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arXiv 1406.3828q-bio.GN
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基因组异常与乳腺癌易感性

Genome disorder and breast cancer susceptibility

Conor Smyth, Iva Špakulova, Owen Cotton-Barratt, Sajjad Rafiq, William Tapper, Rosanna Upstill-Goddard, John L. Hopper, Enes Makalic, Daniel F. Schmidt, Mirosla… 展开作者

Conor Smyth, Iva Špakulova, Owen Cotton-Barratt, Sajjad Rafiq, William Tapper, Rosanna Upstill-Goddard, John L. Hopper, Enes Makalic, Daniel F. Schmidt, Miroslav Kapuscinski, Jörg Fliege, Andrew Collins, Jacek Brodzki, Diana M. Eccles, Ben D. MacArthur

摘要:

许多常见疾病具有复杂的遗传基础,其中大量的遗传变异与环境和生活方式因素相结合,以确定风险。然而,量化这种多基因效应及其与疾病风险的关系一直具有挑战性。为了解决这些困难,我们开发了一个全球措施的信息内容的个人的基因组相对于参考人群,这可能是用来评估全球基因组结构之间的差异的情况下,适当的控制。非正式地,我们称之为相对基因组信息(RGI)的这种测量方法量化了个体基因组的相对“紊乱”。为了测试其预测疾病风险的能力,我们使用RGI来比较来自两个独立的早发性乳腺癌女性样本的单核苷酸多态性基因型与三组独立的对照。我们发现,与所有三组对照组相比,两组乳腺癌病例的RGI显著升高,RGI的疾病风险急剧上升(RGI最高百分位数的比值比大于12)。此外,我们发现这些差异不是由于与少数疾病相关基因座的常见变异的关联,而是由于分布在整个基因组中的数千个标记的组合关联。我们的研究结果表明,一个人的基因组的信息内容可以用来衡量一个复杂的疾病的风险,并建议早发性乳腺癌有一个强大的多基因的基础。

英文摘要:

Many common diseases have a complex genetic basis in which large numbers of genetic variations combine with environmental and lifestyle factors to determine risk. However, quantifying such polygenic effects and their relationship to disease risk has been challenging. In order to address these difficulties we developed a global measure of the information content of an individual's genome relative to a reference population, which may be used to assess differences in global genome structure between cases and appropriate controls. Informally this measure, which we call relative genome information (RGI), quantifies the relative "disorder" of an individual's genome. In order to test its ability to predict disease risk we used RGI to compare single nucleotide polymorphism genotypes from two independent samples of women with early-onset breast cancer with three independent sets of controls. We found that RGI was significantly elevated in both sets of breast cancer cases in comparison with all three sets of controls, with disease risk rising sharply with RGI (odds ratio greater than 12 for the highest percentile RGI). Furthermore, we found that these differences are not due to associations with common variants at a small number of disease-associated loci, but rather are due to the combined associations of thousands of markers distributed throughout the genome. Our results indicate that the information content of an individual's genome may be used to measure the risk of a complex disease, and suggest that early-onset breast cancer has a strongly polygenic basis.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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