Maya S Safarova1, Iftikhar J Kullo. 1. Atherosclerosis and Lipid Genomics Laboratory and Department of Cardiovascular Medicine, Mayo Clinic, Rochester, Minnesota, USA.
Abstract
PURPOSE OF REVIEW: Although primarily designed for medical documentation and billing purposes, the electronic health record (EHR) has significant potential for translational research. In this article, we provide an overview of the use of the EHR for genomics research with a focus on heritable lipid disorders. RECENT FINDINGS: Linking the EHR to genomic data enables repurposing of vast phenotype data for genomic discovery. EHR data can be used to study the genetic basis of common and rare disorders, identify subphenotypes of diseases, assess pathogenicity of novel genomic variants, investigate pleiotropy, and rapidly assemble cohorts for genomic medicine clinical trials. EHR-based discovery can inform clinical practice; examples include use of polygenic risk scores for assessing disease risk and use of phenotype data to interpret rare variants. Despite limitations such as missing data, variable use of standards and poor interoperablility between disparate systems, the EHR is a powerful resource for genomic research. SUMMARY: When linked to genomic data, the EHR can be leveraged for genomic discovery, which in turn can inform clinical care, exemplifying the virtuous cycle of a learning healthcare system.
PURPOSE OF REVIEW: Although primarily designed for medical documentation and billing purposes, the electronic health record (EHR) has significant potential for translational research. In this article, we provide an overview of the use of the EHR for genomics research with a focus on heritable lipid disorders. RECENT FINDINGS: Linking the EHR to genomic data enables repurposing of vast phenotype data for genomic discovery. EHR data can be used to study the genetic basis of common and rare disorders, identify subphenotypes of diseases, assess pathogenicity of novel genomic variants, investigate pleiotropy, and rapidly assemble cohorts for genomic medicine clinical trials. EHR-based discovery can inform clinical practice; examples include use of polygenic risk scores for assessing disease risk and use of phenotype data to interpret rare variants. Despite limitations such as missing data, variable use of standards and poor interoperablility between disparate systems, the EHR is a powerful resource for genomic research. SUMMARY: When linked to genomic data, the EHR can be leveraged for genomic discovery, which in turn can inform clinical care, exemplifying the virtuous cycle of a learning healthcare system.
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