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Middleton LYM, Dou J, Fisher J, Heiss JA, Nguyen VK, Just AC, Faul J, Ware EB, Mitchell C, Colacino JA, M Bakulski K. Saliva cell type DNA methylation reference panel for epidemiological studies in children. Epigenetics 2021; 17:161-177. [PMID: 33588693 DOI: 10.1080/15592294.2021.1890874] [Citation(s) in RCA: 23] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022] Open
Abstract
Saliva is a widely used biological sample, especially in pediatric research, containing a heterogenous mixture of immune and epithelial cells. Associations of exposure or disease with saliva DNA methylation can be influenced by cell-type proportions. Here, we developed a saliva cell-type DNA methylation reference panel to estimate interindividual cell-type heterogeneity in whole saliva studies. Saliva was collected from 22 children (7-16 years) and sorted into immune and epithelial cells, using size exclusion filtration and magnetic bead sorting. DNA methylation was measured using the Illumina MethylationEPIC BeadChip. We assessed cell-type differences in DNA methylation profiles and tested for enriched biological pathways. Immune and epithelial cells differed at 181,577 (22.8%) DNA methylation sites (t-test p < 6.28 × 10-8). Immune cell hypomethylated sites are mapped to genes enriched for immune pathways (p < 3.2 × 10-5). Epithelial cell hypomethylated sites were enriched for cornification (p = 5.2 × 10-4), a key process for hard palette formation. Saliva immune and epithelial cells have distinct DNA methylation profiles which can drive whole-saliva DNA methylation measures. A primary saliva DNA methylation reference panel, easily implemented with an R package, will allow estimates of cell proportions from whole saliva samples and improve epigenetic epidemiology studies by accounting for measurement heterogeneity by cell-type proportions.
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Affiliation(s)
- Lauren Y M Middleton
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA.,Department of Environmental Health Sciences, School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | - John Dou
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | - Jonah Fisher
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI, USA
| | - Jonathan A Heiss
- Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Vy K Nguyen
- Department of Environmental Health Sciences, School of Public Health, University of Michigan, Ann Arbor, MI, USA.,Department of Computational Medicine and Bioinformatics, Medical School, University of Michigan, Ann Arbor, MI, USA
| | - Allan C Just
- Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Jessica Faul
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI, USA
| | - Erin B Ware
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI, USA.,Population Studies Center, Institute for Social Research, University of Michigan
| | - Colter Mitchell
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI, USA.,Population Studies Center, Institute for Social Research, University of Michigan
| | - Justin A Colacino
- Department of Environmental Health Sciences, School of Public Health, University of Michigan, Ann Arbor, MI, USA.,Department of Nutritional Sciences, School of Public Health, University of Michigan.,Center for Computational Medicine and Bioinformatics, University of Michigan.,Program in the Environment, College of Literature, Sciences, and the Arts, University of Michigan
| | - Kelly M Bakulski
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA
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