<p>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 were similarly reproducible with mean absolute replicate difference (MRD) values ranging from 1.014&#xa0;years to 1.194&#xa0;years, pcHorvath1 was more reproducible in arrays (MRD = 0.459&#xa0;years) than methylation sequencing (MRD = 2.320&#xa0;years)&#xa0;and pcHorvath2 was more reproducible in methylation sequencing (MRD = 0.760&#xa0;years) than arrays (MRD = 1.011&#xa0;years). Furthermore, original non-PC versions of these clocks were less reproducible in Twist datasets and, as an example of this, MRD for uncorrected clocks&#xa0;went as high as 15.498 years in arrays and as high as 20.180 years in methylation sequencing. Obvious differences in age prediction were also observed in original clocks compared to their PC-trained versions across both technologies (with a mean absolute difference ranging from 4.492&#xa0;years to 46.724&#xa0;years). This underscores the need for careful selection of epigenetic clocks and technology-specific adjustments when optimizing for accuracy and reproducibility.</p>

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

  • Maxim N. Shokhirev,
  • Adiv A. Johnson

摘要

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 were similarly reproducible with mean absolute replicate difference (MRD) values ranging from 1.014 years to 1.194 years, pcHorvath1 was more reproducible in arrays (MRD = 0.459 years) than methylation sequencing (MRD = 2.320 years) and pcHorvath2 was more reproducible in methylation sequencing (MRD = 0.760 years) than arrays (MRD = 1.011 years). Furthermore, original non-PC versions of these clocks were less reproducible in Twist datasets and, as an example of this, MRD for uncorrected clocks went as high as 15.498 years in arrays and as high as 20.180 years in methylation sequencing. Obvious differences in age prediction were also observed in original clocks compared to their PC-trained versions across both technologies (with a mean absolute difference ranging from 4.492 years to 46.724 years). This underscores the need for careful selection of epigenetic clocks and technology-specific adjustments when optimizing for accuracy and reproducibility.