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Epigenome-wide differential methylation and differential variability as predictors of high-grade cervical intraepithelial neoplasia (CIN2+).

Publication ,  Journal Article
Bukowski, A; Hoyo, C; Graff, M; Vielot, NA; Kosorok, MR; Brewster, WR; Maguire, RL; Murphy, SK; Nedjai, B; Ladoukakis, E; North, KE; Smith, JS
Published in: Am J Epidemiol
April 8, 2025

CpG site methylation patterns have potential to improve differentiation of high-grade screening-detected cervical abnormalities. We assessed CpG differential methylation (DM) and differential variability (DV) in high-grade (CIN2+) vs low-grade (≤ CIN1) lesions. In ≤ CIN1 (n = 117) and CIN2+ (n = 31) samples, cervical sample DNA underwent testing with Illumina HumanMethylation arrays. We assessed DM and DV of CpG methylation M-values among 9 cervical cancer-associated genes. We fit CpG-specific linear models and estimated empirical Bayes standard errors and false discovery rates (FDRs). An exploratory epigenome-wide association study (EWAS) aimed to detect novel DM and DV CpGs (FDR < 0.05) and Gene Ontology (GO) term enrichment. Compared to ≤ CIN1, CIN2+ exhibited greater methylation at CCNA1 cluster 1 (M-value difference 0.24; 95% CI, 0.04-0.43) and RARB cluster 2 (0.16; 95% CI, 0.05-0.28), and lower methylation at CDH1 cluster 1 (-0.15; 95% CI, -0.26 to -0.04). CIN2+ exhibited lower variability at CDH1 cluster 2 (variation difference -0.24; 95% CI, -0.41 to -0.05) and FHIT cluster 1 (-0.30; 95% CI, -0.50 to -0.09). EWAS detected 3534 DM and 270 DV CpGs. Forty-four GO terms were enriched with DM CpGs related to transcriptional, structural, developmental, and neuronal processes. Methylation patterns may help triage screening-detected cervical abnormalities and inform US screening algorithms. This article is part of a Special Collection on Gynecological Cancer.

Duke Scholars

Published In

Am J Epidemiol

DOI

EISSN

1476-6256

Publication Date

April 8, 2025

Volume

194

Issue

4

Start / End Page

1012 / 1022

Location

United States

Related Subject Headings

  • Uterine Cervical Neoplasms
  • Uterine Cervical Dysplasia
  • Middle Aged
  • Humans
  • Genome-Wide Association Study
  • Female
  • Epigenome
  • Epidemiology
  • DNA Methylation
  • CpG Islands
 

Citation

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MLA
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Bukowski, A., Hoyo, C., Graff, M., Vielot, N. A., Kosorok, M. R., Brewster, W. R., … Smith, J. S. (2025). Epigenome-wide differential methylation and differential variability as predictors of high-grade cervical intraepithelial neoplasia (CIN2+). Am J Epidemiol, 194(4), 1012–1022. https://doi.org/10.1093/aje/kwae254
Bukowski, Alexandra, Cathrine Hoyo, Misa Graff, Nadja A. Vielot, Michael R. Kosorok, Wendy R. Brewster, Rachel L. Maguire, et al. “Epigenome-wide differential methylation and differential variability as predictors of high-grade cervical intraepithelial neoplasia (CIN2+).Am J Epidemiol 194, no. 4 (April 8, 2025): 1012–22. https://doi.org/10.1093/aje/kwae254.
Bukowski A, Hoyo C, Graff M, Vielot NA, Kosorok MR, Brewster WR, et al. Epigenome-wide differential methylation and differential variability as predictors of high-grade cervical intraepithelial neoplasia (CIN2+). Am J Epidemiol. 2025 Apr 8;194(4):1012–22.
Bukowski, Alexandra, et al. “Epigenome-wide differential methylation and differential variability as predictors of high-grade cervical intraepithelial neoplasia (CIN2+).Am J Epidemiol, vol. 194, no. 4, Apr. 2025, pp. 1012–22. Pubmed, doi:10.1093/aje/kwae254.
Bukowski A, Hoyo C, Graff M, Vielot NA, Kosorok MR, Brewster WR, Maguire RL, Murphy SK, Nedjai B, Ladoukakis E, North KE, Smith JS. Epigenome-wide differential methylation and differential variability as predictors of high-grade cervical intraepithelial neoplasia (CIN2+). Am J Epidemiol. 2025 Apr 8;194(4):1012–1022.
Journal cover image

Published In

Am J Epidemiol

DOI

EISSN

1476-6256

Publication Date

April 8, 2025

Volume

194

Issue

4

Start / End Page

1012 / 1022

Location

United States

Related Subject Headings

  • Uterine Cervical Neoplasms
  • Uterine Cervical Dysplasia
  • Middle Aged
  • Humans
  • Genome-Wide Association Study
  • Female
  • Epigenome
  • Epidemiology
  • DNA Methylation
  • CpG Islands