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Systematic evaluation of DNA methylation age estimation with common preprocessing methods and the Infinium MethylationEPIC BeadChip array

BACKGROUND: The capacity of technologies measuring DNA methylation (DNAm) is rapidly evolving, as are the options for applicable bioinformatics methods. The most commonly used DNAm microarray, the Illumina Infinium HumanMethylation450 (450K array), has recently been replaced by the Illumina Infinium...

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Autores principales: McEwen, Lisa M, Jones, Meaghan J, Lin, David Tse Shen, Edgar, Rachel D, Husquin, Lucas T, MacIsaac, Julia L, Ramadori, Katia E, Morin, Alexander M, Rider, Christopher F, Carlsten, Chris, Quintana-Murci, Lluís, Horvath, Steve, Kobor, Michael S
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6192219/
https://www.ncbi.nlm.nih.gov/pubmed/30326963
http://dx.doi.org/10.1186/s13148-018-0556-2
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author McEwen, Lisa M
Jones, Meaghan J
Lin, David Tse Shen
Edgar, Rachel D
Husquin, Lucas T
MacIsaac, Julia L
Ramadori, Katia E
Morin, Alexander M
Rider, Christopher F
Carlsten, Chris
Quintana-Murci, Lluís
Horvath, Steve
Kobor, Michael S
author_facet McEwen, Lisa M
Jones, Meaghan J
Lin, David Tse Shen
Edgar, Rachel D
Husquin, Lucas T
MacIsaac, Julia L
Ramadori, Katia E
Morin, Alexander M
Rider, Christopher F
Carlsten, Chris
Quintana-Murci, Lluís
Horvath, Steve
Kobor, Michael S
author_sort McEwen, Lisa M
collection PubMed
description BACKGROUND: The capacity of technologies measuring DNA methylation (DNAm) is rapidly evolving, as are the options for applicable bioinformatics methods. The most commonly used DNAm microarray, the Illumina Infinium HumanMethylation450 (450K array), has recently been replaced by the Illumina Infinium HumanMethylationEPIC (EPIC array), nearly doubling the number of targeted CpG sites. Given that a subset of 450K CpG sites is absent on the EPIC array and that several tools for both data normalization and analyses were developed on the 450K array, it is important to assess their utility when applied to EPIC array data. One of the most commonly used 450K tools is the pan-tissue epigenetic clock, a multivariate predictor of biological age based on DNAm at 353 CpG sites. Of these CpGs, 19 are missing from the EPIC array, thus raising the question of whether EPIC data can be used to accurately estimate DNAm age. We also investigated a 71-CpG epigenetic age predictor, referred to as the Hannum method, which lacks 6 probes on the EPIC array. To evaluate these epigenetic clocks in EPIC data properly, a prior assessment of the effects of data preprocessing methods on DNAm age is also required. METHODS: DNAm was quantified, on both the 450K and EPIC platforms, from human primary monocytes derived from 172 individuals. We calculated DNAm age from raw, and three different preprocessed data forms to assess the effects of different processing methods on the DNAm age estimate. Using an additional cohort, we also investigated DNAm age of peripheral blood mononuclear cells, bronchoalveolar lavage, and bronchial brushing samples using the EPIC array. RESULTS: Using monocyte-derived data from subjects on both the 450K and EPIC, we found that DNAm age was highly correlated across both raw and preprocessing methods (r > 0.91). Thus, the correlation between chronological age and the DNAm age estimate is largely unaffected by platform differences and normalization methods. However, we found that the choice of normalization method and measurement platform can lead to a systematic offset in the age estimate which in turn leads to an increase in the median error. Comparing the 450K and EPIC DNAm age estimates, we observed that the median absolute difference was 1.44–3.10 years across preprocessing methods. CONCLUSIONS: Here, we have provided evidence that the epigenetic clock is resistant to the lack of 19 CpG sites missing from the EPIC array as well as highlighted the importance of considering the technical variance of the epigenetic when interpreting group differences below the reported error. Furthermore, our study highlights the utility of epigenetic age acceleration measure, the residuals from a linear regression of DNAm age on chronological age, as the resulting values are robust with respect to normalization methods and measurement platforms. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s13148-018-0556-2) contains supplementary material, which is available to authorized users.
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spelling pubmed-61922192018-10-22 Systematic evaluation of DNA methylation age estimation with common preprocessing methods and the Infinium MethylationEPIC BeadChip array McEwen, Lisa M Jones, Meaghan J Lin, David Tse Shen Edgar, Rachel D Husquin, Lucas T MacIsaac, Julia L Ramadori, Katia E Morin, Alexander M Rider, Christopher F Carlsten, Chris Quintana-Murci, Lluís Horvath, Steve Kobor, Michael S Clin Epigenetics Short Report BACKGROUND: The capacity of technologies measuring DNA methylation (DNAm) is rapidly evolving, as are the options for applicable bioinformatics methods. The most commonly used DNAm microarray, the Illumina Infinium HumanMethylation450 (450K array), has recently been replaced by the Illumina Infinium HumanMethylationEPIC (EPIC array), nearly doubling the number of targeted CpG sites. Given that a subset of 450K CpG sites is absent on the EPIC array and that several tools for both data normalization and analyses were developed on the 450K array, it is important to assess their utility when applied to EPIC array data. One of the most commonly used 450K tools is the pan-tissue epigenetic clock, a multivariate predictor of biological age based on DNAm at 353 CpG sites. Of these CpGs, 19 are missing from the EPIC array, thus raising the question of whether EPIC data can be used to accurately estimate DNAm age. We also investigated a 71-CpG epigenetic age predictor, referred to as the Hannum method, which lacks 6 probes on the EPIC array. To evaluate these epigenetic clocks in EPIC data properly, a prior assessment of the effects of data preprocessing methods on DNAm age is also required. METHODS: DNAm was quantified, on both the 450K and EPIC platforms, from human primary monocytes derived from 172 individuals. We calculated DNAm age from raw, and three different preprocessed data forms to assess the effects of different processing methods on the DNAm age estimate. Using an additional cohort, we also investigated DNAm age of peripheral blood mononuclear cells, bronchoalveolar lavage, and bronchial brushing samples using the EPIC array. RESULTS: Using monocyte-derived data from subjects on both the 450K and EPIC, we found that DNAm age was highly correlated across both raw and preprocessing methods (r > 0.91). Thus, the correlation between chronological age and the DNAm age estimate is largely unaffected by platform differences and normalization methods. However, we found that the choice of normalization method and measurement platform can lead to a systematic offset in the age estimate which in turn leads to an increase in the median error. Comparing the 450K and EPIC DNAm age estimates, we observed that the median absolute difference was 1.44–3.10 years across preprocessing methods. CONCLUSIONS: Here, we have provided evidence that the epigenetic clock is resistant to the lack of 19 CpG sites missing from the EPIC array as well as highlighted the importance of considering the technical variance of the epigenetic when interpreting group differences below the reported error. Furthermore, our study highlights the utility of epigenetic age acceleration measure, the residuals from a linear regression of DNAm age on chronological age, as the resulting values are robust with respect to normalization methods and measurement platforms. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s13148-018-0556-2) contains supplementary material, which is available to authorized users. BioMed Central 2018-10-16 /pmc/articles/PMC6192219/ /pubmed/30326963 http://dx.doi.org/10.1186/s13148-018-0556-2 Text en © The Author(s). 2018 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Short Report
McEwen, Lisa M
Jones, Meaghan J
Lin, David Tse Shen
Edgar, Rachel D
Husquin, Lucas T
MacIsaac, Julia L
Ramadori, Katia E
Morin, Alexander M
Rider, Christopher F
Carlsten, Chris
Quintana-Murci, Lluís
Horvath, Steve
Kobor, Michael S
Systematic evaluation of DNA methylation age estimation with common preprocessing methods and the Infinium MethylationEPIC BeadChip array
title Systematic evaluation of DNA methylation age estimation with common preprocessing methods and the Infinium MethylationEPIC BeadChip array
title_full Systematic evaluation of DNA methylation age estimation with common preprocessing methods and the Infinium MethylationEPIC BeadChip array
title_fullStr Systematic evaluation of DNA methylation age estimation with common preprocessing methods and the Infinium MethylationEPIC BeadChip array
title_full_unstemmed Systematic evaluation of DNA methylation age estimation with common preprocessing methods and the Infinium MethylationEPIC BeadChip array
title_short Systematic evaluation of DNA methylation age estimation with common preprocessing methods and the Infinium MethylationEPIC BeadChip array
title_sort systematic evaluation of dna methylation age estimation with common preprocessing methods and the infinium methylationepic beadchip array
topic Short Report
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6192219/
https://www.ncbi.nlm.nih.gov/pubmed/30326963
http://dx.doi.org/10.1186/s13148-018-0556-2
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