Predicting DNA methylation level across human tissues

Baoshan Ma, Elissa H. Wilker, Saffron A G Willis-Owen, Hyang Min Byun, Kenny C C Wong, Valeria Motta, Andrea A. Baccarelli, Joel Schwartz, William O C M Cookson, Kamal Khabbaz, Murray A. Mittleman, Miriam F. Moffatt, Liming Liang

Research output: Contribution to journalArticle

47 Citations (Scopus)

Abstract

Differences in methylation across tissues are critical to cell differentiation and are key to understanding the role of epigenetics in complex diseases. In this investigation, we found that locus-specific methylation differences between tissues are highly consistent across individuals. We developed a novel statistical model to predict locus-specific methylation in target tissue based on methylation in surrogate tissue. The method was evaluated in publicly available data and in two studies using the latest IlluminaBeadChips: a childhood asthma study with methylation measured in both peripheral blood leukocytes (PBL) and lymphoblastoid cell lines; and a study of postoperative atrial fibrillation with methylation in PBL, atrium and artery. We found that our method can greatly improve accuracy of cross-tissue prediction at CpG sites that are variable in the target tissue [R2 increases from 0.38 (original R2 between tissues) to 0.89 for PBL-toartery prediction; from 0.39 to 0.95 for PBL-toatrium; and from 0.81 to 0.98 for lymphoblastoid cell line-to-PBL based on cross-validation, and confirmed using cross-study prediction]. An extended model with multiple CpGs further improved performance. Our results suggest that large-scale epidemiology studies using easy-to-access surrogate tissues (e.g. blood) could be recalibrated to improve understanding of epigenetics in hardto- access tissues (e.g. atrium) and might enable non-invasive disease screening using epigenetic profiles.

Original languageEnglish
Pages (from-to)3515-3528
Number of pages14
JournalNucleic Acids Research
Volume42
Issue number6
DOIs
Publication statusPublished - 2014

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DNA Methylation
Methylation
Leukocytes
Epigenomics
Cell Line
Statistical Models
Atrial Fibrillation
Cell Differentiation
Epidemiology
Asthma
Arteries

ASJC Scopus subject areas

  • Genetics

Cite this

Ma, B., Wilker, E. H., Willis-Owen, S. A. G., Byun, H. M., Wong, K. C. C., Motta, V., ... Liang, L. (2014). Predicting DNA methylation level across human tissues. Nucleic Acids Research, 42(6), 3515-3528. https://doi.org/10.1093/nar/gkt1380

Predicting DNA methylation level across human tissues. / Ma, Baoshan; Wilker, Elissa H.; Willis-Owen, Saffron A G; Byun, Hyang Min; Wong, Kenny C C; Motta, Valeria; Baccarelli, Andrea A.; Schwartz, Joel; Cookson, William O C M; Khabbaz, Kamal; Mittleman, Murray A.; Moffatt, Miriam F.; Liang, Liming.

In: Nucleic Acids Research, Vol. 42, No. 6, 2014, p. 3515-3528.

Research output: Contribution to journalArticle

Ma, B, Wilker, EH, Willis-Owen, SAG, Byun, HM, Wong, KCC, Motta, V, Baccarelli, AA, Schwartz, J, Cookson, WOCM, Khabbaz, K, Mittleman, MA, Moffatt, MF & Liang, L 2014, 'Predicting DNA methylation level across human tissues', Nucleic Acids Research, vol. 42, no. 6, pp. 3515-3528. https://doi.org/10.1093/nar/gkt1380
Ma B, Wilker EH, Willis-Owen SAG, Byun HM, Wong KCC, Motta V et al. Predicting DNA methylation level across human tissues. Nucleic Acids Research. 2014;42(6):3515-3528. https://doi.org/10.1093/nar/gkt1380
Ma, Baoshan ; Wilker, Elissa H. ; Willis-Owen, Saffron A G ; Byun, Hyang Min ; Wong, Kenny C C ; Motta, Valeria ; Baccarelli, Andrea A. ; Schwartz, Joel ; Cookson, William O C M ; Khabbaz, Kamal ; Mittleman, Murray A. ; Moffatt, Miriam F. ; Liang, Liming. / Predicting DNA methylation level across human tissues. In: Nucleic Acids Research. 2014 ; Vol. 42, No. 6. pp. 3515-3528.
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