背景:虽然已经广泛研究了实足年龄与全血中DNA甲基化(DNAm)的关系,与年龄相关的DNAm变化的组织特异性仍然是一个活跃的研究领域.研究了大脑等组织中年龄与DNAm的关系,皮肤,免疫细胞,脂肪,肝脏已经确定了组织特异性和非特异性效应,因此,激发了对不同人体组织和细胞类型的其他研究。
结果:这里,我们进行了全表观基因组关联研究,利用来自961个组织样本的DNAM数据(IlluminaEPIC阵列),代表9种组织类型(乳腺,肺,结肠,子房,前列腺,骨骼肌,睾丸,全血,和肾脏)来自基因型-组织表达(GTEx)项目。我们确定了8个组织中与年龄相关的CpG位点(错误发现率<0.05)(除骨骼肌外,n=47)。这包括在所有组织类型中的162,002个独特的高甲基化和90,626个低甲基化CpG位点,在单一组织类型中观察到130,137(80%)高甲基化CpG和74,703(82%)低甲基化CpG位点。虽然大多数与年龄相关的CpG位点表现为组织特异性,基因组特征之间的富集模式,如染色质状态和CpG岛,大多数组织都相似,提示细胞衰老的共同机制。与以前的发现一致,我们观察到,高甲基化的CpG位点在具有抑制的多梳特征和CpG岛的区域中富集,而低甲基化CpG位点优先出现在非CpG岛和增强子中。为了深入了解与年龄相关的DNAm变化的功能效应,我们评估了DNAm与局部基因表达变化之间的相关性,以确定与年龄相关的表达数量性状甲基化(age-eQTM).我们确定了多种组织类型中存在的几种年龄eQTM,包括在CDKN2A中,HENMT1和VCWE区域。
结论:总体而言,我们的研究结果将有助于未来开发衰老的生物标志物,并了解不同人体组织类型的衰老机制。
BACKGROUND: While the association of chronological age with DNA methylation (DNAm) in whole blood has been extensively studied, the tissue-specificity of age-related DNAm changes remains an active area of research. Studies investigating the association of age with DNAm in tissues such as brain, skin, immune cells, fat, and liver have identified tissue-specific and non-specific effects, thus, motivating additional studies of diverse human tissue and cell types.
RESULTS: Here, we performed an epigenome-wide association study, leveraging DNAm data (Illumina EPIC array) from 961 tissue samples representing 9 tissue types (breast, lung, colon, ovary, prostate, skeletal muscle, testis, whole blood, and kidney) from the Genotype-Tissue Expression (GTEx) project. We identified age-associated CpG sites (false discovery rate < 0.05) in 8 tissues (all except skeletal muscle, n = 47). This included 162,002 unique hypermethylated and 90,626 hypomethylated CpG sites across all tissue types, with 130,137 (80%) hypermethylated CpGs and 74,703 (82%) hypomethylated CpG sites observed in a single tissue type. While the majority of age-associated CpG sites appeared tissue-specific, the patterns of enrichment among genomic features, such as chromatin states and CpG islands, were similar across most tissues, suggesting common mechanisms underlying cellular aging. Consistent with previous findings, we observed that hypermethylated CpG sites are enriched in regions with repressed polycomb signatures and CpG islands, while hypomethylated CpG sites preferentially occurred in non-CpG islands and enhancers. To gain insights into the functional effects of age-related DNAm changes, we assessed the correlation between DNAm and local gene expression changes to identify age-related expression quantitative trait methylation (age-eQTMs). We identified several age-eQTMs present in multiple tissue-types, including in the CDKN2A, HENMT1, and VCWE regions.
CONCLUSIONS: Overall, our findings will aid future efforts to develop biomarkers of aging and understand mechanisms of aging in diverse human tissue types.