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Updated: Jul 15, 2026
09:30
Pre-Implantation Genetic Testing for Aneuploidy on a Semiconductor Based Next-Generation Sequencing Platform
Published on: August 17, 2022
Using a translational data platform to create clinical-grade genome-informed risk assessments
Jennifer L Morse1, Megan He1, Hana Bangash2
1Vanderbilt Institute for Clinical and Translational Research, Vanderbilt University Medical Center, Nashville, TN 37232, United States.
JAMIA Open
|July 14, 2026
Summary
An automated platform was developed to integrate diverse data for genomic risk prediction. This system successfully generated genome-informed risk assessments for 11 conditions in a large cohort.
Area of Science:
- Genomics
- Bioinformatics
- Health Informatics
Background:
- Genomic risk prediction is evolving, requiring advanced data handling.
- Standardized, high-throughput methods are crucial for complex health data integration.
Purpose of the Study:
- To develop and implement an automated platform for genomic risk prediction.
- To integrate multiple data types for comprehensive risk assessment.
Main Methods:
- Developed the R4 (Recruitment, Results, and Risk Reduction) platform using REDCap infrastructure.
- Integrated data from clinical sites, labs, surveys, and electronic health records (EHR) across 13 institutions.
Main Results:
- Successfully integrated data for a cohort of 23,840 individuals.
- Generated genome-informed risk assessments (GIRAs) for 11 conditions.
- Established network-wide protocols for data consistency and accuracy through testing and quality control.
Conclusions:
- The R4 Portal facilitated secure, semi-automated generation of risk profiles.
- The platform supports the evolving science of disease risk estimation.
- The electronic MEdical Records and GEnomics (eMERGE) network demonstrated successful implementation.
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