The Construction of Multi-ethnic Polygenic Risk Score using Transfer Learning

As most existing genome-wide association studies (GWAS) were conducted in European ancestry cohorts and as the existing PRS models have limited transferability across ancestry groups, PRS research on non-European ancestry groups is negatively impacted. Here we propose a novel PRS method using transfer learning techniques. Our approach, TL-PRS, uses gradient descent to fine-tune the baseline PRS model from an ancestry group with large sample GWAS to the dataset of target ancestry. In our application of constructing PRS for the six quantitative and two dichotomous traits for 10,285 South Asian and 8,168 African ancestry individuals in UK Biobank, TL-PRS achieved up to 42% average relative improvement compared to the existing methods. Our approach increases the transferability of PRSs across ancestries and thereby helps reduce existing inequities in genetics research.