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
. 2023 Aug 16;6(1):780.
doi: 10.1038/s42003-023-05070-z.

Global endometrial DNA methylation analysis reveals insights into mQTL regulation and associated endometriosis disease risk and endometrial function

Affiliations

Global endometrial DNA methylation analysis reveals insights into mQTL regulation and associated endometriosis disease risk and endometrial function

Sally Mortlock et al. Commun Biol. .

Abstract

Endometriosis is a leading cause of pain and infertility affecting millions of women globally. Herein, we characterize variation in DNA methylation (DNAm) and its association with menstrual cycle phase, endometriosis, and genetic variants through analysis of genotype data and methylation in endometrial samples from 984 deeply-phenotyped participants. We estimate that 15.4% of the variation in endometriosis is captured by DNAm and identify significant differences in DNAm profiles associated with stage III/IV endometriosis, endometriosis sub-phenotypes and menstrual cycle phase, including opening of the window for embryo implantation. Menstrual cycle phase was a major source of DNAm variation suggesting cellular and hormonally-driven changes across the cycle can regulate genes and pathways responsible for endometrial physiology and function. DNAm quantitative trait locus (mQTL) analysis identified 118,185 independent cis-mQTLs including 51 associated with risk of endometriosis, highlighting candidate genes contributing to disease risk. Our work provides functional evidence for epigenetic targets contributing to endometriosis risk and pathogenesis. Data generated serve as a valuable resource for understanding tissue-specific effects of methylation on endometrial biology in health and disease.

PubMed Disclaimer

Conflict of interest statement

The authors declare no competing interests.

Figures

Fig. 1
Fig. 1. Cycle phase differences.
a Upset plot showing the number of significantly differently methylated sites between each comparison on the y-axis bar plot and the number of intersecting DNA methylation (DNAm) sites on the x-axis bar plot. The comparisons included in the intersection are depicted by dots and lines adjoining those dots. A total of 984 samples were included in these analyses (menstrual n = 50, proliferative (PE) n = 473, secretory (SE) n = 461, early secretory (ESE) n = 122, mid secretory (MSE) n = 209, late secretory (LSE) n = 108). b Heatmap of the top 50 most differentially methylated sites between the secretory (orange) and proliferative phase (green) of the menstrual cycle as annotated on the bar above the heatmap. Red denotes positive methylation M-values and blue denotes negative methylation M-values. c Pathways significantly enriched for genes annotated to differentially methylated sites between the secretory and proliferative phase.
Fig. 2
Fig. 2. Network analysis.
a Modules of DNA methylation (DNAm) sites defined using WGCNA and their association with endometriosis status and menstrual cycle stage. * represents the degree of significance (***p-value = 0–0.001; **p-value = 0.001–0.01; *p-value = 0.01–0.05). b Network map of the top 5 most significantly enriched pathways for genes annotated to modules associated with endometriosis stage III/IV case:control. A total of 984 samples were included in these analyses (menstrual n = 50, proliferative (PE) n = 473, secretory (SE) n = 461, early secretory (ESE) n = 122, mid secretory (MSE) n = 209, late secretory (LSE) n = 108; cases n = 637 (stage I/II n = 344, stage III/IV n = 286), controls n = 347).
Fig. 3
Fig. 3. GREB1 mQTL associated with endometriosis risk.
The top panel shows ensemble transcripts present in the locus. The bottom panel consists of association plots, each point is a SNP plotted according to its genomic position on the x-axis and −log10 p-value for its association with endometriosis (red) DNA methylation (DNAm) at cg07314298 (purple) and GREB1 splicing in ovary (blue) on the y-axis. The position of the associated spliced intron (blue) is featured in the middle panel alongside the position of the significant SMR mQTL SNP (red) and DNAm site (purple) and the position of a predicted enhancer in uterus and ovary (green). Boxplots show the difference in DNAm and intron excision according to the genotype at rs1865573. A total of 658 European samples were used in the mQTL analysis to test for associations between genotype and DNAm in endometrium.
Fig. 4
Fig. 4. EEFSEC mQTL associated with endometriosis risk.
The top panel shows ensemble transcripts present in the locus. The bottom panel consists of association plots, each point is a SNP plotted according to its genomic position on the x-axis and −log10 p-value for its association with endometriosis (red) DNA methylation (DNAm) at six SMR significant DNAm sites (purple) and EEFSEC expression in muscle (blue) on the y-axis. The position of the significant SMR mQTL SNPs (red) and DNAm sites (purple) is featured in the middle panel above DNase-seq peaks, H3K27ac peaks and predicted chromatin marks in uterus. A total of 658 European samples were used in the mQTL analysis to test for associations between genotype and DNAm in endometrium.
Fig. 5
Fig. 5. Heatmap for effect sizes of 66 differentially methylated sites across 17 sub-phenotype comparisons.
DNA methylation (DNAm) sites are presented as rows and differential DNAm analysis for each phenotype is presented as columns. * Denotes statistically significant DNAm sites passing the locus specific Bonferroni-based multiple-testing correction (p < 0.05/N of DNAm sites per GWAS locus). allendo: all endometriosis cases (n = 637), prico: NUPP controls (n = 201), spe: superficial lesions (n = 600), sta: rASRM stage I/II disease (n = 344), stb: rASRM stage III/IV disease (n = 286), oma: endometrioma (n = 211), omanode: cases with endometriomas but no deep lesions (n = 50), de: deep lesions (n = 299), denooma: cases with deep lesions but no endometriomas (n = 138), deomaspe: cases with co-occurrence of superficial lesions, endometriomas and deep lesions (n = 155), dyspareunia: cases with dyspareunia (n = 320), onlydysparunia: cases with dyspareunia but no acyclic or dychezia (n = 51), acyclic: cases with acyclic pelvic pain (n = 423), onlyacyclical: cases with acyclic pelvic pain but no dyspareunia or dyschezia (n = 128), obowelmovpa: cases with only dyschezia (n = 98).

References

    1. Rowlands IJ, et al. Prevalence and incidence of endometriosis in Australian women: a data linkage cohort study. BJOG. 2021;128:657–665. doi: 10.1111/1471-0528.16447. - DOI - PubMed
    1. Shafrir AL, et al. Risk for and consequences of endometriosis: A critical epidemiologic review. Best. Pract. Res. Clin. Obstet. Gynaecol. 2018;51:1–15. doi: 10.1016/j.bpobgyn.2018.06.001. - DOI - PubMed
    1. Armour M, Lawson K, Wood A, Smith CA, Abbott J. The cost of illness and economic burden of endometriosis and chronic pelvic pain in Australia: a national online survey. PLoS ONE. 2019;14:e0223316–e0223316. doi: 10.1371/journal.pone.0223316. - DOI - PMC - PubMed
    1. Simoens S, et al. The burden of endometriosis: costs and quality of life of women with endometriosis and treated in referral centres. Hum. Reprod. 2012;27:1292–1299. doi: 10.1093/humrep/des073. - DOI - PubMed
    1. Burney RO, Giudice LC. Pathogenesis and pathophysiology of endometriosis. Fertil. Steril. 2012;98:511–519. doi: 10.1016/j.fertnstert.2012.06.029. - DOI - PMC - PubMed

Publication types