Details

Autor(en) / Beteiligte

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

Titel

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

Ist Teil von

• Oncotarget, 2018-02, Vol.9 (16), p.12796-12804

Ort / Verlag

United States: Impact Journals LLC

Erscheinungsjahr

2018

Quelle

Free E-Journal (出版社公開部分のみ）

Beschreibungen/Notizen

• 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.