A study of the influence of sex on genome wide methylation.
A study of the influence of sex on genome wide methylation.
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DOI：
10.1371/journal.pone.0010028
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发表时间：
2010-04-06
期刊：
影响因子：
3.7
通讯作者：
Calhoun VD
中科院分区：
文献类型：
--
作者：
Liu J;Morgan M;Hutchison K;Calhoun VD
在特定的基因疾病研究和健康的甲基化变异研究中已经观察到甲基化状态的性别差异，但是在基因组范围内的位点到位点水平上研究性别对甲基化的影响或确定基因组关联研究中考虑性别的方法的工作很少。在这项研究中，我们利用20,493个CpG位点研究了基因组性别对197名受试者（54名女性）唾液DNA甲基化的影响。两样本t检验、主成分分析和独立成分分析三种方法均能成功识别性别影响。结果表明，性别不仅影响X染色体基因的甲基化，也影响常染色体的甲基化。580个常染色体位点显示男性和女性之间存在明显差异。它们高度参与了8个功能基团，包括DNA转录、RNA剪接、膜等。同样重要的是，我们发现一些甲基化位点不仅与性别有关，还与其他表型（年龄、吸烟和饮酒水平以及癌症）有关。通过独立的血细胞DNA甲基化数据（来自癌症面板阵列的1298个CpG位点）进行验证。观察到相同的基因组位点特异性影响模式和与癌症的潜在混淆效应。唾液和血细胞之间已确定的性别影响基因重叠率在X染色体为81%，在常染色体为8%。因此，对性的矫正是必要的。我们提出了一种基于独立分量分析的简单校正方法，该方法是一种数据驱动的方法，可以适应样本差异。校正前后的比较表明，该方法能够有效地消除性别的潜在混淆影响，而不影响其他表型。因此，我们的方法能够在全基因组水平上解开性别影响，并为在全基因组甲基化研究中实现更准确的关联分析铺平了道路。
Sex differences in methylation status have been observed in specific gene-disease studies and healthy methylation variation studies, but little work has been done to study the impact of sex on methylation at the genome wide locus-to-locus level or to determine methods for accounting for sex in genomic association studies. In this study we investigate the genomic sex effect on saliva DNA methylation of 197 subjects (54 females) using 20,493 CpG sites. Three methods, two-sample T-test, principle component analysis and independent component analysis, all successfully identify sex influences. The results show that sex not only influences the methylation of genes in the X chromosome but also in autosomes. 580 autosomal sites show strong differences between males and females. They are found to be highly involved in eight functional groups, including DNA transcription, RNA splicing, membrane, etc. Equally important is that we identify some methylation sites associated with not only sex, but also other phenotypes (age, smoking and drinking level, and cancer). Verification was done through an independent blood cell DNA methylation data (1298 CpG sites from a cancer panel array). The same genomic site-specific influence pattern and potential confounding effects with cancer were observed. The overlapping rate of identified sex affected genes between saliva and blood cell is 81% for X chromosome, and 8% for autosomes. Therefore, correction for sex is necessary. We propose a simple correction method based on independent component analysis, which is a data driven method and accommodates sample differences. Comparison before and after the correction suggests that the method is able to effectively remove the potentially confounding effects of sex, and leave other phenotypes untouched. As such, our method is able to disentangle the sex influence on a genome wide level, and paves the way to achieve more accurate association analyses in genome wide methylation studies.
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