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Yusipov I, Kalyakulina A, Trukhanov A, Franceschi C, Ivanchenko M. Map of epigenetic age acceleration: A worldwide analysis. Ageing Res Rev 2024; 100:102418. [PMID: 39002646 DOI: 10.1016/j.arr.2024.102418] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2024] [Revised: 07/03/2024] [Accepted: 07/08/2024] [Indexed: 07/15/2024]
Abstract
We present a systematic analysis of epigenetic age acceleration based on by far the largest collection of publicly available DNA methylation data for healthy samples (93 datasets, 23 K samples), focusing on the geographic (25 countries) and ethnic (31 ethnicities) aspects around the world. We employed the most popular epigenetic tools for assessing age acceleration and examined their quality metrics and ability to extrapolate to epigenetic data from different tissue types and age ranges different from the training data of these models. In most cases, the models proved to be inconsistent with each other and showed different signs of age acceleration, with the PhenoAge model tending to systematically underestimate and different versions of the GrimAge model tending to systematically overestimate the age prediction of healthy subjects. Referring to data availability and consistency, most countries and populations are still not represented in GEO, moreover, different datasets use different criteria for determining healthy controls. Because of this, it is difficult to fully isolate the contribution of "geography/environment", "ethnicity" and "healthiness" to epigenetic age acceleration. Among the explored metrics, only the DunedinPACE, which measures aging rate, appears to adequately reflect the standard of living and socioeconomic indicators in countries, although it has a limited application to blood methylation data only. Invariably, by epigenetic age acceleration, males age faster than females in most of the studied countries and populations.
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Affiliation(s)
- Igor Yusipov
- Artificial Intelligence Research Center, Institute of Information Technologies, Mathematics and Mechanics, Lobachevsky State University, Nizhny Novgorod 603022, Russia; Institute of Biogerontology, Lobachevsky State University, Nizhny Novgorod 603022, Russia.
| | - Alena Kalyakulina
- Artificial Intelligence Research Center, Institute of Information Technologies, Mathematics and Mechanics, Lobachevsky State University, Nizhny Novgorod 603022, Russia; Institute of Biogerontology, Lobachevsky State University, Nizhny Novgorod 603022, Russia.
| | - Arseniy Trukhanov
- Mriya Life Institute, National Academy of Active Longevity, Moscow 124489, Russia.
| | - Claudio Franceschi
- Institute of Biogerontology, Lobachevsky State University, Nizhny Novgorod 603022, Russia.
| | - Mikhail Ivanchenko
- Artificial Intelligence Research Center, Institute of Information Technologies, Mathematics and Mechanics, Lobachevsky State University, Nizhny Novgorod 603022, Russia; Institute of Biogerontology, Lobachevsky State University, Nizhny Novgorod 603022, Russia.
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Mertens J, Belva F, van Montfoort APA, Regin M, Zambelli F, Seneca S, Couvreu de Deckersberg E, Bonduelle M, Tournaye H, Stouffs K, Barbé K, Smeets HJM, Van de Velde H, Sermon K, Blockeel C, Spits C. Children born after assisted reproduction more commonly carry a mitochondrial genotype associating with low birthweight. Nat Commun 2024; 15:1232. [PMID: 38336715 PMCID: PMC10858059 DOI: 10.1038/s41467-024-45446-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2022] [Accepted: 01/23/2024] [Indexed: 02/12/2024] Open
Abstract
Children conceived through assisted reproductive technologies (ART) have an elevated risk of lower birthweight, yet the underlying cause remains unclear. Our study explores mitochondrial DNA (mtDNA) variants as contributors to birthweight differences by impacting mitochondrial function during prenatal development. We deep-sequenced the mtDNA of 451 ART and spontaneously conceived (SC) individuals, 157 mother-child pairs and 113 individual oocytes from either natural menstrual cycles or after ovarian stimulation (OS) and find that ART individuals carried a different mtDNA genotype than SC individuals, with more de novo non-synonymous variants. These variants, along with rRNA variants, correlate with lower birthweight percentiles, independent of conception mode. Their higher occurrence in ART individuals stems from de novo mutagenesis associated with maternal aging and OS-induced oocyte cohort size. Future research will establish the long-term health consequences of these changes and how these findings will impact the clinical practice and patient counselling in the future.
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Affiliation(s)
- Joke Mertens
- Research Group Reproduction and Genetics, Faculty of Medicine and Pharmacy, Vrije Universiteit Brussel, Brussels, Belgium
| | - Florence Belva
- Center for Medical Genetics, UZ Brussel, Brussels, Belgium
| | - Aafke P A van Montfoort
- Department of Obstetrics & Gynaecology, GROW School for Oncology and Developmental Biology, Maastricht University Medical Center, Maastricht, The Netherlands
| | - Marius Regin
- Research Group Reproduction and Genetics, Faculty of Medicine and Pharmacy, Vrije Universiteit Brussel, Brussels, Belgium
| | | | - Sara Seneca
- Research Group Reproduction and Genetics, Faculty of Medicine and Pharmacy, Vrije Universiteit Brussel, Brussels, Belgium
- Center for Medical Genetics, UZ Brussel, Brussels, Belgium
| | - Edouard Couvreu de Deckersberg
- Research Group Reproduction and Genetics, Faculty of Medicine and Pharmacy, Vrije Universiteit Brussel, Brussels, Belgium
| | | | - Herman Tournaye
- Brussels IVF, Center for Reproductive Medicine, UZ Brussel, Brussels, Belgium
- Research Group Biology of the Testis, Faculty of Medicine, Vrije Universiteit Brussel, Brussels, Belgium
| | - Katrien Stouffs
- Research Group Reproduction and Genetics, Faculty of Medicine and Pharmacy, Vrije Universiteit Brussel, Brussels, Belgium
- Center for Medical Genetics, UZ Brussel, Brussels, Belgium
| | - Kurt Barbé
- Interfaculty Center Data Processing & Statistics, Vrije Universiteit Brussel, Brussels, Belgium
| | - Hubert J M Smeets
- Department of Toxicogenomics, Maastricht University, Maastricht, The Netherlands
- MHeNs School Institute for Mental Health and Neuroscience, GROW Institute for Oncology and Developmental Biology, Maastricht University, Maastricht, The Netherlands
| | - Hilde Van de Velde
- Brussels IVF, Center for Reproductive Medicine, UZ Brussel, Brussels, Belgium
- Research Group Reproduction and Immunology, Faculty of Medicine and Pharmacy, Vrije Universiteit Brussel, Brussels, Belgium
| | - Karen Sermon
- Research Group Reproduction and Genetics, Faculty of Medicine and Pharmacy, Vrije Universiteit Brussel, Brussels, Belgium
| | - Christophe Blockeel
- Brussels IVF, Center for Reproductive Medicine, UZ Brussel, Brussels, Belgium
- Department of Obstetrics and Gynaecology, School of Medicine, University of Zagreb, Šalata 3, Zagreb, 10000, Croatia
| | - Claudia Spits
- Research Group Reproduction and Genetics, Faculty of Medicine and Pharmacy, Vrije Universiteit Brussel, Brussels, Belgium.
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