Vanderbilt Genome-Electronic Records Project
Vanderbilt Genome-Electronic Records Project
批准号:
7671509
负责人:
DAN M RODEN
金额:
$165.8万
依托单位:
依托单位国家:
美国
项目类别:
财政年份:
2007
资助国家:
美国
项目状态:
已结题
起止时间:
2007-09-28 至 2011-07-31
关键词:
AddressAreaArrhythmiaArtsBioinformaticsBlood specimenCardiacCardiovascular systemClinical ResearchClinical TrialsCollaborationsCommitCommunicationCommunitiesComputerized Medical RecordDNADataDatabasesDevelopmentDisadvantagedDiseaseDisease susceptibilityEKG QRS ComplexElectrocardiogramElectronicsEthicsGenomeGenomicsGenotypeHealthcareHeart DiseasesInstitutionKnowledgeLeadLegalLinkMeasuresMedical EthicsMedicineMethodsMiningMissionModelingNational Human Genome Research InstituteNatural Language ProcessingNormal RangeOutcomePatient CarePatientsPhenotypePredispositionPrivacyPublic HealthRecordsResearchResearch Ethics CommitteesResearch PersonnelResourcesSamplingScienceStructureSystemTestingTherapeuticTranslational ResearchUpdateValidationVariantVisionclinical careclinical practicedata modelingdata sharingeggendophenotypegenome wide association studyheart rhythmindexingpatient populationphenomerepositorytooltool development
中文摘要
描述(由申请人提供):VGER:范德比尔特基因组-电子记录项目个性化医疗的一个重要潜在资源是DNA库与电子病历(EMR)系统的组合,该系统足够强大,可提供卓越的临床护理,并可作为分析疾病易感性和患者人群治疗结果的资源。范德比尔特EMR是最先进的临床和研究工具(包括> 140万条记录),并与已开发超过3年的DNA储存库相关联;这些是VGER的关键组成部分,VGER是此处提出的范德比尔特基因组电子记录项目。VGER模型从从常规患者护理中收集的废弃血液样本中获取DNA,并可以将这些数据与从EMR中提取并随时更新的去识别数据联系起来。我们将在此分析的表型是心电图上的QRS时限,因为慢传导(由较长的QRS时限表示)是心律失常易感性的标志。这不仅将利用全基因组关联(GWA)方法的力量来产生影响公共卫生关注领域的新生物知识,而且还为开发工具(如自然语言处理方法)提供了一个平台,以优化挖掘EMR。该项目汇集了一组在基因组科学,医学伦理学,生物信息学,去识别科学以及转化和心血管医学方面具有国家认可的成就记录的研究人员,以解决四个具体目标:(1)进行GWA,比较来自QRS持续时间处于正常范围的极端的受试者的样本,并通过在前瞻性确定的临床试验集中对QRS持续时间和心律失常易感性进行基因分型高似然关联进行验证;(2)评估EMR数据的结构化和非结构化成分用于基因组-表型组相关性的有效性和实用性;(3)评估VGER模式的伦理、科学和社会优势和劣势,并确定监督、社区参与的最佳实践,随着资源的增长,数据库和电子病历中的数据的隐私保护和通信;以及(4)为数据库和电子病历中的数据开发和评估正式的隐私保护模型,建立数据共享和集成实践。我们还在这里提出了一项建立行政协调中心的建议,该中心的使命将是促进该网络中的节点、国家人权研究所和外部顾问之间的沟通和合作。我们赞同个性化医疗的愿景,其中基因组和其他患者特定信息驱动个性化,预测性,先发制人和参与式医疗保健,VGER代表了朝着这个方向迈出的重要一步。
英文摘要
DESCRIPTION (provided by applicant): VGER: The Vanderbilt Genome-Electronic Record project An important potential enabling resource for Personalized Medicine is the combination of a DNA repository with Electronic Medical Record (EMR) systems sufficiently robust to provide excellence in clinical care and to serve as resources for analysis of disease susceptibility and therapeutic outcomes across patient populations. The Vanderbilt EMR is a state of the art clinical and research tool (that includes >1.4 million records), and is associated with a DNA repository which has been in development for over 3 years; these are the key components of VGER, the Vanderbilt Genome-Electronic Records project proposed here. The VGER model acquires DNA from discarded blood samples collected from routine patient care, and can link these to de-identified data extracted and readily updated from the EMR. The phenotype we will analyze here is the QRS duration on the electrocardiogram, since slow conduction (indicated by longer QRS duration) is a marker of arrhythmia susceptibility. This will not only exploit the power of Genome-Wide Association (GWA) approaches to generate new biologic knowledge that impacts an area of public health concern, but also provides a platform for the development of tools, such as Natural Language Processing approaches, to optimally mine EMRs. This project brings together a team of investigators with nationally recognized records of accomplishment in genome science, medical ethics, bioinformatics, de-identification science, and translational and cardiovascular medicine to address four Specific Aims: (1) perform a GWA comparing samples from subjects with QRS durations at the extremes of the normal range, and validate by genotyping high likelihood associations in prospectively ascertained clinical trial sets for QRS duration and for arrhythmia susceptibility; (2) evaluate the validity and utility of structured and unstructured components of EMR data for genome-phenome correlations; (3) assess the ethical, scientific, and societal advantages and disadvantages of the VGER model, and determine best practices for oversight, community involvement, and communication as the resource grows; and (4) develop and evaluate formal privacy protection models for data derived from databanks and EMRs, establishing data sharing and integration practices. We also include here a proposal to develop the Administrative Coordinating Center whose mission will be to facilitate communication and collaboration among nodes in this network, the NHGRI, and external advisors. We subscribe to a vision of Personalized Medicine in which genomic and other patient-specific information drives personalized, predictive, preemptive, and participatory health care, and VGER represents an important step in that direction.
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