Alexandra Bukowski, Cathrine Hoyo, Misa Graff, Nadja A Vielot, Michael R Kosorok, Wendy R Brewster, Rachel L Maguire, Susan K Murphy, Belinda Nedjai, Efthymios Ladoukakis, Kari E North, Jennifer S Smith
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引用次数: 0
Abstract
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.
期刊介绍:
The American Journal of Epidemiology is the oldest and one of the premier epidemiologic journals devoted to the publication of empirical research findings, opinion pieces, and methodological developments in the field of epidemiologic research.
It is a peer-reviewed journal aimed at both fellow epidemiologists and those who use epidemiologic data, including public health workers and clinicians.