Copy number variants in Ebstein anomaly

Giannakou, Andreas; Sicko, Robert J.; Zhang, Wei Emma; Romitti, Paul A.; Browne, Marilyn L.; Casini, Michèle; Brody, Lawrence C.; Jelliffe‐Pawlowski, Laura L.; Shaw, Gary M.; Kay, Denise M.; Mills, James L.

doi:10.1371/journal.pone.0188168

Cited by 9 publications

(6 citation statements)

References 65 publications

(68 reference statements)

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“…Among 3463 genes with Episcore > 0.6, 1518 have pLI scores < 0.5. Some of these genes have been implicated in human diseases under a dominant model, such as HEY2 32 , ASF1A 33 , and HAND2 34 (Supplementary Table 1 ). Similarly to the ones with low pLI values in the positive training set, these genes have lower background mutation rate (which is primarily determined by transcript size) than the ones with large pLI values (Supplementary Fig.…”

Section: Resultsmentioning

confidence: 99%

Distinct epigenomic patterns are associated with haploinsufficiency and predict risk genes of developmental disorders

et al. 2018

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Haploinsufficiency is a major mechanism of genetic risk in developmental disorders. Accurate prediction of haploinsufficient genes is essential for prioritizing and interpreting deleterious variants in genetic studies. Current methods based on mutation intolerance in population data suffer from inadequate power for genes with short transcripts. Here we show haploinsufficiency is strongly associated with epigenomic patterns, and develop a computational method (Episcore) to predict haploinsufficiency leveraging epigenomic data from a broad range of tissue and cell types by machine learning methods. Based on data from recent exome sequencing studies on developmental disorders, Episcore achieves better performance in prioritizing likely-gene-disrupting (LGD) de novo variants than current methods. We further show that Episcore is less-biased by gene size, and complementary to mutation intolerance metrics for prioritizing LGD variants. Our approach enables new applications of epigenomic data and facilitates discovery and interpretation of novel risk variants implicated in developmental disorders.

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Section: Resultsmentioning

confidence: 99%

Distinct epigenomic patterns are associated with haploinsufficiency and predict risk genes of developmental disorders

et al. 2018

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“…[16][17] Abnormal CUX1 expression is associated with the Ebstein anomaly, which affects cardiomyocytes and myocardium differentiation. 18 IRX6 was associated with point mutations and small insertions/deletions in a Dutch Brugada syndrome cohort. 19 In the current study, a PPI network analysis showed that ASB1 was defined as a hub gene and played important roles in PPIs in HF.…”

Section: Discussionmentioning

confidence: 97%

“…19 In the current study, a PPI network analysis showed that ASB1 was defined as a hub gene and played important roles in PPIs in HF. ASB1 is a member of the ankyrin repeat and SOCS box-containing (ASB) family of proteins (1)(2)(3)(4)(5)(6)(7)(8)(9)(10)(11)(12)(13)(14)(15)(16)(17)(18). The ASB1 gene, located on chromosome 2q37, encodes a protein with 335 amino acids.…”

Section: Discussionmentioning

confidence: 99%

Identification of vital modules and genes associated with heart failure based on weighted gene coexpression network analysis

Bian

Wang

et al. 2022

ESC Heart Failure

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Aims Heart failure (HF) is a chronic heart disease with a high incidence and mortality. Due to the regulatory complexity of gene coexpression networks, the underlying hub genes regulation in HF remain incompletely appreciated. We aimed to explore potential key modules and genes for HF using weighted gene coexpression network analysis (WGCNA). Methods and resultsThe expression profiles by high throughput sequencing of heart tissues samples from HF and non-HF samples were obtained from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) between HF and non-HF samples were firstly identified. Then, a coexpression network was constructed to identify key modules and potential hub genes. The biological functions of potential hub genes were analysed by Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses. Finally, a protein-protein interaction (PPI) network was constructed using the STRING online tool. A total of 135 DEGs (133 up-regulated and 2 down-regulated DEGs) between HF and non-HF samples were identified in the GSE135055 and GSE123976 datasets. Moreover, a total of 38 modules were screened based on WGCNA in the GSE135055 dataset, and six potential hub genes (UCK2, ASB1, CCNI, CUX1, IRX6, and STX16) were screened from the key module by setting the gene significance over 0.2 and the module membership over 0.8. Furthermore, 78 potential hub genes were obtained by taking the intersection of the 135 DEGs and all genes in the key module, and enrichment analysis revealed that they were mainly involved in the MAPK and PI3K-AKT signalling pathways. Finally, in a PPI network constructed with the 78 potential hub genes, CUX1 and ASB1 were identified as hub genes in HF because they were also identified as potential hub genes in the WGCNA. Conclusions To the best of our knowledge, our study is the first to employ WGCNA to identify the key module and hub genes for HF. Our study identified a module and two genes that might play important roles in HF, which may provide potential biomarkers for the diagnosis of HF and improve our knowledge of the molecular mechanisms underlying HF.

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“…Генами-кандидатами являются MYH7 и NKX2-5. У носителей порока нередко выявляется миссенс-мутация FLNA (филамин А, актин-связывающий протеин) на Xq28 [3][4][5][6]. У родственников редко обнаруживаются мутации кардиального фактора транскрипции NKX2-5, делеции 10p13-p14 и 1p34.3-p36.11 [7].…”

Section: распространенность и возможные причинные факторыunclassified

Ebstein's Anomaly

Delyagin¹,

Doctorova²,

Belokrinitskaya³

2022

EPh

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Ebstein’s anomaly is a rare congenital malformation characterized by apical displacement of the right atrioventricular ring with an anomaly of the development of the tricuspid valve and the frequent presence of other heart defects. According to our data, this defect was diagnosed in 2 cases in more than 6 000 sectional studies: in an adult and a child. According to the echocardiography rooms of non-specialized multidisciplinary children's hospitals and children's polyclinics, the defect is detected with a frequency of 1:24.000–1:32.000 studies. Genetic and environmental factors (viral infections, benzodiazepines, lithium) are indicated as probable causes. Clinical signs are cyanosis, shortness of breath, heart failure, cardiac arrhythmias. Morphologically there are abnormalities of the tricuspid valve, papillary muscles and chordal apparatus, right ventricular myocardial hypertrophy, thinning of the walls of the right atrium and atrialized part of the right ventricle. Decisive for the diagnosis is ultrasound. Displacement of the right atrioventricular ring is revealed. The degree of bias determines the severity of the defect. The amplitude of the tricuspid valve movement is increased. Its valve closure occurs later than the mitral. A 40 ms difference between the tricuspid and mitral valve closure points is a diagnostically important sign of Ebstein’s anomaly. The tactics of a doctor are determined by the clinical picture

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Copy number variants in Ebstein anomaly

Cited by 9 publications

References 65 publications

Distinct epigenomic patterns are associated with haploinsufficiency and predict risk genes of developmental disorders

Distinct epigenomic patterns are associated with haploinsufficiency and predict risk genes of developmental disorders

Identification of vital modules and genes associated with heart failure based on weighted gene coexpression network analysis

Ebstein's Anomaly

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