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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. Graphic abstract

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.

Depending on context and tumor stage, deregulation of autophagy can either suppress tumorigenesis or promote chemoresistance and tumor survival. Histone deacetylases (HDACs) can modulate autophagy, however, the exact mechanisms are not fully understood. Here, we analyze the effects of the broad-spectrum HDAC inhibitors (HDACi) panobinostat and vorinostat on the transcriptional regulation of autophagy with respect to autophagy transcription factor activity (Transcription factor EB—TFEB, forkhead boxO—FOXO) and autophagic flux in neuroblastoma cells. In combination with the late-stage autophagic flux inhibitor bafilomycin A1, HDACis increase the number of autophagic vesicles, indicating an increase in autophagic flux. Both HDACi induce nuclear translocation of the transcription factors FOXO1 and FOXO3a, but not TFEB and promote the expression of pro-autophagic FOXO1/3a target genes. Moreover, FOXO1/3a knockdown experiments impaired HDACi treatment mediated expression of autophagy related genes. Combination of panobinostat with the lysosomal inhibitor chloroquine, which blocks autophagic flux, enhances neuroblastoma cell death in culture and hampers tumor growth in vivo in a neuroblastoma zebrafish xenograft model. In conclusion, our results indicate that pan-HDACi treatment induces autophagy in neuroblastoma at a transcriptional level. Combining HDACis with autophagy modulating drugs suppresses tumor growth of high-risk neuroblastoma cells. These experimental data provide novel insights for optimization of treatment strategies in neuroblastoma.

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.

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.

The genetic underpinnings that orchestrate the vertebrate heart rate are not fully understood yet, but of high clinical importance, since diseases of cardiac impulse formation and propagation are common and severe human arrhythmias. To identify novel regulators of the vertebrate heart rate, we deciphered the pathogenesis of the bradycardia in the homozygous zebrafish mutant hiphop (hip) and identified a missense-mutation (N851K) in Na+/K+-ATPase α1-subunit (atp1a1a.1). N851K affects zebrafish Na+/K+-ATPase ion transport capacity, as revealed by in vitro pump current measurements. Inhibition of the Na+/K+-ATPase in vivo indicates that hip rather acts as a hypomorph than being a null allele. Consequently, reduced Na+/K+-ATPase function leads to prolonged QT interval and refractoriness in the hip mutant heart, as shown by electrocardiogram and in vivo electrical stimulation experiments. We here demonstrate for the first time that Na+/K+-ATPase plays an essential role in heart rate regulation by prolonging myocardial repolarization.

Simple Summary Preclinical analyses identified APR-246 as a potent treatment option for neuroblastoma. However, a specific mode of action, sufficient biomarkers and promising combination partners are still missing. Here, we analyze the susceptibilities of different entities and relate them to gene expression profiles and previously described biomarkers. We propose a gene signature, consisting of 13 genes, as a novel predictive biomarker. Furthermore, we provide evidence that APR-246 directly targets metabolic weaknesses in neuroblastoma cell lines, thus hampering ROS detoxification. This makes APR-246 suitable to be combined with ROS-inducing HDAC inhibitors, a treatment combination that has not been described for neuroblastoma thus far. Abstract APR-246 (Eprenetapopt/PRIMA-1Met) is a very potent anti-cancer drug in clinical trials and was initially developed as a p53 refolding agent. As an alternative mode of action, the elevation of reactive oxygen species (ROS) has been proposed. Through an in silico analysis, we investigated the responses of approximately 800 cancer cell lines (50 entities; Cancer Therapeutics Response Portal, CTRP) to APR-246 treatment. In particular, neuroblastoma, lymphoma and acute lymphocytic leukemia cells were highly responsive. With gene expression data from the Cancer Cell Line Encyclopedia (CCLE; n = 883) and patient samples (n = 1643) from the INFORM registry study, we confirmed that these entities express low levels of SLC7A11, a previously described predictive biomarker for APR-246 responsiveness. Combining the CTRP drug response data with the respective CCLE gene expression profiles, we defined a novel gene signature, predicting the effectiveness of APR-246 treatment with a sensitivity of 90% and a specificity of 94%. We confirmed the predicted APR-246 sensitivity in 8/10 cell lines and in ex vivo cultures of patient samples. Moreover, the combination of ROS detoxification-impeding APR-246 with approved HDAC-inhibitors, known to elevate ROS, substantially increased APR-246 sensitivity in cell cultures and in vivo in two zebrafish neuroblastoma xenograft models. These data provide evidence that APR-246, in combination with HDAC-inhibitors, displays a novel potent targeted treatment option for neuroblastoma patients.

The transcriptome needs to be tightly regulated by mechanisms that include transcription factors, enhancers, and repressors as well as non‐coding RNAs. Besides this dynamic regulation, a large part of phenotypic variability of eukaryotes is expressed through changes in gene transcription caused by genetic variation. In this study, we evaluate genome‐wide structural genomic variants (SVs) and their association with gene expression in the human heart. We detected 3,898 individual SVs affecting all classes of gene transcripts (e.g., mRNA, miRNA, lncRNA) and regulatory genomic regions (e.g., enhancer or TFBS). In a cohort of patients (n = 50) with dilated cardiomyopathy (DCM), 80,635 non‐protein‐coding elements of the genome are deleted or duplicated by SVs, containing 3,758 long non‐coding RNAs and 1,756 protein‐coding transcripts. 65.3% of the SV‐eQTLs do not harbor a significant SNV‐eQTL, and for the regions with both classes of association, we find similar effect sizes. In case of deleted protein‐coding exons, we find downregulation of the associated transcripts, duplication events, however, do not show significant changes over all events. In summary, we are first to describe the genomic variability associated with SVs in heart failure due to DCM and dissect their impact on the transcriptome. Overall, SVs explain up to 7.5% of the variation of cardiac gene expression, underlining the importance to study human myocardial gene expression in the context of the individual genome. This has immediate implications for studies on basic mechanisms of cardiac maladaptation, biomarkers, and (gene) therapeutic studies alike.

Background: Biochemical DNA modification resembles a crucial regulatory layer among genetic information, environmental factors, and the transcriptome. To identify epigenetic susceptibility regions and novel biomarkers linked to myocardial dysfunction and heart failure, we performed the first multi-omics study in myocardial tissue and blood of patients with dilated cardiomyopathy and controls. Methods: Infinium human methylation 450 was used for high-density epigenome-wide mapping of DNA methylation in left-ventricular biopsies and whole peripheral blood of living probands. RNA deep sequencing was performed on the same samples in parallel. Whole-genome sequencing of all patients allowed exclusion of promiscuous genotype-induced methylation calls. Results: In the screening stage, we detected 59 epigenetic loci that are significantly associated with dilated cardiomyopathy (false discovery corrected P ≤0.05), with 3 of them reaching epigenome-wide significance at P ≤5×10 −8 . Twenty-seven (46%) of these loci could be replicated in independent cohorts, underlining the role of epigenetic regulation of key cardiac transcription regulators. Using a staged multi-omics study design, we link a subset of 517 epigenetic loci with dilated cardiomyopathy and cardiac gene expression. Furthermore, we identified distinct epigenetic methylation patterns that are conserved across tissues, rendering these CpGs novel epigenetic biomarkers for heart failure. Conclusions: The present study provides to our knowledge the first epigenome-wide association study in living patients with heart failure using a multi-omics approach.

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.

Routine genetic testing in Dilated Cardiomyopathy (DCM) has recently become reality using Next-Generation Sequencing. Several studies have explored the relationship between genotypes and clinical phenotypes to support risk estimation and therapeutic decisions, however, most studies are small or restricted to a few genes. This study provides to our knowledge the first systematic meta-analysis on genotype-phenotype associations in DCM. We retrieved PubMed/Medline literature on genotype–phenotype associations in patients with DCM and mutations in LMNA, PLN, RBM20, MYBPC3, MYH7, TNNT2 and TNNI3. We summarized and extensively reviewed all studies that passed selection criteria and performed a meta-analysis on key phenotypic parameters. Together, 48 studies with 8097 patients were included. Furthermore, we reviewed recent studies investigating genotype-phenotype associations in DCM patients with TTN mutations. The average frequency of mutations in the investigated genes was between 1 and 5 %. The mean age of DCM onset was the beginning of the fifth decade for all genes. Heart transplantation (HTx) rate was highest in LMNA mutation carriers (27 %), while RBM20 mutation carriers were transplanted at a markedly younger age (mean 28.5 years). While 73 % of DCM patients with LMNA mutations showed cardiac conduction diseases, low voltage was the reported ECG hallmark in PLN mutation carriers. The frequency of ventricular arrhythmia in DCM patients with LMNA (50 %) and PLN (43 %) mutations was significantly higher. The penetrance of DCM phenotype in subjects with TTN truncating variants increased with age and reached 100 % by age of 70. A pooled analysis of available genotype-phenotype data shows a higher prevalence of sudden cardiac death (SCD), cardiac transplantation, or ventricular arrhythmias in LMNA and PLN mutation carriers compared to sarcomeric gene mutations. This study will further support the clinical interpretation of genetic findings.

Next-generation sequencing (NGS) is getting routinely used in the diagnosis of hereditary diseases, such as human cardiomyopathies. Hence, it is of utter importance to secure high quality sequencing data, enabling the identification of disease-relevant mutations or the conclusion of negative test results. During the process of sample preparation, each protocol for target enrichment library preparation has its own requirements for quality control (QC); however, there is little evidence on the actual impact of these guidelines on resulting data quality. In this study, we analyzed the impact of QC during the diverse library preparation steps of Agilent SureSelect XT target enrichment and Illumina sequencing. We quantified the parameters for a cohort of around 600 samples, which include starting amount of DNA, amount of sheared DNA, smallest and largest fragment size of the starting DNA; amount of DNA after the pre-PCR, and smallest and largest fragment size of the resulting DNA; as well as the amount of the final library, the corresponding smallest and largest fragment size, and the number of detected variants. Intriguingly, there is a high tolerance for variations in all QC steps, meaning that within the boundaries proposed in the current study, a considerable variance at each step of QC can be well tolerated without compromising NGS quality.

Alternative splicing is one of the major mechanisms through which the proteomic and functional diversity of eukaryotes is achieved. However, the complex nature of the splicing machinery, its associated splicing regulators and the functional implications of alternatively spliced transcripts are only poorly understood. Here, we investigated the functional role of the splicing regulator rbfox1 in vivo using the zebrafish as a model system. We found that loss of rbfox1 led to progressive cardiac contractile dysfunction and heart failure. By using deep-transcriptome sequencing and quantitative real-time PCR, we show that depletion of rbfox1 in zebrafish results in an altered isoform expression of several crucial target genes, such as actn3a and hug. This study underlines that tightly regulated splicing is necessary for unconstrained cardiac function and renders the splicing regulator rbfox1 an interesting target for investigation in human heart failure and cardiomyopathy., Summary: The zebrafish splicing regulator rbfox1 is necessary for tightly regulated splicing and unconstrained cardiac function, making it an interesting candidate for targeting during human cardiomyopathy.

International audience; Heart failure (HF), a major public health burden affecting 2% of industrialized populations, is a syndrome resulting from structural or functional myocardial impairment leading to inadequate cardiac output to meet the body's metabolic demands [1]. Half of HF patients present systolic dysfunction (systolic-HF), also called reduced ejection fraction (HF-REF), a disease related to various causes including idiopathic Dilated Cardiomyopathy (DCM) and Coronary Artery Diseases (CAD) (ischemic-HF). HF is usually a multifactorial disease but the genetic variants contributing to its susceptibility or its severity may be different according to its underlying causes [2] and their identification is only beginning.[...]

Within just a few years, the new methods for high-throughput next-generation sequencing have generated completely novel insights into the heritability and pathophysiology of human disease. In this review, we wish to highlight the benefits of the current state-of-the-art sequencing technologies for genetic and epigenetic research. We illustrate how these technologies help to constantly improve our understanding of genetic mechanisms in biological systems and summarize the progress made so far. This can be exemplified by the case of heritable heart muscle diseases, so-called cardiomyopathies. Here, next-generation sequencing is able to identify novel disease genes, and first clinical applications demonstrate the successful translation of this technology into personalized patient care.

BACKGROUND Alterations in microRNA (miRNA) expression patterns in whole blood may be useful biomarkers of diverse cardiovascular disorders. We previously reported that miRNAs are significantly dysregulated in acute myocardial infarction (AMI) and applied machine-learning techniques to define miRNA subsets with high diagnostic power for AMI diagnosis. However, the kinetics of the time-dependent sensitivity of these novel miRNA biomarkers remained unknown. METHODS To characterize temporal changes in the expressed human miRNAs (miRNome), we performed here the first whole-genome miRNA kinetic study in AMI patients. We measured miRNA expression levels at multiple time points (0, 2, 4, 12, 24 h after initial presentation) in patients with acute ST-elevation myocardial infarction by using microfluidic primer extension arrays and quantitative real-time PCR. As a prerequisite, all patients enrolled had to have cardiac troponin T concentrations RESULTS We found a subset of miRNAs to be significantly dysregulated both at initial presentation and during the course of AMI. Additionally, we identified novel miRNAs that are dysregulated early during myocardial infarction, such as miR-1915 and miR-181c*. CONCLUSIONS The present proof-of-concept study provides novel insights into the dynamic changes of the human miRNome during AMI.

Aims Non-ischaemic heart failure is one of the today's most prevalent cardiovascular disorders. Since modern pharmacotherapy has proved to be very effective in delaying disease progression and preventing death, imaging modalities and molecular biomarkers play an important role in early identification and clinical management as well as risk assessment of patients. The present study evaluated for the first time whole peripheral blood miRNAs as novel biomarker candidates for non-ischaemic heart failure with reduced ejection fraction (HF-REF). Methods and results We assessed genome-wide miRNA expression profiles in 53 HF-REF patients and 39 controls. We could identify and validate several miRNAs that show altered expression levels in non-ischaemic HF-REF, discriminating cases from controls both as single markers or when combined in a multivariate signature. In addition, we demonstrate that the miRNAs of this signature significantly correlate with disease severity as indicated by left ventricular ejection fraction. Conclusion Our data further denote that miRNAs are potential biomarkers for systolic heart failure. Since their detection levels in whole blood are also related to the degree of left ventricular dysfunction, they may serve as objective molecular tools to assess disease severity and prognosis.

Aims: In this study, we aimed to clinically and genetically characterize LVNC patients and investigate the prevalence of variants in known and novel LVNC disease genes. Introduction: Left ventricular non-compaction cardiomyopathy (LVNC) is an increasingly recognized cause of heart failure, arrhythmia, thromboembolism, and sudden cardiac death. We sought here to dissect its genetic causes, phenotypic presentation and outcome. Methods and results: In our registry with follow-up of in the median 61 months, we analysed 95 LVNC patients (68 unrelated index patients and 27 affected relatives; definite familial LVNC = 23.5%) by cardiac phenotyping, molecular biomarkers and exome sequencing. Cardiovascular events were significantly more frequent in LVNC patients compared with an age-matched group of patients with non-ischaemic dilated cardiomyopathy (hazard ratio = 2.481, P = 0.002). Stringent genetic classification according to ACMG guidelines revealed that TTN, LMNA, and MYBPC3 are the most prevalent disease genes (13 patients are carrying a pathogenic truncating TTN variant, odds ratio = 40.7, Confidence interval = 21.6-76.6, P

A certain degree of bias in high-throughput molecular technologies including microarrays and next-generation sequencing (NGS) is known. To quantify the actual impact of the biomarker discovery platform on miRNA profiles, we first performed a meta-analysis: raw data of 1 539 microarrays and 705 NGS blood-borne miRNomes were statistically evaluated, suggesting a substantial influence of the technology on biomarker profiles. We observed highly significant dependency of the miRNA nucleotide composition on the expression level. Higher expression in NGS was discovered for uracil-rich miRNAs (p = 7 × 10(-37)), while high expression in microarrays was found predominantly for guanine-rich miRNAs (p = 3 × 10(-33)). To verify the findings, 10 identical replicates of one individual were measured using NGS and microarrays (2 525 miRNAs from miRBase version 21). Overall, we calculated a correlation coefficient of 0.414 for both technologies. Detailed analysis however revealed that the correlation was observed only for miRNAs in the early miRBase versions (8). The majority of miRNAs (2 013 from miRBase version 8 onward) was not correlated between microarray and NGS. Specifically, we observed 67 miRNAs with a median read count above 10 in NGS, while they were not detected in any of the 10 replicated array experiments. In contrast, 234 miRNAs were discovered in all 10 replicated array measurements but were not found in any of the NGS experiments of the same individual. While the first group had average guanine content of 22%, the latter group consisted of 41% of this nucleotide. Selected concordant and discordant miRNAs were tested in quantitative real-time-polymerase chain reaction (RT-qPCR) experiments again of the same individual, providing further evidence for the substantial bias depending on the base composition. As a consequence, biomarkers that have been discovered by specific high-throughout technologies have to be carefully considered. Especially for validation of the platform, the selection of reasonable candidates is essential.

Die dilatative Kardiomyopathie (DCM) ist eine der haufigsten Herzmuskelerkrankungen. In einem signifikanten Anteil handelt es sich um eine familiare Erkrankung, weshalb eine gezielte Familienanamnese erfolgen sollte und eine genetische Untersuchung Betroffener und deren Angehoriger erwogen werden mussen. Die genetische Charakterisierung erleichtert sowohl die Differenzialdiagnose als auch eine Risikostratifizierung der betroffenen Patienten. Durch die oft progrediente Verschlechterung der systolischen Herzkraft spielen auser einer leitliniengerechten medikamentosen Herzinsuffizienztherapie immer haufiger interventionelle Verfahren eine wichtige Rolle. Neben der Herztransplantation haben daher insbesondere die kardiale Resynchronisationstherapie, die Mitralklappenrekonstruktion und mechanische Kreislaufunterstutzungssysteme die Prognose der schweren DCM verbessert.

Integrin-linked kinase (ILK) is an essential component of the cardiac mechanical stretch sensor and is bound in a protein complex with parvin and PINCH proteins, the so-called ILK-PINCH-parvin (IPP) complex. We have recently shown that inactivation of ILK or β-parvin activity leads to heart failure in zebrafish via reduced protein kinase B (PKB/Akt) activation. Here, we show that PINCH proteins localize at sarcomeric Z disks and costameres in the zebrafish heart and skeletal muscle. To investigate the in vivo role of PINCH proteins for IPP complex stability and PKB signaling within the vertebrate heart, we inactivated PINCH1 and PINCH2 in zebrafish. Inactivation of either PINCH isoform independently leads to instability of ILK, loss of stretch-responsive anf and vegf expression, and progressive heart failure. The predominant cause of heart failure in PINCH morphants seems to be loss of PKB activity, since PKB phosphorylation at serine 473 is significantly reduced in PINCH-deficient hearts and overexpression of constitutively active PKB reconstitutes cardiac function in PINCH morphants. These findings highlight the essential function of PINCH proteins in controlling cardiac contractility by granting IPP/PKB-mediated signaling.

Background While in the past decades nucleic acid analysis has been predominantly carried out using quantitative low- and high-throughput approaches such as qRT-PCR and microarray technology, next-generation sequencing (NGS) with its single base resolution is now frequently applied in DNA and RNA testing. Especially for small non-coding RNAs such as microRNAs there is a need for analysis and visualization tools that facilitate interpretation of the results also for clinicians. Methods We developed miFRame, which supports the analysis of human small RNA NGS data. Our tool carries out different data analyses for known as well as predicted novel mature microRNAs from known precursors and presents the results in a well interpretable manner. Analyses include among others expression analysis of precursors and mature miRNAs, detection of novel precursors and detection of potential iso-microRNAs. Aggregation of results from different users moreover allows for evaluation whether remarkable results, such as novel mature miRNAs, are indeed specific for the respective experimental set-up or are frequently detected across a broad range of experiments. Results We demonstrate the capabilities of miFRame, which is freely available at http://www.ccb.uni-saarland.de/miframe on two studies, circulating biomarker screening for Multiple Sclerosis (cohort includes clinically isolated syndrome, relapse remitting MS, matched controls) as well as Alzheimer Disease (cohort includes Alzheimer Disease, Mild Cognitive Impairment, matched controls). Here, our tool allowed for an improved biomarker discovery by identifying likely false positive marker candidates. Electronic supplementary material The online version of this article (doi:10.1186/s12967-015-0594-x) contains supplementary material, which is available to authorized users.

BackgroundDespite modern pharmacotherapy and advanced implantable cardiac devices, overall prognosis and quality of life of HF patients remain poor. This is in part due to insufficient patient stratification and lack of individualized therapy planning, resulting in less effective treatments and a significant number of non-responders.Methods and resultsState-of-the-art clinical phenotyping was acquired, including magnetic resonance imaging (MRI) and biomarker assessment. An individualized, multi-scale model of heart function covering cardiac anatomy, electrophysiology, biomechanics and hemodynamics was estimated using a robust framework. The model was computed on n=46 HF patients, showing for the first time that advanced multi-scale models can be fitted consistently on large cohorts. Novel multi-scale parameters derived from the model of all cases were analyzed and compared against clinical parameters, cardiac imaging, lab tests and survival scores to evaluate the explicative power of the model and its potential for better patient stratification. Model validation was pursued by comparing clinical parameters that were not used in the fitting process against model parameters.ConclusionThis paper illustrates how advanced multi-scale models can complement cardiovascular imaging and how they could be applied in patient care. Based on obtained results, it becomes conceivable that, after thorough validation, such heart failure models could be applied for patient management and therapy planning in the future, as we illustrate in one patient of our cohort who received CRT-D implantation.

Objective: Alternative splicing (AS) is one of the key mechanisms for the proteomic and functional diversity of eukaryotes. However, the complex nature of AS, its associated regulators and their targets are only partially understood. In the present study we investigated the transcriptomic diversity in the zebrafish heart using RNA-Sequencing and elucidated the functional role of the splicing regulator A2BP1 in vivo. Results: Using RNA-Sequencing we characterized the cardiac transcriptome of 48 hours post fertilization (hpf) old zebrafish embryos and compared the expression of genes and their isoforms to whole fish tissue. Besides the known cardiac genes, we found several previously described genes, highly expressed in cardiac tissue. The analysis of RNA-Seq data indicates that 14% of all genes expressed in the heart undergo AS by single exon-skipping/inclusion. To determine the effect of splicing factors on mRNA splicing we investigated the functional role of splicing regulator a2bp1 in vivo by using the zebrafish as a model organism. Morpholino-mediated a2bp1 knockdown in zebrafish embryos led to progressive cardiac contractile dysfunction, suggesting an important role of a2bp1 in maintenance of cardiac function. Splicing analysis revealed that loss of a2bp1 does not result in a completely splicing failure, but rather alters the splicing pattern of specific target genes. Here we identified novel spliceforms and potentialy novel targets of splicing factor a2bp1. Splice-junction blockage experiments showed that a balanced isoform expression of the targets actn3a, hug, ktn1, ptpla and camk2g is necessary for maintaining cardiac function in zebrafish. We assume, that the a2bp1-knockdown phenotype is not caused by missplicing of specific targets rather by the cumulative effect of many splicing abnormalities. Conclusion: Our study reveal a novel splicing regulator that is necessary for normal heart function. We showed that dysfunction of a2bp1 not only leads to heart failure, but show that a2bp1 mediates the splicing of different transcripts which might mediate the observed phenotype. Our results highlight the importance of balanced mRNA splicing in the heart and represents intriguing opportunities for novel therapeutic approaches.

Left ventricular noncompaction cardiomyopathy (LVNC) is an increasingly recognized cause of heart failure, arrhythmias, thrombembolic events, and sudden cardiac death. To better understand the contribution of genetic factors to this disease, allowing a better diagnosis, counseling of affected families and estimation of prognosis, we have performed whole-exome deep-sequencing on a cohort of in 104 subjects (67 unrelated LVNC probands, 26 affected relatives form 15 families and 11 additional healthy relatives). By annotating the detected variants with mutation databases (HGMD), we were able to for the first time show an overlap between the distinct causes of LVNC and other genetic cardiomyopathies, as 8 mutations were previously reported to cause hypertrophic cardiomyopathy (HCM), 9 dilated cardiomyopathy (DCM) and 6 arrhythmogenic right ventricular cardiomyopathy (ARVC). Besides already known genetic causes, we identified a number of genes contributing to different pathways, so far not discussed to be of relevance for LVNC. From those, TTN truncating mutations were very frequent, affecting 17.9% of all index patients and one fifth of the familial cases. For two genes, which have already been linked to cardiac noncompaction in animal models, we are first to describe a relevant number of patients carrying mutations in these genes NCOR2 (frequency = 7.5%) and XIRP2 (4.5%). By performing segregation and linkage analyses, as well as in vivo studies, we provide for the first time evidence for a gene that was previously not known to cause a human disease, Compactin1. In conclusion, we show that LVNC has a substantial genetic component and suggest new candidate genes for a functional dissection of their contribution to cardiac development and as potential therapeutic target.

[Abstract] Aim. Numerous genes are known to cause dilated cardiomyopathy (DCM). However, until now technological limitations have hindered elucidation of the contribution of all clinically relevant disease genes to DCM phenotypes in larger cohorts. We now utilized next-generation sequencing to overcome these limitations and screened all DCM disease genes in a large cohort. Methods and results. In this multi-centre, multi-national study, we have enrolled 639 patients with sporadic or familial DCM. To all samples, we applied a standardized protocol for ultra-high coverage next-generation sequencing of 84 genes, leading to 99.1% coverage of the target region with at least 50-fold and a mean read depth of 2415. In this well characterized cohort, we find the highest number of known cardiomyopathy mutations in plakophilin-2, myosin-binding protein C-3, and desmoplakin. When we include yet unknown but predicted disease variants, we find titin, plakophilin-2, myosin-binding protein-C 3, desmoplakin, ryanodine receptor 2, desmocollin-2, desmoglein-2, and SCN5A variants among the most commonly mutated genes. The overlap between DCM, hypertrophic cardiomyopathy (HCM), and channelopathy causing mutations is considerably high. Of note, we find that >38% of patients have compound or combined mutations and 12.8% have three or even more mutations. When comparing patients recruited in the eight participating European countries we find remarkably little differences in mutation frequencies and affected genes. Conclusion. This is to our knowledge, the first study that comprehensively investigated the genetics of DCM in a large-scale cohort and across a broad gene panel of the known DCM genes. Our results underline the high analytical quality and feasibility of Next-Generation Sequencing in clinical genetic diagnostics and provide a sound database of the genetic causes of DCM. Hôpitaux de Paris; PHRC AOM04141

Background: Alzheimer disease (AD) is the most common form of dementia but the identification of reliable, early and non-invasive biomarkers remains a major challenge. We present a novel miRNA-based signature for detecting AD from blood samples. Results: We apply next-generation sequencing to miRNAs from blood samples of 48 AD patients and 22 unaffected controls, yielding a total of 140 unique mature miRNAs with significantly changed expression levels. Of these, 82 have higher and 58 have lower abundance in AD patient samples. We selected a panel of 12 miRNAs for an RT-qPCR analysis on a larger cohort of 202 samples, comprising not only AD patients and healthy controls but also patients with other CNS illnesses. These included mild cognitive impairment, which is assumed to represent a transitional period before the development of AD, as well as multiple sclerosis, Parkinson disease, major depression, bipolar disorder and schizophrenia. miRNA target enrichment analysis of the selected 12 miRNAs indicates an involvement of miRNAs in nervous system development, neuron projection, neuron projection development and neuron projection morphogenesis. Using this 12-miRNA signature, we differentiate between AD and controls with an accuracy of 93%, a specificity of 95% and a sensitivity of 92%. The differentiation of AD from other neurological diseases is possible with accuracies between 74% and 78%. The differentiation of the other CNS disorders from controls yields even higher accuracies. Conclusions: The data indicate that deregulated miRNAs in blood might be used as biomarkers in the diagnosis of AD or other neurological diseases.

AIMS: Dilated cardiomyopathy (DCM) is one of the leading causes for cardiac transplantations and accounts for up to one-third of all heart failure cases. Since extrinsic and monogenic causes explain only a fraction of all cases, common genetic variants are suspected to contribute to the pathogenesis of DCM, its age of onset, and clinical progression. By a large-scale case-control genome-wide association study we aimed here to identify novel genetic risk loci for DCM. METHODS AND RESULTS: Applying a three-staged study design, we analysed more than 4100 DCM cases and 7600 controls. We identified and successfully replicated multiple single nucleotide polymorphism on chromosome 6p21. In the combined analysis, the most significant association signal was obtained for rs9262636 (P = 4.90 × 10-9) located in HCG22, which could again be replicated in an independent cohort. Taking advantage of expression quantitative trait loci (eQTL) as molecular phenotypes, we identified rs9262636 as an eQTL for several closely located genes encoding class I and class II major histocompatibility complex heavy chain receptors. CONCLUSION: The present study reveals a novel genetic susceptibility locus that clearly underlines the role of genetically driven, inflammatory processes in the pathogenesis of idiopathic DCM. &nbsp

With the recent advances in computational power, realistic modeling of heart function within a clinical environment has come into reach. Yet, current modeling frameworks either lack overall completeness or computational performance, and their integration with clinical imaging and data is still tedious. In this paper, we propose an integrated framework to model heart electromechanics from clinical and imaging data, which is fast enough to be embedded in a clinical setting. More precisely, we introduce data-driven techniques for cardiac anatomy estimation and couple them with an efficient GPU (graphics processing unit) implementation of the orthotropic Holzapfel-Ogden model of myocardium tissue, a GPU implementation of a mono-domain electrophysiology model based on the Lattice-Boltzmann method, and a novel method to correctly capture motion during isovolumetric phases. Benchmark experiments conducted on patient data showed that the computation of a whole heart cycle including electrophysiology and biomechanics with mesh resolutions of around 70k elements takes on average 1min 10s on a standard desktop machine (Intel Xeon 2.4GHz, NVIDIA GeForce GTX 580). We were able to compute electrophysiology up to 40.5× faster and biomechanics up to 15.2× faster than with prior CPU-based approaches, which breaks ground towards model-based therapy planning.

Dilated cardiomyopathies (DCM) show remarkable variability in their age of onset, phenotypic presentation, and clinical course. Hence, disease mechanisms must exist that modify the occurrence and progression of DCM, either by genetic or epigenetic factors that may interact with environmental stimuli. In the present study, we examined genome-wide cardiac DNA methylation in patients with idiopathic DCM and controls. We detected methylation differences in pathways related to heart disease, but also in genes with yet unknown function in DCM or heart failure, namely Lymphocyte antigen 75 (LY75), Tyrosine kinase-type cell surface receptor HER3 (ERBB3), Homeobox B13 (HOXB13) and Adenosine receptor A2A (ADORA2A). Mass-spectrometric analysis and bisulphite-sequencing enabled confirmation of the observed DNA methylation changes in independent cohorts. Aberrant DNA methylation in DCM patients was associated with significant changes in LY75 and ADORA2A mRNA expression, but not in ERBB3 and HOXB13. In vivo studies of orthologous ly75 and adora2a in zebrafish demonstrate a functional role of these genes in adaptive or maladaptive pathways in heart failure.

Background: Genome wide association studies (GWAS) are applied to identify genetic loci, which are associated with complex traits and human diseases. Analogous to the evolution of gene expression analyses, pathway analyses have emerged as important tools to uncover functional networks of genome-wide association data. Usually, pathway analyses combine statistical methods with a priori available biological knowledge. To determine significance thresholds for associated pathways, correction for multiple testing and over-representation permutation testing is applied. Results: We systematically investigated the impact of three different permutation test approaches for over-representation analysis to detect false positive pathway candidates and evaluate them on genome-wide association data of Dilated Cardiomyopathy (DCM) and Ulcerative Colitis (UC). Our results provide evidence that the gold standard - permuting the case–control status – effectively improves specificity of GWAS pathway analysis. Although permutation of SNPs does not maintain linkage disequilibrium (LD), these permutations represent an alternative for GWAS data when case–control permutations are not possible. Gene permutations, however, did not add significantly to the specificity. Finally, we provide estimates on the required number of permutations for the investigated approaches. Conclusions: To discover potential false positive functional pathway candidates and to support the results from standard statistical tests such as the Hypergeometric test, permutation tests of case control data should be carried out. The most reasonable alternative was case–control permutation, if this is not possible, SNP permutations may be carried out. Our study also demonstrates that significance values converge rapidly with an increasing number of permutations. By applying the described statistical framework we were able to discover axon guidance, focal adhesion and calcium signaling as important DCM-related pathways and Intestinal immune network for IgA production as most significant UC pathway.