PRS. In this cohort study, LDL-C and T2D risks were inversely associated across genetic mechanisms for LDL-C variation. Further elucidation of the mechanisms associating low LDL-C risk with increased risk of T2D is warranted. Show less

Elevated lipoprotein(a) [Lp(a)] is an independent risk factor for coronary artery disease (CAD). Data on long-term outcomes following invasive coronary angiography (ICA) in those with elevated Lp(a) are limited. This study examined the association of Lp(a) levels with clinical outcomes after index ICA, accounting for baseline atherosclerotic plaque burden. Data were from participants with Lp(a) measurement who underwent index ICA between 2000 and 2023. Lp(a) levels were categorized as normal (<75 nmol/L), intermediate (75- < 125 nmol/L), high (125- < 175 nmol/L), and very high (≥175 nmol/L). Angiographic characteristics (severity, burden), CAD presentation (stable, acute), and subsequent clinical outcomes [acute myocardial infarction (AMI), revascularization, in-stent restenosis (ISR), and all-cause mortality] were assessed. Among 5118 participants, 973 (19.0%) had very high Lp(a). Compared with normal Lp(a), very high Lp(a) was associated with severe obstructive CAD {adjusted odds ratio (aOR), 1.51 [95% confidence interval (CI), 1.17-1.96]}, left main disease [aOR, 1.67 (95% CI, 1.22-2.29)], and a 14.04-point higher Gensini score (95% CI, 9.57-18.52). During a median (interquartile range) follow-up of 16.87 (6.38-18.99) years, participants with very high vs. normal Lp(a) had higher risk of AMI [adjusted hazard ratio (aHR), 1.20 (95% CI, 1.05-1.37)], revascularization [aHR, 1.32 (95% CI, 1.13-1.56)], ISR [aHR, 1.28 (95% CI, 1.04-1.56)], and mortality [aHR, 1.19 (95% CI, 1.05-1.34)]. Among 798 individuals undergoing coronary artery bypass grafting surgery after index ICA, those with very high vs. other Lp(a) were more likely to require subsequent percutaneous coronary intervention [aHR, 2.20 (95% CI, 1.06-4.58)]. Elevated Lp(a) levels are associated with increased burden of coronary atherosclerosis and significant residual risk for adverse outcomes following ICA, highlighting a need for targeted risk-reduction strategies. Show less

Atrial fibrillation (AF) is a prevalent and morbid abnormality of the heart rhythm with a strong genetic component. Here, we meta-analyzed genome and exome sequencing data from 36 studies that included 52,416 AF cases and 277,762 controls. In burden tests of rare coding variation, we identified novel associations between AF and the genes MYBPC3, LMNA, PKP2, FAM189A2 and KDM5B. We further identified associations between AF and rare structural variants owing to deletions in CTNNA3 and duplications of GATA4. We broadly replicated our findings in independent samples from MyCode, deCODE and UK Biobank. Finally, we found that CRISPR knockout of KDM5B in stem-cell-derived atrial cardiomyocytes led to a shortening of the action potential duration and widespread transcriptomic dysregulation of genes relevant to atrial homeostasis and conduction. Our results highlight the contribution of rare coding and structural variants to AF, including genetic links between AF and cardiomyopathies, and expand our understanding of the rare variant architecture for this common arrhythmia. Show less

To broaden our understanding of bradyarrhythmias and conduction disease, we performed common variant genome-wide association analyses in up to 1.3 million individuals and rare variant burden testing in 460,000 individuals for sinus node dysfunction (SND), distal conduction disease (DCD) and pacemaker (PM) implantation. We identified 13, 31 and 21 common variant loci for SND, DCD and PM, respectively. Four well-known loci (SCN5A/SCN10A, CCDC141, TBX20 and CAMK2D) were shared for SND and DCD, while others were more specific for SND or DCD. SND and DCD showed a moderate genetic correlation (r Show less

Despite a proposed causal role for LDL-C (low-density lipoprotein cholesterol) in aortic stenosis (AS), randomized controlled trials of lipid-lowering therapy failed to prevent severe AS. We aimed to assess the impact on AS and peak velocity across the aortic valve conferred by lifelong alterations in LDL-C levels mediated by protein-disrupting variants in 3 clinically significant genes for LDL (low-density lipoprotein) metabolism ( We used sequencing data and electronic health records from UK Biobank (UKB) and All of Us and magnetic resonance imaging data from UKB. We identified predicted protein-disrupting variants with the Loss Of Function Transcript Effect Estimator (LOFTEE) and AlphaMissense algorithms and evaluated their associations with LDL-C and peak velocity across the aortic valve (UK Biobank), as well as diagnosed AS and aortic valve replacement (UK Biobank and All of Us). We included 421 049 unrelated participants (5621 with AS) in UKB and 195 519 unrelated participants (1087 with AS) in All of Us. Carriers of protein-disrupting variants in Rare genetic variants that confer lifelong higher or lower LDL-C levels are associated with substantially increased and decreased risk of AS, respectively. Early and sustained lipid-lowering therapy may slow or prevent AS development. Show less

Artificial intelligence (AI) models applied to 12-lead ECG waveforms can predict atrial fibrillation (AF), a heritable and morbid arrhythmia. However, the factors forming the basis of risk predictions from AI models are usually not well understood. We hypothesized that there might be a genetic basis for an AI algorithm for predicting the 5-year risk of new-onset AF using 12-lead ECGs (ECG-AI)-based risk estimates. We applied a validated ECG-AI model for predicting incident AF to ECGs from 39 986 UK Biobank participants without AF. We then performed a genome-wide association study (GWAS) of the predicted AF risk and compared it with an AF GWAS and a GWAS of risk estimates from a clinical variable model. In the ECG-AI GWAS, we identified 3 signals ( Predicted AF risk from an ECG-AI model is influenced by genetic variation implicating sarcomeric, ion channel and body height pathways. ECG-AI models may identify individuals at risk for disease via specific biological pathways. Show less

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. To assess the contributions of rare and common genetic variation to risk of HCM in the general population. 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. Pathogenic rare variants, common-variant (polygenic) score, and clinical risk factors. Risk of HCM. 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). 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. Show less

Pathogenic variants associated with inherited cardiomyopathy are recognized as important and clinically actionable when identified, leading some clinicians to recommend population-wide genomic screening. To determine the prevalence and clinical importance of pathogenic variants associated with inherited cardiomyopathy within the context of contemporary clinical care. 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. Rare genetic variants predisposing to inherited cardiomyopathy. 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. 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. 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. Show less

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. Show less

The HERMES (HEart failure Molecular Epidemiology for Therapeutic targetS) consortium aims to identify the genomic and molecular basis of heart failure. The consortium currently includes 51 studies from 11 countries, including 68 157 heart failure cases and 949 888 controls, with data on heart failure events and prognosis. All studies collected biological samples and performed genome-wide genotyping of common genetic variants. The enrolment of subjects into participating studies ranged from 1948 to the present day, and the median follow-up following heart failure diagnosis ranged from 2 to 116 months. Forty-nine of 51 individual studies enrolled participants of both sexes; in these studies, participants with heart failure were predominantly male (34-90%). The mean age at diagnosis or ascertainment across all studies ranged from 54 to 84 years. Based on the aggregate sample, we estimated 80% power to genetic variant associations with risk of heart failure with an odds ratio of ≥1.10 for common variants (allele frequency ≥ 0.05) and ≥1.20 for low-frequency variants (allele frequency 0.01-0.05) at P < 5 × 10 HERMES is a global collaboration aiming to (i) identify the genetic determinants of heart failure; (ii) generate insights into the causal pathways leading to heart failure and enable genetic approaches to target prioritization; and (iii) develop genomic tools for disease stratification and risk prediction. Show less

Excess liver fat, called hepatic steatosis, is a leading risk factor for end-stage liver disease and cardiometabolic diseases but often remains undiagnosed in clinical practice because of the need for direct imaging assessments. We developed an abdominal MRI-based machine-learning algorithm to accurately estimate liver fat (correlation coefficients, 0.97-0.99) from a truth dataset of 4,511 middle-aged UK Biobank participants, enabling quantification in 32,192 additional individuals. 17% of participants had predicted liver fat levels indicative of steatosis, and liver fat could not have been reliably estimated based on clinical factors such as BMI. A genome-wide association study of common genetic variants and liver fat replicated three known associations and identified five newly associated variants in or near the Show less

Genome-wide association studies (GWAS) have identified >250 loci for body mass index (BMI), implicating pathways related to neuronal biology. Most GWAS loci represent clusters of common, noncoding variants from which pinpointing causal genes remains challenging. Here we combined data from 718,734 individuals to discover rare and low-frequency (minor allele frequency (MAF) < 5%) coding variants associated with BMI. We identified 14 coding variants in 13 genes, of which 8 variants were in genes (ZBTB7B, ACHE, RAPGEF3, RAB21, ZFHX3, ENTPD6, ZFR2 and ZNF169) newly implicated in human obesity, 2 variants were in genes (MC4R and KSR2) previously observed to be mutated in extreme obesity and 2 variants were in GIPR. The effect sizes of rare variants are ~10 times larger than those of common variants, with the largest effect observed in carriers of an MC4R mutation introducing a stop codon (p.Tyr35Ter, MAF = 0.01%), who weighed ~7 kg more than non-carriers. Pathway analyses based on the variants associated with BMI confirm enrichment of neuronal genes and provide new evidence for adipocyte and energy expenditure biology, widening the potential of genetically supported therapeutic targets in obesity. Show less