Electronic health record phenotypes associated with genetically regulated expression of CFTR and application to cystic fibrosis
Type
ArticleAuthors
Zhong, Xue
Yin, Zhijun
Jia, Gengjie
Zhou, Dan
Wei, Qiang
Faucon, Annika
Evans, Patrick
Gamazon, Eric R.
Li, Bingshan
Tao, Ran
Rzhetsky, Andrey
Bastarache, Lisa
Cox, Nancy J.
Date
2020-04-16Online Publication Date
2020-04-16Print Publication Date
2020-07Embargo End Date
2020-10-15Submitted Date
2019-09-17Permanent link to this record
http://hdl.handle.net/10754/662598
Metadata
Show full item recordAbstract
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.Citation
Zhong, X., Yin, Z., Jia, G., Zhou, D., Wei, Q., Faucon, A., … Cox, N. J. (2020). Electronic health record phenotypes associated with genetically regulated expression of CFTR and application to cystic fibrosis. Genetics in Medicine. doi:10.1038/s41436-020-0786-5Sponsors
This work was funded by the National Institutes of Health (NIH) grants R01MH113362, U01HG009086, R35HG010718, R01HL122712, 1P50MH094267, and U01HL108634-01. A.R. also acknowledges support from the Defense Advanced Research Projects Agency (DARPA) Big Mechanism program under Army Research Office (ARO) contract W911NF1410333, the King Abdullah University of Science and Technology (KAUST), and a gift from Liz and Kent Dauten. BioVU and the Synthetic Derivative of Vanderbilt University Medical Center are supported by the National Center for Advancing Translational Science grant UL1TR000445 from NIH; the genotypes in BioVU used for the analyses described were funded by NIH grants RC2GM092618 and U01HG004603.Publisher
Springer NatureJournal
Genetics in MedicineAdditional Links
http://www.nature.com/articles/s41436-020-0786-5ae974a485f413a2113503eed53cd6c53
10.1038/s41436-020-0786-5