Identification of Novel Variants And Genes Causing Thoracic Aortic Disease
导致胸主动脉疾病的新变异和基因的鉴定
基本信息
- 批准号:10389043
- 负责人:
- 金额:$ 4.93万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2022
- 资助国家:美国
- 起止时间:2022-09-01 至 2024-08-31
- 项目状态:已结题
- 来源:
- 关键词:AffectAneurysmAortaAortic AneurysmAortic DiseasesAortic SegmentAtherosclerosisCandidate Disease GeneCause of DeathCellsCessation of lifeChestClinicalClinical DataDNADNA Sequence AlterationDNA sequencingDataDescending aortaDevelopmentDiseaseDissectionEmbryoEtiologyFamilyFamily memberFrequenciesGene ExpressionGene Expression ProfileGenesGeneticGenetic DiseasesGenetic Predisposition to DiseaseGenomic medicineGenomicsHuman GeneticsIndividualLeadMYLK geneMedicalMusMutationNatural HistoryOperative Surgical ProceduresPathogenicityPatientsPopulation ControlPrognosisPublic HealthReportingRiskRoleRuptureSamplingStatistical Data InterpretationStatistical MethodsSurgical ManagementSusceptibility GeneTestingThoracic Aortic AneurysmTrainingUnited StatesVariantascending aortabasebioinformatics pipelinecase controlcell typeclinical phenotypeclinical sequencingcohortdiagnostic accuracydifferential expressionexome sequencinggene discoverygenetic analysisgenetic predictorsgenetic testinggenetic variantgenomic datahuman old age (65+)improvedin silicoinnovationmolecular subtypesnovelpersonalized careprecision medicinepreventprogramsrepairedrisk variantsegregationsingle-cell RNA sequencingskillstranscriptome sequencingtranscriptomicsvariant of unknown significance
项目摘要
PROJECT SUMMARY/ABSTRACT
IDENTIFICATION OF NOVEL VARIANTS AND GENES CAUSING THORACIC AORTIC DISEASE
Aortic diseases are among the top 20 causes of death in the US. Thoracic aortic aneurysms are rarely
symptomatic and often not detected until they dissect or rupture. One fifth of all cases of thoracic aortic aneurysm
and dissection (TAAD) are familial, and 20-30% of these are associated with a known, germline genetic variant.
The other 70-80% may be due to genes not yet identified. Identifying disease-causing variants and novel risk
genes is important for preventing aortic-related complications or deaths by identifying at risk family members. In
preliminary studies, we conducted exome sequencing in 303 TAAD patients and identified pathogenic variants
in genes known to cause TAAD in 3% of patients and variants of uncertain significance (VUS) in 26%. We
hypothesize that: (1) Many of our identified VUS are disease-causing pathogenic variants and many other new
pathogenic variants in known TAAD risk genes are likely to be discovered, and (2) There are additional novel
genes causing TAAD in our cohort. The aims of the study are to: (1) Identify potential pathogenic variants in
known or candidate TAAD risk genes by integrating genomic and clinical data; (2) Characterize cell-type specific
gene expression patterns in the normal developing mouse ascending aorta; (3) Identify novel TAAD risk genes
through case-control association of rare damaging variants and integrative analysis of genetic and transcriptomic
data and characterize clinical phenotypes of patients carrying mutations in novel risk genes. For this project,
DNA samples for a total of 1507 patients with TAAD have been collected and are currently undergoing exome
sequencing. We will use novel in silico predictors of pathogenicity and family segregation studies to assess
variants in known TAAD risk genes. To identify novel TAAD risk genes, we will use statistical methods to integrate
case-control association of rare damaging variants with gene expression data. In particular, we will quantify gene
expression through bulk and single cell RNA-seq of developing ascending aorta in E15.5 mice, and then identify
cell types associated with TAAD by analysis of known and candidate genes with cell-type specific expression. In
parallel, we will compare cases with a large set of population controls with comparable exome sequencing data
in case-control association analysis. Finally, we will use expression level in relevant cell types to further improve
the power and sensitivity of risk gene identification, with the hypothesis that true risk genes are highly expressed
in one or multiple cell types relevant to the disease. For novel candidate risk genes, we will characterize the
clinical phenotypes of patients who carry damaging variants in these genes. This study will provide training in
human genetics, computational genomics, and precision medicine to gain expertise in analyzing large-scale
genomic data derived from DNA- and RNA-sequencing and will apply these skills to identify novel disease-
causing genes for thoracic aortic aneurysms.
项目总结/文摘
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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Bulat A. Ziganshin其他文献
Nonusefulness of Antithrombotic Therapy After Surgical Bioprosthetic Aortic Valve Replacement
- DOI:
10.1016/j.amjcard.2020.05.018 - 发表时间:
2020-08-15 - 期刊:
- 影响因子:
- 作者:
Anton A. Gryaznov;Ayman Saeyeldin;Mohamad Abdelbaky;Mohammad A. Zafar;Maryam Tanweer;Dimitra Papanikolaou;Mahnoor Imran;Yupeng Li;Bulat A. Ziganshin;John A. Elefteriades - 通讯作者:
John A. Elefteriades
A machine learning approach for predicting complications in descending and thoracoabdominal aortic aneurysms
- DOI:
10.1016/j.jtcvs.2021.12.045 - 发表时间:
2023-10-01 - 期刊:
- 影响因子:
- 作者:
Nicolai P. Ostberg;Mohammad A. Zafar;Sandip K. Mukherjee;Bulat A. Ziganshin;John A. Elefteriades - 通讯作者:
John A. Elefteriades
Direct measurement of ascending aortic diameter by intraoperative caliper assessment
- DOI:
10.1016/j.jtcvs.2020.08.001 - 发表时间:
2021-02-01 - 期刊:
- 影响因子:
- 作者:
Thais Faggion Vinholo;Mohammad A. Zafar;Dimitra Papanikolaou;Juyeon Chung;Hesham Ellauzi;Bulat A. Ziganshin;John A. Elefteriades - 通讯作者:
John A. Elefteriades
Bovine Aortic Arch: A Result of Chance or Mandate of Inheritance?
- DOI:
10.1016/j.amjcard.2022.02.030 - 发表时间:
2022-06-01 - 期刊:
- 影响因子:
- 作者:
Michael Shang;Thais Faggion Vinholo;Joelle Buntin;Mohammad A. Zafar;Bulat A. Ziganshin;John A. Elefteriades - 通讯作者:
John A. Elefteriades
Aortic Size at the Time of Type A and Type B Dissections
- DOI:
10.1016/j.athoracsur.2023.03.037 - 发表时间:
2023-08-01 - 期刊:
- 影响因子:
- 作者:
Zachary G. Perez;Mohammad A. Zafar;Juan J. Velasco;Alexandra Sonsino;Hesham Ellauzi;Clerin John;Asanish Kalyanasundaram;Bulat A. Ziganshin;John A. Elefteriades - 通讯作者:
John A. Elefteriades
Bulat A. Ziganshin的其他文献
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{{ truncateString('Bulat A. Ziganshin', 18)}}的其他基金
Identification of Novel Variants And Genes Causing Thoracic Aortic Disease
导致胸主动脉疾病的新变异和基因的鉴定
- 批准号:
10733412 - 财政年份:2022
- 资助金额:
$ 4.93万 - 项目类别:
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