Abstract

Polygenic risk scores (PRS) can provide useful information for personalized risk stratification and disease risk assessment, especially when combined with non-genetic risk factors. However, their construction depends on the availability of summary statistics from genome-wide association studies (GWAS) independent from the target sample. For best compatibility, it was reported that GWAS and the target sample should match in terms of ancestries. Yet, GWAS, especially in the field of cancer, often lack diversity and are predominated by European ancestry. This bias is a limiting factor in PRS research. By using electronic health records and genetic data from the UK Biobank, we contrast the utility of breast and prostate cancer PRS derived from external European-ancestry-based GWAS across African, East Asian, European, and South Asian ancestry groups. We highlight differences in the PRS distributions of these groups that are amplified when PRS methods condense hundreds of thousands of variants into a single score. While European-GWAS-derived PRS were not directly transferrable across ancestries on an absolute scale, we establish their predictive potential when considering them separately within each group. For example, the top 10% of the breast cancer PRS distributions within each ancestry group each revealed significant enrichments of breast cancer cases compared to the bottom 90% (odds ratio of 2.81 [95%CI: 2.69,2.93] in European, 2.88 [1.85, 4.48] in African, 2.60 [1.25, 5.40] in East Asian, and 2.33 [1.55, 3.51] in South Asian individuals). Our findings highlight a compromise solution for PRS research to compensate for the lack of diversity in well-powered European GWAS efforts while recruitment of diverse participants in the field catches up.

Highlights

  • Translating findings from genome-wide association studies (GWAS) to clinical utility in terms of complex trait prediction is a major milestone in genetics research [1]

  • The translation of results from genome-wide association studies (GWAS) into polygenic risk scores (PRS) to predict disease risk or outcomes is a major aspiration in the field of statistical genetics

  • Discovery of genetic risk factors, especially for cancer traits, are almost exclusively based on individuals with European-ancestry, and it remains unclear if these results can be utilized for PRS applications across non-European ancestries

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Summary

Introduction

Translating findings from genome-wide association studies (GWAS) to clinical utility in terms of complex trait prediction is a major milestone in genetics research [1]. This is especially important for traits whose estimated heritability was reported to be high. The identified common single nucleotide polymorphisms (SNPs) seldom have deterministic consequences. While each identified common risk SNP contributes to the overall disease risk, by itself it is unlikely to predict a large degree of variation in a disease outcome and usually represents a poor predictor by itself. The resulting bias in published GWAS results [6] is passed on to the development and application of PRS for many complex traits and despite current efforts to increase diversity in genetics research will likely continue in the foreseeable future [6]

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