Background Hypertrophic cardiomyopathy (HCM) is caused by rare variants in sarcomere-encoding genes, but little is known about the clinical significance of these variants in the general population. Objectives The goal of this study was to compare lifetime outcomes and cardiovascular phenotypes according to the presence of rare variants in sarcomere-encoding genes among middle-aged adults. Methods This study analyzed whole exome sequencing and cardiac magnetic resonance imaging in UK Biobank participants stratified according to sarcomere-encoding variant status. Results The prevalence of rare variants (allele frequency <0.00004) in HCM-associated sarcomere-encoding genes in 200,584 participants was 2.9% (n = 5,712; 1 in 35), and the prevalence of variants pathogenic or likely pathogenic for HCM (SARC-HCM-P/LP) was 0.25% (n = 493; 1 in 407). SARC-HCM-P/LP variants were associated with an increased risk of death or major adverse cardiac events compared with controls (hazard ratio: 1.69; 95% confidence interval [CI]: 1.38-2.07; P < 0.001), mainly due to heart failure endpoints (hazard ratio: 4.23; 95% CI: 3.07-5.83; P < 0.001). In 21,322 participants with both cardiac magnetic resonance imaging and whole exome sequencing, SARC-HCM-P/LP variants were associated with an asymmetric increase in left ventricular maximum wall thickness (10.9 ± 2.7 mm vs 9.4 ± 1.6 mm; P < 0.001), but hypertrophy (≥13 mm) was only present in 18.4% (n = 9 of 49; 95% CI: 9%-32%). SARC-HCM-P/LP variants were still associated with heart failure after adjustment for wall thickness (hazard ratio: 6.74; 95% CI: 2.43-18.7; P < 0.001). Conclusions In this population of middle-aged adults, SARC-HCM-P/LP variants have low aggregate penetrance for overt HCM but are associated with an increased risk of adverse cardiovascular outcomes and an attenuated cardiomyopathic phenotype. Although absolute event rates are low, identification of these variants may enhance risk stratification beyond familial disease.

Objective To determine whether analysis of microvascular network perfusion using complexity‐based methods can discriminate between groups of individuals at an increased risk of developing CVD. Methods Data were obtained from laser Doppler recordings of skin blood flux at the forearm in 50 participants with non‐alcoholic fatty liver disease grouped for absence (n = 28) or presence (n = 14) of type 2 diabetes and use of calcium channel blocker medication (n = 8). Power spectral density was evaluated and Lempel‐Ziv complexity determined to quantify signal information content at single and multiple time‐scales to account for the different processes modulating network perfusion. Results Complexity was associated with dilatory capacity and respiration and negatively with baseline blood flux and cardiac band power. The relationship between the modulators of flowmotion and complexity of blood flux is shown to change with time‐scale improving discrimination between groups. Multiscale Lempel‐Ziv achieved best classification accuracy of 86.1%. Conclusions Time and frequency domain measures alone are insufficient to discriminate between groups. As cardiovascular disease risk increases, the degree of complexity of the blood flux signal reduces, indicative of a reduced temporal activity and heterogeneous distribution of blood flow within the microvascular network sampled. Complexity‐based methods, particularly multiscale variants, are shown to have good discriminatory capabilities.

Diastole is the sequence of physiological events that occur in the heart during ventricular filling and principally depends on myocardial relaxation and chamber stiffness. Abnormal diastolic function is related to many cardiovascular disease processes and is predictive of health outcomes, but its genetic architecture is largely unknown. Here, we use machine-learning cardiac motion analysis to measure diastolic functional traits in 39,559 participants of the UK Biobank and perform a genome-wide association study. We identified nine significant, independent loci near genes that are associated with maintaining sarcomeric function under biomechanical stress and genes implicated in the development of cardiomyopathy. Age, sex and diabetes were independent predictors of diastolic function and we found a causal relationship between genetically determined ventricular stiffness and incident heart failure. Our results provide insights into the genetic and environmental factors influencing diastolic function that are relevant for identifying causal relationships and potential tractable targets.