Rationale Machine learning may be useful to characterize cardiovascular risk, predict outcomes and identify biomarkers in population studies. Objective To test the ability of random survival forests (RF), a machine learning technique, to predict six cardiovascular outcomes in comparison to standard cardiovascular risk scores. Methods and Results We included participants from the Multi-Ethnic Study of Atherosclerosis (MESA). Baseline measurements were used to predict cardiovascular outcomes over 12 years of follow-up. MESA was designed to study progression of subclinical disease to cardiovascular events where participants were initially free of CV disease. All 6814 participants from MESA, aged 45 to 84 years, from 4 ethnicities, and 6 centers across USA were included. 735 variables from imaging and non-invasive tests, questionnaires and biomarker panels were obtained. We used the RF technique to identify the top 20 predictors of each outcome. Imaging, electrocardiography and serum biomarkers featured heavily on the top-20 lists as opposed to traditional CV risk factors. Age was the most important predictor for all-cause mortality. Fasting glucose levels and carotid ultrasonography measures were important predictors of stroke. Coronary artery calcium score was the most important predictor of coronary heart disease and all atherosclerotic cardiovascular disease combined outcomes. Left ventricular structure and function, and cardiac troponin-T were among the top predictors for incident heart failure. Creatinine, age and ankle brachial index were among the top predictors of atrial fibrillation. Tissue necrosis factor-α and interleukin-2 soluble receptors, and N-terminal pro-Brain Natriuretic Peptide levels were important across all outcomes. The RF technique performed better than established risk scores with increased prediction accuracy (decreased Brier score by 10–25%). Conclusions Machine learning in conjunction with deep phenotyping improve prediction accuracy in cardiovascular event prediction in an initially asymptomatic population. These methods may lead to greater insights regarding subclinical disease markers without apriori assumptions of causality. Clinical Trial Registration Multi-Ethnic Study of Atherosclerosis (MESA) http://mesa-nhlbi.org/. ClinicalTrials.gov Identifier NCT00005487

Cardiovascular magnetic resonance (CMR) enables assessment and quantification of morphological and functional parameters of the heart, including chamber size and function, diameters of the aorta and pulmonary arteries, flow and myocardial relaxation times. Knowledge of reference ranges (“normal values”) for quantitative CMR is crucial to interpretation of results and to distinguish normal from disease. Compared to the previous version of this review published in 2015, we present updated and expanded reference values for morphological and functional CMR parameters of the cardiovascular system based on the peer-reviewed literature and current CMR techniques. Further, databases and references for deep learning methods are included.

Dilated cardiomyopathy (DCM) is an important cause of heart failure and the leading indication for heart transplantation. Many rare genetic variants have been associated with DCM, but common variant studies of the disease have yielded few associated loci. As structural changes in the heart are a defining feature of DCM, we report a genome-wide association study of cardiac magnetic resonance imaging (MRI)-derived left ventricular measurements in 36,041 UK Biobank participants, with replication in 2184 participants from the Multi-Ethnic Study of Atherosclerosis. We identify 45 previously unreported loci associated with cardiac structure and function, many near well-established genes for Mendelian cardiomyopathies. A polygenic score of MRI-derived left ventricular end systolic volume strongly associates with incident DCM in the general population. Even among carriers of TTN truncating mutations, this polygenic score influences the size and function of the human heart. These results further implicate common genetic polymorphisms in the pathogenesis of DCM.

Fibrotic remodelling of the extracellular matrix is a healing mechanism necessary immediately after myocardial injury. However, prolonged increase in myocardial fibrotic activity results in stiffening of the myocardium and heralds adverse outcomes related to systolic and diastolic dysfunction, as well as arrhythmogenesis. Cardiac MRI provides a noninvasive phenotyping tool for accurate and easy detection and quantification of myocardial fibrosis by probing the retention of gadolinium-contrast agent in myocardial tissue. Late-gadolinium enhancement (LGE) cardiac MRI has been used extensively in a large number of studies for measurement of myocardial scarring. T1 mapping, a fairly new technique that can be used to identify the exact T1 value of the tissue, provides a direct measurement of the extracellular volume fraction of the myocardium. In contrast to LGE, T1 mapping can be used to measure diffuse myocardial fibrosis and differentiate between disease processes. In this Review, we describe the basic principles of imaging myocardial fibrosis using contrast-enhanced MRI and summarize its use for prognostic purposes.

The increase in red blood cell mass (polycythemia) due to the reduced oxygen availability (hypoxia) of residence at high altitude or other conditions is generally thought to be beneficial in terms of increasing tissue oxygen supply. However, the extreme polycythemia and accompanying increased mortality due to heart failure in chronic mountain sickness most likely reduces fitness. Tibetan highlanders have adapted to high altitude, possibly in part via the selection of genetic variants associated with reduced polycythemic response to hypoxia. In contrast, high-altitude-adapted Quechua- and Aymara-speaking inhabitants of the Andean Altiplano are not protected from high-altitude polycythemia in the same way, yet they exhibit other adaptive features for which the genetic underpinnings remain obscure. Here, we used whole-genome sequencing to scan high-altitude Andeans for signals of selection. The genes showing the strongest evidence of selection-including BRINP3, NOS2, and TBX5-are associated with cardiovascular development and function but are not in the response-to-hypoxia pathway. Using association mapping, we demonstrated that the haplotypes under selection are associated with phenotypic variations related to cardiovascular health. We hypothesize that selection in response to hypoxia in Andeans could have vascular effects and could serve to mitigate the deleterious effects of polycythemia rather than reduce polycythemia itself.