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全基因组扫描分析非洲裔美国女性乳腺癌风险单倍型。

A genome-wide scan for breast cancer risk haplotypes among African American women.

机构信息

Department of Preventive Medicine, Keck School of Medicine and Norris Comprehensive Cancer Center, University of Southern California, Los Angeles, CA, USA.

出版信息

PLoS One. 2013;8(2):e57298. doi: 10.1371/journal.pone.0057298. Epub 2013 Feb 28.

DOI:10.1371/journal.pone.0057298
PMID:23468962
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC3585353/
Abstract

Genome-wide association studies (GWAS) simultaneously investigating hundreds of thousands of single nucleotide polymorphisms (SNP) have become a powerful tool in the investigation of new disease susceptibility loci. Haplotypes are sometimes thought to be superior to SNPs and are promising in genetic association analyses. The application of genome-wide haplotype analysis, however, is hindered by the complexity of haplotypes themselves and sophistication in computation. We systematically analyzed the haplotype effects for breast cancer risk among 5,761 African American women (3,016 cases and 2,745 controls) using a sliding window approach on the genome-wide scale. Three regions on chromosomes 1, 4 and 18 exhibited moderate haplotype effects. Furthermore, among 21 breast cancer susceptibility loci previously established in European populations, 10p15 and 14q24 are likely to harbor novel haplotype effects. We also proposed a heuristic of determining the significance level and the effective number of independent tests by the permutation analysis on chromosome 22 data. It suggests that the effective number was approximately half of the total (7,794 out of 15,645), thus the half number could serve as a quick reference to evaluating genome-wide significance if a similar sliding window approach of haplotype analysis is adopted in similar populations using similar genotype density.

摘要

全基因组关联研究(GWAS)同时调查数十万个单核苷酸多态性(SNP),已成为研究新疾病易感基因座的有力工具。有时认为单倍型优于 SNP,在遗传关联分析中很有前途。然而,全基因组单倍型分析的应用受到单倍型本身的复杂性和计算的复杂性的阻碍。我们使用全基因组范围内的滑动窗口方法,对 5761 名非裔美国女性(3016 例病例和 2745 例对照)的乳腺癌风险进行了单倍型效应的系统分析。在染色体 1、4 和 18 上有三个区域表现出中度单倍型效应。此外,在先前在欧洲人群中建立的 21 个乳腺癌易感基因座中,10p15 和 14q24 可能含有新的单倍型效应。我们还提出了一种通过对 22 号染色体数据进行置换分析来确定显著性水平和有效独立检验数的启发式方法。它表明,有效数量约为总数的一半(15645 中的 7794),因此如果在使用类似基因型密度的类似人群中采用类似的滑动窗口单倍型分析方法,则可以将其一半作为评估全基因组显著性的快速参考。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/96e6/3585353/450b466def2c/pone.0057298.g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/96e6/3585353/7c7338619818/pone.0057298.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/96e6/3585353/c1898d6c884e/pone.0057298.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/96e6/3585353/068efe41c979/pone.0057298.g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/96e6/3585353/9dd5496a391b/pone.0057298.g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/96e6/3585353/450b466def2c/pone.0057298.g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/96e6/3585353/7c7338619818/pone.0057298.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/96e6/3585353/c1898d6c884e/pone.0057298.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/96e6/3585353/068efe41c979/pone.0057298.g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/96e6/3585353/9dd5496a391b/pone.0057298.g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/96e6/3585353/450b466def2c/pone.0057298.g005.jpg

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