Exome sequence analysis identifies rare coding variants associated with a machine learning-based marker for coronary artery disease.

Coronary artery disease (CAD) exists on a spectrum of disease represented by a combination of risk factors and pathogenic processes. An in silico score for CAD built using machine learning and clinical data in electronic health records captures disease progression, severity and underdiagnosis on this spectrum and could enhance genetic discovery efforts for CAD. Here we tested associations of rare and ultrarare coding variants with the in silico score for CAD in the UK Biobank, All of Us Research Program and BioMe Biobank. We identified associations in 17 genes; of these, 14 show at least moderate levels of prior genetic, biological and/or clinical support for CAD. We also observed an excess of ultrarare coding variants in 321 aggregated CAD genes, suggesting more ultrarare variant associations await discovery. These results expand our understanding of the genetic etiology of CAD and illustrate how digital markers can enhance genetic association investigations for complex diseases.

Prediction of Venous Thromboembolism in Diverse Populations Using Machine Learning and Structured Electronic Health Records.

BACKGROUND: Venous thromboembolism (VTE) is a major cause of morbidity and mortality worldwide. Current risk assessment tools, such as the Caprini and Padua scores and Wells criteria, have limitations in their applicability and accuracy. This study aimed to develop machine learning models using structured electronic health record data to predict diagnosis and 1-year risk of VTE. METHODS: We trained and validated models on data from 159 001 participants in the Mount Sinai Data Warehouse. We then externally tested them on 401 723 participants in the UK Biobank and 123 039 participants in All of Us. All data sets contain populations of diverse ancestries and clinical histories. We used these data sets to develop small, medium, and large models with increasing features on a range of optimizing portability to maximizing performance. We make trained models publicly available in click-and-run format at https://doi.org/10.17632/tkwzysr4y6.6. RESULTS: In the holdout and external test sets, respectively, models achieved areas under the receiver operating characteristic curve of 0.80 to 0.83 and 0.72 to 0.82 for VTE diagnosis prediction and 0.76 to 0.78 and 0.64 to 0.69 for 1-year risk prediction, significantly outperforming the Padua score. Models also demonstrated robust performance across different VTE types and patient subsets, including ethnicity, age, and surgical and hospitalization status. Models identified both established and novel clinical features contributing to VTE risk, offering valuable insights into its underlying pathophysiology. CONCLUSIONS: Machine learning models using structured electronic health record data can significantly improve VTE diagnosis and 1-year risk prediction in diverse populations. Model probability scores exist on a continuum, affecting mortality risk in both healthy individuals and VTE cases. Integrating these models into electronic health record systems to generate real-time predictions may enhance VTE risk assessment, early detection, and preventative measures, ultimately reducing the morbidity and mortality associated with VTE.

Primary Prevention of Subclinical Atherosclerosis in Young Adults: JACC Review Topic of the Week.

There is growing evidence that the atherosclerotic process that leads to symptomatic cardiovascular disease (CVD) starts at an early age. In young adults, exposure to low-density lipoprotein-cholesterol and other cardiovascular risk factor (CVRF) mediators, even at levels considered within normal limits, increases the prevalence of subclinical atherosclerosis and is associated with greater risk of cardiovascular events later in life. The optimal CVRF targets to prevent CVD in asymptomatic young individuals (<40 years) are unknown. The randomized controlled PRECAD (Prevent Coronary Artery Disease) trial has been developed to assess the potential benefit of an aggressive control of CVRF in otherwise healthy young adults. The hypothesis of PRECAD is that in subjects aged 20 to 39 years without known CVD, maintaining low-density lipoprotein-cholesterol <70 mg/dL and strict control of blood pressure and glucose will prevent the onset of atherosclerosis and/or its progression. The primary endpoint will be the change in total atherosclerosis burden, a surrogate for CVD.

Severe hypertriglyceridemia: Existing and emerging therapies.

Severe hypertriglyceridemia (sHTG), defined as a triglyceride (TG) concentration ≥ 500 mg/dL (≥ 5.7 mmol/L) is an important risk factor for acute pancreatitis. Although lifestyle, some medications, and certain conditions such as diabetes may lead to HTG, sHTG results from a combination of major and minor genetic defects in proteins that regulate TG lipolysis. Familial chylomicronemia syndrome (FCS) is a rare disorder caused by complete loss of function in lipoprotein lipase (LPL) or LPL activating proteins due to two homozygous recessive traits or compound heterozygous traits. Multifactorial chylomicronemia syndrome (MCS) and sHTG are due to the accumulation of rare heterozygous variants and polygenic defects that predispose individuals to sHTG phenotypes. Until recently, treatment of sHTG focused on lifestyle interventions, control of secondary factors, and nonselective pharmacotherapies that had modest TG-lowering efficacy and no corresponding reductions in atherosclerotic cardiovascular disease events. Genetic discoveries have allowed for the development of novel pathway-specific therapeutics targeting LPL modulating proteins. New targets directed towards inhibition of apolipoprotein C-III (apoC-III), angiopoietin-like protein 3 (ANGPTL3), angiopoietin-like protein 4 (ANGPTL4), and fibroblast growth factor-21 (FGF21) offer far more efficacy in treating the various phenotypes of sHTG and opportunities to reduce the risk of acute pancreatitis and atherosclerotic cardiovascular disease events.

ABCA1 Deficiency: A Rare Cause of Premature Coronary Artery Disease.

ATP-binding cassette transporter A1 (ABCA1) deficiency results in very low high-density lipoprotein cholesterol levels. Complete ABCA1 deficiency, or Tangier disease, is characterized by premature atherosclerotic cardiovascular disease, yellow-orange tonsils, hepatosplenomegaly, peripheral neuropathy, and corneal opacification. Early recognition of this condition can lead to regular monitoring for atherosclerotic cardiovascular symptoms and treatment of major modifiable risk factors. (Level of Difficulty: Beginner.).

Familial Hypercholesterolemia: Challenges for a High-Risk Population: JACC Focus Seminar 1/3.

The availability of statins, ezetimibe, and PCSK9 inhibitors has significantly improved the prognosis of familial hypercholesterolemia (FH). However, a great number of individuals with FH do not achieve guideline-recommended low-density lipoprotein (LDL) cholesterol levels despite maximal lipid-lowering therapy. Novel therapies that lower LDL independent of LDL receptor activity can help mitigate atherosclerotic cardiovascular disease risk in most homozygous FH and many heterozygous FH patients. However, access to novel therapies remains limited for heterozygous FH patients with persistent elevation of LDL cholesterol despite treatment with multiple classes of cholesterol-lowering therapies. Conduction of cardiovascular outcomes clinical trials in patients with FH can be challenging because of difficulty in recruitment and long periods of follow-up. In the future, the use of validated surrogate measures of atherosclerosis may allow for clinical trials with fewer study participants and shorter duration, thereby expediting access to novel treatments for patients with FH.

Clinical Trial Design for Triglyceride-Rich Lipoprotein-Lowering Therapies: JACC Focus Seminar 3/3.

Triglyceride-rich lipoproteins (TRLs) are a source of residual risk in patients with atherosclerotic cardiovascular disease, and are indirectly correlated with triglyceride (TG) levels. Previous clinical trials studying TG-lowering therapies have either failed to reduce major adverse cardiovascular events or shown no linkage of TG reduction with event reduction, particularly when these agents were tested on a background of statin therapy. Limitations in trial design may explain this lack of efficacy. With the advent of new RNA-silencing therapies in the TG metabolism pathway, there is renewed focus on reducing TRLs for major adverse cardiovascular event reduction. In this context, the pathophysiology of TRLs, pharmacological effects of TRL-lowering therapies, and optimal design of cardiovascular outcomes trials are major considerations.

Clinical Trial Design for Lipoprotein(a)-Lowering Therapies: JACC Focus Seminar 2/3.

Lipoprotein(a) [Lp(a)] is a source of residual risk in patients with atherosclerotic cardiovascular disease (ASCVD). Clinical trials of fully human monoclonal antibodies targeting proprotein convertase subtilisin kexin 9 have shown that reductions in Lp(a) concentrations may be a predictor of event reduction with this class of cholesterol-lowering therapy. With the advent of selective therapies targeting Lp(a) such as antisense oligonucleotides, small-interfering RNA-based therapies, and gene editing, lowering of Lp(a) may lead to reduction in ASCVD. The phase 3 Lp(a)HORIZON (Assessing the Impact of Lipoprotein(a) Lowering with TQJ230 on Major Cardiovascular Events in Patients With CVD) outcomes trial is currently testing the effect of pelacarsen, an antisense oligonucleotide, on ASCVD risk. Olpasiran is a small-interfering RNA that is in a phase 3 clinical trial. As these therapies enter clinical trials, challenges in trial design will have to be addressed to optimize patient selection and outcomes.

Predictors of Survival for Patients with Acute Decompensated Heart Failure Requiring Extra-Corporeal Membrane Oxygenation Therapy.

Chronic systolic heart failure (HF) with acute decompensation can result in cardiogenic shock (CS) requiring short-term mechanical circulatory support. We sought to identify predictors of survival for acute decompensated HF (ADHF) patients requiring veno-arterial extracorporeal membrane oxygenation (VA-ECMO). Patients >18 years old treated at our institution with VA-ECMO from 2009 to 2018 for ADHF with CS were studied. Demographic, hemodynamic, and echocardiographic data were collected. The primary outcome was survival to discharge. Fifty-two patients received VA-ECMO for ADHF with CS; 24 (46.2%) survived. Seventeen (32.7%) had suffered cardiac arrest, and 37 (71.2%) were mechanically ventilated. Mean lactate was 4.33 ± 3.45 mmol/L, and patients were receiving 2.7 ± 1.2 vasopressor/inotropic infusions at ECMO initiation; these did not differ significantly between survivors and nonsurvivors. Pre-ECMO cardiac index was 1.84 ± 0.56L/min/m and 1.94 ± 0.63L/min/m in survivors and nonsurvivors, respectively (p = 0.57). In multivariable analysis, only diabetes mellitus (DM; OR, 13.25; CI, 1.42-123.40; p = 0.02) and mineralocorticoid receptor antagonist use (OR, 0.12; CI, 0.02-0.78; p = 0.03) were independent predictors of mortality. Nineteen (79.2%) survivors required durable ventricular assist device. Among ADHF patients receiving VA-ECMO, DM is a powerful predictor of outcomes while markers of clinical acuity including hemodynamics, vasopressor/inotrope use, and lactate are not. The vast majority of survivors required durable left-ventricular assist devices.