Electronic health record phenotypes associated with genetically regulated expression of CFTR and application to cystic fibrosis.

ABSTRACT:

Purpose

The increasing use of electronic health records (EHRs) and biobanks offers unique opportunities to study Mendelian diseases. We described a novel approach to summarize clinical manifestations from patient EHRs into phenotypic evidence for cystic fibrosis (CF) with potential to alert unrecognized patients of the disease.

Methods

We estimated genetically predicted expression (GReX) of cystic fibrosis transmembrane conductance regulator (CFTR) and tested for association with clinical diagnoses in the Vanderbilt University biobank (N = 9142 persons of European descent with 71 cases of CF). The top associated EHR phenotypes were assessed in combination as a phenotype risk score (PheRS) for discriminating CF case status in an additional 2.8 million patients from Vanderbilt

SUBMITTER: Zhong X 

PROVIDER: S-EPMC7781195 | biostudies-literature | 2020 Jul

REPOSITORIES: biostudies-literature