Clonal Hematopoiesis of Indeterminate Potential With Loss of Tet2 Enhances Risk for Atrial Fibrillation Through Nlrp3 Inflammasome Activation.

BACKGROUND: Clonal hematopoiesis of indeterminate potential (CHIP), a common age-associated phenomenon, associates with increased risk of both hematological malignancy and cardiovascular disease. Although CHIP is known to increase the risk of myocardial infarction and heart failure, the influence of CHIP in cardiac arrhythmias, such as atrial fibrillation (AF), is less explored. METHODS: CHIP prevalence was determined in the UK Biobank, and incident AF analysis was stratified by CHIP status and clone size using Cox proportional hazard models. Lethally irradiated mice were transplanted with hematopoietic-specific loss of Tet2, hematopoietic-specific loss of Tet2 and Nlrp3, or wild-type control and fed a Western diet, compounded with or without NLRP3 (NLR [NACHT, LRR {leucine rich repeat}] family pyrin domain containing protein 3) inhibitor, NP3-361, for 6 to 9 weeks. Mice underwent in vivo invasive electrophysiology studies and ex vivo optical mapping. Cardiomyocytes from Ldlr-/- mice with hematopoietic-specific loss of Tet2 or wild-type control and fed a Western diet were isolated to evaluate calcium signaling dynamics and analysis. Cocultures of pluripotent stem cell-derived atrial cardiomyocytes were incubated with Tet2-deficient bone marrow-derived macrophages, wild-type control, or cytokines IL-1ß (interleukin 1ß) or IL-6 (interleukin 6). RESULTS: Analysis of the UK Biobank showed individuals with CHIP, in particular TET2 CHIP, have increased incident AF. Hematopoietic-specific inactivation of Tet2 increases AF propensity in atherogenic and nonatherogenic mouse models and is associated with increased Nlrp3 expression and CaMKII (Ca2+/calmodulin-dependent protein kinase II) activation, with AF susceptibility prevented by inactivation of Nlrp3. Cardiomyocytes isolated from Ldlr-/- mice with hematopoietic inactivation of Tet2 and fed a Western diet have impaired calcium release from the sarcoplasmic reticulum into the cytosol, contributing to atrial arrhythmogenesis. Abnormal sarcoplasmic reticulum calcium release was recapitulated in cocultures of cardiomyocytes with the addition of Tet2-deficient macrophages or cytokines IL-1ß or IL-6. CONCLUSIONS: We identified a modest association between CHIP, particularly TET2 CHIP, and incident AF in the UK Biobank population. In a mouse model of AF resulting from hematopoietic-specific inactivation of Tet2, we propose altered calcium handling as an arrhythmogenic mechanism, dependent on Nlrp3 inflammasome activation. Our data are in keeping with previous studies of CHIP in cardiovascular disease, and further studies into the therapeutic potential of NLRP3 inhibition for individuals with TET2 CHIP may be warranted.

Clonal haematopoiesis of indeterminate potential predicts incident cardiac arrhythmias.

BACKGROUND AND AIMS: Clonal haematopoiesis of indeterminate potential (CHIP), the age-related expansion of blood cells with preleukemic mutations, is associated with atherosclerotic cardiovascular disease and heart failure. This study aimed to test the association of CHIP with new-onset arrhythmias. METHODS: UK Biobank participants without prevalent arrhythmias were included. Co-primary study outcomes were supraventricular arrhythmias, bradyarrhythmias, and ventricular arrhythmias. Secondary outcomes were cardiac arrest, atrial fibrillation, and any arrhythmia. Associations of any CHIP [variant allele fraction (VAF) ≥ 2%], large CHIP (VAF ≥10%), and gene-specific CHIP subtypes with incident arrhythmias were evaluated using multivariable-adjusted Cox regression. Associations of CHIP with myocardial interstitial fibrosis [T1 measured using cardiac magnetic resonance (CMR)] were also tested. RESULTS: This study included 410 702 participants [CHIP: n = 13 892 (3.4%); large CHIP: n = 9191 (2.2%)]. Any and large CHIP were associated with multi-variable-adjusted hazard ratios of 1.11 [95% confidence interval (CI) 1.04-1.18; P = .001] and 1.13 (95% CI 1.05-1.22; P = .001) for supraventricular arrhythmias, 1.09 (95% CI 1.01-1.19; P = .031) and 1.13 (95% CI 1.03-1.25; P = .011) for bradyarrhythmias, and 1.16 (95% CI, 1.00-1.34; P = .049) and 1.22 (95% CI 1.03-1.45; P = .021) for ventricular arrhythmias, respectively. Associations were independent of coronary artery disease and heart failure. Associations were also heterogeneous across arrhythmia subtypes and strongest for cardiac arrest. Gene-specific analyses revealed an increased risk of arrhythmias across driver genes other than DNMT3A. Large CHIP was associated with 1.31-fold odds (95% CI 1.07-1.59; P = .009) of being in the top quintile of myocardial fibrosis by CMR. CONCLUSIONS: CHIP may represent a novel risk factor for incident arrhythmias, indicating a potential target for modulation towards arrhythmia prevention and treatment.

Selenoprotein deficiency disorder predisposes to aortic aneurysm formation.

Aortic aneurysms, which may dissect or rupture acutely and be lethal, can be a part of multisystem disorders that have a heritable basis. We report four patients with deficiency of selenocysteine-containing proteins due to selenocysteine Insertion Sequence Binding Protein 2 (SECISBP2) mutations who show early-onset, progressive, aneurysmal dilatation of the ascending aorta due to cystic medial necrosis. Zebrafish and male mice with global or vascular smooth muscle cell (VSMC)-targeted disruption of Secisbp2 respectively show similar aortopathy. Aortas from patients and animal models exhibit raised cellular reactive oxygen species, oxidative DNA damage and VSMC apoptosis. Antioxidant exposure or chelation of iron prevents oxidative damage in patient's cells and aortopathy in the zebrafish model. Our observations suggest a key role for oxidative stress and cell death, including via ferroptosis, in mediating aortic degeneration.

Accelerometer-Derived "Weekend Warrior" Physical Activity and Incident Cardiovascular Disease.

Importance: Guidelines recommend 150 minutes or more of moderate to vigorous physical activity (MVPA) per week for overall health benefit, but the relative effects of concentrated vs more evenly distributed activity are unclear. Objective: To examine associations between an accelerometer-derived "weekend warrior" pattern (ie, most MVPA achieved over 1-2 days) vs MVPA spread more evenly with risk of incident cardiovascular events. Design, Setting, and Participants: Retrospective analysis of UK Biobank cohort study participants providing a full week of accelerometer-based physical activity data between June 8, 2013, and December 30, 2015. Exposures: Three MVPA patterns were compared: active weekend warrior (active WW, ≥150 minutes with ≥50% of total MVPA achieved in 1-2 days), active regular (≥150 minutes and not meeting active WW status), and inactive (<150 minutes). The same patterns were assessed using the sample median threshold of 230.4 minutes or more of MVPA per week. Main Outcomes and Measures: Associations between activity pattern and incident atrial fibrillation, myocardial infarction, heart failure, and stroke were assessed using Cox proportional hazards regression, adjusted for age, sex, racial and ethnic background, tobacco use, alcohol intake, Townsend Deprivation Index, employment status, self-reported health, and diet quality. Results: A total of 89 573 individuals (mean [SD] age, 62 [7.8] years; 56% women) who underwent accelerometry were included. When stratified at the threshold of 150 minutes or more of MVPA per week, a total of 37 872 were in the active WW group (42.2%), 21 473 were in the active regular group (24.0%), and 30 228 were in the inactive group (33.7%). In multivariable-adjusted models, both activity patterns were associated with similarly lower risks of incident atrial fibrillation (active WW: hazard ratio [HR], 0.78 [95% CI, 0.74-0.83]; active regular: 0.81 [95% CI, 0.74-0.88; inactive: HR, 1.00 [95% CI, 0.94-1.07]), myocardial infarction (active WW: 0.73 [95% CI, 0.67-0.80]; active regular: 0.65 [95% CI, 0.57-0.74]; and inactive: 1.00 [95% CI, 0.91-1.10]), heart failure (active WW: 0.62 [95% CI, 0.56-0.68]; active regular: 0.64 [95% CI, 0.56-0.73]; and inactive: 1.00 [95% CI, 0.92-1.09]), and stroke (active WW: 0.79 [95% CI, 0.71-0.88]; active regular: 0.83 [95% CI, 0.72-0.97]; and inactive: 1.00 [95% CI, 0.90-1.11]). Findings were consistent at the median threshold of 230.4 minutes or more of MVPA per week, although associations with stroke were no longer significant (active WW: 0.89 [95% CI, 0.79-1.02]; active regular: 0.87 [95% CI, 0.74-1.02]; and inactive: 1.00 [95% CI, 0.90-1.11]). Conclusions and Relevance: Physical activity concentrated within 1 to 2 days was associated with similarly lower risk of cardiovascular outcomes to more evenly distributed activity.

Recruited macrophages elicit atrial fibrillation.

Atrial fibrillation disrupts contraction of the atria, leading to stroke and heart failure. We deciphered how immune and stromal cells contribute to atrial fibrillation. Single-cell transcriptomes from human atria documented inflammatory monocyte and SPP1+ macrophage expansion in atrial fibrillation. Combining hypertension, obesity, and mitral valve regurgitation (HOMER) in mice elicited enlarged, fibrosed, and fibrillation-prone atria. Single-cell transcriptomes from HOMER mouse atria recapitulated cell composition and transcriptome changes observed in patients. Inhibiting monocyte migration reduced arrhythmia in Ccr2-∕- HOMER mice. Cell-cell interaction analysis identified SPP1 as a pleiotropic signal that promotes atrial fibrillation through cross-talk with local immune and stromal cells. Deleting Spp1 reduced atrial fibrillation in HOMER mice. These results identify SPP1+ macrophages as targets for immunotherapy in atrial fibrillation.

Assessment of valvular function in over 47,000 people using deep learning-based flow measurements.

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 0.03cm 2 in 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.

Artificial intelligence-enabled classification of hypertrophic heart diseases using electrocardiograms.

Background: Differentiating among cardiac diseases associated with left ventricular hypertrophy (LVH) informs diagnosis and clinical care. Objective: To evaluate if artificial intelligence-enabled analysis of the 12-lead electrocardiogram (ECG) facilitates automated detection and classification of LVH. Methods: We used a pretrained convolutional neural network to derive numerical representations of 12-lead ECG waveforms from patients in a multi-institutional healthcare system who had cardiac diseases associated with LVH (n = 50,709), including cardiac amyloidosis (n = 304), hypertrophic cardiomyopathy (n = 1056), hypertension (n = 20,802), aortic stenosis (n = 446), and other causes (n = 4766). We then regressed LVH etiologies relative to no LVH on age, sex, and the numerical 12-lead representations using logistic regression ("LVH-Net"). To assess deep learning model performance on single-lead data analogous to mobile ECGs, we also developed 2 single-lead deep learning models by training models on lead I ("LVH-Net Lead I") or lead II ("LVH-Net Lead II") from the 12-lead ECG. We compared the performance of the LVH-Net models to alternative models fit on (1) age, sex, and standard ECG measures, and (2) clinical ECG-based rules for diagnosing LVH. Results: The areas under the receiver operator characteristic curve of LVH-Net by specific LVH etiology were cardiac amyloidosis 0.95 [95% CI, 0.93-0.97], hypertrophic cardiomyopathy 0.92 [95% CI, 0.90-0.94], aortic stenosis LVH 0.90 [95% CI, 0.88-0.92], hypertensive LVH 0.76 [95% CI, 0.76-0.77], and other LVH 0.69 [95% CI 0.68-0.71]. The single-lead models also discriminated LVH etiologies well. Conclusion: An artificial intelligence-enabled ECG model is favorable for detection and classification of LVH and outperforms clinical ECG-based rules.

Plasma extracellular vesicle transcriptome as a dynamic liquid biopsy in acute heart failure.

Background: Acute decompensation is associated with increased mortality in heart failure (HF) patients, though the underlying etiology remains unclear. Extracellular vesicles (EVs) and their cargo may mark specific cardiovascular physiologic states. We hypothesized that EV transcriptomic cargo, including long non-coding RNAs (lncRNAs) and mRNAs, is dynamic from the decompensated to recompensated HF state, reflecting molecular pathways relevant to adverse remodeling. Methods: We examined differential RNA expression from circulating plasma extracellular RNA in acute HF patients at hospital admission and discharge alongside healthy controls. We leveraged different exRNA carrier isolation methods, publicly available tissue banks, and single nuclear deconvolution of human cardiac tissue to identify cell and compartment specificity of the topmost significantly differentially expressed targets. EV-derived transcript fragments were prioritized by fold change (-1.5 to + 1.5) and significance (<5% false discovery rate), and their expression in EVs was subsequently validated in 182 additional patients (24 control; 86 HFpEF; 72 HFrEF) by qRT-PCR. We finally examined the regulation of EV-derived lncRNA transcripts in human cardiac cellular stress models. Results: We identified 138 lncRNAs and 147 mRNAs (present mostly as fragments in EVs) differentially expressed between HF and control. Differentially expressed transcripts between HFrEF vs. control were primarily cardiomyocyte derived, while those between HFpEF vs. control originated from multiple organs and different (non-cardiomyocyte) cell types within the myocardium. We validated 5 lncRNAs and 6 mRNAs to differentiate between HF and control. Of those, 4 lncRNAs (AC092656.1, lnc-CALML5-7, LINC00989, RMRP) were altered by decongestion, with their levels independent of weight changes during hospitalization. Further, these 4 lncRNAs dynamically responded to stress in cardiomyocytes and pericytes in vitro , with a directionality mirroring the acute congested state. Conclusion: Circulating EV transcriptome is significantly altered during acute HF, with distinct cell and organ specificity in HFpEF vs. HFrEF consistent with a multi-organ vs. cardiac origin, respectively. Plasma EV-derived lncRNA fragments were more dynamically regulated with acute HF therapy independent of weight change (relative to mRNAs). This dynamicity was further demonstrated with cellular stress in vitro . Prioritizing transcriptional changes in plasma circulating EVs with HF therapy may be a fruitful approach to HF subtype-specific mechanistic discovery. CLINICAL PERSPECTIVE: What is new?: We performed extracellular transcriptomic analysis on the plasma of patients with acute decompensated heart failure (HFrEF and HFpEF) before and after decongestive efforts.Long non-coding RNAs (lncRNAs) within extracellular vesicles (EVs) changed dynamically upon decongestion in concordance with changes within human iPSC-derived cardiomyocytes under stress.In acute decompensated HFrEF, EV RNAs are mainly derived from cardiomyocytes, whereas in HFpEF, EV RNAs appear to have broader, non-cardiomyocyte origins.What are the clinical implications?: Given their concordance between human expression profiles and dynamic in vitro responses, lncRNAs within EVs during acute HF may provide insight into potential therapeutic targets and mechanistically relevant pathways. These findings provide a "liquid biopsy" support for the burgeoning concept of HFpEF as a systemic disorder extending beyond the heart, as opposed to a more cardiac-focused physiology in HFrEF.

Wearable accelerometer-derived physical activity and incident disease.

Physical activity is regarded as favorable to health but effects across the spectrum of human disease are poorly quantified. In contrast to self-reported measures, wearable accelerometers can provide more precise and reproducible activity quantification. Using wrist-worn accelerometry data from the UK Biobank prospective cohort study, we test associations between moderate-to-vigorous physical activity (MVPA) - both total MVPA minutes and whether MVPA is above a guideline-based threshold of ≥150 min/week-and incidence of 697 diseases using Cox proportional hazards models adjusted for age, sex, body mass index, smoking, Townsend Deprivation Index, educational attainment, diet quality, alcohol use, blood pressure, anti-hypertensive use. We correct for multiplicity at a false discovery rate of 1%. We perform analogous testing using self-reported MVPA. Among 96,244 adults wearing accelerometers for one week (age 62 ± 8 years), MVPA is associated with 373 (54%) tested diseases over a median 6.3 years of follow-up. Greater MVPA is overwhelmingly associated with lower disease risk (98% of associations) with hazard ratios (HRs) ranging 0.70-0.98 per 150 min increase in weekly MVPA, and associations spanning all 16 disease categories tested. Overall, associations with lower disease risk are enriched for cardiac (16%), digestive (14%), endocrine/metabolic (10%), and respiratory conditions (8%) (chi-square p < 0.01). Similar patterns are observed using the guideline-based threshold of ≥150 MVPA min/week. Some of the strongest associations with guideline-adherent activity include lower risks of incident heart failure (HR 0.65, 95% CI 0.55-0.77), type 2 diabetes (HR 0.64, 95% CI 0.58-0.71), cholelithiasis (HR 0.61, 95% CI 0.54-0.70), and chronic bronchitis (HR 0.42, 95% CI 0.33-0.54). When assessed within 456,374 individuals providing self-reported MVPA, effect sizes for guideline-adherent activity are substantially smaller (e.g., heart failure HR 0.84, 95% CI 0.80-0.88). Greater wearable device-based physical activity is robustly associated with lower disease incidence. Future studies are warranted to identify potential mechanisms linking physical activity and disease, and assess whether optimization of measured activity can reduce disease risk.

Transcriptome variation in human tissues revealed by long-read sequencing.

Regulation of transcript structure generates transcript diversity and plays an important role in human disease1-7. The advent of long-read sequencing technologies offers the opportunity to study the role of genetic variation in transcript structure8-16. In this Article, we present a large human long-read RNA-seq dataset using the Oxford Nanopore Technologies platform from 88 samples from Genotype-Tissue Expression (GTEx) tissues and cell lines, complementing the GTEx resource. We identified just over 70,000 novel transcripts for annotated genes, and validated the protein expression of 10% of novel transcripts. We developed a new computational package, LORALS, to analyse the genetic effects of rare and common variants on the transcriptome by allele-specific analysis of long reads. We characterized allele-specific expression and transcript structure events, providing new insights into the specific transcript alterations caused by common and rare genetic variants and highlighting the resolution gained from long-read data. We were able to perturb the transcript structure upon knockdown of PTBP1, an RNA binding protein that mediates splicing, thereby finding genetic regulatory effects that are modified by the cellular environment. Finally, we used this dataset to enhance variant interpretation and study rare variants leading to aberrant splicing patterns.

Accounting for population structure in genetic studies of cystic fibrosis.

CFTR F508del (c.1521_1523delCTT, p.Phe508delPhe) is the most common pathogenic allele underlying cystic fibrosis (CF), and its frequency varies in a geographic cline across Europe. We hypothesized that genetic variation associated with this cline is overrepresented in a large cohort (N > 5,000) of persons with CF who underwent whole-genome sequencing and that this pattern could result in spurious associations between variants correlated with both the F508del genotype and CF-related outcomes. Using principal-component (PC) analyses, we showed that variation in the CFTR region disproportionately contributes to a PC explaining a relatively high proportion of genetic variance. Variation near CFTR was correlated with population structure among persons with CF, and this correlation was driven by a subset of the sample inferred to have European ancestry. We performed genome-wide association studies comparing persons with CF with one versus two copies of the F508del allele; this allowed us to identify genetic variation associated with the F508del allele and to determine that standard PC-adjustment strategies eliminated the significant association signals. Our results suggest that PC adjustment can adequately prevent spurious associations between genetic variants and CF-related traits and are therefore effective tools to control for population structure even when population structure is confounded with disease severity and a common pathogenic variant.

Association of the Interaction Between Familial Hypercholesterolemia Variants and Adherence to a Healthy Lifestyle With Risk of Coronary Artery Disease.

Importance: Familial hypercholesterolemia variants impair clearance of cholesterol from the circulation and increase risk of coronary artery disease (CAD). The extent to which adherence to a healthy lifestyle is associated with a lower risk of CAD in carriers and noncarriers of variants warrants further study. Objective: To assess the association of the interaction between familial hypercholesterolemia variants and adherence to a healthy lifestyle with risk of CAD. Design, Setting, and Participants: This cross-sectional study used 2 independent data sets with gene sequencing and lifestyle data from the UK Biobank: a case-control study of 4896 cases and 5279 controls and a cohort study of 39 920 participants. Participants were recruited from 22 sites across the UK between March 21, 2006, and October 1, 2010. The case-control study included participants with CAD and controls at enrollment. The cohort study used a convenience sample of individuals with available gene sequencing data. Statistical analysis was performed from April 2, 2019, to January 20, 2022. Exposures: Pathogenic or likely pathogenic DNA variants classified by a clinical laboratory geneticist and adherence to a healthy lifestyle based on a 4-point scoring system (1 point for each of the following: healthy diet, regular exercise, not smoking, and absence of obesity). Main Outcomes and Measures: Coronary artery disease, defined as myocardial infarction in the case-control study, and myocardial infarction, ischemic heart disease, or coronary revascularization procedure in the cohort study. Results: The case-control study included 10 175 participants (6828 men [67.1%]; mean [SD] age, 58.6 [7.2] years), and the cohort study included 39 920 participants (18 802 men [47.1%]; mean [SD] age at the end of follow-up, 66.4 [8.0] years). A variant was identified in 35 of 4896 cases (0.7%) and 12 of 5279 controls (0.2%), corresponding to an odds ratio of 3.0 (95% CI, 1.6-5.9), and a variant was identified in 108 individuals (0.3%) in the cohort study, in which the hazard ratio for CAD was 3.8 (95% CI, 2.5-5.8). However, this risk appeared to vary according to lifestyle categories in both carriers and noncarriers of familial hypercholesterolemia variants, without a significant interaction between carrier status and lifestyle (odds ratio, 1.2 [95% CI, 0.6-2.5]; P = .62). Among carriers, a favorable lifestyle conferred 86% lower risk of CAD compared with an unfavorable lifestyle (hazard ratio, 0.14 [95% CI, 0.04-0.41]). The estimated risk of CAD by the age of 75 years varied according to lifestyle, ranging from 10.2% among noncarriers with a favorable lifestyle to 24.0% among noncarriers with an unfavorable lifestyle and ranging from 34.5% among carriers with a favorable lifestyle to 66.2% among carriers with an unfavorable lifestyle. Conclusions and Relevance: This study suggests that, among carriers and noncarriers of a familial hypercholesterolemia variant, significant gradients in risk of CAD are noted according to adherence to a healthy lifestyle pattern. Similar to the general population, individuals who carry familial hypercholesterolemia variants are likely to benefit from lifestyle interventions to reduce their risk of CAD.

TAILS Identifies Candidate Substrates and Biomarkers of ADAMTS7, a Therapeutic Protease Target in Coronary Artery Disease.

Loss-of-function mutations in the secreted enzyme ADAMTS7 (a disintegrin and metalloproteinase with thrombospondin motifs 7) are associated with protection for coronary artery disease. ADAMTS7 catalytic inhibition has been proposed as a therapeutic strategy for treating coronary artery disease; however, the lack of an endogenous substrate has hindered the development of activity-based biomarkers. To identify ADAMTS7 extracellular substrates and their cleavage sites relevant to vascular disease, we used TAILS (terminal amine isotopic labeling of substrates), a method for identifying protease-generated neo-N termini. We compared the secreted proteome of vascular smooth muscle and endothelial cells expressing either full-length mouse ADAMTS7 WT, catalytic mutant ADAMTS7 E373Q, or a control luciferase adenovirus. Significantly enriched N-terminal cleavage sites in ADAMTS7 WT samples were compared to the negative control conditions and filtered for stringency, resulting in catalogs of high confidence candidate ADAMTS7 cleavage sites from our three independent TAILS experiments. Within the overlap of these discovery sets, we identified 24 unique cleavage sites from 16 protein substrates, including cleavage sites in EFEMP1 (EGF-containing fibulin-like extracellular matrix protein 1/Fibulin-3). The ADAMTS7 TAILS preference for EFEMP1 cleavage at the amino acids 123.124 over the adjacent 124.125 site was validated using both endogenous EFEMP1 and purified EFEMP1 in a binary in vitro cleavage assay. Collectively, our TAILS discovery experiments have uncovered hundreds of potential substrates and cleavage sites to explore disease-related biological substrates and facilitate activity-based ADAMTS7 biomarker development.

Screening for Atrial Fibrillation in Older Adults at Primary Care Visits: VITAL-AF Randomized Controlled Trial.

BACKGROUND: Undiagnosed atrial fibrillation (AF) may cause preventable strokes. Guidelines differ regarding AF screening recommendations. We tested whether point-of-care screening with a handheld single-lead ECG at primary care practice visits increases diagnoses of AF. METHODS: We randomized 16 primary care clinics 1:1 to AF screening using a handheld single-lead ECG (AliveCor KardiaMobile) during vital sign assessments, or usual care. Patients included were ages ≥65 years. Screening results were provided to primary care clinicians at the encounter. All confirmatory diagnostic testing and treatment decisions were made by the primary care clinician. New AF diagnoses during the 1-year follow-up were ascertained electronically and manually adjudicated. Proportions and incidence rates were calculated. Effect heterogeneity was assessed. RESULTS: Of 30 715 patients without prevalent AF (n=15 393 screening [91% screened], n=15 322 control), 1.72% of individuals in the screening group had new AF diagnosed at 1 year versus 1.59% in the control group (risk difference, 0.13% [95% CI, -0.16 to 0.42]; P=0.38). In prespecified subgroup analyses, new AF diagnoses in the screening and control groups were greater among those aged ≥85 years (5.56% versus 3.76%, respectively; risk difference, 1.80% [95% CI, 0.18 to 3.30]). The difference in newly diagnosed AF between the screening period and the previous year was marginally greater in the screening versus control group (0.32% versus -0.12%; risk difference, 0.43% [95% CI, -0.01 to 0.84]). The proportion of individuals with newly diagnosed AF who were initiated on oral anticoagulants was not different in the screening (n=194, 73.5%) and control (n=172, 70.8%) arms (risk difference, 2.7% [95% CI, -5.5 to 10.4]). CONCLUSIONS: Screening for AF using a single-lead ECG at primary care visits did not affect new AF diagnoses among all individuals aged 65 years or older compared with usual care. REGISTRATION: URL: https://www. CLINICALTRIALS: gov; Unique identifier: NCT03515057.

Deep Learning of the Retina Enables Phenome- and Genome-Wide Analyses of the Microvasculature.

BACKGROUND: The microvasculature, the smallest blood vessels in the body, has key roles in maintenance of organ health and tumorigenesis. The retinal fundus is a window for human in vivo noninvasive assessment of the microvasculature. Large-scale complementary machine learning-based assessment of the retinal vasculature with phenome-wide and genome-wide analyses may yield new insights into human health and disease. METHODS: We used 97 895 retinal fundus images from 54 813 UK Biobank participants. Using convolutional neural networks to segment the retinal microvasculature, we calculated vascular density and fractal dimension as a measure of vascular branching complexity. We associated these indices with 1866 incident International Classification of Diseases-based conditions (median 10-year follow-up) and 88 quantitative traits, adjusting for age, sex, smoking status, and ethnicity. RESULTS: Low retinal vascular fractal dimension and density were significantly associated with higher risks for incident mortality, hypertension, congestive heart failure, renal failure, type 2 diabetes, sleep apnea, anemia, and multiple ocular conditions, as well as corresponding quantitative traits. Genome-wide association of vascular fractal dimension and density identified 7 and 13 novel loci, respectively, that were enriched for pathways linked to angiogenesis (eg, vascular endothelial growth factor, platelet-derived growth factor receptor, angiopoietin, and WNT signaling pathways) and inflammation (eg, interleukin, cytokine signaling). CONCLUSIONS: Our results indicate that the retinal vasculature may serve as a biomarker for future cardiometabolic and ocular disease and provide insights into genes and biological pathways influencing microvascular indices. Moreover, such a framework highlights how deep learning of images can quantify an interpretable phenotype for integration with electronic health record, biomarker, and genetic data to inform risk prediction and risk modification.

Endothelial ARHGEF26 is an angiogenic factor promoting VEGF signalling.

AIMS: Genetic studies have implicated the ARHGEF26 locus in the risk of coronary artery disease (CAD). However, the causal pathways by which DNA variants at the ARHGEF26 locus confer risk for CAD are incompletely understood. We sought to elucidate the mechanism responsible for the enhanced risk of CAD associated with the ARHGEF26 locus. METHODS AND RESULTS: In a conditional analysis of the ARHGEF26 locus, we show that the sentinel CAD-risk signal is significantly associated with various non-lipid vascular phenotypes. In human endothelial cell (EC), ARHGEF26 promotes the angiogenic capacity, and interacts with known angiogenic factors and pathways. Quantitative mass spectrometry showed that one CAD-risk coding variant, rs12493885 (p.Val29Leu), resulted in a gain-of-function ARHGEF26 that enhances proangiogenic signalling and displays enhanced interactions with several proteins partially related to the angiogenic pathway. ARHGEF26 is required for endothelial angiogenesis by promoting macropinocytosis of Vascular Endothelial Growth Factor Receptor 2 (VEGFR2) on cell membrane and is crucial to Vascular Endothelial Growth Factor (VEGF)-dependent murine vessel sprouting ex vivo. In vivo, global or tissue-specific deletion of ARHGEF26 in EC, but not in vascular smooth muscle cells, significantly reduced atherosclerosis in mice, with enhanced plaque stability. CONCLUSIONS: Our results demonstrate that ARHGEF26 is involved in angiogenesis signaling, and that DNA variants within ARHGEF26 that are associated with CAD risk could affect angiogenic processes by potentiating VEGF-dependent angiogenesis.

Epigenetic Age and the Risk of Incident Atrial Fibrillation.

BACKGROUND: The most prominent risk factor for atrial fibrillation (AF) is chronological age; however, underlying mechanisms are unexplained. Algorithms using epigenetic modifications to the human genome effectively predict chronological age. Chronological and epigenetic predicted ages may diverge in a phenomenon referred to as epigenetic age acceleration (EAA), which may reflect accelerated biological aging. We sought to evaluate for associations between epigenetic age measures and incident AF. METHODS: Measures for 4 epigenetic clocks (Horvath, Hannum, DNA methylation [DNAm] PhenoAge, and DNAm GrimAge) and an epigenetic predictor of PAI-1 (plasminogen activator inhibitor-1) levels (ie, DNAm PAI-1) were determined for study participants from 3 population-based cohort studies. Cox models evaluated for associations with incident AF and results were combined via random-effects meta-analyses. Two-sample summary-level Mendelian randomization analyses evaluated for associations between genetic instruments of the EAA measures and AF. RESULTS: Among 5600 participants (mean age, 65.5 years; female, 60.1%; Black, 50.7%), there were 905 incident AF cases during a mean follow-up of 12.9 years. Unadjusted analyses revealed all 4 epigenetic clocks and the DNAm PAI-1 predictor were associated with statistically significant higher hazards of incident AF, though the magnitudes of their point estimates were smaller relative to the associations observed for chronological age. The pooled EAA estimates for each epigenetic measure, with the exception of Horvath EAA, were associated with incident AF in models adjusted for chronological age, race, sex, and smoking variables. After multivariable adjustment for additional known AF risk factors that could also potentially function as mediators, pooled EAA measures for 2 clocks remained statistically significant. Five-year increases in EAA measures for DNAm GrimAge and DNAm PhenoAge were associated with 19% (adjusted hazard ratio [HR], 1.19 [95% CI, 1.09-1.31]; P<0.01) and 15% (adjusted HR, 1.15 [95% CI, 1.05-1.25]; P<0.01) higher hazards of incident AF, respectively. Mendelian randomization analyses for the 5 EAA measures did not reveal statistically significant associations with AF. CONCLUSIONS: Our study identified adjusted associations between EAA measures and incident AF, suggesting that biological aging plays an important role independent of chronological age, though a potential underlying causal relationship remains unclear. These aging processes may be modifiable and not constrained by the immutable factor of time.

Comparative Clinical Effectiveness of Population-Based Atrial Fibrillation Screening Using Contemporary Modalities: A Decision-Analytic Model.

Background Atrial fibrillation (AF) screening is endorsed by certain guidelines for individuals aged ≥65 years. Yet many AF screening strategies exist, including the use of wrist-worn wearable devices, and their comparative effectiveness is not well-understood. Methods and Results We developed a decision-analytic model simulating 50 million individuals with an age, sex, and comorbidity profile matching the United States population aged ≥65 years (ie, with a guideline-based AF screening indication). We modeled no screening, in addition to 45 distinct AF screening strategies (comprising different modalities and screening intervals), each initiated at a clinical encounter. The primary effectiveness measure was quality-adjusted life-years, with incident stroke and major bleeding as secondary measures. We defined continuous or nearly continuous modalities as those capable of monitoring beyond a single time-point (eg, patch monitor), and discrete modalities as those capable of only instantaneous AF detection (eg, 12-lead ECG). In total, 10 AF screening strategies were effective compared with no screening (300-1500 quality-adjusted life-years gained/100 000 individuals screened). Nine (90%) effective strategies involved use of a continuous or nearly continuous modality such as patch monitor or wrist-worn wearable device, whereas 1 (10%) relied on discrete modalities alone. Effective strategies reduced stroke incidence (number needed to screen to prevent a stroke: 3087-4445) but increased major bleeding (number needed to screen to cause a major bleed: 1815-4049) and intracranial hemorrhage (number needed to screen to cause intracranial hemorrhage: 7693-16 950). The test specificity was a highly influential model parameter on screening effectiveness. Conclusions When modeled from a clinician-directed perspective, the comparative effectiveness of population-based AF screening varies substantially upon the specific strategy used. Future screening interventions and guidelines should consider the relative effectiveness of specific AF screening strategies.