Personalized care in dilated cardiomyopathy: Rationale and study design of the activeDCM trial.

BACKGROUND: Dilated cardiomyopathy (DCM) is a leading cause of heart failure, particularly in younger individuals. Low physical strength is a global risk factor for cardiovascular mortality, and physical activity and a healthy lifestyle have been shown to improve outcomes in patients with heart failure. However, inappropriate exercise may increase the risk of arrhythmias in certain individuals with DCM. The determinants for predicting individual risks in this setting are poorly understood, and clinicians are hesitant to recommend sports for cardiomyopathy patients. The activeDCM trial aims to assess the safety and efficacy of a personalized exercise and activity programme for individuals with DCM. STUDY DESIGN: The activeDCM trial is a prospective, randomized, interventional trial with a 12 month follow-up. Three hundred patients, aged 18-75 years with DCM, left ventricular ejection fraction (LVEF) ≤ 50% and New York Heart Association (NYHA) classes I-III, will be enrolled. The intervention includes a personalized exercise and activity programme. The primary outcome is the increase in peak oxygen uptake (VO2max, mL/kg/min) from baseline to 12 months. Secondary endpoints include adherence to personalized activity programmes, freedom from clinically relevant arrhythmia, unplanned hospitalization for heart failure and changes in NYHA class, quality of life scores, 6 min walk distance, muscular strength, N-terminal pro-B-type natriuretic peptide (NT-proBNP) and high-sensitivity troponin T (hsTnT) levels and cardiac function. Advanced research questions include high-density phenome and omics analysis combined with digital biomarkers derived from Apple Watch devices. DISCUSSION: The activeDCM trial will provide valuable insights into the safety and efficacy of personalized exercise training in DCM patients, inform clinical practice and contribute to the development of heart failure management programmes. The study will generate data on the impact of exercise on various aspects of cardiovascular disease, including genetic, metabolic, phenotypic and longitudinal aspects, facilitating the development of future digital tools and strategies, including the incorporation of smart wearable devices.

Comparative Assessment of Percutaneous Left-Atrial Appendage Occlusion (LAAO) Devices-A Single Center Cohort Study.

BACKGROUND: Percutaneous left-atrial appendage closure (LAAC) is an established method for preventing strokes in patients with atrial fibrillation, offering an alternative to oral anticoagulation. Various occluder devices have been developed to cater to individual anatomical needs and ensure a safe and effective procedure. In this retrospective, monocentric cohort study, we compare different LAAO devices with respect to clinical outcomes, LAA sealing properties, and device-related complications. METHODS: We conducted a retrospective analysis of 270 patients who underwent percutaneous LAA closure in our center between 2009 and 2023. Patient data were extracted from medical records, including gender, age at implantation, indication, device type and size, laboratory values, LAA anatomy, periprocedural complications, ECG parameters, transthoracic and transesophageal echocardiography parameters (TTE and TEE), as well as medication at discharge. Moreover, fluoroscopy time and implantation duration, as well as post-implantation clinical events up to 1 year, were collected. Endpoints were bleeding events, recurrent stroke, thrombi on devices, and death. RESULTS: The implanted devices were the Watchman 2.5, Watchman FLX, Amplatzer Cardiac Plug (ACP), and Amulet. The procedural success rate was 95.7% (n = 265), with cactus anatomy posing the most challenges across all devices. The mean patient age was 75.5 ± 7.7 years, with 64.5% being male. The median CHA2DS2-VASc score was 4.8 ± 1.5 and the median HAS-BLED score was 3.8 ± 1.0. Indications for LAA closure included past bleeding events and elevated bleeding risk. Periprocedural complications were most commonly bleeding at the puncture site, particularly after ACP implantation (p = 0.014). Significant peridevice leaks (PDL) were observed in 21.4% of simple sealing mechanism devices versus 0% in double sealing mechanism devices (p = 0.004). Thrombi were detected on devices in six patients, with no subsequent ischemic stroke or thromboembolic event. Comparative analysis revealed no significant differences in the occurrence of stroke, transient ischemic attack (TIA), thromboembolic events, device-related thrombi, or mortality among different device types. A 62.3% relative risk reduction in thromboembolic events and 38.6% in major bleedings could be observed over 568.2 patient years. CONCLUSIONS: In summary, our study highlights the efficacy and safety of LAA closure using various occluder devices despite anatomical challenges. Our long-term follow-up findings support LAA closure as a promising option for stroke prevention in selected patient cohorts. Further research is needed to refine patient selection criteria and optimize outcomes in LAA closure procedures.

Human Genetics of Ebstein Anomaly.

Ebstein anomaly (EA) is a rare, congenital cardiac defect of the tricuspid valve with a birth prevalence between 0.5 and 1 in 20,000 [1]. It is characterized by displacement of the tricuspid valve toward the apex of the right ventricle (RV) and "atrialization" of the RV (Fig. 57.1) [2]. EA accounts for about 0.5% of all congenital heart diseases (CHD) [2]. Depending on severity of the defect and due to heterogeneity of the disease, patient's presentation varies from severe heart failure symptoms and arrhythmia in neonatal life to asymptomatic adults.

Prediction of diagnosis and diastolic filling pressure by AI-enhanced cardiac MRI: a modelling study of hospital data.

BACKGROUND: With increasing numbers of patients and novel drugs for distinct causes of systolic and diastolic heart failure, automated assessment of cardiac function is important. We aimed to provide a non-invasive method to predict diagnosis of patients undergoing cardiac MRI (cMRI) and to obtain left ventricular end-diastolic pressure (LVEDP). METHODS: For this modelling study, patients who had undergone cardiac catheterisation at University Hospital Heidelberg (Heidelberg, Germany) between July 15, 2004 and March 16, 2023, were identified, as were individual left ventricular pressure measurements. We used existing patient data from routine cardiac diagnostics. From this initial group, we extracted patients who had been diagnosed with ischaemic cardiomyopathy, dilated cardiomyopathy, hypertrophic cardiomyopathy, or amyloidosis, as well as control individuals with no structural phenotype. Data were pseudonymised and only processed within the university hospital's AI infrastructure. We used the data to build different models to predict either demographic (ie, AI-age and AI-sex), diagnostic (ie, AI-coronary artery disease and AI-cardiomyopathy [AI-CMP]), or functional parameters (ie, AI-LVEDP). We randomly divided our datasets via computer into training, validation, and test datasets. AI-CMP was not compared with other models, but was validated in a prospective setting. Benchmarking was also done. FINDINGS: 66 936 patients who had undergone cardiac catheterisation at University Hospital Heidelberg were identified, with more than 183 772 individual left ventricular pressure measurements. We extracted 4390 patients from this initial group, of whom 1131 (25·8%) had been diagnosed with ischaemic cardiomyopathy, 1064 (24·2%) had been diagnosed with dilated cardiomyopathy, 816 (18·6%) had been diagnosed with hypertrophic cardiomyopathy, 202 (4·6%) had been diagnosed with amyloidosis, and 1177 (26·7%) were control individuals with no structural phenotype. The core cohort only included patients with cardiac catherisation and cMRI within 30 days, and emergency cases were excluded. AI-sex was able to predict patient sex with areas under the receiver operating characteristic curves (AUCs) of 0·78 (95% CI 0·77-0·78) and AI-age was able to predict patient age with a mean absolute error of 7·86 years (7·77-7·95), with a Pearson correlation of 0·57 (95% CI 0·56-0·57). The AUCs for the classification tasks ranged between 0·82 (95% CI 0·79-0·84) for ischaemic cardiomyopathy and 0·92 (0·91-0·94) for hypertrophic cardiomyopathy. INTERPRETATION: Our AI models could be easily integrated into clinical practice and provide added value to the information content of cMRI, allowing for disease classification and prediction of diastolic function. FUNDING: Informatics for Life initiative of the Klaus-Tschira Foundation, German Center for Cardiovascular Research, eCardiology section of the German Cardiac Society, and AI Health Innovation Cluster Heidelberg.

Improving sudden cardiac death risk stratification in hypertrophic cardiomyopathy using established clinical variables and genetic information.

BACKGROUND AND AIMS: The cardiac societies of Europe and the United States have established different risk models for preventing sudden cardiac death (SCD) in hypertrophic cardiomyopathy (HCM). The aim of this study is to validate current SCD risk prediction methods in a German HCM cohort and to improve them by the addition of genotype information. METHODS: HCM patients without prior SCD or equivalent arrhythmic events ≥ 18 years of age were enrolled in an expert cardiomyopathy center in Germany. The primary endpoint was defined as SCD/-equivalent within 5 years of baseline evaluation. 5-year SCD-risk estimates and recommendations for ICD implantations, as defined by the ESC and AHA/ACC guidelines, were analyzed. Multivariate cox proportional hazards analyses were integrated with genetic findings as additive SCD risk. RESULTS: 283 patients were included and followed for in median 5.77 years (2.92; 8.85). A disease-causing variant was found in 138 (49%) patients. 14 (5%) patients reached the SCD endpoint (5-year incidence 4.9%). Kaplan-Meier survival analysis shows significantly lower overall SCD event-free survival for patients with an identified disease-causing variant (p < 0.05). The ESC HCM Risk-SCD model showed an area-under-the-curve (AUC) of 0.74 (95% CI 0.68-0.79; p < 0.0001) with a sensitivity of 0.29 (95% CI 0.08-0.58) and specificity of 0.83 (95% CI 0.78-0.88) for a risk estimate ≥ 6%/5-years. By comparison, the AHA/ACC HCM SCD risk stratification model showed an AUC of 0.70 (95% CI 0.65-0.76; p = 0.003) with a sensitivity of 0.93 (95% CI, 0.66-0.998) and specificity of 0.28 (95% CI 0.23-0.34) at the respective cut-off. The modified SCD Risk Score with genetic information yielded an AUC of 0.76 (95% CI 0.71-0.81; p < 0.0001) with a sensitivity of 0.86 (95% CI 0.57-0.98) and specificity of 0.69 (95% CI 0.63-0.74). The number-needed-to-treat (NNT) to prevent 1 SCD event by prophylactic ICD-implantation is 13 for the ESC model, 28 for AHA/ACC and 9 for the modified Genotype-model. CONCLUSION: This study confirms the performance of current risk models in clinical decision making. The integration of genetic findings into current SCD risk stratification methods seem feasible and can add in decision making, especially in borderline risk-groups. A subgroup of patients with high SCD risk remains unidentified by current risk scores.

Generation of an RBM20-mutation-associated left-ventricular non-compaction cardiomyopathy iPSC line (UMGi255-A) into a DCM genetic background to investigate monogenetic cardiomyopathies.

RBM20 mutations account for 3 % of genetic cardiomypathies and manifest with high penetrance and arrhythmogenic effects. Numerous mutations in the conserved RS domain have been described as causing dilated cardiomyopathy (DCM), whereas a particular mutation (p.R634L) drives development of a different cardiac phenotype: left-ventricular non-compaction cardiomyopathy. We generated a mutation-induced pluripotent stem cell (iPSC) line in which the RBM20-LVNC mutation p.R634L was introduced into a DCM patient line with rescued RBM20-p.R634W mutation. These DCM-634L-iPSC can be differentiated into functional cardiomyocytes to test whether this RBM20 mutation induces development of the LVNC phenotype within the genetic context of a DCM patient.

Indirect epigenetic testing identifies a diagnostic signature of cardiomyocyte DNA methylation in heart failure.

Precision-based molecular phenotyping of heart failure must overcome limited access to cardiac tissue. Although epigenetic alterations have been found to underlie pathological cardiac gene dysregulation, the clinical utility of myocardial epigenomics remains narrow owing to limited clinical access to tissue. Therefore, the current study determined whether patient plasma confers indirect phenotypic, transcriptional, and/or epigenetic alterations to ex vivo cardiomyocytes to mirror the failing human myocardium. Neonatal rat ventricular myocytes (NRVMs) and single-origin human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) and were treated with blood plasma samples from patients with dilated cardiomyopathy (DCM) and donor subjects lacking history of cardiovascular disease. Following plasma treatments, NRVMs and hiPSC-CMs underwent significant hypertrophy relative to non-failing controls, as determined via automated high-content screening. Array-based DNA methylation analysis of plasma-treated hiPSC-CMs and cardiac biopsies uncovered robust, and conserved, alterations in cardiac DNA methylation, from which 100 sites were validated using an independent cohort. Among the CpG sites identified, hypo-methylation of the ATG promoter was identified as a diagnostic marker of HF, wherein cg03800765 methylation (AUC = 0.986, P < 0.0001) was found to out-perform circulating NT-proBNP levels in differentiating heart failure. Taken together, these findings support a novel approach of indirect epigenetic testing in human HF.

Deep phenotyping of two preclinical mouse models and a cohort of RBM20 mutation carriers reveals no sex-dependent disease severity in RBM20 cardiomyopathy.

RBM20 cardiomyopathy is an arrhythmogenic form of dilated cardiomyopathy caused by mutations in the splicing factor RBM20. A recent study found a more severe phenotype in male patients with RBM20 cardiomyopathy patients than in female patients. Here, we aim to determine sex differences in an animal model of RBM20 cardiomyopathy and investigate potential underlying mechanisms. In addition, we aim to determine sex and gender differences in clinical parameters in a novel RBM20 cardiomyopathy patient cohort. We characterized an Rbm20 knockout (KO) mouse model, and show that splicing of key RBM20 targets, cardiac function, and arrhythmia susceptibility do not differ between sexes. Next, we performed deep phenotyping of these mice, and show that male and female Rbm20-KO mice possess transcriptomic and phosphoproteomic differences. Hypothesizing that these differences may influence the heart's ability to compensate for stress, we exposed Rbm20-KO mice to acute catecholaminergic stimulation and again found no functional differences. We also replicate the lack of functional differences in a mouse model with the Rbm20-R636Q mutation. Lastly, we present a patient cohort of 33 RBM20 cardiomyopathy patients and show that these patients do not possess sex and gender differences in disease severity. Current mouse models of RBM20 cardiomyopathy show more pronounced changes in gene expression and phosphorylation of cardiac proteins in male mice, but no sex differences in cardiac morphology and function. Moreover, other than reported before, male RBM20 cardiomyopathy patients do not present with worse cardiac function in a patient cohort from Germany and the Netherlands.NEW & NOTEWORTHY Optimal management of the cardiac disease is increasingly personalized, partly because of differences in outcomes between sexes. RBM20 cardiomyopathy has been described to be more severe in male patients, and this carries the risk that male patients are more scrutinized in the clinic than female patients. Our findings do not support this observation and suggest that treatment should not differ between male and female RBM20 cardiomyopathy patients, but instead should focus on the underlying disease mechanism.

NIMA-related kinase 9 regulates the phosphorylation of the essential myosin light chain in the heart.

To adapt to changing hemodynamic demands, regulatory mechanisms modulate actin-myosin-kinetics by calcium-dependent and -independent mechanisms. We investigate the posttranslational modification of human essential myosin light chain (ELC) and identify NIMA-related kinase 9 (NEK9) to interact with ELC. NEK9 is highly expressed in the heart and the interaction with ELC is calcium-dependent. Silencing of NEK9 results in blunting of calcium-dependent ELC-phosphorylation. CRISPR/Cas9-mediated disruption of NEK9 leads to cardiomyopathy in zebrafish. Binding to ELC is mediated via the protein kinase domain of NEK9. A causal relationship between NEK9 activity and ELC-phosphorylation is demonstrated by genetic sensitizing in-vivo. Finally, we observe significantly upregulated ELC-phosphorylation in dilated cardiomyopathy patients and provide a unique map of human ELC-phosphorylation-sites. In summary, NEK9-mediated ELC-phosphorylation is a calcium-dependent regulatory system mediating cardiac contraction and inotropy.

Genotype Complements the Phenotype: Identification of the Pathogenicity of an LMNA Splice Variant by Nanopore Long-Read Sequencing in a Large DCM Family.

Dilated cardiomyopathy (DCM) is a common cause of heart failure (HF) and is of familial origin in 20−40% of cases. Genetic testing by next-generation sequencing (NGS) has yielded a definite diagnosis in many cases; however, some remain elusive. In this study, we used a combination of NGS, human-induced pluripotent-stem-cell-derived cardiomyocytes (iPSC-CMs) and nanopore long-read sequencing to identify the causal variant in a multi-generational pedigree of DCM. A four-generation family with familial DCM was investigated. Next-generation sequencing (NGS) was performed on 22 family members. Skin biopsies from two affected family members were used to generate iPSCs, which were then differentiated into iPSC-CMs. Short-read RNA sequencing was used for the evaluation of the target gene expression, and long-read RNA nanopore sequencing was used to evaluate the relevance of the splice variants. The pedigree suggested a highly penetrant, autosomal dominant mode of inheritance. The phenotype of the family was suggestive of laminopathy, but previous genetic testing using both Sanger and panel sequencing only yielded conflicting evidence for LMNA p.R644C (rs142000963), which was not fully segregated. By re-sequencing four additional affected family members, further non-coding LMNA variants could be detected: rs149339264, rs199686967, rs201379016, and rs794728589. To explore the roles of these variants, iPSC-CMs were generated. RNA sequencing showed the LMNA expression levels to be significantly lower in the iPSC-CMs of the LMNA variant carriers. We demonstrated a dysregulated sarcomeric structure and altered calcium homeostasis in the iPSC-CMs of the LMNA variant carriers. Using targeted nanopore long-read sequencing, we revealed the biological significance of the variant c.356+1G>A, which generates a novel 5' splice site in exon 1 of the cardiac isomer of LMNA, causing a nonsense mRNA product with almost complete RNA decay and haploinsufficiency. Using novel molecular analysis and nanopore technology, we demonstrated the pathogenesis of the rs794728589 (c.356+1G>A) splice variant in LMNA. This study highlights the importance of precise diagnostics in the clinical management and workup of cardiomyopathies.

Multi-omics assessment of dilated cardiomyopathy using non-negative matrix factorization.

Dilated cardiomyopathy (DCM), a myocardial disease, is heterogeneous and often results in heart failure and sudden cardiac death. Unavailability of cardiac tissue has hindered the comprehensive exploration of gene regulatory networks and nodal players in DCM. In this study, we carried out integrated analysis of transcriptome and methylome data using non-negative matrix factorization from a cohort of DCM patients to uncover underlying latent factors and covarying features between whole-transcriptome and epigenome omics datasets from tissue biopsies of living patients. DNA methylation data from Infinium HM450 and mRNA Illumina sequencing of n = 33 DCM and n = 24 control probands were filtered, analyzed and used as input for matrix factorization using R NMF package. Mann-Whitney U test showed 4 out of 5 latent factors are significantly different between DCM and control probands (P<0.05). Characterization of top 10% features driving each latent factor showed a significant enrichment of biological processes known to be involved in DCM pathogenesis, including immune response (P = 3.97E-21), nucleic acid binding (P = 1.42E-18), extracellular matrix (P = 9.23E-14) and myofibrillar structure (P = 8.46E-12). Correlation network analysis revealed interaction of important sarcomeric genes like Nebulin, Tropomyosin alpha-3 and ERC-protein 2 with CpG methylation of ATPase Phospholipid Transporting 11A0, Solute Carrier Family 12 Member 7 and Leucine Rich Repeat Containing 14B, all with significant P values associated with correlation coefficients >0.7. Using matrix factorization, multi-omics data derived from human tissue samples can be integrated and novel interactions can be identified. Hypothesis generating nature of such analysis could help to better understand the pathophysiology of complex traits such as DCM.

VARS2 Depletion Leads to Activation of the Integrated Stress Response and Disruptions in Mitochondrial Fatty Acid Oxidation.

Mutations in mitochondrial aminoacyl-tRNA synthetases (mtARSs) have been reported in patients with mitochondriopathies: most commonly encephalopathy, but also cardiomyopathy. Through a GWAS, we showed possible associations between mitochondrial valyl-tRNA synthetase (VARS2) dysregulations and non-ischemic cardiomyopathy. We aimed to investigate the possible consequences of VARS2 depletion in zebrafish and cultured HEK293A cells. Transient VARS2 loss-of-function was induced in zebrafish embryos using Morpholinos. The enzymatic activity of VARS2 was measured in VARS2-depleted cells via northern blot. Heterozygous VARS2 knockout was established in HEK293A cells using CRISPR/Cas9 technology. BN-PAGE and SDS-PAGE were used to investigate electron transport chain (ETC) complexes, and the oxygen consumption rate and extracellular acidification rate were measured using a Seahorse XFe96 Analyzer. The activation of the integrated stress response (ISR) and possible disruptions in mitochondrial fatty acid oxidation (FAO) were explored using RT-qPCR and western blot. Zebrafish embryos with transient VARS2 loss-of-function showed features of heart failure as well as indications of CNS and skeletal muscle involvements. The enzymatic activity of VARS2 was significantly reduced in VARS2-depleted cells. Heterozygous VARS2-knockout cells showed a rearrangement of ETC complexes in favor of complexes III2, III2 + IV, and supercomplexes without significant respiratory chain deficiencies. These cells also showed the enhanced activation of the ISR, as indicated by increased eIF-2α phosphorylation and a significant increase in the transcript levels of ATF4, ATF5, and DDIT3 (CHOP), as well as disruptions in FAO. The activation of the ISR and disruptions in mitochondrial FAO may underlie the adaptive changes in VARS2-depleted cells.

Controlling my genome with my smartphone: first clinical experiences of the PROMISE system.

BACKGROUND: The development of Precision Medicine strategies requires high-dimensional phenotypic and genomic data, both of which are highly privacy-sensitive data types. Conventional data management systems lack the capabilities to sufficiently handle the expected large quantities of such sensitive data in a secure manner. PROMISE is a genetic data management concept that implements a highly secure platform for data exchange while preserving patient interests, privacy, and autonomy. METHODS: The concept of PROMISE to democratize genetic data was developed by an interdisciplinary team. It integrates a sophisticated cryptographic concept that allows only the patient to grant selective access to defined parts of his genetic information with single DNA base-pair resolution cryptography. The PROMISE system was developed for research purposes to evaluate the concept in a pilot study with nineteen cardiomyopathy patients undergoing genotyping, questionnaires, and longitudinal follow-up. RESULTS: The safety of genetic data was very important to 79%, and patients generally regarded the data as highly sensitive. More than half the patients reported that their attitude towards the handling of genetic data has changed after using the PROMISE app for 4 months (median). The patients reported higher confidence in data security and willingness to share their data with commercial third parties, including pharmaceutical companies (increase from 5 to 32%). CONCLUSION: PROMISE democratizes genomic data by a transparent, secure, and patient-centric approach. This clinical pilot study evaluating a genetic data infrastructure is unique and shows that patient's acceptance of data sharing can be increased by patient-centric decision-making.

Identification of SCN5a p.C335R Variant in a Large Family with Dilated Cardiomyopathy and Conduction Disease.

INTRODUCTION: Familial dilated cardiomyopathy (DCM) is clinically variable and has been associated with mutations in more than 50 genes. Rapid improvements in DNA sequencing have led to the identification of diverse rare variants with unknown significance (VUS), which underlines the importance of functional analyses. In this study, by investigating human-induced pluripotent stem cell-derived cardiomyocytes (iPSC-CMs), we evaluated the pathogenicity of the p.C335R sodium voltage-gated channel alpha subunit 5 (SCN5a) variant in a large family with familial DCM and conduction disease. METHODS: A four-generation family with autosomal dominant familial DCM was investigated. Next-generation sequencing (NGS) was performed in all 16 family members. Clinical deep phenotyping, including endomyocardial biopsy, was performed. Skin biopsies from two patients and one healthy family member were used to generate human-induced pluripotent stem cells (iPSCs), which were then differentiated into cardiomyocytes. Patch-clamp analysis with Xenopus oocytes and iPSC-CMs were performed. RESULTS: A SCN5a variant (c.1003T>C; p.C335R) could be detected in all family members with DCM or conduction disease. A novel truncating TTN variant (p.Ser24998LysfsTer28) could also be identified in two family members with DCM. Family members with the SCN5a variant (p.C335R) showed significantly longer PQ and QRS intervals and lower left ventricular ejection fractions (LV-EF). All four patients who received CRT-D were non-responders. Electrophysiological analysis with Xenopus oocytes showed a loss of function in SCN5a p.C335R. Na+ channel currents were also reduced in iPSC-CMs from DCM patients. Furthermore, iPSC-CM with compound heterozygosity (SCN5a p.C335R and TTNtv) showed significant dysregulation of sarcomere structures, which may be contributed to the severity of the disease and earlier onset of DCM. CONCLUSION: The SCN5a p.C335R variant is causing a loss of function of peak INa in patients with DCM and cardiac conduction disease. The co-existence of genetic variants in channels and structural genes (e.g., SCN5a p.C335R and TTNtv) increases the severity of the DCM phenotype.

A novel risk model for predicting potentially life-threatening arrhythmias in non-ischemic dilated cardiomyopathy (DCM-SVA risk).

BACKGROUND: Non-ischemic dilated cardiomyopathy (DCM) can be complicated by sustained ventricular arrhythmias (SVA) and sudden cardiac death (SCD). By now, left-ventricular ejection fraction (LV-EF) is the main guideline criterion for primary prophylactic ICD implantation, potentially leading either to overtreatment or failed detection of patients at risk without severely impaired LV-EF. The aim of the European multi-center study DETECTIN-HF was to establish a clinical risk calculator for individualized risk stratification of DCM patients. METHODS: 1393 patients (68% male, mean age 50.7 ± 14.3y) from four European countries were included. The outcome was occurrence of first potentially life-threatening ventricular arrhythmia. The model was developed using Cox proportional hazards, and internally validated using cross validation. The model included seven independent and easily accessible clinical parameters sex, history of non-sustained ventricular tachycardia, history of syncope, family history of cardiomyopathy, QRS duration, LV-EF, and history of atrial fibrillation. The model was also expanded to account for presence of LGE as the eight8h parameter for cases with available cMRI and scar information. RESULTS: During a mean follow-up period of 57.0 months, 193 (13.8%) patients experienced an arrhythmic event. The calibration slope of the developed model was 00.97 (95% CI 0.90-1.03) and the C-index was 0.72 (95% CI 0.71-0.73). Compared to current guidelines, the model was able to protect the same number of patients (5-year risk ≥8.5%) with 15% fewer ICD implantations. CONCLUSIONS: This DCM-SVA risk model could improve decision making in primary prevention of SCD in non-ischemic DCM using easily accessible clinical information and will likely reduce overtreatment.

Energy Metabolites as Biomarkers in Ischemic and Dilated Cardiomyopathy.

With more than 25 million people affected, heart failure (HF) is a global threat. As energy production pathways are known to play a pivotal role in HF, we sought here to identify key metabolic changes in ischemic- and non-ischemic HF by using a multi-OMICS approach. Serum metabolites and mRNAseq and epigenetic DNA methylation profiles were analyzed from blood and left ventricular heart biopsy specimens of the same individuals. In total we collected serum from n = 82 patients with Dilated Cardiomyopathy (DCM) and n = 51 controls in the screening stage. We identified several metabolites involved in glycolysis and citric acid cycle to be elevated up to 5.7-fold in DCM (p = 1.7 × 10-6). Interestingly, cardiac mRNA and epigenetic changes of genes encoding rate-limiting enzymes of these pathways could also be found and validated in our second stage of metabolite assessment in n = 52 DCM, n = 39 ischemic HF and n = 57 controls. In conclusion, we identified a new set of metabolomic biomarkers for HF. We were able to identify underlying biological cascades that potentially represent suitable intervention targets.

microRNA neural networks improve diagnosis of acute coronary syndrome (ACS).

BACKGROUND: Cardiac troponins are the preferred biomarkers of acute myocardial infarction. Despite superior sensitivity, serial testing of Troponins to identify patients suffering acute coronary syndromes is still required in many cases to overcome limited specificity. Moreover, unstable angina pectoris relies on reported symptoms in the troponin-negative group. In this study, we investigated genome-wide miRNA levels in a prospective cohort of patients with clinically suspected ACS and determined their diagnostic value by applying an in silico neural network. METHODS: PAXgene blood and serum samples were drawn and hsTnT was measured in patients at initial presentation to our Chest-Pain Unit. After clinical and diagnostic workup, patients were adjudicated by senior cardiologists in duty to their final diagnosis: STEMI, NSTEMI, unstable angina pectoris and non-ACS patients. ACS patients and a cohort of healthy controls underwent deep transcriptome sequencing. Machine learning was implemented to construct diagnostic miRNA classifiers. RESULTS: We developed a neural network model which incorporates 34 validated ACS miRNAs, showing excellent classification results. By further developing additional machine learning models and selecting the best miRNAs, we achieved an accuracy of 0.96 (95% CI 0.96-0.97), sensitivity of 0.95, specificity of 0.96 and AUC of 0.99. The one-point hsTnT value reached an accuracy of 0.89, sensitivity of 0.82, specificity of 0.96, and AUC of 0.96. CONCLUSIONS: Here we show the concept of neural network based biomarkers for ACS. This approach also opens the possibility to include multi-modal data points to further increase precision and perform classification of other ACS differential diagnoses.

Marathon-Induced Cardiac Strain as Model for the Evaluation of Diagnostic microRNAs for Acute Myocardial Infarction.

BACKGROUND: The current gold standard biomarker for myocardial infarction (MI), cardiac troponin (cTn), is recognized for its high sensitivity and organ specificity; however, it lacks diagnostic specificity. Numerous studies have introduced circulating microRNAs as potential biomarkers for MI. This study investigates the MI-specificity of these serum microRNAs by investigating myocardial stress/injury due to strenuous exercise. METHODS: MicroRNA biomarkers were retrieved by comprehensive review of 109 publications on diagnostic serum microRNAs for MI. MicroRNA levels were first measured by next-generation sequencing in pooled sera from runners (n = 46) before and after conducting a full competitive marathon. Hereafter, reverse transcription quantitative real-time PCR (qPCR) of 10 selected serum microRNAs in 210 marathon runners was performed (>10,000 qPCR measurements). RESULTS: 27 potential diagnostic microRNA for MI were retrieved by the literature review. Eight microRNAs (miR-1-3p, miR-21-5p, miR-26a-5p, miR-122-5p, miR-133a-3p, miR-142-5p, miR-191-5p, miR-486-3p) showed positive correlations with cTnT in marathon runners, whereas two miRNAs (miR-134-5p and miR-499a-5p) showed no correlations. Upregulation of miR-133a-3p (p = 0.03) and miR-142-5p (p = 0.01) went along with elevated cTnT after marathon. CONCLUSION: Some MI-associated microRNAs (e.g., miR-133a-3p and miR-142-5p) have similar kinetics under strenuous exercise and MI as compared to cTnT, which suggests that their diagnostic specificity could be limited. In contrast, several MI-associated microRNAs (miR-26a-5p, miR-134-5p, miR-191-5p) showed different release behavior; hence, combining cTnT with these microRNAs within a multi-marker strategy may add diagnostic accuracy in MI.

Generation of pluripotent stem cell lines and CRISPR/Cas9 modified isogenic controls from a patient with dilated cardiomyopathy harboring a RBM20 p.R634W mutation.

RNA binding motif protein 20 (RBM20) is an alternative splicing factor and highly expressed in cardiac tissue. Mutations in the RS domain of RBM20 have been shown to cause different cardiomyopathies. Here, we generated induced pluripotent stem cells (iPSCs) from a dilated cardiomyopathy patient harboring the heterozygous RBM20 mutation p.R634W and consecutively produced isogenic control line using CRISPR/Cas9 genome editing. Patient-specific RBM20 iPSCs and isogenic control line maintained full pluripotency, genomic integrity, and in vitro differentiation capacity. All iPSC-lines were able to differentiate into pure cardiomyocytes, thus providing a valuable tool for studying the pathogenesis of human RBM20-mediated cardiac disease.