New Method for Measuring Genetic Risk Across Different Ancestries
Author Information
Author(s): Huang Yu-Jyun, Kurniansyah Nuzulul, Goodman Matthew O, Spitzer Brian W, Wang Jiongming, Stilp Adrienne, Laurie Cecelia, de Vries Paul S, Chen Han, Min Yuan-I, Sims Mario, Peloso Gina M, Guo Xiuqing, Bis Joshua C, Brody Jennifer A, Raffield Laura M, Smith Jennifer A, Zhao Wei, Rotter Jerome I, Rich Stephen S, Redline Susan, Fornage Myriam, Kaplan Robert, Franceschini Nora, Levy Daniel, Morrison Alanna C, Boerwinkle Eric, Smith Nicholas L, Kooperberg Charles, Psaty Bruce M, Zöllner Sebastian, Sofer Tamar
Primary Institution: Cold Spring Harbor Laboratory
Hypothesis
Can a new framework for polygenic risk scores improve the accuracy of genetic risk assessment in diverse populations?
Conclusion
The expected polygenic risk score framework can provide unbiased estimates of genetic risk across different ancestral backgrounds.
Supporting Evidence
- The ePRS framework adjusts for genetic ancestry to improve risk assessment.
- Simulation studies show that adjusting for ePRS leads to nearly unbiased estimates.
- The framework was tested on cardiovascular-related traits with consistent results.
Takeaway
This study introduces a new way to measure genetic risk that works better for people from different backgrounds, making it fairer for everyone.
Methodology
The study used simulation studies and applied the ePRS framework to datasets to evaluate its effectiveness.
Digital Object Identifier (DOI)
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