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Background: Atherosclerotic cardiovascular disease (ASCVD) risk estimation based on the pooled cohort equation (PCE) overestimates in population-based cohorts. Whether it performs equally across disaggregated demographics in health care populations is less known. Objectives: The purpose of the study was to recalibrate PCE and rederive prevention thresholds in a contemporary health care system and evaluate its performance across sociodemographics. Methods: We retrospectively inspected electronic health records between 2010 to 2012 and 2020 to 2022 within Mass General Brigham health care in New England region. We compared performance of the original vs recalibrated PCE measured by calibration, discrimination, reclassification rate, and net benefit among 160,926 patients aged 40 to 79 years and without prior ASCVD or lipid-lowering medication. Results: Of the 160,926 patients (mean age: 54.6 ± 8.6 years; 61.4% female), 20,373 (12.7%) developed ASCVD over 10 years. The original PCE globally underestimated ASCVD risk (observed vs predicted incidence rate: 0.13 vs 0.05). Recalibration upclassified risk primarily among individuals with low-to-borderline risk by the original PCE and additionally identified 40% of patients who had undergone ASCVD events yet deemed statin-ineligible based on the original PCE. Treatment thresholds yielding the greatest net benefit were ≥24.0% for women (+23.3%) vs ≥26.0% for men (+18.7%), whereas ≥26.0% for White or other race (+24.7%) vs ≥14.0% Black or African American (+12.5%), respectively. Specifically, Hispanic or Latino and non-Hispanic Black patients conferred the greatest sensitivity improvement at ≥12.3% threshold compared to higher ≥23.6% among non-Hispanic Asian or Pacific Islanders. Generally, lower thresholds earlier in life were optimal. Conclusions: Recalibration and personalized treatment thresholds derived within a health system may improve prevention treatment allocation efficiency.

Background Coronary artery disease (CAD) is a leading cause of death among the 38.4 million people with HIV globally. The extent to which cardiovascular polygenic risk scores (PRSs) derived in non‐HIV populations generalize to people with HIV is not well understood. Methods and Results PRSs for CAD (GPSMult) and lipid traits were calculated in a global cohort of people with HIV treated with antiretroviral therapy with low‐to‐moderate atherosclerotic cardiovascular disease risk enrolled in REPRIEVE (Randomized Trial to Prevent Vascular Events in HIV). The PRSs were associated with baseline lipid traits in 4495 genotyped participants, and with subclinical CAD in a subset of 662 who underwent coronary computed tomography angiography. Among participants who underwent coronary computed tomography angiography (mean age, 50.9 [SD, 5.8] years; 16.1% women; 41.8% African, 57.3% European, 1.1% Asian), GPSMult was associated with plaque presence with odds ratio (OR) per SD in GPSMult of 1.42 (95% CI, 1.20–1.68; P=3.8×10−5), stenosis >50% (OR, 2.39 [95% CI, 1.48–3.85]; P=3.4×10−4), and noncalcified/vulnerable plaque (OR, 1.45 [95% CI, 1.23–1.72]; P=9.6×10−6). Effects were consistent in subgroups of age, sex, 10‐year atherosclerotic cardiovascular disease risk, ancestry, and CD4 count. Adding GPSMult to established risk factors increased the C‐statistic for predicting plaque presence from 0.718 to 0.734 (P=0.02). Furthermore, a PRS for low‐density lipoprotein cholesterol was associated with plaque presence with OR of 1.21 (95% CI, 1.01–1.44; P=0.04), and partially calcified plaque with OR of 1.21 (95% CI, 1.01–1.45; P=0.04) per SD. Conclusions Among people with HIV treated with antiretroviral therapy without documented atherosclerotic cardiovascular disease and at low‐to‐moderate calculated risk in REPRIEVE, an externally developed CAD PRS was predictive of subclinical atherosclerosis. PRS for low‐density lipoprotein cholesterol was also associated with subclinical atherosclerosis, supporting a role for low‐density lipoprotein cholesterol in HIV‐associated CAD. Registration URL: https://www.reprievetrial.org; Unique identifier: NCT02344290.

Summary: While lipid traits are known essential mediators of cardiovascular disease, few approaches have taken advantage of their shared genetic effects. We apply a Bayesian multivariate size estimator, mash, to GWAS of four lipid traits in the Million Veterans Program (MVP) and provide posterior mean and local false sign rates for all effects. These estimates borrow information across traits to improve effect size accuracy. We show that controlling local false sign rates accurately and powerfully identifies replicable genetic associations and that multivariate control furthers the ability to explain complex diseases. Our application yields high concordance between independent datasets, more accurately prioritizes causal genes, and significantly improves polygenic prediction beyond state-of-the-art methods by up to 59% for lipid traits. The use of Bayesian multivariate genetic shrinkage has yet to be applied to human quantitative trait GWAS results, and we present a staged approach to prediction on a polygenic scale.

Background High and low birth weight are independently associated with increased cardiovascular disease risk in adulthood. Clonal hematopoiesis of indeterminate potential (CHIP), the age‐related clonal expansion of hematopoietic cells with preleukemic somatic mutations, predicts incident cardiovascular disease independent of traditional cardiovascular risk factors. Whether birth weight predicts development of CHIP later in life is unknown. Methods and Results A total of 221 047 adults enrolled in the UK Biobank with whole exome sequences and self‐reported birth weight were analyzed. Of those, 22 030 (11.5%) had low (4.0 kg). CHIP prevalence was higher among participants with low (6.0%, P=0.049) and high (6.3%, P

Abstract Background Disclosure of pathogenic variants to thoracic aortic dissection biobank participants was implemented. The impact and costs, including confirmatory genetic testing in a Clinical Laboratory Improvement Amendments (CLIA)-certified laboratory, were evaluated. Methods We exome sequenced 240 cases with thoracic aortic dissection and 258 controls, then examined 11 aortopathy genes. Pathogenic variants in 6 aortopathy genes (COL3A1, FBN1, LOX, PRKG1, SMAD3, and TGFBR2) were identified in 26 participants, representing 10.8% of the cohort (26/240). A second research sample was used to validate the initial findings. Mailed letters to participants disclosed that a potentially disease causing DNA alteration had been identified (neither the gene nor variant was disclosed). Participants were offered clinical genetic counseling and confirmatory genetic testing in a CLIA laboratory. Results Excluding 6 participants who were deceased or lost to follow-up, 20 participants received the disclosure letter, 10 of whom proceeded with genetic counseling, confirmatory genetic testing, and enrolled in a survey study. Participants reported satisfaction with the letter (4.2 ± 0.7) and genetic counseling (4.4 ± 0.4; [out of 5, respectively]). The psychosocial impact was characterized by low decisional regret (11.5 ± 11.6) and distress (16.0 ± 4.2, [out of 100, respectively]). The average cost for 26 participants was $400, including validation and sending letters. The average cost for those who received genetic counseling and CLIA laboratory confirmation was $605. Conclusions Participants were satisfied with the return of clinically significant biobank genetic results and CLIA laboratory testing; however, the process required significant time and resources. These findings illustrate the trade-offs involved for researchers considering returning research genetic results.

Aortic valve stenosis (AS) is the most common valvular heart disease. Here the authors identify two new AS loci that also associate with bicuspid aortic valve, aortic root diameter and/or coronary artery disease implicating both developmental abnormalities and atherosclerosis-like processes in AS.

Bicuspid aortic valve (BAV) is the most common human congenital cardiovascular malformation. Here, the authors perform a genome-wide association study for BAV and identify risk variants in the gene region of cardiac-specific transcription factor GATA4 and implicate GATA4 in heart valve development.