Please use this identifier to cite or link to this item: https://doi.org/10.18632/oncotarget.24374
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dc.titleEvaluation of three polygenic risk score models for the prediction of breast cancer risk in Singapore Chinese
dc.contributor.authorChan, C.H.T
dc.contributor.authorMunusamy, P
dc.contributor.authorLoke, S.Y
dc.contributor.authorKoh, G.L
dc.contributor.authorYang, A.Z.Y
dc.contributor.authorLaw, H.Y
dc.contributor.authorYoon, C.S
dc.contributor.authorWong, C.Y
dc.contributor.authorYong, W.S
dc.contributor.authorWong, N.S
dc.contributor.authorNg, R.C.H
dc.contributor.authorOng, K.W
dc.contributor.authorMadhukumar, P
dc.contributor.authorOey, C.L
dc.contributor.authorHo, G.H
dc.contributor.authorTan, P.H
dc.contributor.authorTan, M.H
dc.contributor.authorAng, P
dc.contributor.authorYap, Y.S
dc.contributor.authorLee, A.S.G
dc.date.accessioned2020-09-04T02:24:53Z
dc.date.available2020-09-04T02:24:53Z
dc.date.issued2018
dc.identifier.citationChan, C.H.T, Munusamy, P, Loke, S.Y, Koh, G.L, Yang, A.Z.Y, Law, H.Y, Yoon, C.S, Wong, C.Y, Yong, W.S, Wong, N.S, Ng, R.C.H, Ong, K.W, Madhukumar, P, Oey, C.L, Ho, G.H, Tan, P.H, Tan, M.H, Ang, P, Yap, Y.S, Lee, A.S.G (2018). Evaluation of three polygenic risk score models for the prediction of breast cancer risk in Singapore Chinese. Oncotarget 9 (16) : 12796-12804. ScholarBank@NUS Repository. https://doi.org/10.18632/oncotarget.24374
dc.identifier.issn1949-2553
dc.identifier.urihttps://scholarbank.nus.edu.sg/handle/10635/174363
dc.description.abstractGenome-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 ageadjustment, 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. © Chan et al.
dc.publisherImpact Journals LLC
dc.sourceUnpaywall 20200831
dc.subjectadult
dc.subjectage
dc.subjectArticle
dc.subjectbreast cancer
dc.subjectcancer risk
dc.subjectcase study
dc.subjectChinese
dc.subjectcohort analysis
dc.subjectcontrolled study
dc.subjectdisease association
dc.subjectfemale
dc.subjectgenome-wide association study
dc.subjectgenotype
dc.subjecthuman
dc.subjectmajor clinical study
dc.subjectmiddle aged
dc.subjectpolygenic risk score
dc.subjectpopulation risk
dc.subjectprediction
dc.subjectrisk factor
dc.subjectscoring system
dc.subjectSingaporean
dc.subjectsingle nucleotide polymorphism
dc.typeArticle
dc.contributor.departmentDUKE-NUS MEDICAL SCHOOL
dc.contributor.departmentSURGERY
dc.contributor.departmentMICROBIOLOGY AND IMMUNOLOGY
dc.description.doi10.18632/oncotarget.24374
dc.description.sourcetitleOncotarget
dc.description.volume9
dc.description.issue16
dc.description.page12796-12804
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