"A principal promise of modern genetics is the ability to predict complex disease risk on the basis of a person's genetic profile. If successful, health management strategies can be developed to mitigate risk (disease prevention) and to optimize care (early diagnosis and effective treatment). Large-scale studies by the UK Biobank (UKB) and the Electronic Medical Records and Genomics Network show that risk prediction on the basis of genetics holds promise, and several countries are exploring ways to implement risk-based management in clinical practice1,2."
"However, a substantial limitation is that current PRS models are predominantly based on genome-wide association studies (GWAS) with participants of European ancestry (EUR)4,5, often leading to reduced predictive performance in groups of other ancestry6,7. To fully realize the potential of precision medicine for diverse global populations, population-specific phenome-wide genomic discovery must be performed at scale and clinically applicable polygenic risk models must be optimized in and across populations."
Genetic profiling enables prediction of complex disease risk to support prevention and more effective clinical care. Large-scale cohorts such as UK Biobank and the Electronic Medical Records and Genomics Network demonstrate potential for genetics-based risk prediction and for implementing risk-based management. Polygenic risk scores (PRS) provide a precision medicine approach to identify high-risk individuals. Current PRS models are largely derived from European-ancestry GWAS and often perform worse in other ancestry groups. East Asian populations remain underrepresented in GWAS, and population-specific, phenome-wide genomic discovery plus optimized PRS across populations are needed for equitable precision medicine.
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