The use of electronic health records for psychiatric phenotyping and genomics.

Am J Med Genet B Neuropsychiatr Genet
Authors
Abstract

The widespread adoption of electronic health record (EHRs) in healthcare systems has created a vast and continuously growing resource of clinical data and provides new opportunities for population-based research. In particular, the linking of EHRs to biospecimens and genomic data in biobanks may help address what has become a rate-limiting study for genetic research: the need for large sample sizes. The principal roadblock to capitalizing on these resources is the need to establish the validity of phenotypes extracted from the EHR. For psychiatric genetic research, this represents a particular challenge given that diagnosis is based on patient reports and clinician observations that may not be well-captured in billing codes or narrative records. This review addresses the opportunities and pitfalls in EHR-based phenotyping with a focus on their application to psychiatric genetic research. A growing number of studies have demonstrated that diagnostic algorithms with high positive predictive value can be derived from EHRs, especially when structured data are supplemented by text mining approaches. Such algorithms enable semi-automated phenotyping for large-scale case-control studies. In addition, the scale and scope of EHR databases have been used successfully to identify phenotypic subgroups and derive algorithms for longitudinal risk prediction. EHR-based genomics are particularly well-suited to rapid look-up replication of putative risk genes, studies of pleiotropy (phenomewide association studies or PheWAS), investigations of genetic networks and overlap across the phenome, and pharmacogenomic research. EHR phenotyping has been relatively under-utilized in psychiatric genomic research but may become a key component of efforts to advance precision psychiatry.

Year of Publication
2018
Journal
Am J Med Genet B Neuropsychiatr Genet
Volume
177
Issue
7
Pages
601-612
Date Published
2018 Oct
ISSN
1552-485X
DOI
10.1002/ajmg.b.32548
PubMed ID
28557243
Links
Grant list
K24MH094614 / National Institute of Mental Health
R01MH085542 / MH / NIMH NIH HHS / United States
Tommy Fuss Fund
Demarest Lloyd, Jr. Foundation
K24 MH094614 / MH / NIMH NIH HHS / United States