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Disease Heritability Inferred from Familial Relationships Reported in Medic...

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Disease Heritability Inferred from Familial Relationships Reported in Medical Records


Time: 9:00 AM - 10:00 AM PDT (12:00 PM - 1:00 PM EST), Friday, Sept 14th, 2018

Zoom.us link will be sent 24 hours and 1 hour before the event.

Please RSVP, the registration will be closed at 11:30 PM, Sept 13rd, 2018.

Speaker:

Fernanda C. G. Polubriaginof, MD PhD

Program Director for Research Science at NewYork-Presbyterian Hospital

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.



Bio: Fernanda C. G. Polubriaginof, MD PhD, is the Program Director for Research Science at NewYork-Presbyterian Hospital. Following the completion of her medical degree, she completed her doctoral study in biomedical informatics at Columbia University, New York. The focus of Dr. Polubriaginof’s research is to support and improve clinical care through application of innovative informatics methods. A major focus of her work is the utilization of patient-provided information and electronic health record data to assess disease risk



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