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采用优先连锁不平衡方法对乳腺癌全基因组关联研究发现进行跨种族随访。

Trans-ethnic follow-up of breast cancer GWAS hits using the preferential linkage disequilibrium approach.

作者信息

Zhu Qianqian, Shepherd Lori, Lunetta Kathryn L, Yao Song, Liu Qian, Hu Qiang, Haddad Stephen A, Sucheston-Campbell Lara, Bensen Jeannette T, Bandera Elisa V, Rosenberg Lynn, Liu Song, Haiman Christopher A, Olshan Andrew F, Palmer Julie R, Ambrosone Christine B

机构信息

Department of Biostatistics and Bioinformatics, Roswell Park Cancer Institute, Buffalo, NY, USA.

Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA.

出版信息

Oncotarget. 2016 Dec 13;7(50):83160-83176. doi: 10.18632/oncotarget.13075.

Abstract

Leveraging population-distinct linkage equilibrium (LD) patterns, trans-ethnic follow-up of variants discovered from genome-wide association studies (GWAS) has proved to be useful in facilitating the identification of bona fide causal variants. We previously developed the preferential LD approach, a novel method that successfully identified causal variants driving the GWAS signals within European-descent populations even when the causal variants were only weakly linked with the GWAS-discovered variants. To evaluate the performance of our approach in a trans-ethnic setting, we applied it to follow up breast cancer GWAS hits identified mostly from populations of European ancestry in African Americans (AA). We evaluated 74 breast cancer GWAS variants in 8,315 AA women from the African American Breast Cancer Epidemiology and Risk (AMBER) consortium. Only 27% of them were associated with breast cancer risk at significance level α=0.05, suggesting race-specificity of the identified breast cancer risk loci. We followed up on those replicated GWAS hits in the AMBER consortium utilizing the preferential LD approach, to search for causal variants or better breast cancer markers from the 1000 Genomes variant catalog. Our approach identified stronger breast cancer markers for 80% of the GWAS hits with at least nominal breast cancer association, and in 81% of these cases, the marker identified was among the top 10 of all 1000 Genomes variants in the corresponding locus. The results support trans-ethnic application of the preferential LD approach in search for candidate causal variants, and may have implications for future genetic research of breast cancer in AA women.

摘要

利用群体特异性连锁不平衡(LD)模式,对全基因组关联研究(GWAS)发现的变异进行跨种族随访已被证明有助于识别真正的因果变异。我们之前开发了优先LD方法,这是一种新颖的方法,即使因果变异与GWAS发现的变异仅有微弱关联,也能成功识别出驱动欧洲裔人群中GWAS信号的因果变异。为了评估我们的方法在跨种族环境中的性能,我们将其应用于随访主要在非裔美国人(AA)中识别出的乳腺癌GWAS信号,这些信号大多来自欧洲血统人群。我们评估了来自非裔美国乳腺癌流行病学与风险(AMBER)联盟的8315名AA女性中的74个乳腺癌GWAS变异。在显著性水平α=0.05时,其中只有27%与乳腺癌风险相关,这表明所识别的乳腺癌风险位点具有种族特异性。我们利用优先LD方法对AMBER联盟中那些重复的GWAS信号进行随访,以从千人基因组变异目录中寻找因果变异或更好的乳腺癌标志物。我们的方法为80%至少具有名义上乳腺癌关联的GWAS信号识别出了更强的乳腺癌标志物,并且在其中81%的案例中,所识别的标志物在相应位点的所有千人基因组变异中排名前10。这些结果支持优先LD方法在跨种族应用中寻找候选因果变异,并可能对未来AA女性乳腺癌的基因研究产生影响。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e695/5341253/4c92512da5c1/oncotarget-07-83160-g001.jpg

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