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. 2022 Mar;17(3):327-334.
doi: 10.1080/15592294.2021.1950977. Epub 2021 Jul 13.

A comparison of epithelial cell content of oral samples estimated using cytology and DNA methylation

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A comparison of epithelial cell content of oral samples estimated using cytology and DNA methylation

Yen Ting Wong et al. Epigenetics. 2022 Mar.

Abstract

Saliva and buccal samples are popular for epigenome wide association studies (EWAS) due to their ease of collection compared and their ability to sample a different cell lineage compared to blood. As these samples contain a mix of white blood cells and buccal epithelial cells that can vary within a population, this cellular heterogeneity may confound EWAS. This has been addressed by including cellular heterogeneity obtained through cytology at the time of collection or by using cellular deconvolution algorithms built on epigenetic data from specific cell types. However, to our knowledge, the two methods have not yet been compared. Here we show that the two methods are highly correlated in saliva and buccal samples (R = 0.84, P < 0.0001) by comparing data generated from cytological staining and Infinium MethylationEPIC arrays and the EpiDISH deconvolution algorithm from buccal and saliva samples collected from twenty adults. In addition, by using an expanded dataset from both sample types, we confirmed our previous finding that age has strong, non-linear negative correlation with epithelial cell proportion in both sample types. However, children and adults showed a large within-population variation in cellular heterogeneity. Our results validate the use of the EpiDISH algorithm in estimating the effect of cellular heterogeneity in EWAS and showed DNA methylation generally underestimates the epithelial cell content obtained from cytology.

Keywords: Buccal; DNA methylation; EWAS; cell-type heterogeneity; cytology; epithelial cell; saliva.

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Conflict of interest statement

No potential conflict of interest was reported by the author(s).

Figures

Figure 1.
Figure 1.
Examples of cellular morphology in oral samples. Representative fields of view from Diff-Quik staining of (a) saliva, 100x magnification and (b) OCA buccal sample, 400x magnification. Both samples contain large epithelial cells (Epi) with dense nuclei, and smaller immune cells, exemplified by lymphocytes (Lym), segmented cells (Seg) and monocytes (Mono).
Figure 2.
Figure 2.
Comparison of the percentage proportion of epithelial cells in oral samples, estimated using cytology and DNA methylation arrays, collected using three different methods (OCA, OCB and OG) estimated. Means are indicated with crosses. For both methods, the p-values of the difference between percentage of epithelial cells in OCA and OCB was > 0.05 and for the difference between percentage of epithelial cells of buccal sample collection (OCA and OCB) compared to saliva (OG) were < 0.0001.
Figure 3.
Figure 3.
Range of DNA yields for each oral sample type. Box and whisker plots from saliva (OG) and the two methods of buccal sample collection (OCA and OCB). Means are indicated with crosses.
Figure 4.
Figure 4.
Comparison of the proportion of epithelial cells in oral samples estimated from cytology and DNA methylation arrays. Collection methods are indicated by different colours.
Figure 5.
Figure 5.
Comparison for epithelial cell content of oral samples. (a) The relationship between epithelial cell content of oral samples and age over eight studies. Studies are indicated by different colours. (b) Box and whisker plot from epithelial cell content of oral samples from eight studies. Numbers in brackets indicate the mean age of each study.

References

    1. Teschendorff AE, Zheng SC.. Cell-type deconvolution in epigenome-wide association studies: a review and recommendations. Epigenomics. 2017;9(5):757–768. - PubMed
    1. Zheng SC, Breeze CE, Beck S, et al. EpiDISH web server: epigenetic dissection of intra-sample-heterogeneity with online GUI. Bioinformatics. 2019. DOI:10.1093/bioinformatics/btz833. - DOI - PMC - PubMed
    1. Theda C, Hwang SH, Czajko A, et al. Quantitation of the cellular content of saliva and buccal swab samples. Sci Rep. 2018;8(1):6944. - PMC - PubMed
    1. Teschendorff AE, Relton CL. Statistical and integrative system-level analysis of DNA methylation data. Nat Rev Genet. 2018;19(3):129–147. - PubMed
    1. Zheng SC, Webster AP, Dong D, et al. A novel cell-type deconvolution algorithm reveals substantial contamination by immune cells in saliva, buccal and cervix. Epigenomics. 2018;10(7):925–940. - PubMed