Genome-wide methylation profiles reveal quantitative views of human aging rates.
Genome-wide methylation profiles reveal quantitative views of human aging rates.
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全基因组甲基化谱揭示了人类衰老速度的定量观点。
DOI：
10.1016/j.molcel.2012.10.016
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发表时间：
2013-01-24
期刊：
影响因子：
16
通讯作者：
Zhang, Kang
中科院分区：
文献类型：
--
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
根据分子图谱测量人类衰老的能力在许多领域具有实际意义，包括疾病预防和治疗、法医学和延长寿命。尽管按时间顺序计算的年龄与DNA甲基化的变化有关，但甲基组还没有被用来衡量和比较人类的老龄化速度。在这里，我们使用656名年龄在19岁到101岁之间的人的全血中超过450,000个CpG标记物的测量结果，建立了一个衰老的定量模型。这个模型测量了一个人的甲基组老化的速度，我们显示了性别和遗传变异的影响。此外，我们还表明，衰老速率的差异有助于解释表观遗传漂移，并反映在转录组中。我们的模型突出了衰老过程的特定组成部分，并为研究甲基化在年龄相关疾病中的作用提供了定量读数。
The ability to measure human aging from molecular profiles has practical implications in many fields, including disease prevention and treatment, forensics, and extension of life. Although chronological age has been linked to changes in DNA methylation, the methylome has not yet been used to measure and compare human aging rates. Here, we build a quantitative model of aging using measurements at more than 450,000 CpG markers from the whole blood of 656 human individuals, aged 19 to 101. This model measures the rate at which an individual’s methylome ages, which we show is impacted by gender and genetic variants. Furthermore, we show that differences in aging rates help explain epigenetic drift and are reflected in the transcriptome. Our model highlights specific components of the aging process and provides a quantitative read-out for studying the role of methylation in age-related disease.
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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：
4.4
作者：
Bibikova, Marina;Barnes, Bret;Shen, Richard
通讯作者：
Shen, Richard
影响因子：
3.7
作者：
Bocklandt S;Lin W;Sehl ME;Sánchez FJ;Sinsheimer JS;Horvath S;Vilain E
通讯作者：
Vilain E
影响因子：
9.8
作者：
Fraser HB;Khaitovich P;Plotkin JB;Pääbo S;Eisen MB
通讯作者：
Eisen MB