Our objective was to better understand the genetic bases of dilated cardiomyopathy (DCM), a leading cause of systolic heart failure. We conducted the largest genome-wide association study performed so far in DCM, with 2719 cases and 4440 controls in the discovery population. We identified and replicated two new DCM-associated loci on chromosome 3p25.1 [lead single-nucleotide polymorphism (SNP) rs62232870, P = 8.7 × 10⁻¹¹ and 7.7 × 10⁻⁴ in the discovery and replication steps, respectively] and chromosome 22q11.23 (lead SNP rs7284877, P = 3.3 × 10⁻⁸ and 1.4 × 10⁻³ in the discovery and replication steps, respectively), while confirming two previously identified DCM loci on chromosomes 10 and 1, BAG3 and HSPB7. A genetic risk score constructed from the number of risk alleles at these four DCM loci revealed a 3-fold increased risk of DCM for individuals with 8 risk alleles compared to individuals with 5 risk alleles (median of the referral population). In silico annotation and functional 4C-sequencing analyses on iPSC-derived cardiomyocytes identify SLC6A6 as the most likely DCM gene at the 3p25.1 locus. This gene encodes a taurine transporter whose involvement in myocardial dysfunction and DCM is supported by numerous observations in humans and animals. At the 22q11.23 locus, in silico and data mining annotations, and to a lesser extent functional analysis, strongly suggest SMARCB1 as the candidate culprit gene. This study provides a better understanding of the genetic architecture of DCM and sheds light on novel biological pathways underlying heart failure. Step 1: Through the largest genome-wide association study performed so far in dilated cardiomyopathy, we identified and replicated two new loci on chromosome 3p25.1 and 22q11.23. Step 2: Combined in silico and functional analyses at the associated loci revealed the best culprit gene at each locus: SLC6A6 (chromosome 3) and SMARCB1 (chromosome 22). The discovery of these two new players shed light on novel biological pathways and putative new therapeutic targets.

Post-COVID-19 syndrome (PCS) has been described as ‘the pandemic after the pandemic’ with more than 65 million people worldwide being affected. The enormous range of symptoms makes both diagnosis complex and treatment difficult. In a post-COVID rehabilitation outpatient clinic, 184 patients, mostly non-hospitalized, received a comprehensive, interdisciplinary diagnostic assessment with fixed follow-up appointments. At baseline, three in four patients reported more than 10 symptoms, the most frequent symptoms were fatigue (84.9%), decreased physical capacity (83.0%), tiredness (81.1%), poor concentration (73.6%), sleeping problems (66.7%) and shortness of breath (67.3%). Abnormalities were found in the mean values of scores for fatigue (FAS = 34.3), cognition (MoCA = 25.5), psychological alterations (anxiety, depression, post-traumatic stress disorder), limitation of lung function (CAT) and severity scores for PCS (PCFS, MCRS). Clinical abnormalities were found in elevated values of heart rate, breathing rate at rest, blood pressure and NT-proBNP levels. As the frequency of the described symptoms decreases only slowly but most often significantly over the course, it is important to monitor the patients over a longer period of time. Many of them suffer from an immense symptom burden, often without pre-existing clinical correlates. Our results show a clear association with objectifiable assessments and tests as well as pronounced symptoms.

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.

Purpose: The objective examination of the Post-COVID syndrome (PCS) remains difficult due to heterogeneous definitions and clinical phenotypes. The aim of the study was to verify the functionality and correlates of a recently developed PCS score. Methods: The PCS score was applied to the prospective, multi-center cross-sectoral cohort (in- and outpatients with SARS-CoV-2 infection) of the "National Pandemic Cohort Network (NAPKON, Germany)". Symptom assessment and patient-reported outcome measure questionnaires were analyzed at 3 and 12 months (3/12MFU) after diagnosis. Scores indicative of PCS severity were compared and correlated to demographic and clinical characteristics as well as quality of life (QoL, EQ-5D-5L). Results: Six hundred three patients (mean 54.0 years, 60.6% male, 82.0% hospitalized) were included. Among those, 35.7% (215) had no and 64.3% (388) had mild, moderate, or severe PCS. PCS severity groups differed considering sex and pre-existing respiratory diseases. 3MFU PCS worsened with clinical severity of acute infection ( p = .011), and number of comorbidities ( p = .004). PCS severity was associated with poor QoL at the 3MFU and 12MFU ( p < .001). Conclusion: The PCS score correlated with patients’ QoL and demonstrated to be instructive for clinical characterization and stratification across health care settings. Further studies should critically address the high prevalence, clinical relevance, and the role of comorbidities. Trail registration number: The cohort is registered at www.clinicaltrials.gov under NCT04768998.

(1) Background: COVID-19 is often associated with significant long-term symptoms and disability, i.e., the long/post-COVID syndrome (PCS). Even after presumably mild COVID-19 infections, an increasing number of patients seek medical help for these long-term sequelae, which can affect various organ systems. The pathogenesis of PCS is not yet understood. Therapy has so far been limited to symptomatic treatment. The Greifswald Post COVID Rehabilitation Study (PoCoRe) aims to follow and deeply phenotype outpatients with PCS in the long term, taking a holistic and comprehensive approach to the analysis of their symptoms, signs and biomarkers. (2) Methods: Post-COVID outpatients are screened for symptoms in different organ systems with a standardized medical history, clinical examination, various questionnaires as well as physical and cardiopulmonary function tests. In addition, biomaterials are collected for the analysis of immunomodulators, cytokines, chemokines, proteome patterns as well as specific (auto)antibodies. Patients are treated according to their individual needs, adhering to the current standard of care. PoCoRe’s overall aim is to optimize diagnostics and therapy in PCS patients.