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Disease Heritability Inferred from Familial Relationships Reported in Medical Records.
Polubriaginof, Fernanda C G; Vanguri, Rami; Quinnies, Kayla; Belbin, Gillian M; Yahi, Alexandre; Salmasian, Hojjat; Lorberbaum, Tal; Nwankwo, Victor; Li, Li; Shervey, Mark M; Glowe, Patricia; Ionita-Laza, Iuliana; Simmerling, Mary; Hripcsak, George; Bakken, Suzanne; Goldstein, David; Kiryluk, Krzysztof; Kenny, Eimear E; Dudley, Joel; Vawdrey, David K; Tatonetti, Nicholas P.
Afiliação
  • Polubriaginof FCG; Department of Biomedical Informatics, Columbia University, New York, NY, USA.
  • Vanguri R; Department of Biomedical Informatics, Columbia University, New York, NY, USA.
  • Quinnies K; Department of Biomedical Informatics, Columbia University, New York, NY, USA; Institute for Genomic Medicine, Columbia University, New York, NY, USA.
  • Belbin GM; Department of Genetics and Genomic Sciences, Mount Sinai Health System, New York, NY, USA.
  • Yahi A; Department of Biomedical Informatics, Columbia University, New York, NY, USA.
  • Salmasian H; Department of Biomedical Informatics, Columbia University, New York, NY, USA; Value Institute, NewYork-Presbyterian Hospital, New York, NY, USA.
  • Lorberbaum T; Department of Biomedical Informatics, Columbia University, New York, NY, USA; Department of Physiology and Cellular Biophysics, Columbia University, New York, NY, USA.
  • Nwankwo V; Department of Biomedical Informatics, Columbia University, New York, NY, USA.
  • Li L; Department of Genetics and Genomic Sciences, Mount Sinai Health System, New York, NY, USA.
  • Shervey MM; Department of Genetics and Genomic Sciences, Mount Sinai Health System, New York, NY, USA.
  • Glowe P; Department of Genetics and Genomic Sciences, Mount Sinai Health System, New York, NY, USA.
  • Ionita-Laza I; Mailman School of Public Health, Columbia University, New York, NY, USA; Department of Biostatistics, Columbia University, New York, NY, USA.
  • Simmerling M; Department of Medicine, Weill Cornell Medicine, Cornell University, New York, NY, USA; Quality and Patient Safety, NewYork-Presbyterian Hospital, New York, NY, USA.
  • Hripcsak G; Department of Biomedical Informatics, Columbia University, New York, NY, USA; Medical Informatics Services, NewYork-Presbyterian Hospital, New York, NY; Observational Health Data Sciences and Informatics (OHDSI), New York, NY, USA.
  • Bakken S; Department of Biomedical Informatics, Columbia University, New York, NY, USA; School of Nursing, Columbia University, New York, NY, USA; Data Science Institute, Columbia University, New York, NY, USA.
  • Goldstein D; Institute for Genomic Medicine, Columbia University, New York, NY, USA.
  • Kiryluk K; Department of Medicine, Columbia University, New York, NY, USA.
  • Kenny EE; Department of Genetics and Genomic Sciences, Mount Sinai Health System, New York, NY, USA.
  • Dudley J; Department of Genetics and Genomic Sciences, Mount Sinai Health System, New York, NY, USA.
  • Vawdrey DK; Department of Biomedical Informatics, Columbia University, New York, NY, USA; Value Institute, NewYork-Presbyterian Hospital, New York, NY, USA.
  • Tatonetti NP; Department of Biomedical Informatics, Columbia University, New York, NY, USA; Institute for Genomic Medicine, Columbia University, New York, NY, USA; Observational Health Data Sciences and Informatics (OHDSI), New York, NY, USA; Department of Medicine, Columbia University, New York, NY, USA; Departm
Cell ; 173(7): 1692-1704.e11, 2018 06 14.
Article em En | MEDLINE | ID: mdl-29779949
ABSTRACT
Heritability is essential for understanding the biological causes of disease but requires laborious patient recruitment and phenotype ascertainment. Electronic health records (EHRs) passively capture a wide range of clinically relevant data and provide a resource for studying the heritability of traits that are not typically accessible. EHRs contain next-of-kin information collected via patient emergency contact forms, but until now, these data have gone unused in research. We mined emergency contact data at three academic medical centers and identified 7.4 million familial relationships while maintaining patient privacy. Identified relationships were consistent with genetically derived relatedness. We used EHR data to compute heritability estimates for 500 disease phenotypes. Overall, estimates were consistent with the literature and between sites. Inconsistencies were indicative of limitations and opportunities unique to EHR research. These analyses provide a validation of the use of EHRs for genetics and disease research.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Limite: Humans Idioma: En Ano de publicação: 2018 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Limite: Humans Idioma: En Ano de publicação: 2018 Tipo de documento: Article