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Interrelationships and determinants of aging biomarkers in cord blood

BACKGROUND: Increasing evidence supports the concept of prenatal programming as an early factor in the aging process. DNA methylation age (DNAm age), global genome-wide DNA methylation (global methylation), telomere length (TL), and mitochondrial DNA content (mtDNA content) have independently been s...

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Autores principales: Reimann, Brigitte, Martens, Dries S., Wang, Congrong, Ghantous, Akram, Herceg, Zdenko, Plusquin, Michelle, Nawrot, Tim S.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9361565/
https://www.ncbi.nlm.nih.gov/pubmed/35945616
http://dx.doi.org/10.1186/s12967-022-03541-1
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author Reimann, Brigitte
Martens, Dries S.
Wang, Congrong
Ghantous, Akram
Herceg, Zdenko
Plusquin, Michelle
Nawrot, Tim S.
author_facet Reimann, Brigitte
Martens, Dries S.
Wang, Congrong
Ghantous, Akram
Herceg, Zdenko
Plusquin, Michelle
Nawrot, Tim S.
author_sort Reimann, Brigitte
collection PubMed
description BACKGROUND: Increasing evidence supports the concept of prenatal programming as an early factor in the aging process. DNA methylation age (DNAm age), global genome-wide DNA methylation (global methylation), telomere length (TL), and mitochondrial DNA content (mtDNA content) have independently been shown to be markers of aging, but their interrelationship and determinants at birth remain uncertain. METHODS: We assessed the inter-correlation between the aging biomarkers DNAm age, global methylation, TL and mtDNA content using Pearson's correlation in 190 cord blood samples of the ENVIRONAGE birth cohort. TL and mtDNA content was measured via qPCR, while the DNA methylome was determined using the human 450K methylation Illumina microarray. Subsequently, DNAm age was calculated according to Horvath's epigenetic clock, and mean global, promoter, gene-body, and intergenic DNA methylation were determined. Path analysis, a form of structural equation modeling, was performed to disentangle the complex causal relationships among the aging biomarkers and their potential determinants. RESULTS: DNAm age was inversely correlated with global methylation (r = -0.64, p < 0.001) and mtDNA content (r = − 0.16, p = 0.027). Cord blood TL was correlated with mtDNA content (r = 0.26, p < 0.001) but not with global methylation or DNAm age. Path analysis showed the strongest effect for global methylation on DNAm age with a decrease of 0.64 standard deviations (SD) in DNAm age for each SD (0.01%) increase in global methylation (p < 0.001). Among the applied covariates, newborn sex and season of delivery were the strongest determinants of aging biomarkers. CONCLUSIONS: We provide insight into molecular aging signatures at the start of life, including their interrelations and determinants, showing that cord blood DNAm age is inversely associated with global methylation and mtDNA content but not with newborn telomere length. Our findings demonstrate that cord blood TL and DNAm age relate to different pathways/mechanisms of biological aging and can be influenced by environmental factors already at the start of life. These findings are relevant for understanding fetal programming and for the early prevention of noncommunicable diseases. GRAPHICAL ABSTRACT: [Image: see text] SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12967-022-03541-1.
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spelling pubmed-93615652022-08-10 Interrelationships and determinants of aging biomarkers in cord blood Reimann, Brigitte Martens, Dries S. Wang, Congrong Ghantous, Akram Herceg, Zdenko Plusquin, Michelle Nawrot, Tim S. J Transl Med Research BACKGROUND: Increasing evidence supports the concept of prenatal programming as an early factor in the aging process. DNA methylation age (DNAm age), global genome-wide DNA methylation (global methylation), telomere length (TL), and mitochondrial DNA content (mtDNA content) have independently been shown to be markers of aging, but their interrelationship and determinants at birth remain uncertain. METHODS: We assessed the inter-correlation between the aging biomarkers DNAm age, global methylation, TL and mtDNA content using Pearson's correlation in 190 cord blood samples of the ENVIRONAGE birth cohort. TL and mtDNA content was measured via qPCR, while the DNA methylome was determined using the human 450K methylation Illumina microarray. Subsequently, DNAm age was calculated according to Horvath's epigenetic clock, and mean global, promoter, gene-body, and intergenic DNA methylation were determined. Path analysis, a form of structural equation modeling, was performed to disentangle the complex causal relationships among the aging biomarkers and their potential determinants. RESULTS: DNAm age was inversely correlated with global methylation (r = -0.64, p < 0.001) and mtDNA content (r = − 0.16, p = 0.027). Cord blood TL was correlated with mtDNA content (r = 0.26, p < 0.001) but not with global methylation or DNAm age. Path analysis showed the strongest effect for global methylation on DNAm age with a decrease of 0.64 standard deviations (SD) in DNAm age for each SD (0.01%) increase in global methylation (p < 0.001). Among the applied covariates, newborn sex and season of delivery were the strongest determinants of aging biomarkers. CONCLUSIONS: We provide insight into molecular aging signatures at the start of life, including their interrelations and determinants, showing that cord blood DNAm age is inversely associated with global methylation and mtDNA content but not with newborn telomere length. Our findings demonstrate that cord blood TL and DNAm age relate to different pathways/mechanisms of biological aging and can be influenced by environmental factors already at the start of life. These findings are relevant for understanding fetal programming and for the early prevention of noncommunicable diseases. GRAPHICAL ABSTRACT: [Image: see text] SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12967-022-03541-1. BioMed Central 2022-08-09 /pmc/articles/PMC9361565/ /pubmed/35945616 http://dx.doi.org/10.1186/s12967-022-03541-1 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Reimann, Brigitte
Martens, Dries S.
Wang, Congrong
Ghantous, Akram
Herceg, Zdenko
Plusquin, Michelle
Nawrot, Tim S.
Interrelationships and determinants of aging biomarkers in cord blood
title Interrelationships and determinants of aging biomarkers in cord blood
title_full Interrelationships and determinants of aging biomarkers in cord blood
title_fullStr Interrelationships and determinants of aging biomarkers in cord blood
title_full_unstemmed Interrelationships and determinants of aging biomarkers in cord blood
title_short Interrelationships and determinants of aging biomarkers in cord blood
title_sort interrelationships and determinants of aging biomarkers in cord blood
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9361565/
https://www.ncbi.nlm.nih.gov/pubmed/35945616
http://dx.doi.org/10.1186/s12967-022-03541-1
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