The Correlation Of Methylation Levels Measured Using Illumina 450K And EPIC Beadchips In Blood Samples

Logue, Mark W.; Smith, Alicia K.; Wolf, Erika J.; Maniates, Hannah; Stone, Annjanette; Schichman, Steven A.; McGlinchey, Regina E.; Milberg, William; Miller, Mark W.

doi:10.2217/epi-2017-0078

Cited by 111 publications

(150 citation statements)

References 26 publications

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“…Results for overall correlations in children corroborate studies in adult blood [4] and cancer tissue [1], which show overall correlation coefficients greater than 0.9. Also, similar to the study in adult blood, individual site correlations were much lower in the newborns and children in our study.…”

Section: Discussionsupporting

confidence: 82%

“…Kling et al also reported high overall correlations between EPIC and 450K in both fresh-frozen and formalin-fixed paraffin embedded tumors [3]. Similar results were reported for overall correlation in adult whole blood (n = 145); however, low correlation was observed for many individual sites (55% with r <0.2) and were found to correspond with the variance or range of methylation at a site [4]. Studies comparing the two platforms in samples collected from children have not yet been reported.…”

Section: Introductionmentioning

confidence: 53%

“…Even after quantile normalization, which aims to adjust for differences in Infinium chemistry at type I vs. type II probes, we see that type II probes have a higher distribution of strong correlations between the two platforms. Interestingly, a study in adult blood reported very similar results for the two probe types [4]. These differences underscore the importance of including a normalization technique for probe type in the methylation data processing pipeline.…”

Section: Discussionmentioning

confidence: 95%

“…Prior studies have examined reliability and reproducibility of overlapping EPIC and 450K probes in matched samples of cancer tissue [1,3] and adult whole blood [4]. Pidsley et al showed that correlation between 450K and EPIC for two of the same samples of both cancerous and non-cancerous cell lines across all overlapping sites was high (r >0.9) and that reproducibility for identifying differentially methylated positions (DMPs) between cancer and non-cancerous cells (n = 3 pairs) was excellent, using FDR P <0.01.…”

Section: Introductionmentioning

confidence: 99%

“…We will use data from the same DNA samples analyzed on both the EPIC and 450K chips to explore correlations, difference in performance by type I and II probes, comparability of estimates for cell-type proportions, and reproducibility of a DMP analysis between boys and girls. Overall correlations indicate the correlation between a sample analyzed by both platforms across all sites [4]. In contrast, individual site correlations refer to the correlation of a single site analyzed in all samples on both platforms.…”

Section: Introductionmentioning

confidence: 99%

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Comparison of DNA methylation measured by Illumina 450K and EPIC BeadChips in blood of newborns and 14-year-old children

et al. 2018

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Analysis of DNA methylation helps to understand the effects of environmental exposures as well as the role of epigenetics in human health. Illumina, Inc. recently replaced the HumanMethylation450 BeadChip (450K) with the EPIC BeadChip, which nearly doubles the measured CpG sites to >850,000. Although the new chip uses the same underlying technology, it is important to establish if data between the two platforms are comparable within cohorts and for meta-analyses. DNA methylation was assessed by 450K and EPIC using whole blood from newborn (n = 109) and 14-year-old (n = 86) participants of the Center for the Health Assessment of Mothers and Children of Salinas. The overall per-sample correlations were very high (r >0.99), although many individual CpG sites, especially those with low variance of methylation, had lower correlations (median r = 0.24). There was also a small subset of CpGs with large mean methylation β-value differences between platforms, in both the newborn and 14-year datasets. However, estimates of cell type proportion prediction by 450K and EPIC were highly correlated at both ages. Finally, differentially methylated positions between boys and girls replicated very well by both platforms in newborns and older children. These findings are encouraging for application of combined data from EPIC and 450K platforms for birth cohorts and other population studies. These data in children corroborate recent comparisons of the two BeadChips in adults and in cancer cell lines. However, researchers should be cautious when characterizing individual CpG sites and consider independent methods for validation of significant hits.

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Section: Discussionsupporting

confidence: 82%

Section: Introductionmentioning

confidence: 53%

Section: Discussionmentioning

confidence: 95%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Comparison of DNA methylation measured by Illumina 450K and EPIC BeadChips in blood of newborns and 14-year-old children

et al. 2018

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“Epigenetic clocks”: Theory and applications in human biology

Ryan

2020

American J Hum Biol

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All humans age, but how we age—and how fast—differs considerably from person to person. This deviation between apparent age and chronological age is often referred to as “biological age” (BA) and until recently robust tools for studying BA have been scarce. “Epigenetic clocks” are starting to change this. Epigenetic clocks use predictable changes in the epigenome, usually DNA methylation, to estimate chronological age with unprecedented accuracy. More importantly, deviations between epigenetic age and chronological age predict a broad range of health outcomes and mortality risks better than chronological age alone. Thus, epigenetic clocks appear to capture fundamental molecular processes tied to BA and can serve as powerful tools for studying health, development, and aging across the lifespan. In this article, I review epigenetic clocks, especially as they relate to key theoretical and applied issues in human biology. I first provide an overview of how epigenetic clocks are constructed and what we know about them. I then discuss emerging applications of particular relevance to human biologists—those related to reproduction, life‐history, stress, and the environment. I conclude with an overview of the methods necessary for implementing epigenetic clocks, including considerations of study design, sample collection, and technical considerations for processing and interpreting epigenetic clocks. The goal of this review is to highlight some of the ways that epigenetic clocks can inform questions in human biology, and vice versa, and to provide human biologists with the foundational knowledge necessary to successfully incorporate epigenetic clocks into their research.

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Identification of Cell‐Specific Differential DNA Methylation Associated With Methotrexate Treatment Response in Rheumatoid Arthritis

Adams

Nair

Plant

et al. 2023

Arthritis & Rheumatology

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Objective. We undertook this study to estimate changes in cell-specific DNA methylation (DNAm) associated with methotrexate (MTX) response using whole blood samples collected from rheumatoid arthritis (RA) patients before and after initiation of MTX treatment.Methods. Patients included in this study were from the Rheumatoid Arthritis Medication Study (n = 66) and the University of California San Francisco Rheumatoid Arthritis study (n = 11). All patients met the American College of Rheumatology RA classification criteria. Blood samples were collected at baseline and following treatment. Disease Activity Scores in 28 joints using the C-reactive protein level were collected at baseline and after 3-6 months of treatment with MTX. Methylation profiles were generated using the Illumina Infinium HumanMethylation450 and MethylationEPIC v1.0 BeadChip arrays using DNA from whole blood. MTX response was defined using the EULAR response criteria (responders showed good/moderate response; nonresponders showed no response). Differentially methylated positions were identified using the Limma software package and Tensor Composition Analysis, which is a method for identifying cell-specific differential DNAm at the CpG level from tissue-level ("bulk") data. Differentially methylated regions were identified using Comb-p software.Results. We found evidence of differential global methylation between treatment response groups. Further, we found patterns of cell-specific differential global methylation associated with MTX response. After correction for multiple testing, 1 differentially methylated position was associated with differential DNAm between responders and nonresponders at baseline in CD4+ T cells, CD8+ T cells, and natural killer cells. Thirty-nine cell-specific differentially methylated regions associated with MTX treatment response were identified. There were no significant findings in analyses of whole blood samples.Conclusion. We identified cell-specific changes in DNAm that were associated with MTX treatment response in RA patients. Future studies of DNAm and MTX treatment response should include measurements of DNAm from sorted cells. INTRODUCTIONRheumatoid arthritis (RA) is the most common systemic autoimmune disease and affects up to 1% of the global population (1). Methotrexate (MTX) is a disease-modifying antirheumatic drug (DMARD) that is the most frequent first-line DMARD for the treatment of RA (2). Approximately 30-40% of patients continue with MTX treatment after 2 years (3,4). ReasonsThe views expressed herein are those of the authors and not necessarily those of the NHS, the NIHR, or the Department of Health.

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The Correlation Of Methylation Levels Measured Using Illumina 450K And EPIC Beadchips In Blood Samples

Cited by 111 publications

References 26 publications

Comparison of DNA methylation measured by Illumina 450K and EPIC BeadChips in blood of newborns and 14-year-old children

Comparison of DNA methylation measured by Illumina 450K and EPIC BeadChips in blood of newborns and 14-year-old children

“Epigenetic clocks”: Theory and applications in human biology

Identification of Cell‐Specific Differential DNA Methylation Associated With Methotrexate Treatment Response in Rheumatoid Arthritis

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