Variation in DNA methylation of human blood over a 1-year period using the Illumina MethylationEPIC array. Issue 10 (2nd November 2018)

• Record Type: Journal Article
• Authors: Zaimi, Ina; Pei, Dong; Koestler, Devin C.; Marsit, Carmen J.; De Vivo, Immaculata; Tworoger, Shelley S.; Shields, Alexandra E.; Kelsey, Karl T.; Michaud, Dominique S.
• Is Part Of: Epigenetics. Volume 13:Issue 10/11(2018)
• Page Start: 1056
• Page End: 1071
• Publication Date: 2018-11-02
• Subjects: DNA methylation -- reproducibility -- Illumina MethylationEPIC array; Epigenesis -- Periodicals; Epigenetica; 572.86505
• DOI: 10.1080/15592294.2018.1530008
• Languages: English
• ISSNs: 1559-2294

Abstract

ABSTRACT: Assessing DNA methylation profiles in human blood has become a major focus of epidemiologic inquiry. Understanding variability in CpG-specific DNA methylation over moderate periods of time is a critical first step in identifying CpG sites that are candidates for DNA methylation-based etiologic, diagnostic and prognostic predictors of pathogenesis. Using the Illumina MethylationEPIC [850K] BeadArray, DNA methylation was profiled in paired whole blood samples collected approximately 1 year apart from 35 healthy women enrolled in the Nurses Study II cohort. The median intraclass correlation coefficient (ICC) across all CpG loci was 0.19 [Interquartile Range (IQR) 0.00–0.50]; 74.8% of ICCs were in the low range (0–0.5), 16.9% in the mid-range of ICCs (0.5–0.8), and 8.3% in the high-range of ICCs (0.8–1). ICCs were similar for CpG probes on the 450K Illumina array (median 0.17) and the new probes added to the 850K array (median 0.21). ICCs for CpG loci on the sex chromosomes and known metastable epialleles were high (median 0.71, 0.97, respectively), and ICCs among methylation quantitative trait loci (mQTL) CpGs were significantly higher as compared to non-mQTL CpGs (median 0.73, 0.16, respectively, P < 2 × 10 – 16 ). We observed wide variation in DNA methylation stability over a 1-year period. Probes considered non-stable, due to substantial variation over a moderate period of time and with minimal variability across individuals could be removed in large epidemiological studies. Moreover, adjusting for technical variation that arises from using high-dimensional arrays is critical.