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Gorelov R, Weiner A, Huebner A, Yagi M, Haghani A, Brooke R, Horvath S, Hochedlinger K. Dissecting the impact of differentiation stage, replicative history, and cell type composition on epigenetic clocks. Stem Cell Reports 2024; 19:1242-1254. [PMID: 39178844 DOI: 10.1016/j.stemcr.2024.07.009] [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: 10/03/2023] [Revised: 07/22/2024] [Accepted: 07/23/2024] [Indexed: 08/26/2024] Open
Abstract
Epigenetic clocks, built on DNA methylation patterns of bulk tissues, are powerful age predictors, but their biological basis remains incompletely understood. Here, we conducted a comparative analysis of epigenetic age in murine muscle, epithelial, and blood cell types across lifespan. Strikingly, our results show that cellular subpopulations within these tissues, including adult stem and progenitor cells as well as their differentiated progeny, exhibit different epigenetic ages. Accordingly, we experimentally demonstrate that clocks can be skewed by age-associated changes in tissue composition. Mechanistically, we provide evidence that the observed variation in epigenetic age among adult stem cells correlates with their proliferative state, and, fittingly, forced proliferation of stem cells leads to increases in epigenetic age. Collectively, our analyses elucidate the impact of cell type composition, differentiation state, and replicative potential on epigenetic age, which has implications for the interpretation of existing clocks and should inform the development of more sensitive clocks.
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Affiliation(s)
- Rebecca Gorelov
- Massachusetts General Hospital Department of Molecular Biology, Boston, MA 02114, USA; Massachusetts General Hospital Cancer Center and Center for Regenerative Medicine, Boston, MA 02114, USA; Harvard Stem Cell Institute, Harvard University, Cambridge, MA 02139, USA; Department of Genetics, Harvard Medical School, Boston, MA 02115, USA
| | - Aaron Weiner
- Massachusetts General Hospital Department of Molecular Biology, Boston, MA 02114, USA; Massachusetts General Hospital Cancer Center and Center for Regenerative Medicine, Boston, MA 02114, USA; Harvard Stem Cell Institute, Harvard University, Cambridge, MA 02139, USA; Department of Genetics, Harvard Medical School, Boston, MA 02115, USA
| | - Aaron Huebner
- Massachusetts General Hospital Department of Molecular Biology, Boston, MA 02114, USA; Massachusetts General Hospital Cancer Center and Center for Regenerative Medicine, Boston, MA 02114, USA; Harvard Stem Cell Institute, Harvard University, Cambridge, MA 02139, USA; Department of Genetics, Harvard Medical School, Boston, MA 02115, USA
| | - Masaki Yagi
- Massachusetts General Hospital Department of Molecular Biology, Boston, MA 02114, USA; Massachusetts General Hospital Cancer Center and Center for Regenerative Medicine, Boston, MA 02114, USA; Harvard Stem Cell Institute, Harvard University, Cambridge, MA 02139, USA; Department of Genetics, Harvard Medical School, Boston, MA 02115, USA
| | - Amin Haghani
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA; Altos Labs, San Diego, CA 92121, USA
| | - Robert Brooke
- Epigenetic Clock Development Foundation, Torrance, CA 90502, USA
| | - Steve Horvath
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA; Altos Labs, San Diego, CA 92121, USA; Epigenetic Clock Development Foundation, Torrance, CA 90502, USA; Department of Biostatistics, School of Public Health, University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - Konrad Hochedlinger
- Massachusetts General Hospital Department of Molecular Biology, Boston, MA 02114, USA; Massachusetts General Hospital Cancer Center and Center for Regenerative Medicine, Boston, MA 02114, USA; Harvard Stem Cell Institute, Harvard University, Cambridge, MA 02139, USA; Department of Genetics, Harvard Medical School, Boston, MA 02115, USA.
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2
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Iordache F, Petcu ACI, Alexandru DM. Genetic and Epigenetic Interactions Involved in Senescence of Stem Cells. Int J Mol Sci 2024; 25:9708. [PMID: 39273655 PMCID: PMC11396476 DOI: 10.3390/ijms25179708] [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: 08/07/2024] [Revised: 09/04/2024] [Accepted: 09/05/2024] [Indexed: 09/15/2024] Open
Abstract
Cellular senescence is a permanent condition of cell cycle arrest caused by a progressive shortening of telomeres defined as replicative senescence. Stem cells may also undergo an accelerated senescence response known as premature senescence, distinct from telomere shortening, as a response to different stress agents. Various treatment protocols have been developed based on epigenetic changes in cells throughout senescence, using different drugs and antioxidants, senolytic vaccines, or the reprogramming of somatic senescent cells using Yamanaka factors. Even with all the recent advancements, it is still unknown how different epigenetic modifications interact with genetic profiles and how other factors such as microbiota physiological conditions, psychological states, and diet influence the interaction between genetic and epigenetic pathways. The aim of this review is to highlight the new epigenetic modifications that are involved in stem cell senescence. Here, we review recent senescence-related epigenetic alterations such as DNA methylation, chromatin remodeling, histone modification, RNA modification, and non-coding RNA regulation outlining new possible targets for the therapy of aging-related diseases. The advantages and disadvantages of the animal models used in the study of cellular senescence are also briefly presented.
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Affiliation(s)
- Florin Iordache
- Biochemistry Disciplines, Faculty of Veterinary Medicine, University of Agronomic Sciences and Veterinary Medicine, 050097 Bucharest, Romania
- Advanced Research Center for Innovative Materials, Products and Processes CAMPUS, Politehnica University, 060042 Bucharest, Romania
| | - Adriana Cornelia Ionescu Petcu
- Biochemistry Disciplines, Faculty of Veterinary Medicine, University of Agronomic Sciences and Veterinary Medicine, 050097 Bucharest, Romania
| | - Diana Mihaela Alexandru
- Pharmacology and Pharmacy Disciplines, Faculty of Veterinary Medicine, University of Agronomic Sciences and Veterinary Medicine, 050097 Bucharest, Romania
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3
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Alvarez-Kuglen M, Ninomiya K, Qin H, Rodriguez D, Fiengo L, Farhy C, Hsu WM, Kirk B, Havas A, Feng GS, Roberts AJ, Anderson RM, Serrano M, Adams PD, Sharpee TO, Terskikh AV. ImAge quantitates aging and rejuvenation. NATURE AGING 2024; 4:1308-1327. [PMID: 39210148 DOI: 10.1038/s43587-024-00685-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/23/2023] [Accepted: 07/11/2024] [Indexed: 09/04/2024]
Abstract
For efficient, cost-effective and personalized healthcare, biomarkers that capture aspects of functional, biological aging, thus predicting disease risk and lifespan more accurately and reliably than chronological age, are essential. We developed an imaging-based chromatin and epigenetic age (ImAge) that captures intrinsic age-related trajectories of the spatial organization of chromatin and epigenetic marks in single nuclei, in mice. We show that such trajectories readily emerge as principal changes in each individual dataset without regression on chronological age, and that ImAge can be computed using several epigenetic marks and DNA labeling. We find that interventions known to affect biological aging induce corresponding effects on ImAge, including increased ImAge upon chemotherapy treatment and decreased ImAge upon caloric restriction and partial reprogramming by transient OSKM expression in liver and skeletal muscle. Further, ImAge readouts from chronologically identical mice inversely correlated with their locomotor activity, suggesting that ImAge may capture elements of biological and functional age. In sum, we developed ImAge, an imaging-based biomarker of aging with single-cell resolution rooted in the analysis of spatial organization of epigenetic marks.
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Affiliation(s)
| | - Kenta Ninomiya
- Harry Perkins Institute of Medical Research, The University of Western Australia, Perth, Western Australia, Australia
| | - Haodong Qin
- Department of Physics, University of California San Diego, La Jolla, CA, USA
| | | | | | - Chen Farhy
- Sanford Burnham Prebys, La Jolla, CA, USA
| | - Wei-Mien Hsu
- Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Brian Kirk
- Sanford Burnham Prebys, La Jolla, CA, USA
| | | | - Gen-Sheng Feng
- School of Medicine, Univerity of California San Diego, La Jolla, CA, USA
| | | | - Rozalyn M Anderson
- University of Wisconsin, Madison, WI, USA
- GRECC, William S Middleton Memorial Veterans Hospital, Madison, WI, USA
| | - Manuel Serrano
- Institute for Research in Biomedicine (IRB Barcelona), Barcelona, Spain
- Barcelona Institute of Science and Technology (BIST), Barcelona, Spain
- Altos Labs, Cambridge Institute of Science, Granta Park, UK
| | | | | | - Alexey V Terskikh
- Harry Perkins Institute of Medical Research, The University of Western Australia, Perth, Western Australia, Australia.
- The Scintillon Research Institute, San Diego, CA, USA.
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4
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Bonder MJ, Clark SJ, Krueger F, Luo S, Agostinho de Sousa J, Hashtroud AM, Stubbs TM, Stark AK, Rulands S, Stegle O, Reik W, von Meyenn F. scEpiAge: an age predictor highlighting single-cell ageing heterogeneity in mouse blood. Nat Commun 2024; 15:7567. [PMID: 39217176 PMCID: PMC11366017 DOI: 10.1038/s41467-024-51833-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2023] [Accepted: 08/16/2024] [Indexed: 09/04/2024] Open
Abstract
Ageing is the accumulation of changes and decline of function of organisms over time. The concept and biomarkers of biological age have been established, notably DNA methylation-based clocks. The emergence of single-cell DNA methylation profiling methods opens the possibility of studying the biological age of individual cells. Here, we generate a large single-cell DNA methylation and transcriptome dataset from mouse peripheral blood samples, spanning a broad range of ages. The number of genes expressed increases with age, but gene-specific changes are small. We next develop scEpiAge, a single-cell DNA methylation age predictor, which can accurately predict age in (very sparse) publicly available datasets, and also in single cells. DNA methylation age distribution is wider than technically expected, indicating epigenetic age heterogeneity and functional differences. Our work provides a foundation for single-cell and sparse data epigenetic age predictors, validates their functionality and highlights epigenetic heterogeneity during ageing.
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Affiliation(s)
- Marc Jan Bonder
- Division of Computational Genomics and Systems Genetics, German Cancer Research Center, Heidelberg, Germany.
- Genome Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany.
- Department of Genetics, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands.
- Oncode Institute, Utrecht, The Netherlands.
| | - Stephen J Clark
- Altos Labs, Cambridge Institute of Science, Cambridge, UK.
- Epigenetics Programme, The Babraham Institute, Cambridge, UK.
| | - Felix Krueger
- Altos Labs, Cambridge Institute of Science, Cambridge, UK
- Bioinformatics Group, The Babraham Institute, Cambridge, UK
| | - Siyuan Luo
- Laboratory of Nutrition and Metabolic Epigenetics, Department of Health Sciences and Technology, ETH Zurich, Zurich, Switzerland
| | - João Agostinho de Sousa
- Laboratory of Nutrition and Metabolic Epigenetics, Department of Health Sciences and Technology, ETH Zurich, Zurich, Switzerland
| | - Aida M Hashtroud
- Max Planck Institute for the Physics of Complex Systems, Dresden, Germany
- Arnold Sommerfeld Center for Theoretical Physics and Center for NanoScience, Department of Physics, Ludwig-Maximilians-Universität, Munich, Germany
| | - Thomas M Stubbs
- Epigenetics Programme, The Babraham Institute, Cambridge, UK
- Chronomics Limited, London, UK
| | | | - Steffen Rulands
- Max Planck Institute for the Physics of Complex Systems, Dresden, Germany
- Arnold Sommerfeld Center for Theoretical Physics and Center for NanoScience, Department of Physics, Ludwig-Maximilians-Universität, Munich, Germany
| | - Oliver Stegle
- Division of Computational Genomics and Systems Genetics, German Cancer Research Center, Heidelberg, Germany
- Genome Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany
| | - Wolf Reik
- Altos Labs, Cambridge Institute of Science, Cambridge, UK.
- Epigenetics Programme, The Babraham Institute, Cambridge, UK.
- Wellcome Trust Sanger Institute, Hinxton, Cambridge, UK.
| | - Ferdinand von Meyenn
- Laboratory of Nutrition and Metabolic Epigenetics, Department of Health Sciences and Technology, ETH Zurich, Zurich, Switzerland.
- Department of Medical and Molecular Genetics, King's College London, London, UK.
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5
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Castro JP, Shindyapina AV, Barbieri A, Ying K, Strelkova OS, Paulo JA, Tyshkovskiy A, Meinl R, Kerepesi C, Petrashen AP, Mariotti M, Meer MV, Hu Y, Karamyshev A, Losyev G, Galhardo M, Logarinho E, Indzhykulian AA, Gygi SP, Sedivy JM, Manis JP, Gladyshev VN. Age-associated clonal B cells drive B cell lymphoma in mice. NATURE AGING 2024:10.1038/s43587-024-00671-7. [PMID: 39117982 DOI: 10.1038/s43587-024-00671-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/19/2023] [Accepted: 06/19/2024] [Indexed: 08/10/2024]
Abstract
Although cancer is an age-related disease, how the processes of aging contribute to cancer progression is not well understood. In this study, we uncovered how mouse B cell lymphoma develops as a consequence of a naturally aged system. We show here that this malignancy is associated with an age-associated clonal B cell (ACBC) population that likely originates from age-associated B cells. Driven by c-Myc activation, promoter hypermethylation and somatic mutations, IgM+ ACBCs clonally expand independently of germinal centers and show increased biological age. ACBCs become self-sufficient and support malignancy when transferred into young recipients. Inhibition of mTOR or c-Myc in old mice attenuates pre-malignant changes in B cells during aging. Although the etiology of mouse and human B cell lymphomas is considered distinct, epigenetic changes in transformed mouse B cells are enriched for changes observed in human B cell lymphomas. Together, our findings characterize the spontaneous progression of cancer during aging through both cell-intrinsic and microenvironmental changes and suggest interventions for its prevention.
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Affiliation(s)
- José P Castro
- Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- i3S, Instituto de Investigação e Inovação em Saúde, Universidade do Porto, Porto, Portugal
- Aging and Aneuploidy Laboratory, Instituto de Biologia Molecular e Celular, Universidade do Porto, Porto, Portugal
| | | | | | - Kejun Ying
- Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Olga S Strelkova
- Eaton-Peabody Laboratories, Massachusetts Eye and Ear Infirmary, Boston, MA, USA
- Department of Otolaryngology - Head and Neck Surgery, Harvard Medical School, Boston, MA, USA
| | - João A Paulo
- Department of Cell Biology, Harvard Medical School, Boston, MA, USA
| | | | - Rico Meinl
- Retro Biosciences, Redwood City, CA, USA
| | - Csaba Kerepesi
- Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Institute for Computer Science and Control (SZTAKI), Loránd Eötvös Research Network, Budapest, Hungary
| | - Anna P Petrashen
- Department of Molecular Biology, Cell Biology and Biochemistry, Brown University, Providence, RI, USA
| | - Marco Mariotti
- Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Departament de Genètica, Microbiologia i Estadística, Universitat de Barcelona, Barcelona, Spain
| | - Margarita V Meer
- Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- San Diego Institute of Sciences, Altos Labs, San Diego, CA, USA
| | - Yan Hu
- Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | | | - Grigoriy Losyev
- Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Mafalda Galhardo
- i3S, Instituto de Investigação e Inovação em Saúde, Universidade do Porto, Porto, Portugal
| | - Elsa Logarinho
- i3S, Instituto de Investigação e Inovação em Saúde, Universidade do Porto, Porto, Portugal
| | - Artur A Indzhykulian
- Eaton-Peabody Laboratories, Massachusetts Eye and Ear Infirmary, Boston, MA, USA
- Department of Otolaryngology - Head and Neck Surgery, Harvard Medical School, Boston, MA, USA
| | - Steven P Gygi
- Department of Cell Biology, Harvard Medical School, Boston, MA, USA
| | - John M Sedivy
- Department of Molecular Biology, Cell Biology and Biochemistry, Brown University, Providence, RI, USA
| | - John P Manis
- Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - Vadim N Gladyshev
- Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
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6
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Sailer LL, Haghani A, Zoller JA, Li CZ, Ophir AG, Horvath S. Epigenetic aging studies of pair bonding in prairie voles. Sci Rep 2024; 14:17439. [PMID: 39075111 PMCID: PMC11286801 DOI: 10.1038/s41598-024-67641-2] [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: 03/31/2024] [Accepted: 07/15/2024] [Indexed: 07/31/2024] Open
Abstract
The quality of romantic relationships can predict health consequences related to aging. DNA methylation-based biomarkers of aging accurately estimate chronological age. We developed several highly accurate epigenetic aging clocks, based on highly conserved mammalian CpGs, for the socially monogamous prairie vole (Microtus ochrogaster). In addition, our dual-species human-vole clock accurately measured relative age and illustrates high species conservation of epigenetic aging effects. Next, we assessed how pair bonding impacts epigenetic aging. We did not find evidence that pair-bonded voles exhibit accelerated or decelerated epigenetic aging effects in blood, ear, liver, or brain tissue. Our epigenome wide association study identified CpGs in five genes strongly associated with pair bonding: Foxp4, Phf2, Mms22l, Foxb1, and Eif1ad. Overall, we present accurate DNA methylation-based estimators of age for a species of great interest to researchers studying monogamy in animals. We did not find any evidence that sex-naive animals age differently from pair-bonded animals.
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Affiliation(s)
- Lindsay L Sailer
- Department of Psychology, Cornell University, Ithaca, NY, 14853, USA
| | | | - Joseph A Zoller
- Department of Biostatistics, School of Public Health, University of California, Los Angeles, CA, USA
| | - Caesar Z Li
- Department of Biostatistics, School of Public Health, University of California, Los Angeles, CA, USA
| | - Alexander G Ophir
- Department of Psychology, Cornell University, Ithaca, NY, 14853, USA.
| | - Steve Horvath
- Altos Labs, San Diego, USA.
- Department of Biostatistics, School of Public Health, University of California, Los Angeles, CA, USA.
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, CA, USA.
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7
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Kriukov D, Kuzmina E, Efimov E, Dylov DV, Khrameeva EE. Epistemic uncertainty challenges aging clock reliability in predicting rejuvenation effects. Aging Cell 2024:e14283. [PMID: 39072888 DOI: 10.1111/acel.14283] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2024] [Revised: 06/28/2024] [Accepted: 07/03/2024] [Indexed: 07/30/2024] Open
Abstract
Epigenetic aging clocks have been widely used to validate rejuvenation effects during cellular reprogramming. However, these predictions are unverifiable because the true biological age of reprogrammed cells remains unknown. We present an analytical framework to consider rejuvenation predictions from the uncertainty perspective. Our analysis reveals that the DNA methylation profiles across reprogramming are poorly represented in the aging data used to train clock models, thus introducing high epistemic uncertainty in age estimations. Moreover, predictions of different published clocks are inconsistent, with some even suggesting zero or negative rejuvenation. While not questioning the possibility of age reversal, we show that the high clock uncertainty challenges the reliability of rejuvenation effects observed during in vitro reprogramming before pluripotency and throughout embryogenesis. Conversely, our method reveals a significant age increase after in vivo reprogramming. We recommend including uncertainty estimation in future aging clock models to avoid the risk of misinterpreting the results of biological age prediction.
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Affiliation(s)
- Dmitrii Kriukov
- Skolkovo Institute of Science and Technology, Moscow, Russia
- Artificial Intelligence Research Institute, Moscow, Russia
| | - Ekaterina Kuzmina
- Skolkovo Institute of Science and Technology, Moscow, Russia
- Artificial Intelligence Research Institute, Moscow, Russia
| | - Evgeniy Efimov
- Skolkovo Institute of Science and Technology, Moscow, Russia
| | - Dmitry V Dylov
- Skolkovo Institute of Science and Technology, Moscow, Russia
- Artificial Intelligence Research Institute, Moscow, Russia
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8
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Swer PB, Kharbuli B, Syiem D, Sharma R. Age-related decline in the expression of BRG1, ATM and ATR are partially reversed by dietary restriction in the livers of female mice. Biogerontology 2024:10.1007/s10522-024-10117-7. [PMID: 38970714 DOI: 10.1007/s10522-024-10117-7] [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: 05/24/2024] [Accepted: 06/26/2024] [Indexed: 07/08/2024]
Abstract
BRG1 (Brahma-related gene 1) is a member of the SWI/SNF (switch/sucrose nonfermentable) chromatin remodeling complex which utilizes the energy from ATP hydrolysis for its activity. In addition to its role of regulating the expression of a vast array of genes, BRG1 mediates DNA repair upon genotoxic stress and regulates senescence. During organismal ageing, there is accumulation of unrepaired/unrepairable DNA damage due to progressive breakdown of the DNA repair machinery. The present study investigates the expression level of BRG1 as a function of age in the liver of 5- and 21-month-old female mice. It also explores the impact of dietary restriction on BRG1 expression in the old (21-month) mice. Salient findings of the study are: Real-time PCR and Western blot analyses reveal that BRG1 levels are higher in 5-month-old mice but decrease significantly with age. Dietary restriction increases BRG1 expression in the 21-month-old mice, nearly restoring it to the level observed in the younger group. Similar expression patterns are observed for DNA damage response genes ATM (Ataxia Telangiectasia Mutated) and ATR (Ataxia Telangiectasia and Rad3-related) with the advancement in age and which appears to be modulated by dietary restriction. BRG1 transcriptionally regulates ATM as a function of age and dietary restriction. These results suggest that BRG1, ATM and ATR are downregulated as mice age, and dietary restriction can restore their expression. This implies that dietary restriction may play a crucial role in regulating BRG1 and related gene expression, potentially maintaining liver repair and metabolic processes as mice age.
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Affiliation(s)
- Pynskhem Bok Swer
- Department of Biochemistry, North-Eastern Hill University, Shillong, 793022, India
| | | | - Donkupar Syiem
- Department of Biochemistry, North-Eastern Hill University, Shillong, 793022, India
| | - Ramesh Sharma
- Department of Biochemistry, North-Eastern Hill University, Shillong, 793022, India.
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9
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Parikh C, Glenn RA, Shi Y, Chatterjee K, Swanzey EE, Singer S, Do SC, Zhan Y, Furuta Y, Tahiliani M, Apostolou E, Polyzos A, Koche R, Mezey JG, Vierbuchen T, Stadtfeld M. Genetic variation modulates susceptibility to aberrant DNA hypomethylation and imprint deregulation in naïve pluripotent stem cells. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.06.26.600805. [PMID: 38979237 PMCID: PMC11230387 DOI: 10.1101/2024.06.26.600805] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/10/2024]
Abstract
Naïve pluripotent stem cells (nPSC) frequently undergo pathological and not readily reversible loss of DNA methylation marks at imprinted gene loci. This abnormality poses a hurdle for using pluripotent cell lines in biomedical applications and underscores the need to identify the causes of imprint instability in these cells. We show that nPSCs from inbred mouse strains exhibit pronounced strain-specific susceptibility to locus-specific deregulation of imprinting marks during reprogramming to pluripotency and upon culture with MAP kinase inhibitors, a common approach to maintain naïve pluripotency. Analysis of genetically highly diverse nPSCs from the Diversity Outbred (DO) stock confirms that genetic variation is a major determinant of epigenome stability in pluripotent cells. We leverage the variable DNA hypomethylation in DO lines to identify several trans-acting quantitative trait loci (QTLs) that determine epigenome stability at either specific target loci or genome-wide. Candidate factors encoded by two multi-target QTLs on chromosomes 4 and 17 suggest specific transcriptional regulators that contribute to DNA methylation maintenance in nPSCs. We propose that genetic variants represent candidate biomarkers to identify pluripotent cell lines with desirable properties and might serve as entry points for the targeted engineering of nPSCs with stable epigenomes. Highlights Naïve pluripotent stem cells from distinct inbred mouse strains exhibit variable DNA methylation levels at imprinted gene loci.The vulnerability of pluripotent stem cells to loss of genomic imprinting caused by MAP kinase inhibition strongly differs between inbred mouse strains.Genetically diverse pluripotent stem cell lines from Diversity Outbred mouse stock allow the identification of quantitative trait loci controlling DNA methylation stability.Genetic variants may serve as biomarkers to identify naïve pluripotent stem cell lines that are epigenetically stable in specific culture conditions.
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10
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Yusri K, Kumar S, Fong S, Gruber J, Sorrentino V. Towards Healthy Longevity: Comprehensive Insights from Molecular Targets and Biomarkers to Biological Clocks. Int J Mol Sci 2024; 25:6793. [PMID: 38928497 PMCID: PMC11203944 DOI: 10.3390/ijms25126793] [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: 05/23/2024] [Revised: 06/16/2024] [Accepted: 06/18/2024] [Indexed: 06/28/2024] Open
Abstract
Aging is a complex and time-dependent decline in physiological function that affects most organisms, leading to increased risk of age-related diseases. Investigating the molecular underpinnings of aging is crucial to identify geroprotectors, precisely quantify biological age, and propose healthy longevity approaches. This review explores pathways that are currently being investigated as intervention targets and aging biomarkers spanning molecular, cellular, and systemic dimensions. Interventions that target these hallmarks may ameliorate the aging process, with some progressing to clinical trials. Biomarkers of these hallmarks are used to estimate biological aging and risk of aging-associated disease. Utilizing aging biomarkers, biological aging clocks can be constructed that predict a state of abnormal aging, age-related diseases, and increased mortality. Biological age estimation can therefore provide the basis for a fine-grained risk stratification by predicting all-cause mortality well ahead of the onset of specific diseases, thus offering a window for intervention. Yet, despite technological advancements, challenges persist due to individual variability and the dynamic nature of these biomarkers. Addressing this requires longitudinal studies for robust biomarker identification. Overall, utilizing the hallmarks of aging to discover new drug targets and develop new biomarkers opens new frontiers in medicine. Prospects involve multi-omics integration, machine learning, and personalized approaches for targeted interventions, promising a healthier aging population.
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Affiliation(s)
- Khalishah Yusri
- Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, Singapore 117596, Singapore
- Healthy Longevity Translational Research Program, Yong Loo Lin School of Medicine, National University of Singapore, Singapore 119228, Singapore
| | - Sanjay Kumar
- Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, Singapore 117596, Singapore
- Healthy Longevity Translational Research Program, Yong Loo Lin School of Medicine, National University of Singapore, Singapore 119228, Singapore
| | - Sheng Fong
- Department of Geriatric Medicine, Singapore General Hospital, Singapore 169608, Singapore
- Clinical and Translational Sciences PhD Program, Duke-NUS Medical School, Singapore 169857, Singapore
| | - Jan Gruber
- Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, Singapore 117596, Singapore
- Healthy Longevity Translational Research Program, Yong Loo Lin School of Medicine, National University of Singapore, Singapore 119228, Singapore
- Science Division, Yale-NUS College, Singapore 138527, Singapore
| | - Vincenzo Sorrentino
- Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, Singapore 117596, Singapore
- Healthy Longevity Translational Research Program, Yong Loo Lin School of Medicine, National University of Singapore, Singapore 119228, Singapore
- Department of Medical Biochemistry, Amsterdam UMC, Amsterdam Gastroenterology Endocrinology Metabolism and Amsterdam Neuroscience Cellular & Molecular Mechanisms, University of Amsterdam, Meibergdreef 9, 1105AZ Amsterdam, The Netherlands
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11
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Tarkhov AE, Lindstrom-Vautrin T, Zhang S, Ying K, Moqri M, Zhang B, Tyshkovskiy A, Levy O, Gladyshev VN. Nature of epigenetic aging from a single-cell perspective. NATURE AGING 2024; 4:854-870. [PMID: 38724733 DOI: 10.1038/s43587-024-00616-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/20/2023] [Accepted: 03/26/2024] [Indexed: 05/15/2024]
Abstract
Age-related changes in DNA methylation (DNAm) form the basis of the most robust predictors of age-epigenetic clocks-but a clear mechanistic understanding of exactly which aspects of aging are quantified by these clocks is lacking. Here, to clarify the nature of epigenetic aging, we juxtapose the dynamics of tissue and single-cell DNAm in mice. We compare these changes during early development with those observed during adult aging in mice, and corroborate our analyses with a single-cell RNA sequencing analysis within the same multiomics dataset. We show that epigenetic aging involves co-regulated changes as well as a major stochastic component, and this is consistent with transcriptional patterns. We further support the finding of stochastic epigenetic aging by direct tissue and single-cell DNAm analyses and modeling of aging DNAm trajectories with a stochastic process akin to radiocarbon decay. Finally, we describe a single-cell algorithm for the identification of co-regulated and stochastic CpG clusters showing consistent transcriptomic coordination patterns. Together, our analyses increase our understanding of the basis of epigenetic clocks and highlight potential opportunities for targeting aging and evaluating longevity interventions.
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Affiliation(s)
- Andrei E Tarkhov
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA.
- Retro Biosciences Inc., Redwood City, CA, USA.
| | - Thomas Lindstrom-Vautrin
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Sirui Zhang
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Kejun Ying
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Mahdi Moqri
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Department of Obstetrics & Gynecology, Stanford School of Medicine, Stanford University, Stanford, CA, USA
- Institute for Stem Cell Biology and Regenerative Medicine, Stanford School of Medicine, Stanford University, Stanford, CA, USA
| | - Bohan Zhang
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Alexander Tyshkovskiy
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Orr Levy
- Howard Hughes Medical Institute, Chevy Chase, MD, USA
- Department of Immunobiology, Yale University School of Medicine, New Haven, CT, USA
| | - Vadim N Gladyshev
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA.
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12
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Islam M, Behura SK. Molecular Regulation of Fetal Brain Development in Inbred and Congenic Mouse Strains Differing in Longevity. Genes (Basel) 2024; 15:604. [PMID: 38790233 PMCID: PMC11121069 DOI: 10.3390/genes15050604] [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: 04/19/2024] [Revised: 05/04/2024] [Accepted: 05/08/2024] [Indexed: 05/26/2024] Open
Abstract
The objective of this study was to investigate gene regulation of the developing fetal brain from congenic or inbred mice strains that differed in longevity. Gene expression and alternative splice variants were analyzed in a genome-wide manner in the fetal brain of C57BL/6J mice (long-lived) in comparison to B6.Cg-Cav1tm1Mls/J (congenic, short-lived) and AKR/J (inbred, short-lived) mice on day(d) 12, 15, and 17 of gestation. The analysis showed a contrasting gene expression pattern during fetal brain development in these mice. Genes related to brain development, aging, and the regulation of alternative splicing were significantly differentially regulated in the fetal brain of the short-lived compared to long-lived mice during development from d15 and d17. A significantly reduced number of splice variants was observed on d15 compared to d12 or d17 in a strain-dependent manner. An epigenetic clock analysis of d15 fetal brain identified DNA methylations that were significantly associated with single-nucleotide polymorphic sites between AKR/J and C57BL/6J strains. These methylations were associated with genes that show epigenetic changes in an age-correlated manner in mice. Together, the finding of this study suggest that fetal brain development and longevity are epigenetically linked, supporting the emerging concept of the early-life origin of longevity.
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Affiliation(s)
- Maliha Islam
- Division of Animal Sciences, University of Missouri, Columbia, MO 65211, USA
| | - Susanta K. Behura
- Division of Animal Sciences, University of Missouri, Columbia, MO 65211, USA
- MU Institute for Data Science and Informatics, University of Missouri, Columbia, MO 65211, USA
- Interdisciplinary Reproduction and Health Group, University of Missouri, Columbia, MO 65211, USA
- Interdisciplinary Neuroscience Program, University of Missouri, Columbia, MO 65211, USA
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13
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González JT, Thrush K, Meer M, Levine ME, Higgins-Chen AT. Age-Invariant Genes: Multi-Tissue Identification and Characterization of Murine Reference Genes. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.04.09.588721. [PMID: 38645168 PMCID: PMC11030416 DOI: 10.1101/2024.04.09.588721] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/23/2024]
Abstract
Studies of the aging transcriptome focus on genes that change with age. But what can we learn from age-invariant genes-those that remain unchanged throughout the aging process? These genes also have a practical application: they serve as reference genes (often called housekeeping genes) in expression studies. Reference genes have mostly been identified and validated in young organisms, and no systematic investigation has been done across the lifespan. Here, we build upon a common pipeline for identifying reference genes in RNA-seq datasets to identify age-invariant genes across seventeen C57BL/6 mouse tissues (brain, lung, bone marrow, muscle, white blood cells, heart, small intestine, kidney, liver, pancreas, skin, brown, gonadal, marrow, and subcutaneous adipose tissue) spanning 1 to 21+ months of age. We identify 9 pan-tissue age-invariant genes and many tissue-specific age-invariant genes. These genes are stable across the lifespan and are validated in independent bulk RNA-seq datasets and RT-qPCR. We find age-invariant genes have shorter transcripts on average and are enriched for CpG islands. Interestingly, pathway enrichment analysis for age-invariant genes identifies an overrepresentation of molecular functions associated with some, but not all, hallmarks of aging. Thus, though hallmarks of aging typically involve changes in cell maintenance mechanisms, select genes associated with these hallmarks resist fluctuations in expression with age. Finally, our analysis concludes no classical reference gene is appropriate for aging studies in all tissues. Instead, we provide tissue-specific and pan-tissue genes for assays utilizing reference gene normalization (i.e., RT-qPCR) that can be applied to animals across the lifespan.
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Affiliation(s)
- John T. González
- Department of Pathology, Yale University School of Medicine, New Haven, CT, USA
| | - Kyra Thrush
- Altos Labs, San Diego Institute of Sciences, San Diego, CA, USA
| | - Margarita Meer
- Altos Labs, San Diego Institute of Sciences, San Diego, CA, USA
| | - Morgan E. Levine
- Department of Pathology, Yale University School of Medicine, New Haven, CT, USA
- Altos Labs, San Diego Institute of Sciences, San Diego, CA, USA
| | - Albert T. Higgins-Chen
- Department of Pathology, Yale University School of Medicine, New Haven, CT, USA
- Department of Psychiatry, Yale University School of Medicine, New Haven CT, USA
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14
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de Lima Camillo LP. pyaging: a Python-based compendium of GPU-optimized aging clocks. Bioinformatics 2024; 40:btae200. [PMID: 38603598 PMCID: PMC11058068 DOI: 10.1093/bioinformatics/btae200] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2023] [Revised: 03/28/2024] [Accepted: 04/09/2024] [Indexed: 04/13/2024] Open
Abstract
MOTIVATION Aging is intricately linked to diseases and mortality. It is reflected in molecular changes across various tissues which can be leveraged for the development of biomarkers of aging using machine learning models, known as aging clocks. Despite advancements in the field, a significant challenge remains: the lack of robust, Python-based software tools for integrating and comparing these diverse models. This gap highlights the need for comprehensive solutions that can handle the complexity and variety of data in aging research. RESULTS To address this gap, I introduce pyaging, a comprehensive open-source Python package designed to facilitate aging research. pyaging harmonizes dozens of aging clocks, covering a range of molecular data types such as DNA methylation, transcriptomics, histone mark ChIP-Seq, and ATAC-Seq. The package is not limited to traditional model types; it features a diverse array, from linear and principal component models to neural networks and automatic relevance determination models. Thanks to a PyTorch-based backend that enables GPU acceleration, pyaging is capable of rapid inference, even when dealing with large datasets and complex models. In addition, the package's support for multi-species analysis extends its utility across various organisms, including humans, various mammals, and Caenorhabditis elegans. AVAILABILITY AND IMPLEMENTATION pyaging is accessible on GitHub, at https://github.com/rsinghlab/pyaging, and the distribution is available on PyPi, at https://pypi.org/project/pyaging/. The software is also archived on Zenodo, at https://zenodo.org/doi/10.5281/zenodo.10335011.
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15
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Horvath S, Singh K, Raj K, Khairnar SI, Sanghavi A, Shrivastava A, Zoller JA, Li CZ, Herenu CB, Canatelli-Mallat M, Lehmann M, Habazin S, Novokmet M, Vučković F, Solberg Woods LC, Martinez AG, Wang T, Chiavellini P, Levine AJ, Chen H, Brooke RT, Gordevicius J, Lauc G, Goya RG, Katcher HL. Reversal of biological age in multiple rat organs by young porcine plasma fraction. GeroScience 2024; 46:367-394. [PMID: 37875652 PMCID: PMC10828479 DOI: 10.1007/s11357-023-00980-6] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/07/2023] [Accepted: 10/09/2023] [Indexed: 10/26/2023] Open
Abstract
Young blood plasma is known to confer beneficial effects on various organs in mice and rats. However, it was not known whether plasma from young adult pigs rejuvenates old rat tissues at the epigenetic level; whether it alters the epigenetic clock, which is a highly accurate molecular biomarker of aging. To address this question, we developed and validated six different epigenetic clocks for rat tissues that are based on DNA methylation values derived from n = 613 tissue samples. As indicated by their respective names, the rat pan-tissue clock can be applied to DNA methylation profiles from all rat tissues, while the rat brain, liver, and blood clocks apply to the corresponding tissue types. We also developed two epigenetic clocks that apply to both human and rat tissues by adding n = 1366 human tissue samples to the training data. We employed these six rat clocks to investigate the rejuvenation effects of a porcine plasma fraction treatment in different rat tissues. The treatment more than halved the epigenetic ages of blood, heart, and liver tissue. A less pronounced, but statistically significant, rejuvenation effect could be observed in the hypothalamus. The treatment was accompanied by progressive improvement in the function of these organs as ascertained through numerous biochemical/physiological biomarkers, behavioral responses encompassing cognitive functions. An immunoglobulin G (IgG) N-glycosylation pattern shift from pro- to anti-inflammatory also indicated reversal of glycan aging. Overall, this study demonstrates that a young porcine plasma-derived treatment markedly reverses aging in rats according to epigenetic clocks, IgG glycans, and other biomarkers of aging.
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Affiliation(s)
- Steve Horvath
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, CA, USA.
- Department of Biostatistics, Fielding School of Public Health, University of California, Los Angeles, CA, USA.
- Altos Labs, Cambridge, UK.
| | - Kavita Singh
- Shobhaben Pratapbhai Patel School of Pharmacy and Technology Management, SVKM's NMIMS University, Mumbai, India
| | | | - Shraddha I Khairnar
- Shobhaben Pratapbhai Patel School of Pharmacy and Technology Management, SVKM's NMIMS University, Mumbai, India
| | | | | | - Joseph A Zoller
- Department of Biostatistics, Fielding School of Public Health, University of California, Los Angeles, CA, USA
| | - Caesar Z Li
- Department of Biostatistics, Fielding School of Public Health, University of California, Los Angeles, CA, USA
| | - Claudia B Herenu
- Institute for Experimental Pharmacology of Cordoba (IFEC), School of Chemical Sciences, National University of Cordoba, Cordoba, Argentina
| | - Martina Canatelli-Mallat
- Biochemistry Research Institute of La Plata-Histology B, Pathology B, School of Medicine, University of La Plata, La Plata, Argentina
| | - Marianne Lehmann
- Biochemistry Research Institute of La Plata-Histology B, Pathology B, School of Medicine, University of La Plata, La Plata, Argentina
| | | | | | | | - Leah C Solberg Woods
- Wake Forest University School of Medicine, Medical Center Drive, Winston Salem, NC, USA
| | - Angel Garcia Martinez
- Department of Pharmacology, Addiction Science and Toxicology, The University of Tennessee Health Science Center, Memphis, TN, USA
| | - Tengfei Wang
- Department of Pharmacology, Addiction Science and Toxicology, The University of Tennessee Health Science Center, Memphis, TN, USA
| | - Priscila Chiavellini
- Biochemistry Research Institute of La Plata-Histology B, Pathology B, School of Medicine, University of La Plata, La Plata, Argentina
| | - Andrew J Levine
- Department of Neurology, David Geffen School of Medicine at the University of California, Los Angeles, CA, USA
| | - Hao Chen
- Department of Pharmacology, Addiction Science and Toxicology, The University of Tennessee Health Science Center, Memphis, TN, USA
| | | | | | - Gordan Lauc
- Genos Glycoscience Research Laboratory, Zagreb, Croatia
- Faculty of Pharmacy and Biochemistry, University of Zagreb, Zagreb, Croatia
| | - Rodolfo G Goya
- Biochemistry Research Institute of La Plata-Histology B, Pathology B, School of Medicine, University of La Plata, La Plata, Argentina
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16
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Ying K, Liu H, Tarkhov AE, Sadler MC, Lu AT, Moqri M, Horvath S, Kutalik Z, Shen X, Gladyshev VN. Causality-enriched epigenetic age uncouples damage and adaptation. NATURE AGING 2024; 4:231-246. [PMID: 38243142 PMCID: PMC11070280 DOI: 10.1038/s43587-023-00557-0] [Citation(s) in RCA: 13] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/16/2023] [Accepted: 12/12/2023] [Indexed: 01/21/2024]
Abstract
Machine learning models based on DNA methylation data can predict biological age but often lack causal insights. By harnessing large-scale genetic data through epigenome-wide Mendelian randomization, we identified CpG sites potentially causal for aging-related traits. Neither the existing epigenetic clocks nor age-related differential DNA methylation are enriched in these sites. These CpGs include sites that contribute to aging and protect against it, yet their combined contribution negatively affects age-related traits. We established a new framework to introduce causal information into epigenetic clocks, resulting in DamAge and AdaptAge-clocks that track detrimental and adaptive methylation changes, respectively. DamAge correlates with adverse outcomes, including mortality, while AdaptAge is associated with beneficial adaptations. These causality-enriched clocks exhibit sensitivity to short-term interventions. Our findings provide a detailed landscape of CpG sites with putative causal links to lifespan and healthspan, facilitating the development of aging biomarkers, assessing interventions, and studying reversibility of age-associated changes.
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Affiliation(s)
- Kejun Ying
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- T. H. Chan School of Public Health, Harvard University, Boston, MA, USA
| | - Hanna Liu
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Massachusetts College of Pharmacy and Health Sciences, Boston, MA, USA
- Department of Pharmacy, Massachusetts General Hospital, Boston, MA, USA
| | - Andrei E Tarkhov
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Marie C Sadler
- University Center for Primary Care and Public Health, University of Lausanne, Lausanne, Switzerland
- Department of Computational Biology, University of Lausanne, Lausanne, Switzerland
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Ake T Lu
- Altos Labs, San Diego, CA, USA
- Departments of Human Genetics and Biostatistics, University of California, Los Angeles, Los Angeles, CA, USA
| | - Mahdi Moqri
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Department of Genetics, School of Medicine, Stanford University, Stanford, CA, USA
| | - Steve Horvath
- Altos Labs, San Diego, CA, USA
- Departments of Human Genetics and Biostatistics, University of California, Los Angeles, Los Angeles, CA, USA
| | - Zoltán Kutalik
- University Center for Primary Care and Public Health, University of Lausanne, Lausanne, Switzerland
- Department of Computational Biology, University of Lausanne, Lausanne, Switzerland
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Xia Shen
- Center for Intelligent Medicine Research, Greater Bay Area Institute of Precision Medicine (Guangzhou), Fudan University, Guangzhou, China
- State Key Laboratory of Genetic Engineering, Center for Evolutionary Biology, School of Life Sciences, Fudan University, Shanghai, China
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
- Centre for Global Health Research, Usher Institute, University of Edinburgh, Edinburgh, UK
| | - Vadim N Gladyshev
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA.
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17
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Griffin PT, Kane AE, Trapp A, Li J, Arnold M, Poganik JR, Conway RJ, McNamara MS, Meer MV, Hoffman N, Amorim JA, Tian X, MacArthur MR, Mitchell SJ, Mueller AL, Carmody C, Vera DL, Kerepesi C, Ying K, Noren Hooten N, Mitchell JR, Evans MK, Gladyshev VN, Sinclair DA. TIME-seq reduces time and cost of DNA methylation measurement for epigenetic clock construction. NATURE AGING 2024; 4:261-274. [PMID: 38200273 PMCID: PMC11332592 DOI: 10.1038/s43587-023-00555-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/06/2021] [Accepted: 12/05/2023] [Indexed: 01/12/2024]
Abstract
Epigenetic 'clocks' based on DNA methylation have emerged as the most robust and widely used aging biomarkers, but conventional methods for applying them are expensive and laborious. Here we develop tagmentation-based indexing for methylation sequencing (TIME-seq), a highly multiplexed and scalable method for low-cost epigenetic clocks. Using TIME-seq, we applied multi-tissue and tissue-specific epigenetic clocks in over 1,800 mouse DNA samples from eight tissue and cell types. We show that TIME-seq clocks are accurate and robust, enriched for polycomb repressive complex 2-regulated loci, and benchmark favorably against conventional methods despite being up to 100-fold less expensive. Using dietary treatments and gene therapy, we find that TIME-seq clocks reflect diverse interventions in multiple tissues. Finally, we develop an economical human blood clock (R > 0.96, median error = 3.39 years) in 1,056 demographically representative individuals. These methods will enable more efficient epigenetic clock measurement in larger-scale human and animal studies.
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Affiliation(s)
- Patrick T Griffin
- Blavatnik Institute, Department of Genetics, Paul F. Glenn Center for Biology of Aging Research at Harvard Medical School, Boston, MA, USA
| | - Alice E Kane
- Blavatnik Institute, Department of Genetics, Paul F. Glenn Center for Biology of Aging Research at Harvard Medical School, Boston, MA, USA
- Institute for Systems Biology, Seattle, WA, USA
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, WA, USA
| | - Alexandre Trapp
- Brigham and Women's Hospital, Division of Genetics, Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Jien Li
- Blavatnik Institute, Department of Genetics, Paul F. Glenn Center for Biology of Aging Research at Harvard Medical School, Boston, MA, USA
| | - Matthew Arnold
- Blavatnik Institute, Department of Genetics, Paul F. Glenn Center for Biology of Aging Research at Harvard Medical School, Boston, MA, USA
| | - Jesse R Poganik
- Brigham and Women's Hospital, Division of Genetics, Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Ryan J Conway
- Blavatnik Institute, Department of Genetics, Paul F. Glenn Center for Biology of Aging Research at Harvard Medical School, Boston, MA, USA
| | - Maeve S McNamara
- Blavatnik Institute, Department of Genetics, Paul F. Glenn Center for Biology of Aging Research at Harvard Medical School, Boston, MA, USA
| | - Margarita V Meer
- Brigham and Women's Hospital, Division of Genetics, Department of Medicine, Harvard Medical School, Boston, MA, USA
- Department of Pathology, Yale University School of Medicine, New Haven, CT, USA
- San Diego Institute of Science, Altos Labs, San Diego, CA, USA
| | - Noah Hoffman
- Blavatnik Institute, Department of Genetics, Paul F. Glenn Center for Biology of Aging Research at Harvard Medical School, Boston, MA, USA
| | - João A Amorim
- Blavatnik Institute, Department of Genetics, Paul F. Glenn Center for Biology of Aging Research at Harvard Medical School, Boston, MA, USA
| | - Xiao Tian
- Blavatnik Institute, Department of Genetics, Paul F. Glenn Center for Biology of Aging Research at Harvard Medical School, Boston, MA, USA
- Sanford Burnham Prebys Medical Discovery Institute, La Jolla, CA, USA
| | - Michael R MacArthur
- Department of Health Sciences and Technology, Eidgenössische Technische Hochschule Zürich, Zurich, Switzerland
- Lewis-Sigler Institute of Integrative Genomics, Princeton University, Princeton, NJ, USA
| | - Sarah J Mitchell
- Department of Health Sciences and Technology, Eidgenössische Technische Hochschule Zürich, Zurich, Switzerland
- Ludwig Princeton Branch, Princeton University, Princeton, NJ, USA
| | - Amber L Mueller
- Blavatnik Institute, Department of Genetics, Paul F. Glenn Center for Biology of Aging Research at Harvard Medical School, Boston, MA, USA
- Cell Metabolism, Cell Press, Cambridge, MA, USA
| | - Colleen Carmody
- Blavatnik Institute, Department of Genetics, Paul F. Glenn Center for Biology of Aging Research at Harvard Medical School, Boston, MA, USA
| | - Daniel L Vera
- Blavatnik Institute, Department of Genetics, Paul F. Glenn Center for Biology of Aging Research at Harvard Medical School, Boston, MA, USA
| | - Csaba Kerepesi
- Brigham and Women's Hospital, Division of Genetics, Department of Medicine, Harvard Medical School, Boston, MA, USA
- Institute for Computer Science and Control, Eötvös Loránd Research Network, Budapest, Hungary
| | - Kejun Ying
- Brigham and Women's Hospital, Division of Genetics, Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Nicole Noren Hooten
- Laboratory of Epidemiology and Population Science, National Institute on Aging, National Institutes of Health, Baltimore, MD, USA
| | - James R Mitchell
- Department of Health Sciences and Technology, Eidgenössische Technische Hochschule Zürich, Zurich, Switzerland
| | - Michele K Evans
- Laboratory of Epidemiology and Population Science, National Institute on Aging, National Institutes of Health, Baltimore, MD, USA
| | - Vadim N Gladyshev
- Brigham and Women's Hospital, Division of Genetics, Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - David A Sinclair
- Blavatnik Institute, Department of Genetics, Paul F. Glenn Center for Biology of Aging Research at Harvard Medical School, Boston, MA, USA.
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18
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Abudahab S, Slattum PW, Price ET, McClay JL. Epigenetic regulation of drug metabolism in aging: utilizing epigenetics to optimize geriatric pharmacotherapy. Pharmacogenomics 2024; 25:41-54. [PMID: 38126340 PMCID: PMC10794944 DOI: 10.2217/pgs-2023-0199] [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: 10/19/2023] [Accepted: 12/06/2023] [Indexed: 12/23/2023] Open
Abstract
We explore the relationship between epigenetic aging and drug metabolism. We review current evidence for changes in drug metabolism in normal aging, followed by a description of how epigenetic modifications associated with age can regulate the expression and functionality of genes. In particular, we focus on the role of epigenome-wide studies of human and mouse liver in understanding these age-related processes with respect to xenobiotic processing. We highlight genes encoding drug metabolizing enzymes and transporters revealed to be affected by epigenetic aging in these studies. We conclude that substantial evidence exists for epigenetic aging impacting drug metabolism and transport genes, but more work is needed. We further highlight the promise of pharmacoepigenetics applied to enhancing drug safety in older adults.
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Affiliation(s)
- Sara Abudahab
- Department of Pharmacotherapy & Outcomes Science, School of Pharmacy, Virginia Commonwealth University, Richmond, VA 23298, USA
| | - Patricia W Slattum
- Department of Pharmacotherapy & Outcomes Science, School of Pharmacy, Virginia Commonwealth University, Richmond, VA 23298, USA
- Virginia Center on Aging, Virginia Commonwealth University, Richmond, VA 23298, USA
| | - Elvin T Price
- Department of Pharmacotherapy & Outcomes Science, School of Pharmacy, Virginia Commonwealth University, Richmond, VA 23298, USA
| | - Joseph L McClay
- Department of Pharmacotherapy & Outcomes Science, School of Pharmacy, Virginia Commonwealth University, Richmond, VA 23298, USA
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19
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Islam M, Samal A, Davis DJ, Behura SK. Ablation of placental REST deregulates fetal brain metabolism and impacts gene expression of the offspring brain at the postnatal and adult stages. FASEB J 2024; 38:e23349. [PMID: 38069914 DOI: 10.1096/fj.202301344r] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2023] [Revised: 10/26/2023] [Accepted: 11/20/2023] [Indexed: 12/18/2023]
Abstract
In this study, the transcriptional repressor REST (Repressor Element 1 Silencing Transcription factor) was ablated in the mouse placenta to investigate molecular and cellular impacts on the offspring brain at different life stages. Ablation of placental REST deregulated several brain metabolites, including glucose and lactate that fuel brain energy, vitamin C (ascorbic acid) that functions in the epigenetic programming of the brain during postnatal development, and glutamate and creatine that help the brain to respond to stress conditions during adult life. Bulk RNA-seq analysis showed that a lack of placental REST persistently altered multiple transport genes, including those related to oxygen transportation in the offspring brain. While metabolic genes were impacted in the postnatal brain, different stress response genes were activated in the adult brain. DNA methylation was also impacted in the adult brain due to the loss of placental REST, but in a sex-biased manner. Single-nuclei RNA-seq analysis showed that specific cell types of the brain, particularly those of the choroid plexus and ependyma, which play critical roles in producing cerebrospinal fluid and maintaining metabolic homeostasis, were significantly impacted due to the loss of placental REST. These cells showed significant differential expression of genes associated with the metabotropic (G coupled protein) and ionotropic (ligand-gated ion channel) glutamate receptors, suggesting an impact of ablation of placental REST on the glutamatergic signaling of the offspring brain. The study expands our understanding of placental influences on the offspring brain.
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Affiliation(s)
- Maliha Islam
- Division of Animal Sciences, University of Missouri, Columbia, Missouri, USA
| | - Ananya Samal
- Division of Animal Sciences, University of Missouri, Columbia, Missouri, USA
| | - Daniel J Davis
- Department of Veterinary Pathobiology, University of Missouri, Columbia, Missouri, USA
- Animal Modeling Core, University of Missouri, Columbia, Missouri, USA
| | - Susanta K Behura
- Division of Animal Sciences, University of Missouri, Columbia, Missouri, USA
- MU Institute for Data Science and Informatics, University of Missouri, Columbia, Missouri, USA
- Interdisciplnary Reproductive and Health Group, University of Missouri, Columbia, Missouri, USA
- Interdisciplinary Neuroscience Program, University of Missouri, Columbia, Missouri, USA
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20
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Karimnia N, Harris J, Heazlewood SY, Cao B, Nilsson SK. Metabolic regulation of aged hematopoietic stem cells: key players and mechanisms. Exp Hematol 2023; 128:2-9. [PMID: 37778498 DOI: 10.1016/j.exphem.2023.09.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2023] [Revised: 09/22/2023] [Accepted: 09/25/2023] [Indexed: 10/03/2023]
Affiliation(s)
- Nazanin Karimnia
- Biomedical Manufacturing, Commonwealth Scientific and Industrial Research Organisation, Clayton, Australia; Australian Regenerative Medicine Institute, Monash University, Clayton, Australia
| | - James Harris
- Biomedical Manufacturing, Commonwealth Scientific and Industrial Research Organisation, Clayton, Australia; Australian Regenerative Medicine Institute, Monash University, Clayton, Australia; School of Clinical Sciences, Monash Health, Faculty of Medicine, Nursing and Health Sciences, Monash University, Clayton, Australia
| | - Shen Y Heazlewood
- Biomedical Manufacturing, Commonwealth Scientific and Industrial Research Organisation, Clayton, Australia; Australian Regenerative Medicine Institute, Monash University, Clayton, Australia
| | - Benjamin Cao
- Biomedical Manufacturing, Commonwealth Scientific and Industrial Research Organisation, Clayton, Australia; Australian Regenerative Medicine Institute, Monash University, Clayton, Australia.
| | - Susan K Nilsson
- Biomedical Manufacturing, Commonwealth Scientific and Industrial Research Organisation, Clayton, Australia; Australian Regenerative Medicine Institute, Monash University, Clayton, Australia.
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21
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Morselli M, Bennett R, Shaidani NI, Horb M, Peshkin L, Pellegrini M. Age-associated DNA methylation changes in Xenopus frogs. Epigenetics 2023; 18:2201517. [PMID: 37092296 PMCID: PMC10128463 DOI: 10.1080/15592294.2023.2201517] [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: 09/03/2022] [Accepted: 04/06/2023] [Indexed: 04/25/2023] Open
Abstract
Age-associated changes in DNA methylation have been characterized across various animals, but not yet in amphibians, which are of particular interest because they include widely studied model organisms. In this study, we present clear evidence that the aquatic vertebrate species Xenopus tropicalis displays patterns of age-associated changes in DNA methylation. We have generated whole-genome bisulfite sequencing (WGBS) profiles from skin samples of nine frogs representing young, mature, and old adults and characterized the gene- and chromosome-scale DNA methylation changes with age. Many of the methylation features and changes we observe are consistent with what is known in mammalian species, suggesting that the mechanism of age-related changes is conserved. Moreover, we selected a few thousand age-associated CpG sites to build an assay based on targeted DNA methylation analysis (TBSseq) to expand our findings in future studies involving larger cohorts of individuals. Preliminary results of a pilot TBSeq experiment recapitulate the findings obtained with WGBS setting the basis for the development of an epigenetic clock assay. The results of this study will allow us to leverage the unique resources available for Xenopus to study how DNA methylation relates to other hallmarks of ageing.
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Affiliation(s)
- Marco Morselli
- Molecular, Cell & Developmental Biology, UCLA, Los Angeles, CA, USA
| | - Ronan Bennett
- Molecular, Cell & Developmental Biology, UCLA, Los Angeles, CA, USA
| | - Nikko-Ideen Shaidani
- Eugene Bell Center for Regenerative Biology and Tissue Engineering and National Xenopus Resource, Marine Biological Laboratory, Woods Hole, MA, USA
| | - Marko Horb
- Eugene Bell Center for Regenerative Biology and Tissue Engineering and National Xenopus Resource, Marine Biological Laboratory, Woods Hole, MA, USA
| | - Leonid Peshkin
- Eugene Bell Center for Regenerative Biology and Tissue Engineering and National Xenopus Resource, Marine Biological Laboratory, Woods Hole, MA, USA
- Systems Biology, Harvard Medical School, Boston, MA, USA
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22
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Lu YR, Tian X, Sinclair DA. The Information Theory of Aging. NATURE AGING 2023; 3:1486-1499. [PMID: 38102202 DOI: 10.1038/s43587-023-00527-6] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/28/2022] [Accepted: 10/02/2023] [Indexed: 12/17/2023]
Abstract
Information storage and retrieval is essential for all life. In biology, information is primarily stored in two distinct ways: the genome, comprising nucleic acids, acts as a foundational blueprint and the epigenome, consisting of chemical modifications to DNA and histone proteins, regulates gene expression patterns and endows cells with specific identities and functions. Unlike the stable, digital nature of genetic information, epigenetic information is stored in a digital-analog format, susceptible to alterations induced by diverse environmental signals and cellular damage. The Information Theory of Aging (ITOA) states that the aging process is driven by the progressive loss of youthful epigenetic information, the retrieval of which via epigenetic reprogramming can improve the function of damaged and aged tissues by catalyzing age reversal.
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Affiliation(s)
- Yuancheng Ryan Lu
- Paul F. Glenn Center for Biology of Aging Research, Department of Genetics, Blavatnik Institute, Harvard Medical School, Boston, MA, USA
- Whitehead Institute for Biomedical Research, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Xiao Tian
- Paul F. Glenn Center for Biology of Aging Research, Department of Genetics, Blavatnik Institute, Harvard Medical School, Boston, MA, USA
| | - David A Sinclair
- Paul F. Glenn Center for Biology of Aging Research, Department of Genetics, Blavatnik Institute, Harvard Medical School, Boston, MA, USA.
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23
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Fernandez ME, Martinez-Romero J, Aon MA, Bernier M, Price NL, de Cabo R. How is Big Data reshaping preclinical aging research? Lab Anim (NY) 2023; 52:289-314. [PMID: 38017182 DOI: 10.1038/s41684-023-01286-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2023] [Accepted: 10/10/2023] [Indexed: 11/30/2023]
Abstract
The exponential scientific and technological progress during the past 30 years has favored the comprehensive characterization of aging processes with their multivariate nature, leading to the advent of Big Data in preclinical aging research. Spanning from molecular omics to organism-level deep phenotyping, Big Data demands large computational resources for storage and analysis, as well as new analytical tools and conceptual frameworks to gain novel insights leading to discovery. Systems biology has emerged as a paradigm that utilizes Big Data to gain insightful information enabling a better understanding of living organisms, visualized as multilayered networks of interacting molecules, cells, tissues and organs at different spatiotemporal scales. In this framework, where aging, health and disease represent emergent states from an evolving dynamic complex system, context given by, for example, strain, sex and feeding times, becomes paramount for defining the biological trajectory of an organism. Using bioinformatics and artificial intelligence, the systems biology approach is leading to remarkable advances in our understanding of the underlying mechanism of aging biology and assisting in creative experimental study designs in animal models. Future in-depth knowledge acquisition will depend on the ability to fully integrate information from different spatiotemporal scales in organisms, which will probably require the adoption of theories and methods from the field of complex systems. Here we review state-of-the-art approaches in preclinical research, with a focus on rodent models, that are leading to conceptual and/or technical advances in leveraging Big Data to understand basic aging biology and its full translational potential.
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Affiliation(s)
- Maria Emilia Fernandez
- Experimental Gerontology Section, Translational Gerontology Branch, National Institute on Aging, National Institutes of Health, Baltimore, MD, USA
| | - Jorge Martinez-Romero
- Experimental Gerontology Section, Translational Gerontology Branch, National Institute on Aging, National Institutes of Health, Baltimore, MD, USA
- Laboratory of Epidemiology and Population Science, National Institute on Aging, National Institutes of Health, Baltimore, MD, USA
| | - Miguel A Aon
- Experimental Gerontology Section, Translational Gerontology Branch, National Institute on Aging, National Institutes of Health, Baltimore, MD, USA
- Laboratory of Cardiovascular Science, National Institute on Aging, National Institutes of Health, Baltimore, MD, USA
| | - Michel Bernier
- Experimental Gerontology Section, Translational Gerontology Branch, National Institute on Aging, National Institutes of Health, Baltimore, MD, USA
| | - Nathan L Price
- Experimental Gerontology Section, Translational Gerontology Branch, National Institute on Aging, National Institutes of Health, Baltimore, MD, USA
| | - Rafael de Cabo
- Experimental Gerontology Section, Translational Gerontology Branch, National Institute on Aging, National Institutes of Health, Baltimore, MD, USA.
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24
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Alvarez-Kuglen M, Rodriguez D, Qin H, Ninomiya K, Fiengo L, Farhy C, Hsu WM, Havas A, Feng GS, Roberts AJ, Anderson RM, Serrano M, Adams PD, Sharpee TO, Terskikh AV. Imaging-based chromatin and epigenetic age, ImAge, quantitates aging and rejuvenation. RESEARCH SQUARE 2023:rs.3.rs-3479973. [PMID: 37986947 PMCID: PMC10659560 DOI: 10.21203/rs.3.rs-3479973/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/22/2023]
Abstract
Biomarkers of biological age that predict the risk of disease and expected lifespan better than chronological age are key to efficient and cost-effective healthcare1-3. To advance a personalized approach to healthcare, such biomarkers must reliably and accurately capture individual biology, predict biological age, and provide scalable and cost-effective measurements. We developed a novel approach - image-based chromatin and epigenetic age (ImAge) that captures intrinsic progressions of biological age, which readily emerge as principal changes in the spatial organization of chromatin and epigenetic marks in single nuclei without regression on chronological age. ImAge captured the expected acceleration or deceleration of biological age in mice treated with chemotherapy or following a caloric restriction regimen, respectively. ImAge from chronologically identical mice inversely correlated with their locomotor activity (greater activity for younger ImAge), consistent with the widely accepted role of locomotion as an aging biomarker across species. Finally, we demonstrated that ImAge is reduced following transient expression of OSKM cassette in the liver and skeletal muscles and reveals heterogeneity of in vivo reprogramming. We propose that ImAge represents the first-in-class imaging-based biomarker of aging with single-cell resolution.
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Affiliation(s)
| | | | - Haodong Qin
- UCSD, Department of Physics, La Jolla, CA 92093, USA
| | | | | | - Chen Farhy
- Sanford Burnham Prebys, La Jolla CA 92037, USA
| | - Wei-Mien Hsu
- Salk Institute for Biological Studies, La Jolla, CA 92037, USA
| | - Aaron Havas
- Sanford Burnham Prebys, La Jolla CA 92037, USA
| | - Gen-Sheng Feng
- UCSD School of Medicine, 9500 Gilman Drive, La Jolla, CA 92093, USA
| | | | | | - Manuel Serrano
- Institute for Research in Biomedicine (IRB Barcelona), Barcelona 08028, Spain
- Barcelona Institute of Science and Technology (BIST), Barcelona 08028, Spain
- Altos Labs, Cambridge Institute of Science, Granta Park CB21 6GP, UK
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25
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Statsenko Y, Kuznetsov NV, Morozova D, Liaonchyk K, Simiyu GL, Smetanina D, Kashapov A, Meribout S, Gorkom KNV, Hamoudi R, Ismail F, Ansari SA, Emerald BS, Ljubisavljevic M. Reappraisal of the Concept of Accelerated Aging in Neurodegeneration and Beyond. Cells 2023; 12:2451. [PMID: 37887295 PMCID: PMC10605227 DOI: 10.3390/cells12202451] [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: 08/04/2023] [Revised: 09/01/2023] [Accepted: 09/06/2023] [Indexed: 10/28/2023] Open
Abstract
BACKGROUND Genetic and epigenetic changes, oxidative stress and inflammation influence the rate of aging, which diseases, lifestyle and environmental factors can further accelerate. In accelerated aging (AA), the biological age exceeds the chronological age. OBJECTIVE The objective of this study is to reappraise the AA concept critically, considering its weaknesses and limitations. METHODS We reviewed more than 300 recent articles dealing with the physiology of brain aging and neurodegeneration pathophysiology. RESULTS (1) Application of the AA concept to individual organs outside the brain is challenging as organs of different systems age at different rates. (2) There is a need to consider the deceleration of aging due to the potential use of the individual structure-functional reserves. The latter can be restored by pharmacological and/or cognitive therapy, environment, etc. (3) The AA concept lacks both standardised terminology and methodology. (4) Changes in specific molecular biomarkers (MBM) reflect aging-related processes; however, numerous MBM candidates should be validated to consolidate the AA theory. (5) The exact nature of many potential causal factors, biological outcomes and interactions between the former and the latter remain largely unclear. CONCLUSIONS Although AA is commonly recognised as a perspective theory, it still suffers from a number of gaps and limitations that assume the necessity for an updated AA concept.
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Affiliation(s)
- Yauhen Statsenko
- Department of Radiology, College of Medicine and Health Sciences, United Arab Emirates University, Al Ain P.O. Box 15551, United Arab Emirates; (Y.S.); (G.L.S.); (D.S.); (A.K.); (S.M.); (K.N.-V.G.)
- ASPIRE Precision Medicine Research Institute Abu Dhabi, United Arab Emirates University, Al Ain 27272, United Arab Emirates; (D.M.); (K.L.); (R.H.); (S.A.A.); (B.S.E.); (M.L.)
- Big Data Analytic Center, United Arab Emirates University, Al Ain P.O. Box 15551, United Arab Emirates
| | - Nik V. Kuznetsov
- ASPIRE Precision Medicine Research Institute Abu Dhabi, United Arab Emirates University, Al Ain 27272, United Arab Emirates; (D.M.); (K.L.); (R.H.); (S.A.A.); (B.S.E.); (M.L.)
| | - Daria Morozova
- ASPIRE Precision Medicine Research Institute Abu Dhabi, United Arab Emirates University, Al Ain 27272, United Arab Emirates; (D.M.); (K.L.); (R.H.); (S.A.A.); (B.S.E.); (M.L.)
| | - Katsiaryna Liaonchyk
- ASPIRE Precision Medicine Research Institute Abu Dhabi, United Arab Emirates University, Al Ain 27272, United Arab Emirates; (D.M.); (K.L.); (R.H.); (S.A.A.); (B.S.E.); (M.L.)
| | - Gillian Lylian Simiyu
- Department of Radiology, College of Medicine and Health Sciences, United Arab Emirates University, Al Ain P.O. Box 15551, United Arab Emirates; (Y.S.); (G.L.S.); (D.S.); (A.K.); (S.M.); (K.N.-V.G.)
| | - Darya Smetanina
- Department of Radiology, College of Medicine and Health Sciences, United Arab Emirates University, Al Ain P.O. Box 15551, United Arab Emirates; (Y.S.); (G.L.S.); (D.S.); (A.K.); (S.M.); (K.N.-V.G.)
| | - Aidar Kashapov
- Department of Radiology, College of Medicine and Health Sciences, United Arab Emirates University, Al Ain P.O. Box 15551, United Arab Emirates; (Y.S.); (G.L.S.); (D.S.); (A.K.); (S.M.); (K.N.-V.G.)
| | - Sarah Meribout
- Department of Radiology, College of Medicine and Health Sciences, United Arab Emirates University, Al Ain P.O. Box 15551, United Arab Emirates; (Y.S.); (G.L.S.); (D.S.); (A.K.); (S.M.); (K.N.-V.G.)
| | - Klaus Neidl-Van Gorkom
- Department of Radiology, College of Medicine and Health Sciences, United Arab Emirates University, Al Ain P.O. Box 15551, United Arab Emirates; (Y.S.); (G.L.S.); (D.S.); (A.K.); (S.M.); (K.N.-V.G.)
| | - Rifat Hamoudi
- ASPIRE Precision Medicine Research Institute Abu Dhabi, United Arab Emirates University, Al Ain 27272, United Arab Emirates; (D.M.); (K.L.); (R.H.); (S.A.A.); (B.S.E.); (M.L.)
- Department of Clinical Sciences, College of Medicine, University of Sharjah, Sharjah 27272, United Arab Emirates
- Division of Surgery and Interventional Science, University College London, London NW3 2PS, UK
| | - Fatima Ismail
- Department of Pediatrics, College of Medicine and Health Sciences, United Arab Emirates University, Al Ain P.O. Box 15551, United Arab Emirates;
| | - Suraiya Anjum Ansari
- ASPIRE Precision Medicine Research Institute Abu Dhabi, United Arab Emirates University, Al Ain 27272, United Arab Emirates; (D.M.); (K.L.); (R.H.); (S.A.A.); (B.S.E.); (M.L.)
- Department of Biochemistry and Molecular Biology, College of Medicine and Health Sciences, United Arab Emirates University, Al Ain P.O. Box 15551, United Arab Emirates
| | - Bright Starling Emerald
- ASPIRE Precision Medicine Research Institute Abu Dhabi, United Arab Emirates University, Al Ain 27272, United Arab Emirates; (D.M.); (K.L.); (R.H.); (S.A.A.); (B.S.E.); (M.L.)
- Department of Anatomy, College of Medicine and Health Sciences, United Arab Emirates University, Al Ain P.O. Box 15551, United Arab Emirates
| | - Milos Ljubisavljevic
- ASPIRE Precision Medicine Research Institute Abu Dhabi, United Arab Emirates University, Al Ain 27272, United Arab Emirates; (D.M.); (K.L.); (R.H.); (S.A.A.); (B.S.E.); (M.L.)
- Department of Physiology, College of Medicine and Health Sciences, United Arab Emirates University, Al Ain P.O. Box 15551, United Arab Emirates
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26
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Moqri M, Herzog C, Poganik JR, Justice J, Belsky DW, Higgins-Chen A, Moskalev A, Fuellen G, Cohen AA, Bautmans I, Widschwendter M, Ding J, Fleming A, Mannick J, Han JDJ, Zhavoronkov A, Barzilai N, Kaeberlein M, Cummings S, Kennedy BK, Ferrucci L, Horvath S, Verdin E, Maier AB, Snyder MP, Sebastiano V, Gladyshev VN. Biomarkers of aging for the identification and evaluation of longevity interventions. Cell 2023; 186:3758-3775. [PMID: 37657418 PMCID: PMC11088934 DOI: 10.1016/j.cell.2023.08.003] [Citation(s) in RCA: 91] [Impact Index Per Article: 91.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2023] [Revised: 08/01/2023] [Accepted: 08/02/2023] [Indexed: 09/03/2023]
Abstract
With the rapid expansion of aging biology research, the identification and evaluation of longevity interventions in humans have become key goals of this field. Biomarkers of aging are critically important tools in achieving these objectives over realistic time frames. However, the current lack of standards and consensus on the properties of a reliable aging biomarker hinders their further development and validation for clinical applications. Here, we advance a framework for the terminology and characterization of biomarkers of aging, including classification and potential clinical use cases. We discuss validation steps and highlight ongoing challenges as potential areas in need of future research. This framework sets the stage for the development of valid biomarkers of aging and their ultimate utilization in clinical trials and practice.
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Affiliation(s)
- Mahdi Moqri
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA; Department of Genetics, School of Medicine, Stanford University, Stanford, CA, USA; Department of Obstetrics and Gynecology, School of Medicine, Stanford University, Stanford, CA, USA
| | - Chiara Herzog
- European Translational Oncology Prevention and Screening Institute, Universität Innsbruck, Innsbruck, Austria
| | - Jesse R Poganik
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Jamie Justice
- Department of Internal Medicine, Section on Gerontology and Geriatric Medicine, Wake Forest University School of Medicine, Winston-Salem, NC, USA
| | - Daniel W Belsky
- Department of Epidemiology, Butler Columbia Aging Center, Mailman School of Public Health, Columbia University, New York, NY, USA
| | | | - Alexey Moskalev
- Institute of Biogerontology, Lobachevsky University, Nizhny Novgorod, Russia
| | - Georg Fuellen
- Institute for Biostatistics and Informatics in Medicine and Ageing Research, Rostock University Medical Center, Rostock, Germany; School of Medicine, University College Dublin, Dublin, Ireland
| | - Alan A Cohen
- Department of Environmental Health Sciences, Butler Columbia Aging Center, Mailman School of Public Health, Columbia University, New York, NY, USA
| | - Ivan Bautmans
- Gerontology Department, Vrije Universiteit Brussel, Brussels, Belgium; Frailty in Ageing Research Department, Vrije Universiteit Brussel, Brussels, Belgium
| | - Martin Widschwendter
- European Translational Oncology Prevention and Screening Institute, Universität Innsbruck, Innsbruck, Austria; Department of Women's Cancer, EGA Institute for Women's Health, University College London, London, UK; Department of Women's and Children's Health, Division of Obstetrics and Gynaecology, Karolinska Institutet, Stockholm, Sweden
| | - Jingzhong Ding
- Gerontology and Geriatric Medicine, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | | | | | - Jing-Dong Jackie Han
- Peking-Tsinghua Center for Life Sciences, Academy for Advanced Interdisciplinary Studies, Center for Quantitative Biology, Peking University, Beijing, China
| | - Alex Zhavoronkov
- Insilico Medicine Hong Kong, Pak Shek Kok, New Territories, Hong Kong SAR, China
| | - Nir Barzilai
- Institute for Aging Research, Albert Einstein College of Medicine, Bronx, NY, USA
| | - Matt Kaeberlein
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, WA, USA
| | - Steven Cummings
- San Francisco Coordinating Center, California Pacific Medical Center Research Institute, San Francisco, CA, USA; Department of Epidemiology and Biostatistics, University of California, San Francisco, San Francisco, CA, USA
| | - Brian K Kennedy
- Healthy Longevity Translational Research Programme, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | | | | | - Eric Verdin
- Buck Institute for Research on Aging, Novato, CA, USA
| | - Andrea B Maier
- Department of Human Movement Sciences, @AgeAmsterdam, Amsterdam Movement Sciences, Faculty of Behavioural and Movement Sciences, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands; Healthy Longevity Translational Research Program, Yong Loo Lin School of Medicine, National University of Singapore, Centre for Healthy Longevity, @AgeSingapore, National University Health System, Singapore, Singapore
| | - Michael P Snyder
- Department of Genetics, School of Medicine, Stanford University, Stanford, CA, USA.
| | - Vittorio Sebastiano
- Department of Obstetrics and Gynecology, School of Medicine, Stanford University, Stanford, CA, USA.
| | - Vadim N Gladyshev
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
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27
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Horvath S, Singh K, Raj K, Khairnar S, Sanghavi A, Shrivastava A, Zoller JA, Li CZ, Herenu CB, Canatelli-Mallat M, Lehmann M, Habazin S, Novokmet M, Vučković F, Woods LCS, Martinez AG, Wang T, Chiavellini P, Levine AJ, Chen H, Brooke RT, Gordevicius J, Lauc G, Goya RG, Katcher HL. Reversal of Biological Age in Multiple Rat Organs by Young Porcine Plasma Fraction. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.08.06.552148. [PMID: 37609328 PMCID: PMC10441355 DOI: 10.1101/2023.08.06.552148] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/24/2023]
Abstract
Young blood plasma is known to confer beneficial effects on various organs in mice and rats. However, it was not known whether plasma from young pigs rejuvenates old rat tissues at the epigenetic level; whether it alters the epigenetic clock, which is a highly accurate molecular biomarker of aging. To address this question, we developed and validated six different epigenetic clocks for rat tissues that are based on DNA methylation values derived from n=613 tissue samples. As indicated by their respective names, the rat pan-tissue clock can be applied to DNA methylation profiles from all rat tissues, while the rat brain-, liver-, and blood clocks apply to the corresponding tissue types. We also developed two epigenetic clocks that apply to both human and rat tissues by adding n=1366 human tissue samples to the training data. We employed these six rat clocks to investigate the rejuvenation effects of a porcine plasma fraction treatment in different rat tissues. The treatment more than halved the epigenetic ages of blood, heart, and liver tissue. A less pronounced, but statistically significant, rejuvenation effect could be observed in the hypothalamus. The treatment was accompanied by progressive improvement in the function of these organs as ascertained through numerous biochemical/physiological biomarkers and behavioral responses to assess cognitive functions. An immunoglobulin G (IgG) N-glycosylation pattern shift from pro- to anti-inflammatory also indicated reversal of glycan aging. Overall, this study demonstrates that a young porcine plasma-derived treatment markedly reverses aging in rats according to epigenetic clocks, IgG glycans, and other biomarkers of aging.
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Affiliation(s)
- Steve Horvath
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California, USA
- Department of Biostatistics, Fielding School of Public Health, University of California, Los Angeles, Los Angeles, California, USA
- Altos Labs, Cambridge, UK
| | - Kavita Singh
- Shobhaben Pratapbhai Patel School of Pharmacy and Technology Management, SVKM’S NMIMS University, Mumbai, India
| | | | - Shraddha Khairnar
- Shobhaben Pratapbhai Patel School of Pharmacy and Technology Management, SVKM’S NMIMS University, Mumbai, India
| | | | | | - Joseph A. Zoller
- Department of Biostatistics, Fielding School of Public Health, University of California, Los Angeles, Los Angeles, California, USA
| | - Caesar Z. Li
- Department of Biostatistics, Fielding School of Public Health, University of California, Los Angeles, Los Angeles, California, USA
| | - Claudia B. Herenu
- Institute for Experimental Pharmacology of Cordoba (IFEC), School of Chemical Sciences, National University of Cordoba, Cordoba, Argentina
| | - Martina Canatelli-Mallat
- Biochemistry Research Institute of La Plata – Histology B, Pathology B, School of Medicine, University of La Plata, La Plata CC 455 (zip 1900), Argentina
| | - Marianne Lehmann
- Biochemistry Research Institute of La Plata – Histology B, Pathology B, School of Medicine, University of La Plata, La Plata CC 455 (zip 1900), Argentina
| | | | | | | | - Leah C. Solberg Woods
- Wake Forest University School of Medicine, 1 Medical Center Drive, Winston Salem, NC 27157, USA
| | - Angel Garcia Martinez
- Department of Pharmacology, Addiction Science and Toxicology, The University of Tennessee Health Science Center, Memphis, TN 3993, USA
| | - Tengfei Wang
- Department of Pharmacology, Addiction Science and Toxicology, The University of Tennessee Health Science Center, Memphis, TN 3993, USA
| | - Priscila Chiavellini
- Biochemistry Research Institute of La Plata – Histology B, Pathology B, School of Medicine, University of La Plata, La Plata CC 455 (zip 1900), Argentina
| | - Andrew J. Levine
- Department of Neurology, David Geffen School of Medicine at the University of California, Los Angeles, CA, 90095, USA
| | - Hao Chen
- Department of Pharmacology, Addiction Science and Toxicology, The University of Tennessee Health Science Center, Memphis, TN 3993, USA
| | - Robert T Brooke
- Epigenetic Clock Development Foundation, Torrance, California, USA
| | | | - Gordan Lauc
- Genos Glycoscience Research Laboratory, Zagreb, Croatia
- Faculty of Pharmacy and Biochemistry, University of Zagreb, Zagreb, Croatia
| | - Rodolfo G. Goya
- Biochemistry Research Institute of La Plata – Histology B, Pathology B, School of Medicine, University of La Plata, La Plata CC 455 (zip 1900), Argentina
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28
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Simpson DJ, Zhao Q, Olova NN, Dabrowski J, Xie X, Latorre‐Crespo E, Chandra T. Region-based epigenetic clock design improves RRBS-based age prediction. Aging Cell 2023; 22:e13866. [PMID: 37170475 PMCID: PMC10410054 DOI: 10.1111/acel.13866] [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: 02/08/2023] [Revised: 04/20/2023] [Accepted: 04/21/2023] [Indexed: 05/13/2023] Open
Abstract
Recent studies suggest that epigenetic rejuvenation can be achieved using drugs that mimic calorie restriction and techniques such as reprogramming-induced rejuvenation. To effectively test rejuvenation in vivo, mouse models are the safest alternative. However, we have found that the recent epigenetic clocks developed for mouse reduced-representation bisulphite sequencing (RRBS) data have significantly poor performance when applied to external datasets. We show that the sites captured and the coverage of key CpGs required for age prediction vary greatly between datasets, which likely contributes to the lack of transferability in RRBS clocks. To mitigate these coverage issues in RRBS-based age prediction, we present two novel design strategies that use average methylation over large regions rather than individual CpGs, whereby regions are defined by sliding windows (e.g. 5 kb), or density-based clustering of CpGs. We observe improved correlation and error in our regional blood clocks (RegBCs) compared to published individual-CpG-based techniques when applied to external datasets. The RegBCs are also more robust when applied to low coverage data and detect a negative age acceleration in mice undergoing calorie restriction. Our RegBCs offer a proof of principle that age prediction of RRBS datasets can be improved by accounting for multiple CpGs over a region, which negates the lack of read depth currently hindering individual-CpG-based approaches.
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Affiliation(s)
- Daniel J. Simpson
- MRC Human Genetics Unit, MRC Institute of Genetics and CancerUniversity of EdinburghEdinburghUK
| | - Qian Zhao
- MRC Human Genetics Unit, MRC Institute of Genetics and CancerUniversity of EdinburghEdinburghUK
| | - Nelly N. Olova
- MRC Human Genetics Unit, MRC Institute of Genetics and CancerUniversity of EdinburghEdinburghUK
| | - Jan Dabrowski
- MRC Human Genetics Unit, MRC Institute of Genetics and CancerUniversity of EdinburghEdinburghUK
| | - Xiaoxiao Xie
- MRC Human Genetics Unit, MRC Institute of Genetics and CancerUniversity of EdinburghEdinburghUK
| | - Eric Latorre‐Crespo
- MRC Human Genetics Unit, MRC Institute of Genetics and CancerUniversity of EdinburghEdinburghUK
| | - Tamir Chandra
- MRC Human Genetics Unit, MRC Institute of Genetics and CancerUniversity of EdinburghEdinburghUK
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29
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Zhang B, Lee DE, Trapp A, Tyshkovskiy A, Lu AT, Bareja A, Kerepesi C, McKay LK, Shindyapina AV, Dmitriev SE, Baht GS, Horvath S, Gladyshev VN, White JP. Multi-omic rejuvenation and life span extension on exposure to youthful circulation. NATURE AGING 2023; 3:948-964. [PMID: 37500973 PMCID: PMC11095548 DOI: 10.1038/s43587-023-00451-9] [Citation(s) in RCA: 15] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/23/2021] [Accepted: 06/06/2023] [Indexed: 07/29/2023]
Abstract
Heterochronic parabiosis (HPB) is known for its functional rejuvenation effects across several mouse tissues. However, its impact on biological age and long-term health is unknown. Here we performed extended (3-month) HPB, followed by a 2-month detachment period of anastomosed pairs. Old detached mice exhibited improved physiological parameters and lived longer than control isochronic mice. HPB drastically reduced the epigenetic age of blood and liver based on several clock models using two independent platforms. Remarkably, this rejuvenation effect persisted even after 2 months of detachment. Transcriptomic and epigenomic profiles of anastomosed mice showed an intermediate phenotype between old and young, suggesting a global multi-omic rejuvenation effect. In addition, old HPB mice showed gene expression changes opposite to aging but akin to several life span-extending interventions. Altogether, we reveal that long-term HPB results in lasting epigenetic and transcriptome remodeling, culminating in the extension of life span and health span.
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Affiliation(s)
- Bohan Zhang
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - David E Lee
- Department of Medicine, Duke University School of Medicine, Durham, NC, USA
- Duke Molecular Physiology Institute, Duke University, Durham, NC, USA
| | - Alexandre Trapp
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Retro Biosciences, Redwood City, CA, USA
| | - Alexander Tyshkovskiy
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Belozersky Institute of Physico-Chemical Biology, Moscow State University, Moscow, Russia
| | - Ake T Lu
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, CA, USA
- Altos Labs, San Diego, CA, USA
| | - Akshay Bareja
- Department of Medicine, Duke University School of Medicine, Durham, NC, USA
- Duke Molecular Physiology Institute, Duke University, Durham, NC, USA
| | - Csaba Kerepesi
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Institute for Computer Science and Control (SZTAKI), Eötvös Loránd Research Network, Budapest, Hungary
| | - Lauren K McKay
- Duke Molecular Physiology Institute, Duke University, Durham, NC, USA
- Division of Oral and Craniofacial Health Sciences, Adams School of Dentistry, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Anastasia V Shindyapina
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Retro Biosciences, Redwood City, CA, USA
| | - Sergey E Dmitriev
- Belozersky Institute of Physico-Chemical Biology, Moscow State University, Moscow, Russia
| | - Gurpreet S Baht
- Duke Molecular Physiology Institute, Duke University, Durham, NC, USA
- Department of Orthopaedic Surgery, Duke University School of Medicine, Durham, NC, USA
- Duke Center for the Study of Aging and Human Development, Duke University School of Medicine, Durham, NC, USA
| | - Steve Horvath
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, CA, USA
- Department of Biostatistics, School of Public Health, University of California, Los Angeles, CA, USA
- Altos Labs, San Diego, CA, USA
| | - Vadim N Gladyshev
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
| | - James P White
- Department of Medicine, Duke University School of Medicine, Durham, NC, USA.
- Duke Molecular Physiology Institute, Duke University, Durham, NC, USA.
- Duke Center for the Study of Aging and Human Development, Duke University School of Medicine, Durham, NC, USA.
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30
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Ogrodnik M, Gladyshev VN. The meaning of adaptation in aging: insights from cellular senescence, epigenetic clocks and stem cell alterations. NATURE AGING 2023; 3:766-775. [PMID: 37386259 PMCID: PMC7616215 DOI: 10.1038/s43587-023-00447-5] [Citation(s) in RCA: 14] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/28/2022] [Accepted: 05/30/2023] [Indexed: 07/01/2023]
Abstract
With recent rapid progress in research on aging, there is increasing evidence that many features commonly considered to be mechanisms or drivers of aging in fact represent adaptations. Here, we examine several such features, including cellular senescence, epigenetic aging and stem cell alterations. We draw a distinction between the causes and consequences of aging and define short-term consequences as 'responses' and long-term ones as 'adaptations'. We also discuss 'damaging adaptations', which despite having beneficial effects in the short term, lead to exacerbation of the initial insult and acceleration of aging. Features commonly recognized as 'basic mechanisms of the aging process' are critically examined for the possibility of their adaptation-driven emergence from processes such as cell competition and the wound-like features of the aging body. Finally, we speculate on the meaning of these interactions for the aging process and their relevance for the development of antiaging interventions.
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Affiliation(s)
- Mikolaj Ogrodnik
- Ludwig Boltzmann Research Group Senescence and Healing of Wounds, Vienna, Austria.
- Ludwig Boltzmann Institute for Experimental and Clinical Traumatology, Austrian Workers' Compensation Board Research Center, Vienna, Austria.
- Austrian Cluster for Tissue Regeneration, Vienna, Austria.
| | - Vadim N Gladyshev
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA.
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31
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Ruden DM, Singh A, Rappolee DA. Pathological epigenetic events and reversibility review: the intersection between hallmarks of aging and developmental origin of health and disease. Epigenomics 2023; 15:741-754. [PMID: 37667910 PMCID: PMC10503466 DOI: 10.2217/epi-2023-0224] [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: 06/21/2023] [Accepted: 08/07/2023] [Indexed: 09/06/2023] Open
Abstract
We discuss pathological epigenetic events that are reversible (PEERs). A recent study by Poganik and colleagues showed that severe stress in mice and humans transiently elevates biological age of several tissues, and this transient age increase is reversible when the stress is removed. These studies suggest new strategies for reversing normal aging. However, it is important to note that developmental origin of health and disease studies have shown that developmental exposure to toxic chemicals such as lead causes permanent changes in neuron shape, connectivity and cellular hyperplasia of organs such as the heart and liver. In this review, the PEER hypothesis speculates that the hallmarks of aging and the hallmarks of developmental origin of health and disease intersect at PEERs.
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Affiliation(s)
- Douglas M Ruden
- CS Mott Center for Human Health and Development, Wayne State University, Detroit, MI 48201, USA
- Department of Obstetrics and Gynecology, Wayne State University, Detroit, MI 48201, USA
- Institute of Environmental Health Sciences, Wayne State University, Detroit, MI 48201, USA
| | - Aditi Singh
- Center for Molecular Medicine and Genetics, Wayne State University, Detroit, MI 48201, USA
| | - Daniel A Rappolee
- CS Mott Center for Human Health and Development, Wayne State University, Detroit, MI 48201, USA
- Department of Obstetrics and Gynecology, Wayne State University, Detroit, MI 48201, USA
- Department of Physiology, Wayne State University, Detroit, MI 48201, USA
- Reproductive Stress, Grosse Pointe Farms, MI 48236, USA
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32
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Tyshkovskiy A, Ma S, Shindyapina AV, Tikhonov S, Lee SG, Bozaykut P, Castro JP, Seluanov A, Schork NJ, Gorbunova V, Dmitriev SE, Miller RA, Gladyshev VN. Distinct longevity mechanisms across and within species and their association with aging. Cell 2023; 186:2929-2949.e20. [PMID: 37269831 PMCID: PMC11192172 DOI: 10.1016/j.cell.2023.05.002] [Citation(s) in RCA: 26] [Impact Index Per Article: 26.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2021] [Revised: 12/29/2022] [Accepted: 05/02/2023] [Indexed: 06/05/2023]
Abstract
Lifespan varies within and across species, but the general principles of its control remain unclear. Here, we conducted multi-tissue RNA-seq analyses across 41 mammalian species, identifying longevity signatures and examining their relationship with transcriptomic biomarkers of aging and established lifespan-extending interventions. An integrative analysis uncovered shared longevity mechanisms within and across species, including downregulated Igf1 and upregulated mitochondrial translation genes, and unique features, such as distinct regulation of the innate immune response and cellular respiration. Signatures of long-lived species were positively correlated with age-related changes and enriched for evolutionarily ancient essential genes, involved in proteolysis and PI3K-Akt signaling. Conversely, lifespan-extending interventions counteracted aging patterns and affected younger, mutable genes enriched for energy metabolism. The identified biomarkers revealed longevity interventions, including KU0063794, which extended mouse lifespan and healthspan. Overall, this study uncovers universal and distinct strategies of lifespan regulation within and across species and provides tools for discovering longevity interventions.
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Affiliation(s)
- Alexander Tyshkovskiy
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115, USA; Belozersky Institute of Physico-Chemical Biology, Moscow State University, Moscow 119234, Russia
| | - Siming Ma
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115, USA
| | - Anastasia V Shindyapina
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115, USA
| | - Stanislav Tikhonov
- Belozersky Institute of Physico-Chemical Biology, Moscow State University, Moscow 119234, Russia
| | - Sang-Goo Lee
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115, USA
| | - Perinur Bozaykut
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115, USA; Department of Molecular Biology and Genetics, Faculty of Engineering and Natural Sciences, Acibadem Mehmet Ali Aydinlar University, Istanbul 34752, Turkey
| | - José P Castro
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115, USA; i3S, Instituto de Investigação e Inovação em Saúde, Universidade do Porto, 4200-135 Porto, Portugal; Aging and Aneuploidy Laboratory, IBMC, Instituto de Biologia Molecular e Celular, Universidade do Porto, 4200-135 Porto, Portugal
| | - Andrei Seluanov
- Departments of Biology and Medicine, University of Rochester, Rochester, NY, USA
| | - Nicholas J Schork
- Quantitative Medicine and Systems Biology Division, Translational Genomics Research Institute, Phoenix, AZ, USA
| | - Vera Gorbunova
- Departments of Biology and Medicine, University of Rochester, Rochester, NY, USA
| | - Sergey E Dmitriev
- Belozersky Institute of Physico-Chemical Biology, Moscow State University, Moscow 119234, Russia
| | - Richard A Miller
- Department of Pathology and Geriatrics Center, University of Michigan, Ann Arbor, MI 48109, USA
| | - Vadim N Gladyshev
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115, USA; Broad Institute, Cambridge, MA, USA.
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33
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Poganik JR, Zhang B, Baht GS, Tyshkovskiy A, Deik A, Kerepesi C, Yim SH, Lu AT, Haghani A, Gong T, Hedman AM, Andolf E, Pershagen G, Almqvist C, Clish CB, Horvath S, White JP, Gladyshev VN. Biological age is increased by stress and restored upon recovery. Cell Metab 2023; 35:807-820.e5. [PMID: 37086720 PMCID: PMC11055493 DOI: 10.1016/j.cmet.2023.03.015] [Citation(s) in RCA: 67] [Impact Index Per Article: 67.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/07/2022] [Revised: 12/22/2022] [Accepted: 03/20/2023] [Indexed: 04/24/2023]
Abstract
Aging is classically conceptualized as an ever-increasing trajectory of damage accumulation and loss of function, leading to increases in morbidity and mortality. However, recent in vitro studies have raised the possibility of age reversal. Here, we report that biological age is fluid and exhibits rapid changes in both directions. At epigenetic, transcriptomic, and metabolomic levels, we find that the biological age of young mice is increased by heterochronic parabiosis and restored following surgical detachment. We also identify transient changes in biological age during major surgery, pregnancy, and severe COVID-19 in humans and/or mice. Together, these data show that biological age undergoes a rapid increase in response to diverse forms of stress, which is reversed following recovery from stress. Our study uncovers a new layer of aging dynamics that should be considered in future studies. The elevation of biological age by stress may be a quantifiable and actionable target for future interventions.
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Affiliation(s)
- Jesse R Poganik
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115, USA
| | - Bohan Zhang
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115, USA
| | - Gurpreet S Baht
- Department of Orthopaedic Surgery, Duke University, Durham, NC 27701, USA; Duke Molecular Physiology Institute, Duke University, Durham, NC 27701, USA
| | - Alexander Tyshkovskiy
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115, USA
| | - Amy Deik
- Broad Institute of MIT and Harvard, Cambridge, MA 01241, USA
| | - Csaba Kerepesi
- Institute for Computer Science and Control (SZTAKI), Eötvös Loránd Research Network, Budapest, 1111, Hungary
| | - Sun Hee Yim
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115, USA
| | - Ake T Lu
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA; Altos Labs, San Diego, CA, USA
| | - Amin Haghani
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA; Altos Labs, San Diego, CA, USA
| | - Tong Gong
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Anna M Hedman
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Ellika Andolf
- Department of Clinical Sciences, Division of Obstetrics and Gynaecology, Danderyd Hospital, Karolinska Institutet, Stockholm, Sweden
| | - Göran Pershagen
- Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden; Centre for Occupational and Environmental Medicine, Region Stockholm, Stockholm, Sweden
| | - Catarina Almqvist
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden; Astrid Lindgren Children's Hospital, Karolinska University Hospital, Stockholm, Sweden
| | - Clary B Clish
- Broad Institute of MIT and Harvard, Cambridge, MA 01241, USA
| | - Steve Horvath
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA; Altos Labs, San Diego, CA, USA; Department of Biostatistics, School of Public Health, University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - James P White
- Duke Molecular Physiology Institute, Duke University, Durham, NC 27701, USA; Department of Medicine, Duke University School of Medicine, Durham, NC 27701, USA.
| | - Vadim N Gladyshev
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115, USA; Broad Institute of MIT and Harvard, Cambridge, MA 01241, USA.
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34
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Bao H, Cao J, Chen M, Chen M, Chen W, Chen X, Chen Y, Chen Y, Chen Y, Chen Z, Chhetri JK, Ding Y, Feng J, Guo J, Guo M, He C, Jia Y, Jiang H, Jing Y, Li D, Li J, Li J, Liang Q, Liang R, Liu F, Liu X, Liu Z, Luo OJ, Lv J, Ma J, Mao K, Nie J, Qiao X, Sun X, Tang X, Wang J, Wang Q, Wang S, Wang X, Wang Y, Wang Y, Wu R, Xia K, Xiao FH, Xu L, Xu Y, Yan H, Yang L, Yang R, Yang Y, Ying Y, Zhang L, Zhang W, Zhang W, Zhang X, Zhang Z, Zhou M, Zhou R, Zhu Q, Zhu Z, Cao F, Cao Z, Chan P, Chen C, Chen G, Chen HZ, Chen J, Ci W, Ding BS, Ding Q, Gao F, Han JDJ, Huang K, Ju Z, Kong QP, Li J, Li J, Li X, Liu B, Liu F, Liu L, Liu Q, Liu Q, Liu X, Liu Y, Luo X, Ma S, Ma X, Mao Z, Nie J, Peng Y, Qu J, Ren J, Ren R, Song M, Songyang Z, Sun YE, Sun Y, Tian M, Wang S, Wang S, Wang X, Wang X, Wang YJ, Wang Y, Wong CCL, Xiang AP, Xiao Y, Xie Z, Xu D, Ye J, Yue R, Zhang C, Zhang H, Zhang L, Zhang W, Zhang Y, Zhang YW, Zhang Z, Zhao T, Zhao Y, Zhu D, Zou W, Pei G, Liu GH. Biomarkers of aging. SCIENCE CHINA. LIFE SCIENCES 2023; 66:893-1066. [PMID: 37076725 PMCID: PMC10115486 DOI: 10.1007/s11427-023-2305-0] [Citation(s) in RCA: 90] [Impact Index Per Article: 90.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/19/2023] [Accepted: 02/27/2023] [Indexed: 04/21/2023]
Abstract
Aging biomarkers are a combination of biological parameters to (i) assess age-related changes, (ii) track the physiological aging process, and (iii) predict the transition into a pathological status. Although a broad spectrum of aging biomarkers has been developed, their potential uses and limitations remain poorly characterized. An immediate goal of biomarkers is to help us answer the following three fundamental questions in aging research: How old are we? Why do we get old? And how can we age slower? This review aims to address this need. Here, we summarize our current knowledge of biomarkers developed for cellular, organ, and organismal levels of aging, comprising six pillars: physiological characteristics, medical imaging, histological features, cellular alterations, molecular changes, and secretory factors. To fulfill all these requisites, we propose that aging biomarkers should qualify for being specific, systemic, and clinically relevant.
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Affiliation(s)
- Hainan Bao
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing, 100101, China
| | - Jiani Cao
- State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China
| | - Mengting Chen
- Department of Dermatology, Xiangya Hospital, Central South University, Changsha, 410008, China
- Hunan Key Laboratory of Aging Biology, Xiangya Hospital, Central South University, Changsha, 410008, China
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, 410008, China
| | - Min Chen
- Clinic Center of Human Gene Research, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China
- Hubei Clinical Research Center of Metabolic and Cardiovascular Disease, Huazhong University of Science and Technology, Wuhan, 430022, China
- Hubei Key Laboratory of Metabolic Abnormalities and Vascular Aging, Huazhong University of Science and Technology, Wuhan, 430022, China
| | - Wei Chen
- Stem Cell Translational Research Center, Tongji Hospital, Tongji University School of Medicine, Shanghai, 200065, China
| | - Xiao Chen
- Department of Nuclear Medicine, Daping Hospital, Third Military Medical University, Chongqing, 400042, China
| | - Yanhao Chen
- CAS Key Laboratory of Nutrition, Metabolism and Food Safety, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, 200031, China
| | - Yu Chen
- Shanghai Key Laboratory of Maternal Fetal Medicine, Clinical and Translational Research Center of Shanghai First Maternity and Infant Hospital, Frontier Science Center for Stem Cell Research, Shanghai Key Laboratory of Signaling and Disease Research, School of Life Sciences and Technology, Tongji University, Shanghai, 200092, China
| | - Yutian Chen
- The Department of Endovascular Surgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, China
| | - Zhiyang Chen
- Key Laboratory of Regenerative Medicine of Ministry of Education, Institute of Ageing and Regenerative Medicine, Jinan University, Guangzhou, 510632, China
| | - Jagadish K Chhetri
- National Clinical Research Center for Geriatric Diseases, Xuanwu Hospital, Capital Medical University, Beijing, 100053, China
| | - Yingjie Ding
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing, 100101, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Junlin Feng
- CAS Key Laboratory of Tissue Microenvironment and Tumor, Shanghai Institute of Nutrition and Health, Chinese Academy of Sciences, Shanghai, 200031, China
| | - Jun Guo
- The Key Laboratory of Geriatrics, Beijing Institute of Geriatrics, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing Hospital/National Center of Gerontology of National Health Commission, Beijing, 100730, China
| | - Mengmeng Guo
- School of Pharmaceutical Sciences, Tsinghua University, Beijing, 100084, China
| | - Chuting He
- University of Chinese Academy of Sciences, Beijing, 100049, China
- State Key Laboratory of Membrane Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing, 100101, China
| | - Yujuan Jia
- Department of Neurology, First Affiliated Hospital, Shanxi Medical University, Taiyuan, 030001, China
| | - Haiping Jiang
- State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing, 100101, China
| | - Ying Jing
- Beijing Municipal Geriatric Medical Research Center, Xuanwu Hospital, Capital Medical University, Beijing, 100053, China
- Aging Translational Medicine Center, International Center for Aging and Cancer, Xuanwu Hospital, Capital Medical University, Beijing, 100053, China
- Advanced Innovation Center for Human Brain Protection, and National Clinical Research Center for Geriatric Disorders, Xuanwu Hospital Capital Medical University, Beijing, 100053, China
| | - Dingfeng Li
- Department of Neurology, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, 230036, China
| | - Jiaming Li
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing, 100101, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Jingyi Li
- University of Chinese Academy of Sciences, Beijing, 100049, China
- State Key Laboratory of Membrane Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing, 100101, China
| | - Qinhao Liang
- College of Life Sciences, TaiKang Center for Life and Medical Sciences, Wuhan University, Wuhan, 430072, China
| | - Rui Liang
- Research Institute of Transplant Medicine, Organ Transplant Center, NHC Key Laboratory for Critical Care Medicine, Tianjin First Central Hospital, Nankai University, Tianjin, 300384, China
| | - Feng Liu
- MOE Key Laboratory of Gene Function and Regulation, Guangzhou Key Laboratory of Healthy Aging Research, School of Life Sciences, Institute of Healthy Aging Research, Sun Yat-sen University, Guangzhou, 510275, China
| | - Xiaoqian Liu
- State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing, 100101, China
| | - Zuojun Liu
- School of Life Sciences, Hainan University, Haikou, 570228, China
| | - Oscar Junhong Luo
- Department of Systems Biomedical Sciences, School of Medicine, Jinan University, Guangzhou, 510632, China
| | - Jianwei Lv
- School of Life Sciences, Xiamen University, Xiamen, 361102, China
| | - Jingyi Ma
- The State Key Laboratory of Organ Failure Research, National Clinical Research Center of Kidney Disease, Division of Nephrology, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, China
| | - Kehang Mao
- Peking-Tsinghua Center for Life Sciences, Academy for Advanced Interdisciplinary Studies, Center for Quantitative Biology (CQB), Peking University, Beijing, 100871, China
| | - Jiawei Nie
- Shanghai Institute of Hematology, State Key Laboratory for Medical Genomics, National Research Center for Translational Medicine (Shanghai), International Center for Aging and Cancer, Collaborative Innovation Center of Hematology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
| | - Xinhua Qiao
- National Laboratory of Biomacromolecules, CAS Center for Excellence in Biomacromolecules, Institute of Biophysics, Chinese Academy of Sciences, Beijing, 100101, China
| | - Xinpei Sun
- Peking University International Cancer Institute, Health Science Center, Peking University, Beijing, 100101, China
| | - Xiaoqiang Tang
- Key Laboratory of Birth Defects and Related Diseases of Women and Children of MOE, State Key Laboratory of Biotherapy, West China Second University Hospital, Sichuan University, Chengdu, 610041, China
| | - Jianfang Wang
- Institute for Regenerative Medicine, Shanghai East Hospital, Frontier Science Center for Stem Cell Research, Shanghai Key Laboratory of Signaling and Disease Research, School of Life Sciences and Technology, Tongji University, Shanghai, 200092, China
| | - Qiaoran Wang
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing, 100101, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Siyuan Wang
- Clinical Research Institute, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Science & Peking Union Medical College, Beijing, 100730, China
| | - Xuan Wang
- Hepatobiliary and Pancreatic Center, Medical Research Center, Beijing Tsinghua Changgung Hospital, Beijing, 102218, China
| | - Yaning Wang
- Key Laboratory for Stem Cells and Tissue Engineering, Ministry of Education, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, 510080, China
- Advanced Medical Technology Center, The First Affiliated Hospital, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, 510080, China
| | - Yuhan Wang
- University of Chinese Academy of Sciences, Beijing, 100049, China
- State Key Laboratory of Membrane Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing, 100101, China
| | - Rimo Wu
- Bioland Laboratory (Guangzhou Regenerative Medicine and Health Guangdong Laboratory), Guangzhou, 510005, China
| | - Kai Xia
- Center for Stem Cell Biologyand Tissue Engineering, Key Laboratory for Stem Cells and Tissue Engineering, Ministry of Education, Sun Yat-sen University, Guangzhou, 510080, China
- National-Local Joint Engineering Research Center for Stem Cells and Regenerative Medicine, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, 510080, China
| | - Fu-Hui Xiao
- CAS Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming, 650223, China
- State Key Laboratory of Genetic Resources and Evolution, Key Laboratory of Healthy Aging Research of Yunnan Province, Kunming Key Laboratory of Healthy Aging Study, KIZ/CUHK Joint Laboratory of Bioresources and Molecular Research in Common Diseases, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650223, China
| | - Lingyan Xu
- Shanghai Key Laboratory of Regulatory Biology, Institute of Biomedical Sciences and School of Life Sciences, East China Normal University, Shanghai, 200241, China
| | - Yingying Xu
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing, 100101, China
| | - Haoteng Yan
- Beijing Municipal Geriatric Medical Research Center, Xuanwu Hospital, Capital Medical University, Beijing, 100053, China
- Aging Translational Medicine Center, International Center for Aging and Cancer, Xuanwu Hospital, Capital Medical University, Beijing, 100053, China
- Advanced Innovation Center for Human Brain Protection, and National Clinical Research Center for Geriatric Disorders, Xuanwu Hospital Capital Medical University, Beijing, 100053, China
| | - Liang Yang
- CAS Key Laboratory of Regenerative Biology, Joint School of Life Sciences, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou Medical University, Guangzhou, 510530, China
| | - Ruici Yang
- State Key Laboratory of Cell Biology, Shanghai Institute of Biochemistry and Cell Biology, Center for Excellence in Molecular Cell Science, Chinese Academy of Sciences, University of Chinese Academy of Sciences, Shanghai, 200031, China
| | - Yuanxin Yang
- Interdisciplinary Research Center on Biology and Chemistry, Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences, Shanghai, 201210, China
| | - Yilin Ying
- Department of Geriatrics, Medical Center on Aging of Shanghai Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
- International Laboratory in Hematology and Cancer, Shanghai Jiao Tong University School of Medicine/Ruijin Hospital, Shanghai, 200025, China
| | - Le Zhang
- Gerontology Center of Hubei Province, Wuhan, 430000, China
- Institute of Gerontology, Department of Geriatrics, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China
| | - Weiwei Zhang
- Department of Cardiology, The Second Medical Centre, Chinese PLA General Hospital, National Clinical Research Center for Geriatric Diseases, Beijing, 100853, China
| | - Wenwan Zhang
- CAS Key Laboratory of Tissue Microenvironment and Tumor, Shanghai Institute of Nutrition and Health, Chinese Academy of Sciences, Shanghai, 200031, China
| | - Xing Zhang
- Key Laboratory of Ministry of Education, School of Aerospace Medicine, Fourth Military Medical University, Xi'an, 710032, China
| | - Zhuo Zhang
- Optogenetics & Synthetic Biology Interdisciplinary Research Center, State Key Laboratory of Bioreactor Engineering, Shanghai Frontiers Science Center of Optogenetic Techniques for Cell Metabolism, School of Pharmacy, East China University of Science and Technology, Shanghai, 200237, China
- Research Unit of New Techniques for Live-cell Metabolic Imaging, Chinese Academy of Medical Sciences, Beijing, 100730, China
| | - Min Zhou
- Department of Endocrinology, Endocrinology Research Center, Xiangya Hospital of Central South University, Changsha, 410008, China
| | - Rui Zhou
- Department of Nuclear Medicine and PET Center, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, 310009, China
| | - Qingchen Zhu
- CAS Key Laboratory of Tissue Microenvironment and Tumor, Shanghai Institute of Nutrition and Health, Chinese Academy of Sciences, Shanghai, 200031, China
| | - Zhengmao Zhu
- Department of Genetics and Cell Biology, College of Life Science, Nankai University, Tianjin, 300071, China
- Haihe Laboratory of Cell Ecosystem, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin, 300020, China
| | - Feng Cao
- Department of Cardiology, The Second Medical Centre, Chinese PLA General Hospital, National Clinical Research Center for Geriatric Diseases, Beijing, 100853, China.
| | - Zhongwei Cao
- State Key Laboratory of Biotherapy, West China Second University Hospital, Sichuan University, Chengdu, 610041, China.
| | - Piu Chan
- National Clinical Research Center for Geriatric Diseases, Xuanwu Hospital, Capital Medical University, Beijing, 100053, China.
| | - Chang Chen
- National Laboratory of Biomacromolecules, CAS Center for Excellence in Biomacromolecules, Institute of Biophysics, Chinese Academy of Sciences, Beijing, 100101, China.
| | - Guobing Chen
- Department of Microbiology and Immunology, School of Medicine, Jinan University, Guangzhou, 510632, China.
- Guangdong-Hong Kong-Macau Great Bay Area Geroscience Joint Laboratory, Guangzhou, 510000, China.
| | - Hou-Zao Chen
- Department of Biochemistryand Molecular Biology, State Key Laboratory of Medical Molecular Biology, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100005, China.
| | - Jun Chen
- Peking University Research Center on Aging, Beijing Key Laboratory of Protein Posttranslational Modifications and Cell Function, Department of Biochemistry and Molecular Biology, Department of Integration of Chinese and Western Medicine, School of Basic Medical Science, Peking University, Beijing, 100191, China.
| | - Weimin Ci
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing, 100101, China.
| | - Bi-Sen Ding
- State Key Laboratory of Biotherapy, West China Second University Hospital, Sichuan University, Chengdu, 610041, China.
| | - Qiurong Ding
- CAS Key Laboratory of Nutrition, Metabolism and Food Safety, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, 200031, China.
| | - Feng Gao
- Key Laboratory of Ministry of Education, School of Aerospace Medicine, Fourth Military Medical University, Xi'an, 710032, China.
| | - Jing-Dong J Han
- Peking-Tsinghua Center for Life Sciences, Academy for Advanced Interdisciplinary Studies, Center for Quantitative Biology (CQB), Peking University, Beijing, 100871, China.
| | - Kai Huang
- Clinic Center of Human Gene Research, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China.
- Hubei Clinical Research Center of Metabolic and Cardiovascular Disease, Huazhong University of Science and Technology, Wuhan, 430022, China.
- Hubei Key Laboratory of Metabolic Abnormalities and Vascular Aging, Huazhong University of Science and Technology, Wuhan, 430022, China.
- Department of Cardiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China.
| | - Zhenyu Ju
- Key Laboratory of Regenerative Medicine of Ministry of Education, Institute of Ageing and Regenerative Medicine, Jinan University, Guangzhou, 510632, China.
| | - Qing-Peng Kong
- CAS Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming, 650223, China.
- State Key Laboratory of Genetic Resources and Evolution, Key Laboratory of Healthy Aging Research of Yunnan Province, Kunming Key Laboratory of Healthy Aging Study, KIZ/CUHK Joint Laboratory of Bioresources and Molecular Research in Common Diseases, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650223, China.
| | - Ji Li
- Department of Dermatology, Xiangya Hospital, Central South University, Changsha, 410008, China.
- Hunan Key Laboratory of Aging Biology, Xiangya Hospital, Central South University, Changsha, 410008, China.
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, 410008, China.
| | - Jian Li
- The Key Laboratory of Geriatrics, Beijing Institute of Geriatrics, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing Hospital/National Center of Gerontology of National Health Commission, Beijing, 100730, China.
| | - Xin Li
- State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China.
- University of Chinese Academy of Sciences, Beijing, 100049, China.
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China.
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing, 100101, China.
| | - Baohua Liu
- School of Basic Medical Sciences, Shenzhen University Medical School, Shenzhen, 518060, China.
| | - Feng Liu
- Metabolic Syndrome Research Center, The Second Xiangya Hospital, Central South Unversity, Changsha, 410011, China.
| | - Lin Liu
- Department of Genetics and Cell Biology, College of Life Science, Nankai University, Tianjin, 300071, China.
- Haihe Laboratory of Cell Ecosystem, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin, 300020, China.
- Institute of Translational Medicine, Tianjin Union Medical Center, Nankai University, Tianjin, 300000, China.
- State Key Laboratory of Medicinal Chemical Biology, Nankai University, Tianjin, 300350, China.
| | - Qiang Liu
- Department of Neurology, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, 230036, China.
| | - Qiang Liu
- Department of Neurology, Tianjin Neurological Institute, Tianjin Medical University General Hospital, Tianjin, 300052, China.
- Tianjin Institute of Immunology, Tianjin Medical University, Tianjin, 300070, China.
| | - Xingguo Liu
- CAS Key Laboratory of Regenerative Biology, Joint School of Life Sciences, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou Medical University, Guangzhou, 510530, China.
| | - Yong Liu
- College of Life Sciences, TaiKang Center for Life and Medical Sciences, Wuhan University, Wuhan, 430072, China.
| | - Xianghang Luo
- Department of Endocrinology, Endocrinology Research Center, Xiangya Hospital of Central South University, Changsha, 410008, China.
| | - Shuai Ma
- University of Chinese Academy of Sciences, Beijing, 100049, China.
- State Key Laboratory of Membrane Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China.
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China.
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing, 100101, China.
| | - Xinran Ma
- Shanghai Key Laboratory of Regulatory Biology, Institute of Biomedical Sciences and School of Life Sciences, East China Normal University, Shanghai, 200241, China.
| | - Zhiyong Mao
- Shanghai Key Laboratory of Maternal Fetal Medicine, Clinical and Translational Research Center of Shanghai First Maternity and Infant Hospital, Frontier Science Center for Stem Cell Research, Shanghai Key Laboratory of Signaling and Disease Research, School of Life Sciences and Technology, Tongji University, Shanghai, 200092, China.
| | - Jing Nie
- The State Key Laboratory of Organ Failure Research, National Clinical Research Center of Kidney Disease, Division of Nephrology, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, China.
| | - Yaojin Peng
- State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China.
- University of Chinese Academy of Sciences, Beijing, 100049, China.
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing, 100101, China.
| | - Jing Qu
- State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China.
- University of Chinese Academy of Sciences, Beijing, 100049, China.
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China.
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing, 100101, China.
| | - Jie Ren
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing, 100101, China.
- University of Chinese Academy of Sciences, Beijing, 100049, China.
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China.
| | - Ruibao Ren
- Shanghai Institute of Hematology, State Key Laboratory for Medical Genomics, National Research Center for Translational Medicine (Shanghai), International Center for Aging and Cancer, Collaborative Innovation Center of Hematology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China.
- International Center for Aging and Cancer, Hainan Medical University, Haikou, 571199, China.
| | - Moshi Song
- University of Chinese Academy of Sciences, Beijing, 100049, China.
- State Key Laboratory of Membrane Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China.
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China.
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing, 100101, China.
| | - Zhou Songyang
- MOE Key Laboratory of Gene Function and Regulation, Guangzhou Key Laboratory of Healthy Aging Research, School of Life Sciences, Institute of Healthy Aging Research, Sun Yat-sen University, Guangzhou, 510275, China.
- Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, 510120, China.
| | - Yi Eve Sun
- Stem Cell Translational Research Center, Tongji Hospital, Tongji University School of Medicine, Shanghai, 200065, China.
| | - Yu Sun
- CAS Key Laboratory of Tissue Microenvironment and Tumor, Shanghai Institute of Nutrition and Health, Chinese Academy of Sciences, Shanghai, 200031, China.
- Department of Medicine and VAPSHCS, University of Washington, Seattle, WA, 98195, USA.
| | - Mei Tian
- Human Phenome Institute, Fudan University, Shanghai, 201203, China.
| | - Shusen Wang
- Research Institute of Transplant Medicine, Organ Transplant Center, NHC Key Laboratory for Critical Care Medicine, Tianjin First Central Hospital, Nankai University, Tianjin, 300384, China.
| | - Si Wang
- Beijing Municipal Geriatric Medical Research Center, Xuanwu Hospital, Capital Medical University, Beijing, 100053, China.
- Aging Translational Medicine Center, International Center for Aging and Cancer, Xuanwu Hospital, Capital Medical University, Beijing, 100053, China.
- Advanced Innovation Center for Human Brain Protection, and National Clinical Research Center for Geriatric Disorders, Xuanwu Hospital Capital Medical University, Beijing, 100053, China.
| | - Xia Wang
- School of Pharmaceutical Sciences, Tsinghua University, Beijing, 100084, China.
| | - Xiaoning Wang
- Institute of Geriatrics, The second Medical Center, Beijing Key Laboratory of Aging and Geriatrics, National Clinical Research Center for Geriatric Diseases, Chinese PLA General Hospital, Beijing, 100853, China.
| | - Yan-Jiang Wang
- Department of Neurology and Center for Clinical Neuroscience, Daping Hospital, Third Military Medical University, Chongqing, 400042, China.
| | - Yunfang Wang
- Hepatobiliary and Pancreatic Center, Medical Research Center, Beijing Tsinghua Changgung Hospital, Beijing, 102218, China.
| | - Catherine C L Wong
- Clinical Research Institute, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Science & Peking Union Medical College, Beijing, 100730, China.
| | - Andy Peng Xiang
- Center for Stem Cell Biologyand Tissue Engineering, Key Laboratory for Stem Cells and Tissue Engineering, Ministry of Education, Sun Yat-sen University, Guangzhou, 510080, China.
- National-Local Joint Engineering Research Center for Stem Cells and Regenerative Medicine, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, 510080, China.
| | - Yichuan Xiao
- CAS Key Laboratory of Tissue Microenvironment and Tumor, Shanghai Institute of Nutrition and Health, Chinese Academy of Sciences, Shanghai, 200031, China.
| | - Zhengwei Xie
- Peking University International Cancer Institute, Health Science Center, Peking University, Beijing, 100101, China.
- Beijing & Qingdao Langu Pharmaceutical R&D Platform, Beijing Gigaceuticals Tech. Co. Ltd., Beijing, 100101, China.
| | - Daichao Xu
- Interdisciplinary Research Center on Biology and Chemistry, Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences, Shanghai, 201210, China.
| | - Jing Ye
- Department of Geriatrics, Medical Center on Aging of Shanghai Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China.
- International Laboratory in Hematology and Cancer, Shanghai Jiao Tong University School of Medicine/Ruijin Hospital, Shanghai, 200025, China.
| | - Rui Yue
- Institute for Regenerative Medicine, Shanghai East Hospital, Frontier Science Center for Stem Cell Research, Shanghai Key Laboratory of Signaling and Disease Research, School of Life Sciences and Technology, Tongji University, Shanghai, 200092, China.
| | - Cuntai Zhang
- Gerontology Center of Hubei Province, Wuhan, 430000, China.
- Institute of Gerontology, Department of Geriatrics, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China.
| | - Hongbo Zhang
- Key Laboratory for Stem Cells and Tissue Engineering, Ministry of Education, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, 510080, China.
- Advanced Medical Technology Center, The First Affiliated Hospital, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, 510080, China.
| | - Liang Zhang
- CAS Key Laboratory of Tissue Microenvironment and Tumor, Shanghai Institute of Nutrition and Health, Chinese Academy of Sciences, Shanghai, 200031, China.
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China.
| | - Weiqi Zhang
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing, 100101, China.
- University of Chinese Academy of Sciences, Beijing, 100049, China.
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China.
| | - Yong Zhang
- Bioland Laboratory (Guangzhou Regenerative Medicine and Health Guangdong Laboratory), Guangzhou, 510005, China.
- The State Key Laboratory of Medical Molecular Biology, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences and School of Basic Medicine, Peking Union Medical College, Beijing, 100005, China.
| | - Yun-Wu Zhang
- Fujian Provincial Key Laboratory of Neurodegenerative Disease and Aging Research, Institute of Neuroscience, School of Medicine, Xiamen University, Xiamen, 361102, China.
| | - Zhuohua Zhang
- Key Laboratory of Molecular Precision Medicine of Hunan Province and Center for Medical Genetics, Institute of Molecular Precision Medicine, Xiangya Hospital, Central South University, Changsha, 410078, China.
- Department of Neurosciences, Hengyang Medical School, University of South China, Hengyang, 421001, China.
| | - Tongbiao Zhao
- State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China.
- University of Chinese Academy of Sciences, Beijing, 100049, China.
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China.
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing, 100101, China.
| | - Yuzheng Zhao
- Optogenetics & Synthetic Biology Interdisciplinary Research Center, State Key Laboratory of Bioreactor Engineering, Shanghai Frontiers Science Center of Optogenetic Techniques for Cell Metabolism, School of Pharmacy, East China University of Science and Technology, Shanghai, 200237, China.
- Research Unit of New Techniques for Live-cell Metabolic Imaging, Chinese Academy of Medical Sciences, Beijing, 100730, China.
| | - Dahai Zhu
- Bioland Laboratory (Guangzhou Regenerative Medicine and Health Guangdong Laboratory), Guangzhou, 510005, China.
- The State Key Laboratory of Medical Molecular Biology, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences and School of Basic Medicine, Peking Union Medical College, Beijing, 100005, China.
| | - Weiguo Zou
- State Key Laboratory of Cell Biology, Shanghai Institute of Biochemistry and Cell Biology, Center for Excellence in Molecular Cell Science, Chinese Academy of Sciences, University of Chinese Academy of Sciences, Shanghai, 200031, China.
| | - Gang Pei
- Shanghai Key Laboratory of Signaling and Disease Research, Laboratory of Receptor-Based Biomedicine, The Collaborative Innovation Center for Brain Science, School of Life Sciences and Technology, Tongji University, Shanghai, 200070, China.
| | - Guang-Hui Liu
- University of Chinese Academy of Sciences, Beijing, 100049, China.
- State Key Laboratory of Membrane Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China.
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China.
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing, 100101, China.
- Advanced Innovation Center for Human Brain Protection, and National Clinical Research Center for Geriatric Disorders, Xuanwu Hospital Capital Medical University, Beijing, 100053, China.
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Abstract
Epigenetic alterations during ageing are manifested with altered gene expression linking it to lifespan regulation, genetic instability, and diseases. Diet and epigenetic modifiers exert a profound effect on the lifespan of an organism by modulating the epigenetic marks. However, our understanding of the multifactorial nature of the epigenetic process during ageing and the onset of disease conditions as well as its reversal by epidrugs, diet, or environmental factors is still mystifying. This review covers the key findings in epigenetics related to ageing and age-related diseases. Further, it holds a discussion about the epigenetic clocks and their implications in various age-related disease conditions including cancer. Although, epigenetics is a reversible process how fast the epigenetic alterations can revert to normal is an intriguing question. Therefore, this paper touches on the possibility of utilizing nutrition and MSCs secretome to accelerate the epigenetic reversal and emphasizes the identification of new therapeutic epigenetic modifiers to counter epigenetic alteration during ageing.
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Affiliation(s)
- Shikha Sharma
- Institute for Stem Cell Science and Regenerative Medicine, 429164, Bangalore, India;
| | - Ramesh Bhonde
- Dr D Y Patil Vidyapeeth University, 121766, Pune, Maharashtra, India;
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Xie S, Choudhari S, Wu CL, Abramson K, Corcoran D, Gregory SG, Thimmapuram J, Guilak F, Little D. Aging and obesity prime the methylome and transcriptome of adipose stem cells for disease and dysfunction. FASEB J 2023; 37:e22785. [PMID: 36794668 PMCID: PMC10561192 DOI: 10.1096/fj.202201413r] [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: 08/31/2022] [Revised: 12/20/2022] [Accepted: 01/09/2023] [Indexed: 02/17/2023]
Abstract
The epigenome of stem cells occupies a critical interface between genes and environment, serving to regulate expression through modification by intrinsic and extrinsic factors. We hypothesized that aging and obesity, which represent major risk factors for a variety of diseases, synergistically modify the epigenome of adult adipose stem cells (ASCs). Using integrated RNA- and targeted bisulfite-sequencing in murine ASCs from lean and obese mice at 5- and 12-months of age, we identified global DNA hypomethylation with either aging or obesity, and a synergistic effect of aging combined with obesity. The transcriptome of ASCs in lean mice was relatively stable to the effects of age, but this was not true in obese mice. Functional pathway analyses identified a subset of genes with critical roles in progenitors and in diseases of obesity and aging. Specifically, Mapt, Nr3c2, App, and Ctnnb1 emerged as potential hypomethylated upstream regulators in both aging and obesity (AL vs. YL and AO vs. YO), and App, Ctnnb1, Hipk2, Id2, and Tp53 exhibited additional effects of aging in obese animals. Furthermore, Foxo3 and Ccnd1 were potential hypermethylated upstream regulators of healthy aging (AL vs. YL), and of the effects of obesity in young animals (YO vs. YL), suggesting that these factors could play a role in accelerated aging with obesity. Finally, we identified candidate driver genes that appeared recurrently in all analyses and comparisons undertaken. Further mechanistic studies are needed to validate the roles of these genes capable of priming ASCs for dysfunction in aging- and obesity-associated pathologies.
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Affiliation(s)
- Shaojun Xie
- Bioinformatics Core, Purdue University, 1022 Young Hall, 155 S. Grant Street, West Lafayette, IN 47907
| | - Sulbha Choudhari
- Bioinformatics Core, Purdue University, 1022 Young Hall, 155 S. Grant Street, West Lafayette, IN 47907
- Advanced Biomedical Computational Science, Bioinformatics and Computational Science, Frederick National Laboratory for Cancer Research, 8560 Progress Drive, Frederick, MD 2170
| | - Chia-Lung Wu
- Department of Orthopaedics and Rehabilitation, Center for Musculoskeletal Research, University of Rochester, Rochester, NY, 14611
| | - Karen Abramson
- Duke Molecular Physiology Institute, 300 North Duke Street, Durham, NC 27701
| | - David Corcoran
- Genomic Analysis and Bioinformatics Shared Resource, Duke Center for Genomic and Computational Biology, 101 Science Drive, Duke University Medical Center Box 3382, Durham, NC 27708
- Lineberger Bioinformatics Core, 5200 Marsico Hall, University of North Carolina-Chapel Hill, Chapel Hill, NC 27516
| | - Simon G. Gregory
- Duke Molecular Physiology Institute, 300 North Duke Street, Durham, NC 27701
- Department of Neurology, Duke University School of Medicine, 311 Research Drive, Durham, NC 27710
| | - Jyothi Thimmapuram
- Bioinformatics Core, Purdue University, 1022 Young Hall, 155 S. Grant Street, West Lafayette, IN 47907
| | - Farshid Guilak
- Department of Orthopaedic Surgery, Washington University in St. Louis, 4515 McKinley Ave., St. Louis, MO 63110
- Shriners Hospitals for Children – St. Louis, 4400 Clayton Ave, St. Louis Missouri 63110
| | - Dianne Little
- Departments of Basic Medical Sciences and Biomedical Engineering, Purdue University, 2186 Lynn Hall, 625 Harrison St, West Lafayette, IN 47907-2026
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Wang J, Zhang W, Liu X, Kim M, Zhang K, Tsai RYL. Epigenome-wide analysis of aging effects on liver regeneration. BMC Biol 2023; 21:30. [PMID: 36782243 PMCID: PMC9926786 DOI: 10.1186/s12915-023-01533-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2022] [Accepted: 02/01/2023] [Indexed: 02/15/2023] Open
Abstract
BACKGROUND Aging is known to exert an effect on liver regeneration, with the ability of liver to regenerate displaying a significant decline over time. Liver physiological parameters such as liver volume, blood flow, and metabolism, as well as the ability to regenerate after injury have all been shown to decrease at old age in humans and model systems, with a number of molecular mechanisms proposed to be involved, including DNA methylation-dependent genome remodeling. To address how changes in DNA methylation mediate the adverse aging effect on liver regeneration, we searched for differentially methylated genomic regions (DMRs) in mouse livers co-regulated by aging and regeneration and determined their associated genes and enriched pathways. RESULTS DMRs were identified using whole-genome bisulfite sequencing (WGBS). Pathway analysis of aging DMR-mapped genes revealed two distinct phases of aging, 2-to-8 and 8-to-16 months old (m/o). Regenerative DMR-mapped differentially expressed genes (DEGs) were enriched in pathways controlling cell proliferation and differentiation. Most DMRs shared by both aging and regeneration changed in the same methylation direction between 2 and 8 m/o but in the opposite direction between 8 and 16 m/o. Regenerative DMRs inversely affected by aging during 8-to-16 m/o were found in the promoter/gene regions of 12 genes. Four regenerative DEGs were synchronously regulated by early aging and inversely regulated by mid-to-late aging DMRs. Lead DMR-mapped genes were validated by their expression profiles in liver aging and regeneration. CONCLUSIONS Our study has uncovered new DMRs and gene targets inversely affected by liver aging and regeneration to explain the adverse aging effect on liver regeneration. These findings will be of fundamental importance to understand the epigenomic changes underlying the biology of aging on liver regeneration.
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Affiliation(s)
- Junying Wang
- grid.412408.bInstitute of Biosciences and Technology, Texas A&M Health Science Center, 2121 W. Holcombe Blvd, Houston, TX 77030 USA
| | - Wen Zhang
- grid.412408.bInstitute of Biosciences and Technology, Texas A&M Health Science Center, 2121 W. Holcombe Blvd, Houston, TX 77030 USA
| | - Xiaoqin Liu
- grid.412408.bInstitute of Biosciences and Technology, Texas A&M Health Science Center, 2121 W. Holcombe Blvd, Houston, TX 77030 USA
| | - Minjee Kim
- grid.412408.bInstitute of Biosciences and Technology, Texas A&M Health Science Center, 2121 W. Holcombe Blvd, Houston, TX 77030 USA
| | - Ke Zhang
- grid.412408.bInstitute of Biosciences and Technology, Texas A&M Health Science Center, 2121 W. Holcombe Blvd, Houston, TX 77030 USA ,grid.412408.bDepartment of Translational Medical Sciences, Texas A&M Health Science Center, 2121 W. Holcombe Blvd, Houston, TX 77030 USA
| | - Robert Y. L. Tsai
- grid.412408.bInstitute of Biosciences and Technology, Texas A&M Health Science Center, 2121 W. Holcombe Blvd, Houston, TX 77030 USA ,grid.412408.bDepartment of Translational Medical Sciences, Texas A&M Health Science Center, 2121 W. Holcombe Blvd, Houston, TX 77030 USA
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38
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Yang JH, Hayano M, Griffin PT, Amorim JA, Bonkowski MS, Apostolides JK, Salfati EL, Blanchette M, Munding EM, Bhakta M, Chew YC, Guo W, Yang X, Maybury-Lewis S, Tian X, Ross JM, Coppotelli G, Meer MV, Rogers-Hammond R, Vera DL, Lu YR, Pippin JW, Creswell ML, Dou Z, Xu C, Mitchell SJ, Das A, O'Connell BL, Thakur S, Kane AE, Su Q, Mohri Y, Nishimura EK, Schaevitz L, Garg N, Balta AM, Rego MA, Gregory-Ksander M, Jakobs TC, Zhong L, Wakimoto H, El Andari J, Grimm D, Mostoslavsky R, Wagers AJ, Tsubota K, Bonasera SJ, Palmeira CM, Seidman JG, Seidman CE, Wolf NS, Kreiling JA, Sedivy JM, Murphy GF, Green RE, Garcia BA, Berger SL, Oberdoerffer P, Shankland SJ, Gladyshev VN, Ksander BR, Pfenning AR, Rajman LA, Sinclair DA. Loss of epigenetic information as a cause of mammalian aging. Cell 2023; 186:305-326.e27. [PMID: 36638792 PMCID: PMC10166133 DOI: 10.1016/j.cell.2022.12.027] [Citation(s) in RCA: 208] [Impact Index Per Article: 208.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2021] [Revised: 08/09/2022] [Accepted: 12/15/2022] [Indexed: 01/13/2023]
Abstract
All living things experience an increase in entropy, manifested as a loss of genetic and epigenetic information. In yeast, epigenetic information is lost over time due to the relocalization of chromatin-modifying proteins to DNA breaks, causing cells to lose their identity, a hallmark of yeast aging. Using a system called "ICE" (inducible changes to the epigenome), we find that the act of faithful DNA repair advances aging at physiological, cognitive, and molecular levels, including erosion of the epigenetic landscape, cellular exdifferentiation, senescence, and advancement of the DNA methylation clock, which can be reversed by OSK-mediated rejuvenation. These data are consistent with the information theory of aging, which states that a loss of epigenetic information is a reversible cause of aging.
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Affiliation(s)
- Jae-Hyun Yang
- Paul F. Glenn Center for Biology of Aging Research, Department of Genetics, Blavatnik Institute, Harvard Medical School (HMS), Boston, MA, USA.
| | - Motoshi Hayano
- Paul F. Glenn Center for Biology of Aging Research, Department of Genetics, Blavatnik Institute, Harvard Medical School (HMS), Boston, MA, USA; Department of Ophthalmology, Department of Neuropsychiatry, Keio University School of Medicine, Tokyo, Japan
| | - Patrick T Griffin
- Paul F. Glenn Center for Biology of Aging Research, Department of Genetics, Blavatnik Institute, Harvard Medical School (HMS), Boston, MA, USA
| | - João A Amorim
- Paul F. Glenn Center for Biology of Aging Research, Department of Genetics, Blavatnik Institute, Harvard Medical School (HMS), Boston, MA, USA; IIIUC-Institute of Interdisciplinary Research, University of Coimbra, Coimbra, Portugal
| | - Michael S Bonkowski
- Paul F. Glenn Center for Biology of Aging Research, Department of Genetics, Blavatnik Institute, Harvard Medical School (HMS), Boston, MA, USA
| | - John K Apostolides
- Computational Biology Department, Carnegie Mellon University, Pittsburgh, PA, USA
| | - Elias L Salfati
- Paul F. Glenn Center for Biology of Aging Research, Department of Genetics, Blavatnik Institute, Harvard Medical School (HMS), Boston, MA, USA
| | | | | | - Mital Bhakta
- Cantata/Dovetail Genomics, Scotts Valley, CA, USA
| | | | - Wei Guo
- Zymo Research Corporation, Irvine, CA, USA
| | | | - Sun Maybury-Lewis
- Paul F. Glenn Center for Biology of Aging Research, Department of Genetics, Blavatnik Institute, Harvard Medical School (HMS), Boston, MA, USA
| | - Xiao Tian
- Paul F. Glenn Center for Biology of Aging Research, Department of Genetics, Blavatnik Institute, Harvard Medical School (HMS), Boston, MA, USA
| | - Jaime M Ross
- Paul F. Glenn Center for Biology of Aging Research, Department of Genetics, Blavatnik Institute, Harvard Medical School (HMS), Boston, MA, USA
| | - Giuseppe Coppotelli
- Paul F. Glenn Center for Biology of Aging Research, Department of Genetics, Blavatnik Institute, Harvard Medical School (HMS), Boston, MA, USA
| | - Margarita V Meer
- Department of Medicine, Brigham and Women's Hospital, HMS, Boston, MA, USA
| | - Ryan Rogers-Hammond
- Paul F. Glenn Center for Biology of Aging Research, Department of Genetics, Blavatnik Institute, Harvard Medical School (HMS), Boston, MA, USA
| | - Daniel L Vera
- Paul F. Glenn Center for Biology of Aging Research, Department of Genetics, Blavatnik Institute, Harvard Medical School (HMS), Boston, MA, USA
| | - Yuancheng Ryan Lu
- Paul F. Glenn Center for Biology of Aging Research, Department of Genetics, Blavatnik Institute, Harvard Medical School (HMS), Boston, MA, USA
| | - Jeffrey W Pippin
- Division of Nephrology, University of Washington, Seattle, WA, USA
| | - Michael L Creswell
- Division of Nephrology, University of Washington, Seattle, WA, USA; Georgetown University School of Medicine, Washington, DC, USA
| | - Zhixun Dou
- Department of Cell and Developmental Biology, University of Pennsylvania, Philadelphia, PA, USA
| | - Caiyue Xu
- Department of Cell and Developmental Biology, University of Pennsylvania, Philadelphia, PA, USA
| | | | - Abhirup Das
- Paul F. Glenn Center for Biology of Aging Research, Department of Genetics, Blavatnik Institute, Harvard Medical School (HMS), Boston, MA, USA; Department of Pharmacology, UNSW, Sydney, NSW, Australia
| | | | - Sachin Thakur
- Paul F. Glenn Center for Biology of Aging Research, Department of Genetics, Blavatnik Institute, Harvard Medical School (HMS), Boston, MA, USA
| | - Alice E Kane
- Paul F. Glenn Center for Biology of Aging Research, Department of Genetics, Blavatnik Institute, Harvard Medical School (HMS), Boston, MA, USA
| | - Qiao Su
- Computational Biology Department, Carnegie Mellon University, Pittsburgh, PA, USA
| | - Yasuaki Mohri
- Department of Stem Cell Biology, Tokyo Medical and Dental University, Tokyo, Japan
| | - Emi K Nishimura
- Department of Stem Cell Biology, Tokyo Medical and Dental University, Tokyo, Japan
| | | | - Neha Garg
- Paul F. Glenn Center for Biology of Aging Research, Department of Genetics, Blavatnik Institute, Harvard Medical School (HMS), Boston, MA, USA
| | - Ana-Maria Balta
- Paul F. Glenn Center for Biology of Aging Research, Department of Genetics, Blavatnik Institute, Harvard Medical School (HMS), Boston, MA, USA
| | - Meghan A Rego
- Paul F. Glenn Center for Biology of Aging Research, Department of Genetics, Blavatnik Institute, Harvard Medical School (HMS), Boston, MA, USA
| | | | - Tatjana C Jakobs
- Schepens Eye Research Institute, Massachusetts Eye and Ear Infirmary, HMS, Boston, MA, USA
| | - Lei Zhong
- The Massachusetts General Hospital Cancer Center, HMS, Boston, MA, USA
| | | | - Jihad El Andari
- Department of Infectious Diseases/Virology, Section Viral Vector Technologies, Medical Faculty, University of Heidelberg, BioQuant, Heidelberg, Germany
| | - Dirk Grimm
- Department of Infectious Diseases/Virology, Section Viral Vector Technologies, Medical Faculty, University of Heidelberg, BioQuant, Heidelberg, Germany
| | - Raul Mostoslavsky
- The Massachusetts General Hospital Cancer Center, HMS, Boston, MA, USA
| | - Amy J Wagers
- Paul F. Glenn Center for Biology of Aging Research, Harvard Stem Cell Institute, Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, MA, USA; Joslin Diabetes Center, Boston, MA, USA
| | - Kazuo Tsubota
- Department of Ophthalmology, Department of Neuropsychiatry, Keio University School of Medicine, Tokyo, Japan
| | - Stephen J Bonasera
- Division of Geriatrics, University of Nebraska Medical Center, Durham Research Center II, Omaha, NE, USA
| | - Carlos M Palmeira
- Department of Life Sciences, Faculty of Sciences and Technology, University of Coimbra, Coimbra, Portugal
| | | | | | - Norman S Wolf
- Department of Pathology, University of Washington, Seattle, WA, USA
| | - Jill A Kreiling
- Department of Molecular Biology, Cell Biology and Biochemistry, Brown University, Providence, RI, USA
| | - John M Sedivy
- Department of Molecular Biology, Cell Biology and Biochemistry, Brown University, Providence, RI, USA
| | - George F Murphy
- Department of Pathology, Brigham & Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Richard E Green
- Department of Biomolecular Engineering, UCSC, Santa Cruz, CA, USA
| | - Benjamin A Garcia
- Department of Cell and Developmental Biology, University of Pennsylvania, Philadelphia, PA, USA
| | - Shelley L Berger
- Department of Cell and Developmental Biology, University of Pennsylvania, Philadelphia, PA, USA
| | | | | | - Vadim N Gladyshev
- Department of Medicine, Brigham and Women's Hospital, HMS, Boston, MA, USA
| | - Bruce R Ksander
- Schepens Eye Research Institute, Massachusetts Eye and Ear Infirmary, HMS, Boston, MA, USA
| | - Andreas R Pfenning
- Computational Biology Department, Carnegie Mellon University, Pittsburgh, PA, USA
| | - Luis A Rajman
- Paul F. Glenn Center for Biology of Aging Research, Department of Genetics, Blavatnik Institute, Harvard Medical School (HMS), Boston, MA, USA
| | - David A Sinclair
- Paul F. Glenn Center for Biology of Aging Research, Department of Genetics, Blavatnik Institute, Harvard Medical School (HMS), Boston, MA, USA.
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Gardner ST, Bertucci EM, Sutton R, Horcher A, Aubrey D, Parrott BB. Development of DNA methylation-based epigenetic age predictors in loblolly pine (Pinus taeda). Mol Ecol Resour 2023; 23:131-144. [PMID: 35957540 PMCID: PMC10087248 DOI: 10.1111/1755-0998.13698] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2022] [Revised: 08/01/2022] [Accepted: 08/03/2022] [Indexed: 11/27/2022]
Abstract
Biological ageing is connected to life history variation across ecological scales and informs a basic understanding of age-related declines in organismal function. Altered DNA methylation dynamics are a conserved aspect of biological ageing and have recently been modelled to predict chronological age among vertebrate species. In addition to their utility in estimating individual age, differences between chronological and predicted ages arise due to acceleration or deceleration of epigenetic ageing, and these discrepancies are linked to disease risk and multiple life history traits. Although evidence suggests that patterns of DNA methylation can describe ageing in plants, predictions with epigenetic clocks have yet to be performed. Here, we resolve the DNA methylome across CpG, CHG, and CHH-methylation contexts in the loblolly pine tree (Pinus taeda) and construct epigenetic clocks capable of predicting ages in this species within 6% of its maximum lifespan. Although patterns of CHH-methylation showed little association with age, both CpG and CHG-methylation contexts were strongly associated with ageing, largely becoming hypomethylated with age. Among age-associated loci were those in close proximity to malate dehydrogenase, NADH dehydrogenase, and 18S and 26S ribosomal RNA genes. This study reports one of the first epigenetic clocks in plants and demonstrates the universality of age-associated DNA methylation dynamics which can inform conservation and management practices, as well as our ecological and evolutionary understanding of biological ageing in plants.
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Affiliation(s)
- Steven T. Gardner
- Savannah River Ecology LaboratoryUniversity of GeorgiaAikenSouth CarolinaUSA
| | - Emily M. Bertucci
- Savannah River Ecology LaboratoryUniversity of GeorgiaAikenSouth CarolinaUSA
- Odum School of EcologyUniversity of GeorgiaAthensGeorgiaUSA
| | - Randall Sutton
- US Forest Service Savannah RiverNew EllentonSouth CarolinaUSA
| | - Andy Horcher
- US Forest Service Savannah RiverNew EllentonSouth CarolinaUSA
| | - Doug Aubrey
- Savannah River Ecology LaboratoryUniversity of GeorgiaAikenSouth CarolinaUSA
- Warnell School of ForestryUniversity of GeorgiaAthensGeorgiaUSA
| | - Benjamin B. Parrott
- Savannah River Ecology LaboratoryUniversity of GeorgiaAikenSouth CarolinaUSA
- Odum School of EcologyUniversity of GeorgiaAthensGeorgiaUSA
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40
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Chiavellini P, Lehmann M, Canatelli Mallat M, Zoller JA, Herenu CB, Morel GR, Horvath S, Goya RG. Hippocampal DNA Methylation, Epigenetic Age, and Spatial Memory Performance in Young and Old Rats. J Gerontol A Biol Sci Med Sci 2022; 77:2387-2394. [PMID: 35917578 DOI: 10.1093/gerona/glac153] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2022] [Indexed: 01/20/2023] Open
Abstract
In humans and rats, aging is associated with a progressive deterioration of spatial learning and memory. These functional alterations are correlated with morphological and molecular changes in the hippocampus. Here, we assessed age-related changes in DNA methylation (DNAm) landscape in the rat hippocampus and the correlation of spatial memory with hippocampal DNAm age in 2.6- and 26.6-month-old rats. Spatial memory performance was assessed with the Barnes maze test. To evaluate learning ability and spatial memory retention, we assessed the time spent by animals in goal sector 1 (GS1) and 3 (GS3) when the escape box was removed. The rat pan-tissue clock was applied to DNAm data from hippocampal tissue. An enrichment pathway analysis revealed that neuron fate commitment, brain development, and central nervous system development were processes whose underlying genes were enriched in hypermethylated CpGs in the old rats. In the old rat hippocampi, the methylation levels of CpG proximal to transcription factors associated with genes Pax5, Lbx1, Nr2f2, Hnf1b, Zic1, Zic4, Hoxd9; Hoxd10, Gli3, Gsx1 and Lmx1b, and Nipbl showed a significant regression with spatial memory performance. Regression analysis of different memory performance indices with hippocampal DNAm age was significant. These results suggest that age-related hypermethylation of transcription factors related to certain gene families, such as Zic and Gli, may play a causal role in the decline in spatial memory in old rats. Hippocampal DNAm age seems to be a reliable index of spatial memory performance in young and old rats.
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Affiliation(s)
- Priscila Chiavellini
- Institute for Biochemical Research (INIBIOLP)-Histology B and Pathology B, School of Medicine, National University of La Plata (UNLP), La Plata, Argentina
| | - Marianne Lehmann
- Institute for Biochemical Research (INIBIOLP)-Histology B and Pathology B, School of Medicine, National University of La Plata (UNLP), La Plata, Argentina
| | - Martina Canatelli Mallat
- Institute for Biochemical Research (INIBIOLP)-Histology B and Pathology B, School of Medicine, National University of La Plata (UNLP), La Plata, Argentina
| | - Joseph A Zoller
- Department of Biostatistics, Fielding School of Public Health, University of California, Los Angeles, Los Angeles, California, USA
| | - Claudia B Herenu
- Institute for Experimental Pharmacology (IFEC), School of Chemical Sciences, National University of Cordoba, Cordoba, Argentina
| | - Gustavo R Morel
- Institute for Biochemical Research (INIBIOLP)-Histology B and Pathology B, School of Medicine, National University of La Plata (UNLP), La Plata, Argentina
| | - Steve Horvath
- Department of Biostatistics, Fielding School of Public Health, University of California, Los Angeles, Los Angeles, California, USA
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California, USA
| | - Rodolfo G Goya
- Institute for Biochemical Research (INIBIOLP)-Histology B and Pathology B, School of Medicine, National University of La Plata (UNLP), La Plata, Argentina
- Critical Care Research (CCR), Rancho Cucamonga, California, USA
- Vitality in Aging Research Group (VIA), Fort Lauderdale, Florida, USA
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41
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Coppedè F. DNA methylation as a powerful tool to investigate the biology and pathology of aging. Epigenomics 2022; 14:1541-1544. [PMID: 36803012 DOI: 10.2217/epi-2023-0011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/23/2023] Open
Affiliation(s)
- Fabio Coppedè
- Department of Translational Research & of New Surgical & Medical Technologies, Laboratory of Medical Genetics, University of Pisa, Via Roma 55, Pisa, 56126, Italy
- Interdepartmental Research Center of Biology & Pathology of Aging, University of Pisa, Pisa, 56126, Italy
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42
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Rauchhaus J, Robinson J, Monti L, Di Antonio M. G-quadruplexes Mark Sites of Methylation Instability Associated with Ageing and Cancer. Genes (Basel) 2022; 13:1665. [PMID: 36140833 PMCID: PMC9498706 DOI: 10.3390/genes13091665] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2022] [Revised: 08/03/2022] [Accepted: 09/13/2022] [Indexed: 11/17/2022] Open
Abstract
Regulation of the epigenome is critical for healthy cell function but can become disrupted with age, leading to aberrant epigenetic profiles including altered DNA methylation. Recent studies have indicated that DNA methylation homeostasis can be compromised by the formation of DNA secondary structures known as G-quadruplexes (G4s), which form in guanine-rich regions of the genome. G4s can be recognised and bound by certain methylation-regulating enzymes, and in turn perturb the surrounding methylation architecture. However, the effect G4 formation has on DNA methylation at critical epigenetic sites remains elusive and poorly explored. In this work, we investigate the association between G4 sequences and prominent DNA methylation sites, termed 'ageing clocks', that act as bona fide dysregulated regions in aged and cancerous cells. Using a combination of in vitro (G4-seq) and in cellulo (BG4-ChIP) G4 distribution maps, we show that ageing clocks sites are significantly enriched with G4-forming sequences. The observed enrichment also varies across species and cell lines, being least significant in healthy cells and more pronounced in tumorigenic cells. Overall, our results suggest a biological significance of G4s in the realm of DNA methylation, which may be important for further deciphering the driving forces of diseases characterised by epigenetic abnormality, including ageing.
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Affiliation(s)
- Jonas Rauchhaus
- Imperial College London, Chemistry Department, Molecular Science Research Hub, 82 Wood Lane, London W12 0BZ, UK
- Imperial College London, Department of Bioengineering, Royal School of Mines, Exhibition Road, London SW7 2AZ, UK
| | - Jenna Robinson
- Imperial College London, Chemistry Department, Molecular Science Research Hub, 82 Wood Lane, London W12 0BZ, UK
- Institute of Chemical Biology, Molecular Science Research Hub, 82 Wood Lane, London W12 0BZ, UK
- The Francis Crick Institute, 1 Midland Road, London NW1 1AT, UK
| | - Ludovica Monti
- Imperial College London, Chemistry Department, Molecular Science Research Hub, 82 Wood Lane, London W12 0BZ, UK
- The Francis Crick Institute, 1 Midland Road, London NW1 1AT, UK
| | - Marco Di Antonio
- Imperial College London, Chemistry Department, Molecular Science Research Hub, 82 Wood Lane, London W12 0BZ, UK
- Institute of Chemical Biology, Molecular Science Research Hub, 82 Wood Lane, London W12 0BZ, UK
- The Francis Crick Institute, 1 Midland Road, London NW1 1AT, UK
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43
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Johnson AA, English BW, Shokhirev MN, Sinclair DA, Cuellar TL. Human age reversal: Fact or fiction? Aging Cell 2022; 21:e13664. [PMID: 35778957 PMCID: PMC9381899 DOI: 10.1111/acel.13664] [Citation(s) in RCA: 23] [Impact Index Per Article: 11.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2022] [Revised: 05/23/2022] [Accepted: 06/13/2022] [Indexed: 12/19/2022] Open
Abstract
Although chronological age correlates with various age-related diseases and conditions, it does not adequately reflect an individual's functional capacity, well-being, or mortality risk. In contrast, biological age provides information about overall health and indicates how rapidly or slowly a person is aging. Estimates of biological age are thought to be provided by aging clocks, which are computational models (e.g., elastic net) that use a set of inputs (e.g., DNA methylation sites) to make a prediction. In the past decade, aging clock studies have shown that several age-related diseases, social variables, and mental health conditions associate with an increase in predicted biological age relative to chronological age. This phenomenon of age acceleration is linked to a higher risk of premature mortality. More recent research has demonstrated that predicted biological age is sensitive to specific interventions. Human trials have reported that caloric restriction, a plant-based diet, lifestyle changes involving exercise, a drug regime including metformin, and vitamin D3 supplementation are all capable of slowing down or reversing an aging clock. Non-interventional studies have connected high-quality sleep, physical activity, a healthy diet, and other factors to age deceleration. Specific molecules have been associated with the reduction or reversal of predicted biological age, such as the antihypertensive drug doxazosin or the metabolite alpha-ketoglutarate. Although rigorous clinical trials are needed to validate these initial findings, existing data suggest that aging clocks are malleable in humans. Additional research is warranted to better understand these computational models and the clinical significance of lowering or reversing their outputs.
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Affiliation(s)
- Adiv A. Johnson
- Longevity Sciences, Inc. (dba Tally Health)GreenwichConnecticutUSA
| | - Bradley W. English
- Blavatnik Institute, Department of Genetics, Paul F. Glenn Center for Biology of Aging ResearchHarvard Medical SchoolBostonMassachusettsUSA
| | | | - David A. Sinclair
- Blavatnik Institute, Department of Genetics, Paul F. Glenn Center for Biology of Aging ResearchHarvard Medical SchoolBostonMassachusettsUSA
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Zhou W, Hinoue T, Barnes B, Mitchell O, Iqbal W, Lee SM, Foy KK, Lee KH, Moyer EJ, VanderArk A, Koeman JM, Ding W, Kalkat M, Spix NJ, Eagleson B, Pospisilik JA, Szabó PE, Bartolomei MS, Vander Schaaf NA, Kang L, Wiseman AK, Jones PA, Krawczyk CM, Adams M, Porecha R, Chen BH, Shen H, Laird PW. DNA methylation dynamics and dysregulation delineated by high-throughput profiling in the mouse. CELL GENOMICS 2022; 2:100144. [PMID: 35873672 PMCID: PMC9306256 DOI: 10.1016/j.xgen.2022.100144] [Citation(s) in RCA: 33] [Impact Index Per Article: 16.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/08/2021] [Revised: 03/20/2022] [Accepted: 05/20/2022] [Indexed: 05/21/2023]
Abstract
We have developed a mouse DNA methylation array that contains 296,070 probes representing the diversity of mouse DNA methylation biology. We present a mouse methylation atlas as a rich reference resource of 1,239 DNA samples encompassing distinct tissues, strains, ages, sexes, and pathologies. We describe applications for comparative epigenomics, genomic imprinting, epigenetic inhibitors, patient-derived xenograft assessment, backcross tracing, and epigenetic clocks. We dissect DNA methylation processes associated with differentiation, aging, and tumorigenesis. Notably, we find that tissue-specific methylation signatures localize to binding sites for transcription factors controlling the corresponding tissue development. Age-associated hypermethylation is enriched at regions of Polycomb repression, while hypomethylation is enhanced at regions bound by cohesin complex members. Apc Min/+ polyp-associated hypermethylation affects enhancers regulating intestinal differentiation, while hypomethylation targets AP-1 binding sites. This Infinium Mouse Methylation BeadChip (version MM285) is widely accessible to the research community and will accelerate high-sample-throughput studies in this important model organism.
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Affiliation(s)
- Wanding Zhou
- Center for Computational and Genomic Medicine, Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA
- Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Corresponding author
| | - Toshinori Hinoue
- Department of Epigenetics, Van Andel Institute, Grand Rapids, MI 49503, USA
| | - Bret Barnes
- Illumina, Inc., Bioinformatics and Instrument Software Department, San Diego, CA 92122, USA
| | - Owen Mitchell
- Department of Epigenetics, Van Andel Institute, Grand Rapids, MI 49503, USA
| | - Waleed Iqbal
- Center for Computational and Genomic Medicine, Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA
| | - Sol Moe Lee
- Center for Computational and Genomic Medicine, Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA
| | - Kelly K. Foy
- Department of Epigenetics, Van Andel Institute, Grand Rapids, MI 49503, USA
| | - Kwang-Ho Lee
- Department of Epigenetics, Van Andel Institute, Grand Rapids, MI 49503, USA
| | - Ethan J. Moyer
- Center for Computational and Genomic Medicine, Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA
| | - Alexandra VanderArk
- Department of Metabolism and Nutritional Programming, Van Andel Institute, Grand Rapids, MI 49503, USA
| | - Julie M. Koeman
- Genomics Core, Van Andel Institute, Grand Rapids, MI 49503, USA
| | - Wubin Ding
- Center for Computational and Genomic Medicine, Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA
| | - Manpreet Kalkat
- Department of Epigenetics, Van Andel Institute, Grand Rapids, MI 49503, USA
| | - Nathan J. Spix
- Department of Epigenetics, Van Andel Institute, Grand Rapids, MI 49503, USA
| | - Bryn Eagleson
- Vivarium and Transgenics Core, Van Andel Institute, Grand Rapids, MI 49503, USA
| | | | - Piroska E. Szabó
- Department of Epigenetics, Van Andel Institute, Grand Rapids, MI 49503, USA
| | - Marisa S. Bartolomei
- Department of Cell and Developmental Biology, Epigenetics Institute, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA 19104, USA
| | | | - Liang Kang
- Department of Epigenetics, Van Andel Institute, Grand Rapids, MI 49503, USA
| | - Ashley K. Wiseman
- Department of Epigenetics, Van Andel Institute, Grand Rapids, MI 49503, USA
| | - Peter A. Jones
- Department of Epigenetics, Van Andel Institute, Grand Rapids, MI 49503, USA
| | - Connie M. Krawczyk
- Department of Metabolism and Nutritional Programming, Van Andel Institute, Grand Rapids, MI 49503, USA
| | - Marie Adams
- Genomics Core, Van Andel Institute, Grand Rapids, MI 49503, USA
| | - Rishi Porecha
- Illumina, Inc., Bioinformatics and Instrument Software Department, San Diego, CA 92122, USA
| | | | - Hui Shen
- Department of Epigenetics, Van Andel Institute, Grand Rapids, MI 49503, USA
- Corresponding author
| | - Peter W. Laird
- Department of Epigenetics, Van Andel Institute, Grand Rapids, MI 49503, USA
- Corresponding author
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45
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Inflammatory exposure drives long-lived impairment of hematopoietic stem cell self-renewal activity and accelerated aging. Cell Stem Cell 2022; 29:1273-1284.e8. [PMID: 35858618 PMCID: PMC9357150 DOI: 10.1016/j.stem.2022.06.012] [Citation(s) in RCA: 76] [Impact Index Per Article: 38.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2022] [Revised: 06/08/2022] [Accepted: 06/21/2022] [Indexed: 12/15/2022]
Abstract
Hematopoietic stem cells (HSCs) mediate regeneration of the hematopoietic system following injury, such as following infection or inflammation. These challenges impair HSC function, but whether this functional impairment extends beyond the duration of inflammatory exposure is unknown. Unexpectedly, we observed an irreversible depletion of functional HSCs following challenge with inflammation or bacterial infection, with no evidence of any recovery up to 1 year afterward. HSCs from challenged mice demonstrated multiple cellular and molecular features of accelerated aging and developed clinically relevant blood and bone marrow phenotypes not normally observed in aged laboratory mice but commonly seen in elderly humans. In vivo HSC self-renewal divisions were absent or extremely rare during both challenge and recovery periods. The progressive, irreversible attrition of HSC function demonstrates that temporally discrete inflammatory events elicit a cumulative inhibitory effect on HSCs. This work positions early/mid-life inflammation as a mediator of lifelong defects in tissue maintenance and regeneration.
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46
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Perez-Correa JF, Tharmapalan V, Geiger H, Wagner W. Epigenetic Clocks for Mice Based on Age-Associated Regions That are Conserved Between Mouse Strains and Human. Front Cell Dev Biol 2022; 10:902857. [PMID: 35721486 PMCID: PMC9204067 DOI: 10.3389/fcell.2022.902857] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2022] [Accepted: 05/13/2022] [Indexed: 11/13/2022] Open
Abstract
Aging of mice can be tracked by DNA methylation changes at specific sites in the genome. In this study, we used the recently released Infinium Mouse Methylation BeadChip to compare such epigenetic modifications in C57BL/6 (B6) and DBA/2J (DBA) mice. We observed marked differences in age-associated DNA methylation in these commonly used inbred mouse strains, indicating that epigenetic clocks for one strain cannot be simply applied to other strains without further verification. In B6 mice age-associated hypomethylation prevailed with focused hypermethylation at CpG islands, whereas in DBA mice CpG islands revealed rather hypomethylation upon aging. Interestingly, the CpGs with highest age-correlation were still overlapping in B6 and DBA mice and included the genes Hsf4, Prima1, Aspa, and Wnt3a. Notably, Hsf4 and Prima1 were also top candidates in previous studies based on whole genome deep sequencing approaches. Furthermore, Hsf4, Aspa, and Wnt3a revealed highly significant age-associated DNA methylation in the homologous regions in human. Subsequently, we used pyrosequencing of the four relevant regions to establish a targeted epigenetic clock that provided very high correlation with chronological age in independent cohorts of B6 (R2 = 0.98) and DBA (R2 = 0.91). Taken together, the methylome differs extensively between B6 and DBA mice, while prominent age-associated changes are conserved among these strains and even in humans. Our new targeted epigenetic clock with 4 CpGs provides a versatile tool for other researchers analyzing aging in mice.
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Affiliation(s)
- Juan-Felipe Perez-Correa
- Institute for Stem Cell Biology, RWTH Aachen University Medical School, Aachen, Germany
- Helmholtz Institute for Biomedical Engineering, RWTH Aachen University Medical School, Aachen, Germany
| | - Vithurithra Tharmapalan
- Institute for Stem Cell Biology, RWTH Aachen University Medical School, Aachen, Germany
- Helmholtz Institute for Biomedical Engineering, RWTH Aachen University Medical School, Aachen, Germany
| | - Hartmut Geiger
- Institute of Molecular Medicine, Ulm University, Ulm, Germany
| | - Wolfgang Wagner
- Institute for Stem Cell Biology, RWTH Aachen University Medical School, Aachen, Germany
- Helmholtz Institute for Biomedical Engineering, RWTH Aachen University Medical School, Aachen, Germany
- *Correspondence: Wolfgang Wagner,
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Fennell L, Kane A, Liu C, McKeone D, Hartel G, Su C, Bond C, Bettington M, Leggett B, Whitehall V. Braf mutation induces rapid neoplastic transformation in the aged and aberrantly methylated intestinal epithelium. Gut 2022; 71:1127-1140. [PMID: 34230216 PMCID: PMC9120393 DOI: 10.1136/gutjnl-2020-322166] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/10/2020] [Accepted: 06/30/2021] [Indexed: 12/08/2022]
Abstract
OBJECTIVE Sessile serrated lesions (SSLs) are common across the age spectrum, but the BRAF mutant cancers arising occur predominantly in the elderly. Aberrant DNA methylation is uncommon in SSL from young patients. Here, we interrogate the role of ageing and DNA methylation in SSL initiation and progression. DESIGN We used an inducible model of Braf mutation to direct recombination of the oncogenic Braf V637E allele to the murine intestine. BRAF mutation was activated after periods of ageing, and tissue was assessed for histological, DNA methylation and gene expression changes thereafter. We also investigated DNA methylation alterations in human SSLs. RESULTS Inducing Braf mutation in aged mice was associated with a 10-fold relative risk of serrated lesions compared with young mice. There were extensive differences in age-associated DNA methylation between animals induced at 9 months versus wean, with relatively little differential Braf-specific methylation. DNA methylation at WNT pathway genes scales with age and Braf mutation accelerated age-associated DNA methylation. In human SSLs, increased epigenetic age was associated with high-risk serrated colorectal neoplasia. CONCLUSIONS SSLs arising in the aged intestine are at a significantly higher risk of spontaneous neoplastic progression. These findings provide support for a new conceptual model for serrated colorectal carcinogenesis, whereby risk of Braf-induced neoplastic transformation is dependent on age and may be related to age-associated molecular alterations that accumulate in the ageing intestine, including DNA methylation. This may have implications for surveillance and chemopreventive strategies targeting the epigenome.
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Affiliation(s)
- Lochlan Fennell
- The Conjoint Gastroenterology Laboratory, QIMR Berghofer Medical Research Institute, Herston, Queensland, Australia
- Faculty of Medicine, The University of Queensland, Saint Lucia, Queensland, Australia
| | - Alexandra Kane
- The Conjoint Gastroenterology Laboratory, QIMR Berghofer Medical Research Institute, Herston, Queensland, Australia
- Faculty of Medicine, The University of Queensland, Saint Lucia, Queensland, Australia
- Conjoint Internal Medical Laboratory, Chemical Pathology, Health Support Queensland Pathology Queensland, Herston, Queensland, Australia
| | - Cheng Liu
- The Conjoint Gastroenterology Laboratory, QIMR Berghofer Medical Research Institute, Herston, Queensland, Australia
- Faculty of Medicine, The University of Queensland, Saint Lucia, Queensland, Australia
| | - Diane McKeone
- The Conjoint Gastroenterology Laboratory, QIMR Berghofer Medical Research Institute, Herston, Queensland, Australia
| | - Gunter Hartel
- Statistics Department, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - Chang Su
- The Conjoint Gastroenterology Laboratory, QIMR Berghofer Medical Research Institute, Herston, Queensland, Australia
- Faculty of Medicine, The University of Queensland, Saint Lucia, Queensland, Australia
| | - Catherine Bond
- The Conjoint Gastroenterology Laboratory, QIMR Berghofer Medical Research Institute, Herston, Queensland, Australia
- Faculty of Medicine, The University of Queensland, Saint Lucia, Queensland, Australia
| | - Mark Bettington
- Envoi Specialist Pathologists, Brisbane, Queensland, Australia
| | - Barbara Leggett
- The Conjoint Gastroenterology Laboratory, QIMR Berghofer Medical Research Institute, Herston, Queensland, Australia
- Faculty of Medicine, The University of Queensland, Saint Lucia, Queensland, Australia
- Department of Gastroenterology and Hepatology, The Royal Brisbane and Women's Hospital, Brisbane, Queensland, Australia
| | - Vicki Whitehall
- The Conjoint Gastroenterology Laboratory, QIMR Berghofer Medical Research Institute, Herston, Queensland, Australia
- Faculty of Medicine, The University of Queensland, Saint Lucia, Queensland, Australia
- Conjoint Internal Medical Laboratory, Chemical Pathology, Health Support Queensland Pathology Queensland, Herston, Queensland, Australia
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48
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Horvath S, Lu AT, Haghani A, Zoller JA, Li CZ, Lim AR, Brooke RT, Raj K, Serres-Armero A, Dreger DL, Hogan AN, Plassais J, Ostrander EA. DNA methylation clocks for dogs and humans. Proc Natl Acad Sci U S A 2022; 119:e2120887119. [PMID: 35580182 PMCID: PMC9173771 DOI: 10.1073/pnas.2120887119] [Citation(s) in RCA: 25] [Impact Index Per Article: 12.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2021] [Accepted: 04/05/2022] [Indexed: 12/24/2022] Open
Abstract
DNA methylation profiles have been used to develop biomarkers of aging known as epigenetic clocks, which predict chronological age with remarkable accuracy and show promise for inferring health status as an indicator of biological age. Epigenetic clocks were first built to monitor human aging, but their underlying principles appear to be evolutionarily conserved, as they have now been successfully developed for many mammalian species. Here, we describe reliable and highly accurate epigenetic clocks shown to apply to 93 domestic dog breeds. The methylation profiles were generated using the mammalian methylation array, which utilizes DNA sequences that are conserved across all mammalian species. Canine epigenetic clocks were constructed to estimate age and also average time to death. We also present two highly accurate human–dog dual species epigenetic clocks (R = 0.97), which may facilitate the ready translation from canine to human use (or vice versa) of antiaging treatments being developed for longevity and preventive medicine. Finally, epigenome-wide association studies here reveal individual methylation sites that may underlie the inverse relationship between breed weight and lifespan. Overall, we describe robust biomarkers to measure aging and, potentially, health status in canines.
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Affiliation(s)
- Steve Horvath
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, CA 90095
- Department of Biostatistics, Fielding School of Public Health, University of California, Los Angeles, CA 90095
| | - Ake T. Lu
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, CA 90095
| | - Amin Haghani
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, CA 90095
| | - Joseph A. Zoller
- Department of Biostatistics, Fielding School of Public Health, University of California, Los Angeles, CA 90095
| | - Caesar Z. Li
- Department of Biostatistics, Fielding School of Public Health, University of California, Los Angeles, CA 90095
| | - Andrea R. Lim
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, CA 90095
| | | | - Ken Raj
- Radiation Effects Department, Centre for Radiation, Chemical and Environmental Hazards, Public Health England, Chilton, Didcot OX11 0RQ, United Kingdom
| | | | - Dayna L. Dreger
- National Human Genome Research Institute, NIH, Bethesda, MD 20892
| | - Andrew N. Hogan
- National Human Genome Research Institute, NIH, Bethesda, MD 20892
| | - Jocelyn Plassais
- National Human Genome Research Institute, NIH, Bethesda, MD 20892
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49
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Mach J, Kane AE, Howlett SE, Sinclair DA, Hilmer SN. Applying the AFRAID and FRIGHT clocks to novel preclinical mouse models of polypharmacy. J Gerontol A Biol Sci Med Sci 2022; 77:1304-1312. [PMID: 35313348 PMCID: PMC9255695 DOI: 10.1093/gerona/glac067] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2021] [Indexed: 11/28/2022] Open
Abstract
The Frailty Inferred Geriatric Health Timeline (FRIGHT) and Analysis of Frailty and Death (AFRAID) clocks were developed to predict biological age and lifespan, respectively, in mice. Their utility within the context of polypharmacy (≥5 medications), which is very common in older adults, is unknown. In male C57BL/6J(B6) mice administered chronic polypharmacy, monotherapy, and undergoing treatment cessation (deprescribing), we aimed to compare these clocks between treatment groups; investigate whether treatment affected correlation of these clocks with mortality; and explore factors that may explain variation in predictive performance. Treatment (control, polypharmacy, or monotherapy) commenced from age 12 months. At age 21 months, each treatment group was subdivided to continue treatment or have it deprescribed. Frailty index was assessed and informed calculation of the clocks. AFRAID, FRIGHT, frailty index, and mortality age did not differ between continued treatment groups and control. Compared to continued treatment, deprescribing some treatments had inconsistent negative impacts on some clocks and mortality. FRIGHT and frailty index, but not AFRAID, were associated with mortality. The bias and precision of AFRAID as a predictor of mortality varied between treatment groups. Effects of deprescribing some drugs on elements of the clocks, particularly on weight loss, contributed to bias. Overall, in this cohort, FRIGHT and AFRAID measures identified no treatment effects and limited deprescribing effects (unsurprising as very few effects on frailty or mortality), with variable prediction of mortality. These clocks have utility, but context is important. Future work should refine them for intervention studies to reduce bias from specific intervention effects.
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Affiliation(s)
- John Mach
- Laboratory of Ageing and Pharmacology, Kolling Institute of Medical Research, Faculty of Medicine and Health, The University of Sydney and Royal North Shore Hospital, St Leonards, New South Wales, Australia
| | - Alice E Kane
- Blavatnik Institute, Dept. of Genetics, Paul F. Glenn Center for Biology of Aging Research at Harvard Medical School, Boston, MA
| | - Susan E Howlett
- Departments of Pharmacology and Medicine (Geriatric Medicine), Dalhousie University, Halifax, Canada
| | - David A Sinclair
- Blavatnik Institute, Dept. of Genetics, Paul F. Glenn Center for Biology of Aging Research at Harvard Medical School, Boston, MA
| | - Sarah N Hilmer
- Laboratory of Ageing and Pharmacology, Kolling Institute of Medical Research, Faculty of Medicine and Health, The University of Sydney and Royal North Shore Hospital, St Leonards, New South Wales, Australia
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50
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Crouch J, Shvedova M, Thanapaul RJRS, Botchkarev V, Roh D. Epigenetic Regulation of Cellular Senescence. Cells 2022; 11:672. [PMID: 35203320 PMCID: PMC8870565 DOI: 10.3390/cells11040672] [Citation(s) in RCA: 43] [Impact Index Per Article: 21.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2021] [Revised: 02/07/2022] [Accepted: 02/14/2022] [Indexed: 02/04/2023] Open
Abstract
Senescence is a complex cellular stress response that abolishes proliferative capacity and generates a unique secretory pattern that is implicated in organismal aging and age-related disease. How a cell transitions to a senescent state is multifactorial and often requires transcriptional regulation of multiple genes. Epigenetic alterations to DNA and chromatin are powerful regulators of genome architecture and gene expression, and they play a crucial role in mediating the induction and maintenance of senescence. This review will highlight the changes in chromatin, DNA methylation, and histone alterations that establish and maintain cellular senescence, alongside the specific epigenetic regulation of the senescence-associated secretory phenotype (SASP).
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Affiliation(s)
- Jack Crouch
- Division of Plastic and Reconstructive Surgery, Department of Surgery, Boston University School of Medicine, Boston, MA 02118, USA; (J.C.); (M.S.); (R.J.R.S.T.)
| | - Maria Shvedova
- Division of Plastic and Reconstructive Surgery, Department of Surgery, Boston University School of Medicine, Boston, MA 02118, USA; (J.C.); (M.S.); (R.J.R.S.T.)
| | - Rex Jeya Rajkumar Samdavid Thanapaul
- Division of Plastic and Reconstructive Surgery, Department of Surgery, Boston University School of Medicine, Boston, MA 02118, USA; (J.C.); (M.S.); (R.J.R.S.T.)
| | - Vladimir Botchkarev
- Department of Dermatology, Boston University School of Medicine, Boston, MA 02118, USA;
| | - Daniel Roh
- Division of Plastic and Reconstructive Surgery, Department of Surgery, Boston University School of Medicine, Boston, MA 02118, USA; (J.C.); (M.S.); (R.J.R.S.T.)
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