Understanding modifiers of mendelian mutation penetrance using familial hypercholesterolemia as a model
Understanding modifiers of mendelian mutation penetrance using familial hypercholesterolemia as a model
批准号:
9431712
负责人:
Pradeep Natarajan
金额:
$17.33万
依托单位国家:
美国
项目类别:
财政年份:
2017
资助国家:
美国
项目状态:
已结题
起止时间:
2017-12-07 至 2022-11-30
关键词:
AdultAffectAfricanAlgorithmsAmishBachelor&aposs DegreeBiochemicalCardiologyCardiovascular DiseasesCardiovascular systemCatalogsCause of DeathClinicClinicalClinical InformaticsCloud ComputingCollaborationsComputer SimulationCoronary ArteriosclerosisCoronary heart diseaseDNA sequencingDataData SetDevelopmentDiscriminationDiseaseDisease PathwayElectronic Health RecordElementsEnvironmentEnvironmental Risk FactorEthnic OriginEuropeanEvaluationExposure toFamilial HypercholesterolemiaFamily history ofFoundationsFundingGene MutationGeneral HospitalsGenerationsGeneticGenetic CounselingGenetic DiseasesGenomicsGenotypeGoalsGoldHealthcareHumanHuman GeneticsIndividualInstitutesInternal MedicineInvestigationK-Series Research Career ProgramsKnowledgeLDL Cholesterol LipoproteinsLeadLeadershipLinkLipidsLow-Density LipoproteinsMachine LearningMassachusettsMaster&aposs DegreeMediator of activation proteinMedicalMedicineMendelian disorderMentorshipMethodsModelingMolecular BiologyMutationNational Heart, Lung, and Blood InstituteNational Human Genome Research InstituteNetwork-basedPathogenicityPathway AnalysisPathway interactionsPenetrancePhenotypePhysiciansPhysiologicalPopulationPositioning AttributePrevalencePreventionPrevention strategyPreventivePreventive therapyPrincipal InvestigatorQuality ControlResearchRiskRisk stratificationScientistSolidStatistical ModelsTechnologyTestingTimeTrainingTrans-Omics for Precision MedicineUnited StatesUnited States National Institutes of HealthVariantVeteransWorkbasebiobankbiomedical informaticscareer developmentcloud basedcohortdisorder riskexperiencegenetic analysisgenome sequencinggenomic variationheart disease riskhigh riskhuman diseasehuman genomicshypercholesterolemiaimprovedin vivoinsightlifestyle factorsmetabolomicsnext generationnon-geneticnovelnovel strategiesprecision medicinepredictive modelingprematureprogramspublic health relevanceskillssuccesssymposiumtraitwhole genome
中文摘要
项目总结/摘要
常见疾病的罕见单基因形式提供了关于常见疾病的关键基本见解。
然而,遗传,环境和随机因素影响疾病的风险。家族性
高胆固醇血症(FH)是一种常染色体显性遗传疾病,250例患者中有1例与高胆固醇血症(FH)严重增加有关。
LDL胆固醇与早发冠心病(CHD)风险的关系,是表征修饰剂的理想模型
疾病。尽管存在来自FH突变的高胆固醇血症的强烈遗传驱动因素,我们
最近观察到一半人没有出现预期的严重高胆固醇血症。在这份提案中,我们概述了
几种方法来发现和剖析影响冠心病风险的遗传和非遗传因素,
人类FH突变,并确定这些因素的知识是否可以改善风险识别
在那些有FH突变的人中我们的方法利用了几个多维数据集:全基因组
序列、代谢组学、横截面和纵向心血管表型。在目标1中,我们
聚合和管理75,000个深度(30倍)全基因组序列和心血管表型。在目标2中,
我们将发现遗传和非遗传修饰的低密度脂蛋白胆固醇和冠心病的风险,在FH和评估其
代谢组学后果。在目标3中,我们将开发一种结合遗传学和纵向非遗传学的方法。
百万退伍军人计划中约4,000名FH突变患者中CHD风险分层的遗传暴露。
除了拟议的目标外,这份五年期提案还概述了一项全面战略,
研究者(PI)在学术心血管医学方面的科学和专业发展。的
研究策略建立在PI先前的研究经验和临床培训的基础上。除了一个
本科学位的分子生物学和硕士学位的生物医学信息学,他完成后,
内科和心血管医学的研究生医学培训。他最近开发了一种新的
预防/遗传心脏病诊所,重点是评估和管理那些有或有家庭的人
在马萨诸塞州总医院(MGH)有早发CHD病史,包括FH患者。这项建议
现在专注于将他在人类遗传学和基因组学方面的科学技能扩展到新的领域:
基因组学、统计遗传学、临床信息学和风险建模。职业发展目标将在
通过多方面的方法实现,包括指导,合作,教学课程,
会议和科学调查。这项工作将在一个独特的培训环境中进行,
MGH和布罗德研究所。成功完成此职业发展奖将导致
改善对CHD决定因素的基本理解,导致PI过渡到
独立的物理学家,科学家,并提供了一个坚实的基础,他将申请R 01级的资金。
英文摘要
PROJECT SUMMARY / ABSTRACT
Rare monogenic forms of common diseases have provided key fundamental insights about common disease.
However, genetic, environmental, and stochastic elements influence risk for disease. Familial
hypercholesterolemia (FH), an autosomal dominant disorder afflicting 1 in 250 linked to severe increases in
LDL cholesterol and premature coronary heart disease (CHD) risk, is an ideal model to characterize modifiers
of disease. Despite the presence of a strong genetic driver of hypercholesterolemia from FH mutations, we
recently observed that half do not have the expected severe hypercholesterolemia. In this proposal, we outline
several methods to discover and dissect the genetic and non-genetic factors influencing CHD risk conferred by
FH mutations in humans and determine whether knowledge of these factors can improve risk discrimination
among those with FH mutations. Our approach harnesses several multi-dimensional datasets: whole genome
sequences, metabolomics, and cross-sectional and longitudinal cardiovascular phenotypes. In Aim 1, we will
aggregate and curate 75,000 deep (30X) whole genome sequences and cardiovascular phenotypes. In Aim 2,
we will discover genetic and non-genetic modifiers of LDL cholesterol and CHD risk in FH and evaluate their
metabolomic consequences. In Aim 3, we will develop a method incorporating genetics and longitudinal non-
genetic exposures for CHD risk stratification among ~4,000 with FH mutations in the Million Veteran Program.
In addition to the proposed Aims, this five-year proposal outlines a comprehensive strategy for the principal
investigator's (PI's) scientific and professional development in academic cardiovascular medicine. The
research strategy builds upon the PI's prior research experience and clinical training. In addition to an
undergraduate degree in Molecular Biology and master's degree in Biomedical Informatics, he completed post-
graduate medical training in Internal Medicine and Cardiovascular Medicine. He recently developed a new
preventive/genetic cardiology clinic focusing on the evaluation and management of those with or a family
history of premature CHD, including those with FH, at Massachusetts General Hospital (MGH). This proposal
now focuses on expanding his scientific skills in human genetics and genomics into new domains: integrative
genomics, statistical genetics, clinical informatics, and risk modeling. The career development goals will be at
achieved through a multi-faceted approach involving mentorship, collaboration, didactic coursework,
conferences, and scientific investigation. This work will take place in a unique training environment comprised
of MGH and the Broad Institute. Successful completion of this career development award will result in
improved fundamental understanding of the determinants of CHD, result in the PI's transition to an
independent physician-scientist, and provide a solid foundation from which he will apply for R01-level funding.
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