Dilated cardiomyopathy – details make the difference

McGurk, Kathryn A; Halliday, Brian P

doi:10.1002/ejhf.2586

Cited by 4 publications

(2 citation statements)

References 16 publications

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“…; https://doi.org/10.1101/2023.03. 15.23287112 doi: medRxiv preprint Variant-specific estimates of penetrance are required to appropriately inform clinical practice and to fully utilise genetics as a tool to individualise the risk of developing disease in asymptomatic carriers 6,23 . It is challenging to estimate the penetrance of individual rare variants through other study methods as longitudinal population studies require very large sample sizes and long-term follow-up is required if penetrance is agerelated.…”

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confidence: 99%

The penetrance of rare variants in cardiomyopathy-associated genes: a cross-sectional approach to estimate penetrance for secondary findings

McGurk

Zhang

Theotokis

et al. 2023

Preprint

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Understanding the penetrance of pathogenic variants identified as secondary findings (SFs) is of paramount importance with the growing availability of genetic testing. We estimated penetrance through large-scale analyses of patients referred for diagnostic sequencing for hypertrophic cardiomyopathy (HCM; 10,400 cases, 1,340 variants) and dilated cardiomyopathy (DCM; 2,564 cases, 665 variants), using a cross-sectional approach comparing allele frequencies against reference populations (293,226 participants from UK Biobank and gnomAD). We generated updated prevalence estimates for HCM (1:543) and DCM (1:220). In aggregate, the penetrance by late adulthood of rare, pathogenic variants (23% for HCM, 35% for DCM) and likely pathogenic variants (7% for HCM, 10% for DCM) was substantial for dominant CM. Penetrance was significantly higher for variant subgroups annotated as loss of function or ultra-rare, and for males compared to females for variants in HCM-associated genes. We estimated variant-specific penetrance for 316 recurrent variants most likely to be identified as SFs (51% HCM and 17% DCM cases). 49 variants were observed at least ten times (14% of cases) in HCM-associated genes. Median penetrance was 14.6% (±14.4% SD). We explore estimates of penetrance by age, sex, and ancestry, and simulate the impact of including future cohorts. This dataset is the first to report penetrance of individual variants at scale and will inform the management of individuals undergoing genetic screening for SFs. While most variants had low penetrance and the costs and harms of screening are unclear, some carriers of highly penetrant variants may benefit from SFs.

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Section: (Which Was Not Certified By Peer Review)mentioning

confidence: 99%

The penetrance of rare variants in cardiomyopathy-associated genes: a cross-sectional approach to estimate penetrance for secondary findings

McGurk

Zhang

Theotokis

et al. 2023

Preprint

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“…Dilated cardiomyopathy is a common heart disease that is mainly caused by cardiac injury and apoptosis and increased ventricular wall thickness ( 1 ). Its etiology is unclear, but it may be related to genetic and environmental factors ( 2 , 3 ). It is estimated that there are approximately 25 million new cases each year ( 4 ).…”

Section: Introductionmentioning

confidence: 99%

Selection of key genes for dilated cardiomyopathy based on machine learning algorithms and assessment of diagnostic accuracy

Chen,

Xuan,

et al. 2023

J Thorac Dis

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Background The mechanisms of the occurrence and progression of dilated cardiomyopathy are still unclear and further exploration is needed. The upgrading of programming languages and the improvement of biological databases have created conditions for us to explore the structural and functional information of biological molecules at the nucleic acid and protein levels, screen key pathogenic genes, and elucidate pathogenic mechanisms. This study aimed to screen key pathogenic genes using machine learning algorithms and explore the correlation between key genes and immune microenvironment through transcriptome sequencing data sets of myocardial samples from patients with dilated cardiomyopathy, providing new ideas for elucidating the pathogenesis of the disease. Methods The transcriptome sequencing data sets of heart tissue from patients with dilated cardiomyopathy were downloaded from the Gene Expression Omnibus (GEO) database (GSE29819 and GSE21610). Differentially expressed genes (DEGs) were screened between pathological and normal tissues. The key genes were screened using least absolute shrinkage and selection operator (LASSO) regression analysis and random forest tree algorithms. The diagnostic efficiency of the key genes for the disease was evaluated using the receiver operating characteristic (ROC) curve. Results Compared with the normal heart tissue (control group) samples, there were 213 DEGs in the heart tissue samples of patients with dilated cardiomyopathy (treat group), including 101 upregulated and 102 downregulated genes. CCL5 and CTGF were highly expressed in the treat group compared to the control group. The ROC curve showed that the areas under the curve (AUCs) of CCL5 and CTGF were 0.821 and 0.902, respectively (P<0.05). In the treat group samples, CCL5 was positively correlated with the infiltration content of most immune cell subtypes. Conclusions CCL5 and CTGF are key disease-causing genes in dilated cardiomyopathy and have good diagnostic efficiency for the disease. CCL5 and CTGF may be related to immune cell enrichment and myocardial fibrosis, respectively.

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The penetrance of rare variants in cardiomyopathy-associated genes: A cross-sectional approach to estimating penetrance for secondary findings

McGurk,

Zhang,

Theotokis

et al. 2023

The American Journal of Human Genetics

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Dilated cardiomyopathy – details make the difference

Cited by 4 publications

References 16 publications

The penetrance of rare variants in cardiomyopathy-associated genes: a cross-sectional approach to estimate penetrance for secondary findings

The penetrance of rare variants in cardiomyopathy-associated genes: a cross-sectional approach to estimate penetrance for secondary findings

Selection of key genes for dilated cardiomyopathy based on machine learning algorithms and assessment of diagnostic accuracy

The penetrance of rare variants in cardiomyopathy-associated genes: A cross-sectional approach to estimating penetrance for secondary findings

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