| 1. |
- Haas, Jan, et al.
(författare)
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Atlas of the clinical genetics of human dilated cardiomyopathy
- 2015
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Ingår i: European Heart Journal. - : Oxford University Press. - 0195-668X .- 1522-9645. ; 36:18, s. 1123-U43
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Tidskriftsartikel (refereegranskat)abstract
- Aim: We were able to show that targeted Next-Generation Sequencing is well suited to be applied in clinical routine diagnostics, substantiating the ongoing paradigm shift from low- to high-throughput genomics in medicine. By means of our atlas of the genetics of human DCM, we aspire to soon be able to apply our findings to the individual patient with cardiomyopathy in daily clinical practice. 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.
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| 2. |
- Corrado, Domenico, et al.
(författare)
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Proposed diagnostic criteria for arrhythmogenic cardiomyopathy : European Task Force consensus report
- 2024
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Ingår i: International Journal of Cardiology. - : Elsevier. - 0167-5273 .- 1874-1754. ; 395
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Tidskriftsartikel (refereegranskat)abstract
- Arrhythmogenic cardiomyopathy (ACM) is a heart muscle disease characterized by prominent "non-ischemic" myocardial scarring predisposing to ventricular electrical instability. Diagnostic criteria for the original phenotype, arrhythmogenic right ventricular cardiomyopathy (ARVC), were first proposed in 1994 and revised in 2010 by an international Task Force (TF). A 2019 International Expert report appraised these previous criteria, finding good accuracy for diagnosis of ARVC but a lack of sensitivity for identification of the expanding phenotypic disease spectrum, which includes left-sided variants, i.e., biventricular (ABVC) and arrhythmogenic left ventricular cardiomyopathy (ALVC). The ARVC phenotype together with these left-sided variants are now more appropriately named ACM. The lack of diagnostic criteria for the left ventricular (LV) phenotype has resulted in clinical under-recognition of ACM patients over the 4 decades since the disease discovery. In 2020, the "Padua criteria" were proposed for both right-and left-sided ACM phenotypes. The presently proposed criteria represent a refinement of the 2020 Padua criteria and have been developed by an expert European TF to improve the diagnosis of ACM with upgraded and internationally recognized criteria. The growing recognition of the diagnostic role of CMR has led to the incorporation of myocardial tissue characterization findings for detection of myocardial scar using the late-gadolinium enhancement (LGE) technique to more fully characterize right, biventricular and left disease variants, whether genetic or acquired (phenocopies), and to exclude other "non-scarring" myocardial disease. The "ring-like' pattern of myocardial LGE/scar is now a recognized diagnostic hallmark of ALVC. Additional diagnostic criteria regarding LV depolarization and repolarization ECG abnor-malities and ventricular arrhythmias of LV origin are also provided. These proposed upgrading of diagnostic criteria represents a working framework to improve management of ACM patients.
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| 3. |
- Elliott, Perry, et al.
(författare)
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Classification of the cardiomyopathies: a position statement from the European Society Of Cardiology Working Group on Myocardial and Pericardial Diseases.
- 2008
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Ingår i: European heart journal. - : Oxford University Press (OUP). - 0195-668X .- 1522-9645. ; 29:2, s. 270-6
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Tidskriftsartikel (refereegranskat)abstract
- In biology, classification systems are used to promote understanding and systematic discussion through the use of logical groups and hierarchies. In clinical medicine, similar principles are used to standardise the nomenclature of disease. For more than three decades, heart muscle diseases have been classified into primary or idiopathic myocardial diseases (cardiomyopathies) and secondary disorders that have similar morphological appearances, but which are caused by an identifiable pathology such as coronary artery disease or myocardial infiltration (specific heart muscle diseases). In this document, The European Society of Cardiology Working Group on Myocardial and Pericardial Diseases presents an update of the existing classification scheme. The aim is to help clinicians look beyond generic diagnostic labels in order to reach more specific diagnoses.
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| 4. |
- Shakur, Rameen, et al.
(författare)
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Prognostic implications of troponin T variations in inherited cardiomyopathies using systems biology
- 2021
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Ingår i: npj Genomic Medicine. - : Springer Science and Business Media LLC. - 2056-7944. ; 6:1
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Tidskriftsartikel (refereegranskat)abstract
- The cardiac troponin T variations have often been used as an example of the application of clinical genotyping for prognostication and risk stratification measures for the management of patients with a family history of sudden cardiac death or familial cardiomyopathy. Given the disparity in patient outcomes and therapy options, we investigated the impact of variations on the intermolecular interactions across the thin filament complex as an example of an unbiased systems biology method to better define clinical prognosis to aid future management options. We present a novel unbiased dynamic model to define and analyse the functional, structural and physico-chemical consequences of genetic variations among the troponins. This was subsequently integrated with clinical data from accessible global multi-centre systematic reviews of familial cardiomyopathy cases from 106 articles of the literature: 136 disease-causing variations pertaining to 981 global clinical cases. Troponin T variations showed distinct pathogenic hotspots for dilated and hypertrophic cardiomyopathies; considering the causes of cardiovascular death separately, there was a worse survival in terms of sudden cardiac death for patients with a variation at regions 90–129 and 130–179 when compared to amino acids 1–89 and 200–288. Our data support variations among 90–130 as being a hotspot for sudden cardiac death and the region 131–179 for heart failure death/transplantation outcomes wherein the most common phenotype was dilated cardiomyopathy. Survival analysis into regions of high risk (regions 90–129 and 130–180) and low risk (regions 1–89 and 200–288) was significant for sudden cardiac death (p = 0.011) and for heart failure death/transplant (p = 0.028). Our integrative genomic, structural, model from genotype to clinical data integration has implications for enhancing clinical genomics methodologies to improve risk stratification.
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