Search

Valvular heart disease is associated with a high global burden of disease. Even mild aortic stenosis confers increased morbidity and mortality, prompting interest in understanding normal variation in valvular function at scale.We developed a deep learning model to study velocity-encoded magnetic resonance imaging in 47,223 UK Biobank participants. We calculated eight traits, including peak velocity, mean gradient, aortic valve area, forward stroke volume, mitral and aortic regurgitant volume, greatest average velocity, and ascending aortic diameter. We then computed sex-stratified reference ranges for these phenotypes in up to 31,909 healthy individuals. In healthy individuals, we found an annual decrement of 0.03cm2in the aortic valve area. Participants with mitral valve prolapse had a 1 standard deviation [SD] higher mitral regurgitant volume (P=9.6 × 10−12), and those with aortic stenosis had a 4.5 SD-higher mean gradient (P=1.5 × 10−431), validating the derived phenotypes’ associations with clinical disease. Greater levels of ApoB, triglycerides, and Lp(a) assayed nearly 10 years prior to imaging were associated with higher gradients across the aortic valve. Metabolomic profiles revealed that increased glycoprotein acetyls were also associated with an increased aortic valve mean gradient (0.92 SD, P=2.1 x 10−22). Finally, velocity-derived phenotypes were risk markers for aortic and mitral valve surgery even at thresholds below what is considered relevant disease currently.Using machine learning to quantify the rich phenotypic data of the UK Biobank, we report the largest assessment of valvular function and cardiovascular disease in the general population.

BackgroundOral nirmatrelvir/ritonavir is a treatment for COVID-19, but whether treatment during the acute phase reduces the risk of developing Long COVID is unknown.MethodsUsing the Covid Citizen Science (CCS) online cohort, we surveyed individuals who reported their first SARS-CoV-2 positive test between March and August 2022 regarding Long COVID symptoms. We excluded those who were pregnant, unvaccinated, hospitalized for COVID-19, or received other antiviral therapy. The primary exposure was oral nirmatrelvir/ritonavir. The primary outcome was the presence of any Long COVID symptoms reported on cross-sectional surveys in November and December 2022. We used propensity-score models and inverse probability of treatment weighting to adjust for differences in treatment propensity. Our secondary question was whether symptom or test positivity rebound were associated with Long COVID.Results4684 individuals met the eligibility criteria, of whom 988 (21.1%) were treated and 3696 (78.9%) were untreated; 353/988 (35.7%) treated and 1258/3696 (34.0%) untreated responded to the survey. Median age was 55 years and 66% were female. We did not identify an association between nirmatrelvir/ritonavir treatment and Long COVID symptoms (OR 1.15; 95%CI 0.80-1.64). Among n=666 treated with nirmatrelvir/ritonavir who responded who responded to questions about rebound, rebound symptoms or test positivity were not associated with Long COVID symptoms (OR 1.34; 95%CI 0.74-2.41; p=0.33).ConclusionsWithin this cohort, treatment with nirmatrelvir/ritonavir among vaccinated, non-hospitalized individuals was not associated with lower prevalence of Long COVID symptoms or severity of Long COVID. Experiencing rebound symptoms or test positivity is not strongly associated with developing Long COVID.

AimsThe behavior of pacemaker cardiomyocytes (PCs) in the sinoatrial node (SAN) is modulated by neurohormonal and paracrine factors, many of which signal through G-protein coupled receptors (GPCRs). The aims of the present study are to catalog GPCRs that are differentially expressed in the mammalian SAN and to define the acute physiological consequences of activating the cholecystokinin-A signaling system in the SAN and in isolated PCs.Methods and ResultsUsing bulk and single cell RNA sequencing datasets, we identify a set of GPCRs that are differentially expressed between SAN and right atrial tissue, including several whose roles in PCs and in the SAN have not been thoroughly characterized. Focusing on one such GPCR, Cholecystokinin-A receptor (CCKAR), we demonstrate expression ofCckarmRNA specifically in mammalian PCs, and further demonstrate that subsets of SAN fibroblasts and neurons within the cardiac intrinsic nervous system express cholecystokinin, the ligand for CCKAR. Using mouse models, we find that while baseline SAN function is not dramatically affected by loss of CCKAR, the firing rate of individual PCs is slowed by exposure to sulfated cholecystokinin-8 (sCCK-8), the high affinity ligand for CCKAR. The effect of sCCK-8 on firing rate is mediated by reduction in the rate of spontaneous phase 4 depolarization of PCs and is mitigated by activation of beta-adrenergic signaling. Finally, while perfusion of sCCK-8 onto the SANex-vivoreduces the beating rate modestly, exposure to sCCK-8 unexpectedly shortened the sinus node recovery time, a finding that has potential implications for treatment of SAN dysfunction.Conclusions(1) PCs express many GPCRs whose specific roles in SAN function have not been characterized, (2) the cholecystokinin-A pathway constitutes a novel signaling system that regulates SAN function and PC electrophysiology.Translational PerspectiveThe time required for the sinoatrial node (SAN) to resume function after overdrive suppression is called the sinus node recovery time (SNRT). In the tachy-brady syndrome, pathological prolongation of the SNRT results in symptomatic sinus pauses that follow the termination of a tachyarrhythmia, leading to loss of consciousness. Tachy-brady syndrome is the most common presentation of sinus node dysfunction and can only be treated with a permanent pacemaker. In this study, we find that activation of the cholecystokinin-A signaling system can shorten the SNRT, raising the possibility of developing new pharmacological methods to treat tachy-brady syndrome.

Cells interpret a variety of signals through G protein-coupled receptors (GPCRs) and stimulate the generation of second messengers such as cyclic adenosine monophosphate (cAMP). A long-standing puzzle is deciphering how GPCRs elicit different physiological responses despite generating similar levels of cAMP. We previously showed that some GPCRs generate cAMP from both the plasma membrane and the Golgi apparatus. Here, we demonstrate that cardiomyocytes distinguish between subcellular cAMP inputs to elicit different physiological outputs. We show that generating cAMP from the Golgi leads to regulation of a specific PKA target that increases the rate of cardiomyocyte relaxation. In contrast, cAMP generation from the plasma membrane activates a different PKA target that increases contractile force. We further validated the physiological consequences of these observations in intact zebrafish and mice. Thus, we demonstrate that the same GPCR acting through the same second messenger regulates cardiac contraction and relaxation dependent on its subcellular location.

Despite some inconsistent reporting of symptoms, studies have demonstrated that at least 20% of individuals infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) will remain asymptomatic. Although most global efforts have focused on understanding factors underlying severe illness in COVID-19 (coronavirus disease of 2019), the examination of asymptomatic infection provides a unique opportunity to consider early disease and immunologic features promoting rapid viral clearance. Owing to its critical role in the immune response, we postulated that variation in the human leukocyte antigen (HLA) loci may underly processes mediating asymptomatic infection. We enrolled 29,947 individuals registered in the National Marrow Donor Program for whom high-resolution HLA genotyping data were available in the UCSF Citizen Science smartphone-based study designed to track COVID-19 symptoms and outcomes. Our discovery cohort (n=1428) was comprised of unvaccinated, self-identified subjects who reported a positive test result for SARS-CoV-2. We tested for association of five HLA loci (HLA-A, -B, -C, -DRB1, -DQB1) with disease course and identified a strong association of HLA-B*15:01 with asymptomatic infection, and reproduced this association in two independent cohorts. Suggesting that this genetic association is due to pre-existing T-cell immunity, we show that T cells from pre-pandemic individuals carrying HLA-B*15:01 were reactive to the immunodominant SARS-CoV-2 S-derived peptide NQKLIANQF, and 100% of the reactive cells displayed memory phenotype. Finally, we characterize the protein structure of HLA-B*15:01-peptide complexes, demonstrating that the NQKLIANQF peptide from SARS-CoV-2, and the highly homologous NQKLIANAF from seasonal coronaviruses OC43-CoV and HKU1-CoV, share similar ability to be stabilized and presented by HLA-B*15:01, providing the molecular basis for T-cell cross-reactivity and HLA-B*15:01-mediated pre-existing immunity.

Expanding access to precision medicine will increasingly require that patient biometrics can be measured in remote care settings. VO2max, the maximum volume of oxygen usable during intense exercise, is one of the most predictive biometric risk factors for cardiovascular disease, frailty, and overall mortality.1,2 However, VO2max measurements are rarely performed in clinical care or large-scale epidemiologic studies due to the high cost, participant burden, and need for specialized laboratory equipment and staff.3,4 To overcome these barriers, we developed two smartphone sensor-based protocols for estimating VO2max: a generalization of a 12-minute run test (12-MRT) and a submaximal 3-minute step test (3-MST). In laboratory settings, Lins concordance for these two tests relative to gold standard VO2max testing was pc=0.66 for 12-MRT and pc=0.61 for 3-MST. Relative to “silver standards”5 (Cooper/Tecumseh protocols), concordance was pc=0.96 and pc=0.94, respectively. However, in remote settings, 12-MRT was significantly less concordant with gold standard (pc=0.25) compared to 3-MST (pc=0.61), though both had high test-retest reliability (ICC=0.88 and 0.86, respectively). These results demonstrate the importance of real-world evidence for validation of digital health measurements. In order to validate 3-MST in a broadly representative population in accordance with the All of Us Research Program6 for which this measurement was developed, the camera-based heart rate measurement was investigated for potential bias. No systematic measurement error was observed that corresponded to skin pigmentation level, operating system, or cost of the phone used. The smartphone-based 3-MST protocol, here termed Heart Snapshot, maintained fidelity across demographic variation in age and sex, across diverse skin pigmentation, and between iOS and Android implementations of various smartphone models. The source code for these smartphone measurements, along with the data used to validate them,6 are openly available to the research community.