A One-Shot Lossless Algorithm for Cross-Cohort Learning in Mixed-Outcomes Analysis
Ruowang Li1, Luke Benz2, Rui Duan2
1Department of Computational Biomedicine, Cedars-Sinai Medical Center, Los Angeles, CA 90049, USA.
Medrxiv : the Preprint Server for Health Sciences
|January 23, 2024
Summary
A new algorithm, mixWAS, efficiently integrates distributed electronic health records (EHRs) using summary statistics. This lossless method enhances accuracy and efficiency for cross-cohort genetic association studies in healthcare research.
Area of Science:
- Genetics
- Bioinformatics
- Computational Biology
Background:
- Integrating diverse electronic health records (EHRs) for cross-cohort studies is crucial but challenging due to data heterogeneity, distributed storage, and privacy concerns.
- Traditional data pooling or harmonization methods can be inefficient and limit the scope of cross-cohort learning.
Purpose of the Study:
- To introduce mixWAS, a novel one-shot, lossless algorithm for efficient integration of distributed EHR datasets using summary statistics.
- To enable preservation of cohort-specific covariate associations and support simultaneous mixed-outcome analyses.
Main Methods:
- mixWAS algorithm utilizes summary statistics for lossless integration of distributed EHR data.
- The method preserves cohort-specific covariate associations and supports simultaneous multi-outcome analyses.
- Simulations and application to US and UK EHR data were used for validation.
Main Results:
- mixWAS demonstrated superior accuracy and efficiency compared to conventional methods in simulations.
- Applied to seven US EHR cohorts, mixWAS identified 4,534 significant cross-cohort genetic associations for traits including blood lipids, BMI, and circulatory diseases.
- Validation in an independent UK EHR dataset confirmed 97.7% of the identified associations, demonstrating robustness.
Conclusions:
- mixWAS enables lossless cross-cohort integration of EHR data, improving precision in multi-outcome analyses.
- The algorithm enhances the potential for actionable insights in healthcare and genetic research.
- mixWAS offers an efficient and accurate approach for leveraging distributed health data.
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