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Diez Benavente E, Hartman RJG, Sakkers TR, Wesseling M, Sloots Y, Slenders L, Boltjes A, Mol BM, de Borst GJ, de Kleijn DPV, Prange KHM, de Winther MPJ, Kuiper J, Civelek M, van der Laan SW, Horvath S, Onland-Moret NC, Mokry M, Pasterkamp G, den Ruijter HM. Atherosclerotic Plaque Epigenetic Age Acceleration Predicts a Poor Prognosis and Is Associated With Endothelial-to-Mesenchymal Transition in Humans. Arterioscler Thromb Vasc Biol 2024; 44:1419-1431. [PMID: 38634280 DOI: 10.1161/atvbaha.123.320692] [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: 01/08/2024] [Accepted: 03/25/2024] [Indexed: 04/19/2024]
Abstract
BACKGROUND Epigenetic age estimators (clocks) are predictive of human mortality risk. However, it is not yet known whether the epigenetic age of atherosclerotic plaques is predictive for the risk of cardiovascular events. METHODS Whole-genome DNA methylation of human carotid atherosclerotic plaques (n=485) and of blood (n=93) from the Athero-Express endarterectomy cohort was used to calculate epigenetic age acceleration (EAA). EAA was linked to clinical characteristics, plaque histology, and future cardiovascular events (n=136). We studied whole-genome DNA methylation and bulk and single-cell transcriptomics to uncover molecular mechanisms of plaque EAA. We experimentally confirmed our in silico findings using in vitro experiments in primary human coronary endothelial cells. RESULTS Male and female patients with severe atherosclerosis had a median chronological age of 69 years. The median epigenetic age was 65 years in females (median EAA, -2.2 [interquartile range, -4.3 to 2.2] years) and 68 years in males (median EAA, -0.3 [interquartile range, -2.9 to 3.8] years). Patients with diabetes and a high body mass index had higher plaque EAA. Increased EAA of plaque predicted future events in a 3-year follow-up in a Cox regression model (univariate hazard ratio, 1.7; P=0.0034) and adjusted multivariate model (hazard ratio, 1.56; P=0.02). Plaque EAA predicted outcome independent of blood EAA (hazard ratio, 1.3; P=0.018) and of plaque hemorrhage (hazard ratio, 1.7; P=0.02). Single-cell RNA sequencing in plaque samples from 46 patients in the same cohort revealed smooth muscle and endothelial cells as important cell types in plaque EAA. Endothelial-to-mesenchymal transition was associated with EAA, which was experimentally confirmed by TGFβ-triggered endothelial-to-mesenchymal transition inducing rapid epigenetic aging in coronary endothelial cells. CONCLUSIONS Plaque EAA is a strong and independent marker of poor outcome in patients with severe atherosclerosis. Plaque EAA was linked to mesenchymal endothelial and smooth muscle cells. Endothelial-to-mesenchymal transition was associated with EAA, which was experimentally validated. Epigenetic aging mechanisms may provide new targets for treatments that reduce atherosclerosis complications.
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Affiliation(s)
- Ernest Diez Benavente
- Laboratory of Experimental Cardiology (E.D.B., R.J.G.H., T.R.S., Y.S., M.M., H.M.d.R.), University Medical Center Utrecht, Utrecht University, the Netherlands
| | - Robin J G Hartman
- Laboratory of Experimental Cardiology (E.D.B., R.J.G.H., T.R.S., Y.S., M.M., H.M.d.R.), University Medical Center Utrecht, Utrecht University, the Netherlands
| | - Tim R Sakkers
- Laboratory of Experimental Cardiology (E.D.B., R.J.G.H., T.R.S., Y.S., M.M., H.M.d.R.), University Medical Center Utrecht, Utrecht University, the Netherlands
| | - Marian Wesseling
- Central Diagnostic Laboratory (M.W., L.S., A.B., S.W.v.d.L., M.M., G.P.), University Medical Center Utrecht, Utrecht University, the Netherlands
| | - Yannicke Sloots
- Laboratory of Experimental Cardiology (E.D.B., R.J.G.H., T.R.S., Y.S., M.M., H.M.d.R.), University Medical Center Utrecht, Utrecht University, the Netherlands
| | - Lotte Slenders
- Central Diagnostic Laboratory (M.W., L.S., A.B., S.W.v.d.L., M.M., G.P.), University Medical Center Utrecht, Utrecht University, the Netherlands
| | - Arjan Boltjes
- Central Diagnostic Laboratory (M.W., L.S., A.B., S.W.v.d.L., M.M., G.P.), University Medical Center Utrecht, Utrecht University, the Netherlands
| | - Barend M Mol
- Department of Vascular Surgery (B.M.M., G.J.d.B., D.P.V.d.K.), University Medical Center Utrecht, Utrecht University, the Netherlands
| | - Gert J de Borst
- Department of Vascular Surgery (B.M.M., G.J.d.B., D.P.V.d.K.), University Medical Center Utrecht, Utrecht University, the Netherlands
| | - Dominique P V de Kleijn
- Department of Vascular Surgery (B.M.M., G.J.d.B., D.P.V.d.K.), University Medical Center Utrecht, Utrecht University, the Netherlands
| | - Koen H M Prange
- Division of Biotherapeutics, Leiden Academic Centre for Drug Research, Leiden University, the Netherlands (K.H.M.P., M.P.J.d.W., J.K.)
| | - Menno P J de Winther
- Division of Biotherapeutics, Leiden Academic Centre for Drug Research, Leiden University, the Netherlands (K.H.M.P., M.P.J.d.W., J.K.)
| | - Johan Kuiper
- Division of Biotherapeutics, Leiden Academic Centre for Drug Research, Leiden University, the Netherlands (K.H.M.P., M.P.J.d.W., J.K.)
| | - Mete Civelek
- Center for Public Health Genomics (M.C.), University of Virginia, Charlottesville
- Department of Biomedical Engineering (M.C.), University of Virginia, Charlottesville
| | - Sander W van der Laan
- Central Diagnostic Laboratory (M.W., L.S., A.B., S.W.v.d.L., M.M., G.P.), University Medical Center Utrecht, Utrecht University, the Netherlands
| | - Steve Horvath
- Department of Human Genetics, David Geffen School of Medicine (S.H.), University of California, Los Angeles
- Department of Biostatistics, Fielding School of Public Health (S.H.), University of California, Los Angeles
- Altos Labs, Cambridge Institute of Science, United Kingdom (S.H.)
| | - N Charlotte Onland-Moret
- Julius Center for Health Sciences and Primary Care (N.C.O.-M.), University Medical Center Utrecht, Utrecht University, the Netherlands
| | - Michal Mokry
- Laboratory of Experimental Cardiology (E.D.B., R.J.G.H., T.R.S., Y.S., M.M., H.M.d.R.), University Medical Center Utrecht, Utrecht University, the Netherlands
- Central Diagnostic Laboratory (M.W., L.S., A.B., S.W.v.d.L., M.M., G.P.), University Medical Center Utrecht, Utrecht University, the Netherlands
| | - Gerard Pasterkamp
- Central Diagnostic Laboratory (M.W., L.S., A.B., S.W.v.d.L., M.M., G.P.), University Medical Center Utrecht, Utrecht University, the Netherlands
| | - Hester M den Ruijter
- Laboratory of Experimental Cardiology (E.D.B., R.J.G.H., T.R.S., Y.S., M.M., H.M.d.R.), University Medical Center Utrecht, Utrecht University, the Netherlands
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Tarkhov AE, Lindstrom-Vautrin T, Zhang S, Ying K, Moqri M, Zhang B, Tyshkovskiy A, Levy O, Gladyshev VN. Nature of epigenetic aging from a single-cell perspective. NATURE AGING 2024:10.1038/s43587-024-00616-0. [PMID: 38724733 DOI: 10.1038/s43587-024-00616-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/20/2023] [Accepted: 03/26/2024] [Indexed: 05/15/2024]
Abstract
Age-related changes in DNA methylation (DNAm) form the basis of the most robust predictors of age-epigenetic clocks-but a clear mechanistic understanding of exactly which aspects of aging are quantified by these clocks is lacking. Here, to clarify the nature of epigenetic aging, we juxtapose the dynamics of tissue and single-cell DNAm in mice. We compare these changes during early development with those observed during adult aging in mice, and corroborate our analyses with a single-cell RNA sequencing analysis within the same multiomics dataset. We show that epigenetic aging involves co-regulated changes as well as a major stochastic component, and this is consistent with transcriptional patterns. We further support the finding of stochastic epigenetic aging by direct tissue and single-cell DNAm analyses and modeling of aging DNAm trajectories with a stochastic process akin to radiocarbon decay. Finally, we describe a single-cell algorithm for the identification of co-regulated and stochastic CpG clusters showing consistent transcriptomic coordination patterns. Together, our analyses increase our understanding of the basis of epigenetic clocks and highlight potential opportunities for targeting aging and evaluating longevity interventions.
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Affiliation(s)
- Andrei E Tarkhov
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA.
- Retro Biosciences Inc., Redwood City, CA, USA.
| | - Thomas Lindstrom-Vautrin
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Sirui Zhang
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Kejun Ying
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Mahdi Moqri
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Department of Obstetrics & Gynecology, Stanford School of Medicine, Stanford University, Stanford, CA, USA
- Institute for Stem Cell Biology and Regenerative Medicine, Stanford School of Medicine, Stanford University, Stanford, CA, USA
| | - Bohan Zhang
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Alexander Tyshkovskiy
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Orr Levy
- Howard Hughes Medical Institute, Chevy Chase, MD, USA
- Department of Immunobiology, Yale University School of Medicine, New Haven, CT, USA
| | - Vadim N Gladyshev
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA.
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Cai Y, Han Z, Cheng H, Li H, Wang K, Chen J, Liu ZX, Xie Y, Lin Y, Zhou S, Wang S, Zhou X, Jin S. The impact of ageing mechanisms on musculoskeletal system diseases in the elderly. Front Immunol 2024; 15:1405621. [PMID: 38774874 PMCID: PMC11106385 DOI: 10.3389/fimmu.2024.1405621] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2024] [Accepted: 04/22/2024] [Indexed: 05/24/2024] Open
Abstract
Ageing is an inevitable process that affects various tissues and organs of the human body, leading to a series of physiological and pathological changes. Mechanisms such as telomere depletion, stem cell depletion, macrophage dysfunction, and cellular senescence gradually manifest in the body, significantly increasing the incidence of diseases in elderly individuals. These mechanisms interact with each other, profoundly impacting the quality of life of older adults. As the ageing population continues to grow, the burden on the public health system is expected to intensify. Globally, the prevalence of musculoskeletal system diseases in elderly individuals is increasing, resulting in reduced limb mobility and prolonged suffering. This review aims to elucidate the mechanisms of ageing and their interplay while exploring their impact on diseases such as osteoarthritis, osteoporosis, and sarcopenia. By delving into the mechanisms of ageing, further research can be conducted to prevent and mitigate its effects, with the ultimate goal of alleviating the suffering of elderly patients in the future.
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Affiliation(s)
- Yijin Cai
- School of Medical and Life Sciences, Chengdu University of Traditional Chinese Medicine, Chengdu, China
| | - Zhongyu Han
- School of Medical and Life Sciences, Chengdu University of Traditional Chinese Medicine, Chengdu, China
| | - Hong Cheng
- School of Automation Engineering, University of Electronic Science and Technology, Chengdu, China
| | - Hongpeng Li
- School of Medical and Life Sciences, Chengdu University of Traditional Chinese Medicine, Chengdu, China
| | - Ke Wang
- Eye School of Chengdu University of Traditional Chinese Medicine, Chengdu, China
| | - Jia Chen
- School of Health Preservation and Rehabilitation, Chengdu University of Traditional Chinese Medicine, Chengdu, China
| | - Zhi-Xiang Liu
- School of Health Preservation and Rehabilitation, Chengdu University of Traditional Chinese Medicine, Chengdu, China
| | - Yulong Xie
- School of Health Preservation and Rehabilitation, Chengdu University of Traditional Chinese Medicine, Chengdu, China
| | - Yumeng Lin
- Eye School of Chengdu University of Traditional Chinese Medicine, Chengdu, China
| | - Shuwei Zhou
- Jiangsu Key Laboratory of Molecular and Functional Imaging, Department of Radiology, Zhongda Hospital, School of Medicine, Southeast University, Nanjing, China
| | - Siyu Wang
- Department of Gastroenterology, The First Hospital of Hunan University of Chinese Medicine, Changsha, China
| | - Xiao Zhou
- Second Clinical Medical College, Heilongjiang University of Chinese Medicine, Heilongjiang, China
| | - Song Jin
- Department of Rehabilitation, Hospital of Chengdu University of Traditional Chinese Medicine, Chengdu, China
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Shi W, Fang J, Ren H, Sun P, Liu J, Deng F, Zhang S, Wang Q, Wang J, Tong S, Tang S, Shi X. Association between exposure to chemical mixtures and epigenetic ageing biomarkers: Modifying effects of thyroid hormones and physical activity. JOURNAL OF HAZARDOUS MATERIALS 2024; 469:134009. [PMID: 38492399 DOI: 10.1016/j.jhazmat.2024.134009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/15/2023] [Revised: 02/23/2024] [Accepted: 03/09/2024] [Indexed: 03/18/2024]
Abstract
Evidence on the effects of internal chemical mixture exposures on biological age is limited. It also remains unclear whether hormone homeostasis and lifestyle factors can modify such a relationship. Based on the Biomarkers for Air Pollutants Exposure (BAPE) study, which involved healthy older adults aged 60-69 years in China, we found that chemical mixture exposures, including metals, polycyclic aromatic hydrocarbons (PAHs), per- and polyfluoroalkyl substances (PFASs), phthalates (PAEs), and organophosphate esters (OPEs), were significantly associated with shortened DNAmTL and accelerated SkinBloodClock, in which PFASs and OPEs in blood were the primary contributors to DNAmTL, while metals and PAEs had relatively higher contributions in urine. Furthermore, lower levels of thyroxin appeared to exacerbate the adverse effects of environmental chemicals on epigenetic ageing but relatively higher levels of physical activity had the beneficial impact. These findings may have important implications for the development of healthy ageing strategy and aged care policy, particularly in light of the global acceleration of population ageing.
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Affiliation(s)
- Wanying Shi
- Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, and Beijing Municipal Key Laboratory of Clinical Epidemiology, Beijing 100069, China; China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
| | - Jianlong Fang
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
| | - Huimin Ren
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China; Department of Toxicology, School of Public Health, China Medical University, Shenyang, Liaoning 110122, China
| | - Peijie Sun
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China; Department of Toxicology, School of Public Health, China Medical University, Shenyang, Liaoning 110122, China
| | - Juan Liu
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
| | - Fuchang Deng
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
| | - Shuyi Zhang
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
| | - Qiong Wang
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
| | - Jiaonan Wang
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
| | - Shilu Tong
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China; School of Public Health and Social Work, Queensland University of Technology, Brisbane 4001, Australia
| | - Song Tang
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China; Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu 211166, China.
| | - Xiaoming Shi
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China; Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu 211166, China.
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5
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Martinez-Feduchi P, Jin P, Yao B. Epigenetic modifications of DNA and RNA in Alzheimer's disease. Front Mol Neurosci 2024; 17:1398026. [PMID: 38726308 PMCID: PMC11079283 DOI: 10.3389/fnmol.2024.1398026] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2024] [Accepted: 04/15/2024] [Indexed: 05/12/2024] Open
Abstract
Alzheimer's disease (AD) is a complex neurodegenerative disorder and the most common form of dementia. There are two main types of AD: familial and sporadic. Familial AD is linked to mutations in amyloid precursor protein (APP), presenilin-1 (PSEN1), and presenilin-2 (PSEN2). On the other hand, sporadic AD is the more common form of the disease and has genetic, epigenetic, and environmental components that influence disease onset and progression. Investigating the epigenetic mechanisms associated with AD is essential for increasing understanding of pathology and identifying biomarkers for diagnosis and treatment. Chemical covalent modifications on DNA and RNA can epigenetically regulate gene expression at transcriptional and post-transcriptional levels and play protective or pathological roles in AD and other neurodegenerative diseases.
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Affiliation(s)
| | | | - Bing Yao
- Department of Human Genetics, Emory University School of Medicine, Atlanta, GA, United States
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Frey HC, Sun X, Oudeif F, Corona DL, He Z, Won T, Schultz TL, Carruthers VB, Laouar A, Laouar Y. A Membrane Lipid Signature Unravels the Dynamic Landscape of Group 1 ILCs. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.04.17.589821. [PMID: 38659946 PMCID: PMC11042254 DOI: 10.1101/2024.04.17.589821] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/26/2024]
Abstract
In an era where the established lines between cell identities are blurred by intra-lineage plasticity, distinguishing between stable and transitional states becomes imperative. This challenge is particularly pronounced within the Group 1 ILC lineage, where the similarity and plasticity between NK cells and ILC1s obscure their classification and the assignment of their unique contributions to immune regulation. This study exploits the unique property of Asialo-GM1 (AsGM1)-a membrane lipid associated with cytotoxic attributes absent in ILC1s-as a definitive criterion to distinguish between these cells. By prioritizing cytotoxic potential as the cardinal differentiator, our strategic use of the AsGM1 signature achieved precise delineation of NK cells and ILC1s across tissues, validated by RNA-seq analysis. This capability extends beyond steady-state classifications, adeptly capturing the binary classification of NK cells and ILC1s during acute liver injury. By leveraging two established models of NK-to-ILC1 plasticity driven by TGFβ and Toxoplasma gondii , we demonstrate the stability of the AsGM1 signature, which sharply contrasts with the loss of Eomes. This signature identified a spectrum of known and novel NK cell derivatives-ILC1-like entities that bridge traditional binary classifications in aging and infection. The early detection of the AsGM1 signature at the immature NK (iNK) stage, preceding Eomes, and its stability, unaffected by transcriptional reprogramming that typically alters Eomes, position AsGM1 as a unique, site-agnostic marker for fate mapping NK-to-ILC1 plasticity. This provides a powerful tool to explore the expanding heterogeneity within the Group 1 ILC landscape, effectively transcending the ambiguity inherent to the NK-to-ILC1 continuum.
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Abdelrahman Z, Maxwell AP, McKnight AJ. Genetic and Epigenetic Associations with Post-Transplant Diabetes Mellitus. Genes (Basel) 2024; 15:503. [PMID: 38674437 PMCID: PMC11050138 DOI: 10.3390/genes15040503] [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: 03/12/2024] [Revised: 04/10/2024] [Accepted: 04/12/2024] [Indexed: 04/28/2024] Open
Abstract
Post-transplant diabetes mellitus (PTDM) is a common complication of solid organ transplantation. PTDM prevalence varies due to different diabetes definitions. Consensus guidelines for the diagnosis of PTDM have been published based on random blood glucose levels, glycated hemoglobin (HbA1c), and oral glucose tolerance test (OGTT). The task of diagnosing PTDM continues to pose challenges, given the potential for diabetes to manifest at different time points after transplantation, thus demanding constant clinical vigilance and repeated testing. Interpreting HbA1c levels can be challenging after renal transplantation. Pre-transplant risk factors for PTDM include obesity, sedentary lifestyle, family history of diabetes, ethnicity (e.g., African-Caribbean or South Asian ancestry), and genetic risk factors. Risk factors for PTDM include immunosuppressive drugs, weight gain, hepatitis C, and cytomegalovirus infection. There is also emerging evidence that genetic and epigenetic variation in the organ transplant recipient may influence the risk of developing PTDM. This review outlines many known risk factors for PTDM and details some of the pathways, genetic variants, and epigenetic features associated with PTDM. Improved understanding of established and emerging risk factors may help identify people at risk of developing PTDM and may reduce the risk of developing PTDM or improve the management of this complication of organ transplantation.
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Affiliation(s)
- Zeinab Abdelrahman
- Centre for Public Health, Queen’s University of Belfast, Belfast BT12 6BA, UK; (Z.A.); (A.P.M.)
| | - Alexander Peter Maxwell
- Centre for Public Health, Queen’s University of Belfast, Belfast BT12 6BA, UK; (Z.A.); (A.P.M.)
- Regional Nephrology Unit, Belfast City Hospital, Belfast BT9 7AB, UK
| | - Amy Jayne McKnight
- Centre for Public Health, Queen’s University of Belfast, Belfast BT12 6BA, UK; (Z.A.); (A.P.M.)
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Pio-Lopez L, Levin M. Aging as a loss of morphostatic information: A developmental bioelectricity perspective. Ageing Res Rev 2024; 97:102310. [PMID: 38636560 DOI: 10.1016/j.arr.2024.102310] [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: 11/05/2023] [Revised: 02/21/2024] [Accepted: 04/12/2024] [Indexed: 04/20/2024]
Abstract
Maintaining order at the tissue level is crucial throughout the lifespan, as failure can lead to cancer and an accumulation of molecular and cellular disorders. Perhaps, the most consistent and pervasive result of these failures is aging, which is characterized by the progressive loss of function and decline in the ability to maintain anatomical homeostasis and reproduce. This leads to organ malfunction, diseases, and ultimately death. The traditional understanding of aging is that it is caused by the accumulation of molecular and cellular damage. In this article, we propose a complementary view of aging from the perspective of endogenous bioelectricity which has not yet been integrated into aging research. We propose a view of aging as a morphostasis defect, a loss of biophysical prepattern information, encoding anatomical setpoints used for dynamic tissue and organ homeostasis. We hypothesize that this is specifically driven by abrogation of the endogenous bioelectric signaling that normally harnesses individual cell behaviors toward the creation and upkeep of complex multicellular structures in vivo. Herein, we first describe bioelectricity as the physiological software of life, and then identify and discuss the links between bioelectricity and life extension strategies and age-related diseases. We develop a bridge between aging and regeneration via bioelectric signaling that suggests a research program for healthful longevity via morphoceuticals. Finally, we discuss the broader implications of the homologies between development, aging, cancer and regeneration and how morphoceuticals can be developed for aging.
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Affiliation(s)
- Léo Pio-Lopez
- Allen Discovery Center, Tufts University, Medford, MA 02155, USA
| | - Michael Levin
- Allen Discovery Center, Tufts University, Medford, MA 02155, USA; Wyss Institute for Biologically Inspired Engineering, Boston, MA 02115, USA.
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Jeremian R, Lytvyn Y, Fotovati R, Li K, Malinowski A, Sachdeva M, Jack C, Gooderham M, Croitoru DO, Yeung J, Piguet V. Dysregulation of epigenetic, biological and mitotic age in the context of biologic drug treatment and phototherapy in plaque psoriasis patients. J Eur Acad Dermatol Venereol 2024. [PMID: 38619335 DOI: 10.1111/jdv.19978] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/25/2023] [Accepted: 02/28/2024] [Indexed: 04/16/2024]
Affiliation(s)
- Richie Jeremian
- Faculty of Medicine and Health Sciences, McGill University, Montréal, Quebec, Canada
- McGill University Health Centre (MUHC) Center of Excellence for Atopic Dermatitis, Montréal, Quebec, Canada
| | - Yuliya Lytvyn
- Division of Dermatology, Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
| | - Rayyan Fotovati
- Faculty of Medicine and Health Sciences, McGill University, Montréal, Quebec, Canada
| | - Kaiyang Li
- Faculty of Medicine and Health Sciences, McGill University, Montréal, Quebec, Canada
- McGill University Health Centre (MUHC) Center of Excellence for Atopic Dermatitis, Montréal, Quebec, Canada
| | - Alexandra Malinowski
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada
| | - Muskaan Sachdeva
- Division of Dermatology, Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
| | - Carolyn Jack
- Faculty of Medicine and Health Sciences, McGill University, Montréal, Quebec, Canada
- McGill University Health Centre (MUHC) Center of Excellence for Atopic Dermatitis, Montréal, Quebec, Canada
| | | | - David O Croitoru
- Division of Dermatology, Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
| | - Jensen Yeung
- Division of Dermatology, Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
| | - Vincent Piguet
- Division of Dermatology, Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
- Division of Dermatology, Department of Medicine, Women's College Hospital, Toronto, Ontario, Canada
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Weigl M, Krammer TL, Pultar M, Wieser M, Chaib S, Suda M, Diendorfer A, Khamina-Kotisch K, Giorgadze N, Pirtskhalava T, Johnson KO, Inman CL, Xue A, Lämmermann I, Meixner B, Wang L, Xu M, Grillari R, Ogrodnik M, Tchkonia T, Hackl M, Kirkland JL, Grillari J. Profiling microRNA expression during senescence and aging: mining for a diagnostic tool of senescent-cell burden. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.04.10.588794. [PMID: 38645053 PMCID: PMC11030445 DOI: 10.1101/2024.04.10.588794] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/23/2024]
Abstract
In the last decade cellular senescence, a hallmark of aging, has come into focus for pharmacologically targeting aging processes. Senolytics are one of these interventive strategies that have advanced into clinical trials, creating an unmet need for minimally invasive biomarkers of senescent cell load to identify patients at need for senotherapy. We created a landscape of miRNA and mRNA expression in five human cell types induced to senescence in-vitro and provide proof-of-principle evidence that miRNA expression can track senescence burden dynamically in-vivo using transgenic p21 high senescent cell clearance in HFD fed mice. Finally, we profiled miRNA expression in seven different tissues, total plasma, and plasma derived EVs of young and 25 months old mice. In a systematic analysis, we identified 22 candidate senomiRs with potential to serve as circulating biomarkers of senescence not only in rodents, but also in upcoming human clinical senolytic trials.
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11
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Pedicino D, Liuzzo G. Plasma proteins can tell your biological organs' age (including the heart). Eur Heart J 2024; 45:1196-1197. [PMID: 38289864 DOI: 10.1093/eurheartj/ehae038] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/01/2024] Open
Affiliation(s)
- Daniela Pedicino
- Department of Cardiovascular Medicine, Fondazione Policlinico Universitario A. Gemelli-IRCCS, Largo A. Gemelli 8, Rome 00168, Italy
| | - Giovanna Liuzzo
- Department of Cardiovascular Medicine, Fondazione Policlinico Universitario A. Gemelli-IRCCS, Largo A. Gemelli 8, Rome 00168, Italy
- Department of Cardiovascular and Pulmonary Sciences, Catholic University, School of Medicine, Largo F. Vito 1, Rome 00168, Italy
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12
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Mboning L, Rubbi L, Thompson M, Bouchard LS, Pellegrini M. BayesAge: A maximum likelihood algorithm to predict epigenetic age. FRONTIERS IN BIOINFORMATICS 2024; 4:1329144. [PMID: 38638123 PMCID: PMC11024280 DOI: 10.3389/fbinf.2024.1329144] [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: 10/28/2023] [Accepted: 02/01/2024] [Indexed: 04/20/2024] Open
Abstract
Introduction: DNA methylation, specifically the formation of 5-methylcytosine at the C5 position of cytosine, undergoes reproducible changes as organisms age, establishing it as a significant biomarker in aging studies. Epigenetic clocks, which integrate methylation patterns to predict age, often employ linear models based on penalized regression, yet they encounter challenges in handling missing data, count-based bisulfite sequence data, and interpretation. Methods: To address these limitations, we introduce BayesAge, an extension of the scAge methodology originally designed for single-cell DNA methylation analysis. BayesAge employs maximum likelihood estimation (MLE) for age inference, models count data using binomial distributions, and incorporates LOWESS smoothing to capture non-linear methylation-age dynamics. This approach is tailored for bulk bisulfite sequencing datasets. Results: BayesAge demonstrates superior performance compared to scAge. Notably, its age residuals exhibit no age association, offering a less biased representation of epigenetic age variation across populations. Furthermore, BayesAge facilitates the estimation of error bounds on age inference. When applied to down-sampled data, BayesAge achieves a higher coefficient of determination between predicted and actual ages compared to both scAge and penalized regression. Discussion: BayesAge presents a promising advancement in epigenetic age prediction, addressing key challenges encountered by existing models. By integrating robust statistical techniques and tailored methodologies for count-based data, BayesAge offers improved accuracy and interpretability in predicting age from bulk bisulfite sequencing datasets. Its ability to estimate error bounds enhances the reliability of age inference, thereby contributing to a more comprehensive understanding of epigenetic aging processes.
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Affiliation(s)
- Lajoyce Mboning
- Department of Chemistry and Biochemistry, University of California Los Angeles, Los Angeles, CA, United States
| | - Liudmilla Rubbi
- Department of Molecular, Cell and Developmental Biology, University of Los Angeles, Los Angeles, CA, United States
| | - Michael Thompson
- Department of Molecular, Cell and Developmental Biology, University of Los Angeles, Los Angeles, CA, United States
| | - Louis-S. Bouchard
- Department of Chemistry and Biochemistry, University of California Los Angeles, Los Angeles, CA, United States
| | - Matteo Pellegrini
- Department of Molecular, Cell and Developmental Biology, University of Los Angeles, Los Angeles, CA, United States
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13
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Sanders KL, Manuel AM, Liu A, Leng B, Chen X, Zhao Z. Unveiling Gene Interactions in Alzheimer's Disease by Integrating Genetic and Epigenetic Data with a Network-Based Approach. EPIGENOMES 2024; 8:14. [PMID: 38651367 PMCID: PMC11036294 DOI: 10.3390/epigenomes8020014] [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: 03/05/2024] [Revised: 03/26/2024] [Accepted: 03/28/2024] [Indexed: 04/25/2024] Open
Abstract
Alzheimer's Disease (AD) is a complex disease and the leading cause of dementia in older people. We aimed to uncover aspects of AD's pathogenesis that may contribute to drug repurposing efforts by integrating DNA methylation and genetic data. Implementing the network-based tool, a dense module search of genome-wide association studies (dmGWAS), we integrated a large-scale GWAS dataset with DNA methylation data to identify gene network modules associated with AD. Our analysis yielded 286 significant gene network modules. Notably, the foremost module included the BIN1 gene, showing the largest GWAS signal, and the GNAS gene, the most significantly hypermethylated. We conducted Web-based Cell-type-Specific Enrichment Analysis (WebCSEA) on genes within the top 10% of dmGWAS modules, highlighting monocyte as the most significant cell type (p < 5 × 10-12). Functional enrichment analysis revealed Gene Ontology Biological Process terms relevant to AD pathology (adjusted p < 0.05). Additionally, drug target enrichment identified five FDA-approved targets (p-value = 0.03) for further research. In summary, dmGWAS integration of genetic and epigenetic signals unveiled new gene interactions related to AD, offering promising avenues for future studies.
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Affiliation(s)
- Keith L. Sanders
- Center for Precision Health, McWilliams School of Biomedical Informatics, Houston, TX 77030, USA; (K.L.S.); (A.M.M.); (A.L.); (X.C.)
| | - Astrid M. Manuel
- Center for Precision Health, McWilliams School of Biomedical Informatics, Houston, TX 77030, USA; (K.L.S.); (A.M.M.); (A.L.); (X.C.)
| | - Andi Liu
- Center for Precision Health, McWilliams School of Biomedical Informatics, Houston, TX 77030, USA; (K.L.S.); (A.M.M.); (A.L.); (X.C.)
- Department of Epidemiology, Human Genetics and Environmental Sciences, School of Public Health, Houston, TX 77030, USA
| | - Boyan Leng
- Center for Precision Health, McWilliams School of Biomedical Informatics, Houston, TX 77030, USA; (K.L.S.); (A.M.M.); (A.L.); (X.C.)
| | - Xiangning Chen
- Center for Precision Health, McWilliams School of Biomedical Informatics, Houston, TX 77030, USA; (K.L.S.); (A.M.M.); (A.L.); (X.C.)
| | - Zhongming Zhao
- Center for Precision Health, McWilliams School of Biomedical Informatics, Houston, TX 77030, USA; (K.L.S.); (A.M.M.); (A.L.); (X.C.)
- Department of Epidemiology, Human Genetics and Environmental Sciences, School of Public Health, Houston, TX 77030, USA
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14
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Yücel AD, Gladyshev VN. The long and winding road of reprogramming-induced rejuvenation. Nat Commun 2024; 15:1941. [PMID: 38431638 PMCID: PMC10908844 DOI: 10.1038/s41467-024-46020-5] [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: 07/22/2023] [Accepted: 02/12/2024] [Indexed: 03/05/2024] Open
Abstract
Organismal aging is inherently connected to the aging of its constituent cells and systems. Reducing the biological age of the organism may be assisted by reducing the age of its cells - an approach exemplified by partial cell reprogramming through the expression of Yamanaka factors or exposure to chemical cocktails. It is crucial to protect cell type identity during partial reprogramming, as cells need to retain or rapidly regain their functions following the treatment. Another critical issue is the ability to quantify biological age as reprogrammed older cells acquire younger states. We discuss recent advances in reprogramming-induced rejuvenation and offer a critical review of this procedure and its relationship to the fundamental nature of aging. We further comparatively analyze partial reprogramming, full reprogramming and transdifferentiation approaches, assess safety concerns and emphasize the importance of distinguishing rejuvenation from dedifferentiation. Finally, we highlight translational opportunities that the reprogramming-induced rejuvenation approach offers.
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Affiliation(s)
- Ali Doğa Yücel
- Department of Molecular Biology and Genetics, Koc University, Istanbul, 34450, Turkey
- Brigham and Women's Hospital, Harvard Medical School, Boston, MA, 02115, USA
| | - Vadim N Gladyshev
- Brigham and Women's Hospital, Harvard Medical School, Boston, MA, 02115, USA.
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15
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Kapadia CD, Goodell MA. Tissue mosaicism following stem cell aging: blood as an exemplar. NATURE AGING 2024; 4:295-308. [PMID: 38438628 DOI: 10.1038/s43587-024-00589-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/23/2023] [Accepted: 02/07/2024] [Indexed: 03/06/2024]
Abstract
Loss of stem cell regenerative potential underlies aging of all tissues. Somatic mosaicism, the emergence of cellular patchworks within tissues, increases with age and has been observed in every organ yet examined. In the hematopoietic system, as in most tissues, stem cell aging through a variety of mechanisms occurs in lockstep with the emergence of somatic mosaicism. Here, we draw on insights from aging hematopoiesis to illustrate fundamental principles of stem cell aging and somatic mosaicism. We describe the generalizable changes intrinsic to aged stem cells and their milieu that provide the backdrop for somatic mosaicism to emerge. We discuss genetic and nongenetic mechanisms that can result in tissue somatic mosaicism and existing methodologies to detect such clonal outgrowths. Finally, we propose potential avenues to modify mosaicism during aging, with the ultimate aim of increasing tissue resiliency.
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Affiliation(s)
- Chiraag D Kapadia
- Department of Molecular and Cellular Biology, Baylor College of Medicine, Houston, TX, USA
- Center for Cell and Gene Therapy, Baylor College of Medicine, Houston, TX, USA
| | - Margaret A Goodell
- Department of Molecular and Cellular Biology, Baylor College of Medicine, Houston, TX, USA.
- Center for Cell and Gene Therapy, Baylor College of Medicine, Houston, TX, USA.
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16
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Pereira B, Correia FP, Alves IA, Costa M, Gameiro M, Martins AP, Saraiva JA. Epigenetic reprogramming as a key to reverse ageing and increase longevity. Ageing Res Rev 2024; 95:102204. [PMID: 38272265 DOI: 10.1016/j.arr.2024.102204] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2023] [Revised: 12/18/2023] [Accepted: 01/19/2024] [Indexed: 01/27/2024]
Abstract
The pursuit for the fountain of youth has long been a fascination amongst scientists and humanity. Ageing is broadly characterized by a cellular decline with increased susceptibility to age-related diseases, being intimately associated with epigenetic modifications. Recently, reprogramming-induced rejuvenation strategies have begun to greatly alter longevity research not only to tackle age-related defects but also to possibly reverse the cellular ageing process. Hence, in this review, we highlight the major epigenetic changes during ageing and the state-of-art of the current emerging epigenetic reprogramming strategies leveraging on transcription factors. Notably, partial reprogramming enables the resetting of the ageing clock without erasing cellular identity. Promising chemical-based rejuvenation strategies harnessing small molecules, including DNA methyltransferase and histone deacetylase inhibitors are also discussed. Moreover, in parallel to longevity interventions, the foundations of epigenetic clocks for accurate ageing assessment and evaluation of reprogramming approaches are briefly presented. Going further, with such scientific breakthroughs, we are witnessing a rise in the longevity biotech industry aiming to extend the health span and ideally achieve human rejuvenation one day. In this context, we overview the main scenarios proposed for the future of the socio-economic and ethical challenges associated with such an emerging field. Ultimately, this review aims to inspire future research on interventions that promote healthy ageing for all.
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Affiliation(s)
- Beatriz Pereira
- Department of Chemistry, University of Aveiro, Aveiro, Portugal
| | | | - Inês A Alves
- Department of Chemistry, University of Aveiro, Aveiro, Portugal
| | - Margarida Costa
- Department of Chemistry, University of Aveiro, Aveiro, Portugal
| | - Mariana Gameiro
- Department of Chemistry, University of Aveiro, Aveiro, Portugal
| | - Ana P Martins
- LAQV-REQUIMTE, Department of Chemistry, University of Aveiro, Aveiro, Portugal
| | - Jorge A Saraiva
- LAQV-REQUIMTE, Department of Chemistry, University of Aveiro, Aveiro, Portugal.
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17
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Yang JH, Hayano M, Rajman LA, Sinclair DA. Response to: The information theory of aging has not been tested. Cell 2024; 187:1103-1105. [PMID: 38428391 DOI: 10.1016/j.cell.2024.01.014] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2023] [Revised: 12/12/2023] [Accepted: 01/10/2024] [Indexed: 03/03/2024]
Affiliation(s)
- Jae-Hyun Yang
- Paul F. Glenn Center for Biology of Aging Research, Department of Genetics, Blavatnik Institute, Harvard Medical School (HMS), Boston, MA, USA
| | - Motoshi Hayano
- Department of Neuropsychiatry, Keio University School of Medicine, Tokyo, Japan
| | - Luis A Rajman
- Paul F. Glenn Center for Biology of Aging Research, Department of Genetics, Blavatnik Institute, Harvard Medical School (HMS), Boston, MA, USA
| | - David A Sinclair
- Paul F. Glenn Center for Biology of Aging Research, Department of Genetics, Blavatnik Institute, Harvard Medical School (HMS), Boston, MA, USA.
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18
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Lee E, Carreras-Gallo N, Lopez L, Turner L, Lin A, Mendez TL, Went H, Tomusiak A, Verdin E, Corley M, Ndhlovu L, Smith R, Dwaraka VB. Exploring the effects of Dasatinib, Quercetin, and Fisetin on DNA methylation clocks: a longitudinal study on senolytic interventions. Aging (Albany NY) 2024; 16:3088-3106. [PMID: 38393697 DOI: 10.18632/aging.205581] [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: 08/03/2023] [Accepted: 01/19/2024] [Indexed: 02/25/2024]
Abstract
Senolytics, small molecules targeting cellular senescence, have emerged as potential therapeutics to enhance health span. However, their impact on epigenetic age remains unstudied. This study aimed to assess the effects of Dasatinib and Quercetin (DQ) senolytic treatment on DNA methylation (DNAm), epigenetic age, and immune cell subsets. In a Phase I pilot study, 19 participants received DQ for 6 months, with DNAm measured at baseline, 3 months, and 6 months. Significant increases in epigenetic age acceleration were observed in first-generation epigenetic clocks and mitotic clocks at 3 and 6 months, along with a notable decrease in telomere length. However, no significant differences were observed in second and third-generation clocks. Building upon these findings, a subsequent investigation evaluated the combination of DQ with Fisetin (DQF), a well-known antioxidant and antiaging senolytic molecule. After one year, 19 participants (including 10 from the initial study) received DQF for 6 months, with DNAm assessed at baseline and 6 months. Remarkably, the addition of Fisetin to the treatment resulted in non-significant increases in epigenetic age acceleration, suggesting a potential mitigating effect of Fisetin on the impact of DQ on epigenetic aging. Furthermore, our analyses unveiled notable differences in immune cell proportions between the DQ and DQF treatment groups, providing a biological basis for the divergent patterns observed in the evolution of epigenetic clocks. These findings warrant further research to validate and comprehensively understand the implications of these combined interventions.
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Affiliation(s)
- Edwin Lee
- Institute For Hormonal Balance, Orlando, FL 32819, USA
| | | | | | | | - Aaron Lin
- TruDiagnostic, Lexington, KY 40503, USA
| | | | | | - Alan Tomusiak
- Buck Institute for Research on Aging, Novato, CA 94945, USA
| | - Eric Verdin
- Buck Institute for Research on Aging, Novato, CA 94945, USA
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19
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Kelly C, Junker A, Englestad K, Hirano M, Trumpff C, Picard M. Perceived association of mood and symptom severity in adults with mitochondrial diseases. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.02.02.24302076. [PMID: 38352338 PMCID: PMC10862998 DOI: 10.1101/2024.02.02.24302076] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/17/2024]
Abstract
Individuals with genetic mitochondrial diseases suffer from multisystemic symptoms that vary in severity from day-to-day and week-to-week, but the underlying causes of symptomatic fluctuations are not understood. Based upon observations that: i) patients and their families frequently report that stressful life events either trigger exacerbations of existing symptoms or the onset of new symptoms, ii) psychological states and stress hormones influence mitochondrial energy production capacity, and iii) epidemiological reports document a robust connection between traumatic/stressful life events and various neurologic disorders, we hypothesized that mitochondrial disease symptom severity may vary according to participant's mood. To investigate this we administered the Stress, Health and Emotion Survey (SHES) in 70 adults (majority white (84%) cisgender women (83%), ages 18-74) with self-reported mitochondrial diseases (MELAS, 18%; CPEO, 17%; Complex I deficiency, 13%). Participants rated the severity of each of their symptom(s) over the past year on either good or bad days. On days marked by more stress, sadness and other negative emotions, some but not all symptoms were reported to be worse, including fatigue, exercise intolerance, brain fog, and fine motor coordination. By contrast, on days marked by happiness and calmness, participants reported these and other symptoms to be better, or less severe. Other symptoms including diminished sweating, hearing problems, and dystonia were in general unrelated to mood. Thus, some individuals living with mitochondrial diseases, at times perceive a connection between their mood and symptom severity. These preliminary associative results constitute an initial step towards developing more comprehensive models of the factors that influence the clinical course of mitochondrial diseases.
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Affiliation(s)
- Catherine Kelly
- Department of Psychiatry, Division of Behavioral Medicine, Columbia University Irving Medical Center, New York, NY 10032, USA
| | - Alex Junker
- Department of Psychiatry, Division of Behavioral Medicine, Columbia University Irving Medical Center, New York, NY 10032, USA
| | - Kris Englestad
- Department of Neurology, H. Houston Merritt Center, Columbia University Irving Medical Center, New York, New York 10032, USA
| | - Michio Hirano
- Department of Neurology, H. Houston Merritt Center, Columbia University Irving Medical Center, New York, New York 10032, USA
| | - Caroline Trumpff
- Department of Psychiatry, Division of Behavioral Medicine, Columbia University Irving Medical Center, New York, NY 10032, USA
| | - Martin Picard
- Department of Psychiatry, Division of Behavioral Medicine, Columbia University Irving Medical Center, New York, NY 10032, USA
- Department of Neurology, H. Houston Merritt Center, Columbia University Irving Medical Center, New York, New York 10032, USA
- New York State Psychiatric Institute, New York, NY 10032, USA
- Robert N Butler Columbia Aging Center, Mailman School of Public Health, New York, NY 10032, USA
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20
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Macip CC, Hasan R, Hoznek V, Kim J, Lu YR, Metzger LE, Sethna S, Davidsohn N. Gene Therapy-Mediated Partial Reprogramming Extends Lifespan and Reverses Age-Related Changes in Aged Mice. Cell Reprogram 2024; 26:24-32. [PMID: 38381405 PMCID: PMC10909732 DOI: 10.1089/cell.2023.0072] [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] [Indexed: 02/22/2024] Open
Abstract
Aging is a complex progression of changes best characterized as the chronic dysregulation of cellular processes leading to deteriorated tissue and organ function. Although aging cannot currently be prevented, its impact on life- and healthspan in the elderly can potentially be minimized by interventions that aim to return these cellular processes to optimal function. Recent studies have demonstrated that partial reprogramming using the Yamanaka factors (or a subset; OCT4, SOX2, and KLF4; OSK) can reverse age-related changes in vitro and in vivo. However, it is still unknown whether the Yamanaka factors (or a subset) are capable of extending the lifespan of aged wild-type (WT) mice. In this study, we show that systemically delivered adeno-associated viruses, encoding an inducible OSK system, in 124-week-old male mice extend the median remaining lifespan by 109% over WT controls and enhance several health parameters. Importantly, we observed a significant improvement in frailty scores indicating that we were able to improve the healthspan along with increasing the lifespan. Furthermore, in human keratinocytes expressing exogenous OSK, we observed significant epigenetic markers of age reversal, suggesting a potential reregulation of genetic networks to a younger potentially healthier state. Together, these results may have important implications for the development of partial reprogramming interventions to reverse age-associated diseases in the elderly.
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Affiliation(s)
| | | | | | - Jihyun Kim
- Rejuvenate Bio, San Diego, California, USA
| | - Yuancheng Ryan Lu
- Department of Biology, Whitehead Institute for Biomedical Research, Cambridge, Massachusetts, USA
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21
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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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22
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Prosz A, Pipek O, Börcsök J, Palla G, Szallasi Z, Spisak S, Csabai I. Biologically informed deep learning for explainable epigenetic clocks. Sci Rep 2024; 14:1306. [PMID: 38225268 PMCID: PMC10789766 DOI: 10.1038/s41598-023-50495-5] [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: 01/17/2023] [Accepted: 12/20/2023] [Indexed: 01/17/2024] Open
Abstract
Ageing is often characterised by progressive accumulation of damage, and it is one of the most important risk factors for chronic disease development. Epigenetic mechanisms including DNA methylation could functionally contribute to organismal aging, however the key functions and biological processes may govern ageing are still not understood. Although age predictors called epigenetic clocks can accurately estimate the biological age of an individual based on cellular DNA methylation, their models have limited ability to explain the prediction algorithm behind and underlying key biological processes controlling ageing. Here we present XAI-AGE, a biologically informed, explainable deep neural network model for accurate biological age prediction across multiple tissue types. We show that XAI-AGE outperforms the first-generation age predictors and achieves similar results to deep learning-based models, while opening up the possibility to infer biologically meaningful insights of the activity of pathways and other abstract biological processes directly from the model.
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Affiliation(s)
- Aurel Prosz
- Danish Cancer Institute, Copenhagen, Denmark
| | - Orsolya Pipek
- Department of Physics of Complex Systems, ELTE Eötvös Loránd University, Budapest, Hungary
| | - Judit Börcsök
- Danish Cancer Institute, Copenhagen, Denmark
- Biotech Research & Innovation Centre (BRIC), University of Copenhagen, Copenhagen, Denmark
| | - Gergely Palla
- Department of Biological Physics, ELTE Eötvös Loránd University, Budapest, Hungary
- Health Services Management Training Centre, Semmelweis University, Budapest, Hungary
| | | | - Sandor Spisak
- Institute of Enzymology, HUN-REN Research Centre for Natural Sciences, Budapest, Hungary.
| | - István Csabai
- Department of Physics of Complex Systems, ELTE Eötvös Loránd University, Budapest, Hungary
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23
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Ndhlovu LC, Bendall ML, Dwaraka V, Pang APS, Dopkins N, Carreras N, Smith R, Nixon DF, Corley MJ. Retroelement-Age Clocks: Epigenetic Age Captured by Human Endogenous Retrovirus and LINE-1 DNA methylation states. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.12.06.570422. [PMID: 38106164 PMCID: PMC10723416 DOI: 10.1101/2023.12.06.570422] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/19/2023]
Abstract
Human endogenous retroviruses (HERVs), the remnants of ancient viral infections embedded within the human genome, and long interspersed nuclear elements 1 (LINE-1), a class of autonomous retrotransposons, are silenced by host epigenetic mechanisms including DNA methylation. The resurrection of particular retroelements has been linked to biological aging. Whether the DNA methylation states of locus specific HERVs and LINEs can be used as a biomarker of chronological age in humans remains unclear. We show that highly predictive epigenetic clocks of chronological age can be constructed from retroelement DNA methylation states in the immune system, across human tissues, and pan-mammalian species. We found retroelement epigenetic clocks were reversed during transient epigenetic reprogramming, accelerated in people living with HIV-1, responsive to antiretroviral therapy, and accurate in estimating long-term culture ages of human brain organoids. Our findings support the hypothesis of epigenetic dysregulation of retroelements as a potential contributor to the biological hallmarks of aging.
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Affiliation(s)
- Lishomwa C. Ndhlovu
- Department of Medicine, Division of Infectious Diseases, Weill Cornell Medicine, New York City, New York, USA
| | - Matthew L. Bendall
- Department of Medicine, Division of Infectious Diseases, Weill Cornell Medicine, New York City, New York, USA
| | | | - Alina PS Pang
- Department of Medicine, Division of Infectious Diseases, Weill Cornell Medicine, New York City, New York, USA
| | - Nicholas Dopkins
- Department of Medicine, Division of Infectious Diseases, Weill Cornell Medicine, New York City, New York, USA
| | | | | | - Douglas F. Nixon
- Department of Medicine, Division of Infectious Diseases, Weill Cornell Medicine, New York City, New York, USA
| | - Michael J. Corley
- Department of Medicine, Division of Infectious Diseases, Weill Cornell Medicine, New York City, New York, USA
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24
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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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25
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Felt JM, Yusupov N, Harrington KD, Fietz J, Zhang Z“Z, Sliwinski MJ, Ram N, O'Donnell KJ, Meaney MJ, Putnam FW, Noll JG, Binder EB, Shenk CE. Epigenetic age acceleration as a biomarker for impaired cognitive abilities in adulthood following early life adversity and psychiatric disorders. Neurobiol Stress 2023; 27:100577. [PMID: 37885906 PMCID: PMC10597797 DOI: 10.1016/j.ynstr.2023.100577] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2023] [Revised: 09/20/2023] [Accepted: 09/23/2023] [Indexed: 10/28/2023] Open
Abstract
Background Early life adversity and psychiatric disorders are associated with earlier declines in neurocognitive abilities during adulthood. These declines may be preceded by changes in biological aging, specifically epigenetic age acceleration, providing an opportunity to uncover genome-wide biomarkers that identify individuals most likely to benefit from early screening and prevention. Methods Five unique epigenetic age acceleration clocks derived from peripheral blood were examined in relation to latent variables of general and speeded cognitive abilities across two independent cohorts: 1) the Female Growth and Development Study (FGDS; n = 86), a 30-year prospective cohort study of substantiated child sexual abuse and non-abused controls, and 2) the Biological Classification of Mental Disorders study (BeCOME; n = 313), an adult community cohort established based on psychiatric disorders. Results A faster pace of biological aging (DunedinPoAm) was associated with lower general cognitive abilities in both cohorts and slower speeded abilities in the BeCOME cohort. Acceleration in the Horvath clock was significantly associated with slower speeded abilities in the BeCOME cohort but not the FGDS. Acceleration in the Hannum clock and the GrimAge clock were not significantly associated with either cognitive ability. Accelerated PhenoAge was associated with slower speeded abilities in the FGDS but not the BeCOME cohort. Conclusions The present results suggest that epigenetic age acceleration has the potential to serve as a biomarker for neurocognitive decline in adults with a history of early life adversity or psychiatric disorders. Estimates of epigenetic aging may identify adults at risk of cognitive decline that could benefit from early neurocognitive screening.
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Affiliation(s)
- John M. Felt
- Center for Healthy Aging, The Pennsylvania State University, United States
| | - Natan Yusupov
- Department Genes and Environment, Max Planck Institute of Psychiatry - Munich, Germany
- International Max Planck Research School for Translational Psychiatry, Max Planck Institute of Psychiatry, Germany
| | | | - Julia Fietz
- Department Genes and Environment, Max Planck Institute of Psychiatry - Munich, Germany
- International Max Planck Research School for Translational Psychiatry, Max Planck Institute of Psychiatry, Germany
| | | | - Martin J. Sliwinski
- Center for Healthy Aging, The Pennsylvania State University, United States
- Department of Human Development and Family Studies, The Pennsylvania State University, United States
| | - Nilam Ram
- Department of Communications, Stanford University, United States
- Department of Psychology, Stanford University, United States
| | - Kieran J. O'Donnell
- Child Study Center, Yale University, United States
- Department of Obstetrics, Gynecology, and Reproductive Sciences, Yale University, United States
- The Douglas Hospital Research Centre, Department of Psychiatry, McGill University, Canada
- Child and Brain Development Program, Canadian Institute for Advanced Research, Canada
| | - BeCOME Working Group
- Department Genes and Environment, Max Planck Institute of Psychiatry - Munich, Germany
- Max Planck Institute of Psychiatry, Munich, Germany
| | - Michael J. Meaney
- The Douglas Hospital Research Centre, Department of Psychiatry, McGill University, Canada
- Child and Brain Development Program, Canadian Institute for Advanced Research, Canada
- Singapore Institute of Clinical Sciences, Singapore
| | - Frank W. Putnam
- Department of Psychiatry, University of North Carolina School of Medicine, United States
| | - Jennie G. Noll
- Department of Human Development and Family Studies, The Pennsylvania State University, United States
| | - Elisabeth B. Binder
- Department Genes and Environment, Max Planck Institute of Psychiatry - Munich, Germany
- Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, United States
| | - Chad E. Shenk
- Department of Human Development and Family Studies, The Pennsylvania State University, United States
- Department of Pediatrics, The Pennsylvania State University College of Medicine, United States
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26
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Bejaoui Y, Oshima J, Hajj NE. Insights into aging from progeroid syndrome epigenetics. Aging (Albany NY) 2023; 15:7336-7337. [PMID: 37552095 PMCID: PMC10457063 DOI: 10.18632/aging.204977] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2023] [Accepted: 05/08/2023] [Indexed: 08/09/2023]
Affiliation(s)
- Yosra Bejaoui
- College of Health and Life Sciences, Hamad Bin Khalifa University, Qatar Foundation, Qatar
| | - Junko Oshima
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, WA 98105, USA
- Department of Clinical Cell Biology and Medicine, Graduate School of Medicine, Chiba University, Chiba, Japan
| | - Nady El Hajj
- College of Health and Life Sciences, Hamad Bin Khalifa University, Qatar Foundation, Qatar
- College of Science and Engineering, Hamad Bin Khalifa University, Qatar Foundation, Doha, Qatar
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27
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Yang JH, Petty CA, Dixon-McDougall T, Lopez MV, Tyshkovskiy A, Maybury-Lewis S, Tian X, Ibrahim N, Chen Z, Griffin PT, Arnold M, Li J, Martinez OA, Behn A, Rogers-Hammond R, Angeli S, Gladyshev VN, Sinclair DA. Chemically induced reprogramming to reverse cellular aging. Aging (Albany NY) 2023; 15:5966-5989. [PMID: 37437248 PMCID: PMC10373966 DOI: 10.18632/aging.204896] [Citation(s) in RCA: 16] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2023] [Accepted: 07/04/2023] [Indexed: 07/14/2023]
Abstract
A hallmark of eukaryotic aging is a loss of epigenetic information, a process that can be reversed. We have previously shown that the ectopic induction of the Yamanaka factors OCT4, SOX2, and KLF4 (OSK) in mammals can restore youthful DNA methylation patterns, transcript profiles, and tissue function, without erasing cellular identity, a process that requires active DNA demethylation. To screen for molecules that reverse cellular aging and rejuvenate human cells without altering the genome, we developed high-throughput cell-based assays that distinguish young from old and senescent cells, including transcription-based aging clocks and a real-time nucleocytoplasmic compartmentalization (NCC) assay. We identify six chemical cocktails, which, in less than a week and without compromising cellular identity, restore a youthful genome-wide transcript profile and reverse transcriptomic age. Thus, rejuvenation by age reversal can be achieved, not only by genetic, but also chemical means.
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Affiliation(s)
- Jae-Hyun Yang
- Paul F. Glenn Center for Biology of Aging Research, Department of Genetics, Blavatnik Institute, Harvard Medical School (HMS), Boston, MA 02115, USA
| | - Christopher A. Petty
- Paul F. Glenn Center for Biology of Aging Research, Department of Genetics, Blavatnik Institute, Harvard Medical School (HMS), Boston, MA 02115, USA
| | - Thomas Dixon-McDougall
- Paul F. Glenn Center for Biology of Aging Research, Department of Genetics, Blavatnik Institute, Harvard Medical School (HMS), Boston, MA 02115, USA
| | - Maria Vina Lopez
- Molecular and Biomedical Sciences, University of Maine, Orono, ME 04467, USA
| | - 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
| | - Sun Maybury-Lewis
- Paul F. Glenn Center for Biology of Aging Research, Department of Genetics, Blavatnik Institute, Harvard Medical School (HMS), Boston, MA 02115, USA
| | - Xiao Tian
- Paul F. Glenn Center for Biology of Aging Research, Department of Genetics, Blavatnik Institute, Harvard Medical School (HMS), Boston, MA 02115, USA
| | - Nabilah Ibrahim
- Paul F. Glenn Center for Biology of Aging Research, Department of Genetics, Blavatnik Institute, Harvard Medical School (HMS), Boston, MA 02115, USA
| | - Zhili Chen
- Paul F. Glenn Center for Biology of Aging Research, Department of Genetics, Blavatnik Institute, Harvard Medical School (HMS), Boston, MA 02115, USA
| | - Patrick T. Griffin
- Paul F. Glenn Center for Biology of Aging Research, Department of Genetics, Blavatnik Institute, Harvard Medical School (HMS), Boston, MA 02115, USA
| | - Matthew Arnold
- Paul F. Glenn Center for Biology of Aging Research, Department of Genetics, Blavatnik Institute, Harvard Medical School (HMS), Boston, MA 02115, USA
| | - Jien Li
- Paul F. Glenn Center for Biology of Aging Research, Department of Genetics, Blavatnik Institute, Harvard Medical School (HMS), Boston, MA 02115, USA
| | - Oswaldo A. Martinez
- Paul F. Glenn Center for Biology of Aging Research, Department of Genetics, Blavatnik Institute, Harvard Medical School (HMS), Boston, MA 02115, USA
- Department of Biology and Chemistry, Massachusetts Institute of Technology, Cambridge, MA 02142, USA
| | - Alexander Behn
- Paul F. Glenn Center for Biology of Aging Research, Department of Genetics, Blavatnik Institute, Harvard Medical School (HMS), Boston, MA 02115, USA
| | - Ryan Rogers-Hammond
- Paul F. Glenn Center for Biology of Aging Research, Department of Genetics, Blavatnik Institute, Harvard Medical School (HMS), Boston, MA 02115, USA
| | - Suzanne Angeli
- Molecular and Biomedical Sciences, University of Maine, Orono, ME 04467, USA
| | - Vadim N. Gladyshev
- Division of Genetics, Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA 02115, USA
| | - David A. Sinclair
- Paul F. Glenn Center for Biology of Aging Research, Department of Genetics, Blavatnik Institute, Harvard Medical School (HMS), Boston, MA 02115, USA
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28
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Peng G, Sosnowski DW, Murphy SK, Johnson SB, Skaar D, Schleif WS, Hernandez RG, Monforte H, Zhao H, Hoyo C. An epigenetic clock for gestational age based on human umbilical vein endothelial cells from a diverse population of newborns. RESEARCH SQUARE 2023:rs.3.rs-3112428. [PMID: 37461438 PMCID: PMC10350106 DOI: 10.21203/rs.3.rs-3112428/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/28/2023]
Abstract
Background Epigenetic clocks are emerging as a useful tool in many areas of research. Many epigenetic clocks have been developed for adults; however, there are fewer clocks focused on newborns and most are trained using blood from European ancestry populations. In this study, we built an epigenetic clock based on primary human umbilical vein endothelial cells from a racially and ethnically diverse population. Results Using human umbilical vein endothelial cell [HUVEC]-derived DNA, we calculated epigenetic gestational age using 83 CpG sites selected through elastic net regression. In this study with newborns from different racial/ethnic identities, epigenetic gestational age and clinical gestational age were more highly correlated (r = 0.85), than epigenetic clocks built from adult and other pediatric populations. The correlation was also higher than clocks based on blood samples from newborns with European ancestry. We also found that birth weight was positively associated with epigenetic gestational age acceleration (EGAA), while NICU admission was associated with lower EGAA. Newborns self-identified as Hispanic or non-Hispanic Black had lower EGAA than self-identified as non-Hispanic White. Conclusions Epigenetic gestational age can be used to estimate clinical gestational age and may help index neonatal development. Caution should be exercised when using epigenetic clocks built from adults with children, especially newborns. We highlight the importance of cell type-specific epigenetic clocks and general pan tissue epigenetic clocks derived from a large racially and ethnically diverse population.
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Affiliation(s)
- Gang Peng
- Indiana University School of Medicine
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Quinn EB, Hsiao CJ, Maisha FM, Mulligan CJ. Low birthweight is associated with epigenetic age acceleration in the first 3 years of life. Evol Med Public Health 2023; 11:251-261. [PMID: 37485054 PMCID: PMC10360162 DOI: 10.1093/emph/eoad019] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2023] [Revised: 05/08/2023] [Indexed: 07/25/2023] Open
Abstract
Background and objectives The Developmental Origins of Health and Disease hypothesis posits that early life adversity is associated with poor adult health outcomes. Epidemiological evidence has supported this framework by linking low birthweight with adult health and mortality, but the mechanisms remain unclear. Accelerated epigenetic aging may be a pathway to connect early life experiences with adult health outcomes, based on associations of accelerated epigenetic aging with increased morbidity and mortality. Methodology Sixty-seven mother-infant dyads were recruited in the eastern Democratic Republic of Congo. Birthweight data were collected at birth, and blood samples were collected at birth and follow-up visits up to age 3. DNA methylation data were generated with the Illumina MethylationEPIC array and used to estimate epigenetic age. A multilevel model was used to test for associations between birthweight and epigenetic age acceleration. Results Chronological age was highly correlated with epigenetic age from birth to age 3 (r = 0.95, p < 2.2 × 10-16). Variation in epigenetic age acceleration increased over time. Birthweight, dichotomized around 2500 g, predicted epigenetic age acceleration over the first 3 years of life (b = -0.39, p = 0.005). Conclusions and implications Our longitudinal analysis provides the first evidence for accelerated epigenetic aging that emerges between birth and age 3 and associates with low birthweight. These results suggest that early life experiences, such as low birthweight, may shape the trajectory of epigenetic aging in early childhood. Furthermore, accelerated epigenetic aging may be a pathway that links low birthweight and poor adult health outcomes.
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Affiliation(s)
- Edward B Quinn
- Department of Anthropology, University of Florida, Gainesville, FL 32608, USA
- Genetics Institute, University of Florida, Gainesville, FL 32608, USA
| | - Chu J Hsiao
- Department of Anthropology, University of Florida, Gainesville, FL 32608, USA
- Genetics Institute, University of Florida, Gainesville, FL 32608, USA
- College of Medicine, University of Florida, Gainesville, FL 32608, USA
| | - Felicien M Maisha
- Department of Anthropology, University of Florida, Gainesville, FL 32608, USA
- Genetics Institute, University of Florida, Gainesville, FL 32608, USA
- HEAL Africa Hospital, Goma, Democratic Republic of Congo
- Maisha Institute, Goma, Democratic Republic of Congo
| | - Connie J Mulligan
- Corresponding author. Department of Anthropology, University of Florida, 2033 Mowry Road, PO Box 103610, Gainesville, FL 32610-3610, USA. Tel: 352-273-8092; E-mail:
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30
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Ogrodnik M, Gladyshev VN. The meaning of adaptation in aging: insights from cellular senescence, epigenetic clocks and stem cell alterations. NATURE AGING 2023:10.1038/s43587-023-00447-5. [PMID: 37386259 DOI: 10.1038/s43587-023-00447-5] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/28/2022] [Accepted: 05/30/2023] [Indexed: 07/01/2023]
Abstract
With recent rapid progress in research on aging, there is increasing evidence that many features commonly considered to be mechanisms or drivers of aging in fact represent adaptations. Here, we examine several such features, including cellular senescence, epigenetic aging and stem cell alterations. We draw a distinction between the causes and consequences of aging and define short-term consequences as 'responses' and long-term ones as 'adaptations'. We also discuss 'damaging adaptations', which despite having beneficial effects in the short term, lead to exacerbation of the initial insult and acceleration of aging. Features commonly recognized as 'basic mechanisms of the aging process' are critically examined for the possibility of their adaptation-driven emergence from processes such as cell competition and the wound-like features of the aging body. Finally, we speculate on the meaning of these interactions for the aging process and their relevance for the development of antiaging interventions.
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Affiliation(s)
- Mikolaj Ogrodnik
- Ludwig Boltzmann Research Group Senescence and Healing of Wounds, Vienna, Austria.
- Ludwig Boltzmann Institute for Experimental and Clinical Traumatology, Austrian Workers' Compensation Board Research Center, Vienna, Austria.
- Austrian Cluster for Tissue Regeneration, Vienna, Austria.
| | - Vadim N Gladyshev
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA.
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Schoepf IC, Esteban-Cantos A, Thorball CW, Rodés B, Reiss P, Rodríguez-Centeno J, Riebensahm C, Braun DL, Marzolini C, Seneghini M, Bernasconi E, Cavassini M, Buvelot H, Thurnheer MC, Kouyos RD, Fellay J, Günthard HF, Arribas JR, Ledergerber B, Tarr PE. Epigenetic ageing accelerates before antiretroviral therapy and decelerates after viral suppression in people with HIV in Switzerland: a longitudinal study over 17 years. THE LANCET. HEALTHY LONGEVITY 2023; 4:e211-e218. [PMID: 37148893 DOI: 10.1016/s2666-7568(23)00037-5] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2023] [Revised: 03/09/2023] [Accepted: 03/10/2023] [Indexed: 05/08/2023] Open
Abstract
BACKGROUND Accelerated epigenetic ageing can occur in untreated HIV infection and is partially reversible with effective antiretroviral therapy (ART). We aimed to make a long-term comparison of epigenetic ageing dynamics in people with HIV during untreated HIV infection and during suppressive ART. METHODS In this longitudinal study, conducted over 17 years in HIV outpatient clinics in Switzerland, we applied 5 established epigenetic age estimators (epigenetic clocks) in peripheral blood mononuclear cells (PBMCs) in Swiss HIV Cohort Study participants before or during suppressive ART. All participants had a longitudinal set of PBMC samples available at four timepoints (T1-T4). T1 and T2 had to be 3 years or longer apart, as did T3 and T4. We assessed epigenetic age acceleration (EAA) and a novel rate of epigenetic ageing. FINDINGS Between March 13, 1990, and Jan 18, 2018, we recruited 81 people with HIV from the Swiss HIV Cohort Study. We excluded one participant because a sample did not meet quality checks (transmission error). 52 (65%) of 80 patients were men, 76 (95%) were white, and the median patient age was 43 (IQR 37·5-47) years. Per year of untreated HIV infection (median observation 8·08 years, IQR 4·83-11·09), mean EAA was 0·47 years (95% CI 0·37 to 0·57) for Horvath's clock, 0·43 years (0·3 to 0·57) for Hannum's clock, 0·36 years (0·27 to 0·44) for SkinBlood clock, and 0·69 years (0·51 to 0·86) for PhenoAge. Per year of suppressive ART (median observation 9·8 years, IQR 7·2-11), mean EAA was -0·35 years (95% CI -0·44 to -0·27) for Horvath's clock, -0·39 years (-0·50 to -0·27) for Hannum's clock, -0·26 years (-0·33 to -0·18) for SkinBlood clock, and -0·49 years (-0·64 to -0·35) for PhenoAge. Our findings indicate that people with HIV epigenetically aged by a mean of 1·47 years for Horvath's clock, 1·43 years for Hannum's clock, 1·36 years for SkinBlood clock, and 1·69 years for PhenoAge per year of untreated HIV infection; and 0·65 years for Horvath's clock, 0·61 years for Hannum's clock, 0·74 years for SkinBlood clock, and 0·51 years for PhenoAge, per year of suppressive ART. GrimAge showed some change in the mean EAA during untreated HIV infection (0·10 years, 0·02 to 0·19) and suppressive ART (-0·05 years, -0·12 to 0·02). We obtained very similar results using the rate of epigenetic ageing. Contribution of multiple HIV-related, antiretroviral, and immunological variables, and of a DNA methylation-associated polygenic risk score to EAA was small. INTERPRETATION In a longitudinal study over more than 17 years, epigenetic ageing accelerated during untreated HIV infection and decelerated during suppressive ART, highlighting the importance of limiting the duration of untreated HIV infection. FUNDING Swiss HIV Cohort Study, Swiss National Science Foundation, and Gilead Sciences.
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Affiliation(s)
- Isabella C Schoepf
- Department of Infectious Diseases, Bern University Hospital, University of Bern, Bern, Switzerland; University Department of Medicine and Infectious Diseases Service, Kantonsspital Baselland, University of Basel, Bruderholz, Switzerland
| | - Andrés Esteban-Cantos
- HIV/AIDS and Infectious Diseases Research Group, Hospital La Paz Institute for Health Research, Madrid, Spain; CIBER of Infectious Diseases, Madrid, Spain
| | - Christian W Thorball
- Precision Medicine Unit, Centre hospitalier universitaire vaudois, Switzerland; School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne, Switzerland
| | - Berta Rodés
- HIV/AIDS and Infectious Diseases Research Group, Hospital La Paz Institute for Health Research, Madrid, Spain; CIBER of Infectious Diseases, Madrid, Spain
| | - Peter Reiss
- Amsterdam UMC, location University of Amsterdam, Global Health, Amsterdam, Netherlands; Amsterdam Institute for Global Health and Development, Amsterdam, Netherlands
| | - Javier Rodríguez-Centeno
- HIV/AIDS and Infectious Diseases Research Group, Hospital La Paz Institute for Health Research, Madrid, Spain; CIBER of Infectious Diseases, Madrid, Spain
| | - Carlotta Riebensahm
- Department of Infectious Diseases, Bern University Hospital, University of Bern, Bern, Switzerland; Graduate School of Health Sciences, University of Bern, Bern, Switzerland
| | - Dominique L Braun
- Department of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich, Zurich, Switzerland
| | - Catia Marzolini
- Division of Infectious Diseases and Hospital Epidemiology, University Hospital Basel, Basel, Switzerland
| | - Marco Seneghini
- Division of Infectious Diseases, Kantonsspital St Gallen, St Gallen, Switzerland
| | - Enos Bernasconi
- Division of Infectious Diseases, Ente Ospedaliero Cantonale, University of Geneva and University of Southern Switzerland, Lugano, Switzerland
| | - Matthias Cavassini
- Infectious Diseases Service, Lausanne University Hospital University of Lausanne, Switzerland
| | - Hélène Buvelot
- Division of Infectious Disease, Geneva University Hospital, Geneva, Switzerland
| | | | - Roger D Kouyos
- Department of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich, Zurich, Switzerland; Institute of Medical Virology, University of Zurich, Zurich, Switzerland
| | - Jacques Fellay
- Precision Medicine Unit, Centre hospitalier universitaire vaudois, Switzerland; School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne, Switzerland
| | - Huldrych F Günthard
- Department of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich, Zurich, Switzerland; Institute of Medical Virology, University of Zurich, Zurich, Switzerland
| | - José R Arribas
- HIV/AIDS and Infectious Diseases Research Group, Hospital La Paz Institute for Health Research, Madrid, Spain; CIBER of Infectious Diseases, Madrid, Spain
| | - Bruno Ledergerber
- Department of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich, Zurich, Switzerland
| | - Philip E Tarr
- University Department of Medicine and Infectious Diseases Service, Kantonsspital Baselland, University of Basel, Bruderholz, Switzerland.
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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: 42] [Impact Index Per Article: 42.0] [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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Balfour D, Melton PE, McVeigh JA, Huang R, Eastwood PR, Wanstall S, Reynolds AC, Cohen‐Woods S. Childhood sleep health and epigenetic age acceleration in late adolescence: Cross-sectional and longitudinal analyses. Acta Paediatr 2023; 112:1001-1010. [PMID: 36808764 PMCID: PMC10952569 DOI: 10.1111/apa.16719] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/23/2022] [Revised: 01/14/2023] [Accepted: 02/17/2023] [Indexed: 02/22/2023]
Abstract
AIM Investigate if childhood measures of sleep health are associated with epigenetic age acceleration in late adolescence. METHODS Parent-reported sleep trajectories from age 5 to 17, self-reported sleep problems at age 17, and six measures of epigenetic age acceleration at age 17 were studied in 1192 young Australians from the Raine Study Gen2. RESULTS There was no evidence for a relationship between the parent-reported sleep trajectories and epigenetic age acceleration (p ≥ 0.17). There was a positive cross-sectional relationship between self-reported sleep problem score and intrinsic epigenetic age acceleration at age 17 (b = 0.14, p = 0.04), which was attenuated after controlling for depressive symptom score at the same age (b = 0.08, p = 0.34). Follow-up analyses suggested this finding may represent greater overtiredness and intrinsic epigenetic age acceleration in adolescents with higher depressive symptoms. CONCLUSION There was no evidence for a relationship between self- or parent-reported sleep health and epigenetic age acceleration in late adolescence after adjusting for depressive symptoms. Mental health should be considered as a potential confounding variable in future research on sleep and epigenetic age acceleration, particularly if subjective measures of sleep are used.
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Affiliation(s)
- David Balfour
- College of Education, Psychology, and Social WorkFlinders UniversityAdelaideSouth AustraliaAustralia
| | - Phillip E. Melton
- Menzies Institute for Medical Research, College of Health and MedicineUniversity of TasmaniaHobartTasmaniaAustralia
- School of Population and Global HealthThe University of Western AustraliaNedlandsWestern AustraliaAustralia
| | - Joanne A. McVeigh
- Curtin School of Allied HealthCurtin UniversityPerthWestern AustraliaAustralia
- Movement Physiology Laboratory, School of PhysiologyUniversity of the WitwatersrandJohannesburgSouth Africa
| | - Rae‐Chi Huang
- Nutrition and Health Innovation Research Institute (NHIRI)Edith Cowan UniversityPerthWestern AustraliaAustralia
| | - Peter R. Eastwood
- Flinders Health and Medical Research Institute (Sleep Health)Flinders UniversityAdelaideSouth AustraliaAustralia
| | - Sian Wanstall
- Flinders Health and Medical Research Institute (Sleep Health)Flinders UniversityAdelaideSouth AustraliaAustralia
| | - Amy C. Reynolds
- Flinders Health and Medical Research Institute (Sleep Health)Flinders UniversityAdelaideSouth AustraliaAustralia
| | - Sarah Cohen‐Woods
- College of Education, Psychology, and Social WorkFlinders UniversityAdelaideSouth AustraliaAustralia
- Flinders University Institute for Mental Health and WellbeingFlinders UniversityAdelaideSouth AustraliaAustralia
- Flinders Centre for Innovation in CancerFlinders UniversityAdelaideSouth AustraliaAustralia
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34
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Abstract
Ageing is inherent to all human beings, yet why we age remains a hotly contested topic. Most mechanistic explanations of ageing posit that ageing is caused by the accumulation of one or more forms of molecular damage. Here, I propose that we age not because of inevitable damage to the hardware but rather because of intrinsic design flaws in the software, defined as the DNA code that orchestrates how a single cell develops into an adult organism. As the developmental software runs, its sequence of events is reflected in shifting cellular epigenetic states. Overall, I suggest that to understand ageing we need to decode our software and the flow of epigenetic information throughout the life course.
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Affiliation(s)
- João Pedro de Magalhães
- Genomics of Ageing and Rejuvenation Lab, Institute of Inflammation and Ageing, University of Birmingham, Birmingham, B15 2WB, UK.
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35
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Zhang J, Wang S, Liu B. New Insights into the Genetics and Epigenetics of Aging Plasticity. Genes (Basel) 2023; 14:genes14020329. [PMID: 36833255 PMCID: PMC9956228 DOI: 10.3390/genes14020329] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/26/2022] [Revised: 01/14/2023] [Accepted: 01/24/2023] [Indexed: 01/31/2023] Open
Abstract
Biological aging is characterized by irreversible cell cycle blockade, a decreased capacity for tissue regeneration, and an increased risk of age-related diseases and mortality. A variety of genetic and epigenetic factors regulate aging, including the abnormal expression of aging-related genes, increased DNA methylation levels, altered histone modifications, and unbalanced protein translation homeostasis. The epitranscriptome is also closely associated with aging. Aging is regulated by both genetic and epigenetic factors, with significant variability, heterogeneity, and plasticity. Understanding the complex genetic and epigenetic mechanisms of aging will aid the identification of aging-related markers, which may in turn aid the development of effective interventions against this process. This review summarizes the latest research in the field of aging from a genetic and epigenetic perspective. We analyze the relationships between aging-related genes, examine the possibility of reversing the aging process by altering epigenetic age.
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Affiliation(s)
- Jie Zhang
- Shenzhen Key Laboratory for Systemic Aging and Intervention (SKL-SAI), School of Basic Medical Sciences, Shenzhen University, Shenzhen 518000, China
| | - Shixiao Wang
- Shenzhen Key Laboratory for Systemic Aging and Intervention (SKL-SAI), School of Basic Medical Sciences, Shenzhen University, Shenzhen 518000, China
| | - Baohua Liu
- Shenzhen Key Laboratory for Systemic Aging and Intervention (SKL-SAI), School of Basic Medical Sciences, Shenzhen University, Shenzhen 518000, China
- Guangdong Key Laboratory of Genome Stability and Human Disease Prevention, School of Basic Medical Sciences, Medical School, Lihu Campus, Shenzhen University, Shenzhen 518000, China
- Correspondence: ; Tel.: +86-75586674609
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36
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Yang JH, Hayano M, Griffin PT, Amorim JA, Bonkowski MS, Apostolides JK, Salfati EL, Blanchette M, Munding EM, Bhakta M, Chew YC, Guo W, Yang X, Maybury-Lewis S, Tian X, Ross JM, Coppotelli G, Meer MV, Rogers-Hammond R, Vera DL, Lu YR, Pippin JW, Creswell ML, Dou Z, Xu C, Mitchell SJ, Das A, O'Connell BL, Thakur S, Kane AE, Su Q, Mohri Y, Nishimura EK, Schaevitz L, Garg N, Balta AM, Rego MA, Gregory-Ksander M, Jakobs TC, Zhong L, Wakimoto H, El Andari J, Grimm D, Mostoslavsky R, Wagers AJ, Tsubota K, Bonasera SJ, Palmeira CM, Seidman JG, Seidman CE, Wolf NS, Kreiling JA, Sedivy JM, Murphy GF, Green RE, Garcia BA, Berger SL, Oberdoerffer P, Shankland SJ, Gladyshev VN, Ksander BR, Pfenning AR, Rajman LA, Sinclair DA. Loss of epigenetic information as a cause of mammalian aging. Cell 2023; 186:305-326.e27. [PMID: 36638792 PMCID: PMC10166133 DOI: 10.1016/j.cell.2022.12.027] [Citation(s) in RCA: 156] [Impact Index Per Article: 156.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2021] [Revised: 08/09/2022] [Accepted: 12/15/2022] [Indexed: 01/13/2023]
Abstract
All living things experience an increase in entropy, manifested as a loss of genetic and epigenetic information. In yeast, epigenetic information is lost over time due to the relocalization of chromatin-modifying proteins to DNA breaks, causing cells to lose their identity, a hallmark of yeast aging. Using a system called "ICE" (inducible changes to the epigenome), we find that the act of faithful DNA repair advances aging at physiological, cognitive, and molecular levels, including erosion of the epigenetic landscape, cellular exdifferentiation, senescence, and advancement of the DNA methylation clock, which can be reversed by OSK-mediated rejuvenation. These data are consistent with the information theory of aging, which states that a loss of epigenetic information is a reversible cause of aging.
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Affiliation(s)
- Jae-Hyun Yang
- Paul F. Glenn Center for Biology of Aging Research, Department of Genetics, Blavatnik Institute, Harvard Medical School (HMS), Boston, MA, USA.
| | - Motoshi Hayano
- Paul F. Glenn Center for Biology of Aging Research, Department of Genetics, Blavatnik Institute, Harvard Medical School (HMS), Boston, MA, USA; Department of Ophthalmology, Department of Neuropsychiatry, Keio University School of Medicine, Tokyo, Japan
| | - Patrick T Griffin
- Paul F. Glenn Center for Biology of Aging Research, Department of Genetics, Blavatnik Institute, Harvard Medical School (HMS), Boston, MA, USA
| | - João A Amorim
- Paul F. Glenn Center for Biology of Aging Research, Department of Genetics, Blavatnik Institute, Harvard Medical School (HMS), Boston, MA, USA; IIIUC-Institute of Interdisciplinary Research, University of Coimbra, Coimbra, Portugal
| | - Michael S Bonkowski
- Paul F. Glenn Center for Biology of Aging Research, Department of Genetics, Blavatnik Institute, Harvard Medical School (HMS), Boston, MA, USA
| | - John K Apostolides
- Computational Biology Department, Carnegie Mellon University, Pittsburgh, PA, USA
| | - Elias L Salfati
- Paul F. Glenn Center for Biology of Aging Research, Department of Genetics, Blavatnik Institute, Harvard Medical School (HMS), Boston, MA, USA
| | | | | | - Mital Bhakta
- Cantata/Dovetail Genomics, Scotts Valley, CA, USA
| | | | - Wei Guo
- Zymo Research Corporation, Irvine, CA, USA
| | | | - Sun Maybury-Lewis
- Paul F. Glenn Center for Biology of Aging Research, Department of Genetics, Blavatnik Institute, Harvard Medical School (HMS), Boston, MA, USA
| | - Xiao Tian
- Paul F. Glenn Center for Biology of Aging Research, Department of Genetics, Blavatnik Institute, Harvard Medical School (HMS), Boston, MA, USA
| | - Jaime M Ross
- Paul F. Glenn Center for Biology of Aging Research, Department of Genetics, Blavatnik Institute, Harvard Medical School (HMS), Boston, MA, USA
| | - Giuseppe Coppotelli
- Paul F. Glenn Center for Biology of Aging Research, Department of Genetics, Blavatnik Institute, Harvard Medical School (HMS), Boston, MA, USA
| | - Margarita V Meer
- Department of Medicine, Brigham and Women's Hospital, HMS, Boston, MA, USA
| | - Ryan Rogers-Hammond
- Paul F. Glenn Center for Biology of Aging Research, Department of Genetics, Blavatnik Institute, Harvard Medical School (HMS), Boston, MA, USA
| | - Daniel L Vera
- Paul F. Glenn Center for Biology of Aging Research, Department of Genetics, Blavatnik Institute, Harvard Medical School (HMS), Boston, MA, USA
| | - Yuancheng Ryan Lu
- Paul F. Glenn Center for Biology of Aging Research, Department of Genetics, Blavatnik Institute, Harvard Medical School (HMS), Boston, MA, USA
| | - Jeffrey W Pippin
- Division of Nephrology, University of Washington, Seattle, WA, USA
| | - Michael L Creswell
- Division of Nephrology, University of Washington, Seattle, WA, USA; Georgetown University School of Medicine, Washington, DC, USA
| | - Zhixun Dou
- Department of Cell and Developmental Biology, University of Pennsylvania, Philadelphia, PA, USA
| | - Caiyue Xu
- Department of Cell and Developmental Biology, University of Pennsylvania, Philadelphia, PA, USA
| | | | - Abhirup Das
- Paul F. Glenn Center for Biology of Aging Research, Department of Genetics, Blavatnik Institute, Harvard Medical School (HMS), Boston, MA, USA; Department of Pharmacology, UNSW, Sydney, NSW, Australia
| | | | - Sachin Thakur
- Paul F. Glenn Center for Biology of Aging Research, Department of Genetics, Blavatnik Institute, Harvard Medical School (HMS), Boston, MA, USA
| | - Alice E Kane
- Paul F. Glenn Center for Biology of Aging Research, Department of Genetics, Blavatnik Institute, Harvard Medical School (HMS), Boston, MA, USA
| | - Qiao Su
- Computational Biology Department, Carnegie Mellon University, Pittsburgh, PA, USA
| | - Yasuaki Mohri
- Department of Stem Cell Biology, Tokyo Medical and Dental University, Tokyo, Japan
| | - Emi K Nishimura
- Department of Stem Cell Biology, Tokyo Medical and Dental University, Tokyo, Japan
| | | | - Neha Garg
- Paul F. Glenn Center for Biology of Aging Research, Department of Genetics, Blavatnik Institute, Harvard Medical School (HMS), Boston, MA, USA
| | - Ana-Maria Balta
- Paul F. Glenn Center for Biology of Aging Research, Department of Genetics, Blavatnik Institute, Harvard Medical School (HMS), Boston, MA, USA
| | - Meghan A Rego
- Paul F. Glenn Center for Biology of Aging Research, Department of Genetics, Blavatnik Institute, Harvard Medical School (HMS), Boston, MA, USA
| | | | - Tatjana C Jakobs
- Schepens Eye Research Institute, Massachusetts Eye and Ear Infirmary, HMS, Boston, MA, USA
| | - Lei Zhong
- The Massachusetts General Hospital Cancer Center, HMS, Boston, MA, USA
| | | | - Jihad El Andari
- Department of Infectious Diseases/Virology, Section Viral Vector Technologies, Medical Faculty, University of Heidelberg, BioQuant, Heidelberg, Germany
| | - Dirk Grimm
- Department of Infectious Diseases/Virology, Section Viral Vector Technologies, Medical Faculty, University of Heidelberg, BioQuant, Heidelberg, Germany
| | - Raul Mostoslavsky
- The Massachusetts General Hospital Cancer Center, HMS, Boston, MA, USA
| | - Amy J Wagers
- Paul F. Glenn Center for Biology of Aging Research, Harvard Stem Cell Institute, Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, MA, USA; Joslin Diabetes Center, Boston, MA, USA
| | - Kazuo Tsubota
- Department of Ophthalmology, Department of Neuropsychiatry, Keio University School of Medicine, Tokyo, Japan
| | - Stephen J Bonasera
- Division of Geriatrics, University of Nebraska Medical Center, Durham Research Center II, Omaha, NE, USA
| | - Carlos M Palmeira
- Department of Life Sciences, Faculty of Sciences and Technology, University of Coimbra, Coimbra, Portugal
| | | | | | - Norman S Wolf
- Department of Pathology, University of Washington, Seattle, WA, USA
| | - Jill A Kreiling
- Department of Molecular Biology, Cell Biology and Biochemistry, Brown University, Providence, RI, USA
| | - John M Sedivy
- Department of Molecular Biology, Cell Biology and Biochemistry, Brown University, Providence, RI, USA
| | - George F Murphy
- Department of Pathology, Brigham & Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Richard E Green
- Department of Biomolecular Engineering, UCSC, Santa Cruz, CA, USA
| | - Benjamin A Garcia
- Department of Cell and Developmental Biology, University of Pennsylvania, Philadelphia, PA, USA
| | - Shelley L Berger
- Department of Cell and Developmental Biology, University of Pennsylvania, Philadelphia, PA, USA
| | | | | | - Vadim N Gladyshev
- Department of Medicine, Brigham and Women's Hospital, HMS, Boston, MA, USA
| | - Bruce R Ksander
- Schepens Eye Research Institute, Massachusetts Eye and Ear Infirmary, HMS, Boston, MA, USA
| | - Andreas R Pfenning
- Computational Biology Department, Carnegie Mellon University, Pittsburgh, PA, USA
| | - Luis A Rajman
- Paul F. Glenn Center for Biology of Aging Research, Department of Genetics, Blavatnik Institute, Harvard Medical School (HMS), Boston, MA, USA
| | - David A Sinclair
- Paul F. Glenn Center for Biology of Aging Research, Department of Genetics, Blavatnik Institute, Harvard Medical School (HMS), Boston, MA, USA.
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37
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López-Otín C, Blasco MA, Partridge L, Serrano M, Kroemer G. Hallmarks of aging: An expanding universe. Cell 2023; 186:243-278. [PMID: 36599349 DOI: 10.1016/j.cell.2022.11.001] [Citation(s) in RCA: 860] [Impact Index Per Article: 860.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2022] [Revised: 09/19/2022] [Accepted: 11/01/2022] [Indexed: 01/05/2023]
Abstract
Aging is driven by hallmarks fulfilling the following three premises: (1) their age-associated manifestation, (2) the acceleration of aging by experimentally accentuating them, and (3) the opportunity to decelerate, stop, or reverse aging by therapeutic interventions on them. We propose the following twelve hallmarks of aging: genomic instability, telomere attrition, epigenetic alterations, loss of proteostasis, disabled macroautophagy, deregulated nutrient-sensing, mitochondrial dysfunction, cellular senescence, stem cell exhaustion, altered intercellular communication, chronic inflammation, and dysbiosis. These hallmarks are interconnected among each other, as well as to the recently proposed hallmarks of health, which include organizational features of spatial compartmentalization, maintenance of homeostasis, and adequate responses to stress.
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Affiliation(s)
- Carlos López-Otín
- Departamento de Bioquímica y Biología Molecular, Instituto Universitario de Oncología (IUOPA), Universidad de Oviedo, Oviedo, Spain; Instituto de Investigación Sanitaria del Principado de Asturias (ISPA), Oviedo, Spain; Centro de Investigación Biomédica en Red de Cáncer (CIBERONC), Madrid, Spain.
| | - Maria A Blasco
- Telomeres and Telomerase Group, Molecular Oncology Program, Spanish National Cancer Centre (CNIO), Madrid, Spain
| | - Linda Partridge
- Department of Genetics, Evolution and Environment, Institute of Healthy Ageing, University College London, London, UK; Max Planck Institute for Biology of Ageing, Cologne, Germany
| | - Manuel Serrano
- Institute for Research in Biomedicine (IRB Barcelona), Barcelona Institute of Science and Technology (BIST), Barcelona, Spain; Catalan Institution for Research and Advanced Studies (ICREA), Barcelona, Spain; Altos Labs, Cambridge, UK
| | - Guido Kroemer
- Centre de Recherche des Cordeliers, Equipe labellisée par la Ligue contre le cancer, Université de Paris, Sorbonne Université, INSERM U1138, Institut Universitaire de France, Paris, France; Metabolomics and Cell Biology Platforms, Gustave Roussy, Villejuif, France; Institut du Cancer Paris CARPEM, Department of Biology, Hôpital Européen Georges Pompidou, AP-HP, Paris, France.
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38
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Hartmann C, Herling L, Hartmann A, Köckritz V, Fuellen G, Walter M, Hermann A. Systematic estimation of biological age of in vitro cell culture systems by an age-associated marker panel. FRONTIERS IN AGING 2023; 4:1129107. [PMID: 36873743 PMCID: PMC9975507 DOI: 10.3389/fragi.2023.1129107] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/21/2022] [Accepted: 02/02/2023] [Indexed: 02/17/2023]
Abstract
Aging is a process that affects almost all multicellular organisms and since our population ages with increasing prevalence of age-related diseases, it is important to study basic processes involved in aging. Many studies have been published so far using different and often single age markers to estimate the biological age of organisms or different cell culture systems. However, comparability of studies is often hampered by the lack of a uniform panel of age markers. Consequently, we here suggest an easy-to-use biomarker-based panel of classical age markers to estimate the biological age of cell culture systems that can be used in standard cell culture laboratories. This panel is shown to be sensitive in a variety of aging conditions. We used primary human skin fibroblasts of different donor ages and additionally induced either replicative senescence or artificial aging by progerin overexpression. Using this panel, highest biological age was found for artificial aging by progerin overexpression. Our data display that aging varies depending on cell line and aging model and even from individual to individual showing the need for comprehensive analyses.
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Affiliation(s)
- Christiane Hartmann
- Translational Neurodegeneration Section "Albrecht-Kossel", Department of Neurology, University Medical Center Rostock, Rostock, Germany
| | - Luise Herling
- Translational Neurodegeneration Section "Albrecht-Kossel", Department of Neurology, University Medical Center Rostock, Rostock, Germany
| | - Alexander Hartmann
- Institute of Clinical Chemistry and Laboratory Medicine, University Medical Center Rostock, Rostock, Germany
| | - Verena Köckritz
- Translational Neurodegeneration Section "Albrecht-Kossel", Department of Neurology, University Medical Center Rostock, Rostock, Germany
| | - Georg Fuellen
- Institute for Biostatistics and Informatics in Medicine and Ageing Research, Rostock University Medical Center, Rostock, Germany.,Center for Transdisciplinary Neurosciences Rostock (CTNR), University Medical Center Rostock, Rostock, Germany
| | - Michael Walter
- Institute of Clinical Chemistry and Laboratory Medicine, University Medical Center Rostock, Rostock, Germany.,Center for Transdisciplinary Neurosciences Rostock (CTNR), University Medical Center Rostock, Rostock, Germany
| | - Andreas Hermann
- Translational Neurodegeneration Section "Albrecht-Kossel", Department of Neurology, University Medical Center Rostock, Rostock, Germany.,Center for Transdisciplinary Neurosciences Rostock (CTNR), University Medical Center Rostock, Rostock, Germany.,Deutsches Zentrum für Neurodegenerative Erkrankungen (DZNE) Rostock/Greifswald, Rostock, Germany
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39
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Nunn AVW, Guy GW, Brysch W, Bell JD. Understanding Long COVID; Mitochondrial Health and Adaptation-Old Pathways, New Problems. Biomedicines 2022; 10:3113. [PMID: 36551869 PMCID: PMC9775339 DOI: 10.3390/biomedicines10123113] [Citation(s) in RCA: 23] [Impact Index Per Article: 11.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2022] [Revised: 11/28/2022] [Accepted: 11/30/2022] [Indexed: 12/04/2022] Open
Abstract
Many people infected with the SARS-CoV-2 suffer long-term symptoms, such as "brain fog", fatigue and clotting problems. Explanations for "long COVID" include immune imbalance, incomplete viral clearance and potentially, mitochondrial dysfunction. As conditions with sub-optimal mitochondrial function are associated with initial severity of the disease, their prior health could be key in resistance to long COVID and recovery. The SARs virus redirects host metabolism towards replication; in response, the host can metabolically react to control the virus. Resolution is normally achieved after viral clearance as the initial stress activates a hormetic negative feedback mechanism. It is therefore possible that, in some individuals with prior sub-optimal mitochondrial function, the virus can "tip" the host into a chronic inflammatory cycle. This might explain the main symptoms, including platelet dysfunction. Long COVID could thus be described as a virally induced chronic and self-perpetuating metabolically imbalanced non-resolving state characterised by mitochondrial dysfunction, where reactive oxygen species continually drive inflammation and a shift towards glycolysis. This would suggest that a sufferer's metabolism needs to be "tipped" back using a stimulus, such as physical activity, calorie restriction, or chemical compounds that mimic these by enhancing mitochondrial function, perhaps in combination with inhibitors that quell the inflammatory response.
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Affiliation(s)
- Alistair V. W. Nunn
- Research Centre for Optimal Health, Department of Life Sciences, University of Westminster, London W1W 6UW, UK
| | - Geoffrey W. Guy
- The Guy Foundation, Chedington Court, Beaminster, Dorset DT8 3HY, UK
| | | | - Jimmy D. Bell
- Research Centre for Optimal Health, Department of Life Sciences, University of Westminster, London W1W 6UW, UK
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