The role of coronary artery disease in lung transplantation: a propensity-matched analysis.

BACKGROUND AND AIMS: Candidate selection for lung transplantation (LuTx) is pivotal to ensure individual patient benefit as well as optimal donor organ allocation. The impact of coronary artery disease (CAD) on post-transplant outcomes remains controversial. We provide comprehensive data on the relevance of CAD for short- and long-term outcomes following LuTx and identify risk factors for mortality. METHODS: We retrospectively analyzed all adult patients (≥ 18 years) undergoing primary and isolated LuTx between January 2000 and August 2021 at the LMU University Hospital transplant center. Using 1:1 propensity score matching, 98 corresponding pairs of LuTx patients with and without relevant CAD were identified. RESULTS: Among 1,003 patients having undergone LuTx, 104 (10.4%) had relevant CAD at baseline. There were no significant differences in in-hospital mortality (8.2% vs. 8.2%, p > 0.999) as well as overall survival (HR 0.90, 95%CI [0.61, 1.32], p = 0.800) between matched CAD and non-CAD patients. Similarly, cardiovascular events such as myocardial infarction (7.1% CAD vs. 2.0% non-CAD, p = 0.170), revascularization by percutaneous coronary intervention (5.1% vs. 1.0%, p = 0.212), and stroke (2.0% vs. 6.1%, p = 0.279), did not differ statistically between both matched groups. 7.1% in the CAD group and 2.0% in the non-CAD group (p = 0.078) died from cardiovascular causes. Cox regression analysis identified age at transplantation (HR 1.02, 95%CI [1.01, 1.04], p < 0.001), elevated bilirubin (HR 1.33, 95%CI [1.15, 1.54], p < 0.001), obstructive lung disease (HR 1.43, 95%CI [1.01, 2.02], p = 0.041), decreased forced vital capacity (HR 0.99, 95%CI [0.99, 1.00], p = 0.042), necessity of reoperation (HR 3.51, 95%CI [2.97, 4.14], p < 0.001) and early transplantation time (HR 0.97, 95%CI [0.95, 0.99], p = 0.001) as risk factors for all-cause mortality, but not relevant CAD (HR 0.96, 95%CI [0.71, 1.29], p = 0.788). Double lung transplant was associated with lower all-cause mortality (HR 0.65, 95%CI [0.52, 0.80], p < 0.001), but higher in-hospital mortality (OR 2.04, 95%CI [1.04, 4.01], p = 0.039). CONCLUSION: In this cohort, relevant CAD was not associated with worse outcomes and should therefore not be considered a contraindication for LuTx. Nonetheless, cardiovascular events in CAD patients highlight the necessity of control of cardiovascular risk factors and a structured cardiac follow-up.

A contemporary training concept in critical care cardiology.

Critical care cardiology (CCC) in the modern era is shaped by a multitude of innovative treatment options and an increasingly complex, ageing patient population. Generating high-quality evidence for novel interventions and devices in an intensive care setting is exceptionally challenging. As a result, formulating the best possible therapeutic approach continues to rely predominantly on expert opinion and local standard operating procedures. Fostering the full potential of CCC and the maturation of the next generation of decision-makers in this field calls for an updated training concept, that encompasses the extensive knowledge and skills required to care for critically ill cardiac patients while remaining adaptable to the trainee's individual career planning and existing educational programs. In the present manuscript, we suggest a standardized training phase in preparation of the first ICU rotation, propose a modular CCC core curriculum, and outline how training components could be conceptualized within three sub-specialization tracks for aspiring cardiac intensivists.

Scrutinizing the Role of Venoarterial Extracorporeal Membrane Oxygenation: Has Clinical Practice Outpaced the Evidence?

The use of venoarterial extracorporeal membrane oxygenation (VA-ECMO) for temporary mechanical circulatory support in various clinical scenarios has been increasing consistently, despite the lack of sufficient evidence regarding its benefit and safety from adequately powered randomized controlled trials. Although the ARREST trial (Advanced Reperfusion Strategies for Patients with Out-of-Hospital Cardiac Arrest and Refractory Ventricular Fibrillation) and a secondary analysis of the PRAGUE OHCA trial (Prague Out-of-Hospital Cardiac Arrest) provided some evidence in favor of VA-ECMO in the setting of out-of-hospital cardiac arrest, the INCEPTION trial (Early Initiation of Extracorporeal Life Support in Refractory Out-of-Hospital Cardiac Arrest) has not found a relevant improvement of short-term mortality with extracorporeal cardiopulmonary resuscitation. In addition, the results of the recently published ECLS-SHOCK trial (Extracorporeal Life Support in Cardiogenic Shock) and ECMO-CS trial (Extracorporeal Membrane Oxygenation in the Therapy of Cardiogenic Shock) discourage the routine use of VA-ECMO in patients with infarct-related cardiogenic shock. Ongoing clinical trials (ANCHOR [Assessment of ECMO in Acute Myocardial Infarction Cardiogenic Shock, NCT04184635], REVERSE [Impella CP With VA ECMO for Cardiogenic Shock, NCT03431467], UNLOAD ECMO [Left Ventricular Unloading to Improve Outcome in Cardiogenic Shock Patients on VA-ECMO, NCT05577195], PIONEER [Hemodynamic Support With ECMO and IABP in Elective Complex High-risk PCI, NCT04045873]) may clarify the usefulness of VA-ECMO in specific patient subpopulations and the efficacy of combined mechanical circulatory support strategies. Pending further data to refine patient selection and management recommendations for VA-ECMO, it remains uncertain whether the present usage of this device improves outcomes.

Genetic architecture of cardiac dynamic flow volumes.

Cardiac blood flow is a critical determinant of human health. However, the definition of its genetic architecture is limited by the technical challenge of capturing dynamic flow volumes from cardiac imaging at scale. We present DeepFlow, a deep-learning system to extract cardiac flow and volumes from phase-contrast cardiac magnetic resonance imaging. A mixed-linear model applied to 37,653 individuals from the UK Biobank reveals genome-wide significant associations across cardiac dynamic flow volumes spanning from aortic forward velocity to aortic regurgitation fraction. Mendelian randomization reveals a causal role for aortic root size in aortic valve regurgitation. Among the most significant contributing variants, localizing genes (near ELN, PRDM6 and ADAMTS7) are implicated in connective tissue and blood pressure pathways. Here we show that DeepFlow cardiac flow phenotyping at scale, combined with genotyping data, reinforces the contribution of connective tissue genes, blood pressure and root size to aortic valve function.

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.

The challenges of research data management in cardiovascular science: a DGK and DZHK position paper-executive summary.

The sharing and documentation of cardiovascular research data are essential for efficient use and reuse of data, thereby aiding scientific transparency, accelerating the progress of cardiovascular research and healthcare, and contributing to the reproducibility of research results. However, challenges remain. This position paper, written on behalf of and approved by the German Cardiac Society and German Centre for Cardiovascular Research, summarizes our current understanding of the challenges in cardiovascular research data management (RDM). These challenges include lack of time, awareness, incentives, and funding for implementing effective RDM; lack of standardization in RDM processes; a need to better identify meaningful and actionable data among the increasing volume and complexity of data being acquired; and a lack of understanding of the legal aspects of data sharing. While several tools exist to increase the degree to which data are findable, accessible, interoperable, and reusable (FAIR), more work is needed to lower the threshold for effective RDM not just in cardiovascular research but in all biomedical research, with data sharing and reuse being factored in at every stage of the scientific process. A culture of open science with FAIR research data should be fostered through education and training of early-career and established research professionals. Ultimately, FAIR RDM requires permanent, long-term effort at all levels. If outcomes can be shown to be superior and to promote better (and better value) science, modern RDM will make a positive difference to cardiovascular science and practice. The full position paper is available in the supplementary materials.

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.

Insulin resistance in Takotsubo syndrome.

AIMS: Takotsubo syndrome (TTS) is an acute heart failure (AHF) syndrome mimicking the symptoms of acute myocardial infarction. Impaired outcome has been shown, making risk stratification and novel therapeutic concepts a necessity. We hypothesized insulin resistance with elevated plasma glucose and potentially myocardial glucose deprivation to contribute to the pathogenesis of TTS and investigated the therapeutic benefit of insulin in vivo. METHODS AND RESULTS: First, we retrospectively analysed patient data of n = 265 TTS cases (85.7% female, mean age 71.1 ± 14.1 years) with documented initial plasma glucose from the Department of Cardiology of the University Hospital Heidelberg in Germany (May 2011 to May 2021). Median split of the study population according to glucose levels (≤123 mg/dL vs. >123 mg/dL) yielded significantly elevated mean heart rate (80.75 ± 18.96 vs. 90.01 ± 22.19 b.p.m., P < 0.001), left ventricular end-diastolic pressure (LVEDP, 18.51 ± 8.35 vs. 23.09 ± 7.97 mmHg, P < 0.001), C-reactive protein (26.14 ± 43.30 vs. 46.4 ± 68.6 mg/L, P = 0.006), leukocyte count (10.12 ± 4.29 vs. 15.05 ± 9.83/nL, P < 0.001), peak high-sensitive Troponin T (hs-TnT, 515.44 ± 672.15 vs. 711.40 ± 736.37 pg/mL, P = 0.005), reduced left ventricular ejection fraction (EF, 34.92 ± 8.94 vs. 31.35 ± 8.06%, P < 0.001), and elevated intrahospital mortality (2.3% vs. 12.1%, P = 0.002) in the high-glucose group (Student's t-test, Mann-Whitney U test, or chi-squared test). Linear regression indicated a significant association of glucose with HR (P < 0.001), LVEDP (P = 0.014), hs-TnT kinetics from admission to the next day (P < 0.001), hs-TnT the day after admission (P < 0.001), as well as peak hsTnT (P < 0.001). Logistic regression revealed significant association of glucose with a composite intrahospital outcome including catecholamine use, respiratory support, and resuscitation [OR 1.010 (1.004-1.015), P = 0.001]. To further investigate the potential role of glucose in TTS pathophysiology experimentally, we utilized an in vivo murine model of epinephrine (EPI)-driven reversible AHF. For this, male mice underwent therapeutic injection of insulin (INS, 1 IU/kg) or/and glucose (GLU, 0.5 g/kg) after EPI (2.5 mg/kg), both of which markedly improved mean EF (EPI 34.3% vs. EPI + INS + GLU 43.7%, P = 0.025) and significantly blunted mean hs-TnT (EPI 14 393 pg/mL vs. EPI + INS 6864 pg/mL at 24 h, P = 0.039). Particularly, insulin additionally ameliorated myocardial pro-inflammatory gene expression, suggesting an anti-inflammatory effect of acute insulin therapy. CONCLUSIONS: Elevated initial plasma glucose was associated with adverse outcome-relevant parameters in TTS and may present a surrogate parameter of heightened catecholaminergic drive. In mice, insulin- and glucose injection both improved EPI-induced AHF and myocardial damage, indicating insulin resistance rather than detrimental effects of hyperglycaemia itself as the underlying cause. Future studies will investigate the role of HbA1c as a risk stratifier and of insulin-based therapy in TTS.

Machine learning-based prediction of in-hospital death for patients with takotsubo syndrome: The InterTAK-ML model.

AIMS: Takotsubo syndrome (TTS) is associated with a substantial rate of adverse events. We sought to design a machine learning (ML)-based model to predict the risk of in-hospital death and to perform a clustering of TTS patients to identify different risk profiles. METHODS AND RESULTS: A ridge logistic regression-based ML model for predicting in-hospital death was developed on 3482 TTS patients from the International Takotsubo (InterTAK) Registry, randomly split in a train and an internal validation cohort (75% and 25% of the sample size, respectively) and evaluated in an external validation cohort (1037 patients). Thirty-one clinically relevant variables were included in the prediction model. Model performance represented the primary endpoint and was assessed according to area under the curve (AUC), sensitivity and specificity. As secondary endpoint, a K-medoids clustering algorithm was designed to stratify patients into phenotypic groups based on the 10 most relevant features emerging from the main model. The overall incidence of in-hospital death was 5.2%. The InterTAK-ML model showed an AUC of 0.89 (0.85-0.92), a sensitivity of 0.85 (0.78-0.95) and a specificity of 0.76 (0.74-0.79) in the internal validation cohort and an AUC of 0.82 (0.73-0.91), a sensitivity of 0.74 (0.61-0.87) and a specificity of 0.79 (0.77-0.81) in the external cohort for in-hospital death prediction. By exploiting the 10 variables showing the highest feature importance, TTS patients were clustered into six groups associated with different risks of in-hospital death (28.8% vs. 15.5% vs. 5.4% vs. 1.0.8% vs. 0.5%) which were consistent also in the external cohort. CONCLUSION: A ML-based approach for the identification of TTS patients at risk of adverse short-term prognosis is feasible and effective. The InterTAK-ML model showed unprecedented discriminative capability for the prediction of in-hospital death.

Mislocalization of pathogenic RBM20 variants in dilated cardiomyopathy is caused by loss-of-interaction with Transportin-3.

Severe forms of dilated cardiomyopathy (DCM) are associated with point mutations in the alternative splicing regulator RBM20 that are frequently located in the arginine/serine-rich domain (RS-domain). Such mutations can cause defective splicing and cytoplasmic mislocalization, which leads to the formation of detrimental cytoplasmic granules. Successful development of personalized therapies requires identifying the direct mechanisms of pathogenic RBM20 variants. Here, we decipher the molecular mechanism of RBM20 mislocalization and its specific role in DCM pathogenesis. We demonstrate that mislocalized RBM20 RS-domain variants retain their splice regulatory activity, which reveals that aberrant cellular localization is the main driver of their pathological phenotype. A genome-wide CRISPR knockout screen combined with image-enabled cell sorting identified Transportin-3 (TNPO3) as the main nuclear importer of RBM20. We show that the direct RBM20-TNPO3 interaction involves the RS-domain, and is disrupted by pathogenic variants. Relocalization of pathogenic RBM20 variants to the nucleus restores alternative splicing and dissolves cytoplasmic granules in cell culture and animal models. These findings provide proof-of-principle for developing therapeutic strategies to restore RBM20's nuclear localization in RBM20-DCM patients.

The Heart and Artificial Intelligence-How Can We Improve Medicine Without Causing Harm.

PURPOSE OF REVIEW: The introduction of Artificial Intelligence into the healthcare system offers enormous opportunities for biomedical research, the improvement of patient care, and cost reduction in high-end medicine. Digital concepts and workflows are already playing an increasingly important role in cardiology. The fusion of computer science and medicine offers great transformative potential and enables enormous acceleration processes in cardiovascular medicine. RECENT FINDINGS: As medical data becomes smart, it is also becoming more valuable and vulnerable to malicious actors. In addition, the gap between what is technically possible and what is allowed by privacy legislation is growing. Principles of the General Data Protection Regulation that have been in force since May 2018, such as transparency, purpose limitation, and data minimization, seem to hinder the development and use of Artificial Intelligence. Concepts to secure data integrity and incorporate legal and ethical principles can help to avoid the potential risks of digitization and may result in an European leadership in regard to privacy protection and AI. The following review provides an overview of relevant aspects of Artificial Intelligence and Machine Learning, highlights selected applications in cardiology, and discusses central ethical and legal considerations.

Precision medicine in complex diseases-Molecular subgrouping for improved prediction and treatment stratification.

Complex diseases are caused by a combination of genetic, lifestyle, and environmental factors and comprise common noncommunicable diseases, including allergies, cardiovascular disease, and psychiatric and metabolic disorders. More than 25% of Europeans suffer from a complex disease, and together these diseases account for 70% of all deaths. The use of genomic, molecular, or imaging data to develop accurate diagnostic tools for treatment recommendations and preventive strategies, and for disease prognosis and prediction, is an important step toward precision medicine. However, for complex diseases, precision medicine is associated with several challenges. There is a significant heterogeneity between patients of a specific disease-both with regards to symptoms and underlying causal mechanisms-and the number of underlying genetic and nongenetic risk factors is often high. Here, we summarize precision medicine approaches for complex diseases and highlight the current breakthroughs as well as the challenges. We conclude that genomic-based precision medicine has been used mainly for patients with highly penetrant monogenic disease forms, such as cardiomyopathies. However, for most complex diseases-including psychiatric disorders and allergies-available polygenic risk scores are more probabilistic than deterministic and have not yet been validated for clinical utility. However, subclassifying patients of a specific disease into discrete homogenous subtypes based on molecular or phenotypic data is a promising strategy for improving diagnosis, prediction, treatment, prevention, and prognosis. The availability of high-throughput molecular technologies, together with large collections of health data and novel data-driven approaches, offers promise toward improved individual health through precision medicine.

The DZHK research platform: maximisation of scientific value by enabling access to health data and biological samples collected in cardiovascular clinical studies.

The German Centre for Cardiovascular Research (DZHK) is one of the German Centres for Health Research and aims to conduct early and guideline-relevant studies to develop new therapies and diagnostics that impact the lives of people with cardiovascular disease. Therefore, DZHK members designed a collaboratively organised and integrated research platform connecting all sites and partners. The overarching objectives of the research platform are the standardisation of prospective data and biological sample collections among all studies and the development of a sustainable centrally standardised storage in compliance with general legal regulations and the FAIR principles. The main elements of the DZHK infrastructure are web-based and central units for data management, LIMS, IDMS, and transfer office, embedded in a framework consisting of the DZHK Use and Access Policy, and the Ethics and Data Protection Concept. This framework is characterised by a modular design allowing a high standardisation across all studies. For studies that require even tighter criteria additional quality levels are defined. In addition, the Public Open Data strategy is an important focus of DZHK. The DZHK operates as one legal entity holding all rights of data and biological sample usage, according to the DZHK Use and Access Policy. All DZHK studies collect a basic set of data and biosamples, accompanied by specific clinical and imaging data and biobanking. The DZHK infrastructure was constructed by scientists with the focus on the needs of scientists conducting clinical studies. Through this, the DZHK enables the interdisciplinary and multiple use of data and biological samples by scientists inside and outside the DZHK. So far, 27 DZHK studies recruited well over 11,200 participants suffering from major cardiovascular disorders such as myocardial infarction or heart failure. Currently, data and samples of five DZHK studies of the DZHK Heart Bank can be applied for.

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.

Cardiac splicing as a diagnostic and therapeutic target.

Despite advances in therapeutics for heart failure and arrhythmias, a substantial proportion of patients with cardiomyopathy do not respond to interventions, indicating a need to identify novel modifiable myocardial pathobiology. Human genetic variation associated with severe forms of cardiomyopathy and arrhythmias has highlighted the crucial role of alternative splicing in myocardial health and disease, given that it determines which mature RNA transcripts drive the mechanical, structural, signalling and metabolic properties of the heart. In this Review, we discuss how the analysis of cardiac isoform expression has been facilitated by technical advances in multiomics and long-read and single-cell sequencing technologies. The resulting insights into the regulation of alternative splicing - including the identification of cardiac splice regulators as therapeutic targets and the development of a translational pipeline to evaluate splice modulators in human engineered heart tissue, animal models and clinical trials - provide a basis for improved diagnosis and therapy. Finally, we consider how the medical and scientific communities can benefit from facilitated acquisition and interpretation of splicing data towards improved clinical decision-making and patient care.

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.