Estimate of disease heritability using 7.4 million familial relationships inferred from electronic health records
| Autor: | Krzysztof Kiryluk, Gillian M. Belbin, Patricia Glowe, Hojjat Salmasian, Joel T. Dudley, Li Li, Rami Vanguri, Fernanda Polubriaginof, George Hripcsak, Kayla M. Quinnies, Suzanne Bakken, David K. Vawdrey, Iuliana Ionita-Laza, Eimear E. Kenny, Victor Nwankwo, Mark M. Shervey, Alexandre Yahi, Tal Lorberbaum, Nicholas P. Tatonetti, Daniel G. Goldstein, Mary Simmerling |
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| Rok vydání: | 2016 |
| Předmět: |
0303 health sciences
Patient privacy Disease Health records Heritability Biology 3. Good health Patient recruitment 03 medical and health sciences 0302 clinical medicine Clinical phenotype health care economics and organizations 030217 neurology & neurosurgery 030304 developmental biology Demography |
| DOI: | 10.1101/066068 |
| Popis: | Heritability is essential for understanding the biological causes of disease, but requires laborious patient recruitment and phenotype ascertainment. Electronic health records (EHR) passively capture a wide range of clinically relevant data and provide a novel 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 millions of 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 literature and between sites. Inconsistencies were indicative of limitations and opportunities unique to EHR research. These analyses provide a novel validation of the use of EHRs for genetics and disease research.One Sentence SummaryWe demonstrate that next-of-kin information can be used to identify familial relationships in the EHR, providing unique opportunities for precision medicine studies. |
| Databáze: | OpenAIRE |
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