Concordant and discordant DNA methylation signatures of aging in human blood and brain.
Concordant and discordant DNA methylation signatures of aging in human blood and brain.
复制标题
人类血液和大脑衰老的一致性和不一致的DNA甲基化特征。
DOI:
10.1186/s13072-015-0011-y
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发表时间:
2015
影响因子:
3.9
通讯作者:
Kobor MS
中科院分区:
文献类型:
--
作者:
Farré P;Jones MJ;Meaney MJ;Emberly E;Turecki G;Kobor MS
DNA methylation is an epigenetic mark that balances plasticity with stability. While DNA methylation exhibits tissue specificity, it can also vary with age and potentially environmental exposures. In studies of DNA methylation, samples from specific tissues, especially brain, are frequently limited and so surrogate tissues are often used. As yet, we do not fully understand how DNA methylation profiles of these surrogate tissues relate to the profiles of the central tissue of interest. We have adapted principal component analysis to analyze data from the Illumina 450K Human Methylation array using a set of 17 individuals with 3 brain regions and whole blood. All of the top five principal components in our analysis were associated with a variable of interest: principal component 1 (PC1) differentiated brain from blood, PCs 2 and 3 were representative of tissue composition within brain and blood, respectively, and PCs 4 and 5 were associated with age of the individual (PC4 in brain and PC5 in both brain and blood). We validated our age-related PCs in four independent sample sets, including additional brain and blood samples and liver and buccal cells. Gene ontology analysis of all five PCs showed enrichment for processes that inform on the functions of each PC. Principal component analysis (PCA) allows simultaneous and independent analysis of tissue composition and other phenotypes of interest. We discovered an epigenetic signature of age that is not associated with cell type composition and required no correction for cellular heterogeneity. The online version of this article (doi:10.1186/s13072-015-0011-y) contains supplementary material, which is available to authorized users.
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影响因子:
10
作者:
Jiang R;Jones MJ;Sava F;Kobor MS;Carlsten C
通讯作者:
Carlsten C
影响因子:
3.7
作者:
Boks MP;Derks EM;Weisenberger DJ;Strengman E;Janson E;Sommer IE;Kahn RS;Ophoff RA
通讯作者:
Ophoff RA
影响因子:
4.5
作者:
Christensen BC;Houseman EA;Marsit CJ;Zheng S;Wrensch MR;Wiemels JL;Nelson HH;Karagas MR;Padbury JF;Bueno R;Sugarbaker DJ;Yeh RF;Wiencke JK;Kelsey KT
通讯作者:
Kelsey KT
影响因子:
12.3
作者:
Jaffe AE;Irizarry RA
通讯作者:
Irizarry RA
影响因子:
16
作者:
Hannum, Gregory;Guinney, Justin;Zhao, Ling;Zhang, Li;Hughes, Guy;Sadda, SriniVas;Klotzle, Brandy;Bibikova, Marina;Fan, Jian-Bing;Gao, Yuan;Deconde, Rob;Chen, Menzies;Rajapakse, Indika;Friend, Stephen;Ideker, Trey;Zhang, Kang
通讯作者:
Zhang, Kang