DNA methylation of cord blood cell types: Applications for mixed cell birth studies

• Published in: Epigenetics 2016-05, Vol.11 (5), p.354-362
• Main Authors: 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
• Format: Article
• Language: English
• Subjects: B-Lymphocytes - metabolism; CD4-Positive T-Lymphocytes - metabolism; CD8-Positive T-Lymphocytes - metabolism; Cellular heterogeneity; cord blood; CpG Islands - genetics; DNA methylation; DNA Methylation - genetics; epidemiology; Epigenomics; Erythroblasts - metabolism; Female; Fetal Blood - cytology; Fetal Blood - metabolism; Genome, Human; Granulocytes - metabolism; Humans; Infant, Newborn; Killer Cells, Natural - metabolism; Live Birth - genetics; Male; Monocytes - metabolism; nucleated red blood cells; Research Paper
• ISSN: 1559-2294; 1559-2308
• DOI: 10.1080/15592294.2016.1161875

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.