HerediGene Population Study IT infrastructure: A model to support genomic research recruitment and precision public health.

Autor:	Taylor DP; Intermountain Health, Salt Lake City, UT., Heale BSE; Humanized Health Consulting, Salt Lake City, UT., Chisum B; Intermountain Health, Salt Lake City, UT., Christensen GB; Intermountain Health, Salt Lake City, UT., Wilcox DF; Intermountain Health, Salt Lake City, UT., Banks KM; Intermountain Health, Salt Lake City, UT., Tripp JS; Intermountain Health, Salt Lake City, UT., Liu T; Intermountain Health, Salt Lake City, UT., Ruesch JB; Intermountain Health, Salt Lake City, UT., Sheffield TJ; Intermountain Health, Salt Lake City, UT., Breinholt JW; Intermountain Health, Salt Lake City, UT., Harward JC; Intermountain Health, Salt Lake City, UT., Hakoda EC; Intermountain Health, Salt Lake City, UT., May T; Intermountain Health, Salt Lake City, UT., Bonkowsky JL; Division of Pediatric Neurology, Department of Pediatrics, University of Utah School of Medicine, Salt Lake City, UT.; Center for Personalized Medicine, Primary Children's Hospital, Intermountain Health, Salt Lake City, UT., Walton NA; Intermountain Health, Salt Lake City, UT., McLeod HL; Intermountain Health, Salt Lake City, UT., Nadauld LD; Intermountain Health, Salt Lake City, UT., Ranade-Kharkar P; Intermountain Health, Salt Lake City, UT.
Jazyk:	angličtina
Zdroj:	AMIA ... Annual Symposium proceedings. AMIA Symposium [AMIA Annu Symp Proc] 2024 Jan 11; Vol. 2023, pp. 689-698. Date of Electronic Publication: 2024 Jan 11 (Print Publication: 2023).
Abstrakt:	The HerediGene Population Study is a large research study focused on identifying new genetic biomarkers for disease prevention, diagnosis, prognosis, and development of new therapeutics. A substantial IT infrastructure evolved to reach enrollment targets and return results to participants. More than 170,000 participants have been enrolled in the study to date, with 5.87% of those whole genome sequenced and 0.46% of those genotyped harboring pathogenic variants. Among other purposes, this infrastructure supports: (1) identifying candidates from clinical criteria, (2) monitoring for qualifying clinical events (e.g., blood draw), (3) contacting candidates, (4) obtaining consent electronically, (5) initiating lab orders, (6) integrating consent and lab orders into clinical workflow, (7) de-identifying samples and clinical data, (8) shipping/transmitting samples and clinical data, (9) genotyping/sequencing samples, (10) and re-identifying and returning results for participants where applicable. This study may serve as a model for similar genomic research and precision public health initiatives. (©2023 AMIA - All rights reserved.)
Databáze:	MEDLINE
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