Bakulski Kelly M, Feinberg Jason I, Andrews Shan V, Yang Jack, Brown Shannon, L McKenney Stephanie, Witter Frank, Walston Jeremy, Feinberg Andrew P, Fallin M Daniele
a Department of Epidemiology , Johns Hopkins University Bloomberg School of Public Health , Baltimore , Maryland , USA.
b Center for Epigenetics, Johns Hopkins University School of Medicine , Baltimore , Maryland , USA.
Epigenetics. 2016 May 3;11(5):354-62. doi: 10.1080/15592294.2016.1161875. Epub 2016 Mar 28.
Epigenome-wide association studies of disease widely use DNA methylation measured in blood as a surrogate tissue. Cell proportions can vary between people and confound associations of exposure or outcome. An adequate reference panel for estimating cell proportions from adult whole blood for DNA methylation studies is available, but an analogous cord blood cell reference panel is not yet available. Cord blood has unique cell types and the epigenetic signatures of standard cell types may not be consistent throughout the life course. Using magnetic bead sorting, we isolated cord blood cell types (nucleated red blood cells, granulocytes, monocytes, natural killer cells, B cells, CD4(+)T cells, and CD8(+)T cells) from 17 live births at Johns Hopkins Hospital. We confirmed enrichment of the cell types using fluorescence assisted cell sorting and ran DNA from the separated cell types on the Illumina Infinium HumanMethylation450 BeadChip array. After filtering, the final analysis was on 104 samples at 429,794 probes. We compared cell type specific signatures in cord to each other and methylation at 49.2% of CpG sites on the array differed by cell type (F-test P < 10(-8)). Differences between nucleated red blood cells and the remainder of the cell types were most pronounced (36.9% of CpG sites at P < 10(-8)) and 99.5% of these sites were hypomethylated relative to the other cell types. We also compared the mean-centered sorted cord profiles to the available adult reference panel and observed high correlation between the overlapping cell types for granulocytes and monocytes (both r=0.74), and poor correlation for CD8(+)T cells and NK cells (both r=0.08). We further provide an algorithm for estimating cell proportions in cord blood using the newly developed cord reference panel, which estimates biologically plausible cell proportions in whole cord blood samples.
疾病的全表观基因组关联研究广泛使用血液中测量的DNA甲基化作为替代组织。细胞比例在个体之间可能会有所不同,并混淆暴露或结果的关联。目前有一个用于从成人全血中估计DNA甲基化研究细胞比例的合适参考面板,但类似的脐带血细胞参考面板尚未可用。脐带血具有独特的细胞类型,标准细胞类型的表观遗传特征在整个生命过程中可能不一致。我们使用磁珠分选技术,从约翰霍普金斯医院的17例活产中分离出脐带血细胞类型(有核红细胞、粒细胞、单核细胞、自然杀伤细胞、B细胞、CD4(+)T细胞和CD8(+)T细胞)。我们使用荧光辅助细胞分选技术确认了细胞类型的富集,并将分离出的细胞类型的DNA在Illumina Infinium HumanMethylation450 BeadChip阵列上进行检测。经过筛选,最终分析在429,794个探针的104个样本上进行。我们比较了脐带血中细胞类型特异性特征之间的差异,发现阵列上49.2%的CpG位点的甲基化因细胞类型而异(F检验P < 10(-8))。有核红细胞与其他细胞类型之间的差异最为明显(36.9%的CpG位点P < 10(-8)),其中99.5%的这些位点相对于其他细胞类型是低甲基化的。我们还将平均中心化的分选脐带血图谱与现有的成人参考面板进行比较,观察到粒细胞和单核细胞重叠细胞类型之间的相关性较高(r均为0.74),而CD8(+)T细胞和自然杀伤细胞之间的相关性较差(r均为0.08)。我们进一步提供了一种使用新开发的脐带血参考面板估计脐带血中细胞比例的算法,该算法可估计全脐带血样本中生物学上合理的细胞比例。