Agreement in DNA methylation levels from the Illumina 450K array across batches, tissues, and time

ABSTRACT

Epigenome-wide association studies (EWAS) have focused primarily on DNA methylation as a chemically stable and functional epigenetic modification. However, the stability and accuracy of the measurement of methylation in different tissues and extraction types is still being actively studied, and the longitudinal stability of DNA methylation in commonly studied peripheral tissues is of great interest. Here, we used data from two studies, three tissue types, and multiple time points to assess the stability of DNA methylation measured with the Illumina Infinium HumanMethylation450 BeadChip array. Redundancy analysis enabled visual assessment of agreement of replicate samples overall and showed good agreement after removing effects of tissue type, age, and sex. At the probe level, analysis of variance contrasts separating technical and biological replicates clearly showed better agreement between technical replicates versus longitudinal samples, and suggested increased stability for buccal cells versus blood or blood spots. Intraclass correlations (ICCs) demonstrated that inter-individual variability is of similar magnitude to within-sample variability at many probes; however, as inter-individual variability increased, so did ICC. Furthermore, we were able to demonstrate decreasing agreement in methylation levels with time, despite a maximal sampling interval of only 576 days. Finally, at 6 popular candidate genes, there was a large range of stability across probes. Our findings highlight important sources of technical and biological variation in DNA methylation across different tissues over time. These data will help to inform longitudinal sampling strategies of future EWAS.

KEYWORDS:

• Intraclass correlations
• methylation
• redundancy analysis
• replication
• tissue stability

Data availability statement

The raw methylation measures are not available due to patient confidentiality. However, we provide the F-statistics and the ICC measures for different subgroupings, and for both datasets at https://doi.org/10.5281/zenodo.996561.

Acknowledgements

This work was funded by the Ludmer Centre for Neuroinformatics and Mental Health. Sadly, G.V.'s substantial contributions are acknowledged posthumously. MSK is the Canada Research Chair in Social Epigenetics, Senior Fellow of the Canadian Institute for Advanced Research, and Sunny Hill BC Leadership Chair in Child Development. LM McEwen is supported by a CIHR Frederick Banting and Charles Best Doctoral Research Award (F15-04283).

Author contributions

Conceptualization, C.G., K. O.; Methodology, C.G., K.O.; Data Curation, M.M., K.O., H.G. and P.S.; Validation, M.F. and G.V.; Formal Analysis, C.G., G.V. and M.F.; Resources, K.O., H.G., J.L.M., L.M.M, M.M. and C.G.; Writing-Original Draft, C.G. and G.V.; Writing-Review & Editing, C.G., K.O. and M.F.; Visualization, G.V. and M.F.; Supervision, C.G.; Project Administration, C.G.; Funding Acquisition, C.G. and M.M.

Disclosure of potential conflicts of interest

No potential conflicts of interest were disclosed.

Additional information

Funding

This work was supported by the Ludmer Centre for Neuroinformatics and Mental Health; CIHR Frederick Banting and Charles Best Doctoral Research Award [grant number F15-04283].