👤 James Pirruccello

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

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

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

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

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

Angiopoietin-like 3 (ANGPTL3) has emerged as a key regulator of lipoprotein metabolism in humans. Homozygous loss of ANGPTL3 function causes familial combined hypolipidemia characterized by low plasma levels of triglycerides (TG), high-density lipoprotein cholesterol (HDL-C), and low-density lipoprotein cholesterol (LDL-C). While known effects of ANGPTL3 in inhibiting lipoprotein lipase and endothelial lipase contribute to the low TG and HDL-C, respectively, the basis of low LDL-C remains unclear. Our aim was to explore the role of ANGPTL3 in modulating plasma LDL-C. We performed RNAi-mediated gene silencing of ANGPTL3 in five mouse models and in human hepatoma cells. We validated results by deleting ANGPTL3 gene using the CRISPR/Cas9 genome editing system. RNAi-mediated Angptl3 silencing in mouse livers resulted in very low TG, HDL-C and LDL-C, a pattern similar to the human phenotype. The effect was observed in wild-type and obese mice, while in hCETP/apolipoprotein (Apo) B-100 double transgenic mice, the silencing decreased LDL-C and TG, but not HDL-C. In a humanized mouse model (Apobec1 Reduced secretion and increased uptake of ApoB-containing lipoproteins may contribute to the low LDL-C observed in mice and humans with genetic ANGPTL3 deficiency. Show less

Genome-wide association studies (GWAS) for plasma lipid levels have mapped numerous genomic loci, with each region often containing many protein-coding genes. Targeted re-sequencing of exons is a strategy to pinpoint causal variants and genes. We performed solution-based hybrid selection of 9008 exons at 939 genes within 95 GWAS loci for plasma lipid levels and sequenced using next-generation sequencing technology individuals with extremely high as well as low to normal levels of low-density lipoprotein cholesterol (LDL-C, n = 311; mean low = 71 mg/dl versus high = 241 mg/dl), triglycerides (TG, n = 308; mean low = 75 mg/dl versus high = 1938 mg/dl), and high-density lipoprotein cholesterol (HDL-C, n = 684; mean low = 32 mg/dl versus high = 102 mg/dl). We identified 15,002 missense, nonsense, or splice site variants with a frequency <5%. We tested whether coding sequence variants, individually or aggregated within a gene, were associated with plasma lipid levels. To replicate findings, we performed sequencing in independent participants (n = 6424). Across discovery and replication sequencing, we found 6 variants with significant associations with plasma lipids. Of these, one was a novel association: p.Ser147Asn variant in APOA4 (14.3% frequency, TG OR = 0.49, P = 7.1 × 10(-4)) with TG. In gene-level association analyses where rare variants within each gene are collapsed, APOC3 (P = 2.1 × 10(-5)) and LDLR (P = 5.0 × 10(-12)) were associated with plasma lipids. After sequencing genes from 95 GWAS loci in participants with extremely high plasma lipid levels, we identified one new coding variant associated with TG. These results provide insight regarding design of similar sequencing studies with respect to sample size, follow-up, and analysis methodology. Show less

The National Heart, Lung, and Blood Institute's Candidate Gene Association Resource (CARe), a planned cross-cohort analysis of genetic variation in cardiovascular, pulmonary, hematologic, and sleep-related traits, comprises >40,000 participants representing 4 ethnic groups in 9 community-based cohorts. The goals of CARe include the discovery of new variants associated with traits using a candidate gene approach and the discovery of new variants using the genome-wide association mapping approach specifically in African Americans. CARe has assembled DNA samples for >40,000 individuals self-identified as European American, African American, Hispanic, or Chinese American, with accompanying data on hundreds of phenotypes that have been standardized and deposited in the CARe Phenotype Database. All participants were genotyped for 7 single-nucleotide polymorphisms (SNPs) selected based on prior association evidence. We performed association analyses relating each of these SNPs to lipid traits, stratified by sex and ethnicity, and adjusted for age and age squared. In at least 2 of the ethnic groups, SNPs near CETP, LIPC, and LPL strongly replicated for association with high-density lipoprotein cholesterol concentrations, PCSK9 with low-density lipoprotein cholesterol levels, and LPL and APOA5 with serum triglycerides. Notably, some SNPs showed varying effect sizes and significance of association in different ethnic groups. The CARe Pilot Study validates the operational framework for phenotype collection, SNP genotyping, and analytic pipeline of the CARe project and validates the planned candidate gene study of approximately 2000 biological candidate loci in all participants and genome-wide association study in approximately 8000 African American participants. CARe will serve as a valuable resource for the scientific community. Show less