Low reliability of DNA methylation across Illumina Infinium platforms in cord blood: implications for replication studies and meta-analyses of prenatal exposures

Abstract

Background: There is an increasing interest in the role of epigenetics in epidemiology, but the emerging research field faces several critical biological and technical challenges. In particular, recent studies have shown poor correlation of measured DNA methylation (DNAm) levels within and across Illumina Infinium platforms in various tissues. In this study, we have investigated concordance between 450 k and EPIC Infinium platforms in cord blood. We could not replicate our previous findings on the association of prenatal paracetamol exposure with cord blood DNAm, which prompted an investigation of cross-platform DNAm differences.

Results: This study is based on two DNAm data sets from cord blood samples selected from the Norwegian Mother, Father and Child Cohort Study (MoBa). DNAm of one data set was measured using the 450 k platform and the other data set was measured using the EPIC platform. Initial analyses of the EPIC data could not replicate any of our previous significant findings in the 450 k data on associations between prenatal paracetamol exposure and cord blood DNAm. A subset of the samples (n = 17) was included in both data sets, which enabled analyses of technical sources potentially contributing to the negative replication. Analyses of these 17 samples with repeated measurements revealed high per-sample correlations ([Formula: see text] 0.99), but low per-CpG correlations ([Formula: see text] ≈ 0.24) between the platforms. 1.7% of the CpGs exhibited a mean DNAm difference across platforms > 0.1. Furthermore, only 26.7% of the CpGs exhibited a moderate or better cross-platform reliability (intra-class correlation coefficient ≥ 0.5).

Conclusion: The observations of low cross-platform probe correlation and reliability corroborate previous reports in other tissues. Our study cannot determine the origin of the differences between platforms. Nevertheless, it emulates the setting in studies using data from multiple Infinium platforms, often analysed several years apart. Therefore, the findings may have important implications for future epigenome-wide association studies (EWASs), in replication, meta-analyses and longitudinal studies. Cognisance and transparency of the challenges related to cross-platform studies may enhance the interpretation, replicability and validity of EWAS results both in cord blood and other tissues, ultimately improving the clinical relevance of epigenetic epidemiology.

Keywords: EWAS; Epigenetic epidemiology; Epigenetics; Illumina Infinium platforms; MBRN; Microarrays; MoBa; Reliability; Replication; Validity.

Fig. 1

Overview of the ICC distribution computed from raw data and from data pre-processed using the default settings of five common EWAS analysis pipelines. Additionally, we included one common analysis pipeline (“RnBeads (customised)”, including the normalisation methods ENmix.oob and BMIQ). All pipelines examined also exhibited ICCs lower than –2, but these were removed from the illustration for visualisation purposes. The default settings of each analysis pipeline are detailed in Additional file 1: Table S1

Fig. 2

(A–C) Scatter plots of the first three principal components (PC1–3) from PCA of DNAm data from samples with repeated measurements (n = 17 samples) using the 450 k and EPIC platforms, and (D) a scree plot showing the amount of variance explained by the first nine PCs

Fig. 3

Mean absolute difference in measured DNA methylation (Δβ) per CpG, on the 450 k and EPIC platforms. Red dotted lines indicate a mean Δβ > 0.1, > 0.25 and > 0.5. Illumina CpG IDs are named if the mean Δβ > 0.5

Fig. 4

Pearson’s correlation coefficients of DNAm in replicates of the 450 k and EPIC platforms, for (A) per-sample correlations in a correlogram, and (B) per-CpG correlations as distributions stratified by variance quartiles, based on the variance of the respective CpGs on the EPIC platform

Fig. 5

(A) Histogram of the ICCs computed from the 17 samples assessed on both the 450 k and EPIC platforms. (B) Density distribution of mean difference in DNAm level, stratified by ICC category. (C) Density distribution of Pearson’s correlation coefficient, stratified by ICC category. The ICC categories are defined as follows: poor: ICC < 0.5; moderate: 0.5 ≤ ICC < 0.75; good: 0.75 ≤ ICC < 0.9; and excellent: ICC ≥ 0.9. The dark grey, dotted line indicates the median ICC, and the light grey, dotted line indicates the mean ICC. Outlying CpGs with ICCs less than the mean ICC minus three standard deviations were removed for visualisation purposes, but were included for summary statistic calculations