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Beyond PheWAS: Recognition of Phenotype Patterns for Discovery and Translation

超越 PheWAS：识别表型模式以进行发现和翻译

基本信息

批准号：
10226268
负责人：
Lisa Bastarache
金额：
$ 62.37万
依托单位：
VANDERBILT UNIVERSITY MEDICAL CENTER
依托单位国家：
美国
项目类别：
财政年份：
2011
资助国家：
美国
起止时间：
2011-09-01 至 2023-08-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/10226268
关键词：
Academic Medical Centers Algorithms All of Us Research Program Benign Catalogs ClinVar Clinical Code Coupled DNA Data Data Set Diagnosis Diagnostic Procedure Disease Electronic Health Record Electronic Medical Records and Genomics Network Evaluation Future General Practices Genes Genetic Genetic Markers Genomic medicine Genotype Gold Grant Health Surveys Hereditary Disease Human Human Genome Project In Vitro Individual International Label Laboratories Link Maps Measures Medical Medical Genetics Medicine Mendelian disorder Methodological Studies Methodology Methods Michigan Online Mendelian Inheritance In Man Ontology Outcome Participant Pathogenicity Patients Pattern Penetrance Performance Pharmaceutical Preparations Phase Phenotype Population Population Heterogeneity Prognosis Reporting Research Resources Risk Running Scoring Method Single Nucleotide Polymorphism Site Surveys Testing Translational Research Translations Validation Variant Weight Work base biobank case control clinical Diagnosis clinical care clinical implementation cohort data modeling data standards diverse data exome exome sequencing genetic testing genome wide association study genome-wide high risk improved individualized medicine novel novel strategies novel therapeutics patient subsets personalized medicine personalized screening phenome phenotypic data pleiotropism precision medicine prediction algorithm rare variant repository screening guidelines side effect targeted treatment tool trait treatment strategy web site

项目摘要

Project Summary 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 clinical understanding of risks and mechanisms for many diseases and conditions and that may ultimately guide diagnosis and therapy on a patient-specific basis. The previous two cycles of this effort (2011-2014 and 2014-2018) introduced the phenome-wide association study (PheWAS) as a systematic and efficient approach to identify novel disease-variant associations and discover pleiotropy using electronic health records (EHRs). This proposal will develop novel methods to identify associations based on patterns of phenotypes using a phenotype risk score (PheRS) methodology to systematically search for the influence of Mendelian disease variants on common disease. By doing so, it also creates a way to assess pathogenicity for rare variants, and will identify patients at highest risk of having undiagnosed Mendelian disease. The project is enabled by large DNA biobanks coupled to de-identified copies of EHR. This project has four specific aims. First, we will develop and validate PheRS for assessment of variant pathogenicity by leveraging billing codes, laboratory data, and NLP features in its predictive algorithms. The second aim is to apply PheRS in huge populations to create a robust repository of rare variant associations in diverse populations (eMERGE Network and large national cohorts, which could approach 2 million people with genotype data). The third aim is to assess Mendelian disease penetrance and evaluate PheRS as a tool to identify patients at risk for undiagnosed Mendelian disease. The fourth aim is make these tools and resources broadly available to aid in variant interpretation and facilitate others running PheRS. The tools generated from this project will validate new approaches to interpreting the function of rare variants, improve basic understanding of Mendelian disease, greatly enhance our understanding of the contribution of Mendelian disease variants to common disease and traits, and offers a potential approach to identify subpopulations of patients for whom new therapies may offer benefit.

项目总结