From GWAS to PheWAS: Scanning the EMR phenome for gene-disease associations

从 GWAS 到 PheWAS：扫描 EMR 表组以寻找基因-疾病关联

• 批准号: 8326646
• 负责人: Joshua C. Denny
• 金额: $ 33.25万
• 依托单位: VANDERBILT UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2011
• 资助国家: 美国
• 起止时间: 2011-09-01 至 2014-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8326646
• 关键词: Academic Medical Centers; Algorithms; Appointment; Blood specimen; Characteristics; Clinic; Clinical; Clinical Research; Clinical Treatment; Clinical Trials; Clinical and Translational Science Awards; Code; Computerized Medical Record; Coupled; DNA; DNA Databases; Data; Data Element; Descriptor; Diagnosis; Diagnostic; Diagnostic Procedure; Disease; Disease Association; Enrollment; Expert Systems; Funding; Future; Genes; Genetic; Genetic Markers; Genetic Research; Genomics; Genotype; Goals; Hand; Individual; Institution; Investigation; Joints; Laboratories; Letters; Link; Machine Learning; Manuals; Medicine; Methods; Names; Natural Language Processing; Patients; Phenotype; Physicians; Population; Positioning Attribute; Records; Research; Research Personnel; Research Project Grants; Resources; Risk; Sampling; Scanning; Secure; Single Nucleotide Polymorphism; Site; Statistical Methods; Structure; Syndrome; Techniques; Terminology; Testing; Text; Time; United States National Institutes of Health; Update; Validation; analytical method; base; biobank; biomedical informatics; case control; cohort; disease phenotype; disorder risk; experience; genetic association; genome-wide; heuristics; improved; knowledge base; novel; novel strategies; patient population; phenome; phenomics; research clinical testing; tool; treatment response

DESCRIPTION (provided by applicant): Genomic medicine offers hope for improved diagnostic methods and for more effective, patient-specific therapies. Genome-wide associated studies (GWAS) elucidate genetic markers that improve understanding of risks and causes for many diseases, and may guide diagnosis and therapy on a patient-specific basis. This project will take another approach to identify gene-disease associations: perform "reverse GWAS," or phenome- wide association study (PheWAS), to determine which phenotypes are associated with a given genotype. The project is enabled by a large DNA biobank coupled to a de- identified copy of the electronic medical record. This project has four specific aims. First, the project will develop and validate a standardized approach to extract disease phenotypes from EMR records, integrating national standard terminologies of clinical disorders and descriptors relating to treatment and diagnosis of each disease to create a sharable knowledge base. The project will use natural language processing, structured data queries, and heuristic and machine learning methods to accurately identify patients with each disease and corresponding controls. The second aim is to perform PheWAS analyses using existing genotype data. To validate the method, the project will use PheWAS to "rediscover" SNPs with known disease associations. The project will also investigate statistical methods for large-scale multiple hypothesis testing to discover novel phenotype associations. The third aim is to apply the PheWAS algorithms in four other sites with EMR-linked DNA biobanks and compare results. In the fourth aim, the project will validate novel phenotype-genotype associations discovered through PheWAS with new genotyping in a previously untested population. The tools generated from this project will not only make PheWAS possible, but will also broadly enable clinical research and subsequent genetic studies.

描述（由申请人提供）：基因组医学为改进的诊断方法和更有效的患者特定疗法提供了希望。全基因组相关研究（GWAS）阐明了遗传标记，以提高对许多疾病的风险和原因的理解，并可能在患者特定的基础上指导诊断和治疗。该项目将采用另一种方法来识别基因疾病关联：执行“反向GWAS”或现象广泛的关联研究（PHEWAS），以确定哪些表型与给定的基因型相关。该项目是由大型DNA生物库启用的，该大型生物库与电子病历的删除副本相连。该项目具有四个具体目标。首先，该项目将开发并验证一种从EMR记录中提取疾病表型的标准化方法，整合了与治疗和诊断每种疾病有关的临床疾病的国家标准术语，以创建可共享的知识库。该项目将使用自然语言处理，结构化数据查询以及启发式和机器学习方法，以准确鉴定患有每种疾病和相应对照的患者。第二个目的是使用现有的基因型数据进行PHEWAS分析。为了验证该方法，该项目将使用Phewas“重新发现”具有已知疾病关联的SNP。该项目还将研究大规模多个假设检验的统计方法，以发现新的表型关联。第三个目的是将PHEWAS算法应用于其他四个具有EMR连接DNA生物库的站点，并比较结果。在第四个目标中，该项目将验证通过Phewas发现的新型表型基因型关联，并在以前未经测试的人群中具有新的基因分型。该项目产生的工具不仅可以使Phewas成为可能，而且还将广泛地实现临床研究和随后的遗传研究。