Identification of potential candidate genes and pathways in atrioventricular nodal reentry tachycardia by whole‐exome sequencing

et al. 2022

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BackgroundAtrioventricular nodal reentrant tachycardia (AVNRT) is a common arrhythmia. Growing evidence suggests that family aggregation and genetic factors are involved in AVNRT. However, in families with a history of AVNRT, disease-causing genes have not been reported.ObjectiveTo investigate the genetic contribution of familial AVNRT using a WES approach.MethodsBlood samples were collected from 20 patients from nine families with a history of AVNRT and 100 control participants, and we systematically analyzed mutation profiles using whole-exome sequencing. Gene-based burden analysis, integration of previous sporadic AVNRT data, pedigree-based co-segregation, protein-protein interaction network analysis, single-cell RNA sequencing, and confirmation of animal phenotype were performed.ResultsAmong 95 reference genes, seven pathogenic genes have been identified both in sporadic and familial AVNRT, including CASQ2, AGXT, ANK2, SYNE2, ZFHX3, GJD3, and SCN4A. Among the 37 reference genes from sporadic AVNRT, five pathogenic genes were identified in patients with both familial and sporadic AVNRT: LAMC1, RYR2, COL4A3, NOS1, and ATP2C2. Considering the unique internal pathogenic gene within pedigrees, three genes, TRDN, CASQ2, and WNK1, were likely to be the pathogenic genes in familial AVNRT. Notably, the core calcium-signaling pathway may be closely associated with the occurrence of AVNRT, including CASQ2, RYR2, TRDN, NOS1, ANK2, and ATP2C2.ConclusionThese results revealed the underlying mechanism for familial AVNRT.

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confidence: 69%

Section: Resultsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Integrative analyses identify potential key genes and calcium-signaling pathway in familial AVNRT using whole-exome sequencing

Huang

et al. 2022

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“…Recently, owing to the advancement in whole exome sequencing (WES), it has been successfully used to discover disease-related genes of for multiple Mendelian or non-Mendelian diseases [9]. However, Genome-Wide Association Studies (GWAS) focuses on common mutations (MAF ≥ 5%), and its impact is small, RR≈1.2-1.5 [10].…”

Section: Introductionmentioning

confidence: 99%

Integrative analyses identify potential key genes and pathways in Keshan disease using whole-exome sequencing

Huang

et al. 2021

Preprint

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Keshan disease (KD), an endemic heart disease with multifocal necrosis and replacement fibrosis of the myocardium, is still a nightmare situation for human health. However, molecular mechanism in the pathogenesis of KD remains unclear. Herein, blood samples were collected from 68 KD patients and 100 controls, and we systematically analyzed mutation profiles using whole-exome sequencing (WES). Causative genes of dilated cardiomyopathy (DCM), gene-based burden analysis, disease and pathway enrichment analysis, and protein-protein interaction (PPI) network analysis were performed. Of the 98 DCM-causative genes, 106 rare variants in 28 genes were detected in KD patients with minor allele frequency (MAF) < 0.001. Gene-based burden analysis, PPI network analysis, and automated Phenolyzer analysis were performed to prioritize 199 candidate genes, which combined with 98 DCM-causative genes, and reference genes from gene microarray or proteomics in KD. Then, 19 candidate pathogenic genes were selected, and 9 candidate genes were identified using PPI analysis, including HIF1A, GART, ALAD, VCL, DTNA, NEXN, INPPL1, NOS3, and JAK2. The 199 candidate genes were further analyzed using disease enrichment with CTD database and PPI analysis, and 21 candidate genes were identified. By combining with disease enrichment and PPI analysis, 7 Selenium (Se)-related genes were further identified, including ALAD, RBM10, GSN, GGT1, ADD1, PARP1, and NOS3. Based on the gene function and data validation, NEXN, TAF1C, FUT4, ALAD, ZNF608, and STX2 were the most likely pathogenic genes in KD. Notably, ALAD is the only candidate pathogenic gene identified by four different analyses, and its homozygous mutant mice could affect heart development and cause death. Keywords: Keshan disease, dilated cardiomyopathy, whole-exome sequencing, gene-based burden analysis, automated Phenolyzer analysis

Identification of potential candidate genes and pathways in atrioventricular nodal reentry tachycardia by whole‐exome sequencing

Clinical & Translational Med

Yang

et al. 2020

Background Atrioventricular nodal reentry tachycardia (AVNRT) is the most common manifestation of paroxysmal supraventricular tachycardia (PSVT). Increasing data have indicated familial clustering and participation of genetic factors in AVNRT, and no pathogenic genes related to AVNRT have been reported. Methods Whole‐exome sequencing (WES) was performed in 82 patients with AVNRT and 100 controls. Reference genes, genome‐wide association analysis, gene‐based collapsing, and pathway enrichment analysis were performed. A protein‐protein interaction (PPI) network was then established; WES database in the UK Biobank and one only genetic study of AVNRT in Denmark were used for external data validation. Results Among 95 reference genes, 126 rare variants in 48 genes were identified in the cases (minor allele frequency < 0.001). Gene‐based collapsing analysis and pathway enrichment analysis revealed six functional pathways related to AVNRT as with neuronal system/neurotransmitter release cycles and ion channel/cardiac conduction among the top 30 enriched pathways, and then 36 candidate pathogenic genes were selected. By combining with PPI analysis, 10 candidate genes were identified, including RYR2, NOS1, SCN1A, CFTR, EPHB4, ROBO1, PRKAG2, MMP2, ASPH, and ABCC8. From the UK Biobank database, 18 genes from candidate genes including SCN1A, PRKAG2, NOS1, and CFTR had rare variants in arrhythmias, and the rare variants in PIK3CB, GAD2, and HIP1R were in patients with PSVT. Moreover, one rare variant of RYR2 (c.4652A > G, p.Asn1551Ser) in our study was also detected in the Danish study. Considering the gene functional roles and external data validation, the most likely candidate genes were SCN1A, PRKAG2, RYR2, CFTR, NOS1, PIK3CB, GAD2, and HIP1R. Conclusion The preliminary results first revealed potential candidate genes such as SCN1A, PRKAG2, RYR2, CFTR, NOS1, PIK3CB, GAD2, and HIP1R, and the pathways mediated by these genes, including neuronal system/neurotransmitter release cycles or ion channels/cardiac conduction, might be involved in AVNRT.