Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
Review
. 2017 Oct 1;26(R2):R216-R224.
doi: 10.1093/hmg/ddx275.

Cell-type deconvolution from DNA methylation: a review of recent applications

Affiliations
Review

Cell-type deconvolution from DNA methylation: a review of recent applications

Alexander J Titus et al. Hum Mol Genet. .

Abstract

Recent advances in cell-type deconvolution approaches are adding to our understanding of the biology underlying disease development and progression. DNA methylation (DNAm) can be used as a biomarker of cell types, and through deconvolution approaches, to infer underlying cell type proportions. Cell-type deconvolution algorithms have two main categories: reference-based and reference-free. Reference-based algorithms are supervised methods that determine the underlying composition of cell types within a sample by leveraging differentially methylated regions (DMRs) specific to cell type, identified from DNAm measures of purified cell populations. Reference-free algorithms are unsupervised methods for use when cell-type specific DMRs are not available, allowing scientists to estimate putative cellular proportions or control for potential confounding from cell type. Reference-based deconvolution is typically applied to blood samples and has potentiated our understanding of the relation between immune profiles and disease by allowing estimation of immune cell proportions from archival DNA. Bioinformatic analyses using DNAm to infer immune cell proportions, part of a new field known as Immunomethylomics, provides a new direction for consideration in epigenome wide association studies (EWAS).

PubMed Disclaimer

Figures

Figure 1
Figure 1
Measured DNA methylation is a composite of signals from specific cell types in a bio-specimen.
Figure 2
Figure 2
Overview of the Immunomethylomics workflow from 1) reference-based deconvolution and cell proportion estimates to 2) utilizing cell proportion estimates in analyses.

Similar articles

Cited by

References

    1. Khavari D.A., Sen G.L., Rinn J.L. (2010) DNA methylation and epigenetic control of cellular differentiation. Cell Cycle, 9, 3880–3883. - PubMed
    1. Ji H., Ehrlich L.I.R., Seita J., Murakami P., Doi A., Lindau P., Lee H., Aryee M.J., Irizarry R.A., Kim K.. et al. (2010) Comprehensive methylome map of lineage commitment from haematopoietic progenitors. Nature, 467, 338–342. - PMC - PubMed
    1. Rönnerblad M., Andersson R., Olofsson T., Douagi I., Karimi M., Lehmann S.S., Hoof I., de Hoon M., Itoh M., Nagao-Sato S.. et al. (2014) Analysis of the DNA methylome and transcriptome in granulopoiesis reveals timed changes and dynamic enhancer methylation. Blood, 123, e79–e89. - PubMed
    1. Houseman E.A., Accomando W.P., Koestler D.C., Christensen B.C., Marsit C.J., Nelson H.H., Wiencke J.K., Kelsey K.T. (2012) DNA methylation arrays as surrogate measures of cell mixture distribution. BMC Bioinformatics, 13, 86.. - PMC - PubMed
    1. Wiencke J.K., Koestler D.C., Salas L.A., Wiemels J.L., Roy R.P., Hansen H.M., Rice T., McCoy L.S., Bracci P.M., Molinaro A.M.. et al. (2017) Immunomethylomic approach to explore the blood neutrophil lymphocyte ratio (NLR) in glioma survival. Clin. Epigenetics, 9, 10.. - PMC - PubMed

Publication types