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

// Claire Hian Tzer Chan 1, * , Prabhakaran Munusamy 1, * , Sau Yeen Loke 1 , Geok Ling Koh 1 , Audrey Zhi Yi Yang 1 , Hai Yang Law 2 , Chui Sheun Yoon 2 , Chow Yin Wong 3 , Wei Sean Yong 4 , Nan Soon Wong 5, 6 , Raymond Chee Hui Ng 5 , Kong Wee Ong 4 , Preetha Madhukumar 4 , Chung Lie Oey 4 , Gay Hui Ho 4, 7 , Puay Hoon Tan 8 , Min Han Tan 5, 9, 10 , Peter Ang 5, 6 , Yoon Sim Yap 5 and Ann Siew Gek Lee 1, 11, 12 1 Division of Medical Sciences, Humphrey Oei Institute of Cancer Research, National Cancer Centre, Singapore 2 DNA Diagnostic and Research Laboratory, KK Women’s and Children’s Hospital, Singapore 3 Department of General Surgery, Singapore General Hospital, Singapore 4 Department of Surgical Oncology, National Cancer Centre, Singapore 5 Department of Medical Oncology, National Cancer Centre, Singapore 6 Oncocare Cancer Centre, Gleneagles Medical Centre, Singapore 7 Koong and Ho Surgery Centre, Singapore 8 Department of Pathology, Singapore General Hospital, Singapore 9 Institute of Bioengineering and Nanotechnology, Singapore 10 Lucence Diagnostics Pte Ltd, Singapore 11 Department of Physiology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore 12 Office of Clinical and Academic Faculty Affairs, Duke-NUS Graduate Medical School, Singapore * These authors contributed equally to the work Correspondence to: Ann Siew Gek Lee, email: dmslsg@nccs.com.sg Keywords: breast cancer; single-nucleotide polymorphism; risk loci; genotyping; polygenic risk score Received: July 27, 2017 Accepted: January 25, 2018 Published: January 31, 2018 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.