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Multicenter Study
. 2020 Nov 23;12(1):180.
doi: 10.1186/s13148-020-00966-7.

DNA methylation signatures to predict the cervicovaginal microbiome status

Nuno R Nené  1   2 , James Barrett  1   3   4 , Allison Jones  1 , Iona Evans  1 , Daniel Reisel  1 , John F Timms  1 , Tobias Paprotka  5 , Andreas Leimbach  5 , Dorella Franchi  6 , Nicoletta Colombo  6   7 , Line Bjørge  8   9 , Michal Zikan  10   11 , David Cibula  11 , Martin Widschwendter  12   13   14
Affiliations
Multicenter Study

DNA methylation signatures to predict the cervicovaginal microbiome status

Nuno R Nené et al. Clin Epigenetics. .

Abstract

Background: The composition of the microbiome plays an important role in human health and disease. Whether there is a direct association between the cervicovaginal microbiome and the host's epigenome is largely unexplored.

Results: Here we analyzed a total of 448 cervicovaginal smear samples and studied both the DNA methylome of the host and the microbiome using the Illumina EPIC array and next-generation sequencing, respectively. We found that those CpGs that are hypo-methylated in samples with non-lactobacilli (O-type) dominating communities are strongly associated with gastrointestinal differentiation and that a signature consisting of 819 CpGs was able to discriminate lactobacilli-dominating (L-type) from O-type samples with an area under the receiver operator characteristic curve (AUC) of 0.84 (95% CI = 0.77-0.90) in an independent validation set. The performance found in samples with more than 50% epithelial cells was further improved (AUC 0.87) and in women younger than 50 years of age was even higher (AUC 0.91). In a subset of 96 women, the buccal but not the blood cell DNA showed the same trend as the cervicovaginal samples in discriminating women with L- from O-type cervicovaginal communities.

Conclusions: These findings strongly support the view that the epithelial epigenome plays an essential role in hosting specific microbial communities.

Keywords: Cervicovaginal microbiome; DNA methylation; Epigenome–microbiome interaction; Penalized regression.

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Conflict of interest statement

AL and TP are employees of Eurofins, which offers 16S rRNA gene sequencing as a service. NC reports personal fees from Roche, Pharmamar, AstraZeneca, Clovis, Tesaro, Pfizer, Takeda and Biocad. All other authors declare no competing interests.

Figures

Fig. 1
Fig. 1
Enrichment of input CpG feature space. a Input feature pool enrichment for CpG region. b Input feature pool enrichment for cell-type (eFORGE). See “Methods” section for details. See also Additional file 1: Fig. S4
Fig. 2
Fig. 2
WID-LO-index performance in cervical samples. a Receiver operating characteristic curves for the linear classifier in the validation set. b, c WID-LO-index in the validation set, trend with IC (b) and with age (c). d Adjusted odds ratios for the association of WID-LO-index with community-type determined from sample microbiota proportions, Age < 50 years subgroup. See also Additional file 1: Fig. S7. (*) corresponds to adjustment for Age. (**) corresponds to adjustment for IC. (***) corresponds to adjustment for age and IC. Odds ratios, 95% confidence intervals and p values were calculated under a logistic regression model with a bias reduction method. IC = immune cell proportion. The WID-LO-index was generated with 819 selected CpGs. See “Methods” section for details
Fig. 3
Fig. 3
Association of the WID-LO-index with each of the additional covariates collected. a Age < 50 years. b Age ≥ 50 years. See “Methods” section for details. BMI = body mass index (kg/m2). OCP = oral contraceptive pill. HRT = hormone replacement therapy. CH = combined hormone. See also Additional file 1: Tables S5 and S6
Fig. 4
Fig. 4
Validation in buccal and blood samples. a, b Receiver operating characteristic curves for the linear WID-LO-index classifier in buccal (a) and blood samples (b). c, d Receiver operating characteristic curves for the NL WID-LO-index, in the validation set (c) and in buccal samples (d). See also Additional file 1: Figs. S10, S11, S12 and S13. The WID-LO-index was generated with 819 CpGs. The NL WID-LO-index was generated with 1,162 features (c, d). IC = immune cell proportion. See “Methods” section for details
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