Analysis of variability and epigenetic age prediction across microarray and methylation sequencing technologies

Published: 21 July 2025| Version 1 | DOI: 10.17632/72h6tht2c8.1
Contributor:
Max Shokh

Description

The variability and accuracy of epigenetic aging clocks are dependent on the choice of clock and the underlying technology utilized for methylation measurement. Using 100 technical replicate samples from two adult buccal cohorts, we compared technical methylation variability and signal strength between the Infinium MethylationEPIC v2.0 array and the Twist Human Methylome Panel across 753,648 shared CpGs. Twist methylation sequencing showed skewed methylation distributions and fewer highly correlated CpGs than MethylationEPIC arrays. Variance analysis revealed a skew toward higher signal strength in MethylationEPIC datasets with a subset of CpGs showing high signal strength in both methylation sequencing and array datasets. Despite these biases, four principal component (PC) trained epigenetic clocks (pcHorvath1, pcHorvath2, pcHannum, and pcDNAm PhenoAge) were robust across both technologies, even with missing data. While pcHannum and pcDNAm PhenoAge had similar replicate errors across both technologies, pcHorvath1 was more reproducible on arrays while pcHorvath2 was more reproducible on methylation sequencing. Furthermore, original non-PC versions of these clocks were significantly less reproducible in Twist datasets and displayed obvious differences in age prediction compared to their PC-trained versions across both technologies. For example, mean replicate error for the original, non-PC DNAm PhenoAge clock jumped from 3.850 years in arrays to 6.156 years in methylation sequencing. This underscores the need for careful selection of epigenetic clocks and technology-specific adjustments when optimizing for accuracy and reproducibility. It further emphasizes the importance of correcting for technical noise which, if left unaddressed, is substantial. Files include metadata sheets, methylation beta tables, and methylation bedGraph files.

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Please see the accompanying paper for detailed methods and tools used.

Categories

DNA Sequencing, Methylation, Aging, Micro Array Analysis, Epigenetics

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