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Shah S, Yu S, Zhang C, Ali I, Wang X, Qian Y, Xiao T. Retrotransposon SINEs in Age-Related Diseases: Mechanisms and Therapeutic Implications. Ageing Res Rev 2024:102539. [PMID: 39395576 DOI: 10.1016/j.arr.2024.102539] [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: 06/27/2024] [Revised: 09/27/2024] [Accepted: 10/03/2024] [Indexed: 10/14/2024]
Abstract
Retrotransposons are self-replicating genomic elements that move from one genomic location to another using a "copy-and-paste" method involving RNA intermediaries. One family of retrotransposon that has garnered considerable attention for its association with age-related diseases and anti-aging interventions is the short interspersed nuclear elements (SINEs). This review summarizes current knowledge on the roles of SINEs in aging processes and therapies. To underscore the significant research on the involvement of SINEs in aging-related diseases, we commence by outlining compelling evidence on the classification and mechanism, highlighting implications in age-related phenomena. The intricate relationship between SINEs and diseases such as neurodegenerative disorders, heart failure, high blood pressure, atherosclerosis, type 2 diabetes mellitus, osteoporosis, visual system dysfunctions, and cancer is explored, emphasizing their roles in various age-related diseases. Recent investigations into the anti-aging potential of SINE-targeted treatments are examined, with particular attention to how SINE antisense RNA mitigate age-related alterations at the cellular and molecular levels, offering insights into potential therapeutic targets for age-related pathologies. This review aims to compile the most recent advances on the multifaceted roles of SINE retrotransposons in age-related diseases and anti-aging interventions, providing valuable insights into underlying mechanisms and therapeutic avenues for promoting healthy aging.
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Affiliation(s)
- Suleman Shah
- Thoracic Surgery Department of the First Affiliated Hospital, Guangdong Key Laboratory of Genome Instability and Human Disease Prevention, Department of Cell Biology and Genetics, Shenzhen University Medical School, Shenzhen University, Shenzhen 518055, China; Guangdong Key Laboratory for Biomedical Measurements and Ultrasound Imaging, National-Regional Key Technology Engineering Laboratory for Medical Ultrasound, School of Biomedical Engineering, Shenzhen University Medical school, Shenzhen 518055, China
| | - Siyi Yu
- State Key Laboratory of Oral & Maxillofacial Reconstruction and Regeneration, Key Laboratory of Oral Biomedicine Ministry of Education, Hubei Key Laboratory of Stomatology, School & Hospital of Stomatology, Wuhan University, Wuhan 430079, China
| | - Chen Zhang
- Department of Thoracic Surgery, The People's Hospital of Guangxi Zhuang Autonomous Region, Guangxi Academy of Medical Sciences, Nanning 530021, China
| | - Ilyas Ali
- Guangdong Key Laboratory for Biomedical Measurements and Ultrasound Imaging, National-Regional Key Technology Engineering Laboratory for Medical Ultrasound, School of Biomedical Engineering, Shenzhen University Medical school, Shenzhen 518055, China
| | - Xiufang Wang
- Department of Genetics, Hebei Medical University, Hebei Key Lab of Laboratory Animal, Shijiazhuang, 050017, China
| | - Youhui Qian
- Thoracic Surgery Department of the First Affiliated Hospital, Guangdong Key Laboratory of Genome Instability and Human Disease Prevention, Department of Cell Biology and Genetics, Shenzhen University Medical School, Shenzhen University, Shenzhen 518055, China.
| | - Tian Xiao
- Thoracic Surgery Department of the First Affiliated Hospital, Guangdong Key Laboratory of Genome Instability and Human Disease Prevention, Department of Cell Biology and Genetics, Shenzhen University Medical School, Shenzhen University, Shenzhen 518055, China.
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2
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Yao L, Yang C, Graff JC, Wang G, Wang G, Gu W. From Reactive to Proactive - The Future Life Design to Promote Health and Extend the Human Lifespan. Adv Biol (Weinh) 2024; 8:e2400148. [PMID: 39037380 DOI: 10.1002/adbi.202400148] [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: 03/15/2024] [Revised: 06/11/2024] [Indexed: 07/23/2024]
Abstract
Disease treatment and prevention have improved the human lifespan. Current studies on aging, such as the biological clock and senolytic drugs have focused on the medical treatments of various disorders and health maintenance. However, to efficiently extend the human lifespan to its theoretical maximum, medicine can take a further proactive approach and identify the inapparent disorders that affect the gestation, body growth, and reproductive stages of the so-called "healthy" population. The goal is to upgrade the standard health status to a new level by targeting the inapparent disorders. Thus, future research can shift from reaction, response, and prevention to proactive, quality promotion and vigor prolonging; from single disease-oriented to multiple dimension protocol for a healthy body; from treatment of symptom onset to keep away from disorders; and from the healthy aging management to a healthy promotion design beginning at the birth.
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Affiliation(s)
- Lan Yao
- College of Health management, Harbin Medical University, 157 Baojian Road, Harbin, Heilongjiang, 150081, China
- Department of Orthopedic Surgery and BME-Campbell Clinic, University of Tennessee Health Science Center, Memphis, TN, 38163, USA
| | - Chengyuan Yang
- Department of Orthopedic Surgery and BME-Campbell Clinic, University of Tennessee Health Science Center, Memphis, TN, 38163, USA
| | - J Carolyn Graff
- Department of Health Promotion and Disease Prevention, College of Nursing, University of Tennessee Health Science Center, Memphis, TN, 38163, USA
| | - Guiying Wang
- Department of General Surgery, The Second Hospital of Hebei Medical University, Shijiazhuang, Hebei, 050011, China
| | - Gang Wang
- Department of Pancreatic and Biliary Surgery, The First Affiliated Hospital of Harbin Medical University, Harbin, Heilongjiang, 150007, China
- Key Laboratory of Hepatosplenic Surgery, Ministry of Education, The First Affiliated Hospital of Harbin Medical University, Harbin, Heilongjiang, 150007, China
| | - Weikuan Gu
- Department of Orthopedic Surgery and BME-Campbell Clinic, University of Tennessee Health Science Center, Memphis, TN, 38163, USA
- Research Service, Memphis VA Medical Center, 1030 Jefferson Avenue, Memphis, TN, 38104, USA
- Department of Pharmaceutical Sciences, University of Tennessee Health Science Center, 881 Madison Ave, Memphis, TN, 38163, USA
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3
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Horvath S, Zhang J, Haghani A, Lu AT, Fei Z. Fundamental equations linking methylation dynamics to maximum lifespan in mammals. Nat Commun 2024; 15:8093. [PMID: 39285199 PMCID: PMC11405513 DOI: 10.1038/s41467-024-51855-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2023] [Accepted: 08/20/2024] [Indexed: 09/22/2024] Open
Abstract
We describe a framework that addresses concern that the rate of change in any aging biomarker displays a trivial inverse relation with maximum lifespan. We apply this framework to methylation data from the Mammalian Methylation Consortium. We study the relationship of lifespan with the average rate of change in methylation (AROCM) from two datasets: one with 90 dog breeds and the other with 125 mammalian species. After examining 54 chromatin states, we conclude three key findings: First, a reciprocal relationship exists between the AROCM in bivalent promoter regions and maximum mammalian lifespan: AROCM ∝ 1/MaxLifespan. Second, the correlation between average methylation and age bears no relation to maximum lifespan, Cor(Methyl,Age) ⊥ MaxLifespan. Third, the rate of methylation change in young animals is related to that in old animals: Young animals' AROCM ∝ Old AROCM. These findings critically hinge on the chromatin context, as different results emerge in other chromatin contexts.
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Affiliation(s)
- Steve Horvath
- Department of Human Genetics, University of California, Los Angeles, CA, USA.
- Department of Biostatistics, University of California, Los Angeles, CA, USA.
- Altos Labs, San Diego, CA, USA.
| | - Joshua Zhang
- Department of Human Genetics, University of California, Los Angeles, CA, USA
| | - Amin Haghani
- Department of Human Genetics, University of California, Los Angeles, CA, USA
- Altos Labs, San Diego, CA, USA
| | - Ake T Lu
- Department of Human Genetics, University of California, Los Angeles, CA, USA
- Altos Labs, San Diego, CA, USA
| | - Zhe Fei
- Department of Statistics, University of California, Riverside, CA, USA.
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4
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Hao Y, Han K, Wang T, Yu J, Ding H, Dao F. Exploring the potential of epigenetic clocks in aging research. Methods 2024; 231:37-44. [PMID: 39251102 DOI: 10.1016/j.ymeth.2024.09.001] [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: 07/01/2024] [Revised: 07/26/2024] [Accepted: 09/01/2024] [Indexed: 09/11/2024] Open
Abstract
The process of aging is a notable risk factor for numerous age-related illnesses. Hence, a reliable technique for evaluating biological age or the pace of aging is crucial for understanding the aging process and its influence on the progression of disease. Epigenetic alterations are recognized as a prominent biomarker of aging, and epigenetic clocks formulated on this basis have been shown to provide precise estimations of chronological age. Extensive research has validated the effectiveness of epigenetic clocks in determining aging rates, identifying risk factors for aging, evaluating the impact of anti-aging interventions, and predicting the emergence of age-related diseases. This review provides a detailed overview of the theoretical principles underlying the development of epigenetic clocks and their utility in aging research. Furthermore, it explores the existing obstacles and possibilities linked to epigenetic clocks and proposes potential avenues for future studies in this field.
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Affiliation(s)
- Yuduo Hao
- Center for Informational Biology, University of Electronic Science and Technology of China, Chengdu 610054, China
| | - Kaiyuan Han
- Center for Informational Biology, University of Electronic Science and Technology of China, Chengdu 610054, China
| | - Ting Wang
- Center for Informational Biology, University of Electronic Science and Technology of China, Chengdu 610054, China
| | - Junwen Yu
- Center for Informational Biology, University of Electronic Science and Technology of China, Chengdu 610054, China
| | - Hui Ding
- Center for Informational Biology, University of Electronic Science and Technology of China, Chengdu 610054, China.
| | - Fuying Dao
- School of Biological Sciences, Nanyang Technological University, Singapore 639798, Singapore.
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5
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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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6
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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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7
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Félix J, Martínez de Toda I, Díaz-Del Cerro E, González-Sánchez M, De la Fuente M. Frailty and biological age. Which best describes our aging and longevity? Mol Aspects Med 2024; 98:101291. [PMID: 38954948 DOI: 10.1016/j.mam.2024.101291] [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: 11/09/2023] [Revised: 05/01/2024] [Accepted: 06/26/2024] [Indexed: 07/04/2024]
Abstract
Frailty and Biological Age are two closely related concepts; however, frailty is a multisystem geriatric syndrome that applies to elderly subjects, whereas biological age is a gerontologic way to describe the rate of aging of each individual, which can be used from the beginning of the aging process, in adulthood. If frailty reaches less consensus on the definition, it is a term much more widely used than this of biological age, which shows a clearer definition but is scarcely employed in social and medical fields. In this review, we suggest that this Biological Age is the best to describe how we are aging and determine our longevity, and several examples support our proposal.
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Affiliation(s)
- Judith Félix
- Department of Genetics, Physiology, and Microbiology (Unit of Animal Physiology), Faculty of Biological Sciences, Complutense University of Madrid, 28040 Madrid, Spain; Institute of Investigation Hospital 12 Octubre (imas12), 28041 Madrid, Spain.
| | - Irene Martínez de Toda
- Department of Genetics, Physiology, and Microbiology (Unit of Animal Physiology), Faculty of Biological Sciences, Complutense University of Madrid, 28040 Madrid, Spain; Institute of Investigation Hospital 12 Octubre (imas12), 28041 Madrid, Spain.
| | - Estefanía Díaz-Del Cerro
- Department of Genetics, Physiology, and Microbiology (Unit of Animal Physiology), Faculty of Biological Sciences, Complutense University of Madrid, 28040 Madrid, Spain; Institute of Investigation Hospital 12 Octubre (imas12), 28041 Madrid, Spain.
| | - Mónica González-Sánchez
- Department of Genetics, Physiology, and Microbiology (Unit of Genetics), Faculty of Biological Sciences, Complutense University of Madrid, 28040 Madrid, Spain; Institute of Investigation Hospital 12 Octubre (imas12), 28041 Madrid, Spain.
| | - Mónica De la Fuente
- Department of Genetics, Physiology, and Microbiology (Unit of Animal Physiology), Faculty of Biological Sciences, Complutense University of Madrid, 28040 Madrid, Spain; Institute of Investigation Hospital 12 Octubre (imas12), 28041 Madrid, Spain.
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8
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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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9
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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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10
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Lujan C, Tyler EJ, Ecker S, Webster AP, Stead ER, Martinez-Miguel VE, Milligan D, Garbe JC, Stampfer MR, Beck S, Lowe R, Bishop CL, Bjedov I. An expedited screening platform for the discovery of anti-ageing compounds in vitro and in vivo. Genome Med 2024; 16:85. [PMID: 38956711 PMCID: PMC11218148 DOI: 10.1186/s13073-024-01349-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2023] [Accepted: 05/21/2024] [Indexed: 07/04/2024] Open
Abstract
BACKGROUND Restraining or slowing ageing hallmarks at the cellular level have been proposed as a route to increased organismal lifespan and healthspan. Consequently, there is great interest in anti-ageing drug discovery. However, this currently requires laborious and lengthy longevity analysis. Here, we present a novel screening readout for the expedited discovery of compounds that restrain ageing of cell populations in vitro and enable extension of in vivo lifespan. METHODS Using Illumina methylation arrays, we monitored DNA methylation changes accompanying long-term passaging of adult primary human cells in culture. This enabled us to develop, test, and validate the CellPopAge Clock, an epigenetic clock with underlying algorithm, unique among existing epigenetic clocks for its design to detect anti-ageing compounds in vitro. Additionally, we measured markers of senescence and performed longevity experiments in vivo in Drosophila, to further validate our approach to discover novel anti-ageing compounds. Finally, we bench mark our epigenetic clock with other available epigenetic clocks to consolidate its usefulness and specialisation for primary cells in culture. RESULTS We developed a novel epigenetic clock, the CellPopAge Clock, to accurately monitor the age of a population of adult human primary cells. We find that the CellPopAge Clock can detect decelerated passage-based ageing of human primary cells treated with rapamycin or trametinib, well-established longevity drugs. We then utilise the CellPopAge Clock as a screening tool for the identification of compounds which decelerate ageing of cell populations, uncovering novel anti-ageing drugs, torin2 and dactolisib (BEZ-235). We demonstrate that delayed epigenetic ageing in human primary cells treated with anti-ageing compounds is accompanied by a reduction in senescence and ageing biomarkers. Finally, we extend our screening platform in vivo by taking advantage of a specially formulated holidic medium for increased drug bioavailability in Drosophila. We show that the novel anti-ageing drugs, torin2 and dactolisib (BEZ-235), increase longevity in vivo. CONCLUSIONS Our method expands the scope of CpG methylation profiling to accurately and rapidly detecting anti-ageing potential of drugs using human cells in vitro, and in vivo, providing a novel accelerated discovery platform to test sought after anti-ageing compounds and geroprotectors.
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Affiliation(s)
- Celia Lujan
- UCL Cancer Institute, Paul O'Gorman Building, University College London, 72 Huntley Street London, London, WC1E 6DD, UK
| | - Eleanor Jane Tyler
- Centre for Cell Biology and Cutaneous Research, Blizard Institute, Barts and The London Faculty of Medicine and Dentistry, Queen Mary University of London, 4 Newark Street, London, E1 2AT, UK
| | - Simone Ecker
- UCL Cancer Institute, Paul O'Gorman Building, University College London, 72 Huntley Street London, London, WC1E 6DD, UK
| | - Amy Philomena Webster
- UCL Cancer Institute, Paul O'Gorman Building, University College London, 72 Huntley Street London, London, WC1E 6DD, UK
- University of Exeter Medical School, Exeter, UK
| | - Eleanor Rachel Stead
- UCL Cancer Institute, Paul O'Gorman Building, University College London, 72 Huntley Street London, London, WC1E 6DD, UK
| | - Victoria Eugenia Martinez-Miguel
- UCL Cancer Institute, Paul O'Gorman Building, University College London, 72 Huntley Street London, London, WC1E 6DD, UK
- Max Planck Institute for Biology of Ageing, Cologne, Germany
| | - Deborah Milligan
- Centre for Cell Biology and Cutaneous Research, Blizard Institute, Barts and The London Faculty of Medicine and Dentistry, Queen Mary University of London, 4 Newark Street, London, E1 2AT, UK
| | - James Charles Garbe
- Biological Systems and Engineering Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA
| | - Martha Ruskin Stampfer
- Biological Systems and Engineering Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA
| | - Stephan Beck
- UCL Cancer Institute, Paul O'Gorman Building, University College London, 72 Huntley Street London, London, WC1E 6DD, UK.
| | - Robert Lowe
- Centre for Genomics and Child Health, Blizard Institute, Barts and The London Faculty of Medicine and Dentistry, Queen Mary University of London, 4 Newark Street, London, E1 2AT, UK.
| | - Cleo Lucinda Bishop
- Centre for Cell Biology and Cutaneous Research, Blizard Institute, Barts and The London Faculty of Medicine and Dentistry, Queen Mary University of London, 4 Newark Street, London, E1 2AT, UK.
| | - Ivana Bjedov
- UCL Cancer Institute, Paul O'Gorman Building, University College London, 72 Huntley Street London, London, WC1E 6DD, UK.
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11
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Wang H, Xiao F, Gao Z, Guo L, Yang L, Li G, Kong Q. Methylation entropy landscape of Chinese long-lived individuals reveals lower epigenetic noise related to human healthy aging. Aging Cell 2024; 23:e14163. [PMID: 38566438 PMCID: PMC11258444 DOI: 10.1111/acel.14163] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2023] [Revised: 03/12/2024] [Accepted: 03/15/2024] [Indexed: 04/04/2024] Open
Abstract
The transition from ordered to noisy is a significant epigenetic signature of aging and age-related disease. As a paradigm of healthy human aging and longevity, long-lived individuals (LLI, >90 years old) may possess characteristic strategies in coping with the disordered epigenetic regulation. In this study, we constructed high-resolution blood epigenetic noise landscapes for this cohort by a methylation entropy (ME) method using whole genome bisulfite sequencing (WGBS). Although a universal increase in global ME occurred with chronological age in general control samples, this trend was suppressed in LLIs. Importantly, we identified 38,923 genomic regions with LLI-specific lower ME (LLI-specific lower entropy regions, for short, LLI-specific LERs). These regions were overrepresented in promoters, which likely function in transcriptional noise suppression. Genes associated with LLI-specific LERs have a considerable impact on SNP-based heritability of some aging-related disorders (e.g., asthma and stroke). Furthermore, neutrophil was identified as the primary cell type sustaining LLI-specific LERs. Our results highlight the stability of epigenetic order in promoters of genes involved with aging and age-related disorders within LLI epigenomes. This unique epigenetic feature reveals a previously unknown role of epigenetic order maintenance in specific genomic regions of LLIs, which helps open a new avenue on the epigenetic regulation mechanism in human healthy aging and longevity.
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Affiliation(s)
- Hao‐Tian Wang
- Key Laboratory of Genetic Evolution & Animal Models (Chinese Academy of Sciences), Key Laboratory of Healthy Aging Research of Yunnan Province, Kunming Key Laboratory of Healthy Aging StudyKIZ/CUHK Joint Laboratory of Bioresources and Molecular Research in Common Diseases, Kunming Institute of Zoology, Chinese Academy of SciencesKunmingChina
| | - Fu‐Hui Xiao
- Key Laboratory of Genetic Evolution & Animal Models (Chinese Academy of Sciences), Key Laboratory of Healthy Aging Research of Yunnan Province, Kunming Key Laboratory of Healthy Aging StudyKIZ/CUHK Joint Laboratory of Bioresources and Molecular Research in Common Diseases, Kunming Institute of Zoology, Chinese Academy of SciencesKunmingChina
| | - Zong‐Liang Gao
- Key Laboratory of Genetic Evolution & Animal Models (Chinese Academy of Sciences), Key Laboratory of Healthy Aging Research of Yunnan Province, Kunming Key Laboratory of Healthy Aging StudyKIZ/CUHK Joint Laboratory of Bioresources and Molecular Research in Common Diseases, Kunming Institute of Zoology, Chinese Academy of SciencesKunmingChina
| | - Li‐Yun Guo
- Key Laboratory of Genetic Evolution & Animal Models (Chinese Academy of Sciences), Key Laboratory of Healthy Aging Research of Yunnan Province, Kunming Key Laboratory of Healthy Aging StudyKIZ/CUHK Joint Laboratory of Bioresources and Molecular Research in Common Diseases, Kunming Institute of Zoology, Chinese Academy of SciencesKunmingChina
| | - Li‐Qin Yang
- Key Laboratory of Genetic Evolution & Animal Models (Chinese Academy of Sciences), Key Laboratory of Healthy Aging Research of Yunnan Province, Kunming Key Laboratory of Healthy Aging StudyKIZ/CUHK Joint Laboratory of Bioresources and Molecular Research in Common Diseases, Kunming Institute of Zoology, Chinese Academy of SciencesKunmingChina
| | - Gong‐Hua Li
- Key Laboratory of Genetic Evolution & Animal Models (Chinese Academy of Sciences), Key Laboratory of Healthy Aging Research of Yunnan Province, Kunming Key Laboratory of Healthy Aging StudyKIZ/CUHK Joint Laboratory of Bioresources and Molecular Research in Common Diseases, Kunming Institute of Zoology, Chinese Academy of SciencesKunmingChina
| | - Qing‐Peng Kong
- Key Laboratory of Genetic Evolution & Animal Models (Chinese Academy of Sciences), Key Laboratory of Healthy Aging Research of Yunnan Province, Kunming Key Laboratory of Healthy Aging StudyKIZ/CUHK Joint Laboratory of Bioresources and Molecular Research in Common Diseases, Kunming Institute of Zoology, Chinese Academy of SciencesKunmingChina
- CAS Center for Excellence in Animal Evolution and GeneticsChinese Academy of SciencesKunmingChina
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12
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Zhu T, Tong H, Du Z, Beck S, Teschendorff AE. An improved epigenetic counter to track mitotic age in normal and precancerous tissues. Nat Commun 2024; 15:4211. [PMID: 38760334 PMCID: PMC11101651 DOI: 10.1038/s41467-024-48649-8] [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: 09/24/2023] [Accepted: 05/09/2024] [Indexed: 05/19/2024] Open
Abstract
The cumulative number of stem cell divisions in a tissue, known as mitotic age, is thought to be a major determinant of cancer-risk. Somatic mutational and DNA methylation (DNAm) clocks are promising tools to molecularly track mitotic age, yet their relationship is underexplored and their potential for cancer risk prediction in normal tissues remains to be demonstrated. Here we build and validate an improved pan-tissue DNAm counter of total mitotic age called stemTOC. We demonstrate that stemTOC's mitotic age proxy increases with the tumor cell-of-origin fraction in each of 15 cancer-types, in precancerous lesions, and in normal tissues exposed to major cancer risk factors. Extensive benchmarking against 6 other mitotic counters shows that stemTOC compares favorably, specially in the preinvasive and normal-tissue contexts. By cross-correlating stemTOC to two clock-like somatic mutational signatures, we confirm the mitotic-like nature of only one of these. Our data points towards DNAm as a promising molecular substrate for detecting mitotic-age increases in normal tissues and precancerous lesions, and hence for developing cancer-risk prediction strategies.
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Affiliation(s)
- Tianyu Zhu
- CAS Key Laboratory of Computational Biology, CAS-MPG Partner Institute for Computational Biology, Shanghai Institute of Nutrition and Health, Shanghai Institute for Biological Sciences, University of Chinese Academy of Sciences, Chinese Academy of Sciences, 320 Yue Yang Road, Shanghai, 200031, China
| | - Huige Tong
- CAS Key Laboratory of Computational Biology, CAS-MPG Partner Institute for Computational Biology, Shanghai Institute of Nutrition and Health, Shanghai Institute for Biological Sciences, University of Chinese Academy of Sciences, Chinese Academy of Sciences, 320 Yue Yang Road, Shanghai, 200031, China
| | - Zhaozhen Du
- CAS Key Laboratory of Computational Biology, CAS-MPG Partner Institute for Computational Biology, Shanghai Institute of Nutrition and Health, Shanghai Institute for Biological Sciences, University of Chinese Academy of Sciences, Chinese Academy of Sciences, 320 Yue Yang Road, Shanghai, 200031, China
| | - Stephan Beck
- Medical Genomics Group, UCL Cancer Institute, University College London, 72 Huntley Street, WC1E 6BT, London, UK
| | - Andrew E Teschendorff
- CAS Key Laboratory of Computational Biology, CAS-MPG Partner Institute for Computational Biology, Shanghai Institute of Nutrition and Health, Shanghai Institute for Biological Sciences, University of Chinese Academy of Sciences, Chinese Academy of Sciences, 320 Yue Yang Road, Shanghai, 200031, China.
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13
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Wang T, Huang Y, Yang J. Statistical Models for High-Risk Intestinal Metaplasia with DNA Methylation Profiling. EPIGENOMES 2024; 8:19. [PMID: 38804368 PMCID: PMC11130831 DOI: 10.3390/epigenomes8020019] [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: 03/26/2024] [Revised: 04/28/2024] [Accepted: 05/09/2024] [Indexed: 05/29/2024] Open
Abstract
We consider the newly developed multinomial mixed-link models for a high-risk intestinal metaplasia (IM) study with DNA methylation data. Different from the traditional multinomial logistic models commonly used for categorical responses, the mixed-link models allow us to select the most appropriate link function for each category. We show that the selected multinomial mixed-link model (Model 1) using the total number of stem cell divisions (TNSC) based on DNA methylation data outperforms the traditional logistic models in terms of cross-entropy loss from ten-fold cross-validations with significant p-values 8.12×10-4 and 6.94×10-5. Based on our selected model, the significance of TNSC's effect in predicting the risk of IM is justified with a p-value less than 10-6. We also select the most appropriate mixed-link models (Models 2 and 3) when an additional covariate, the status of gastric atrophy, is available. When the status is negative, mild, or moderate, we recommend Model 2; otherwise, we prefer Model 3. Both Models 2 and 3 can predict the risk of IM significantly better than Model 1, which justifies that the status of gastric atrophy is informative in predicting the risk of IM.
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Affiliation(s)
| | | | - Jie Yang
- Department of Mathematics, Statistics, and Computer Science, University of Illinois at Chicago, Chicago, IL 60607, USA; (T.W.); (Y.H.)
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14
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Lim GM, Maharajan N, Cho GW. How calorie restriction slows aging: an epigenetic perspective. J Mol Med (Berl) 2024; 102:629-640. [PMID: 38456926 DOI: 10.1007/s00109-024-02430-y] [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: 05/02/2023] [Revised: 01/14/2024] [Accepted: 02/07/2024] [Indexed: 03/09/2024]
Abstract
Genomic instability and epigenetic alterations are some of the prominent factors affecting aging. Age-related heterochromatin loss and decreased whole-genome DNA methylation are associated with abnormal gene expression, leading to diseases and genomic instability. Modulation of these epigenetic changes is crucial for preserving genomic integrity and controlling cellular identity is important for slowing the aging process. Numerous studies have shown that caloric restriction is the gold standard for promoting longevity and healthy aging in various species ranging from rodents to primates. It can be inferred that delaying of aging through the main effector such as calorie restriction is involved in cellular identity and epigenetic modification. Thus, an understanding of aging through calorie restriction may seek a more in-depth understanding. In this review, we discuss how caloric restriction promotes longevity and healthy aging through genomic stability and epigenetic alterations. We have also highlighted how the effectors of caloric restriction are involved in modulating the chromatin-based barriers.
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Affiliation(s)
- Gyeong Min Lim
- Department of Biological Science, College of Natural Science, Chosun University, 309 Pilmun-Daero, Dong-Gu, Gwangju, 61452, Republic of Korea
- BK21 FOUR Education Research Group for Age-Associated Disorder Control Technology, Department of Integrative Biological Science, Chosun University, Gwangju, 61452, Republic of Korea
| | - Nagarajan Maharajan
- The Department of Obstetrics & Gynecology and Reproductive Sciences, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Gwang-Won Cho
- Department of Biological Science, College of Natural Science, Chosun University, 309 Pilmun-Daero, Dong-Gu, Gwangju, 61452, Republic of Korea.
- BK21 FOUR Education Research Group for Age-Associated Disorder Control Technology, Department of Integrative Biological Science, Chosun University, Gwangju, 61452, Republic of Korea.
- The Basic Science Institute of Chosun University, Chosun University, Gwangju, 61452, Republic of Korea.
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15
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Flori L, Spezzini J, Calderone V, Testai L. Role of mitochondrial potassium channels in ageing. Mitochondrion 2024; 76:101857. [PMID: 38403095 DOI: 10.1016/j.mito.2024.101857] [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: 12/01/2023] [Revised: 02/13/2024] [Accepted: 02/22/2024] [Indexed: 02/27/2024]
Abstract
Ageing is described as an inevitable decline in body functions over time and an increase in susceptibility to age-related diseases. Therefore, the increase of life expectancy is also viewed as a condition in which many elderly will develop age-related diseases and disabilities, such as cardiovascular, metabolic, neurological and oncological ones. Currently, several recognized cellular hallmarks of senescence are taken in consideration to evaluate the level of biological ageing and are the topic to plan preventive/curative anti-ageing interventions, including genomic instability, epigenetic alterations, and mitochondrial dysfunction. In this scenario, alterations in the function/expression of mitochondrial ion channels have been found in ageing and associated to an impairment of calcium cycling and a reduced mitochondrial membrane potential. Although several ion channels have been described at mitochondrial level, undoubtedly the mitochondrial potassium (mitoK) channels are the most investigated. Therefore, this review summarized the evidence that sheds to light a correlation between age-related diseases and alteration of mitoK channels, focusing the attention of the main age-related diseases, i.e. cardiovascular, neurological and oncological ones.
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Affiliation(s)
- Lorenzo Flori
- Department of Pharmacy, University of Pisa, Pisa, Italy
| | | | - Vincenzo Calderone
- Department of Pharmacy, University of Pisa, Pisa, Italy; Interdepartmental Research Centre of Ageing Biology and Pathology, University of Pisa, Pisa, Italy
| | - Lara Testai
- Department of Pharmacy, University of Pisa, Pisa, Italy; Interdepartmental Research Centre of Ageing Biology and Pathology, University of Pisa, Pisa, Italy.
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16
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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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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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Knight AK, Spencer JB, Smith AK. DNA methylation as a window into female reproductive aging. Epigenomics 2024; 16:175-188. [PMID: 38131149 PMCID: PMC10841041 DOI: 10.2217/epi-2023-0298] [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: 08/24/2023] [Accepted: 12/05/2023] [Indexed: 12/23/2023] Open
Abstract
People with ovaries experience reproductive aging as their reproductive function and system declines. This has significant implications for both fertility and long-term health, with people experiencing an increased risk of cardiometabolic disorders after menopause. Reproductive aging can be assessed through markers of ovarian reserve, response to fertility treatment or molecular biomarkers, including DNA methylation. Changes in DNA methylation with age associate with poorer reproductive outcomes, and epigenome-wide studies can provide insight into genes and pathways involved. DNA methylation-based epigenetic clocks can quantify biological age in reproductive tissues and systemically. This review provides an overview of hallmarks and theories of aging in the context of the reproductive system, and then focuses on studies of DNA methylation in reproductive tissues.
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Affiliation(s)
- Anna K Knight
- Research Division, Department of Gynecology & Obstetrics, Emory University School of Medicine, Atlanta, GA 30322, USA
| | - Jessica B Spencer
- Reproductive Endocrinology & Infertility Division, Department of Gynecology & Obstetrics, Emory University School of Medicine, Atlanta, GA 30322, USA
| | - Alicia K Smith
- Research Division, Department of Gynecology & Obstetrics, Emory University School of Medicine, Atlanta, GA 30322, USA
- Reproductive Endocrinology & Infertility Division, Department of Gynecology & Obstetrics, Emory University School of Medicine, Atlanta, GA 30322, USA
- Department of Psychiatry & Behavioral Sciences, Emory University School of Medicine, Atlanta, GA 30322, USA
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19
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Mozhui K, Kim H, Villani F, Haghani A, Sen S, Horvath S. Pleiotropic influence of DNA methylation QTLs on physiological and ageing traits. Epigenetics 2023; 18:2252631. [PMID: 37691384 PMCID: PMC10496549 DOI: 10.1080/15592294.2023.2252631] [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: 05/01/2023] [Revised: 07/31/2023] [Accepted: 08/16/2023] [Indexed: 09/12/2023] Open
Abstract
DNA methylation is influenced by genetic and non-genetic factors. Here, we chart quantitative trait loci (QTLs) that modulate levels of methylation at highly conserved CpGs using liver methylome data from mouse strains belonging to the BXD family. A regulatory hotspot on chromosome 5 had the highest density of trans-acting methylation QTLs (trans-meQTLs) associated with multiple distant CpGs. We refer to this locus as meQTL.5a. Trans-modulated CpGs showed age-dependent changes and were enriched in developmental genes, including several members of the MODY pathway (maturity onset diabetes of the young). The joint modulation by genotype and ageing resulted in a more 'aged methylome' for BXD strains that inherited the DBA/2J parental allele at meQTL.5a. Further, several gene expression traits, body weight, and lipid levels mapped to meQTL.5a, and there was a modest linkage with lifespan. DNA binding motif and protein-protein interaction enrichment analyses identified the hepatic nuclear factor, Hnf1a (MODY3 gene in humans), as a strong candidate. The pleiotropic effects of meQTL.5a could contribute to variations in body size and metabolic traits, and influence CpG methylation and epigenetic ageing that could have an impact on lifespan.
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Affiliation(s)
- Khyobeni Mozhui
- Department of Preventive Medicine, University of Tennessee Health Science Center, Memphis, TN, USA
- Department of Genetics, Genomics and Informatics, University of Tennessee Health Science Center, Memphis, TN, USA
| | - Hyeonju Kim
- Department of Preventive Medicine, University of Tennessee Health Science Center, Memphis, TN, USA
| | - Flavia Villani
- Department of Genetics, Genomics and Informatics, University of Tennessee Health Science Center, Memphis, TN, USA
| | - Amin Haghani
- Department of Human Genetics, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
- Altos Labs, San Diego, CA, USA
| | - Saunak Sen
- Department of Preventive Medicine, University of Tennessee Health Science Center, Memphis, TN, USA
| | - Steve Horvath
- Department of Human Genetics, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
- Altos Labs, San Diego, CA, USA
- Department of Biostatistics, Fielding School of Public Health, University of California Los Angeles, Los Angeles, CA, USA
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20
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Abstract
Keratinocyte senescence contributes to skin ageing and epidermal dysfunction. According to the existing knowledge, the transcription factor ΔNp63α plays pivotal roles in differentiation and proliferation of keratinocytes. It is traditionally accepted that ΔNp63α exerts its functions via binding to promoter regions to activate or repress gene transcription. However, accumulating evidence demonstrates that ΔNp63α can bind to elements away from promoter regions of its target genes, mediating epigenetic regulation. On the other hand, several epigenetic alterations, including DNA methylation, histone modification and variation, chromatin remodelling, as well as enhancer-promoter looping, are found to be related to cell senescence. To systematically elucidate how ΔNp63α affects keratinocyte senescence via epigenetic regulation, we comprehensively compiled the literatures on the roles of ΔNp63α in keratinocyte senescence, epigenetics in cellular senescence, and the relation between ΔNp63α-mediated epigenetic regulation and keratinocyte senescence. Based on the published data, we conclude that ΔNp63α mediates epigenetic regulation via multiple mechanisms: recruiting epigenetic enzymes to modify DNA or histones, coordinating chromatin remodelling complexes (CRCs) or regulating their expression, and mediating enhancer-promoter looping. Consequently, the expression of genes related to cell cycle is modulated, and proliferation of keratinocytes and renewal of stem cells are maintained, by ΔNp63α. During skin inflammaging, the decline of ΔNp63α may lead to epigenetic dysregulation, resultantly deteriorating keratinocyte senescence.
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Affiliation(s)
- Linghan Kuang
- Department of Laboratory Medicine, West China Second University Hospital, Sichuan University, Chengdu 610041, China.,Key Laboratory of Birth Defects and Related Diseases of Women and Children (Sichuan University), Ministry of Education, Chengdu 610041, China
| | - Chenghua Li
- Center of Growth, Metabolism and Aging, Key Laboratory of Biological Resources and Ecological Environment of Ministry of Education, College of Life Sciences, Sichuan University, Chengdu 610065, China
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21
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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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22
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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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23
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Harvanek ZM, Boks MP, Vinkers CH, Higgins-Chen AT. The Cutting Edge of Epigenetic Clocks: In Search of Mechanisms Linking Aging and Mental Health. Biol Psychiatry 2023; 94:694-705. [PMID: 36764569 PMCID: PMC10409884 DOI: 10.1016/j.biopsych.2023.02.001] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/31/2022] [Revised: 01/31/2023] [Accepted: 02/01/2023] [Indexed: 02/11/2023]
Abstract
Individuals with psychiatric disorders are at increased risk of age-related diseases and early mortality. Recent studies demonstrate that this link between mental health and aging is reflected in epigenetic clocks, aging biomarkers based on DNA methylation. The reported relationships between epigenetic clocks and mental health are mostly correlational, and the mechanisms are poorly understood. Here, we review recent progress concerning the molecular and cellular processes underlying epigenetic clocks as well as novel technologies enabling further studies of the causes and consequences of epigenetic aging. We then review the current literature on how epigenetic clocks relate to specific aspects of mental health, such as stress, medications, substance use, health behaviors, and symptom clusters. We propose an integrated framework where mental health and epigenetic aging are each broken down into multiple distinct processes, which are then linked to each other, using stress and schizophrenia as examples. This framework incorporates the heterogeneity and complexity of both mental health conditions and aging, may help reconcile conflicting results, and provides a basis for further hypothesis-driven research in humans and model systems to investigate potentially causal mechanisms linking aging and mental health.
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Affiliation(s)
- Zachary M Harvanek
- Department of Psychiatry, Yale University School of Medicine, New Haven, Connecticut
| | - Marco P Boks
- Department of Psychiatry, University Medical Center Utrecht Brain Center, University of Utrecht, Utrecht, the Netherlands
| | - Christiaan H Vinkers
- Department of Psychiatry, Amsterdam University Medical Center, location Vrije Universiteit Amsterdam, Amsterdam, the Netherlands; Mood, Anxiety, Psychosis, Sleep & Stress program, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
| | - Albert T Higgins-Chen
- Department of Psychiatry, Yale University School of Medicine, New Haven, Connecticut; Department of Pathology, Yale University School of Medicine, New Haven, Connecticut.
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24
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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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25
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Petrashen AP, Lin Y, Kun B, Kreiling JA. A cluster of X-linked miRNAs are de-repressed with age in mouse liver and target growth hormone signaling. FRONTIERS IN AGING 2023; 4:1261121. [PMID: 37881503 PMCID: PMC10594992 DOI: 10.3389/fragi.2023.1261121] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/18/2023] [Accepted: 09/28/2023] [Indexed: 10/27/2023]
Abstract
Growth hormone (GH) signaling influences lifespan in a wide variety of mammalian species. We previously reported that a cluster of miRNAs located on the X-chromosome are de-repressed with age in male mouse liver, and a subset, the mir-465 family, can directly attenuate expression of the growth hormone receptor (GHR) in vitro leading to a reduction in GH signaling. Here we show that this cluster of miRNAs is also upregulated in the liver with age in females, and that calorie restriction and the Ames dwarf genotype, both known to delay aging, attenuate the upregulation of the miRNA cluster. Upregulation of mir-465 in vivo leads to a reduction in GHR mRNA in the liver and an attenuation of GH signaling, indicated by a reduction in GHR, IGF-1, IGFBP3, and ALS mRNA expression. There is a corresponding reduction in IGF-1 protein levels in the liver and plasma. These results suggest that the age-associated upregulation of the X-chromosomal cluster of miRNAs could influence lifespan.
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Affiliation(s)
| | | | | | - Jill A. Kreiling
- Department of Molecular Biology, Cell Biology and Biochemistry, Center for the Biology of Aging, Brown University, Providence, RI, United States
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26
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Lyons CE, Razzoli M, Bartolomucci A. The impact of life stress on hallmarks of aging and accelerated senescence: Connections in sickness and in health. Neurosci Biobehav Rev 2023; 153:105359. [PMID: 37586578 PMCID: PMC10592082 DOI: 10.1016/j.neubiorev.2023.105359] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2023] [Revised: 07/03/2023] [Accepted: 08/10/2023] [Indexed: 08/18/2023]
Abstract
Chronic stress is a risk factor for numerous aging-related diseases and has been shown to shorten lifespan in humans and other social mammals. Yet how life stress causes such a vast range of diseases is still largely unclear. In recent years, the impact of stress on health and aging has been increasingly associated with the dysregulation of the so-called hallmarks of aging. These are basic biological mechanisms that influence intrinsic cellular functions and whose alteration can lead to accelerated aging. Here, we review correlational and experimental literature (primarily focusing on evidence from humans and murine models) on the contribution of life stress - particularly stress derived from adverse social environments - to trigger hallmarks of aging, including cellular senescence, sterile inflammation, telomere shortening, production of reactive oxygen species, DNA damage, and epigenetic changes. We also evaluate the validity of stress-induced senescence and accelerated aging as an etiopathological proposition. Finally, we highlight current gaps of knowledge and future directions for the field, and discuss perspectives for translational geroscience.
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Affiliation(s)
- Carey E Lyons
- Department of Integrative Biology and Physiology, University of Minnesota, Minneapolis, MN, USA; Graduate Program in Neuroscience, University of Minnesota, Minneapolis, MN, USA
| | - Maria Razzoli
- Department of Integrative Biology and Physiology, University of Minnesota, Minneapolis, MN, USA
| | - Alessandro Bartolomucci
- Department of Integrative Biology and Physiology, University of Minnesota, Minneapolis, MN, USA; Department of Medicine and Surgery, University of Parma, Parma, Italy.
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27
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Henry JP. [Epigenetics and aging: How is epigenetics linked to aging?]. Med Sci (Paris) 2023; 39:732-737. [PMID: 37943133 DOI: 10.1051/medsci/2023122] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2023] Open
Abstract
Links between aging and epigenetics have been revealed by bio-mathematicians. Methylation of cytosine, which is a characteristic of the epigenome, varies with age on some ADN loci, increasing or decreasing. From an analysis of the methylome, algorithms giving an "epigenetic age" were obtained, strongly correlated with the age. Surprisingly, this approach could be applied consistently to different tissues or unpurified cells. It was successfully applied to tissues of 185 mammalian species. The epigenetic age of embryonic pluripotent stem cells is nearly zero and it decreases to "ground zero" during gastrulation. The average methylation curve as a function of age allows discrimination between slowly or rapidly aging individuals. At the present time, more than 10 different epigenetic clocks have been proposed for medical applications. The localization of aging-sensitive CpG pairs on the genome revealed networks of "co-methylation", involved in different functions such as regulation of morphogenesis or cell differentiation. From these studies, aging appears as a continuous process, with the epigenetic clock starting to "tick" in the embryo.
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Affiliation(s)
- Jean-Pierre Henry
- Ancien directeur de l'institut de biologie physico-chimique, Fondation Edmond de Rothschild, 13 rue Pierre et Marie Curie, 75005 Paris, France
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28
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Lu AT, Fei Z, Haghani A, Robeck TR, Zoller JA, Li CZ, Lowe R, Yan Q, Zhang J, Vu H, Ablaeva J, Acosta-Rodriguez VA, Adams DM, Almunia J, Aloysius A, Ardehali R, Arneson A, Baker CS, Banks G, Belov K, Bennett NC, Black P, Blumstein DT, Bors EK, Breeze CE, Brooke RT, Brown JL, Carter GG, Caulton A, Cavin JM, Chakrabarti L, Chatzistamou I, Chen H, Cheng K, Chiavellini P, Choi OW, Clarke SM, Cooper LN, Cossette ML, Day J, DeYoung J, DiRocco S, Dold C, Ehmke EE, Emmons CK, Emmrich S, Erbay E, Erlacher-Reid C, Faulkes CG, Ferguson SH, Finno CJ, Flower JE, Gaillard JM, Garde E, Gerber L, Gladyshev VN, Gorbunova V, Goya RG, Grant MJ, Green CB, Hales EN, Hanson MB, Hart DW, Haulena M, Herrick K, Hogan AN, Hogg CJ, Hore TA, Huang T, Izpisua Belmonte JC, Jasinska AJ, Jones G, Jourdain E, Kashpur O, Katcher H, Katsumata E, Kaza V, Kiaris H, Kobor MS, Kordowitzki P, Koski WR, Krützen M, Kwon SB, Larison B, Lee SG, Lehmann M, Lemaitre JF, Levine AJ, Li C, Li X, Lim AR, Lin DTS, Lindemann DM, Little TJ, Macoretta N, Maddox D, Matkin CO, Mattison JA, McClure M, Mergl J, Meudt JJ, Montano GA, Mozhui K, Munshi-South J, Naderi A, Nagy M, Narayan P, Nathanielsz PW, Nguyen NB, Niehrs C, O'Brien JK, O'Tierney Ginn P, Odom DT, Ophir AG, Osborn S, Ostrander EA, Parsons KM, Paul KC, Pellegrini M, Peters KJ, Pedersen AB, Petersen JL, Pietersen DW, Pinho GM, Plassais J, Poganik JR, Prado NA, Reddy P, Rey B, Ritz BR, Robbins J, Rodriguez M, Russell J, Rydkina E, Sailer LL, Salmon AB, Sanghavi A, Schachtschneider KM, Schmitt D, Schmitt T, Schomacher L, Schook LB, Sears KE, Seifert AW, Seluanov A, Shafer ABA, Shanmuganayagam D, Shindyapina AV, Simmons M, Singh K, Sinha I, Slone J, Snell RG, Soltanmaohammadi E, Spangler ML, Spriggs MC, Staggs L, Stedman N, Steinman KJ, Stewart DT, Sugrue VJ, Szladovits B, Takahashi JS, Takasugi M, Teeling EC, Thompson MJ, Van Bonn B, Vernes SC, Villar D, Vinters HV, Wallingford MC, Wang N, Wayne RK, Wilkinson GS, Williams CK, Williams RW, Yang XW, Yao M, Young BG, Zhang B, Zhang Z, Zhao P, Zhao Y, Zhou W, Zimmermann J, Ernst J, Raj K, Horvath S. Universal DNA methylation age across mammalian tissues. NATURE AGING 2023; 3:1144-1166. [PMID: 37563227 PMCID: PMC10501909 DOI: 10.1038/s43587-023-00462-6] [Citation(s) in RCA: 64] [Impact Index Per Article: 64.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/29/2022] [Accepted: 06/21/2023] [Indexed: 08/12/2023]
Abstract
Aging, often considered a result of random cellular damage, can be accurately estimated using DNA methylation profiles, the foundation of pan-tissue epigenetic clocks. Here, we demonstrate the development of universal pan-mammalian clocks, using 11,754 methylation arrays from our Mammalian Methylation Consortium, which encompass 59 tissue types across 185 mammalian species. These predictive models estimate mammalian tissue age with high accuracy (r > 0.96). Age deviations correlate with human mortality risk, mouse somatotropic axis mutations and caloric restriction. We identified specific cytosines with methylation levels that change with age across numerous species. These sites, highly enriched in polycomb repressive complex 2-binding locations, are near genes implicated in mammalian development, cancer, obesity and longevity. Our findings offer new evidence suggesting that aging is evolutionarily conserved and intertwined with developmental processes across all mammals.
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Affiliation(s)
- A T Lu
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
- Altos Labs, San Diego Institute of Science, San Diego, CA, USA
| | - Z Fei
- Department of Biostatistics, Fielding School of Public Health, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Statistics, University of California, Riverside, Riverside, CA, USA
| | - A Haghani
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
- Altos Labs, San Diego Institute of Science, San Diego, CA, USA
| | - T R Robeck
- Zoological SeaWorld Parks and Entertainment, Orlando, FL, USA
| | - J A Zoller
- Department of Biostatistics, Fielding School of Public Health, University of California, Los Angeles, Los Angeles, CA, USA
| | - C Z Li
- Department of Biostatistics, Fielding School of Public Health, University of California, Los Angeles, Los Angeles, CA, USA
| | - R Lowe
- Altos Labs, Cambridge Institute of Science, Cambridge, UK
| | - Q Yan
- Altos Labs, San Diego Institute of Science, San Diego, CA, USA
| | - J Zhang
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - H Vu
- Bioinformatics Interdepartmental Program, University of California, Los Angeles, CA, USA
- Department of Biological Chemistry, University of California, Los Angeles, Los Angeles, CA, USA
| | - J Ablaeva
- Department of Biology, University of Rochester, Rochester, NY, USA
| | - V A Acosta-Rodriguez
- Department of Neuroscience, Peter O'Donnell Jr. Brain Institute, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - D M Adams
- Department of Biology, University of Maryland, College Park, MD, USA
| | - J Almunia
- Loro Parque Fundacion, Puerto de la Cruz, Spain
| | - A Aloysius
- Department of Biology, University of Kentucky, Lexington, KY, USA
| | - R Ardehali
- Division of Cardiology, Department of Internal Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - A Arneson
- Bioinformatics Interdepartmental Program, University of California, Los Angeles, CA, USA
- Department of Biological Chemistry, University of California, Los Angeles, Los Angeles, CA, USA
| | - C S Baker
- Marine Mammal Institute, Oregon State University, Newport, OR, USA
| | - G Banks
- School of Science and Technology, Clifton Campus, Nottingham Trent University, Nottingham, UK
| | - K Belov
- School of Life and Environmental Sciences, the University of Sydney, Sydney, New South Wales, Australia
| | - N C Bennett
- Department of Zoology and Entomology, University of Pretoria, Hatfield, South Africa
| | - P Black
- Busch Gardens Tampa, Tampa, FL, USA
| | - D T Blumstein
- Department of Ecology and Evolutionary Biology, University of California, Los Angeles, Los Angeles, CA, USA
- Rocky Mountain Biological Laboratory, Crested Butte, CO, USA
| | - E K Bors
- Marine Mammal Institute, Oregon State University, Newport, OR, USA
| | - C E Breeze
- Altius Institute for Biomedical Sciences, Seattle, WA, USA
| | - R T Brooke
- Epigenetic Clock Development Foundation, Los Angeles, CA, USA
| | - J L Brown
- Center for Species Survival, Smithsonian Conservation Biology Institute, Front Royal, VA, USA
| | - G G Carter
- Department of Evolution, Ecology and Organismal Biology, The Ohio State University, Columbus, OH, USA
| | - A Caulton
- AgResearch, Invermay Agricultural Centre, Mosgiel, New Zealand
- Department of Biochemistry, University of Otago, Dunedin, New Zealand
| | - J M Cavin
- Gulf World, Dolphin Company, Panama City Beach, FL, USA
| | - L Chakrabarti
- School of Veterinary Medicine and Science, University of Nottingham, Nottingham, UK
| | - I Chatzistamou
- Department of Pathology, Microbiology and Immunology, School of Medicine, University of South Carolina, Columbia, SC, USA
| | - H Chen
- Department of Pharmacology, Addiction Science and Toxicology, the University of Tennessee Health Science Center, Memphis, TN, USA
| | - K Cheng
- Medical Informatics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - P Chiavellini
- Biochemistry Research Institute of La Plata, Histology and Pathology, School of Medicine, University of La Plata, La Plata, Argentina
| | - O W Choi
- Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - S M Clarke
- AgResearch, Invermay Agricultural Centre, Mosgiel, New Zealand
| | - L N Cooper
- Department of Anatomy and Neurobiology, Northeast Ohio Medical University, Rootstown, OH, USA
| | - M L Cossette
- Department of Environmental and Life Sciences, Trent University, Peterborough, Ontario, Canada
| | - J Day
- Taronga Institute of Science and Learning, Taronga Conservation Society Australia, Mosman, New South Wales, Australia
| | - J DeYoung
- Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - S DiRocco
- SeaWorld of Florida, Orlando, FL, USA
| | - C Dold
- Zoological Operations, SeaWorld Parks and Entertainment, Orlando, FL, USA
| | | | - C K Emmons
- Conservation Biology Division, Northwest Fisheries Science Center, National Marine Fisheries Service, National Oceanic and Atmospheric Administration, Seattle, WA, USA
| | - S Emmrich
- Departments of Biology and Medicine, University of Rochester, Rochester, NY, USA
| | - E Erbay
- Altos Labs, San Francisco, CA, USA
| | - C Erlacher-Reid
- SeaWorld of Florida, Orlando, FL, USA
- SeaWorld Orlando, Orlando, FL, USA
| | - C G Faulkes
- School of Biological and Behavioural Sciences, Queen Mary University of London, London, UK
| | - S H Ferguson
- Fisheries and Oceans Canada, Freshwater Institute, Winnipeg, Manitoba, Canada
- Department of Biological Sciences, University of Manitoba, Winnipeg, Manitoba, Canada
| | - C J Finno
- Department of Population Health and Reproduction, University of California, Davis School of Veterinary Medicine, Davis, CA, USA
| | | | - J M Gaillard
- Universite de Lyon, Universite Lyon 1, CNRS, Laboratoire de Biometrie et Biologie Evolutive, Villeurbanne, France
| | - E Garde
- Greenland Institute of Natural Resources, Nuuk, Greenland
| | - L Gerber
- Evolution and Ecology Research Centre, School of Biological, Earth and Environmental Sciences, UNSW Sydney, Sydney, New South Wales, Australia
| | - V N Gladyshev
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - V Gorbunova
- Departments of Biology and Medicine, University of Rochester, Rochester, NY, USA
| | - R G Goya
- Biochemistry Research Institute of La Plata, Histology and Pathology, School of Medicine, University of La Plata, La Plata, Argentina
| | - M J Grant
- Applied Translational Genetics Group, School of Biological Sciences, Centre for Brain Research, the University of Auckland, Auckland, New Zealand
| | - C B Green
- Department of Neuroscience, Peter O'Donnell Jr. Brain Institute, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - E N Hales
- Department of Population Health and Reproduction, University of California, Davis School of Veterinary Medicine, Davis, CA, USA
| | - M B Hanson
- Conservation Biology Division, Northwest Fisheries Science Center, National Marine Fisheries Service, National Oceanic and Atmospheric Administration, Seattle, WA, USA
| | - D W Hart
- Department of Zoology and Entomology, University of Pretoria, Hatfield, South Africa
| | - M Haulena
- Vancouver Aquarium, Vancouver, British Columbia, Canada
| | - K Herrick
- SeaWorld of California, San Diego, CA, USA
| | - A N Hogan
- Cancer Genetics and Comparative Genomics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - C J Hogg
- School of Life and Environmental Sciences, the University of Sydney, Sydney, New South Wales, Australia
| | - T A Hore
- Department of Anatomy, University of Otago, Dunedin, New Zealand
| | - T Huang
- Division of Human Genetics, Department of Pediatrics, University at Buffalo, Buffalo, NY, USA
- Division of Genetics and Metabolism, Oishei Children's Hospital, Buffalo, NY, USA
| | | | - A J Jasinska
- Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - G Jones
- School of Biological Sciences, University of Bristol, Bristol, UK
| | | | - O Kashpur
- Mother Infant Research Institute, Tufts Medical Center, Boston, MA, USA
| | - H Katcher
- Yuvan Research, Mountain View, CA, USA
| | | | - V Kaza
- Peromyscus Genetic Stock Center, University of South Carolina, Columbia, SC, USA
| | - H Kiaris
- Peromyscus Genetic Stock Center, University of South Carolina, Columbia, SC, USA
- Department of Drug Discovery and Biomedical Sciences, College of Pharmacy, University of South Carolina, Columbia, SC, USA
| | - M S Kobor
- Edwin S.H. Leong Healthy Aging Program, Centre for Molecular Medicine and Therapeutics, University of British Columbia, Vancouver, British Columbia, Canada
| | - P Kordowitzki
- Institute of Animal Reproduction and Food Research of the Polish Academy of Sciences, Olsztyn, Poland
- Institute for Veterinary Medicine, Nicolaus Copernicus University, Torun, Poland
| | - W R Koski
- LGL Limited, King City, Ontario, Canada
| | - M Krützen
- Evolutionary Genetics Group, Department of Evolutionary Anthropology, University of Zurich, Zurich, Switzerland
| | - S B Kwon
- Bioinformatics Interdepartmental Program, University of California, Los Angeles, CA, USA
- Department of Biological Chemistry, University of California, Los Angeles, Los Angeles, CA, USA
| | - B Larison
- Department of Ecology and Evolutionary Biology, UCLA, Los Angeles, CA, USA
- Center for Tropical Research, Institute for the Environment and Sustainability, UCLA, Los Angeles, CA, USA
| | - S G Lee
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - M Lehmann
- Biochemistry Research Institute of La Plata, Histology and Pathology, School of Medicine, University of La Plata, La Plata, Argentina
| | - J F Lemaitre
- Universite de Lyon, Universite Lyon 1, CNRS, Laboratoire de Biometrie et Biologie Evolutive, Villeurbanne, France
| | - A J Levine
- Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - C Li
- Texas Pregnancy and Life-course Health Center, Southwest National Primate Research Center, San Antonio, TX, USA
- Department of Animal Science, College of Agriculture and Natural Resources, Laramie, WY, USA
| | - X Li
- Technology Center for Genomics and Bioinformatics, Department of Pathology and Laboratory Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - A R Lim
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - D T S Lin
- Centre for Molecular Medicine and Therapeutics, BC Children's Hospital Research Institute, University of British Columbia, Vancouver, British Columbia, Canada
| | | | - T J Little
- Institute of Ecology and Evolution, School of Biological Sciences, University of Edinburgh, Edinburgh, UK
| | - N Macoretta
- Departments of Biology and Medicine, University of Rochester, Rochester, NY, USA
| | - D Maddox
- White Oak Conservation, Yulee, FL, USA
| | - C O Matkin
- North Gulf Oceanic Society, Homer, AK, USA
| | - J A Mattison
- Translational Gerontology Branch, National Institute on Aging Intramural Research Program, National Institutes of Health, Baltimore, MD, USA
| | | | - J Mergl
- Marineland of Canada, Niagara Falls, Ontario, Canada
| | - J J Meudt
- Biomedical and Genomic Research Group, Department of Animal and Dairy Sciences, University of Wisconsin-Madison, Madison, WI, USA
| | - G A Montano
- Zoological Operations, SeaWorld Parks and Entertainment, Orlando, FL, USA
| | - K Mozhui
- Department of Preventive Medicine, University of Tennessee Health Science Center, College of Medicine, Memphis, TN, USA
- Department of Genetics, Genomics and Informatics, University of Tennessee Health Science Center, College of Medicine, Memphis, TN, USA
| | - J Munshi-South
- Louis Calder Center-Biological Field Station, Department of Biological Sciences, Fordham University, Armonk, NY, USA
| | - A Naderi
- Department of Drug Discovery and Biomedical Sciences, College of Pharmacy, University of South Carolina, Columbia, SC, USA
| | - M Nagy
- Museum fur Naturkunde, Leibniz Institute for Evolution and Biodiversity Science, Berlin, Germany
| | - P Narayan
- Applied Translational Genetics Group, School of Biological Sciences, Centre for Brain Research, the University of Auckland, Auckland, New Zealand
| | - P W Nathanielsz
- Texas Pregnancy and Life-course Health Center, Southwest National Primate Research Center, San Antonio, TX, USA
- Department of Animal Science, College of Agriculture and Natural Resources, Laramie, WY, USA
| | - N B Nguyen
- Division of Cardiology, Department of Internal Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - C Niehrs
- Institute of Molecular Biology, Mainz, Germany
- Division of Molecular Embryology, DKFZ-ZMBH Alliance, Heidelberg, Germany
| | - J K O'Brien
- Taronga Institute of Science and Learning, Taronga Conservation Society Australia, Mosman, New South Wales, Australia
| | - P O'Tierney Ginn
- Mother Infant Research Institute, Tufts Medical Center, Boston, MA, USA
- Department of Obstetrics and Gynecology, Tufts University School of Medicine, Boston, MA, USA
| | - D T Odom
- Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge, UK
- Division of Regulatory Genomics and Cancer Evolution, Deutsches Krebsforschungszentrum, Heidelberg, Germany
| | - A G Ophir
- Department of Psychology, Cornell University, Ithaca, NY, USA
| | - S Osborn
- SeaWorld of Texas, San Antonio, TX, USA
| | - E A Ostrander
- Cancer Genetics and Comparative Genomics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - K M Parsons
- Conservation Biology Division, Northwest Fisheries Science Center, National Marine Fisheries Service, National Oceanic and Atmospheric Administration, Seattle, WA, USA
| | - K C Paul
- Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - M Pellegrini
- Department of Molecular Cell and Developmental Biology, University of California, Los Angeles, Los Angeles, CA, USA
| | - K J Peters
- Evolutionary Genetics Group, Department of Evolutionary Anthropology, University of Zurich, Zurich, Switzerland
- School of Earth, Atmospheric and Life Sciences, University of Wollongong, Wollongong, Australia
| | - A B Pedersen
- Institute of Evolutionary Biology, School of Biological Sciences, University of Edinburgh, Edinburgh, UK
| | - J L Petersen
- Department of Animal Science, University of Nebraska, Lincoln, NE, USA
| | - D W Pietersen
- Mammal Research Institute, Department of Zoology and Entomology, University of Pretoria, Hatfield, South Africa
| | - G M Pinho
- Department of Ecology and Evolutionary Biology, UCLA, Los Angeles, CA, USA
| | - J Plassais
- Cancer Genetics and Comparative Genomics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - J R Poganik
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - N A Prado
- Department of Biology, College of Arts and Science, Adelphi University, Garden City, NY, USA
| | - P Reddy
- Altos Labs, San Diego Institute of Science, San Diego, CA, USA
- Salk Institute for Biological Studies, La Jolla, CA, USA
| | - B Rey
- Universite de Lyon, Universite Lyon 1, CNRS, Laboratoire de Biometrie et Biologie Evolutive, Villeurbanne, France
| | - B R Ritz
- Department of Epidemiology, UCLA Fielding School of Public Health, Los Angeles, CA, USA
- Department of Environmental Health Sciences, UCLA Fielding School of Public Health, Los Angeles, CA, USA
- Department of Neurology, UCLA David Geffen School of Medicine, Los Angeles, CA, USA
| | - J Robbins
- Center for Coastal Studies, Provincetown, MA, USA
| | | | - J Russell
- SeaWorld of California, San Diego, CA, USA
| | - E Rydkina
- Departments of Biology and Medicine, University of Rochester, Rochester, NY, USA
| | - L L Sailer
- Department of Psychology, Cornell University, Ithaca, NY, USA
| | - A B Salmon
- The Sam and Ann Barshop Institute for Longevity and Aging Studies and Department of Molecular Medicine, UT Health San Antonio and the Geriatric Research Education and Clinical Center, South Texas Veterans Healthcare System, San Antonio, TX, USA
| | | | - K M Schachtschneider
- Department of Radiology, University of Illinois at Chicago, Chicago, IL, USA
- Department of Biochemistry and Molecular Genetics, University of Illinois at Chicago, Chicago, IL, USA
- National Center for Supercomputing Applications, University of Illinois at Urbana-Champaign, Urbana, IL, USA
| | - D Schmitt
- College of Agriculture, Missouri State University, Springfield, MO, USA
| | - T Schmitt
- SeaWorld of California, San Diego, CA, USA
| | | | - L B Schook
- Department of Radiology, University of Illinois at Chicago, Chicago, IL, USA
- Department of Animal Sciences, University of Illinois at Urbana-Champaign, Champaign, IL, USA
| | - K E Sears
- Department of Ecology and Evolutionary Biology, UCLA, Los Angeles, CA, USA
- Department of Molecular Cell and Developmental Biology, University of California, Los Angeles, Los Angeles, CA, USA
| | - A W Seifert
- Department of Biology, University of Kentucky, Lexington, KY, USA
| | - A Seluanov
- Departments of Biology and Medicine, University of Rochester, Rochester, NY, USA
| | - A B A Shafer
- Department of Forensic Science, Environmental and Life Sciences, Trent University, Peterborough, Ontario, Canada
| | - D Shanmuganayagam
- Biomedical and Genomic Research Group, Department of Animal and Dairy Sciences, University of Wisconsin-Madison, Madison, WI, USA
- Department of Surgery, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
| | - A V Shindyapina
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | | | - K Singh
- Shobhaben Pratapbhai Patel School of Pharmacy and Technology Management, SVKM'S NMIMS University, Mumbai, India
| | - I Sinha
- Department of Ecology and Evolutionary Biology, UCLA, Los Angeles, CA, USA
| | - J Slone
- Division of Human Genetics, Department of Pediatrics, University at Buffalo, Buffalo, NY, USA
| | - R G Snell
- Applied Translational Genetics Group, School of Biological Sciences, Centre for Brain Research, the University of Auckland, Auckland, New Zealand
| | - E Soltanmaohammadi
- Department of Drug Discovery and Biomedical Sciences, College of Pharmacy, University of South Carolina, Columbia, SC, USA
| | - M L Spangler
- Department of Animal Science, University of Nebraska, Lincoln, NE, USA
| | | | - L Staggs
- SeaWorld of Florida, Orlando, FL, USA
| | | | - K J Steinman
- Species Preservation Laboratory, SeaWorld San Diego, San Diego, CA, USA
| | - D T Stewart
- Biology Department, Acadia University, Wolfville, Nova Scotia, Canada
| | - V J Sugrue
- Department of Anatomy, University of Otago, Dunedin, New Zealand
| | - B Szladovits
- Department of Pathobiology and Population Sciences, Royal Veterinary College, Hatfield, UK
| | - J S Takahashi
- Department of Neuroscience, Peter O'Donnell Jr. Brain Institute, University of Texas Southwestern Medical Center, Dallas, TX, USA
- Howard Hughes Medical Institute, Department of Neuroscience, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - M Takasugi
- Departments of Biology and Medicine, University of Rochester, Rochester, NY, USA
| | - E C Teeling
- School of Biology and Environmental Science, University College Dublin, Dublin, Ireland
| | - M J Thompson
- Department of Molecular Cell and Developmental Biology, University of California, Los Angeles, Los Angeles, CA, USA
| | - B Van Bonn
- John G. Shedd Aquarium, Chicago, IL, USA
| | - S C Vernes
- School of Biology, the University of St Andrews, Fife, UK
- Neurogenetics of Vocal Communication Group, Max Planck Institute for Psycholinguistics, Nijmegen, the Netherlands
| | - D Villar
- Blizard Institute, Faculty of Medicine and Dentistry, Queen Mary University of London, London, UK
| | - H V Vinters
- Department of Pathology and Laboratory Medicine, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA
| | - M C Wallingford
- Mother Infant Research Institute, Tufts Medical Center, Boston, MA, USA
- Division of Obstetrics and Gynecology, Tufts University School of Medicine, Boston, MA, USA
| | - N Wang
- Center for Neurobehavioral Genetics, Jane and Terry Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA
| | - R K Wayne
- Department of Ecology and Evolutionary Biology, UCLA, Los Angeles, CA, USA
| | - G S Wilkinson
- Department of Biology, University of Maryland, College Park, MD, USA
| | - C K Williams
- Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - R W Williams
- Department of Genetics, Genomics and Informatics, University of Tennessee Health Science Center, College of Medicine, Memphis, TN, USA
| | - X W Yang
- Center for Neurobehavioral Genetics, Jane and Terry Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA
| | - M Yao
- Department of Biostatistics, Fielding School of Public Health, University of California, Los Angeles, Los Angeles, CA, USA
| | - B G Young
- Fisheries and Oceans Canada, Winnipeg, Manitoba, Canada
| | - B Zhang
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Z Zhang
- Departments of Biology and Medicine, University of Rochester, Rochester, NY, USA
| | - P Zhao
- Division of Cardiology, Department of Internal Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
- Eli and Edythe Broad Center of Regenerative Medicine and Stem Cell Research, University of California, Los Angeles, CA, USA
| | - Y Zhao
- Departments of Biology and Medicine, University of Rochester, Rochester, NY, USA
| | - W Zhou
- Center for Computational and Genomic Medicine, Children's Hospital of Philadelphia, Philadelphia, PA, USA
- Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - J Zimmermann
- Department of Mathematics and Technology, University of Applied Sciences Koblenz, Koblenz, Germany
| | - J Ernst
- Bioinformatics Interdepartmental Program, University of California, Los Angeles, CA, USA
- Department of Biological Chemistry, University of California, Los Angeles, Los Angeles, CA, USA
| | - K Raj
- Altos Labs, Cambridge Institute of Science, Cambridge, UK
| | - S Horvath
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA.
- Altos Labs, San Diego Institute of Science, San Diego, CA, USA.
- Department of Biostatistics, Fielding School of Public Health, University of California, Los Angeles, Los Angeles, CA, USA.
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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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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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Casanova-Maldonado I, Arancibia D, Lois P, Peña-Villalobos I, Palma V. Hyperbaric oxygen treatment increases intestinal stem cell proliferation through the mTORC1/S6K1 signaling pathway in Mus musculus. Biol Res 2023; 56:41. [PMID: 37438828 DOI: 10.1186/s40659-023-00444-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2023] [Accepted: 06/05/2023] [Indexed: 07/14/2023] Open
Abstract
BACKGROUND Hyperbaric oxygen treatment (HBOT) has been reported to modulate the proliferation of neural and mesenchymal stem cell populations, but the molecular mechanisms underlying these effects are not completely understood. In this study, we aimed to assess HBOT somatic stem cell modulation by evaluating the role of the mTOR complex 1 (mTORC1), a key regulator of cell metabolism whose activity is modified depending on oxygen levels, as a potential mediator of HBOT in murine intestinal stem cells (ISCs). RESULTS We discovered that acute HBOT synchronously increases the proliferation of ISCs without affecting the animal's oxidative metabolism through activation of the mTORC1/S6K1 axis. mTORC1 inhibition by rapamycin administration for 20 days also increases ISCs proliferation, generating a paradoxical response in mice intestines, and has been proposed to mimic a partial starvation state. Interestingly, the combination of HBOT and rapamycin does not have a synergic effect, possibly due to their differential impact on the mTORC1/S6K1 axis. CONCLUSIONS HBOT can induce an increase in ISCs proliferation along with other cell populations within the crypt through mTORC1/S6K1 modulation without altering the oxidative metabolism of the animal's small intestine. These results shed light on the molecular mechanisms underlying HBOT therapeutic action, laying the groundwork for future studies.
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Affiliation(s)
- Ignacio Casanova-Maldonado
- Laboratory of Stem Cells and Developmental Biology, Faculty of Sciences, Universidad de Chile, Las Encinas 3370, Milenio Building Floor 3, 7800024, Santiago de Chile, Nunoa, Chile.
| | - David Arancibia
- Laboratory of Stem Cells and Developmental Biology, Faculty of Sciences, Universidad de Chile, Las Encinas 3370, Milenio Building Floor 3, 7800024, Santiago de Chile, Nunoa, Chile
| | - Pablo Lois
- Laboratory of Stem Cells and Developmental Biology, Faculty of Sciences, Universidad de Chile, Las Encinas 3370, Milenio Building Floor 3, 7800024, Santiago de Chile, Nunoa, Chile
- Education Department, Faculty of Humanities, Universidad Mayor, Santiago de Chile, Providencia, Chile
| | - Isaac Peña-Villalobos
- Laboratory of Stem Cells and Developmental Biology, Faculty of Sciences, Universidad de Chile, Las Encinas 3370, Milenio Building Floor 3, 7800024, Santiago de Chile, Nunoa, Chile.
| | - Verónica Palma
- Laboratory of Stem Cells and Developmental Biology, Faculty of Sciences, Universidad de Chile, Las Encinas 3370, Milenio Building Floor 3, 7800024, Santiago de Chile, Nunoa, Chile.
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32
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Maji RK, Czepukojc B, Scherer M, Tierling S, Cadenas C, Gianmoena K, Gasparoni N, Nordström K, Gasparoni G, Laggai S, Yang X, Sinha A, Ebert P, Falk-Paulsen M, Kinkley S, Hoppstädter J, Chung HR, Rosenstiel P, Hengstler JG, Walter J, Schulz MH, Kessler SM, Kiemer AK. Alterations in the hepatocyte epigenetic landscape in steatosis. Epigenetics Chromatin 2023; 16:30. [PMID: 37415213 DOI: 10.1186/s13072-023-00504-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2023] [Accepted: 06/21/2023] [Indexed: 07/08/2023] Open
Abstract
Fatty liver disease or the accumulation of fat in the liver, has been reported to affect the global population. This comes with an increased risk for the development of fibrosis, cirrhosis, and hepatocellular carcinoma. Yet, little is known about the effects of a diet containing high fat and alcohol towards epigenetic aging, with respect to changes in transcriptional and epigenomic profiles. In this study, we took up a multi-omics approach and integrated gene expression, methylation signals, and chromatin signals to study the epigenomic effects of a high-fat and alcohol-containing diet on mouse hepatocytes. We identified four relevant gene network clusters that were associated with relevant pathways that promote steatosis. Using a machine learning approach, we predict specific transcription factors that might be responsible to modulate the functionally relevant clusters. Finally, we discover four additional CpG loci and validate aging-related differential CpG methylation. Differential CpG methylation linked to aging showed minimal overlap with altered methylation in steatosis.
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Affiliation(s)
- Ranjan Kumar Maji
- Institute for Cardiovascular Regeneration, Goethe-University, 60590, Frankfurt, Germany
- German Centre for Cardiovascular Research (DZHK), Partner Site Rhine-Main, 60590, Frankfurt, Germany
| | - Beate Czepukojc
- Department of Pharmacy, Pharmaceutical Biology, Saarland University, 66123, Saarbrücken, Germany
| | - Michael Scherer
- Centre for Genomic Regulation (CRG), Barcelona Institute of Science and Technology (BIST), 08003, Barcelona, Spain
| | - Sascha Tierling
- Department of Genetics, Saarland University, 66123, Saarbrücken, Germany
| | - Cristina Cadenas
- IfADo: Leibniz Research Centre for Working Environment and Human Factors, Dortmund, Germany
| | - Kathrin Gianmoena
- IfADo: Leibniz Research Centre for Working Environment and Human Factors, Dortmund, Germany
| | - Nina Gasparoni
- Department of Genetics, Saarland University, 66123, Saarbrücken, Germany
| | - Karl Nordström
- Department of Genetics, Saarland University, 66123, Saarbrücken, Germany
| | - Gilles Gasparoni
- Department of Genetics, Saarland University, 66123, Saarbrücken, Germany
| | - Stephan Laggai
- Department of Pharmacy, Pharmaceutical Biology, Saarland University, 66123, Saarbrücken, Germany
| | - Xinyi Yang
- Institute of Medical Bioinformatics and Biostatistics, Philipps University of Marburg, 35032, Marburg, Germany
| | - Anupam Sinha
- Institute of Clinical Molecular Biology, Christian-Albrechts-University, 24105, Kiel, Germany
| | - Peter Ebert
- Core Unit Bioinformatics, Medical Faculty, Heinrich Heine University, 40225, Düsseldorf, Germany
- Department of Computational Biology and Applied Algorithmics, Max Planck Institute for Informatics, 66123, Saarbrücken, Germany
| | - Maren Falk-Paulsen
- Institute of Clinical Molecular Biology, Christian-Albrechts-University, 24105, Kiel, Germany
| | - Sarah Kinkley
- Department of Computational Molecular Biology, Max Planck Institute for Molecular Genetics, 14195, Berlin, Germany
| | - Jessica Hoppstädter
- Department of Pharmacy, Pharmaceutical Biology, Saarland University, 66123, Saarbrücken, Germany
| | - Ho-Ryun Chung
- Institute of Medical Bioinformatics and Biostatistics, Philipps University of Marburg, 35032, Marburg, Germany
| | - Philip Rosenstiel
- Institute of Clinical Molecular Biology, Christian-Albrechts-University, 24105, Kiel, Germany
| | - Jan G Hengstler
- IfADo: Leibniz Research Centre for Working Environment and Human Factors, Dortmund, Germany
| | - Jörn Walter
- Department of Genetics, Saarland University, 66123, Saarbrücken, Germany
| | - Marcel H Schulz
- Institute for Cardiovascular Regeneration, Goethe-University, 60590, Frankfurt, Germany.
- German Centre for Cardiovascular Research (DZHK), Partner Site Rhine-Main, 60590, Frankfurt, Germany.
- Department of Computational Biology and Applied Algorithmics, Max Planck Institute for Informatics, 66123, Saarbrücken, Germany.
- Excellence Cluster on Multimodal Computing and Interaction, Saarland University, 66123, Saarbrücken, Germany.
| | - Sonja M Kessler
- Department of Pharmacy, Pharmaceutical Biology, Saarland University, 66123, Saarbrücken, Germany.
- Institute of Pharmacy, Experimental Pharmacology for Natural Sciences, Martin Luther University Halle-Wittenberg, Halle, Germany.
- Halle Research Centre for Drug Therapy (HRCDT), Halle, Germany.
| | - Alexandra K Kiemer
- Department of Pharmacy, Pharmaceutical Biology, Saarland University, 66123, Saarbrücken, Germany.
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33
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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: 27] [Impact Index Per Article: 27.0] [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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34
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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: 74] [Impact Index Per Article: 74.0] [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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35
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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: 99] [Impact Index Per Article: 99.0] [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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36
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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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37
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Razzoli M, Nyuyki-Dufe K, Chen BH, Bartolomucci A. Contextual modifiers of healthspan, lifespan, and epigenome in mice under chronic social stress. Proc Natl Acad Sci U S A 2023; 120:e2211755120. [PMID: 37043532 PMCID: PMC10120026 DOI: 10.1073/pnas.2211755120] [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: 07/28/2022] [Accepted: 02/24/2023] [Indexed: 04/13/2023] Open
Abstract
Sustained life stress and low socioeconomic status are among the major causes of aging-related diseases and decreased life expectancy. Experimental rodent models can help to identify the underlying mechanisms, yet very few studies address the long-term consequences of social stress on aging. We conducted a randomized study involving more than 300 male mice of commonly used laboratory strains (C57BL/6J, CD1, and Sv129Ev) chosen for the spontaneous aggression gradient and stress-vulnerability. Mice were exposed to a lifelong chronic psychosocial stress protocol to model social gradients in aging and disease vulnerability. Low social rank, inferred based on a discretized aggression index, was found to negatively impact lifespan in our study population. However, social rank interacted with genetic background in that low-ranking C57BL/6J, high-ranking Sv129Ev, and middle-ranking CD1 mice had lower survival, respectively, implying a cost of maintaining a given social rank that varies across strains. Machine learning linear discriminant analysis identified baseline fat-free mass as the most important predictor of mouse genetic background and social rank in the present dataset. Finally, strain and social rank differences were significantly associated with epigenetic changes, most significantly in Sv129Ev mice and in high-ranking compared to lower ranking subjects. Overall, we identified genetic background and social rank as critical contextual modifiers of aging and lifespan in an ethologically relevant rodent model of social stress, thereby providing a preclinical experimental paradigm to study the impact of social determinants of health disparities and accelerated aging.
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Affiliation(s)
- Maria Razzoli
- Department of Integrative Biology and Physiology, University of Minnesota, Minneapolis, MN55455
| | - Kewir Nyuyki-Dufe
- Department of Integrative Biology and Physiology, University of Minnesota, Minneapolis, MN55455
| | - Brian H. Chen
- FOXO Technologies Inc., Minneapolis, MN55401
- Division of Epidemiology, The Herbert Wertheim School of Public Health and Human Longevity Science, University of California, San Diego, La Jolla, CA92093
| | - Alessandro Bartolomucci
- Department of Integrative Biology and Physiology, University of Minnesota, Minneapolis, MN55455
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38
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Ahadi S, Wilson KA, Babenko B, McLean CY, Bryant D, Pritchard O, Kumar A, Carrera EM, Lamy R, Stewart JM, Varadarajan A, Berndl M, Kapahi P, Bashir A. Longitudinal fundus imaging and its genome-wide association analysis provide evidence for a human retinal aging clock. eLife 2023; 12:e82364. [PMID: 36975205 PMCID: PMC10110236 DOI: 10.7554/elife.82364] [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: 08/02/2022] [Accepted: 03/22/2023] [Indexed: 03/29/2023] Open
Abstract
Biological age, distinct from an individual's chronological age, has been studied extensively through predictive aging clocks. However, these clocks have limited accuracy in short time-scales. Here we trained deep learning models on fundus images from the EyePACS dataset to predict individuals' chronological age. Our retinal aging clocking, 'eyeAge', predicted chronological age more accurately than other aging clocks (mean absolute error of 2.86 and 3.30 years on quality-filtered data from EyePACS and UK Biobank, respectively). Additionally, eyeAge was independent of blood marker-based measures of biological age, maintaining an all-cause mortality hazard ratio of 1.026 even when adjusted for phenotypic age. The individual-specific nature of eyeAge was reinforced via multiple GWAS hits in the UK Biobank cohort. The top GWAS locus was further validated via knockdown of the fly homolog, Alk, which slowed age-related decline in vision in flies. This study demonstrates the potential utility of a retinal aging clock for studying aging and age-related diseases and quantitatively measuring aging on very short time-scales, opening avenues for quick and actionable evaluation of gero-protective therapeutics.
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Affiliation(s)
- Sara Ahadi
- Google ResearchMountain ViewUnited States
| | | | | | | | | | | | - Ajay Kumar
- Department of Biophysics, Post Graduate Institute of Medical Education and ResearchChandigarhIndia
| | | | - Ricardo Lamy
- Department of Ophthalmology, Zuckerberg San Francisco General Hospital and Trauma CenterSan FranciscoUnited States
| | - Jay M Stewart
- Department of Ophthalmology, University of California, San FranciscoSan FranciscoUnited States
| | | | | | - Pankaj Kapahi
- Buck Institute for Research on AgingNovatoUnited States
| | - Ali Bashir
- Google ResearchMountain ViewUnited States
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39
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Pamplona R, Jové M, Gómez J, Barja G. Whole organism aging: Parabiosis, inflammaging, epigenetics, and peripheral and central aging clocks. The ARS of aging. Exp Gerontol 2023; 174:112137. [PMID: 36871903 DOI: 10.1016/j.exger.2023.112137] [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: 12/31/2022] [Revised: 02/21/2023] [Accepted: 03/02/2023] [Indexed: 03/07/2023]
Abstract
The strong interest shown in the study of the causes of aging in recent decades has uncovered many mechanisms that could contribute to the rate of aging. These include mitochondrial ROS production, DNA modification and repair, lipid peroxidation-induced membrane fatty acid unsaturation, autophagy, telomere shortening rate, apoptosis, proteostasis, senescent cells, and most likely there are many others waiting to be discovered. However, all these well-known mechanisms work only or mainly at the cellular level. Although it is known that organs within a single individual do not age at exactly the same rate, there is a well-defined species longevity. Therefore, loose coordination of aging rate among the different cells and tissues is needed to ensure species lifespan. In this article we focus on less known extracellular, systemic, and whole organism level mechanisms that could loosely coordinate aging of the whole individual to keep it within the margins of its species longevity. We discuss heterochronic parabiosis experiments, systemic factors distributed through the vascular system like DAMPs, mitochondrial DNA and its fragments, TF-like vascular proteins, and inflammaging, as well as epigenetic and proposed aging clocks situated at different levels of organization from individual cells to the brain. These interorgan systems can help to determine species longevity as a further adaptation to the ecosystem.
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Affiliation(s)
- Reinald Pamplona
- Department of Experimental Medicine, University of Lleida (UdL), Lleida Biomedical Research Institute (IRBLleida), E25198 Lleida, Spain
| | - Mariona Jové
- Department of Experimental Medicine, University of Lleida (UdL), Lleida Biomedical Research Institute (IRBLleida), E25198 Lleida, Spain
| | - José Gómez
- Department of Biology and Geology, Physics and Inorganic Chemistry, ESCET, Rey Juan Carlos University, E28933 Móstoles, Madrid, Spain
| | - Gustavo Barja
- Faculty of Biological Sciences, Complutense University of Madrid (UCM), E28040 Madrid, Spain.
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40
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Khan J, Pernicova I, Nisar K, Korbonits M. Mechanisms of ageing: growth hormone, dietary restriction, and metformin. Lancet Diabetes Endocrinol 2023; 11:261-281. [PMID: 36848915 DOI: 10.1016/s2213-8587(23)00001-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/14/2022] [Revised: 12/21/2022] [Accepted: 12/22/2022] [Indexed: 03/01/2023]
Abstract
Tackling the mechanisms underlying ageing is desirable to help to extend the duration and improve the quality of life. Life extension has been achieved in animal models by suppressing the growth hormone-insulin-like growth factor 1 (IGF-1) axis and also via dietary restriction. Metformin has become the focus of increased interest as a possible anti-ageing drug. There is some overlap in the postulated mechanisms of how these three approaches could produce anti-ageing effects, with convergence on common downstream pathways. In this Review, we draw on evidence from both animal models and human studies to assess the effects of suppression of the growth hormone-IGF-1 axis, dietary restriction, and metformin on ageing.
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Affiliation(s)
- Jansher Khan
- Centre for Endocrinology, William Harvey Research Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UK
| | - Ida Pernicova
- Endocrinology and Metabolic Medicine, Sheffield Teaching Hospitals NHS Foundation Trust, Sheffield, UK
| | - Kiran Nisar
- Centre for Endocrinology, William Harvey Research Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UK
| | - Márta Korbonits
- Centre for Endocrinology, William Harvey Research Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UK.
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41
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Ji S, Xiong M, Chen H, Liu Y, Zhou L, Hong Y, Wang M, Wang C, Fu X, Sun X. Cellular rejuvenation: molecular mechanisms and potential therapeutic interventions for diseases. Signal Transduct Target Ther 2023; 8:116. [PMID: 36918530 PMCID: PMC10015098 DOI: 10.1038/s41392-023-01343-5] [Citation(s) in RCA: 30] [Impact Index Per Article: 30.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2022] [Revised: 12/16/2022] [Accepted: 01/19/2023] [Indexed: 03/16/2023] Open
Abstract
The ageing process is a systemic decline from cellular dysfunction to organ degeneration, with more predisposition to deteriorated disorders. Rejuvenation refers to giving aged cells or organisms more youthful characteristics through various techniques, such as cellular reprogramming and epigenetic regulation. The great leaps in cellular rejuvenation prove that ageing is not a one-way street, and many rejuvenative interventions have emerged to delay and even reverse the ageing process. Defining the mechanism by which roadblocks and signaling inputs influence complex ageing programs is essential for understanding and developing rejuvenative strategies. Here, we discuss the intrinsic and extrinsic factors that counteract cell rejuvenation, and the targeted cells and core mechanisms involved in this process. Then, we critically summarize the latest advances in state-of-art strategies of cellular rejuvenation. Various rejuvenation methods also provide insights for treating specific ageing-related diseases, including cellular reprogramming, the removal of senescence cells (SCs) and suppression of senescence-associated secretory phenotype (SASP), metabolic manipulation, stem cells-associated therapy, dietary restriction, immune rejuvenation and heterochronic transplantation, etc. The potential applications of rejuvenation therapy also extend to cancer treatment. Finally, we analyze in detail the therapeutic opportunities and challenges of rejuvenation technology. Deciphering rejuvenation interventions will provide further insights into anti-ageing and ageing-related disease treatment in clinical settings.
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Affiliation(s)
- Shuaifei Ji
- Research Center for Tissue Repair and Regeneration Affiliated to Medical Innovation Research Department and 4th Medical Center, PLA General Hospital and PLA Medical College; PLA Key Laboratory of Tissue Repair and Regenerative Medicine and Beijing Key Research Laboratory of Skin Injury, Repair and Regeneration; Research Unit of Trauma Care, Tissue Repair and Regeneration, Chinese Academy of Medical Sciences, 2019RU051, Beijing, 100048, P. R. China
| | - Mingchen Xiong
- Research Center for Tissue Repair and Regeneration Affiliated to Medical Innovation Research Department and 4th Medical Center, PLA General Hospital and PLA Medical College; PLA Key Laboratory of Tissue Repair and Regenerative Medicine and Beijing Key Research Laboratory of Skin Injury, Repair and Regeneration; Research Unit of Trauma Care, Tissue Repair and Regeneration, Chinese Academy of Medical Sciences, 2019RU051, Beijing, 100048, P. R. China
| | - Huating Chen
- Research Center for Tissue Repair and Regeneration Affiliated to Medical Innovation Research Department and 4th Medical Center, PLA General Hospital and PLA Medical College; PLA Key Laboratory of Tissue Repair and Regenerative Medicine and Beijing Key Research Laboratory of Skin Injury, Repair and Regeneration; Research Unit of Trauma Care, Tissue Repair and Regeneration, Chinese Academy of Medical Sciences, 2019RU051, Beijing, 100048, P. R. China
| | - Yiqiong Liu
- Research Center for Tissue Repair and Regeneration Affiliated to Medical Innovation Research Department and 4th Medical Center, PLA General Hospital and PLA Medical College; PLA Key Laboratory of Tissue Repair and Regenerative Medicine and Beijing Key Research Laboratory of Skin Injury, Repair and Regeneration; Research Unit of Trauma Care, Tissue Repair and Regeneration, Chinese Academy of Medical Sciences, 2019RU051, Beijing, 100048, P. R. China
| | - Laixian Zhou
- Research Center for Tissue Repair and Regeneration Affiliated to Medical Innovation Research Department and 4th Medical Center, PLA General Hospital and PLA Medical College; PLA Key Laboratory of Tissue Repair and Regenerative Medicine and Beijing Key Research Laboratory of Skin Injury, Repair and Regeneration; Research Unit of Trauma Care, Tissue Repair and Regeneration, Chinese Academy of Medical Sciences, 2019RU051, Beijing, 100048, P. R. China
| | - Yiyue Hong
- Research Center for Tissue Repair and Regeneration Affiliated to Medical Innovation Research Department and 4th Medical Center, PLA General Hospital and PLA Medical College; PLA Key Laboratory of Tissue Repair and Regenerative Medicine and Beijing Key Research Laboratory of Skin Injury, Repair and Regeneration; Research Unit of Trauma Care, Tissue Repair and Regeneration, Chinese Academy of Medical Sciences, 2019RU051, Beijing, 100048, P. R. China
| | - Mengyang Wang
- Research Center for Tissue Repair and Regeneration Affiliated to Medical Innovation Research Department and 4th Medical Center, PLA General Hospital and PLA Medical College; PLA Key Laboratory of Tissue Repair and Regenerative Medicine and Beijing Key Research Laboratory of Skin Injury, Repair and Regeneration; Research Unit of Trauma Care, Tissue Repair and Regeneration, Chinese Academy of Medical Sciences, 2019RU051, Beijing, 100048, P. R. China
| | - Chunming Wang
- State Key Laboratory of Quality Research in Chinese Medicine, Institute of Chinese Medical Sciences, University of Macau, Taipa, 999078, Macau SAR, China.
| | - Xiaobing Fu
- Research Center for Tissue Repair and Regeneration Affiliated to Medical Innovation Research Department and 4th Medical Center, PLA General Hospital and PLA Medical College; PLA Key Laboratory of Tissue Repair and Regenerative Medicine and Beijing Key Research Laboratory of Skin Injury, Repair and Regeneration; Research Unit of Trauma Care, Tissue Repair and Regeneration, Chinese Academy of Medical Sciences, 2019RU051, Beijing, 100048, P. R. China.
| | - Xiaoyan Sun
- Research Center for Tissue Repair and Regeneration Affiliated to Medical Innovation Research Department and 4th Medical Center, PLA General Hospital and PLA Medical College; PLA Key Laboratory of Tissue Repair and Regenerative Medicine and Beijing Key Research Laboratory of Skin Injury, Repair and Regeneration; Research Unit of Trauma Care, Tissue Repair and Regeneration, Chinese Academy of Medical Sciences, 2019RU051, Beijing, 100048, P. R. China.
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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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Zhai J, Kongsberg WH, Pan Y, Hao C, Wang X, Sun J. Caloric restriction induced epigenetic effects on aging. Front Cell Dev Biol 2023; 10:1079920. [PMID: 36712965 PMCID: PMC9880295 DOI: 10.3389/fcell.2022.1079920] [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: 10/25/2022] [Accepted: 12/31/2022] [Indexed: 01/15/2023] Open
Abstract
Aging is the subject of many studies, facilitating the discovery of many interventions. Epigenetic influences numerous life processes by regulating gene expression and also plays a crucial role in aging regulation. Increasing data suggests that dietary changes can alter epigenetic marks associated with aging. Caloric restriction (CR)is considered an intervention to regulate aging and prolong life span. At present, CR has made some progress by regulating signaling pathways associated with aging as well as the mechanism of action of intercellular signaling molecules against aging. In this review, we will focus on autophagy and epigenetic modifications to elaborate the molecular mechanisms by which CR delays aging by triggering autophagy, epigenetic modifications, and the interaction between the two in caloric restriction. In order to provide new ideas for the study of the mechanism of aging and delaying aging.
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Affiliation(s)
| | | | | | | | | | - Jie Sun
- *Correspondence: Xiaojing Wang, ; Jie Sun,
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Deryabin PI, Borodkina AV. Epigenetic clocks provide clues to the mystery of uterine ageing. Hum Reprod Update 2022; 29:259-271. [PMID: 36515535 DOI: 10.1093/humupd/dmac042] [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: 08/12/2022] [Revised: 11/28/2022] [Indexed: 12/15/2022] Open
Abstract
BACKGROUND Rising maternal ages and age-related fertility decline are a global challenge for modern reproductive medicine. Clinicians and researchers pay specific attention to ovarian ageing and hormonal insufficiency in this regard. However, uterine ageing is often left out of the picture, with the majority of reproductive clinicians being close to unanimous on the absence of age-related functional decline in the uterine tissues. Therefore, most existing techniques to treat an age-related decline in implantation rates are based primarily on hormonal supplementation and oocyte donation. Solving the issue of uterine ageing might lead to an adjustment to these methods. OBJECTIVE AND RATIONALE A focus on uterine ageing and the possibility of slowing it emerged with the development of the information theory of ageing, which identifies genomic instability and erosion of the epigenetic landscape as important drivers of age-related decline in the functionality of most cells and tissues. Age-related smoothing of this landscape and a decline in tissue function can be assessed by measuring the ticking of epigenetic clocks. Within this review, we explore whether the uterus experiences age-related alterations using this elegant approach. We analyse existing data on epigenetic clocks in the endometrium, highlight approaches to improve the accuracy of the clocks in this cycling tissue, speculate on the endometrial pathologies whose progression might be predicted by the altered speed of epigenetic clocks and discuss the possibilities of slowing down the ticking of these clocks. SEARCH METHODS Data for this review were identified by searches of Medline, PubMed and Google Scholar. References from relevant articles using the search terms 'ageing', 'maternal age', 'female reproduction', 'uterus', 'endometrium', 'implantation', 'decidualization', 'epigenetic clock', 'biological age', 'DNA methylation', 'fertility' and 'infertility' were selected. A total of 95 articles published in English between 1985 and 2022 were included, six of which describe the use of the epigenetic clock to evaluate uterine/endometrium ageing. OUTCOMES Application of the Horvath and DNAm PhenoAge epigenetic clocks demonstrated a poor correlation with chronological age in the endometrium. Several approaches were suggested to enhance the predictive power of epigenetic clocks for the endometrium. The first was to increase the number of samples in the training dataset, as for the Zang clock, or to use more sophisticated clock-building algorithms, as for the AltumAge clock. The second method is to adjust the clocks according to the dynamic nature of the endometrium. Using either approach revealed a strong correlation with chronological age in the endometrium, providing solid evidence for age-related functional decline in this tissue. Furthermore, age acceleration/deceleration, as estimated by epigenetic clocks, might be a promising tool to predict or to gain insights into the origin of various endometrial pathologies, including recurrent implantation failure, cancer and endometriosis. Finally, there are several strategies to slow down or even reverse epigenetic clocks that might be applied to reduce the risk of age-related uterine impairments. WIDER IMPLICATIONS The uterine factor should be considered, along with ovarian issues, to correct for the decline in female fertility with age. Epigenetic clocks can be tested to gain a deeper understanding of various endometrial disorders.
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Affiliation(s)
- Pavel I Deryabin
- Mechanisms of Cellular Senescence Group, Institute of Cytology of the Russian Academy of Sciences, Saint-Petersburg, Russia
| | - Aleksandra V Borodkina
- Mechanisms of Cellular Senescence Group, Institute of Cytology of the Russian Academy of Sciences, Saint-Petersburg, Russia
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Aminzadeh-Gohari S, Kofler B, Herzog C. Dietary restriction in senolysis and prevention and treatment of disease. Crit Rev Food Sci Nutr 2022; 64:5242-5268. [PMID: 36484738 PMCID: PMC7616065 DOI: 10.1080/10408398.2022.2153355] [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] [Indexed: 12/13/2022]
Abstract
Aging represents a key risk factor for a plethora of diseases. Targeting detrimental processes which occur during aging, especially before onset of age-related disease, could provide drastic improvements in healthspan. There is increasing evidence that dietary restriction (DR), including caloric restriction, fasting, or fasting-mimicking diets, extend both lifespan and healthspan. This has sparked interest in the use of dietary regimens as a non-pharmacological means to slow aging and prevent disease. Here, we review the current evidence on the molecular mechanisms underlying DR-induced health improvements, including removal of senescent cells, metabolic reprogramming, and epigenetic rejuvenation.
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Affiliation(s)
- Sepideh Aminzadeh-Gohari
- Research Program for Receptor Biochemistry and Tumor Metabollism, Department of Pediatrics, University Hospital of the Paracelsus Medical University, Salzburg, Austria
- European Translational Oncology Prevention and Screening Institute, Universität Innsbruck, Innsbruck, Austria
- Research Institute for Biomedical Ageing, Universität Innsbruck, Innsbruck, Austria
| | - Barbara Kofler
- Research Program for Receptor Biochemistry and Tumor Metabollism, Department of Pediatrics, University Hospital of the Paracelsus Medical University, Salzburg, Austria
| | - Chiara Herzog
- European Translational Oncology Prevention and Screening Institute, Universität Innsbruck, Innsbruck, Austria
- Research Institute for Biomedical Ageing, Universität Innsbruck, Innsbruck, Austria
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Genome-Wide DNA Methylation Profile Indicates Potential Epigenetic Regulation of Aging in the Rhesus Macaque Thymus. Int J Mol Sci 2022; 23:ijms232314984. [PMID: 36499310 PMCID: PMC9738698 DOI: 10.3390/ijms232314984] [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: 10/21/2022] [Revised: 11/23/2022] [Accepted: 11/24/2022] [Indexed: 12/03/2022] Open
Abstract
We analyzed whole-genome bisulfite sequencing (WGBS) and RNA sequencing data of two young (1 year old) and two adult (9 years old) rhesus macaques (Macaca mulatta) to characterize the genomic DNA methylation profile of the thymus and explore the molecular mechanism of age-related changes in the thymus. Combining the two-omics data, we identified correlations between DNA methylation and gene expression and found that DNA methylation played an essential role in the functional changes of the aging thymus, especially in immunity and coagulation. The hypomethylation levels of C3 and C5AR2 and the hypermethylation level of C7 may lead to the high expressions of these genes in adult rhesus macaque thymuses, thus activating the classical complement pathway and the alternative pathway and enhancing their innate immune function. Adult thymuses had an enhanced coagulation pathway, which may have resulted from the hypomethylation and upregulated expressions of seven coagulation-promoting factor genes (F13A1, CLEC4D, CLEC4E, FCN3, PDGFRA, FGF2 and FGF7) and the hypomethylation and low expression of CPB2 to inhibit the degradation of blood clots. Furthermore, the functional decline in differentiation, activation and maturation of T cells in adult thymuses was also closely related to the changes in methylation levels and gene expression levels of T cell development genes (CD3G, GAD2, ADAMDEC1 and LCK) and the thymogenic hormone gene TMPO. A comparison of the age-related methylated genes among four mammal species revealed that most of the epigenetic clocks were species-specific. Furthermore, based on the genomic landscape of allele-specific DNA methylation, we identified several age-related clustered sequence-dependent allele-specific DNA methylated (cS-ASM) genes. Overall, these DNA methylation patterns may also help to assist with understanding the mechanisms of the aging thymus with the epigenome.
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Xie K, Fuchs H, Scifo E, Liu D, Aziz A, Aguilar-Pimentel JA, Amarie OV, Becker L, da Silva-Buttkus P, Calzada-Wack J, Cho YL, Deng Y, Edwards AC, Garrett L, Georgopoulou C, Gerlini R, Hölter SM, Klein-Rodewald T, Kramer M, Leuchtenberger S, Lountzi D, Mayer-Kuckuk P, Nover LL, Oestereicher MA, Overkott C, Pearson BL, Rathkolb B, Rozman J, Russ J, Schaaf K, Spielmann N, Sanz-Moreno A, Stoeger C, Treise I, Bano D, Busch DH, Graw J, Klingenspor M, Klopstock T, Mock BA, Salomoni P, Schmidt-Weber C, Weiergräber M, Wolf E, Wurst W, Gailus-Durner V, Breteler MMB, Hrabě de Angelis M, Ehninger D. Deep phenotyping and lifetime trajectories reveal limited effects of longevity regulators on the aging process in C57BL/6J mice. Nat Commun 2022; 13:6830. [PMID: 36369285 PMCID: PMC9652467 DOI: 10.1038/s41467-022-34515-y] [Citation(s) in RCA: 18] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2022] [Accepted: 10/27/2022] [Indexed: 11/13/2022] Open
Abstract
Current concepts regarding the biology of aging are primarily based on studies aimed at identifying factors regulating lifespan. However, lifespan as a sole proxy measure for aging can be of limited value because it may be restricted by specific pathologies. Here, we employ large-scale phenotyping to analyze hundreds of markers in aging male C57BL/6J mice. For each phenotype, we establish lifetime profiles to determine when age-dependent change is first detectable relative to the young adult baseline. We examine key lifespan regulators (putative anti-aging interventions; PAAIs) for a possible countering of aging. Importantly, unlike most previous studies, we include in our study design young treated groups of animals, subjected to PAAIs prior to the onset of detectable age-dependent phenotypic change. Many PAAI effects influence phenotypes long before the onset of detectable age-dependent change, but, importantly, do not alter the rate of phenotypic change. Hence, these PAAIs have limited effects on aging.
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Affiliation(s)
- Kan Xie
- Translational Biogerontology Lab, German Center for Neurodegenerative Diseases (DZNE), Venusberg-Campus 1/99, 53127, Bonn, Germany
| | - Helmut Fuchs
- Institute of Experimental Genetics, German Mouse Clinic, Helmholtz Zentrum München, German Research Center for Environmental Health, 85764, Neuherberg, Germany
| | - Enzo Scifo
- Translational Biogerontology Lab, German Center for Neurodegenerative Diseases (DZNE), Venusberg-Campus 1/99, 53127, Bonn, Germany
| | - Dan Liu
- Population Health Sciences, German Center for Neurodegenerative Diseases (DZNE), Venusberg-Campus 1/99, 53127, Bonn, Germany
| | - Ahmad Aziz
- Population Health Sciences, German Center for Neurodegenerative Diseases (DZNE), Venusberg-Campus 1/99, 53127, Bonn, Germany.,Department of Neurology, Faculty of Medicine, University of Bonn, Bonn, Germany
| | - Juan Antonio Aguilar-Pimentel
- Institute of Experimental Genetics, German Mouse Clinic, Helmholtz Zentrum München, German Research Center for Environmental Health, 85764, Neuherberg, Germany
| | - Oana Veronica Amarie
- Institute of Experimental Genetics, German Mouse Clinic, Helmholtz Zentrum München, German Research Center for Environmental Health, 85764, Neuherberg, Germany
| | - Lore Becker
- Institute of Experimental Genetics, German Mouse Clinic, Helmholtz Zentrum München, German Research Center for Environmental Health, 85764, Neuherberg, Germany
| | - Patricia da Silva-Buttkus
- Institute of Experimental Genetics, German Mouse Clinic, Helmholtz Zentrum München, German Research Center for Environmental Health, 85764, Neuherberg, Germany
| | - Julia Calzada-Wack
- Institute of Experimental Genetics, German Mouse Clinic, Helmholtz Zentrum München, German Research Center for Environmental Health, 85764, Neuherberg, Germany
| | - Yi-Li Cho
- Institute of Experimental Genetics, German Mouse Clinic, Helmholtz Zentrum München, German Research Center for Environmental Health, 85764, Neuherberg, Germany
| | - Yushuang Deng
- Translational Biogerontology Lab, German Center for Neurodegenerative Diseases (DZNE), Venusberg-Campus 1/99, 53127, Bonn, Germany
| | - A Cole Edwards
- Translational Biogerontology Lab, German Center for Neurodegenerative Diseases (DZNE), Venusberg-Campus 1/99, 53127, Bonn, Germany
| | - Lillian Garrett
- Institute of Experimental Genetics, German Mouse Clinic, Helmholtz Zentrum München, German Research Center for Environmental Health, 85764, Neuherberg, Germany.,Institute of Developmental Genetics, Helmholtz Zentrum München, German Research Center for Environmental Health, 85764, Neuherberg, Germany
| | - Christina Georgopoulou
- Translational Biogerontology Lab, German Center for Neurodegenerative Diseases (DZNE), Venusberg-Campus 1/99, 53127, Bonn, Germany
| | - Raffaele Gerlini
- Institute of Experimental Genetics, German Mouse Clinic, Helmholtz Zentrum München, German Research Center for Environmental Health, 85764, Neuherberg, Germany
| | - Sabine M Hölter
- Institute of Experimental Genetics, German Mouse Clinic, Helmholtz Zentrum München, German Research Center for Environmental Health, 85764, Neuherberg, Germany.,Institute of Developmental Genetics, Helmholtz Zentrum München, German Research Center for Environmental Health, 85764, Neuherberg, Germany
| | - Tanja Klein-Rodewald
- Institute of Experimental Genetics, German Mouse Clinic, Helmholtz Zentrum München, German Research Center for Environmental Health, 85764, Neuherberg, Germany
| | | | - Stefanie Leuchtenberger
- Institute of Experimental Genetics, German Mouse Clinic, Helmholtz Zentrum München, German Research Center for Environmental Health, 85764, Neuherberg, Germany
| | - Dimitra Lountzi
- Translational Biogerontology Lab, German Center for Neurodegenerative Diseases (DZNE), Venusberg-Campus 1/99, 53127, Bonn, Germany
| | - Phillip Mayer-Kuckuk
- Institute of Experimental Genetics, German Mouse Clinic, Helmholtz Zentrum München, German Research Center for Environmental Health, 85764, Neuherberg, Germany
| | - Lena L Nover
- Translational Biogerontology Lab, German Center for Neurodegenerative Diseases (DZNE), Venusberg-Campus 1/99, 53127, Bonn, Germany
| | - Manuela A Oestereicher
- Institute of Experimental Genetics, German Mouse Clinic, Helmholtz Zentrum München, German Research Center for Environmental Health, 85764, Neuherberg, Germany
| | - Clemens Overkott
- Translational Biogerontology Lab, German Center for Neurodegenerative Diseases (DZNE), Venusberg-Campus 1/99, 53127, Bonn, Germany
| | - Brandon L Pearson
- Translational Biogerontology Lab, German Center for Neurodegenerative Diseases (DZNE), Venusberg-Campus 1/99, 53127, Bonn, Germany.,Mailman School of Public Health, Columbia University, 630W. 168th St., New York, NY, 10032, USA
| | - Birgit Rathkolb
- Institute of Experimental Genetics, German Mouse Clinic, Helmholtz Zentrum München, German Research Center for Environmental Health, 85764, Neuherberg, Germany.,Member of German Center for Diabetes Research (DZD), 85764, Neuherberg, Germany.,Institute of Molecular Animal Breeding and Biotechnology, Gene Center, Ludwig-Maximilians-University Munich, Munich, Germany
| | - Jan Rozman
- Institute of Experimental Genetics, German Mouse Clinic, Helmholtz Zentrum München, German Research Center for Environmental Health, 85764, Neuherberg, Germany.,Member of German Center for Diabetes Research (DZD), 85764, Neuherberg, Germany.,Institute of Molecular Genetics of the Czech Academy of Sciences, Czech Centre for Phenogenomics, Prumyslova 595, Vestec, 252 50, Czech Republic
| | - Jenny Russ
- Nuclear Function Lab, German Center for Neurodegenerative Diseases (DZNE), Venusberg-Campus 1/99, 53127, Bonn, Germany
| | - Kristina Schaaf
- Translational Biogerontology Lab, German Center for Neurodegenerative Diseases (DZNE), Venusberg-Campus 1/99, 53127, Bonn, Germany
| | - Nadine Spielmann
- Institute of Experimental Genetics, German Mouse Clinic, Helmholtz Zentrum München, German Research Center for Environmental Health, 85764, Neuherberg, Germany
| | - Adrián Sanz-Moreno
- Institute of Experimental Genetics, German Mouse Clinic, Helmholtz Zentrum München, German Research Center for Environmental Health, 85764, Neuherberg, Germany
| | - Claudia Stoeger
- Institute of Experimental Genetics, German Mouse Clinic, Helmholtz Zentrum München, German Research Center for Environmental Health, 85764, Neuherberg, Germany
| | - Irina Treise
- Institute of Experimental Genetics, German Mouse Clinic, Helmholtz Zentrum München, German Research Center for Environmental Health, 85764, Neuherberg, Germany
| | - Daniele Bano
- Aging and Neurodegeneration Lab, German Center for Neurodegenerative Diseases (DZNE), Venusberg-Campus 1/99, 53127, Bonn, Germany
| | - Dirk H Busch
- Institute for Medical Microbiology, Immunology, and Hygiene, Technische Universität München, 81675, Munich, Germany
| | - Jochen Graw
- Institute of Developmental Genetics, Helmholtz Zentrum München, German Research Center for Environmental Health, 85764, Neuherberg, Germany
| | - Martin Klingenspor
- Molecular Nutritional Medicine, Else Kröner-Fresenius Center, Technische Universität München, 85350, Freising-Weihenstephan, Germany
| | - Thomas Klopstock
- Friedrich-Baur-Institut, Department of Neurology, Ludwig-Maximilians-University Munich, 80336, Munich, Germany.,DZNE, German Center for Neurodegenerative Diseases, 80336, Munich, Germany.,Munich Cluster for Systems Neurology (SyNergy), 80336, Munich, Germany
| | - Beverly A Mock
- Laboratory of Cancer Biology and Genetics, CCR, NCI, NIH, Bethesda, MD, 20892, USA
| | - Paolo Salomoni
- Nuclear Function Lab, German Center for Neurodegenerative Diseases (DZNE), Venusberg-Campus 1/99, 53127, Bonn, Germany
| | - Carsten Schmidt-Weber
- Center of Allergy & Environment (ZAUM), Technische Universität München, and Helmholtz Zentrum München, 85764, Neuherberg, Germany
| | - Marco Weiergräber
- Research Group Experimental Neuropsychopharmacology, Federal Institute for Drugs and Medical Devices, 53175, Bonn, Germany
| | - Eckhard Wolf
- Institute of Molecular Animal Breeding and Biotechnology, Gene Center, Ludwig-Maximilians-University Munich, Munich, Germany
| | - Wolfgang Wurst
- Institute of Developmental Genetics, Helmholtz Zentrum München, German Research Center for Environmental Health, 85764, Neuherberg, Germany.,DZNE, German Center for Neurodegenerative Diseases, 80336, Munich, Germany.,Chair of Developmental Genetics, TUM School of Life Sciences (SoLS), Technische Universität München, Freising, Germany
| | - Valérie Gailus-Durner
- Institute of Experimental Genetics, German Mouse Clinic, Helmholtz Zentrum München, German Research Center for Environmental Health, 85764, Neuherberg, Germany
| | - Monique M B Breteler
- Population Health Sciences, German Center for Neurodegenerative Diseases (DZNE), Venusberg-Campus 1/99, 53127, Bonn, Germany.,Institute for Medical Biometry, Informatics and Epidemiology, Faculty of Medicine, University of Bonn, Venusberg-Campus 1, 53127, Bonn, Germany
| | - Martin Hrabě de Angelis
- Institute of Experimental Genetics, German Mouse Clinic, Helmholtz Zentrum München, German Research Center for Environmental Health, 85764, Neuherberg, Germany.,Member of German Center for Diabetes Research (DZD), 85764, Neuherberg, Germany.,Chair of Experimental Genetics, TUM School of Life Sciences (SoLS), Technische Universität München, 85354, Freising, Germany
| | - Dan Ehninger
- Translational Biogerontology Lab, German Center for Neurodegenerative Diseases (DZNE), Venusberg-Campus 1/99, 53127, Bonn, Germany.
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Wang K, Liu H, Hu Q, Wang L, Liu J, Zheng Z, Zhang W, Ren J, Zhu F, Liu GH. Epigenetic regulation of aging: implications for interventions of aging and diseases. Signal Transduct Target Ther 2022; 7:374. [PMID: 36336680 PMCID: PMC9637765 DOI: 10.1038/s41392-022-01211-8] [Citation(s) in RCA: 149] [Impact Index Per Article: 74.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2022] [Revised: 09/14/2022] [Accepted: 09/28/2022] [Indexed: 11/09/2022] Open
Abstract
Aging is accompanied by the decline of organismal functions and a series of prominent hallmarks, including genetic and epigenetic alterations. These aging-associated epigenetic changes include DNA methylation, histone modification, chromatin remodeling, non-coding RNA (ncRNA) regulation, and RNA modification, all of which participate in the regulation of the aging process, and hence contribute to aging-related diseases. Therefore, understanding the epigenetic mechanisms in aging will provide new avenues to develop strategies to delay aging. Indeed, aging interventions based on manipulating epigenetic mechanisms have led to the alleviation of aging or the extension of the lifespan in animal models. Small molecule-based therapies and reprogramming strategies that enable epigenetic rejuvenation have been developed for ameliorating or reversing aging-related conditions. In addition, adopting health-promoting activities, such as caloric restriction, exercise, and calibrating circadian rhythm, has been demonstrated to delay aging. Furthermore, various clinical trials for aging intervention are ongoing, providing more evidence of the safety and efficacy of these therapies. Here, we review recent work on the epigenetic regulation of aging and outline the advances in intervention strategies for aging and age-associated diseases. A better understanding of the critical roles of epigenetics in the aging process will lead to more clinical advances in the prevention of human aging and therapy of aging-related diseases.
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Affiliation(s)
- Kang Wang
- State Key Laboratory of Membrane Biology, Institute of Zoology, Chinese Academy of Sciences, 100101, Beijing, China
- State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, 100101, Beijing, China
- University of Chinese Academy of Sciences, 100049, Beijing, China
| | - Huicong Liu
- School of Biomedical Engineering, Shanghai Jiao Tong University, 200030, Shanghai, China
| | - Qinchao Hu
- State Key Laboratory of Membrane Biology, Institute of Zoology, Chinese Academy of Sciences, 100101, Beijing, China
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, 100101, Beijing, China
- Hospital of Stomatology, Sun Yat-sen University, 510060, Guangzhou, China
- Guangdong Provincial Key Laboratory of Stomatology, Guanghua School of Stomatology, Sun Yat-sen University, 510060, Guangzhou, China
| | - Lingna Wang
- School of Biomedical Engineering, Shanghai Jiao Tong University, 200030, Shanghai, China
| | - Jiaqing Liu
- School of Biomedical Engineering, Shanghai Jiao Tong University, 200030, Shanghai, China
| | - Zikai Zheng
- University of Chinese Academy of Sciences, 100049, Beijing, China
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, 100101, Beijing, China
| | - Weiqi Zhang
- University of Chinese Academy of Sciences, 100049, Beijing, China
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, 100101, Beijing, China
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, 100101, Beijing, China
| | - Jie Ren
- University of Chinese Academy of Sciences, 100049, Beijing, China.
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, 100101, Beijing, China.
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, 100101, Beijing, China.
| | - Fangfang Zhu
- School of Biomedical Engineering, Shanghai Jiao Tong University, 200030, Shanghai, China.
| | - Guang-Hui Liu
- State Key Laboratory of Membrane Biology, Institute of Zoology, Chinese Academy of Sciences, 100101, Beijing, China.
- University of Chinese Academy of Sciences, 100049, Beijing, China.
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, 100101, Beijing, China.
- Advanced Innovation Center for Human Brain Protection, National Clinical Research Center for Geriatric Disorders, Xuanwu Hospital, Capital Medical University, 100053, Beijing, China.
- Beijing Institute for Stem Cell and Regenerative Medicine, 100101, Beijing, China.
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Li A, Koch Z, Ideker T. Epigenetic aging: Biological age prediction and informing a mechanistic theory of aging. J Intern Med 2022; 292:733-744. [PMID: 35726002 DOI: 10.1111/joim.13533] [Citation(s) in RCA: 34] [Impact Index Per Article: 17.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/29/2022]
Abstract
Numerous studies have shown that epigenetic age-an individual's degree of aging based on patterns of DNA methylation-can be computed and is associated with an array of factors including diet, lifestyle, genetics, and disease. One can expect that still further associations will emerge with additional aging research, but to what end? Prediction of age was an important first step, but-in our view-the focus must shift from chasing increasingly accurate age computations to understanding the links between the epigenome and the mechanisms and physiological changes of aging. Here, we outline emerging areas of epigenetic aging research that prioritize biological understanding and clinical application. First, we survey recent progress in epigenetic clocks, which are beginning to predict not only chronological age but aging outcomes such as all-cause mortality and onset of disease, or which integrate aging signals across multiple biological processes. Second, we discuss research that exemplifies how investigation of the epigenome is building a mechanistic theory of aging and informing clinical practice. Such examples include identifying methylation sites and the genes most strongly predictive of aging-a subset of which have shown strong potential as biomarkers of neurodegenerative disease and cancer; relating epigenetic clock predictions to hallmarks of aging; and using longitudinal studies of DNA methylation to characterize human disease, resulting in the discovery of epigenetic indications of type 1 diabetes and the propensity for psychotic experiences.
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Affiliation(s)
- Adam Li
- Division of Genetics, Department of Medicine, University of California San Diego, La Jolla, California, USA
| | - Zane Koch
- Division of Genetics, Department of Medicine, University of California San Diego, La Jolla, California, USA
| | - Trey Ideker
- Division of Genetics, Department of Medicine, University of California San Diego, La Jolla, California, USA
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Epigenetic clock: A promising biomarker and practical tool in aging. Ageing Res Rev 2022; 81:101743. [PMID: 36206857 DOI: 10.1016/j.arr.2022.101743] [Citation(s) in RCA: 53] [Impact Index Per Article: 26.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2022] [Revised: 09/13/2022] [Accepted: 09/30/2022] [Indexed: 01/31/2023]
Abstract
As a complicated process, aging is characterized by various changes at the cellular, subcellular and nuclear levels, one of which is epigenetic aging. With increasing awareness of the critical role that epigenetic alternations play in aging, DNA methylation patterns have been employed as a measure of biological age, currently referred to as the epigenetic clock. This review provides a comprehensive overview of the epigenetic clock as a biomarker of aging and a useful tool to manage healthy aging. In this burgeoning scientific field, various kinds of epigenetic clocks continue to emerge, including Horvath's clock, Hannum's clock, DNA PhenoAge, and DNA GrimAge. We hereby present the most classic epigenetic clocks, as well as their differences. Correlations of epigenetic age with morbidity, mortality and other factors suggest the potential of epigenetic clocks for risk prediction and identification in the context of aging. In particular, we summarize studies on promising age-reversing interventions, with epigenetic clocks employed as a practical tool in the efficacy evaluation. We also discuss how the lack of higher-quality information poses a major challenge, and offer some suggestions to address existing obstacles. Hopefully, our review will help provide an appropriate understanding of the epigenetic clocks, thereby enabling novel insights into the aging process and how it can be manipulated to promote healthy aging.
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