User-centered development of an mHealth app for cardiovascular prevention.

Background: Mobile health (mHealth) apps can be used for cardiovascular disease (CVD) prevention. User-centered design, evidence-based content and user testing can be applied to ensure a high level of usability and adequate app access. Objective: To develop and evaluate an mHealth app (HerzFit) for CVD prevention. Methods: HerzFit´s development included a user-centered design approach and guideline-based content creation based on the identified requirements of the target group. Beta testing and a preliminary usability evaluation of the HerzFit prototype were performed. For evaluation, German versions of the System Usability Scale (SUS) and the mHealth App Usability Questionnaire (GER-MAUQ) as well as free text feedback were applied. Results: User-centered design thinking led to the definition of four personas. Based on their requirements, HerzFit enables users to individually assess, monitor, and optimize their cardiovascular risk profile. Users are also provided with a variety of evidence-based information on CVD and their risk factors. The user interface and system design followed the identified functional requirements. Beta-testers provided feedback on the structure and functionality and rated the usability of HerzFit´s prototype as slightly above average both in SUS and GER-MAUQ rating. Participants positively noted the variety of functions and information presented in HerzFit, while negative feedback mostly concerned wearable synchronization. Conclusions: The present study demonstrates the user-centered development of a guideline-based mHealth app for CVD prevention. Beta-testing and a preliminary usability study were used to further improve the HerzFit app until its official release.

Reticulated Platelets Predict Cardiovascular Death and Adverse Events in Coronary Artery Disease: A Systematic Review and Meta-analysis.

BACKGROUND: The pro-thrombotic immature or reticulated platelets (RPs) are known to be elevated in high-risk patients and in different pathological settings. It has been shown that RPs correlate with an insufficient antiplatelet response to antiplatelet agents. RPs are emerging novel predictors of adverse cardiovascular events in cardiovascular disease. This study, using the totality of existing evidence, evaluated the prognostic role of RPs in patients with coronary artery disease. METHODS: We performed a systematic review and meta-analysis including trials of acute and chronic coronary syndrome reporting clinical outcomes according to RPs levels in the peripheral blood. We compared patients with elevated RPs (RPshigh) to patients without elevated RPs (RPslow). Odds ratios (ORs) and 95% CIs were used as metric of choice for treatment effects with random-effects models. The primary endpoint was major adverse cardiovascular and cerebrovascular events (MACCE). Secondary endpoints were cardiovascular death, myocardial infarction, ischemic stroke, urgent coronary revascularization and bleedings. RESULTS: A total of 7 studies, including 2213 patients, were included. The risk for MACCE was significantly higher in RPshigh compared to RPslow patients (OR 2.67 [1.87; 3.81], I2 = 43.8%). RPshigh were associated with cardiovascular death (OR 2.09 [1.36; 3.22], I2 = 40.4%). No associations for RPshigh were detected with the other singular components of MACCE: myocardial infarction (OR 1.73 [0.89; 3.38] I2 = 60.5%) and stroke (OR 1.72 [0.59; 4.96] I2 = 21%). The risk of bleeding did not differ between groups(OR 0.58 [0.15; 2.22] I2 = 86.1%). CONCLUSION: Elevated RPs are significantly associated with increased risk of cardiovascular events and cardiovascular death.

Unique 40-year survival after heart transplantation with normal graft function and spontaneous operational tolerance.

Unique 40-year survival after heart transplantation with normal graft function and spontaneous operational tolerance.

Guideline-Based Cardiovascular Risk Assessment Delivered by an mHealth App: Development Study.

BACKGROUND: Identifying high-risk individuals is crucial for preventing cardiovascular diseases (CVDs). Currently, risk assessment is mostly performed by physicians. Mobile health apps could help decouple the determination of risk from medical resources by allowing unrestricted self-assessment. The respective test results need to be interpretable for laypersons. OBJECTIVE: Together with a patient organization, we aimed to design a digital risk calculator that allows people to individually assess and optimize their CVD risk. The risk calculator was integrated into the mobile health app HerzFit, which provides the respective background information. METHODS: To cover a broad spectrum of individuals for both primary and secondary prevention, we integrated the respective scores (Framingham 10-year CVD, Systematic Coronary Risk Evaluation 2, Systematic Coronary Risk Evaluation 2 in Older Persons, and Secondary Manifestations Of Arterial Disease) into a single risk calculator that was recalibrated for the German population. In primary prevention, an individual's heart age is estimated, which gives the user an easy-to-understand metric for assessing cardiac health. For secondary prevention, the risk of recurrence was assessed. In addition, a comparison of expected to mean and optimal risk levels was determined. The risk calculator is available free of charge. Data safety is ensured by processing the data locally on the users' smartphones. RESULTS: Offering a risk calculator to the general population requires the use of multiple instruments, as each provides only a limited spectrum in terms of age and risk distribution. The integration of 4 internationally recommended scores allows risk calculation in individuals aged 30 to 90 years with and without CVD. Such integration requires recalibration and harmonization to provide consistent and plausible estimates. In the first 14 months after the launch, the HerzFit calculator was downloaded more than 96,000 times, indicating great demand. Public information campaigns proved effective in publicizing the risk calculator and contributed significantly to download numbers. CONCLUSIONS: The HerzFit calculator provides CVD risk assessment for the general population. The public demonstrated great demand for such a risk calculator as it was downloaded up to 10,000 times per month, depending on campaigns creating awareness for the instrument.

ADAMTS-7 Modulates Atherosclerotic Plaque Formation by Degradation of TIMP-1.

BACKGROUND: The ADAMTS7 locus was genome-wide significantly associated with coronary artery disease. Lack of the ECM (extracellular matrix) protease ADAMTS-7 (A disintegrin and metalloproteinase-7) was shown to reduce atherosclerotic plaque formation. Here, we sought to identify molecular mechanisms and downstream targets of ADAMTS-7 mediating the risk of atherosclerosis. METHODS: Targets of ADAMTS-7 were identified by high-resolution mass spectrometry of atherosclerotic plaques from Apoe-/- and Apoe-/-Adamts7-/- mice. ECM proteins were identified using solubility profiling. Putative targets were validated using immunofluorescence, in vitro degradation assays, coimmunoprecipitation, and Förster resonance energy transfer-based protein-protein interaction assays. ADAMTS7 expression was measured in fibrous caps of human carotid artery plaques. RESULTS: In humans, ADAMTS7 expression was higher in caps of unstable as compared to stable carotid plaques. Compared to Apoe-/- mice, atherosclerotic aortas of Apoe-/- mice lacking Adamts-7 (Apoe-/-Adamts7-/-) contained higher protein levels of Timp-1 (tissue inhibitor of metalloprotease-1). In coimmunoprecipitation experiments, the catalytic domain of ADAMTS-7 bound to TIMP-1, which was degraded in the presence of ADAMTS-7 in vitro. ADAMTS-7 reduced the inhibitory capacity of TIMP-1 at its canonical target MMP-9 (matrix metalloprotease-9). As a downstream mechanism, we investigated collagen content in plaques of Apoe-/- and Apoe-/-Adamts7-/- mice after a Western diet. Picrosirius red staining of the aortic root revealed less collagen as a readout of higher MMP-9 activity in Apoe-/- as compared to Apoe-/- Adamts7-/- mice. To facilitate high-throughput screening for ADAMTS-7 inhibitors with the aim of decreasing TIMP-1 degradation, we designed a Förster resonance energy transfer-based assay targeting the ADAMTS-7 catalytic site. CONCLUSIONS: ADAMTS-7, which is induced in unstable atherosclerotic plaques, decreases TIMP-1 stability reducing its inhibitory effect on MMP-9, which is known to promote collagen degradation and is likewise associated with coronary artery disease. Disrupting the interaction of ADAMTS-7 and TIMP-1 might be a strategy to increase collagen content and plaque stability for the reduction of atherosclerosis-related events.

Leukocytes carrying Clonal Hematopoiesis of Indeterminate Potential (CHIP) Mutations invade Human Atherosclerotic Plaques.

Background: Leukocyte progenitors derived from clonal hematopoiesis of undetermined potential (CHIP) are associated with increased cardiovascular events. However, the prevalence and functional relevance of CHIP in coronary artery disease (CAD) are unclear, and cells affected by CHIP have not been detected in human atherosclerotic plaques. Methods: CHIP mutations in blood and tissues were identified by targeted deep-DNA-sequencing (DNAseq: coverage >3,000) and whole-genome-sequencing (WGS: coverage >35). CHIP-mutated leukocytes were visualized in human atherosclerotic plaques by mutaFISH™. Functional relevance of CHIP mutations was studied by RNAseq. Results: DNAseq of whole blood from 540 deceased CAD patients of the Munich cardIovaScular StudIes biObaNk (MISSION) identified 253 (46.9%) CHIP mutation carriers (mean age 78.3 years). DNAseq on myocardium, atherosclerotic coronary and carotid arteries detected identical CHIP mutations in 18 out of 25 mutation carriers in tissue DNA. MutaFISH™ visualized individual macrophages carrying DNMT3A CHIP mutations in human atherosclerotic plaques. Studying monocyte-derived macrophages from Stockholm-Tartu Atherosclerosis Reverse Networks Engineering Task (STARNET; n=941) by WGS revealed CHIP mutations in 14.2% (mean age 67.1 years). RNAseq of these macrophages revealed that expression patterns in CHIP mutation carriers differed substantially from those of non-carriers. Moreover, patterns were different depending on the underlying mutations, e.g. those carrying TET2 mutations predominantly displayed upregulated inflammatory signaling whereas ASXL1 mutations showed stronger effects on metabolic pathways. Conclusions: Deep-DNA-sequencing reveals a high prevalence of CHIP mutations in whole blood of CAD patients. CHIP-affected leukocytes invade plaques in human coronary arteries. RNAseq data obtained from macrophages of CHIP-affected patients suggest that pro-atherosclerotic signaling differs depending on the underlying mutations. Further studies are necessary to understand whether specific pathways affected by CHIP mutations may be targeted for personalized treatment.

P2Y12 Inhibitor or Aspirin Monotherapy for Secondary Prevention of Coronary Events.

BACKGROUND: Aspirin is the only antiplatelet agent with a Class I recommendation for long-term prevention of cardiovascular events in patients with coronary artery disease (CAD). There is inconsistent evidence on how it compares with alternative antiplatelet agents. OBJECTIVES: This study compared P2Y12 inhibitor monotherapy vs aspirin in patients with CAD. METHODS: We conducted a patient-level meta-analysis of randomized trials comparing P2Y12 inhibitor monotherapy vs aspirin monotherapy for the prevention of cardiovascular events in patients with established CAD. The primary outcome was the composite of cardiovascular death, myocardial infarction, and stroke. Prespecified key secondary outcomes were major bleeding and net adverse clinical events (the composite of the primary outcome and major bleeding). Data were pooled in a 1-step meta-analysis. RESULTS: Patient-level data were obtained from 7 trials. Overall, 24,325 participants were available for analysis, including 12,178 patients assigned to receive P2Y12 inhibitor monotherapy (clopidogrel in 7,545 [62.0%], ticagrelor in 4,633 [38.0%]) and 12,147 assigned to receive aspirin. Risk of the primary outcome was lower with P2Y12 inhibitor monotherapy compared with aspirin over 2 years (HR: 0.88; 95% CI: 0.79-0.97; P = 0.012), mainly owing to less myocardial infarction (HR: 0.77; 95% CI: 0.66-0.90; P < 0.001). Major bleeding was similar (HR: 0.87; 95% CI: 0.70-1.09; P = 0.23) and net adverse clinical events were lower (HR: 0.89; 95% CI: 0.81-0.98; P = 0.020) with P2Y12 inhibitors. The treatment effect was consistent across prespecified subgroups and types of P2Y12 inhibitors. CONCLUSIONS: Given its superior efficacy and similar overall safety, P2Y12 inhibitor monotherapy might be preferred over aspirin monotherapy for long-term secondary prevention in patients with established CAD. (P2Y12 Inhibitor or Aspirin Monotherapy as Secondary Prevention in Patients With Coronary Artery Disease: An Individual Patient Data Meta-Analysis of Randomized Trials [PANTHER collaborative initiative]; CRD42021290774).

Distinct genetic liability profiles define clinically relevant patient strata across common diseases.

Genome-wide association studies have unearthed a wealth of genetic associations across many complex diseases. However, translating these associations into biological mechanisms contributing to disease etiology and heterogeneity has been challenging. Here, we hypothesize that the effects of disease-associated genetic variants converge onto distinct cell type specific molecular pathways within distinct subgroups of patients. In order to test this hypothesis, we develop the CASTom-iGEx pipeline to operationalize individual level genotype data to interpret personal polygenic risk and identify the genetic basis of clinical heterogeneity. The paradigmatic application of this approach to coronary artery disease and schizophrenia reveals a convergence of disease associated variant effects onto known and novel genes, pathways, and biological processes. The biological process specific genetic liabilities are not equally distributed across patients. Instead, they defined genetically distinct groups of patients, characterized by different profiles across pathways, endophenotypes, and disease severity. These results provide further evidence for a genetic contribution to clinical heterogeneity and point to the existence of partially distinct pathomechanisms across patient subgroups. Thus, the universally applicable approach presented here has the potential to constitute an important component of future personalized medicine concepts.

Use of big data from health insurance for assessment of cardiovascular outcomes.

Outcome research that supports guideline recommendations for primary and secondary preventions largely depends on the data obtained from clinical trials or selected hospital populations. The exponentially growing amount of real-world medical data could enable fundamental improvements in cardiovascular disease (CVD) prediction, prevention, and care. In this review we summarize how data from health insurance claims (HIC) may improve our understanding of current health provision and identify challenges of patient care by implementing the perspective of patients (providing data and contributing to society), physicians (identifying at-risk patients, optimizing diagnosis and therapy), health insurers (preventive education and economic aspects), and policy makers (data-driven legislation). HIC data has the potential to inform relevant aspects of the healthcare systems. Although HIC data inherit limitations, large sample sizes and long-term follow-up provides enormous predictive power. Herein, we highlight the benefits and limitations of HIC data and provide examples from the cardiovascular field, i.e. how HIC data is supporting healthcare, focusing on the demographical and epidemiological differences, pharmacotherapy, healthcare utilization, cost-effectiveness and outcomes of different treatments. As an outlook we discuss the potential of using HIC-based big data and modern artificial intelligence (AI) algorithms to guide patient education and care, which could lead to the development of a learning healthcare system and support a medically relevant legislation in the future.

Machine Learning Identifies New Predictors on Restenosis Risk after Coronary Artery Stenting in 10,004 Patients with Surveillance Angiography.

OBJECTIVE: Machine learning (ML) approaches have the potential to uncover regular patterns in multi-layered data. Here we applied self-organizing maps (SOMs) to detect such patterns with the aim to better predict in-stent restenosis (ISR) at surveillance angiography 6 to 8 months after percutaneous coronary intervention with stenting. METHODS: In prospectively collected data from 10,004 patients receiving percutaneous coronary intervention (PCI) for 15,004 lesions, we applied SOMs to predict ISR angiographically 6-8 months after index procedure. SOM findings were compared with results of conventional uni- and multivariate analyses. The predictive value of both approaches was assessed after random splitting of patients into training and test sets (50:50). RESULTS: Conventional multivariate analyses revealed 10, mostly known, predictors for restenosis after coronary stenting: balloon-to-vessel ratio, complex lesion morphology, diabetes mellitus, left main stenting, stent type (bare metal vs. first vs. second generation drug eluting stent), stent length, stenosis severity, vessel size reduction, and prior bypass surgery. The SOM approach identified all these and nine further predictors, including chronic vessel occlusion, lesion length, and prior PCI. Moreover, the SOM-based model performed well in predicting ISR (AUC under ROC: 0.728); however, there was no meaningful advantage in predicting ISR at surveillance angiography in comparison with the conventional multivariable model (0.726, p = 0.3). CONCLUSIONS: The agnostic SOM-based approach identified-without clinical knowledge-even more contributors to restenosis risk. In fact, SOMs applied to a large prospectively sampled cohort identified several novel predictors of restenosis after PCI. However, as compared with established covariates, ML technologies did not improve identification of patients at high risk for restenosis after PCI in a clinically relevant fashion.

Machine learning identifies pathophysiologically and prognostically informative phenotypes among patients with mitral regurgitation undergoing transcatheter edge-to-edge repair.

AIMS: Patients with mitral regurgitation (MR) present with considerable heterogeneity in cardiac damage depending on underlying aetiology, disease progression, and comorbidities. This study aims to capture their cardiopulmonary complexity by employing a machine-learning (ML)-based phenotyping approach. METHODS AND RESULTS: Data were obtained from 1426 patients undergoing mitral valve transcatheter edge-to-edge repair (MV TEER) for MR. The ML model was developed using 609 patients (derivation cohort) and validated on 817 patients from two external institutions. Phenotyping was based on echocardiographic data, and ML-derived phenotypes were correlated with 5-year outcomes. Unsupervised agglomerative clustering revealed four phenotypes among the derivation cohort: Cluster 1 showed preserved left ventricular ejection fraction (LVEF; 56.5 ± 7.79%) and regular left ventricular end-systolic diameter (LVESD; 35.2 ± 7.52 mm); 5-year survival in Cluster 1, hereinafter serving as a reference, was 60.9%. Cluster 2 presented with preserved LVEF (55.7 ± 7.82%) but showed the largest mitral valve effective regurgitant orifice area (0.623 ± 0.360 cm2) and highest systolic pulmonary artery pressures (68.4 ± 16.2 mmHg); 5-year survival ranged at 43.7% (P-value: 0.032). Cluster 3 was characterized by impaired LVEF (31.0 ± 10.4%) and enlarged LVESD (53.2 ± 10.9 mm); 5-year survival was reduced to 38.3% (P-value: <0.001). The poorest 5-year survival (23.8%; P-value: <0.001) was observed in Cluster 4 with biatrial dilatation (left atrial volume: 312 ± 113 mL; right atrial area: 46.0 ± 8.83 cm2) although LVEF was only slightly reduced (51.5 ± 11.0%). Importantly, the prognostic significance of ML-derived phenotypes was externally confirmed. CONCLUSION: ML-enabled phenotyping captures the complexity of extra-mitral valve cardiac damage, which does not necessarily occur in a sequential fashion. This novel phenotyping approach can refine risk stratification in patients undergoing MV TEER in the future.

Sex differences among patients receiving ticagrelor monotherapy or aspirin after coronary bypass surgery: A prespecified subgroup analysis of the TiCAB trial.

BACKGROUND: There is limited evidence on the association of sex with outcomes among patients undergoing coronary bypass surgery (CABG) and treated with ticagrelor monotherapy or aspirin. METHODS: This was a pre-specified sub-analysis of TiCAB, an investigator-initiated placebo-controlled randomized trial. Primary efficacy endpoint was the composite of cardiovascular death, myocardial infarction, stroke, or repeat revascularization 1 year after CABG. Safety endpoint was BARC type 2, 3 or 5 bleeding. RESULTS: A total of 280 (15.0%) women and 1579 (85.0%) men were included. Compared with men, women were older (66.1 ± 10.2 vs. 70.1 ± 9.3 years) with more acute presentation (17.0% vs 21.1%). The incidence of the primary endpoint was similar between women and men (9.2% vs. 8.9%, HR 1.08, 95%CI 0.71-1.66, P = 0.71). Cardiovascular death occurred more often in women (2.9% vs 1.0%, adjusted HR 2.87, 95%CI 1.23-6.70, P = 0.02). The incidence of bleeding was similar between the sexes (2.2% vs. 2.5%, HR 0.91, 95% CI 0.51-1.65, P = 0.77). Ticagrelor vs aspirin was associated with a similar risk of the primary endpoint in women (10.6% vs. 7.9%, HR 1.39, 95%CI 0.63-3.05, P = 0.42) and men (9.5% vs. 8.2%, HR 1.15, 95%CI 0.82-1.62, P = 0.41;pinteraction = 0.69), and a similar risk of bleeding in women (2.9% vs. 1.4%, HR 2.09, 95%CI 0.38-11.41, P = 0.40) and men (2.2% vs. 2.8%, HR 0.80, 95%CI 0.42-1.52, P = 0.49;pinteraction = 0.35). CONCLUSIONS: Among women and men undergoing CABG, ticagrelor monotherapy was associated with a similar risk of the primary efficacy endpoint and bleeding compared with aspirin. The risk of cardiovascular death was increased in women irrespective of antiplatelet therapy.

Elucidation of the genetic causes of bicuspid aortic valve disease.

AIMS: The present study aims to characterize the genetic risk architecture of bicuspid aortic valve (BAV) disease, the most common congenital heart defect. METHODS AND RESULTS: We carried out a genome-wide association study (GWAS) including 2236 BAV patients and 11 604 controls. This led to the identification of a new risk locus for BAV on chromosome 3q29. The single nucleotide polymorphism rs2550262 was genome-wide significant BAV associated (P = 3.49 × 10-08) and was replicated in an independent case-control sample. The risk locus encodes a deleterious missense variant in MUC4 (p.Ala4821Ser), a gene that is involved in epithelial-to-mesenchymal transformation. Mechanistical studies in zebrafish revealed that loss of Muc4 led to a delay in cardiac valvular development suggesting that loss of MUC4 may also play a role in aortic valve malformation. The GWAS also confirmed previously reported BAV risk loci at PALMD (P = 3.97 × 10-16), GATA4 (P = 1.61 × 10-09), and TEX41 (P = 7.68 × 10-04). In addition, the genetic BAV architecture was examined beyond the single-marker level revealing that a substantial fraction of BAV heritability is polygenic and ∼20% of the observed heritability can be explained by our GWAS data. Furthermore, we used the largest human single-cell atlas for foetal gene expression and show that the transcriptome profile in endothelial cells is a major source contributing to BAV pathology. CONCLUSION: Our study provides a deeper understanding of the genetic risk architecture of BAV formation on the single marker and polygenic level.

Immature Platelet Fraction Predicts Adverse Events in Patients With Acute Coronary Syndrome: the ISAR-REACT 5 Reticulated Platelet Substudy.

BACKGROUND: Immature or reticulated platelets are associated with impaired efficacy of antiplatelet drugs and adverse events in cardiovascular patients. Their role as a predictive biomarker in patients with acute coronary syndrome treated with potent P2Y12 receptor inhibitors is not fully understood. We aimed to prospectively evaluate reticulated platelets as a predictor of the primary end point of the ISAR-REACT 5 trial consisting of death, myocardial infarction, or stroke at 1 year in patients with acute coronary syndrome randomized to prasugrel or ticagrelor. METHODS: Immature platelet fraction (IPF) was assessed within 48 hours after randomization. Patients were divided based on the IPF median values: the IPFhigh group included patients with IPF>median and the IPFlow group included patients with IPF≤median. Platelet aggregation was assessed using the Multiplate Analyzer and was correlated to IPF. RESULTS: Five hundred seventy-seven patients were included in the study. IPF values in % (median [interquartile range]) within the first 48 hours did not differ between the two study groups: 3.6 (2.5-5.2)% in the prasugrel group and 3.6 (2.5-5.4)% in the ticagrelor group (P=0.882). The incidence of the primary end point was significantly higher in the IPFhigh (IPF>3.6%) group compared with the IPFlow (IPF≤3.6%) group: 13.0% versus 7.2% (HRadj, 1.74 [1.02-3.00]; P=0.044), independently from the assigned drug (Pint=0.159). No significant association between IPF and BARC 3 to 5 bleeding was observed. ADP-induced platelet aggregation correlated significantly with IPF in patients treated with prasugrel (r=0.22; P=0.005) while no correlation was detected in patients treated with ticagrelor (r=0.09; P=0.257). CONCLUSIONS: Independently from drug treatment, IPF was associated with the primary end point and therefore is a promising biomarker for the prediction of adverse cardiovascular events in patients with acute coronary syndrome treated with prasugrel or ticagrelor. REGISTRATION: https://www. CLINICALTRIALS: gov; Unique identifier: NCT01944800.

Discovery and systematic characterization of risk variants and genes for coronary artery disease in over a million participants.

The discovery of genetic loci associated with complex diseases has outpaced the elucidation of mechanisms of disease pathogenesis. Here we conducted a genome-wide association study (GWAS) for coronary artery disease (CAD) comprising 181,522 cases among 1,165,690 participants of predominantly European ancestry. We detected 241 associations, including 30 new loci. Cross-ancestry meta-analysis with a Japanese GWAS yielded 38 additional new loci. We prioritized likely causal variants using functionally informed fine-mapping, yielding 42 associations with less than five variants in the 95% credible set. Similarity-based clustering suggested roles for early developmental processes, cell cycle signaling and vascular cell migration and proliferation in the pathogenesis of CAD. We prioritized 220 candidate causal genes, combining eight complementary approaches, including 123 supported by three or more approaches. Using CRISPR-Cas9, we experimentally validated the effect of an enhancer in MYO9B, which appears to mediate CAD risk by regulating vascular cell motility. Our analysis identifies and systematically characterizes >250 risk loci for CAD to inform experimental interrogation of putative causal mechanisms for CAD.

Artificial intelligence-enabled phenotyping of patients with severe aortic stenosis: on the recovery of extra-aortic valve cardiac damage after transcatheter aortic valve replacement.

OBJECTIVE: A novel artificial intelligence-based phenotyping approach to stratify patients with severe aortic stenosis (AS) prior to transcatheter aortic valve replacement (TAVR) has been proposed, based on echocardiographic and haemodynamic data. This study aimed to analyse the recovery of extra-aortic valve cardiac damage in accordance with this novel stratification system following TAVR. METHODS: The proposed phenotyping approach was previously established employing data from 366 patients with severe AS from a bicentric registry. For this consecutive study, echocardiographic follow-up data, obtained on day 147±75.1 after TAVR, were available from 247 patients (67.5%). RESULTS: Correction of severe AS by TAVR significantly reduced the proportion of patients suffering from concurrent severe mitral regurgitation (from 9.29% to 3.64%, p value: 0.0015). Moreover, pulmonary artery pressures were ameliorated (estimated systolic pulmonary artery pressure: from 47.2±15.8 to 43.3±15.1 mm Hg, p value: 0.0079). However, right heart dysfunction as well as the proportion of patients with severe tricuspid regurgitation remained unchanged. Clusters with persistent right heart dysfunction ultimately displayed 2-year survival rates of 69.2% (95% CI 56.6% to 84.7%) and 74.6% (95% CI 65.9% to 84.4%), which were significantly lower compared with clusters with little or no persistent cardiopulmonary impairment (88.3% (95% CI 83.3% to 93.5%) and 85.5% (95% CI 77.1% to 94.8%)). CONCLUSIONS: This phenotyping approach preprocedurally identifies patients with severe AS, who will not recover from extra-aortic valve cardiac damage following TAVR and whose survival is therefore significantly reduced. Importantly, not the degree of pulmonary hypertension at initial presentation, but the irreversibility of right heart dysfunction determines prognosis.

Identification of the Transcription Factor ATF3 as a Direct and Indirect Regulator of the LDLR.

Coronary artery disease (CAD) is a complex, multifactorial disease caused, in particular, by inflammation and cholesterol metabolism. At the molecular level, the role of tissue-specific signaling pathways leading to CAD is still largely unexplored. This study relied on two main resources: (1) genes with impact on atherosclerosis/CAD, and (2) liver-specific transcriptome analyses from human and mouse studies. The transcription factor activating transcription factor 3 (ATF3) was identified as a key regulator of a liver network relevant to atherosclerosis and linked to inflammation and cholesterol metabolism. ATF3 was predicted to be a direct and indirect (via MAF BZIP Transcription Factor F (MAFF)) regulator of low-density lipoprotein receptor (LDLR). Chromatin immunoprecipitation DNA sequencing (ChIP-seq) data from human liver cells revealed an ATF3 binding motif in the promoter regions of MAFF and LDLR. siRNA knockdown of ATF3 in human Hep3B liver cells significantly upregulated LDLR expression (p < 0.01). Inflammation induced by lipopolysaccharide (LPS) stimulation resulted in significant upregulation of ATF3 (p < 0.01) and subsequent downregulation of LDLR (p < 0.001). Liver-specific expression data from human CAD patients undergoing coronary artery bypass grafting (CABG) surgery (STARNET) and mouse models (HMDP) confirmed the regulatory role of ATF3 in the homeostasis of cholesterol metabolism. This study suggests that ATF3 might be a promising treatment candidate for lowering LDL cholesterol and reducing cardiovascular risk.

Opportunities and Challenges in Understanding Atherosclerosis by Human Biospecimen Studies.

Over the last few years, new high-throughput biotechnologies and bioinformatic methods are revolutionizing our way of deep profiling tissue specimens at the molecular levels. These recent innovations provide opportunities to advance our understanding of atherosclerosis using human lesions aborted during autopsies and cardiac surgeries. Studies on human lesions have been focusing on understanding the relationship between molecules in the lesions with tissue morphology, genetic risk of atherosclerosis, and future adverse cardiovascular events. This review will highlight ways to utilize human atherosclerotic lesions in translational research by work from large cardiovascular biobanks to tissue registries. We will also discuss the opportunities and challenges of working with human atherosclerotic lesions in the era of next-generation sequencing.

Validation of the 30-Year Framingham Risk Score in a German Population-Based Cohort.

The Framingham Risk Score to predict 30-year risk (FRS30y) of cardiovascular disease (CVD) constitutes an important tool for long-term risk prediction. However, due to its complex statistical properties and the paucity of large population-based cohorts with appropriate data, validation of the FRS30y is lacking. A population-based cohort from Southern Germany (N = 3110, 1516 (48.7%) women) was followed up for a median time of 29.5 [18.7, 31.2] years. Discrimination and calibration were assessed for the original, recalibrated and refitted FRS30y version. During follow up, 620 incident CVD events (214 in women) occurred. The FRS30y showed adequate discrimination (original and recalibrated version: Area under the curve (AUC): 78.4 for women and 74.9 for men) but overestimated actual CVD risk (original version: discordance 45.4% for women and 37.3% for men, recalibrated version: 37.6% and 28.6%, respectively). Refitting showed substantial improvement in neither discrimination nor calibration. The performance of FRS30y is adequate for long-term CVD risk prediction and could serve as an important tool in risk communication, especially for younger audiences.