Epigenetics (Dec 2022)

Comparison of DNA methylation measurements from EPIC BeadChip and SeqCap targeted bisulphite sequencing in PON1 and nine additional candidate genes

  • Dennis Khodasevich,
  • Anna R. Smith,
  • Karen Huen,
  • Brenda Eskenazi,
  • Andres Cardenas,
  • Nina Holland

DOI
https://doi.org/10.1080/15592294.2022.2091818
Journal volume & issue
Vol. 17, no. 13
pp. 1944 – 1955

Abstract

Read online

Epigenome-wide association studies (EWAS) are widely implemented in epidemiology, and the Illumina HumanMethylationEPIC BeadChip (EPIC) DNA microarray is the most-used technology. Recently, next-generation sequencing (NGS)-based methods, which assess DNA methylation at single-base resolution, have become more affordable and technically feasible. While the content of microarray technology is fixed, NGS-based approaches, such as the Roche Nimblegen, SeqCap Epi Enrichment System (SeqCap), offer the flexibility of targeting most CpGs in a gene. With the current usage of microarrays and emerging NGS-based technologies, it is important to establish whether data generated from the two platforms are comparable. We harnessed 112 samples from the Center for the Health Assessment of Mothers and Children of Salinas (CHAMACOS) birth cohort study and compared DNA methylation between the EPIC microarray and SeqCap for PON1 and nine additional candidate genes, by evaluating epigenomic coverage and correlations. We conducted multivariable linear regression and principal component analyses to assess the ability of the EPIC array and SeqCap to detect biological differences in gene methylation by the PON1−108 single nucleotide polymorphism. We found an overall high concordance (r = 0.84) between SeqCap and EPIC DNA methylation, among highly methylated and minimally methylated regions. However, substantial disagreement was present between the two methods in moderately methylated regions, with SeqCap measurements exhibiting greater within-site variation. Additionally, SeqCap did not capture PON1 SNP associated differences in DNA methylation that were evident with the EPIC array. Our findings indicate that microarrays perform well for analysing DNA methylation in large cohort studies but with limited coverage.

Keywords