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Am J Med Genet B Neuropsychiatr Genet DOI:10.1002/ajmg.b.32548

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

Publication TypeJournal Article
Year of Publication2018
AuthorsSmoller, JW
JournalAm J Med Genet B Neuropsychiatr Genet
Volume177
Issue7
Pages601-612
Date Published2018 Oct
ISSN1552-485X
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.

DOI10.1002/ajmg.b.32548
Pubmed

http://www.ncbi.nlm.nih.gov/pubmed/28557243?dopt=Abstract

Alternate JournalAm. J. Med. Genet. B Neuropsychiatr. Genet.
PubMed ID28557243
Grant ListK24MH094614 / / 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