6 research outputs found

    Epigenetic Regulation of Alternative mRNA Splicing in Dilated Cardiomyopathy

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    In recent years, the genetic architecture of dilated cardiomyopathy (DCM) has been more thoroughly elucidated. However, there is still insufficient knowledge on the modifiers and regulatory principles that lead to the failure of myocardial function. The current study investigates the association of epigenome-wide DNA methylation and alternative splicing, both of which are important regulatory principles in DCM. We analyzed screening and replication cohorts of cases and controls and identified distinct transcriptomic patterns in the myocardium that differ significantly, and we identified a strong association of intronic DNA methylation and flanking exons usage (p < 2 × 10−16). By combining differential exon usage (DEU) and differential methylation regions (DMR), we found a significant change of regulation in important sarcomeric and other DCM-associated pathways. Interestingly, inverse regulation of Titin antisense non-coding RNA transcript splicing and DNA methylation of a locus reciprocal to TTN substantiate these findings and indicate an additional role for non-protein-coding transcripts. In summary, this study highlights for the first time the close interrelationship between genetic imprinting by DNA methylation and the transport of this epigenetic information towards the dynamic mRNA splicing landscape. This expands our knowledge of the genome–environment interaction in DCM besides simple gene expression regulation

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

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    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 compre hensive 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 lim ited. 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

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

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    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

    SARS-CoV-2 Infects Human Engineered Heart Tissues and Models COVID-19 Myocarditis.

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    There is ongoing debate as to whether cardiac complications of coronavirus disease-2019 (COVID-19) result from myocardial viral infection or are secondary to systemic inflammation and/or thrombosis. We provide evidence that cardiomyocytes are infected in patients with COVID-19 myocarditis and are susceptible to severe acute respiratory syndrome coronavirus 2. We establish an engineered heart tissue model of COVID-19 myocardial pathology, define mechanisms of viral pathogenesis, and demonstrate that cardiomyocyte severe acute respiratory syndrome coronavirus 2 infection results in contractile deficits, cytokine production, sarcomere disassembly, and cell death. These findings implicate direct infection of cardiomyocytes in the pathogenesis of COVID-19 myocardial pathology and provides a model system to study this emerging disease

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

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    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
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