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Lagunas-Rangel FA. Aging insights from heterochronic parabiosis models. NPJ AGING 2024; 10:38. [PMID: 39154047 PMCID: PMC11330497 DOI: 10.1038/s41514-024-00166-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/07/2024] [Accepted: 08/07/2024] [Indexed: 08/19/2024]
Abstract
Heterochronic parabiosis consists of surgically connecting the circulatory systems of a young and an old animal. This technique serves as a model to study circulating factors that accelerate aging in young organisms exposed to old blood or induce rejuvenation in old organisms exposed to young blood. Despite the promising results, the exact cellular and molecular mechanisms remain unclear, so this study aims to explore and elucidate them in more detail.
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Yu D, Luo L, Wang H, Shyh-Chang N. Pregnancy-induced metabolic reprogramming and regenerative responses to pro-aging stresses. Trends Endocrinol Metab 2024:S1043-2760(24)00192-9. [PMID: 39122601 DOI: 10.1016/j.tem.2024.07.011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/30/2024] [Revised: 07/12/2024] [Accepted: 07/17/2024] [Indexed: 08/12/2024]
Abstract
Pregnancy is associated with physiological adaptations that affect virtually all organs, enabling the mother to support the growing fetus and placenta while withstanding the demands of pregnancy. As a result, mammalian pregnancy is a unique state that exerts paradoxical effects on maternal health. On one hand, the metabolic stress induced by pregnancy can accelerate aging and functional decline in organs. On the other hand, pregnancy activates metabolic programming and tissue regenerative responses that can reverse age-related impairments. In this sense, the oocyte-to-blastocyst transition is not the only physiological reprogramming event in the mammalian body, as pregnancy-induced regeneration could constitute a second physiological reprogramming event. Here, we review findings on how pregnancy dualistically leads to aging and rejuvenation in the maternal body.
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Affiliation(s)
- Dainan Yu
- Key Laboratory of Organ Regeneration and Reconstruction, State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing 100101, China; Beijing Institute for Stem Cell and Regenerative Medicine, Beijing 100101, China
| | - Lanfang Luo
- Key Laboratory of Organ Regeneration and Reconstruction, State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing 100101, China; Beijing Institute for Stem Cell and Regenerative Medicine, Beijing 100101, China; School of Biological Engineering, Zhuhai Campus of Zunyi Medical University, Guangdong 519000, China
| | - Hongmei Wang
- Key Laboratory of Organ Regeneration and Reconstruction, State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing 100101, China; Beijing Institute for Stem Cell and Regenerative Medicine, Beijing 100101, China; University of Chinese Academy of Sciences, Beijing 100049, China.
| | - Ng Shyh-Chang
- Key Laboratory of Organ Regeneration and Reconstruction, State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing 100101, China; Beijing Institute for Stem Cell and Regenerative Medicine, Beijing 100101, China; University of Chinese Academy of Sciences, Beijing 100049, China.
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Marttila S, Rajić S, Ciantar J, Mak JKL, Junttila IS, Kummola L, Hägg S, Raitoharju E, Kananen L. Biological aging of different blood cell types. GeroScience 2024:10.1007/s11357-024-01287-w. [PMID: 39060678 DOI: 10.1007/s11357-024-01287-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2024] [Accepted: 07/10/2024] [Indexed: 07/28/2024] Open
Abstract
Biological age (BA) captures detrimental age-related changes. The best-known and most-used BA indicators include DNA methylation-based epigenetic clocks and telomere length (TL). The most common biological sample material for epidemiological aging studies, whole blood, is composed of different cell types. We aimed to compare differences in BAs between blood cell types and assessed the BA indicators' cell type-specific associations with chronological age (CA). An analysis of DNA methylation-based BA indicators, including TL, methylation level at cg16867657 in ELOVL2, as well as the Hannum, Horvath, DNAmPhenoAge, and DunedinPACE epigenetic clocks, was performed on 428 biological samples of 12 blood cell types. BA values were different in the majority of the pairwise comparisons between cell types, as well as in comparison to whole blood (p < 0.05). DNAmPhenoAge showed the largest cell type differences, up to 44.5 years and DNA methylation-based TL showed the lowest differences. T cells generally had the "youngest" BA values, with differences across subsets, whereas monocytes had the "oldest" values. All BA indicators, except DunedinPACE, strongly correlated with CA within a cell type. Some differences such as DNAmPhenoAge-difference between naïve CD4 + T cells and monocytes were constant regardless of the blood donor's CA (range 20-80 years), while for DunedinPACE they were not. In conclusion, DNA methylation-based indicators of BA exhibit cell type-specific characteristics. Our results have implications for understanding the molecular mechanisms underlying epigenetic clocks and underscore the importance of considering cell composition when utilizing them as indicators for the success of aging interventions.
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Affiliation(s)
- Saara Marttila
- Molecular Epidemiology (MOLE), Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland.
- Gerontology Research Center, Tampere University, Tampere, Finland.
- Tays Research Services, Wellbeing Services County of Pirkanmaa, Tampere University Hospital, Tampere, Finland.
| | - Sonja Rajić
- Molecular Epidemiology (MOLE), Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - Joanna Ciantar
- Molecular Epidemiology (MOLE), Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - Jonathan K L Mak
- Department of Medical Epidemiology and Biostatistics, Karolinska Institute, Stockholm, Sweden
- Department of Pharmacology and Pharmacy, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, China
| | - Ilkka S Junttila
- Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
- Fimlab Laboratories, Tampere, Finland
- Northern Finland Laboratory Centre (NordLab), Oulu, Finland
- Research Unit of Biomedicine, University of Oulu, Oulu, Finland
| | - Laura Kummola
- Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - Sara Hägg
- Department of Medical Epidemiology and Biostatistics, Karolinska Institute, Stockholm, Sweden
| | - Emma Raitoharju
- Molecular Epidemiology (MOLE), Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
- Tays Research Services, Wellbeing Services County of Pirkanmaa, Tampere University Hospital, Tampere, Finland
| | - Laura Kananen
- Gerontology Research Center, Tampere University, Tampere, Finland.
- Department of Medical Epidemiology and Biostatistics, Karolinska Institute, Stockholm, Sweden.
- Faculty of Social Sciences (Health Sciences), Tampere University, Tampere, Finland.
- Department of Neurobiology, Care Sciences and Society (NVS), Karolinska Institute, Stockholm, Sweden.
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Moix S, Sadler MC, Kutalik Z, Auwerx C. Breaking down causes, consequences, and mediating effects of telomere length variation on human health. Genome Biol 2024; 25:125. [PMID: 38760657 PMCID: PMC11101352 DOI: 10.1186/s13059-024-03269-9] [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: 11/01/2023] [Accepted: 05/07/2024] [Indexed: 05/19/2024] Open
Abstract
BACKGROUND Telomeres form repeated DNA sequences at the ends of chromosomes, which shorten with each cell division. Yet, factors modulating telomere attrition and the health consequences thereof are not fully understood. To address this, we leveraged data from 326,363 unrelated UK Biobank participants of European ancestry. RESULTS Using linear regression and bidirectional univariable and multivariable Mendelian randomization (MR), we elucidate the relationships between leukocyte telomere length (LTL) and 142 complex traits, including diseases, biomarkers, and lifestyle factors. We confirm that telomeres shorten with age and show a stronger decline in males than in females, with these factors contributing to the majority of the 5.4% of LTL variance explained by the phenome. MR reveals 23 traits modulating LTL. Smoking cessation and high educational attainment associate with longer LTL, while weekly alcohol intake, body mass index, urate levels, and female reproductive events, such as childbirth, associate with shorter LTL. We also identify 24 traits affected by LTL, with risk for cardiovascular, pulmonary, and some autoimmune diseases being increased by short LTL, while longer LTL increased risk for other autoimmune conditions and cancers. Through multivariable MR, we show that LTL may partially mediate the impact of educational attainment, body mass index, and female age at childbirth on proxied lifespan. CONCLUSIONS Our study sheds light on the modulators, consequences, and the mediatory role of telomeres, portraying an intricate relationship between LTL, diseases, lifestyle, and socio-economic factors.
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Affiliation(s)
- Samuel Moix
- Department of Computational Biology, UNIL, Lausanne, 1015, Switzerland.
- Swiss Institute of Bioinformatics, Lausanne, 1015, Switzerland.
| | - Marie C Sadler
- Department of Computational Biology, UNIL, Lausanne, 1015, Switzerland
- Swiss Institute of Bioinformatics, Lausanne, 1015, Switzerland
- University Center for Primary Care and Public Health, Lausanne, 1015, Switzerland
| | - Zoltán Kutalik
- Department of Computational Biology, UNIL, Lausanne, 1015, Switzerland.
- Swiss Institute of Bioinformatics, Lausanne, 1015, Switzerland.
- University Center for Primary Care and Public Health, Lausanne, 1015, Switzerland.
| | - Chiara Auwerx
- Department of Computational Biology, UNIL, Lausanne, 1015, Switzerland.
- Swiss Institute of Bioinformatics, Lausanne, 1015, Switzerland.
- University Center for Primary Care and Public Health, Lausanne, 1015, Switzerland.
- Center for Integrative Genetics, UNIL, Lausanne, 1015, Switzerland.
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