Genetic Discovery and Application in a Clinical Setting Continuing a Partnership

基因发现及其在临床环境中的应用继续合作

• 批准号: 8192387
• 负责人: Gail Pairitz Jarvik
• 金额: $ 81.88万
• 依托单位: KAISER FOUNDATION HEALTH PLAN OF WASHINGTON
• 依托单位国家: 美国
• 财政年份: 2011
• 资助国家: 美国
• 起止时间: 2011-08-15 至 2015-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8192387
• 关键词: Address; Adoption; Adverse event; Algorithms; Anemia; Antihypertensive Agents; Bioethics; Blood Pressure; Bone Marrow Diseases; Caregivers; Caring; Chromosome abnormality; Clinical; Clinical Research; Clostridium difficile; Collaborations; Communicable Diseases; Communities; Computerized Medical Record; Consent; DNA; Data; Development; Diabetes Mellitus; Diarrhea; Disease; Disease susceptibility; Dysmyelopoietic Syndromes; Ensure; Epidemiology; Evidence Based Medicine; Excision; Focus Groups; Fostering; Funding; Genetic; Genetic Polymorphism; Genomics; Goals; HLA Antigens; Health; Health system; Healthcare; Hematocrit procedure; Herpes zoster disease; Herpesvirus Type 3; Incidental Findings; Individual; Infection; Karyotype; Knowledge; Leadership; Libraries; Link; Low-Density Lipoproteins; Medical; Medical Records; Medical center; Medicine; Mental Depression; Methods; Mining; Modeling; Nail plate; Natural Language Processing; Needs Assessment; Other Genetics; Outcome; Oxidoreductase; Patient Care; Patients; Pharmaceutical Preparations; Pharmacy facility; Phenotype; Policies; Population; Positioning Attribute; Predisposition; Preventive; Primary Health Care; Principal Investigator; Qualifying; Reaction; Research; Research Personnel; Resources; Serotonin; Single Nucleotide Polymorphism; Site; Solutions; Systems Biology; Technology; Testing; Therapeutic; United States National Institutes of Health; Variant; aging population; base; biobank; clinical application; clinical care; clinical practice; clinical research site; clinically relevant; comparative effectiveness; design; effectiveness research; ethical legal social implication; evidence base; experience; genetic technology; genome wide association study; improved; inhibitor/antagonist; leukemia; leukocyte antigen typing; longitudinal database; member; novel; patient home care; patient oriented; patient population; prototype; response; reuptake; skills; standard care; trait

DESCRIPTION (provided by applicant): The Seattle eMERGE project aims to bring personal genomics to practice settings by taking advantage of the extensive electronic medical record (EMR) and biorepository of Group Health Cooperative (GH), including a 33-year pharmacy database and longitudinal data on an aging population. Algorithms developed in eMERGE I will be used to combine genome-wide association studies with phenotypes mined from EMRs to discover new polymorphism-phenotype relationships. Target phenotypes are infectious disease susceptibility, specifically to Clostridium difficile diarrhea, shingles from varicella zoster virus, and fungal nail infection, responses to antihypertensive drugs, serotonin-specific reuptake inhibitors, and statins, including adverse events. A new algorithm will follow longitudinal glycemia and hematocrit trajectories, and a novel automated method will detect karyotype abnormalities for assessing correlation to myelodysplasia and leukemia. Data will also support phenotypes investigated at other eMERGE sites. To create a model for introducing genomics into clinical practice, successful needs assessment methods from eMERGE I will engage stakeholders in guiding development of prototype EMR user interfaces in a clinical decision support format. The test case will be human leukocyte antigen-typing for an adverse drug reaction and the setting will be the patient-centered medical home care model developed at GH. This proposal provides the eMERGE network and its collaborators with the Seattle team's unique expertise in using natural language processing (NLP) to extract information from EMRs, and assisting in adoption of NLP methods. To disseminate eMERGE results and foster collaborations, it takes advantage of leadership positions of the investigators, including partners within eMERGE, other consortia and the HMO Research network, especially the potential for developments supported by the NIH Director's Common Fund in biobanking and megaepidemiology. Completion of the aims will reveal new, medically useful markers, improve the linking of high-throughput genomic methods to EMR data, and develop policies and practices for bringing individualized evidence-based medicine to communities. RELEVANCE (See instrucfions): To advance personalized medicine-treatment and preventive care based on individual traits; this project matches small differences in DNA to infectious disease susceptibility and response to statins, serotonin- specific reuptake inhibitors (SSRIs) and blood pressure medications. Methods to use these results in clinical care will be guided by focus groups of patients and caregivers in the patient-centered Group Health system.

描述（由申请人提供）：西雅图 eMERGE 项目旨在通过利用 Group Health Cooperative (GH) 广泛的电子病历 (EMR) 和生物存储库，包括 33 年的药房数据库和纵向数据库，将个人基因组学引入实践环境。有关人口老龄化的数据。 eMERGE I 中开发的算法将用于将全基因组关联研究与从 EMR 中挖掘的表型相结合，以发现新的多态性-表型关系。目标表型是传染病的易感性，特别是对艰难梭菌腹泻、水痘带状疱疹病毒带状疱疹和指甲真菌感染的易感性，对抗高血压药物、血清素特异性再摄取抑制剂和他汀类药物的反应，包括不良事件。一种新的算法将遵循纵向血糖和血细胞比容轨迹，一种新的自动化方法将检测核型异常，以评估与骨髓增生异常和白血病的相关性。数据还将支持在其他 eMERGE 站点调查的表型。为了创建将基因组学引入临床实践的模型，eMERGE 的成功需求评估方法，我将让利益相关者参与指导以临床决策支持格式开发原型 EMR 用户界面。测试案例将是药物不良反应的人类白细胞抗原分型，背景将是 GH 开发的以患者为中心的医疗家庭护理模式。该提案为 eMERGE 网络及其合作者提供了西雅图团队在使用自然语言处理 (NLP) 从 EMR 中提取信息并协助采用 NLP 方法方面的独特专业知识。为了传播 eMERGE 结果并促进合作，它利用了研究人员的领导地位，包括 eMERGE 内的合作伙伴、其他联盟和 HMO 研究网络，特别是 NIH 主任共同基金在生物样本库和大流行病学方面支持的发展潜力。完成这些目标将揭示新的、医学上有用的标记，改善高通量基因组方法与电子病历数据的联系，并制定政策和实践，将个体化的循证医学带入社区。 相关性（参见说明）：根据个人特征推进个性化药物治疗和预防保健；该项目匹配了 DNA 对传染病的易感性以及对他汀类药物、血清素特异性再摄取抑制剂 (SSRI) 和血压药物的反应的微小差异。在临床护理中使用这些结果的方法将由以患者为中心的团体健康系统中的患者和护理人员焦点小组指导。