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Genetics of arrhythmic mitral valve prolapse: large pedigree collection within the UCSF MVP registry

Genetics of arrhythmic mitral valve prolapse: large pedigree collection within the UCSF MVP registry
心律失常二尖瓣脱垂的遗传学:UCSF MVP 登记处的大量谱系收集
批准号:
10850759
负责人:
Francesca N Delling
金额:
$77.5万
依托单位国家:
美国
项目类别:
财政年份:
2020
资助国家:
美国
项目状态:
未结题
起止时间:
2020-05-26 至 2025-04-30
关键词:
18 year old3-DimensionalATAC-seqAdministrative SupplementAdultAffectAmbulatory MonitoringArrhythmiaBiological AssayBiological ModelsCardiacCardiac Electrophysiologic TechniquesCardiomyopathiesCase StudyCell Culture TechniquesCell modelCharacteristicsCiliaClinicalCollectionComplexComputer ModelsDataData SetDetectionDevelopmentDiffuseDiseaseEchocardiographyEducational workshopElectrocardiogramEmbryoFLNC geneFamilyFamily memberFibrosisFoundationsFutureGadoliniumGeneral PopulationGenerationsGenesGeneticGenetic DeterminismGenetic MarkersGenetic studyGenotypeGenotype-Tissue Expression ProjectGoalsHeart ArrestHolter ElectrocardiographyImageImplantable DefibrillatorsIn VitroIndividualInheritedInstitutionInvestigationKnock-inLeftLifeLinkMagnetic ResonanceMalignant - descriptorMapsMechanicsMemoryMinorityMitral ValveMitral Valve InsufficiencyMitral Valve ProlapseMutationMyocardialMyopathyNational Heart, Lung, and Blood InstituteNeonatalOutcomeOutcome StudyParticipantPathogenicityPathologyPatientsPhenotypePreventionPrimary PreventionProteinsRegistriesResearchRiskTestingUnited StatesVariantVentricularVentricular ArrhythmiaWifecardiac magnetic resonance imagingcohortcoronary fibrosisdata modelingdemographicsexome sequencinggenetic pedigreegenetic variantgenome wide association studyheart imagingimaging biomarkerin vivomultimodalitynovelphenotypic biomarkerpredictive markerprobandprospectiveprotein expressionrecruitrisk prediction modelrisk stratificationscreeningsegregationsudden cardiac death

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中文摘要
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英文摘要
PROJECT SUMMARY Mitral valve prolapse (MVP) is a common valvulopathy with a strong hereditary component affecting over 7 million individuals in the United States. Every year, up to 1.8% of MVPs will develop sudden cardiac arrest (SCA) or sudden cardiac death (SCD). In prior studies, SCD/SCA in MVP has either been linked to severe mitral regurgitation (MR) or to a malignant bileaflet phenotype with mild MR, mitral annular disjunction (MAD) and abnormal valvular-myocardial mechanics leading to complex ventricular ectopy (ComVE) and/or left ventricular replacement fibrosis [late gadolinium enhancement or LGE by cardiac magnetic resonance (CMR) imaging]. We have shown, supported by an ongoing R01, that diffuse fibrosis by CMR/T1 mapping is linked to increased arrhythmic risk, regardless of bileaflet phenotype, severe MR, or presence of LGE. Hence, arrhythmic MVP may not be a “pure” valvulopathy, but rather a component of a primary subclinical myopathy. In addition to mutations in cilia-related genes (DCHS1, TNS1, LMCD1, DZIP1) previously described in “general” MVP, cardiomyopathy or channelopathy genes (FLNC, LMNA, ALPK3, SCN5A) have been recently proposed in arrhythmic MVP, albeit in case reports, or GWAS studies with heterogeneous presentations. Through an ongoing R01 and an expanding MVP registry at our institution, we have identified a total of 14 arrhythmic MVP probands and pedigrees, and 50 sporadic arrhythmic MVP cases. In this administrative supplement application, we seek to complete whole exome sequencing, arrhythmic characterization, and CMR in a minority of family members that have yet to undergo these investigations. Our central hypothesis is that among MVP genetic variants, cardiomyopathy or channelopathy genes act alone or in combination with cilia- related variants to increase the risk of SCD/SCA in MVP. To test our central hypothesis and accomplish our overall objective, we propose the following Specific Aims: Aim 1: To identify clinical features and genetic determinants of arrhythmic risk in MVP SCD/SCA pedigrees, and Aim 2: To test pathogenicity of genetic variants and understand mechanisms of arrhythmic MVP using protein expression data and cell model assays. Data obtained through this administrative supplement is essential for better MVP SCD/SCA risk stratification, thus enabling future prevention of SCD via ICD placement in appropriately selected MVP patients. Use of cell model assays to validate our genetic findings is essential to understand arrhythmogenesis in MVP patients. Our proposal is motivated by a recent NHLBI workshop on research opportunities in MVP and the CAROL Act in memory of a US congressman’s wife who died suddenly from MVP.
期刊论文(8)
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科研奖励(0)
会议论文
DOI: 10.3389/fcvm.2021.574446
发表时间: 2021
期刊: Frontiers in cardiovascular medicine
影响因子: 3.6
作者: [Tayal B, Delling FN, Malahfji M, Shah DJ]
通讯作者: Shah DJ
Interstitial Fibrosis and Arrhythmic Mitral Valve Prolapse: Unravelling Sex-Based Differences.
间质纤维化和心律失常二尖瓣脱垂:揭示性别差异。
DOI: 10.1101/2024.01.12.24301217
发表时间: 2024
期刊: medRxiv : the preprint server for health sciences
影响因子: --
作者: [Tastet,Lionel, Dixit,Shalini, Nguyen,Thuy, Lim,LisaJ, Al-Akchar,Mohammad, Bibby,Dwight, Arya,Farzin, Cristin,Luca, Anwar,Shafkat, Higuchi,Satoshi, Hsia,Henry, Lee,YooJin, Delling,FrancescaN]
通讯作者: Delling,FrancescaN
Mechanical Dispersion Discriminates Between Arrhythmic and Nonarrhythmic Sudden Death: From the POST SCD Study.
机械弥散区分心律失常性和非心律失常性猝死:来自 POST SCD 研究。
DOI: 10.1016/j.jacep.2024.01.002
发表时间: 2024
期刊: JACC. Clinical electrophysiology
影响因子: --
作者: [Tastet,Lionel, Ramakrishna,Satvik, Lim,LisaJ, Bibby,Dwight, Olgin,JeffreyE, Connolly,AndrewJ, Moffatt,Ellen, Tseng,ZianH, Delling,FrancescaN]
通讯作者: Delling,FrancescaN
Sex Differences and Similarities in Valvular Heart Disease.
瓣膜心脏病的性别差异和相似之处。
DOI: 10.1161/circresaha.121.319914
发表时间: 2022-02-18
期刊: Circulation research
影响因子: 20.1
作者: [DesJardin JT, Chikwe J, Hahn RT, Hung JW, Delling FN]
通讯作者: Delling FN
8
    Prospective sudden cardiac death risk stratification using CMR and echocardiography machine learning in mitral valve prolapse
    Prospective sudden cardiac death risk stratification using CMR and echocardiography machine learning in mitral valve prolapse
    Prospective sudden cardiac death risk stratification using CMR and echocardiography machine learning in mitral valve prolapse
    Prospective sudden cardiac death risk stratification using CMR and echocardiography machine learning in mitral valve prolapse
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