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Effects of iron homeostasis on epigenetic age acceleration: a two-sample Mendelian randomization study

BACKGROUND: Epigenetic clocks constructed from DNA methylation patterns have emerged as excellent predictors of aging and aging-related health outcomes. Iron, a crucial element, is meticulously regulated within organisms, a phenomenon referred as iron homeostasis. Previous researches have demonstrat...

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Autores principales: Wang, Zhihao, Liu, Yi, Zhang, Shuxin, Yuan, Yunbo, Chen, Siliang, Li, Wenhao, Zuo, Mingrong, Xiang, Yufan, Li, Tengfei, Yang, Wanchun, Yang, Yuan, Liu, Yanhui
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10559596/
https://www.ncbi.nlm.nih.gov/pubmed/37805541
http://dx.doi.org/10.1186/s13148-023-01575-w
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author Wang, Zhihao
Liu, Yi
Zhang, Shuxin
Yuan, Yunbo
Chen, Siliang
Li, Wenhao
Zuo, Mingrong
Xiang, Yufan
Li, Tengfei
Yang, Wanchun
Yang, Yuan
Liu, Yanhui
author_facet Wang, Zhihao
Liu, Yi
Zhang, Shuxin
Yuan, Yunbo
Chen, Siliang
Li, Wenhao
Zuo, Mingrong
Xiang, Yufan
Li, Tengfei
Yang, Wanchun
Yang, Yuan
Liu, Yanhui
author_sort Wang, Zhihao
collection PubMed
description BACKGROUND: Epigenetic clocks constructed from DNA methylation patterns have emerged as excellent predictors of aging and aging-related health outcomes. Iron, a crucial element, is meticulously regulated within organisms, a phenomenon referred as iron homeostasis. Previous researches have demonstrated the sophisticated connection between aging and iron homeostasis. However, their causal relationship remains relatively unexplored. RESULTS: Through two-sample Mendelian randomization (MR) utilizing the random effect inverse variance weighted (IVW) method, each standard deviation (SD) increase in serum iron was associated with increased GrimAge acceleration (GrimAA, Beta(IVW) = 0.27, P = 8.54E−03 in 2014 datasets; Beta(IVW) = 0.31, P = 1.25E−02 in 2021 datasets), HannumAge acceleration (HannumAA, Beta(IVW) = 0.32, P = 4.50E−03 in 2014 datasets; Beta(IVW) = 0.32, P = 8.03E−03 in 2021 datasets) and Intrinsic epigenetic age acceleration (IEAA, Beta(IVW) = 0.34, P = 5.33E−04 in 2014 datasets; Beta(IVW) = 0.49, P = 9.94E−04 in 2021 datasets). Similar results were also observed in transferrin saturation. While transferrin manifested a negative association with epigenetic age accelerations (EAAs) sensitivity analyses. Besides, lack of solid evidence to support a causal relationship from EAAs to iron-related biomarkers. CONCLUSIONS: The results of present investigation unveiled the causality of iron overload on acceleration of epigenetic clocks. Researches are warranted to illuminate the underlying mechanisms and formulate strategies for potential interventions. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13148-023-01575-w.
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spelling pubmed-105595962023-10-08 Effects of iron homeostasis on epigenetic age acceleration: a two-sample Mendelian randomization study Wang, Zhihao Liu, Yi Zhang, Shuxin Yuan, Yunbo Chen, Siliang Li, Wenhao Zuo, Mingrong Xiang, Yufan Li, Tengfei Yang, Wanchun Yang, Yuan Liu, Yanhui Clin Epigenetics Research BACKGROUND: Epigenetic clocks constructed from DNA methylation patterns have emerged as excellent predictors of aging and aging-related health outcomes. Iron, a crucial element, is meticulously regulated within organisms, a phenomenon referred as iron homeostasis. Previous researches have demonstrated the sophisticated connection between aging and iron homeostasis. However, their causal relationship remains relatively unexplored. RESULTS: Through two-sample Mendelian randomization (MR) utilizing the random effect inverse variance weighted (IVW) method, each standard deviation (SD) increase in serum iron was associated with increased GrimAge acceleration (GrimAA, Beta(IVW) = 0.27, P = 8.54E−03 in 2014 datasets; Beta(IVW) = 0.31, P = 1.25E−02 in 2021 datasets), HannumAge acceleration (HannumAA, Beta(IVW) = 0.32, P = 4.50E−03 in 2014 datasets; Beta(IVW) = 0.32, P = 8.03E−03 in 2021 datasets) and Intrinsic epigenetic age acceleration (IEAA, Beta(IVW) = 0.34, P = 5.33E−04 in 2014 datasets; Beta(IVW) = 0.49, P = 9.94E−04 in 2021 datasets). Similar results were also observed in transferrin saturation. While transferrin manifested a negative association with epigenetic age accelerations (EAAs) sensitivity analyses. Besides, lack of solid evidence to support a causal relationship from EAAs to iron-related biomarkers. CONCLUSIONS: The results of present investigation unveiled the causality of iron overload on acceleration of epigenetic clocks. Researches are warranted to illuminate the underlying mechanisms and formulate strategies for potential interventions. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13148-023-01575-w. BioMed Central 2023-10-07 /pmc/articles/PMC10559596/ /pubmed/37805541 http://dx.doi.org/10.1186/s13148-023-01575-w Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This 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
Wang, Zhihao
Liu, Yi
Zhang, Shuxin
Yuan, Yunbo
Chen, Siliang
Li, Wenhao
Zuo, Mingrong
Xiang, Yufan
Li, Tengfei
Yang, Wanchun
Yang, Yuan
Liu, Yanhui
Effects of iron homeostasis on epigenetic age acceleration: a two-sample Mendelian randomization study
title Effects of iron homeostasis on epigenetic age acceleration: a two-sample Mendelian randomization study
title_full Effects of iron homeostasis on epigenetic age acceleration: a two-sample Mendelian randomization study
title_fullStr Effects of iron homeostasis on epigenetic age acceleration: a two-sample Mendelian randomization study
title_full_unstemmed Effects of iron homeostasis on epigenetic age acceleration: a two-sample Mendelian randomization study
title_short Effects of iron homeostasis on epigenetic age acceleration: a two-sample Mendelian randomization study
title_sort effects of iron homeostasis on epigenetic age acceleration: a two-sample mendelian randomization study
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10559596/
https://www.ncbi.nlm.nih.gov/pubmed/37805541
http://dx.doi.org/10.1186/s13148-023-01575-w
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