Evaluation of three polygenic risk score models for the prediction of breast cancer risk in Singapore Chinese.

Claire Hian Tzer Chan,Hai Yang Law,Kong Wee Ong,Preetha Madhukumar,Puay Hoon Tan,Yoon Sim Yap,Chow Yin Wong,Prabhakaran Munusamy,Peter Ang,Sau Yeen Loke,Nan Soon Wong,Wei Sean Yong,Geok Ling Koh,Audrey Zhi Yi Yang,Chung Lie Oey,Ann Siew Gek Lee,Chui Sheun Yoon,Raymond Ng ,Min Tan

doi:10.18632/oncotarget.24374

Claire Hian Tzer Chan, Hai Yang Law + Show 17 more

Open Access

https://doi.org/10.18632/oncotarget.24374

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Abstract

Genome-wide association studies (GWAS) have proven highly successful in identifying single nucleotide polymorphisms (SNPs) associated with breast cancer (BC) risk. The majority of these studies are on European populations, with limited SNP association data in other populations. We genotyped 51 GWAS-identified SNPs in two independent cohorts of Singaporean Chinese. Cohort 1 comprised 1294 BC cases and 885 controls and was used to determine odds ratios (ORs); Cohort 2 had 301 BC cases and 243 controls for deriving polygenic risk scores (PRS). After age-adjustment, 11 SNPs were found to be significantly associated with BC risk. Five SNPs were present in <1% of Cohort 1 and were excluded from further PRS analysis. To assess the cumulative effect of the remaining 46 SNPs on BC risk, we generated three PRS models: Model-1 included 46 SNPs; Model-2 included 11 statistically significant SNPs; and Model-3 included the SNPs in Model-2 but excluded SNPs that were in strong linkage disequilibrium with the others. Across Models-1, -2 and -3, women in the highest PRS quartile had the greatest ORs of 1.894 (95% CI = 1.157–3.100), 2.013 (95% CI = 1.227–3.302) and 1.751 (95% CI = 1.073–2.856) respectively, suggesting a direct correlation between PRS and BC risk. Given the potential of PRS in BC risk stratification, our findings suggest the need to tailor the selection of SNPs to be included in an ethnic-specific PRS model.

Highlights

Advances in technology and large collaborative efforts have led to the success of genome-wide association studies (GWAS) in their discovery of multiple breast cancer (BC)-associated risk loci
After excluding samples that failed to reach 95% call rate for all assays, samples were further separated into two independent cohorts; Cohort 1 included 1294 cases and 885 controls to determine the association of the single nucleotide polymorphism (SNP) with BC risk, and Cohort 2 included 301 cases and 243 controls to derive polygenic risk scores (PRS) models
Associations of the remaining 46 SNPs with BC risk in our Singapore Chinese cohort are reflected in Supplementary Table 3

Summary

Introduction

Advances in technology and large collaborative efforts have led to the success of genome-wide association studies (GWAS) in their discovery of multiple breast cancer (BC)-associated risk loci. Fine-scale mapping has subsequently been carried out to identify functional SNPs associated with BC risk in a particular ethnic group [16, 23]. Fine-scale mapping of regions identified by GWAS [24,25,26,27] and meta-analysis of existing GWAS [28,29,30,31,32,33] have contributed to the growing number of SNPs associated with BC susceptibility. As breast cancer is a highly heterogeneous disease, association studies have been performed to discover risk loci specific to a particular breast cancer histological type or hormone receptor subtype [3, 4, 8, 17, 28, 30, 33,34,35,36]

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