Multi-ancestry and multi-phenotype integration for increasing power in polygenic prediction
Date:
Yosuke presented his recent works on inclusive polygenic score (iPGS) and multi-PRS at Systems Cardiology Group Research Seminar, Department of Cardiovascular Medicine, the University of Tokyo Hospital.
Slides
Learning objectives
- Summarize recent methodological developments in polygenic score (PGS) research
- Identify the caveats and limitations of existing approaches to PGS analysis of complex traits
- Plan ways to improve the diversity and inclusion in study designs of human genetics studies
- Plan ways to integrate multiple phenotypes in human genetics studies
Links
References
- Tanigawa and Kellis. Power of inclusion: Enhancing polygenic prediction with admixed individuals. Am J Hum Genet. 2023
- Sinnott-Armstrong, Tanigawa et al. Genetics of 35 blood and urine biomarkers in the UK Biobank. Nat Gen. 2021
- Tanigawa et al. Significant sparse polygenic risk scores across 813 traits in UK Biobank. PLoS Gen. 2022.
- Application of BASIL across 800+ traits in UK Biobank
- Data browser: https://biobankengine.stanford.edu/prs
- Qian et al. A fast and scalable framework for large-scale and ultrahigh-dimensional sparse regression with application to the UK Biobank. PLoS Gen. 2020.
- Sparse polygenic scores from individual-level data, BASIL algorithm
- Kachuri et al. Principles and methods for transferring polygenic risk scores across global populations. Nat Rev Genet. 2023.
- Review on multi-ancestry-aware PGS methods
- O’Sullivan et al. Polygenic Risk Scores for Cardiovascular Disease: A Scientific Statement From the American Heart Association. Circulation. 2022
- Perspectives on how PGS may inform clinical practice
Thank you, Dr. Seitaro Nomura, for invitation!