Assessing polygenic risk score models for applications in populations with under-represented genomics data: an example of Vietnam.

ABSTRACT: Most polygenic risk score (PRS)models have been based on data from populations of European origins (accounting for the majority of the large genomics datasets, e.g. >78% in the UK Biobank and >85% in the GTEx project). Although several large-scale Asian biobanks were initiated (e.g. Japanese, Korean, Han Chinese biobanks), most other Asian countries have little or near-zero genomics data. To implement PRS models for under-represented populations, we explored transfer learning approaches, assuming that information from existing large datasets can compensate for the small sample size that can be feasibly obtained in developing countries, like Vietnam. Here, we benchmark 13 common PRS methods in meta-population strategy (combining individual genotype data from multiple populations) and multi-

SUBMITTER: Pham D 

PROVIDER: S-EPMC9677487 | biostudies-literature | 2022 Nov

REPOSITORIES: biostudies-literature