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Summary: Background: Smartphone apps might enable interventions to increase physical activity, but few randomised trials testing this hypothesis have been done. The MyHeart Counts Cardiovascular Health Study is a longitudinal smartphone-based study with the aim of elucidating the determinants of cardiovascular health. We aimed to investigate the effect of four different physical activity coaching interventions on daily step count in a substudy of the MyHeart Counts Study. Methods: In this randomised, controlled crossover trial, we recruited adults (aged ≥18 years) in the USA with access to an iPhone smartphone (Apple, Cupertino, CA, USA; version 5S or newer) who had downloaded the MyHeart Counts app (version 2.0). After completion of a 1 week baseline period of interaction with the MyHeart Counts app, participants were randomly assigned to receive one of 24 permutations (four combinations of four 7 day interventions) in a crossover design using a random number generator built into the app. Interventions consisted of either daily prompts to complete 10 000 steps, hourly prompts to stand following 1 h of sitting, instructions to read the guidelines from the American Heart Association website, or e-coaching based upon the individual's personal activity patterns from the baseline week of data collection. Participants completed the trial in a free-living setting. Due to the nature of the interventions, participants could not be masked from the intervention. Investigators were not masked to intervention allocation. The primary outcome was change in mean daily step count from baseline for each of the four interventions, assessed in the modified intention-to-treat analysis set, which included all participants who had completed 7 days of baseline monitoring and at least 1 day of one of the four interventions. This trial is registered with ClinicalTrials.gov, NCT03090321. Findings: Between Dec 12, 2016, and June 6, 2018, 2783 participants consented to enrol in the coaching study, of whom 1075 completed 7 days of baseline monitoring and at least 1 day of one of the four interventions and thus were included in the modified intention-to-treat analysis set. 493 individuals completed the full set of assigned interventions. All four interventions significantly increased mean daily step count from baseline (mean daily step count 2914 [SE 74]): mean step count increased by 319 steps (75) for participants in the American Heart Association website prompt group (p

Background: Smartphone applications may enable interventions to increase physical activity but this has limited evidence in randomized trials. Objectives: The MyHeart Counts Cardiovascular Health study (MHC) is a smartphone-based longitudinal research study aimed at elucidating the determinants of cardiovascular health. Among MHC participants, we performed a randomized controlled trial to investigate the response to four different physical activity coaching interventions on the primary outcome of change in daily step count. Secondary outcomes included life satisfaction, 6-minute walk distance, and sleep quality. Methods: The trial was completed entirely using personal smartphones: participants were digitally consented, the interventions were delivered via the device, and measurements of the primary and secondary outcomes were collected from smartphone sensors. Participants were enrolled from December 12, 2016 to June 6, 2018 and followed for up to 5 weeks. Participants completed the trial through the MyHeart Counts phone app in a free-living setting. All adults over 18 years of age with access to a smartphone (Apple iPhone, version 5S or later) were eligible to participate. After one week of baseline measurements, participants (n=2783) were randomized to a sequence of four, week-long interventions delivered in random order. Interventions consisted of either daily prompts to complete 10,000 steps (completed by n=853); hourly prompts to stand following a full hour of sitting (completed by n=879); instructions to read the guidelines from the American Heart Association website (completed by n=868); and e-coaching based upon the individual's personal activity patterns from the baseline week of data collection (completed by n=896). Results: 2783 participants consented to enroll in the coaching study, of whom 1075 completed the baseline week of data collection and at least one of the four interventions. 493 individuals completed the full set of assigned interventions. All four interventions were found effective at modestly increasing daily step count by a mean of 266 ±75 steps from a baseline mean of 2958±69 steps (p=0.003). Intervention-specific step increases were: 319±74 steps (p

Background The genetic determinants of heart failure (HF) and response to medical therapy remain unknown. We hypothesized that identifying genetic variants of HF that associate with response to medical therapy would elucidate the genetic basis of cardiac function. Objectives This study sought to identify genetic variations associated with response to HF therapy. Methods This study compared extremes of response to medical therapy in 866 HF patients using a genome-wide approach that informed the systems-based design of a customized single nucleotide variant array. The effect of genotype on gene expression was measured using allele-specific luciferase reporter assays. Candidate gene transcription-deficient mice underwent echocardiography and treadmill exercise. The ability of the target gene agonist to rescue mice from chemically-induced HF was assessed with echocardiography. Results Of 866 HF patients, 136 had an ejection fraction improvement of 20% attributed to resynchronization (n = 83), revascularization (n = 7), tachycardia resolution (n = 2), alcohol cessation (n = 1), or medications (n = 43). Those with the minor allele for rs7767652, upstream of hypocretin (orexin) receptor-2 (HCRTR2), were less likely to have improved left ventricular function (odds ratio: 0.40 per minor allele; p = 3.29 × 10−5). In a replication cohort of 798 patients, those with a minor allele for rs7767652 had a lower prevalence of ejection fraction >35% (odds ratio: 0.769 per minor allele; p = 0.021). In an HF model, HCRTR2-deficient mice exhibited poorer cardiac function, worse treadmill exercise capacity, and greater myocardial scarring. Orexin, an HCRTR2 agonist, rescued function in this HF mouse model. Conclusions A systems approach identified a novel genetic contribution to human HF and a promising therapeutic agent efficacious in an HF model.

Objectives This study sought to discover the key determinants of exercise capacity, maximal oxygen consumption (oxygen uptake [Vo2]), and ventilatory efficiency (ventilation/carbon dioxide output [VE/Vco2] slope) and assess the prognostic potential of metabolic exercise testing in hypertrophic cardiomyopathy (HCM). Background The intrinsic mechanisms leading to reduced functional tolerance in HCM are unclear. Methods The study sample included 156 HCM patients consecutively enrolled from January 1, 2007 to January 1, 2012 with a complete clinical assessment, including rest and stress echocardiography and cardiopulmonary exercise test (CPET) with impedance cardiography. Patients were also followed for the composite outcome of cardiac-related death, heart transplant, and functional deterioration leading to septal reduction therapy (myectomy or septal alcohol ablation). Results Abnormalities in CPET responses were frequent, with 39% (n = 61) of the sample showing a reduced exercise tolerance (Vo2 max 34). The variables most strongly associated with exercise capacity (expressed in metabolic equivalents), were peak cardiac index (r = 0.51, p 34 (hazard ratio: 3.14; 95% CI: 1.26 to 7.87; p = 0.014), and LAVI >40 ml/m2 (hazard ratio: 3.32; 95% CI: 1.08 to 10.16; p = 0.036). Conclusions In HCM, peak cardiac index is the main determinant of exercise capacity, but it is not significantly related to ventilatory efficiency. Peak Vo2, ventilatory inefficiency, and LAVI are associated with an increased risk of major events in the short-term follow-up.

Summary Background The cost of genomic information has fallen steeply, but the clinical translation of genetic risk estimates remains unclear. We aimed to undertake an integrated analysis of a complete human genome in a clinical context. Methods We assessed a patient with a family history of vascular disease and early sudden death. Clinical assessment included analysis of this patient's full genome sequence, risk prediction for coronary artery disease, screening for causes of sudden cardiac death, and genetic counselling. Genetic analysis included the development of novel methods for the integration of whole genome and clinical risk. Disease and risk analysis focused on prediction of genetic risk of variants associated with mendelian disease, recognised drug responses, and pathogenicity for novel variants. We queried disease-specific mutation databases and pharmacogenomics databases to identify genes and mutations with known associations with disease and drug response. We estimated post-test probabilities of disease by applying likelihood ratios derived from integration of multiple common variants to age-appropriate and sex-appropriate pre-test probabilities. We also accounted for gene-environment interactions and conditionally dependent risks. Findings Analysis of 2·6 million single nucleotide polymorphisms and 752 copy number variations showed increased genetic risk for myocardial infarction, type 2 diabetes, and some cancers. We discovered rare variants in three genes that are clinically associated with sudden cardiac death— TMEM43, DSP , and MYBPC3 . A variant in LPA was consistent with a family history of coronary artery disease. The patient had a heterozygous null mutation in CYP2C19 suggesting probable clopidogrel resistance, several variants associated with a positive response to lipid-lowering therapy, and variants in CYP4F2 and VKORC1 that suggest he might have a low initial dosing requirement for warfarin. Many variants of uncertain importance were reported. Interpretation Although challenges remain, our results suggest that whole-genome sequencing can yield useful and clinically relevant information for individual patients. Funding National Institute of General Medical Sciences; National Heart, Lung And Blood Institute; National Human Genome Research Institute; Howard Hughes Medical Institute; National Library of Medicine, Lucile Packard Foundation for Children's Health; Hewlett Packard Foundation; Breetwor Family Foundation.

Purpose Previous studies have shown that hypertrophic cardiomyopathy (HCM) can also affect the right ventricle (RV), but there are not univoque data about it. The aim of this study is to describe RV dysfunction in patients with HCM using the myocardial performance index (MPI), tricuspid annular plane systolic excursion (TAPSE) and RV fractional area change (RVFAC) and their association with clinical outcome. Methods and Materials Consecutive patients with HCM followed at Stanford Hospital from 1999 to 2012 were included in the study. A total of 324 patients with HCM were included in the study. A group of 99 age and sex matched healthy volunteers were used as controls. Multivariable regression analysis was used to determine independent correlates of RV function. Results Compared to matched controls, patients with HCM had higher RVMPI (0.51±0.18 vs. 0.25±0.06, p 0.4 (HR 3.13 per 0.3, CI 95% 1.63 to 6.0, p Conclusions RV dysfunction based on RVMPI is common in patients with HCM and is more frequently observed among patients with LV dysfunction and pulmonary hypertension. RV dysfunction based on RVMPI was associated with a history of syncope, defibrillator discharge or lower maximal VO2.