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Hayat M, Syed RA, Qaiser H, Uzair M, Al-Regaiey K, Khallaf R, Albassam LAM, Kaleem I, Wang X, Wang R, Bhatti MS, Bashir S. Decoding molecular mechanisms: brain aging and Alzheimer's disease. Neural Regen Res 2025; 20:2279-2299. [PMID: 39104174 DOI: 10.4103/nrr.nrr-d-23-01403] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2023] [Accepted: 07/04/2024] [Indexed: 08/07/2024] Open
Abstract
The complex morphological, anatomical, physiological, and chemical mechanisms within the aging brain have been the hot topic of research for centuries. The aging process alters the brain structure that affects functions and cognitions, but the worsening of such processes contributes to the pathogenesis of neurodegenerative disorders, such as Alzheimer's disease. Beyond these observable, mild morphological shifts, significant functional modifications in neurotransmission and neuronal activity critically influence the aging brain. Understanding these changes is important for maintaining cognitive health, especially given the increasing prevalence of age-related conditions that affect cognition. This review aims to explore the age-induced changes in brain plasticity and molecular processes, differentiating normal aging from the pathogenesis of Alzheimer's disease, thereby providing insights into predicting the risk of dementia, particularly Alzheimer's disease.
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Affiliation(s)
- Mahnoor Hayat
- Atta-ur-Rahman School of Applied Biosciences (ASAB), National University of Sciences and Technology (NUST), Islamabad, Pakistan
| | - Rafay Ali Syed
- Department of Biotechnology, Quaid-i-Azam University, Islamabad, Pakistan
| | - Hammad Qaiser
- Department of Biological Sciences, Faculty of Basic & Applied Sciences, International Islamic University Islamabad (IIUI), Islamabad, Pakistan
| | - Mohammad Uzair
- Department of Bioengineering, King Fahd University of Petroleum and Minerals, Dhahran, Saudi Arabia
| | - Khalid Al-Regaiey
- Department of Physiology, College of Medicine, King Saud University, Riyadh, Saudi Arabia
| | - Roaa Khallaf
- Department of Neurology, Neuroscience Center, King Fahad Specialist Hospital, Dammam, Saudi Arabia
| | | | - Imdad Kaleem
- Department of Biosciences, Commission on Science and Technology for Sustainable Development in the South (COMSATS University), Islamabad, Pakistan
| | - Xueyi Wang
- Department of Psychiatry, The First Hospital of Hebei Medical University, Shijiazhuang, Hebei Province, China
- Mental Health Institute of Hebei Medical University, Shijiazhuang, Hebei Province, China
| | - Ran Wang
- Department of Psychiatry, The First Hospital of Hebei Medical University, Shijiazhuang, Hebei Province, China
- Mental Health Institute of Hebei Medical University, Shijiazhuang, Hebei Province, China
| | - Mehwish S Bhatti
- Department of Neurobiology and Behavior, University of California, Irvine, CA, USA
| | - Shahid Bashir
- Neuroscience Center, King Fahad Specialist Hospital Dammam, Dammam, Saudi Arabia
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2
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Hao Y, Han K, Wang T, Yu J, Ding H, Dao F. Exploring the potential of epigenetic clocks in aging research. Methods 2024; 231:37-44. [PMID: 39251102 DOI: 10.1016/j.ymeth.2024.09.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2024] [Revised: 07/26/2024] [Accepted: 09/01/2024] [Indexed: 09/11/2024] Open
Abstract
The process of aging is a notable risk factor for numerous age-related illnesses. Hence, a reliable technique for evaluating biological age or the pace of aging is crucial for understanding the aging process and its influence on the progression of disease. Epigenetic alterations are recognized as a prominent biomarker of aging, and epigenetic clocks formulated on this basis have been shown to provide precise estimations of chronological age. Extensive research has validated the effectiveness of epigenetic clocks in determining aging rates, identifying risk factors for aging, evaluating the impact of anti-aging interventions, and predicting the emergence of age-related diseases. This review provides a detailed overview of the theoretical principles underlying the development of epigenetic clocks and their utility in aging research. Furthermore, it explores the existing obstacles and possibilities linked to epigenetic clocks and proposes potential avenues for future studies in this field.
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Affiliation(s)
- Yuduo Hao
- Center for Informational Biology, University of Electronic Science and Technology of China, Chengdu 610054, China
| | - Kaiyuan Han
- Center for Informational Biology, University of Electronic Science and Technology of China, Chengdu 610054, China
| | - Ting Wang
- Center for Informational Biology, University of Electronic Science and Technology of China, Chengdu 610054, China
| | - Junwen Yu
- Center for Informational Biology, University of Electronic Science and Technology of China, Chengdu 610054, China
| | - Hui Ding
- Center for Informational Biology, University of Electronic Science and Technology of China, Chengdu 610054, China.
| | - Fuying Dao
- School of Biological Sciences, Nanyang Technological University, Singapore 639798, Singapore.
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3
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Gigliotti G, Joshi R, Khalid A, Widmer D, Boccellino M, Viggiano D. Epigenetics, Microbiome and Personalized Medicine: Focus on Kidney Disease. Int J Mol Sci 2024; 25:8592. [PMID: 39201279 PMCID: PMC11354516 DOI: 10.3390/ijms25168592] [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: 07/03/2024] [Revised: 07/25/2024] [Accepted: 07/31/2024] [Indexed: 09/02/2024] Open
Abstract
Personalized medicine, which involves modifying treatment strategies/drug dosages based on massive laboratory/imaging data, faces large statistical and study design problems. The authors believe that the use of continuous multidimensional data, such as those regarding gut microbiota, or binary multidimensional systems properly transformed into a continuous variable, such as the epigenetic clock, offer an advantageous scenario for the design of trials of personalized medicine. We will discuss examples focusing on kidney diseases, specifically on IgA nephropathy. While gut dysbiosis can provide a treatment strategy to restore the standard gut microbiota using probiotics, transforming epigenetic omics data into epigenetic clocks offers a promising tool for personalized acute and chronic kidney disease care. Epigenetic clocks involve a complex transformation of DNA methylome data into estimated biological age. These clocks can identify people at high risk of developing kidney problems even before symptoms appear. Some of the effects of both the epigenetic clock and microbiota on kidney diseases seem to be mediated by endothelial dysfunction. These "big data" (epigenetic clocks and microbiota) can help tailor treatment plans by pinpointing patients likely to experience rapid declines or those who might not need overly aggressive therapies.
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Affiliation(s)
| | - Rashmi Joshi
- Department Translational Medical Sciences, University of Campania, 81100 Naples, Italy; (R.J.); (A.K.); (D.V.)
| | - Anam Khalid
- Department Translational Medical Sciences, University of Campania, 81100 Naples, Italy; (R.J.); (A.K.); (D.V.)
| | | | - Mariarosaria Boccellino
- Department Experimental Medicine, University of Campania, 81100 Naples, Italy
- Department Life Sciences, Health and Health Professions, Link University, 00165 Rome, Italy
| | - Davide Viggiano
- Department Translational Medical Sciences, University of Campania, 81100 Naples, Italy; (R.J.); (A.K.); (D.V.)
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4
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Guynes K, Sarre LA, Carrillo-Baltodano AM, Davies BE, Xu L, Liang Y, Martín-Zamora FM, Hurd PJ, de Mendoza A, Martín-Durán JM. Annelid methylomes reveal ancestral developmental and aging-associated epigenetic erosion across Bilateria. Genome Biol 2024; 25:204. [PMID: 39090757 PMCID: PMC11292947 DOI: 10.1186/s13059-024-03346-z] [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: 01/17/2024] [Accepted: 07/23/2024] [Indexed: 08/04/2024] Open
Abstract
BACKGROUND DNA methylation in the form of 5-methylcytosine (5mC) is the most abundant base modification in animals. However, 5mC levels vary widely across taxa. While vertebrate genomes are hypermethylated, in most invertebrates, 5mC concentrates on constantly and highly transcribed genes (gene body methylation; GbM) and, in some species, on transposable elements (TEs), a pattern known as "mosaic". Yet, the role and developmental dynamics of 5mC and how these explain interspecies differences in DNA methylation patterns remain poorly understood, especially in Spiralia, a large clade of invertebrates comprising nearly half of the animal phyla. RESULTS Here, we generate base-resolution methylomes for three species with distinct genomic features and phylogenetic positions in Annelida, a major spiralian phylum. All possible 5mC patterns occur in annelids, from typical invertebrate intermediate levels in a mosaic distribution to hypermethylation and methylation loss. GbM is common to annelids with 5mC, and methylation differences across species are explained by taxon-specific transcriptional dynamics or the presence of intronic TEs. Notably, the link between GbM and transcription decays during development, alongside a gradual and global, age-dependent demethylation in adult stages. Additionally, reducing 5mC levels with cytidine analogs during early development impairs normal embryogenesis and reactivates TEs in the annelid Owenia fusiformis. CONCLUSIONS Our study indicates that global epigenetic erosion during development and aging is an ancestral feature of bilateral animals. However, the tight link between transcription and gene body methylation is likely more important in early embryonic stages, and 5mC-mediated TE silencing probably emerged convergently across animal lineages.
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Affiliation(s)
- Kero Guynes
- School of Biological and Behavioural Sciences, Queen Mary University of London, Mile End Road, London, E1 4NS, UK
- Institute of Molecular Biotechnology of the Austrian Academy of Sciences (IMBA), Vienna BioCenter (VBC), Vienna, 1030, Austria
| | - Luke A Sarre
- School of Biological and Behavioural Sciences, Queen Mary University of London, Mile End Road, London, E1 4NS, UK
| | - Allan M Carrillo-Baltodano
- School of Biological and Behavioural Sciences, Queen Mary University of London, Mile End Road, London, E1 4NS, UK
| | - Billie E Davies
- School of Biological and Behavioural Sciences, Queen Mary University of London, Mile End Road, London, E1 4NS, UK
| | - Lan Xu
- School of Biological and Behavioural Sciences, Queen Mary University of London, Mile End Road, London, E1 4NS, UK
| | - Yan Liang
- School of Biological and Behavioural Sciences, Queen Mary University of London, Mile End Road, London, E1 4NS, UK
| | - Francisco M Martín-Zamora
- School of Biological and Behavioural Sciences, Queen Mary University of London, Mile End Road, London, E1 4NS, UK
- Altos Labs, Cambridge, UK
| | - Paul J Hurd
- School of Biological and Behavioural Sciences, Queen Mary University of London, Mile End Road, London, E1 4NS, UK
| | - Alex de Mendoza
- School of Biological and Behavioural Sciences, Queen Mary University of London, Mile End Road, London, E1 4NS, UK.
| | - José M Martín-Durán
- School of Biological and Behavioural Sciences, Queen Mary University of London, Mile End Road, London, E1 4NS, UK.
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5
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Griñán-Ferré C, Bellver-Sanchis A, Guerrero A, Pallàs M. Advancing personalized medicine in neurodegenerative diseases: The role of epigenetics and pharmacoepigenomics in pharmacotherapy. Pharmacol Res 2024; 205:107247. [PMID: 38834164 DOI: 10.1016/j.phrs.2024.107247] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/16/2024] [Revised: 04/23/2024] [Accepted: 05/30/2024] [Indexed: 06/06/2024]
Abstract
About 80 % of brain disorders have a genetic basis. The pathogenesis of most neurodegenerative diseases is associated with a myriad of genetic defects, epigenetic alterations (DNA methylation, histone/chromatin remodeling, miRNA dysregulation), and environmental factors. The emergence of new sequencing technologies and tools to study the epigenome has led to identifying predictive biomarkers for earlier diagnosis, opening up the possibility of prophylactical interventions. As a result, advances in pharmacogenetics and pharmacoepigenomics now allow for personalized treatments based on the profile of each patient and the specific genetic and epigenetic mechanisms involved. This Review highlights the complexity of neurodegenerative diseases and the variability in patient responses to pharmacotherapy, emphasizing the influence of genetic polymorphisms on the pharmacokinetics and pharmacodynamics of drugs used to treat those conditions. We specifically discuss the potential modulatory effect of several genetic polymorphisms associated with an increased risk of developing different neurodegenerative diseases. We explore genetic and genomic technologies and the potential of analyzing individual-specific drug metabolism to predict and influence drug response and associated clinical outcomes. We also provide insights into the mechanism of action of the drugs under investigation and their potential impact on disease-modifying pathways. Finally, the Review underscores the great potential of this field to enhance the effectiveness and safety of drug treatments through personalized medicine.
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Affiliation(s)
- Christian Griñán-Ferré
- Department of Pharmacology and Therapeutic Chemistry, Institut de Neurociències-Universitat de Barcelona, Avda. Joan XXIII, 27, Barcelona 08028, Spain; Centro de Investigación en Red, Enfermedades Neurodegenerativas (CIBERNED), Instituto de Salud Carlos III, Madrid, Spain.
| | - Aina Bellver-Sanchis
- Department of Pharmacology and Therapeutic Chemistry, Institut de Neurociències-Universitat de Barcelona, Avda. Joan XXIII, 27, Barcelona 08028, Spain
| | - Ana Guerrero
- Department of Pharmacology and Therapeutic Chemistry, Institut de Neurociències-Universitat de Barcelona, Avda. Joan XXIII, 27, Barcelona 08028, Spain
| | - Mercè Pallàs
- Department of Pharmacology and Therapeutic Chemistry, Institut de Neurociències-Universitat de Barcelona, Avda. Joan XXIII, 27, Barcelona 08028, Spain; Centro de Investigación en Red, Enfermedades Neurodegenerativas (CIBERNED), Instituto de Salud Carlos III, Madrid, Spain
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6
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Yu Y, Martins LM. Mitochondrial One-Carbon Metabolism and Alzheimer's Disease. Int J Mol Sci 2024; 25:6302. [PMID: 38928008 PMCID: PMC11203557 DOI: 10.3390/ijms25126302] [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: 03/12/2024] [Revised: 05/13/2024] [Accepted: 05/15/2024] [Indexed: 06/28/2024] Open
Abstract
Mitochondrial one-carbon metabolism provides carbon units to several pathways, including nucleic acid synthesis, mitochondrial metabolism, amino acid metabolism, and methylation reactions. Late-onset Alzheimer's disease is the most common age-related neurodegenerative disease, characterised by impaired energy metabolism, and is potentially linked to mitochondrial bioenergetics. Here, we discuss the intersection between the molecular pathways linked to both mitochondrial one-carbon metabolism and Alzheimer's disease. We propose that enhancing one-carbon metabolism could promote the metabolic processes that help brain cells cope with Alzheimer's disease-related injuries. We also highlight potential therapeutic avenues to leverage one-carbon metabolism to delay Alzheimer's disease pathology.
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Affiliation(s)
- Yizhou Yu
- MRC Toxicology Unit, University of Cambridge, Gleeson Building, Tennis Court Road, Cambridge CB2 1QR, UK
| | - L. Miguel Martins
- MRC Toxicology Unit, University of Cambridge, Gleeson Building, Tennis Court Road, Cambridge CB2 1QR, UK
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7
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Trexler M, Bányai L, Kerekes K, Patthy L. Arginines of the CGN codon family are Achilles' heels of cancer genes. Sci Rep 2024; 14:11715. [PMID: 38778164 PMCID: PMC11111792 DOI: 10.1038/s41598-024-62553-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2023] [Accepted: 05/17/2024] [Indexed: 05/25/2024] Open
Abstract
Recent studies have revealed that arginine is the most favorable target of amino acid alteration in most cancer types and it has been suggested that the high preference for arginine mutations reflects the critical roles of this amino acid in the function of proteins. High rates of mutations of arginine residues in cancer, however, might also be due to increased mutability of arginine codons of the CGN family as the CpG dinucleotides of these codons may be methylated. In the present work we have analyzed spectra of single base substitutions of cancer genes (oncogenes, tumor suppressor genes) and passenger genes in cancer tissues to assess the contributions of CpG hypermutability and selection to arginine mutations. Our studies have shown that arginines encoded by the CGN codon family display higher rates of mutation in both cancer genes and passenger genes than arginine codons AGA and AGG that are devoid of CpG dinucleotide, suggesting that the predominance of arginine mutations in cancer is primarily due to CpG hypermutability, rather than selection for arginine replacement. Nevertheless, our results also suggest that CGN codons for arginines may serve as Achilles' heels of cancer genes. CpG hypermutability of key arginines of proto-oncogenes, leading to high rates of recurrence of driver mutations, contributes significantly to carcinogenesis. Similarly, our results indicate that hypermutability of the CpG dinucleotide of CGA codons (converting them to TGA stop codons) contributes significantly to recurrent truncation and inactivation of tumor suppressor genes.
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Affiliation(s)
- Mária Trexler
- Institute of Enzymology, HUN-REN Research Centre for Natural Sciences, Budapest, 1117, Hungary
| | - László Bányai
- Institute of Enzymology, HUN-REN Research Centre for Natural Sciences, Budapest, 1117, Hungary
| | - Krisztina Kerekes
- Institute of Enzymology, HUN-REN Research Centre for Natural Sciences, Budapest, 1117, Hungary
| | - László Patthy
- Institute of Enzymology, HUN-REN Research Centre for Natural Sciences, Budapest, 1117, Hungary.
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8
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Simonenko SY, Bogdanova DA, Kuldyushev NA. Emerging Roles of Vitamin B 12 in Aging and Inflammation. Int J Mol Sci 2024; 25:5044. [PMID: 38732262 PMCID: PMC11084641 DOI: 10.3390/ijms25095044] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/09/2024] [Revised: 04/28/2024] [Accepted: 04/29/2024] [Indexed: 05/13/2024] Open
Abstract
Vitamin B12 (cobalamin) is an essential nutrient for humans and animals. Metabolically active forms of B12-methylcobalamin and 5-deoxyadenosylcobalamin are cofactors for the enzymes methionine synthase and mitochondrial methylmalonyl-CoA mutase. Malfunction of these enzymes due to a scarcity of vitamin B12 leads to disturbance of one-carbon metabolism and impaired mitochondrial function. A significant fraction of the population (up to 20%) is deficient in vitamin B12, with a higher rate of deficiency among elderly people. B12 deficiency is associated with numerous hallmarks of aging at the cellular and organismal levels. Cellular senescence is characterized by high levels of DNA damage by metabolic abnormalities, increased mitochondrial dysfunction, and disturbance of epigenetic regulation. B12 deficiency could be responsible for or play a crucial part in these disorders. In this review, we focus on a comprehensive analysis of molecular mechanisms through which vitamin B12 influences aging. We review new data about how deficiency in vitamin B12 may accelerate cellular aging. Despite indications that vitamin B12 has an important role in health and healthy aging, knowledge of the influence of vitamin B12 on aging is still limited and requires further research.
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Affiliation(s)
- Sergey Yu. Simonenko
- Research Center for Translational Medicine, Sirius University of Science and Technology, 354340 Sochi, Russia;
| | - Daria A. Bogdanova
- Division of Immunobiology and Biomedicine, Center for Genetics and Life Sciences, Sirius University of Science and Technology, 354340 Sochi, Russia
| | - Nikita A. Kuldyushev
- Research Center for Translational Medicine, Sirius University of Science and Technology, 354340 Sochi, Russia;
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9
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Rizzo JF, Shah MP, Krasniqi D, Lu YR, Sinclair DA, Ksander BR. The Role of Epigenetics in Accelerated Aging: A Reconsideration of Later-Life Visual Loss After Early Optic Neuropathy. J Neuroophthalmol 2024; 44:16-21. [PMID: 37938114 DOI: 10.1097/wno.0000000000002041] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2023]
Abstract
BACKGROUND In 2005, we reported 3 patients with bilateral optic nerve damage early in life. These patients had stable vision for decades but then experienced significant bilateral vision loss with no obvious cause. Our hypothesis, novel at that time, was that the late decline of vision was due to age-related attrition of retinal ganglion cells superimposed on a reduced neuronal population due to the earlier injury. EVIDENCE ACQUISITION The field of epigenetics provides a new paradigm with which to consider the normal aging process and the impact of neuronal injury, which has been shown to accelerate aging. Late-in-life decline in function after early neuronal injury occurs in multiple sclerosis due to dysregulated inflammation and postpolio syndrome. Recent studies by our group in mice have also demonstrated the possibility of partial reversal of cellular aging and the potential to mitigate anatomical damage after injury and even improve visual function. RESULTS The results in mice and nonhuman primates published elsewhere have shown enhanced neuronal survival and visual function after partial epigenetic reprogramming. CONCLUSIONS Injury promotes epigenetic aging , and this finding can be observed in several clinically relevant scenarios. An understanding of the epigenetic mechanisms at play opens the opportunity to restore function in the nervous system and elsewhere with cellular rejuvenation therapies. Our earlier cases exemplify how reconsideration of previously established concepts can motivate inquiry of new paradigms.
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Affiliation(s)
- Joseph F Rizzo
- Department of Ophthalmology and the Neuro-Ophthalmology Service (JFR), Massachusetts Eye and Ear and the Harvard Medical School, Boston, Massachusetts; Avedisian and Chobanian School of Medicine (MPS), Boston University, Boston, Massachusetts; Department of Ophthalmology (MPS, DK, BRK), Harvard Medical School, Schepens Eye Research Institute of Mass Eye & Ear, Boston, Massachusetts; Department of Biology (YRL), Whitehead Institute for Biomedical Sciences, MIT, Cambridge, Massachusetts; and Paul F. Glenn Center for Biology of Aging Research (DAS), Department of Genetics, Blavatnik Institute, Harvard Medical School, Boston, Massachusetts
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10
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Lozupone M, Solfrizzi V, Sardone R, Dibello V, Castellana F, Zupo R, Lampignano L, Bortone I, Daniele A, Panza F. The epigenetics of frailty. Epigenomics 2024; 16:189-202. [PMID: 38112012 DOI: 10.2217/epi-2023-0279] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2023] Open
Abstract
The conceptual change of frailty, from a physical to a biopsychosocial phenotype, expanded the field of frailty, including social and behavioral domains with critical interaction between different frailty models. Environmental exposures - including physical exercise, psychosocial factors and diet - may play a role in the frailty pathophysiology. Complex underlying mechanisms involve the progressive interactions of genetics with epigenetics and of multimorbidity with environmental factors. Here we review the literature on possible mechanisms explaining the association between epigenetic hallmarks (i.e., global DNA methylation, DNA methylation age acceleration and microRNAs) and frailty, considered as biomarkers of aging. Frailty could be considered the result of environmental epigenetic factors on biological aging, caused by conflicting DNA methylation age and chronological age.
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Affiliation(s)
- Madia Lozupone
- Department of Translational Biomedicine & Neuroscience 'DiBraiN', University of Bari Aldo Moro, Bari, Italy
| | - Vincenzo Solfrizzi
- Cesare Frugoni Internal & Geriatric Medicine & Memory Unit, University of Bari Aldo Moro, Bari, Italy
| | | | - Vittorio Dibello
- Cesare Frugoni Internal & Geriatric Medicine & Memory Unit, University of Bari Aldo Moro, Bari, Italy
- Department of Orofacial Pain & Dysfunction, Academic Centre for Dentistry Amsterdam (ACTA), University of Amsterdam & Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Fabio Castellana
- Cesare Frugoni Internal & Geriatric Medicine & Memory Unit, University of Bari Aldo Moro, Bari, Italy
| | - Roberta Zupo
- Cesare Frugoni Internal & Geriatric Medicine & Memory Unit, University of Bari Aldo Moro, Bari, Italy
| | | | - Ilaria Bortone
- Department of Translational Biomedicine & Neuroscience 'DiBraiN', University of Bari Aldo Moro, Bari, Italy
| | - Antonio Daniele
- Department of Neuroscience, Catholic University of Sacred Heart, Rome, Italy
- Neurology Unit, IRCCS Fondazione Policlinico Universitario A. Gemelli, Rome, Italy
| | - Francesco Panza
- Cesare Frugoni Internal & Geriatric Medicine & Memory Unit, University of Bari Aldo Moro, Bari, Italy
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11
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Kho J, Delgado ML, McCracken GR, Munden J, Ruzzante DE. Epigenetic patterns in Atlantic herring (Clupea harengus): Temperature and photoperiod as environmental stressors during larval development. Mol Ecol 2024; 33:e17187. [PMID: 37909655 DOI: 10.1111/mec.17187] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2023] [Revised: 10/11/2023] [Accepted: 10/16/2023] [Indexed: 11/03/2023]
Abstract
Understanding the molecular mechanisms underlying individual responses to environmental changes is crucial for species conservation and management. Pelagic fishes including Atlantic herring (Clupea harengus) are of particular interest because of their key ecological and economic roles and their susceptibility to a changing ocean from global warming. Temperature and photoperiod have been linked with spawning time and location in adult herring, but no study has thus far investigated the role of environmental factors on gene regulation during the vulnerable early developmental stages. Here, we examine DNA methylation patterns of larval herring bred under two temperatures (11°C and 13°C) and photoperiod (6 and 12 h) regimes in a 2 × 2 factorial design. We found consistently high levels of global methylation across all individuals and a decline in global methylation with increased developmental stage that was more pronounced at 13°C (p ≤ 0.007) than at 11°C (p ≥ 0.21). Most of the differentially methylated sites were in exon and promoter regions for genes linked to metabolism and development, some of which were hypermethylated at higher temperature. These results demonstrate the important role of DNA methylation during larval development and suggest that this molecular mechanism might be key in regulating early-stage responses to environmental stressors in Atlantic herring.
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Affiliation(s)
- J Kho
- Department of Biology, Dalhousie University, Halifax, Canada
| | - M L Delgado
- Department of Biology, Dalhousie University, Halifax, Canada
| | - G R McCracken
- Department of Biology, Dalhousie University, Halifax, Canada
| | - J Munden
- Herring Science Council, Halifax, Canada
| | - D E Ruzzante
- Department of Biology, Dalhousie University, Halifax, Canada
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12
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Fan K, Pfister E, Weng Z. Toward a comprehensive catalog of regulatory elements. Hum Genet 2023; 142:1091-1111. [PMID: 36935423 DOI: 10.1007/s00439-023-02519-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2022] [Accepted: 01/03/2023] [Indexed: 03/21/2023]
Abstract
Regulatory elements are the genomic regions that interact with transcription factors to control cell-type-specific gene expression in different cellular environments. A precise and complete catalog of functional elements encoded by the human genome is key to understanding mammalian gene regulation. Here, we review the current state of regulatory element annotation. We first provide an overview of assays for characterizing functional elements, including genome, epigenome, transcriptome, three-dimensional chromatin interaction, and functional validation assays. We then discuss computational methods for defining regulatory elements, including peak-calling and other statistical modeling methods. Finally, we introduce several high-quality lists of regulatory element annotations and suggest potential future directions.
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Affiliation(s)
- Kaili Fan
- Program in Bioinformatics and Integrative Biology, University of Massachusetts Chan Medical School, 368 Plantation Street, ASC5-1069, Worcester, MA, 01605, USA
- Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, MA, 02138, USA
| | - Edith Pfister
- Program in Bioinformatics and Integrative Biology, University of Massachusetts Chan Medical School, 368 Plantation Street, ASC5-1069, Worcester, MA, 01605, USA
| | - Zhiping Weng
- Program in Bioinformatics and Integrative Biology, University of Massachusetts Chan Medical School, 368 Plantation Street, ASC5-1069, Worcester, MA, 01605, USA.
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13
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Jeong S, Cho S, Yang SK, Oh SA, Kang YK. Parallel shift of DNA methylation and gene expression toward the mean in mouse spleen with aging. Aging (Albany NY) 2023; 15:6690-6709. [PMID: 37494662 PMCID: PMC10415566 DOI: 10.18632/aging.204903] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2023] [Accepted: 07/06/2023] [Indexed: 07/28/2023]
Abstract
Age-associated DNA-methylation drift (AMD) manifests itself in two ways in mammals: global decrease (hypomethylation) and local increase of DNA methylation (hypermethylation). To comprehend the principle behind this bidirectional AMD, we studied methylation states of spatially clustered CpG dinucleotides in mouse splenic DNA using reduced-representation-bisulfite-sequencing (RRBS). The mean methylation levels of whole CpGs declined with age. Promoter-resident CpGs, generally weakly methylated (<5%) in young mice, became hypermethylated in old mice, whereas CpGs in gene-body and intergenic regions, initially moderately (~33%) and extensively (>80%) methylated, respectively, were hypomethylated in the old. Chromosome-wise analysis of methylation revealed that inter-individual heterogeneities increase with age. The density of nearby CpGs was used to classify individual CpGs, which found hypermethylation in CpG-rich regions and hypomethylation in CpG-poor regions. When genomic regions were grouped by methylation level, high-methylation regions tended to become hypomethylated whereas low-methylation regions tended to become hypermethylated, regardless of genomic structure/function. Data analysis revealed that while methylation level and CpG density were interdependent, methylation level was a better predictor of the AMD pattern representing a shift toward the mean. Further analysis of gene-expression data showed a decrease in the expression of highly-expressed genes and an increase in the expression of lowly-expressed genes with age. This shift towards the mean in gene-expression changes was correlated with that of methylation changes, indicating a potential link between the two age-associated changes. Our findings suggest that age-associated hyper- and hypomethylation events are stochastic and attributed to malfunctioning intrinsic mechanisms for methylation maintenance in low- and high-methylation regions, respectively.
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Affiliation(s)
- Sangkyun Jeong
- Medical Research Division, Korea Institute of Oriental Medicine (KIOM), Yuseong-gu, Daejeon 34054, South Korea
- Genomics Department, Keyomics Co. Ltd., Yuseong-gu, Daejeon 34013, South Korea
| | - Sunwha Cho
- Genomics Department, Keyomics Co. Ltd., Yuseong-gu, Daejeon 34013, South Korea
| | - Seung Kyoung Yang
- Genomics Department, Keyomics Co. Ltd., Yuseong-gu, Daejeon 34013, South Korea
| | - Soo A. Oh
- Medical Research Division, Korea Institute of Oriental Medicine (KIOM), Yuseong-gu, Daejeon 34054, South Korea
| | - Yong-Kook Kang
- Development and Differentiation Research Center, Aging Convergence Research Center (ACRC), Korea Research Institute of Bioscience Biotechnology (KRIBB), Yuseong-gu, Daejeon 34141, South Korea
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14
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Kim HS, Jang S, Kim J. Genome-Wide Integrative Transcriptional Profiling Identifies Age-Associated Signatures in Dogs. Genes (Basel) 2023; 14:1131. [PMID: 37372311 DOI: 10.3390/genes14061131] [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: 04/26/2023] [Revised: 05/19/2023] [Accepted: 05/22/2023] [Indexed: 06/29/2023] Open
Abstract
Mammals experience similar stages of embryonic development, birth, infancy, youth, adolescence, maturity, and senescence. While embryonic developmental processes have been extensively researched, many molecular mechanisms regulating the different life stages after birth, such as aging, remain unresolved. We investigated the conserved and global molecular transitions in transcriptional remodeling with age in dogs of 15 breeds, which revealed that genes underlying hormone level regulation and developmental programs were differentially regulated during aging. Subsequently, we show that the candidate genes associated with tumorigenesis also exhibit age-dependent DNA methylation patterns, which might have contributed to the tumor state through inhibiting the plasticity of cell differentiation processes during aging, and ultimately suggesting the molecular events that link the processes of aging and cancer. These results highlight that the rate of age-related transcriptional remodeling is influenced not only by the lifespan, but also by the timing of critical physiological milestones.
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Affiliation(s)
- Hyun Seung Kim
- Division of Applied Life Science (BK21 Four), Gyeongsang National University, Jinju 52828, Republic of Korea
- Institute of Agriculture and Life Sciences, Gyeongsang National University, Jinju 52828, Republic of Korea
| | - Subin Jang
- Division of Applied Life Science (BK21 Four), Gyeongsang National University, Jinju 52828, Republic of Korea
- Institute of Agriculture and Life Sciences, Gyeongsang National University, Jinju 52828, Republic of Korea
| | - Jaemin Kim
- Division of Applied Life Science (BK21 Four), Gyeongsang National University, Jinju 52828, Republic of Korea
- Institute of Agriculture and Life Sciences, Gyeongsang National University, Jinju 52828, Republic of Korea
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15
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Kaushik A, Chaudhary V, Longkumer I, Saraswathy KN, Jain S. Sex-specific variations in global DNA methylation levels with age: a population-based exploratory study from North India. Front Genet 2023; 14:1038529. [PMID: 37255712 PMCID: PMC10225692 DOI: 10.3389/fgene.2023.1038529] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2022] [Accepted: 05/03/2023] [Indexed: 06/01/2023] Open
Abstract
Purpose: Aging is one of the most important risk factors for a number of human diseases. Epigenetic alterations, including changes in DNA methylation patterns, have been reported to be one of the hallmarks of aging. Being a malleable process, the role of site-specific DNA methylation in aging is being extensively investigated; however, much less attention has been given to alterations in global DNA methylation with aging at the population level. The present study aims to explore overall and sex-specific variations in global DNA methylation patterns with age. Methods: A total of 1,127 adult individuals (792 females) aged 30-75 years belonging to Haryana, North India, were recruited. Socio-demographic data was collected using a pretested interview schedule. Global DNA methylation analysis, of peripheral blood leucocyte (PBL) DNA, was performed using the ELISA-based colorimetric technique. Results: Though the overall correlation analysis revealed a weak inverse trend between global DNA methylation and age, the adjusted regression model showed no significant association between global DNA methylation and age. In age-stratified analysis, global DNA methylation levels were found to be fairly stable until 60 years of age, followed by a decline in the above-60 age group. Further, no significant difference in DNA patterns methylation pattern was observed between males and females. Conclusion: Overall, the study suggests a lack of association between global DNA methylation and age, especially until 60 years of age, and a similar DNA methylation pattern between males and females with respect to age.
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Affiliation(s)
- Anshika Kaushik
- Laboratory of Molecular and Biochemical Anthropology, Department of Anthropology, University of Delhi, Delhi, India
| | - Vineet Chaudhary
- Laboratory of Molecular and Biochemical Anthropology, Department of Anthropology, University of Delhi, Delhi, India
| | - Imnameren Longkumer
- Laboratory of Molecular and Biochemical Anthropology, Department of Anthropology, University of Delhi, Delhi, India
| | | | - Sonal Jain
- Laboratory of Molecular and Biochemical Anthropology, Department of Anthropology, University of Delhi, Delhi, India
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16
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Bao H, Cao J, Chen M, Chen M, Chen W, Chen X, Chen Y, Chen Y, Chen Y, Chen Z, Chhetri JK, Ding Y, Feng J, Guo J, Guo M, He C, Jia Y, Jiang H, Jing Y, Li D, Li J, Li J, Liang Q, Liang R, Liu F, Liu X, Liu Z, Luo OJ, Lv J, Ma J, Mao K, Nie J, Qiao X, Sun X, Tang X, Wang J, Wang Q, Wang S, Wang X, Wang Y, Wang Y, Wu R, Xia K, Xiao FH, Xu L, Xu Y, Yan H, Yang L, Yang R, Yang Y, Ying Y, Zhang L, Zhang W, Zhang W, Zhang X, Zhang Z, Zhou M, Zhou R, Zhu Q, Zhu Z, Cao F, Cao Z, Chan P, Chen C, Chen G, Chen HZ, Chen J, Ci W, Ding BS, Ding Q, Gao F, Han JDJ, Huang K, Ju Z, Kong QP, Li J, Li J, Li X, Liu B, Liu F, Liu L, Liu Q, Liu Q, Liu X, Liu Y, Luo X, Ma S, Ma X, Mao Z, Nie J, Peng Y, Qu J, Ren J, Ren R, Song M, Songyang Z, Sun YE, Sun Y, Tian M, Wang S, Wang S, Wang X, Wang X, Wang YJ, Wang Y, Wong CCL, Xiang AP, Xiao Y, Xie Z, Xu D, Ye J, Yue R, Zhang C, Zhang H, Zhang L, Zhang W, Zhang Y, Zhang YW, Zhang Z, Zhao T, Zhao Y, Zhu D, Zou W, Pei G, Liu GH. Biomarkers of aging. SCIENCE CHINA. LIFE SCIENCES 2023; 66:893-1066. [PMID: 37076725 PMCID: PMC10115486 DOI: 10.1007/s11427-023-2305-0] [Citation(s) in RCA: 90] [Impact Index Per Article: 90.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/19/2023] [Accepted: 02/27/2023] [Indexed: 04/21/2023]
Abstract
Aging biomarkers are a combination of biological parameters to (i) assess age-related changes, (ii) track the physiological aging process, and (iii) predict the transition into a pathological status. Although a broad spectrum of aging biomarkers has been developed, their potential uses and limitations remain poorly characterized. An immediate goal of biomarkers is to help us answer the following three fundamental questions in aging research: How old are we? Why do we get old? And how can we age slower? This review aims to address this need. Here, we summarize our current knowledge of biomarkers developed for cellular, organ, and organismal levels of aging, comprising six pillars: physiological characteristics, medical imaging, histological features, cellular alterations, molecular changes, and secretory factors. To fulfill all these requisites, we propose that aging biomarkers should qualify for being specific, systemic, and clinically relevant.
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Affiliation(s)
- Hainan Bao
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing, 100101, China
| | - Jiani Cao
- State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China
| | - Mengting Chen
- Department of Dermatology, Xiangya Hospital, Central South University, Changsha, 410008, China
- Hunan Key Laboratory of Aging Biology, Xiangya Hospital, Central South University, Changsha, 410008, China
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, 410008, China
| | - Min Chen
- Clinic Center of Human Gene Research, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China
- Hubei Clinical Research Center of Metabolic and Cardiovascular Disease, Huazhong University of Science and Technology, Wuhan, 430022, China
- Hubei Key Laboratory of Metabolic Abnormalities and Vascular Aging, Huazhong University of Science and Technology, Wuhan, 430022, China
| | - Wei Chen
- Stem Cell Translational Research Center, Tongji Hospital, Tongji University School of Medicine, Shanghai, 200065, China
| | - Xiao Chen
- Department of Nuclear Medicine, Daping Hospital, Third Military Medical University, Chongqing, 400042, China
| | - Yanhao Chen
- CAS Key Laboratory of Nutrition, Metabolism and Food Safety, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, 200031, China
| | - Yu Chen
- Shanghai Key Laboratory of Maternal Fetal Medicine, Clinical and Translational Research Center of Shanghai First Maternity and Infant Hospital, Frontier Science Center for Stem Cell Research, Shanghai Key Laboratory of Signaling and Disease Research, School of Life Sciences and Technology, Tongji University, Shanghai, 200092, China
| | - Yutian Chen
- The Department of Endovascular Surgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, China
| | - Zhiyang Chen
- Key Laboratory of Regenerative Medicine of Ministry of Education, Institute of Ageing and Regenerative Medicine, Jinan University, Guangzhou, 510632, China
| | - Jagadish K Chhetri
- National Clinical Research Center for Geriatric Diseases, Xuanwu Hospital, Capital Medical University, Beijing, 100053, China
| | - Yingjie Ding
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing, 100101, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Junlin Feng
- CAS Key Laboratory of Tissue Microenvironment and Tumor, Shanghai Institute of Nutrition and Health, Chinese Academy of Sciences, Shanghai, 200031, China
| | - Jun Guo
- The Key Laboratory of Geriatrics, Beijing Institute of Geriatrics, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing Hospital/National Center of Gerontology of National Health Commission, Beijing, 100730, China
| | - Mengmeng Guo
- School of Pharmaceutical Sciences, Tsinghua University, Beijing, 100084, China
| | - Chuting He
- University of Chinese Academy of Sciences, Beijing, 100049, China
- State Key Laboratory of Membrane Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing, 100101, China
| | - Yujuan Jia
- Department of Neurology, First Affiliated Hospital, Shanxi Medical University, Taiyuan, 030001, China
| | - Haiping Jiang
- State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing, 100101, China
| | - Ying Jing
- Beijing Municipal Geriatric Medical Research Center, Xuanwu Hospital, Capital Medical University, Beijing, 100053, China
- Aging Translational Medicine Center, International Center for Aging and Cancer, Xuanwu Hospital, Capital Medical University, Beijing, 100053, China
- Advanced Innovation Center for Human Brain Protection, and National Clinical Research Center for Geriatric Disorders, Xuanwu Hospital Capital Medical University, Beijing, 100053, China
| | - Dingfeng Li
- Department of Neurology, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, 230036, China
| | - Jiaming Li
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing, 100101, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Jingyi Li
- University of Chinese Academy of Sciences, Beijing, 100049, China
- State Key Laboratory of Membrane Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing, 100101, China
| | - Qinhao Liang
- College of Life Sciences, TaiKang Center for Life and Medical Sciences, Wuhan University, Wuhan, 430072, China
| | - Rui Liang
- Research Institute of Transplant Medicine, Organ Transplant Center, NHC Key Laboratory for Critical Care Medicine, Tianjin First Central Hospital, Nankai University, Tianjin, 300384, China
| | - Feng Liu
- MOE Key Laboratory of Gene Function and Regulation, Guangzhou Key Laboratory of Healthy Aging Research, School of Life Sciences, Institute of Healthy Aging Research, Sun Yat-sen University, Guangzhou, 510275, China
| | - Xiaoqian Liu
- State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing, 100101, China
| | - Zuojun Liu
- School of Life Sciences, Hainan University, Haikou, 570228, China
| | - Oscar Junhong Luo
- Department of Systems Biomedical Sciences, School of Medicine, Jinan University, Guangzhou, 510632, China
| | - Jianwei Lv
- School of Life Sciences, Xiamen University, Xiamen, 361102, China
| | - Jingyi Ma
- The State Key Laboratory of Organ Failure Research, National Clinical Research Center of Kidney Disease, Division of Nephrology, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, China
| | - Kehang Mao
- Peking-Tsinghua Center for Life Sciences, Academy for Advanced Interdisciplinary Studies, Center for Quantitative Biology (CQB), Peking University, Beijing, 100871, China
| | - Jiawei Nie
- Shanghai Institute of Hematology, State Key Laboratory for Medical Genomics, National Research Center for Translational Medicine (Shanghai), International Center for Aging and Cancer, Collaborative Innovation Center of Hematology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
| | - Xinhua Qiao
- National Laboratory of Biomacromolecules, CAS Center for Excellence in Biomacromolecules, Institute of Biophysics, Chinese Academy of Sciences, Beijing, 100101, China
| | - Xinpei Sun
- Peking University International Cancer Institute, Health Science Center, Peking University, Beijing, 100101, China
| | - Xiaoqiang Tang
- Key Laboratory of Birth Defects and Related Diseases of Women and Children of MOE, State Key Laboratory of Biotherapy, West China Second University Hospital, Sichuan University, Chengdu, 610041, China
| | - Jianfang Wang
- Institute for Regenerative Medicine, Shanghai East Hospital, Frontier Science Center for Stem Cell Research, Shanghai Key Laboratory of Signaling and Disease Research, School of Life Sciences and Technology, Tongji University, Shanghai, 200092, China
| | - Qiaoran Wang
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing, 100101, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Siyuan Wang
- Clinical Research Institute, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Science & Peking Union Medical College, Beijing, 100730, China
| | - Xuan Wang
- Hepatobiliary and Pancreatic Center, Medical Research Center, Beijing Tsinghua Changgung Hospital, Beijing, 102218, China
| | - Yaning Wang
- Key Laboratory for Stem Cells and Tissue Engineering, Ministry of Education, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, 510080, China
- Advanced Medical Technology Center, The First Affiliated Hospital, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, 510080, China
| | - Yuhan Wang
- University of Chinese Academy of Sciences, Beijing, 100049, China
- State Key Laboratory of Membrane Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing, 100101, China
| | - Rimo Wu
- Bioland Laboratory (Guangzhou Regenerative Medicine and Health Guangdong Laboratory), Guangzhou, 510005, China
| | - Kai Xia
- Center for Stem Cell Biologyand Tissue Engineering, Key Laboratory for Stem Cells and Tissue Engineering, Ministry of Education, Sun Yat-sen University, Guangzhou, 510080, China
- National-Local Joint Engineering Research Center for Stem Cells and Regenerative Medicine, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, 510080, China
| | - Fu-Hui Xiao
- CAS Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming, 650223, China
- State Key Laboratory of Genetic Resources and Evolution, Key Laboratory of Healthy Aging Research of Yunnan Province, Kunming Key Laboratory of Healthy Aging Study, KIZ/CUHK Joint Laboratory of Bioresources and Molecular Research in Common Diseases, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650223, China
| | - Lingyan Xu
- Shanghai Key Laboratory of Regulatory Biology, Institute of Biomedical Sciences and School of Life Sciences, East China Normal University, Shanghai, 200241, China
| | - Yingying Xu
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing, 100101, China
| | - Haoteng Yan
- Beijing Municipal Geriatric Medical Research Center, Xuanwu Hospital, Capital Medical University, Beijing, 100053, China
- Aging Translational Medicine Center, International Center for Aging and Cancer, Xuanwu Hospital, Capital Medical University, Beijing, 100053, China
- Advanced Innovation Center for Human Brain Protection, and National Clinical Research Center for Geriatric Disorders, Xuanwu Hospital Capital Medical University, Beijing, 100053, China
| | - Liang Yang
- CAS Key Laboratory of Regenerative Biology, Joint School of Life Sciences, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou Medical University, Guangzhou, 510530, China
| | - Ruici Yang
- State Key Laboratory of Cell Biology, Shanghai Institute of Biochemistry and Cell Biology, Center for Excellence in Molecular Cell Science, Chinese Academy of Sciences, University of Chinese Academy of Sciences, Shanghai, 200031, China
| | - Yuanxin Yang
- Interdisciplinary Research Center on Biology and Chemistry, Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences, Shanghai, 201210, China
| | - Yilin Ying
- Department of Geriatrics, Medical Center on Aging of Shanghai Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
- International Laboratory in Hematology and Cancer, Shanghai Jiao Tong University School of Medicine/Ruijin Hospital, Shanghai, 200025, China
| | - Le Zhang
- Gerontology Center of Hubei Province, Wuhan, 430000, China
- Institute of Gerontology, Department of Geriatrics, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China
| | - Weiwei Zhang
- Department of Cardiology, The Second Medical Centre, Chinese PLA General Hospital, National Clinical Research Center for Geriatric Diseases, Beijing, 100853, China
| | - Wenwan Zhang
- CAS Key Laboratory of Tissue Microenvironment and Tumor, Shanghai Institute of Nutrition and Health, Chinese Academy of Sciences, Shanghai, 200031, China
| | - Xing Zhang
- Key Laboratory of Ministry of Education, School of Aerospace Medicine, Fourth Military Medical University, Xi'an, 710032, China
| | - Zhuo Zhang
- Optogenetics & Synthetic Biology Interdisciplinary Research Center, State Key Laboratory of Bioreactor Engineering, Shanghai Frontiers Science Center of Optogenetic Techniques for Cell Metabolism, School of Pharmacy, East China University of Science and Technology, Shanghai, 200237, China
- Research Unit of New Techniques for Live-cell Metabolic Imaging, Chinese Academy of Medical Sciences, Beijing, 100730, China
| | - Min Zhou
- Department of Endocrinology, Endocrinology Research Center, Xiangya Hospital of Central South University, Changsha, 410008, China
| | - Rui Zhou
- Department of Nuclear Medicine and PET Center, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, 310009, China
| | - Qingchen Zhu
- CAS Key Laboratory of Tissue Microenvironment and Tumor, Shanghai Institute of Nutrition and Health, Chinese Academy of Sciences, Shanghai, 200031, China
| | - Zhengmao Zhu
- Department of Genetics and Cell Biology, College of Life Science, Nankai University, Tianjin, 300071, China
- Haihe Laboratory of Cell Ecosystem, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin, 300020, China
| | - Feng Cao
- Department of Cardiology, The Second Medical Centre, Chinese PLA General Hospital, National Clinical Research Center for Geriatric Diseases, Beijing, 100853, China.
| | - Zhongwei Cao
- State Key Laboratory of Biotherapy, West China Second University Hospital, Sichuan University, Chengdu, 610041, China.
| | - Piu Chan
- National Clinical Research Center for Geriatric Diseases, Xuanwu Hospital, Capital Medical University, Beijing, 100053, China.
| | - Chang Chen
- National Laboratory of Biomacromolecules, CAS Center for Excellence in Biomacromolecules, Institute of Biophysics, Chinese Academy of Sciences, Beijing, 100101, China.
| | - Guobing Chen
- Department of Microbiology and Immunology, School of Medicine, Jinan University, Guangzhou, 510632, China.
- Guangdong-Hong Kong-Macau Great Bay Area Geroscience Joint Laboratory, Guangzhou, 510000, China.
| | - Hou-Zao Chen
- Department of Biochemistryand Molecular Biology, State Key Laboratory of Medical Molecular Biology, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100005, China.
| | - Jun Chen
- Peking University Research Center on Aging, Beijing Key Laboratory of Protein Posttranslational Modifications and Cell Function, Department of Biochemistry and Molecular Biology, Department of Integration of Chinese and Western Medicine, School of Basic Medical Science, Peking University, Beijing, 100191, China.
| | - Weimin Ci
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing, 100101, China.
| | - Bi-Sen Ding
- State Key Laboratory of Biotherapy, West China Second University Hospital, Sichuan University, Chengdu, 610041, China.
| | - Qiurong Ding
- CAS Key Laboratory of Nutrition, Metabolism and Food Safety, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, 200031, China.
| | - Feng Gao
- Key Laboratory of Ministry of Education, School of Aerospace Medicine, Fourth Military Medical University, Xi'an, 710032, China.
| | - Jing-Dong J Han
- Peking-Tsinghua Center for Life Sciences, Academy for Advanced Interdisciplinary Studies, Center for Quantitative Biology (CQB), Peking University, Beijing, 100871, China.
| | - Kai Huang
- Clinic Center of Human Gene Research, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China.
- Hubei Clinical Research Center of Metabolic and Cardiovascular Disease, Huazhong University of Science and Technology, Wuhan, 430022, China.
- Hubei Key Laboratory of Metabolic Abnormalities and Vascular Aging, Huazhong University of Science and Technology, Wuhan, 430022, China.
- Department of Cardiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China.
| | - Zhenyu Ju
- Key Laboratory of Regenerative Medicine of Ministry of Education, Institute of Ageing and Regenerative Medicine, Jinan University, Guangzhou, 510632, China.
| | - Qing-Peng Kong
- CAS Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming, 650223, China.
- State Key Laboratory of Genetic Resources and Evolution, Key Laboratory of Healthy Aging Research of Yunnan Province, Kunming Key Laboratory of Healthy Aging Study, KIZ/CUHK Joint Laboratory of Bioresources and Molecular Research in Common Diseases, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650223, China.
| | - Ji Li
- Department of Dermatology, Xiangya Hospital, Central South University, Changsha, 410008, China.
- Hunan Key Laboratory of Aging Biology, Xiangya Hospital, Central South University, Changsha, 410008, China.
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, 410008, China.
| | - Jian Li
- The Key Laboratory of Geriatrics, Beijing Institute of Geriatrics, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing Hospital/National Center of Gerontology of National Health Commission, Beijing, 100730, China.
| | - Xin Li
- State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China.
- University of Chinese Academy of Sciences, Beijing, 100049, China.
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China.
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing, 100101, China.
| | - Baohua Liu
- School of Basic Medical Sciences, Shenzhen University Medical School, Shenzhen, 518060, China.
| | - Feng Liu
- Metabolic Syndrome Research Center, The Second Xiangya Hospital, Central South Unversity, Changsha, 410011, China.
| | - Lin Liu
- Department of Genetics and Cell Biology, College of Life Science, Nankai University, Tianjin, 300071, China.
- Haihe Laboratory of Cell Ecosystem, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin, 300020, China.
- Institute of Translational Medicine, Tianjin Union Medical Center, Nankai University, Tianjin, 300000, China.
- State Key Laboratory of Medicinal Chemical Biology, Nankai University, Tianjin, 300350, China.
| | - Qiang Liu
- Department of Neurology, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, 230036, China.
| | - Qiang Liu
- Department of Neurology, Tianjin Neurological Institute, Tianjin Medical University General Hospital, Tianjin, 300052, China.
- Tianjin Institute of Immunology, Tianjin Medical University, Tianjin, 300070, China.
| | - Xingguo Liu
- CAS Key Laboratory of Regenerative Biology, Joint School of Life Sciences, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou Medical University, Guangzhou, 510530, China.
| | - Yong Liu
- College of Life Sciences, TaiKang Center for Life and Medical Sciences, Wuhan University, Wuhan, 430072, China.
| | - Xianghang Luo
- Department of Endocrinology, Endocrinology Research Center, Xiangya Hospital of Central South University, Changsha, 410008, China.
| | - Shuai Ma
- University of Chinese Academy of Sciences, Beijing, 100049, China.
- State Key Laboratory of Membrane Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China.
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China.
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing, 100101, China.
| | - Xinran Ma
- Shanghai Key Laboratory of Regulatory Biology, Institute of Biomedical Sciences and School of Life Sciences, East China Normal University, Shanghai, 200241, China.
| | - Zhiyong Mao
- Shanghai Key Laboratory of Maternal Fetal Medicine, Clinical and Translational Research Center of Shanghai First Maternity and Infant Hospital, Frontier Science Center for Stem Cell Research, Shanghai Key Laboratory of Signaling and Disease Research, School of Life Sciences and Technology, Tongji University, Shanghai, 200092, China.
| | - Jing Nie
- The State Key Laboratory of Organ Failure Research, National Clinical Research Center of Kidney Disease, Division of Nephrology, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, China.
| | - Yaojin Peng
- State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China.
- University of Chinese Academy of Sciences, Beijing, 100049, China.
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing, 100101, China.
| | - Jing Qu
- State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China.
- University of Chinese Academy of Sciences, Beijing, 100049, China.
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China.
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing, 100101, China.
| | - Jie Ren
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing, 100101, China.
- University of Chinese Academy of Sciences, Beijing, 100049, China.
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China.
| | - Ruibao Ren
- Shanghai Institute of Hematology, State Key Laboratory for Medical Genomics, National Research Center for Translational Medicine (Shanghai), International Center for Aging and Cancer, Collaborative Innovation Center of Hematology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China.
- International Center for Aging and Cancer, Hainan Medical University, Haikou, 571199, China.
| | - Moshi Song
- University of Chinese Academy of Sciences, Beijing, 100049, China.
- State Key Laboratory of Membrane Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China.
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China.
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing, 100101, China.
| | - Zhou Songyang
- MOE Key Laboratory of Gene Function and Regulation, Guangzhou Key Laboratory of Healthy Aging Research, School of Life Sciences, Institute of Healthy Aging Research, Sun Yat-sen University, Guangzhou, 510275, China.
- Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, 510120, China.
| | - Yi Eve Sun
- Stem Cell Translational Research Center, Tongji Hospital, Tongji University School of Medicine, Shanghai, 200065, China.
| | - Yu Sun
- CAS Key Laboratory of Tissue Microenvironment and Tumor, Shanghai Institute of Nutrition and Health, Chinese Academy of Sciences, Shanghai, 200031, China.
- Department of Medicine and VAPSHCS, University of Washington, Seattle, WA, 98195, USA.
| | - Mei Tian
- Human Phenome Institute, Fudan University, Shanghai, 201203, China.
| | - Shusen Wang
- Research Institute of Transplant Medicine, Organ Transplant Center, NHC Key Laboratory for Critical Care Medicine, Tianjin First Central Hospital, Nankai University, Tianjin, 300384, China.
| | - Si Wang
- Beijing Municipal Geriatric Medical Research Center, Xuanwu Hospital, Capital Medical University, Beijing, 100053, China.
- Aging Translational Medicine Center, International Center for Aging and Cancer, Xuanwu Hospital, Capital Medical University, Beijing, 100053, China.
- Advanced Innovation Center for Human Brain Protection, and National Clinical Research Center for Geriatric Disorders, Xuanwu Hospital Capital Medical University, Beijing, 100053, China.
| | - Xia Wang
- School of Pharmaceutical Sciences, Tsinghua University, Beijing, 100084, China.
| | - Xiaoning Wang
- Institute of Geriatrics, The second Medical Center, Beijing Key Laboratory of Aging and Geriatrics, National Clinical Research Center for Geriatric Diseases, Chinese PLA General Hospital, Beijing, 100853, China.
| | - Yan-Jiang Wang
- Department of Neurology and Center for Clinical Neuroscience, Daping Hospital, Third Military Medical University, Chongqing, 400042, China.
| | - Yunfang Wang
- Hepatobiliary and Pancreatic Center, Medical Research Center, Beijing Tsinghua Changgung Hospital, Beijing, 102218, China.
| | - Catherine C L Wong
- Clinical Research Institute, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Science & Peking Union Medical College, Beijing, 100730, China.
| | - Andy Peng Xiang
- Center for Stem Cell Biologyand Tissue Engineering, Key Laboratory for Stem Cells and Tissue Engineering, Ministry of Education, Sun Yat-sen University, Guangzhou, 510080, China.
- National-Local Joint Engineering Research Center for Stem Cells and Regenerative Medicine, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, 510080, China.
| | - Yichuan Xiao
- CAS Key Laboratory of Tissue Microenvironment and Tumor, Shanghai Institute of Nutrition and Health, Chinese Academy of Sciences, Shanghai, 200031, China.
| | - Zhengwei Xie
- Peking University International Cancer Institute, Health Science Center, Peking University, Beijing, 100101, China.
- Beijing & Qingdao Langu Pharmaceutical R&D Platform, Beijing Gigaceuticals Tech. Co. Ltd., Beijing, 100101, China.
| | - Daichao Xu
- Interdisciplinary Research Center on Biology and Chemistry, Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences, Shanghai, 201210, China.
| | - Jing Ye
- Department of Geriatrics, Medical Center on Aging of Shanghai Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China.
- International Laboratory in Hematology and Cancer, Shanghai Jiao Tong University School of Medicine/Ruijin Hospital, Shanghai, 200025, China.
| | - Rui Yue
- Institute for Regenerative Medicine, Shanghai East Hospital, Frontier Science Center for Stem Cell Research, Shanghai Key Laboratory of Signaling and Disease Research, School of Life Sciences and Technology, Tongji University, Shanghai, 200092, China.
| | - Cuntai Zhang
- Gerontology Center of Hubei Province, Wuhan, 430000, China.
- Institute of Gerontology, Department of Geriatrics, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China.
| | - Hongbo Zhang
- Key Laboratory for Stem Cells and Tissue Engineering, Ministry of Education, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, 510080, China.
- Advanced Medical Technology Center, The First Affiliated Hospital, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, 510080, China.
| | - Liang Zhang
- CAS Key Laboratory of Tissue Microenvironment and Tumor, Shanghai Institute of Nutrition and Health, Chinese Academy of Sciences, Shanghai, 200031, China.
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China.
| | - Weiqi Zhang
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing, 100101, China.
- University of Chinese Academy of Sciences, Beijing, 100049, China.
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China.
| | - Yong Zhang
- Bioland Laboratory (Guangzhou Regenerative Medicine and Health Guangdong Laboratory), Guangzhou, 510005, China.
- The State Key Laboratory of Medical Molecular Biology, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences and School of Basic Medicine, Peking Union Medical College, Beijing, 100005, China.
| | - Yun-Wu Zhang
- Fujian Provincial Key Laboratory of Neurodegenerative Disease and Aging Research, Institute of Neuroscience, School of Medicine, Xiamen University, Xiamen, 361102, China.
| | - Zhuohua Zhang
- Key Laboratory of Molecular Precision Medicine of Hunan Province and Center for Medical Genetics, Institute of Molecular Precision Medicine, Xiangya Hospital, Central South University, Changsha, 410078, China.
- Department of Neurosciences, Hengyang Medical School, University of South China, Hengyang, 421001, China.
| | - Tongbiao Zhao
- State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China.
- University of Chinese Academy of Sciences, Beijing, 100049, China.
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China.
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing, 100101, China.
| | - Yuzheng Zhao
- Optogenetics & Synthetic Biology Interdisciplinary Research Center, State Key Laboratory of Bioreactor Engineering, Shanghai Frontiers Science Center of Optogenetic Techniques for Cell Metabolism, School of Pharmacy, East China University of Science and Technology, Shanghai, 200237, China.
- Research Unit of New Techniques for Live-cell Metabolic Imaging, Chinese Academy of Medical Sciences, Beijing, 100730, China.
| | - Dahai Zhu
- Bioland Laboratory (Guangzhou Regenerative Medicine and Health Guangdong Laboratory), Guangzhou, 510005, China.
- The State Key Laboratory of Medical Molecular Biology, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences and School of Basic Medicine, Peking Union Medical College, Beijing, 100005, China.
| | - Weiguo Zou
- State Key Laboratory of Cell Biology, Shanghai Institute of Biochemistry and Cell Biology, Center for Excellence in Molecular Cell Science, Chinese Academy of Sciences, University of Chinese Academy of Sciences, Shanghai, 200031, China.
| | - Gang Pei
- Shanghai Key Laboratory of Signaling and Disease Research, Laboratory of Receptor-Based Biomedicine, The Collaborative Innovation Center for Brain Science, School of Life Sciences and Technology, Tongji University, Shanghai, 200070, China.
| | - Guang-Hui Liu
- University of Chinese Academy of Sciences, Beijing, 100049, China.
- State Key Laboratory of Membrane Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China.
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China.
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing, 100101, China.
- Advanced Innovation Center for Human Brain Protection, and National Clinical Research Center for Geriatric Disorders, Xuanwu Hospital Capital Medical University, Beijing, 100053, China.
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17
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Copley KE, Shorter J. Repetitive elements in aging and neurodegeneration. Trends Genet 2023; 39:381-400. [PMID: 36935218 PMCID: PMC10121923 DOI: 10.1016/j.tig.2023.02.008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2022] [Revised: 02/12/2023] [Accepted: 02/14/2023] [Indexed: 03/19/2023]
Abstract
Repetitive elements (REs), such as transposable elements (TEs) and satellites, comprise much of the genome. Here, we review how TEs and (peri)centromeric satellite DNA may contribute to aging and neurodegenerative disorders, including amyotrophic lateral sclerosis (ALS). Alterations in RE expression, retrotransposition, and chromatin microenvironment may shorten lifespan, elicit neurodegeneration, and impair memory and movement. REs may cause these phenotypes via DNA damage, protein sequestration, insertional mutagenesis, and inflammation. We discuss several TE families, including gypsy, HERV-K, and HERV-W, and how TEs interact with various factors, including transactive response (TAR) DNA-binding protein 43 kDa (TDP-43) and the siRNA and piwi-interacting (pi)RNA systems. Studies of TEs in neurodegeneration have focused on Drosophila and, thus, further examination in mammals is needed. We suggest that therapeutic silencing of REs could help mitigate neurodegenerative disorders.
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Affiliation(s)
- Katie E Copley
- Department of Biochemistry and Biophysics, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA 19104, USA; Neuroscience Graduate Group, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA 19104, USA
| | - James Shorter
- Department of Biochemistry and Biophysics, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA 19104, USA; Neuroscience Graduate Group, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA 19104, USA.
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18
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Abstract
Epigenetic alterations during ageing are manifested with altered gene expression linking it to lifespan regulation, genetic instability, and diseases. Diet and epigenetic modifiers exert a profound effect on the lifespan of an organism by modulating the epigenetic marks. However, our understanding of the multifactorial nature of the epigenetic process during ageing and the onset of disease conditions as well as its reversal by epidrugs, diet, or environmental factors is still mystifying. This review covers the key findings in epigenetics related to ageing and age-related diseases. Further, it holds a discussion about the epigenetic clocks and their implications in various age-related disease conditions including cancer. Although, epigenetics is a reversible process how fast the epigenetic alterations can revert to normal is an intriguing question. Therefore, this paper touches on the possibility of utilizing nutrition and MSCs secretome to accelerate the epigenetic reversal and emphasizes the identification of new therapeutic epigenetic modifiers to counter epigenetic alteration during ageing.
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Affiliation(s)
- Shikha Sharma
- Institute for Stem Cell Science and Regenerative Medicine, 429164, Bangalore, India;
| | - Ramesh Bhonde
- Dr D Y Patil Vidyapeeth University, 121766, Pune, Maharashtra, India;
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19
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Hill C, Duffy S, Coulter T, Maxwell AP, McKnight AJ. Harnessing Genomic Analysis to Explore the Role of Telomeres in the Pathogenesis and Progression of Diabetic Kidney Disease. Genes (Basel) 2023; 14:609. [PMID: 36980881 PMCID: PMC10048490 DOI: 10.3390/genes14030609] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2023] [Revised: 02/20/2023] [Accepted: 02/21/2023] [Indexed: 03/06/2023] Open
Abstract
The prevalence of diabetes is increasing globally, and this trend is predicted to continue for future decades. Research is needed to uncover new ways to manage diabetes and its co-morbidities. A significant secondary complication of diabetes is kidney disease, which can ultimately result in the need for renal replacement therapy, via dialysis or transplantation. Diabetic kidney disease presents a substantial burden to patients, their families and global healthcare services. This review highlights studies that have harnessed genomic, epigenomic and functional prediction tools to uncover novel genes and pathways associated with DKD that are useful for the identification of therapeutic targets or novel biomarkers for risk stratification. Telomere length regulation is a specific pathway gaining attention recently because of its association with DKD. Researchers are employing both observational and genetics-based studies to identify telomere-related genes associated with kidney function decline in diabetes. Studies have also uncovered novel functions for telomere-related genes beyond the immediate regulation of telomere length, such as transcriptional regulation and inflammation. This review summarises studies that have revealed the potential to harness therapeutics that modulate telomere length, or the associated epigenetic modifications, for the treatment of DKD, to potentially slow renal function decline and reduce the global burden of this disease.
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Affiliation(s)
- Claire Hill
- Centre for Public Health, Queen’s University of Belfast, Belfast BT12 6BA, UK
| | - Seamus Duffy
- Centre for Public Health, Queen’s University of Belfast, Belfast BT12 6BA, UK
| | - Tiernan Coulter
- Centre for Public Health, Queen’s University of Belfast, Belfast BT12 6BA, UK
| | - Alexander Peter Maxwell
- Centre for Public Health, Queen’s University of Belfast, Belfast BT12 6BA, UK
- 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
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20
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Costa MR, Dos Santos AYI, de Miranda TB, Aires R, de Camargo Coque A, Hurtado ECP, Bernardi MM, Pecorari VGA, Andia DC, Birbrair A, Guillemin GJ, Latini A, da Silva RA. Impact of neuroinflammation on epigenetic transcriptional control of Sonic Hedgehog members in the central nervous system. Brain Res 2023; 1799:148180. [PMID: 36463954 DOI: 10.1016/j.brainres.2022.148180] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2022] [Revised: 09/14/2022] [Accepted: 11/23/2022] [Indexed: 12/03/2022]
Abstract
Sonic Hedgehog (Shh) signaling plays a critical role during central nervous system (CNS) development, and its dysregulation leads to neurological disorders. Nevertheless, little is known about Shh signaling regulation in the adult brain. Here, we investigated the contribution of DNA methylation on the transcriptional control of Shh signaling pathway members and its basal distribution impact on the brain, as well as its modulation by inflammation. The methylation status of the promoter regions of these members and the transcriptional profile of DNA-modifying enzymes (DNA Methyltransferases - DNMTs and Tet Methylcytosine Dioxygenase - TETs) were investigated in a murine model of neuroinflammation by qPCR. We showed that, in the adult brain, methylation in the CpG promoter regions of the Shh signaling pathway members was critical to determine the endogenous differential transcriptional pattern observed between distinct brain regions. We also found that neuroinflammation differentially modulates gene expression of DNA-modifying enzymes. This study reveals the basal transcriptional profile of DNMTs and TETs enzymes in the CNS and demonstrates the effect of neuroinflammation on the transcriptional control of members of the Shh Signaling pathway in the adult brain.
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Affiliation(s)
| | | | | | - Rogério Aires
- Epigenetic Study Center and Gene Regulation - CEEpiRG, Program in Environmental and Experimental Pathology, Paulista University, São Paulo 04026-002, São Paulo, Brazil
| | - Alex de Camargo Coque
- Epigenetic Study Center and Gene Regulation - CEEpiRG, Program in Environmental and Experimental Pathology, Paulista University, São Paulo 04026-002, São Paulo, Brazil
| | - Elizabeth Cristina Perez Hurtado
- Epigenetic Study Center and Gene Regulation - CEEpiRG, Program in Environmental and Experimental Pathology, Paulista University, São Paulo 04026-002, São Paulo, Brazil.
| | - Maria Martha Bernardi
- Epigenetic Study Center and Gene Regulation - CEEpiRG, Program in Environmental and Experimental Pathology, Paulista University, São Paulo 04026-002, São Paulo, Brazil
| | | | - Denise Carleto Andia
- School of Dentistry, Health Science Institute, Paulista University, São Paulo 04026-002, São Paulo, Brazil.
| | - Alexander Birbrair
- Department of Pathology, Federal University of Minas Gerais, Belo Horizonte, MG, Brazil
| | - Gilles J Guillemin
- Neuroinflammation Group, Faculty of Medicine, Health and Human Sciences, Macquarie University, Sydney, NSW 2109, Australia.
| | - Alexandra Latini
- Bioenergetics and Oxidative Stress Lab - LABOX, Department of Biochemistry, Center for Biological Sciences, Federal University of Santa Catarina, Florianopolis, Brazil
| | - Rodrigo A da Silva
- School of Dentistry, University of Taubaté, 12020-3400 Taubaté, São Paulo, Brazil; Epigenetic Study Center and Gene Regulation - CEEpiRG, Program in Environmental and Experimental Pathology, Paulista University, São Paulo 04026-002, São Paulo, Brazil.
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21
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Yazar V, Dawson VL, Dawson TM, Kang SU. DNA Methylation Signature of Aging: Potential Impact on the Pathogenesis of Parkinson's Disease. JOURNAL OF PARKINSON'S DISEASE 2023; 13:145-164. [PMID: 36710687 PMCID: PMC10041453 DOI: 10.3233/jpd-223517] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/25/2023]
Abstract
Regulation of gene expression by epigenetic modifications means lasting and heritable changes in the function of genes without alterations in the DNA sequence. Of all epigenetic mechanisms identified thus far, DNA methylation has been of particular interest in both aging and age-related disease research over the last decade given the consistency of site-specific DNA methylation changes during aging that can predict future health and lifespan. An increasing line of evidence has implied the dynamic nature of DNA (de)methylation events that occur throughout the lifespan has a role in the pathophysiology of aging and age-associated neurodegenerative conditions, including Parkinson's disease (PD). In this regard, PD methylome shows, to some extent, similar genome-wide changes observed in the methylome of healthy individuals of matching age. In this review, we start by providing a brief overview of studies outlining global patterns of DNA methylation, then its mechanisms and regulation, within the context of aging and PD. Considering diverging lines of evidence from different experimental and animal models of neurodegeneration and how they combine to shape our current understanding of tissue-specific changes in DNA methylome in health and disease, we report a high-level comparison of the genomic methylation landscapes of brain, with an emphasis on dopaminergic neurons in PD and in natural aging. We believe this will be particularly useful for systematically dissecting overlapping genome-wide alterations in DNA methylation during PD and healthy aging, and for improving our knowledge of PD-specific changes in methylation patterns independent of aging process.
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Affiliation(s)
- Volkan Yazar
- Neuroregeneration and Stem Cell Programs, Institute for Cell Engineering, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Valina L Dawson
- Neuroregeneration and Stem Cell Programs, Institute for Cell Engineering, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Solomon H. Snyder Department of Neuroscience, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Department of Physiology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Adrienne Helis Malvin Medical Research Foundation, New Orleans, LA, USA
- Diana Helis Henry Medical Research Foundation, New Orleans, LA, USA
| | - Ted M Dawson
- Neuroregeneration and Stem Cell Programs, Institute for Cell Engineering, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Solomon H. Snyder Department of Neuroscience, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Department of Pharmacology and and Molecular Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Adrienne Helis Malvin Medical Research Foundation, New Orleans, LA, USA
- Diana Helis Henry Medical Research Foundation, New Orleans, LA, USA
| | - Sung-Ung Kang
- Neuroregeneration and Stem Cell Programs, Institute for Cell Engineering, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Solomon H. Snyder Department of Neuroscience, Johns Hopkins University School of Medicine, Baltimore, MD, USA
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22
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Wang K, Liu H, Hu Q, Wang L, Liu J, Zheng Z, Zhang W, Ren J, Zhu F, Liu GH. Epigenetic regulation of aging: implications for interventions of aging and diseases. Signal Transduct Target Ther 2022; 7:374. [PMID: 36336680 PMCID: PMC9637765 DOI: 10.1038/s41392-022-01211-8] [Citation(s) in RCA: 137] [Impact Index Per Article: 68.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2022] [Revised: 09/14/2022] [Accepted: 09/28/2022] [Indexed: 11/09/2022] Open
Abstract
Aging is accompanied by the decline of organismal functions and a series of prominent hallmarks, including genetic and epigenetic alterations. These aging-associated epigenetic changes include DNA methylation, histone modification, chromatin remodeling, non-coding RNA (ncRNA) regulation, and RNA modification, all of which participate in the regulation of the aging process, and hence contribute to aging-related diseases. Therefore, understanding the epigenetic mechanisms in aging will provide new avenues to develop strategies to delay aging. Indeed, aging interventions based on manipulating epigenetic mechanisms have led to the alleviation of aging or the extension of the lifespan in animal models. Small molecule-based therapies and reprogramming strategies that enable epigenetic rejuvenation have been developed for ameliorating or reversing aging-related conditions. In addition, adopting health-promoting activities, such as caloric restriction, exercise, and calibrating circadian rhythm, has been demonstrated to delay aging. Furthermore, various clinical trials for aging intervention are ongoing, providing more evidence of the safety and efficacy of these therapies. Here, we review recent work on the epigenetic regulation of aging and outline the advances in intervention strategies for aging and age-associated diseases. A better understanding of the critical roles of epigenetics in the aging process will lead to more clinical advances in the prevention of human aging and therapy of aging-related diseases.
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Affiliation(s)
- Kang Wang
- State Key Laboratory of Membrane Biology, Institute of Zoology, Chinese Academy of Sciences, 100101, Beijing, China
- State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, 100101, Beijing, China
- University of Chinese Academy of Sciences, 100049, Beijing, China
| | - Huicong Liu
- School of Biomedical Engineering, Shanghai Jiao Tong University, 200030, Shanghai, China
| | - Qinchao Hu
- State Key Laboratory of Membrane Biology, Institute of Zoology, Chinese Academy of Sciences, 100101, Beijing, China
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, 100101, Beijing, China
- Hospital of Stomatology, Sun Yat-sen University, 510060, Guangzhou, China
- Guangdong Provincial Key Laboratory of Stomatology, Guanghua School of Stomatology, Sun Yat-sen University, 510060, Guangzhou, China
| | - Lingna Wang
- School of Biomedical Engineering, Shanghai Jiao Tong University, 200030, Shanghai, China
| | - Jiaqing Liu
- School of Biomedical Engineering, Shanghai Jiao Tong University, 200030, Shanghai, China
| | - Zikai Zheng
- University of Chinese Academy of Sciences, 100049, Beijing, China
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, 100101, Beijing, China
| | - Weiqi Zhang
- University of Chinese Academy of Sciences, 100049, Beijing, China
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, 100101, Beijing, China
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, 100101, Beijing, China
| | - Jie Ren
- University of Chinese Academy of Sciences, 100049, Beijing, China.
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, 100101, Beijing, China.
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, 100101, Beijing, China.
| | - Fangfang Zhu
- School of Biomedical Engineering, Shanghai Jiao Tong University, 200030, Shanghai, China.
| | - Guang-Hui Liu
- State Key Laboratory of Membrane Biology, Institute of Zoology, Chinese Academy of Sciences, 100101, Beijing, China.
- University of Chinese Academy of Sciences, 100049, Beijing, China.
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, 100101, Beijing, China.
- Advanced Innovation Center for Human Brain Protection, National Clinical Research Center for Geriatric Disorders, Xuanwu Hospital, Capital Medical University, 100053, Beijing, China.
- Beijing Institute for Stem Cell and Regenerative Medicine, 100101, Beijing, China.
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23
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Pérez RF, Tejedor JR, Fernández AF, Fraga MF. Aging and cancer epigenetics: Where do the paths fork? Aging Cell 2022; 21:e13709. [PMID: 36103298 PMCID: PMC9577950 DOI: 10.1111/acel.13709] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2022] [Accepted: 08/29/2022] [Indexed: 01/25/2023] Open
Abstract
Aging and cancer are clearly associated processes, at both the epidemiological and molecular level. Epigenetic mechanisms are good candidates to explain the molecular links between the two phenomena, but recent reports have also revealed considerable differences, particularly regarding the loss of DNA methylation in the two processes. The large-scale generation and availability of genome-wide epigenetic data now permits systematic studies to be undertaken which may help clarify the similarities and differences between aging and cancer epigenetic alterations. In addition, the development of epigenetic clocks provides a new dimension in which to investigate diseases at the molecular level. Here, we examine current and future questions about the roles of DNA methylation mechanisms as causal factors in the processes of aging and cancer so that we may better understand if and how aging-associated epigenetic alterations lead to tumorigenesis. It seems certain that comprehending the molecular mechanisms underlying epigenetic clocks, especially with regard to somatic stem cell aging, combined with applying single-cell epigenetic-age profiling technologies to aging and cancer cohorts, and the integration of existing and upcoming epigenetic evidence within the genetic damage models of aging will prove to be crucial to improving understanding of these two interrelated phenomena.
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Affiliation(s)
- Raúl Fernández Pérez
- Cancer Epigenetics and Nanomedicine LaboratoryNanomaterials and Nanotechnology Research Center (CINN‐CSIC)El EntregoSpain
- Health Research Institute of Asturias (ISPA‐FINBA)Institute of Oncology of Asturias (IUOPA) and Department of Organisms and Systems Biology (BOS)University of OviedoOviedoSpain
- Rare Diseases CIBER (CIBERER)Carlos III Health Institute (ISCIII)MadridSpain
| | - Juan Ramón Tejedor
- Cancer Epigenetics and Nanomedicine LaboratoryNanomaterials and Nanotechnology Research Center (CINN‐CSIC)El EntregoSpain
- Health Research Institute of Asturias (ISPA‐FINBA)Institute of Oncology of Asturias (IUOPA) and Department of Organisms and Systems Biology (BOS)University of OviedoOviedoSpain
- Rare Diseases CIBER (CIBERER)Carlos III Health Institute (ISCIII)MadridSpain
| | - Agustín Fernández Fernández
- Cancer Epigenetics and Nanomedicine LaboratoryNanomaterials and Nanotechnology Research Center (CINN‐CSIC)El EntregoSpain
- Health Research Institute of Asturias (ISPA‐FINBA)Institute of Oncology of Asturias (IUOPA) and Department of Organisms and Systems Biology (BOS)University of OviedoOviedoSpain
- Rare Diseases CIBER (CIBERER)Carlos III Health Institute (ISCIII)MadridSpain
| | - Mario Fernández Fraga
- Cancer Epigenetics and Nanomedicine LaboratoryNanomaterials and Nanotechnology Research Center (CINN‐CSIC)El EntregoSpain
- Health Research Institute of Asturias (ISPA‐FINBA)Institute of Oncology of Asturias (IUOPA) and Department of Organisms and Systems Biology (BOS)University of OviedoOviedoSpain
- Rare Diseases CIBER (CIBERER)Carlos III Health Institute (ISCIII)MadridSpain
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24
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Svoboda LK, Perera BPU, Morgan RK, Polemi KM, Pan J, Dolinoy DC. Toxicoepigenetics and Environmental Health: Challenges and Opportunities. Chem Res Toxicol 2022; 35:1293-1311. [PMID: 35876266 PMCID: PMC9812000 DOI: 10.1021/acs.chemrestox.1c00445] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/07/2023]
Abstract
The rapidly growing field of toxicoepigenetics seeks to understand how toxicant exposures interact with the epigenome to influence disease risk. Toxicoepigenetics is a promising field of environmental health research, as integrating epigenetics into the field of toxicology will enable a more thorough evaluation of toxicant-induced disease mechanisms as well as the elucidation of the role of the epigenome as a biomarker of exposure and disease and possible mediator of exposure effects. Likewise, toxicoepigenetics will enhance our knowledge of how environmental exposures, lifestyle factors, and diet interact to influence health. Ultimately, an understanding of how the environment impacts the epigenome to cause disease may inform risk assessment, permit noninvasive biomonitoring, and provide potential opportunities for therapeutic intervention. However, the translation of research from this exciting field into benefits for human and animal health presents several challenges and opportunities. Here, we describe four significant areas in which we see opportunity to transform the field and improve human health by reducing the disease burden caused by environmental exposures. These include (1) research into the mechanistic role for epigenetic change in environment-induced disease, (2) understanding key factors influencing vulnerability to the adverse effects of environmental exposures, (3) identifying appropriate biomarkers of environmental exposures and their associated diseases, and (4) determining whether the adverse effects of environment on the epigenome and human health are reversible through pharmacologic, dietary, or behavioral interventions. We then highlight several initiatives currently underway to address these challenges.
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Affiliation(s)
- Laurie K Svoboda
- Department of Environmental Health Sciences, School of Public Health, University of Michigan, Ann Arbor, Michigan 48109, United States
| | - Bambarendage P U Perera
- Department of Environmental Health Sciences, School of Public Health, University of Michigan, Ann Arbor, Michigan 48109, United States
| | - Rachel K Morgan
- Department of Environmental Health Sciences, School of Public Health, University of Michigan, Ann Arbor, Michigan 48109, United States
| | - Katelyn M Polemi
- Department of Environmental Health Sciences, School of Public Health, University of Michigan, Ann Arbor, Michigan 48109, United States
| | - Junru Pan
- Department Nutritional Sciences, School of Public Health, University of Michigan, Ann Arbor, Michigan 48109, United States
| | - Dana C Dolinoy
- Department of Environmental Health Sciences, School of Public Health, University of Michigan, Ann Arbor, Michigan 48109, United States
- Department Nutritional Sciences, School of Public Health, University of Michigan, Ann Arbor, Michigan 48109, United States
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Osburn SC, Mesquita P, Neal FK, Rumbley M, Holmes MT, Ruple BA, Mobley CB, Brown MD, McCullough DJ, Kavazis AN, Roberts MD. Long-term voluntary wheel running effects on markers of Long Interspersed Nuclear Element-1 in skeletal muscle, liver, and brain tissue of female rats. Am J Physiol Cell Physiol 2022; 323:C907-C919. [PMID: 35938680 DOI: 10.1152/ajpcell.00234.2022] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022]
Abstract
We sought to determine the effects of long-term voluntary wheel running on markers of Long Interspersed Nuclear Element-1 (L1) in skeletal muscle, liver, and the hippocampus of female rats. Additionally, markers of the cGAS-STING DNA sensing pathway that results in inflammation were interrogated. Female Lewis rats (n=34) were separated into one of three groups including a 6-month-old group to serve as a young comparator group (CTL, n=10), a group that had access to a running wheel for voluntary wheel running (EX, n=12), and an age-matched group that did not (SED, n=12). Both SED and EX groups were carried out from 6 months to 15 months of age. There were no significant differences in L1 mRNA expression for any of the tissues between groups. Methylation of the L1 promoter in the soleus and hippocampus was significantly higher in SED and EX compared to CTL (p<0.05). ORF1p expression was higher in older SED and EX rats compared to CTL for every tissue (p<0.05). There were no differences between groups for L1 mRNA or cGAS-STING pathway markers. Our results suggest there is an increased ORF1 protein expression across tissues with aging that is not mitigated by voluntary wheel running. Additionally, while previous data imply that L1 methylation changes may play a role in acute exercise for L1 RNA expression, this does not seem to occur during extended periods of voluntary wheel running.
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Affiliation(s)
- Shelby C Osburn
- School of Kinesiology, Auburn University, Auburn, AL, United States
| | - Paulo Mesquita
- School of Kinesiology, Auburn University, Auburn, AL, United States
| | - Frances K Neal
- School of Kinesiology, Auburn University, Auburn, AL, United States
| | - Melissa Rumbley
- School of Kinesiology, Auburn University, Auburn, AL, United States
| | - Matthew T Holmes
- School of Kinesiology, Auburn University, Auburn, AL, United States
| | - Bradley A Ruple
- School of Kinesiology, Auburn University, Auburn, AL, United States
| | - C Brooks Mobley
- School of Kinesiology, Auburn University, Auburn, AL, United States
| | - Michael D Brown
- School of Public Health, University of Maryland, College Park, MD, United States
| | - Danielle J McCullough
- School of Kinesiology, Auburn University, Auburn, AL, United States.,Edward Via College of Osteopathic Medicine, Auburn, AL, United States
| | | | - Michael D Roberts
- School of Kinesiology, Auburn University, Auburn, AL, United States.,Edward Via College of Osteopathic Medicine, Auburn, AL, United States
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26
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Baker EC, Earnhardt AL, Cilkiz KZ, Collins HC, Littlejohn BP, Cardoso RC, Ghaffari N, Long CR, Riggs PK, Randel RD, Welsh TH, Riley DG. DNA methylation patterns and gene expression from amygdala tissue of mature Brahman cows exposed to prenatal stress. Front Genet 2022; 13:949309. [PMID: 35991551 PMCID: PMC9389044 DOI: 10.3389/fgene.2022.949309] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2022] [Accepted: 06/30/2022] [Indexed: 11/23/2022] Open
Abstract
Prenatal stress can alter postnatal performance and temperament of cattle. These phenotypic effects may result from changes in gene expression caused by stress-induced epigenetic alterations. Specifically, shifts in gene expression caused by DNA methylation within the brain’s amygdala can result in altered behavior because it regulates fear, stress response and aggression in mammals Thus, the objective of this experiment was to identify DNA methylation and gene expression differences in the amygdala tissue of 5-year-old prenatally stressed (PNS) Brahman cows compared to control cows. Pregnant Brahman cows (n = 48) were transported for 2-h periods at 60 ± 5, 80 ± 5, 100 ± 5, 120 ± 5, and 140 ± 5 days of gestation. A non-transported group (n = 48) were controls (Control). Amygdala tissue was harvested from 6 PNS and 8 Control cows at 5 years of age. Overall methylation of gene body regions, promoter regions, and cytosine-phosphate-guanine (CpG) islands were compared between the two groups. In total, 202 genes, 134 promoter regions, and 133 CpG islands exhibited differential methylation (FDR ≤ 0.15). Following comparison of gene expression in the amygdala between the PNS and Control cows, 2 differentially expressed genes were identified (FDR ≤ 0.15). The minimal differences observed could be the result of natural changes of DNA methylation and gene expression as an animal ages, or because this degree of transportation stress was not severe enough to cause lasting effects on the offspring. A younger age may be a more appropriate time to assess methylation and gene expression differences produced by prenatal stress.
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Affiliation(s)
- Emilie C. Baker
- Department of Animal Science, Texas A&M University, College Station, TX, United States
| | - Audrey L. Earnhardt
- Department of Animal Science, Texas A&M University, College Station, TX, United States
- Texas A&M AgriLife Research, College Station, TX, United States
- Texas A&M AgriLife Research, Overton, TX, United States
| | - Kubra Z. Cilkiz
- Department of Animal Science, Texas A&M University, College Station, TX, United States
| | - Haley C. Collins
- Department of Animal Science, Texas A&M University, College Station, TX, United States
| | - Brittni P. Littlejohn
- Department of Animal Science, Texas A&M University, College Station, TX, United States
- Texas A&M AgriLife Research, Overton, TX, United States
| | - Rodolfo C. Cardoso
- Department of Animal Science, Texas A&M University, College Station, TX, United States
| | - Noushin Ghaffari
- Department of Computer Science, Prairie View A&M University, Prairie View, TX, United States
| | - Charles R. Long
- Department of Animal Science, Texas A&M University, College Station, TX, United States
- Texas A&M AgriLife Research, Overton, TX, United States
| | - Penny K. Riggs
- Department of Animal Science, Texas A&M University, College Station, TX, United States
| | - Ronald D. Randel
- Department of Animal Science, Texas A&M University, College Station, TX, United States
- Texas A&M AgriLife Research, Overton, TX, United States
| | - Thomas H. Welsh
- Department of Animal Science, Texas A&M University, College Station, TX, United States
- Texas A&M AgriLife Research, College Station, TX, United States
| | - David G. Riley
- Department of Animal Science, Texas A&M University, College Station, TX, United States
- *Correspondence: David G. Riley,
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Beal AP, Hackerott S, Feldheim K, Gruber SH, Eirin‐Lopez JM. Age group DNA methylation differences in lemon sharks ( Negaprion brevirostris): Implications for future age estimation tools. Ecol Evol 2022; 12:e9226. [PMID: 36052296 PMCID: PMC9425014 DOI: 10.1002/ece3.9226] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2022] [Revised: 07/05/2022] [Accepted: 07/05/2022] [Indexed: 11/11/2022] Open
Abstract
Age information is often non-existent for most shark populations due to a lack of measurable physiological and morphological traits that can be used to estimate age. Recently, epigenetic clocks have been found to accurately estimate age for mammals, birds, and fish. However, since these clocks rely, among other things, on the availability of reference genomes, their application is hampered in non-traditional model organisms lacking such molecular resources. The technique known as Methyl-Sensitive Amplified Polymorphism (MSAP) has emerged as a valid alternative for studying DNA methylation biomarkers when reference genome information is missing, and large numbers of samples need to be processed. Accordingly, the MSAP technique was used in the present study to characterize global DNA methylation patterns in lemon sharks from three different age groups (juveniles, subadults, and adults). The obtained results reveal that, while MSAP analyses lack enough resolution as a standalone approach to infer age in these organisms, the global DNA methylation patterns observed using this technique displayed significant differences between age groups. Overall, these results confer that DNA methylation does change with age in sharks like what has been seen for other vertebrates and that MSAP could be useful as part of an epigenetics pipeline to infer the broad range of ages found in large samples sizes.
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Affiliation(s)
- Andria Paige Beal
- Environmental Epigenetics Laboratory, Institute of EnvironmentFlorida International UniversityMiamiFloridaUSA
| | - Serena Hackerott
- Environmental Epigenetics Laboratory, Institute of EnvironmentFlorida International UniversityMiamiFloridaUSA
| | - Kevin Feldheim
- Pritzker Laboratory for Molecular Systematics and EvolutionField Museum of Natural HistoryChicagoIllinoisUSA
| | | | - Jose M. Eirin‐Lopez
- Environmental Epigenetics Laboratory, Institute of EnvironmentFlorida International UniversityMiamiFloridaUSA
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28
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Pharmacological Approaches to Decelerate Aging: A Promising Path. OXIDATIVE MEDICINE AND CELLULAR LONGEVITY 2022; 2022:4201533. [PMID: 35860429 PMCID: PMC9293537 DOI: 10.1155/2022/4201533] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/13/2022] [Revised: 05/24/2022] [Accepted: 06/26/2022] [Indexed: 11/17/2022]
Abstract
Biological aging or senescence is a course in which cellular function decreases over a period of time and is a consequence of altered signaling mechanisms that are triggered in stressed cells leading to cell damage. Aging is among the principal risk factors for many chronic illnesses such as cancer, cardiovascular disorders, and neurodegenerative diseases. Taking this into account, targeting fundamental aging mechanisms therapeutically may effectively impact numerous chronic illnesses. Selecting ideal therapeutic options in order to hinder the process of aging and decelerate the progression of age-related diseases is valuable. Along therapeutic options, life style modifications may well render the process of aging. The process of aging is affected by alteration in many cellular and signaling pathways amid which mTOR, SIRT1, and AMPK pathways are the most emphasized. Herein, we have discussed the mechanisms of aging focusing mainly on the mentioned pathways as well as the role of inflammation and autophagy in aging. Moreover, drugs and natural products with antiaging properties are discussed in detail.
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Andreu-Sánchez S, Aubert G, Ripoll-Cladellas A, Henkelman S, Zhernakova DV, Sinha T, Kurilshikov A, Cenit MC, Jan Bonder M, Franke L, Wijmenga C, Fu J, van der Wijst MGP, Melé M, Lansdorp P, Zhernakova A. Genetic, parental and lifestyle factors influence telomere length. Commun Biol 2022; 5:565. [PMID: 35681050 PMCID: PMC9184499 DOI: 10.1038/s42003-022-03521-7] [Citation(s) in RCA: 19] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2022] [Accepted: 05/22/2022] [Indexed: 11/09/2022] Open
Abstract
The average length of telomere repeats (TL) declines with age and is considered to be a marker of biological ageing. Here, we measured TL in six blood cell types from 1046 individuals using the clinically validated Flow-FISH method. We identified remarkable cell-type-specific variations in TL. Host genetics, environmental, parental and intrinsic factors such as sex, parental age, and smoking are associated to variations in TL. By analysing the genome-wide methylation patterns, we identified that the association of maternal, but not paternal, age to TL is mediated by epigenetics. Single-cell RNA-sequencing data for 62 participants revealed differential gene expression in T-cells. Genes negatively associated with TL were enriched for pathways related to translation and nonsense-mediated decay. Altogether, this study addresses cell-type-specific differences in telomere biology and its relation to cell-type-specific gene expression and highlights how perinatal factors play a role in determining TL, on top of genetics and lifestyle.
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Affiliation(s)
- Sergio Andreu-Sánchez
- Department of Genetics, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands.
- Department of Pediatrics, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands.
| | - Geraldine Aubert
- Terry Fox Laboratory, British Columbia Cancer Research Center, Vancouver, BC, Canada
- Repeat Diagnostics Inc, Vancouver, BC, Canada
| | - Aida Ripoll-Cladellas
- Life Sciences Department, Barcelona Supercomputing Center, 08034, Barcelona, Catalonia, Spain
| | - Sandra Henkelman
- European Research Institute for the Biology of Ageing, University of Groningen, Groningen, the Netherlands
| | - Daria V Zhernakova
- Department of Genetics, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
- Laboratory of Genomic Diversity, Center for Computer Technologies, ITMO University, St. Petersburg, 197101, Russia
| | - Trishla Sinha
- Department of Genetics, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
| | - Alexander Kurilshikov
- Department of Genetics, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
| | - Maria Carmen Cenit
- Department of Genetics, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
- Microbial Ecology, Nutrition, and Health Research Unit, Institute of Agrochemistry and Food Technology (IATA-CSIC), 46980, Paterna-Valencia, Spain
| | - Marc Jan Bonder
- Department of Genetics, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
- Division of Computational Genomics and Systems Genetics, German Cancer Research Center (DKFZ), 69120, Heidelberg, Germany
- European Molecular Biology Laboratory, Genome Biology Unit, 69117, Heidelberg, Germany
| | - Lude Franke
- Department of Genetics, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
| | - Cisca Wijmenga
- Department of Genetics, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
| | - Jingyuan Fu
- Department of Genetics, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
- Department of Pediatrics, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
| | - Monique G P van der Wijst
- Department of Genetics, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
| | - Marta Melé
- Life Sciences Department, Barcelona Supercomputing Center, 08034, Barcelona, Catalonia, Spain
| | - Peter Lansdorp
- Terry Fox Laboratory, British Columbia Cancer Research Center, Vancouver, BC, Canada.
- European Research Institute for the Biology of Ageing, University of Groningen, Groningen, the Netherlands.
- Departments of Hematology and Medical Genetics, University of British Columbia, Vancouver, BC, Canada.
| | - Alexandra Zhernakova
- Department of Genetics, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands.
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eClock: An ensemble-based method to accurately predict ages with a biased distribution from DNA methylation data. PLoS One 2022; 17:e0267349. [PMID: 35522643 PMCID: PMC9075636 DOI: 10.1371/journal.pone.0267349] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2021] [Accepted: 04/06/2022] [Indexed: 11/19/2022] Open
Abstract
DNA methylation is closely related to senescence, so it has been used to develop statistical models, called clock models, to predict chronological ages accurately. However, because the training data always have a biased age distribution, the model performance becomes weak for the samples with a small age distribution density. To solve this problem, we developed the R package eClock, which uses a bagging-SMOTE method to adjust the biased distribution and predict age with an ensemble model. Moreover, it also provides a bootstrapped model based on bagging only and a traditional clock model. The performance on three datasets showed that the bagging-SMOTE model significantly improved rare sample age prediction. In addition to model construction, the package also provides other functions such as data visualization and methylation feature conversion to facilitate the research in relevant areas.
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Seale K, Horvath S, Teschendorff A, Eynon N, Voisin S. Making sense of the ageing methylome. Nat Rev Genet 2022; 23:585-605. [PMID: 35501397 DOI: 10.1038/s41576-022-00477-6] [Citation(s) in RCA: 66] [Impact Index Per Article: 33.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 03/18/2022] [Indexed: 12/22/2022]
Abstract
Over time, the human DNA methylation landscape accrues substantial damage, which has been associated with a broad range of age-related diseases, including cardiovascular disease and cancer. Various age-related DNA methylation changes have been described, including at the level of individual CpGs, such as differential and variable methylation, and at the level of the whole methylome, including entropy and correlation networks. Here, we review these changes in the ageing methylome as well as the statistical tools that can be used to quantify them. We detail the evidence linking DNA methylation to ageing phenotypes and the longevity strategies aimed at altering both DNA methylation patterns and machinery to extend healthspan and lifespan. Lastly, we discuss theories on the mechanistic causes of epigenetic ageing.
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Affiliation(s)
- Kirsten Seale
- Institute for Health and Sport (iHeS), Victoria University, Footscray, Melbourne, Victoria, Australia
| | - Steve Horvath
- Department of Human Genetics, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA.,Altos Labs, San Diego, CA, USA
| | - Andrew Teschendorff
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, Chinese Academy of Sciences, Shanghai, China.,UCL Cancer Institute, University College London, London, UK
| | - Nir Eynon
- Institute for Health and Sport (iHeS), Victoria University, Footscray, Melbourne, Victoria, Australia.
| | - Sarah Voisin
- Institute for Health and Sport (iHeS), Victoria University, Footscray, Melbourne, Victoria, Australia.
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32
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Mi J, Chen X, Tang Y, You Y, Liu Q, Xiao J, Ling W. S-adenosylhomocysteine induces cellular senescence in rat aorta vascular smooth muscle cells via NF-κB-SASP pathway. J Nutr Biochem 2022; 107:109063. [DOI: 10.1016/j.jnutbio.2022.109063] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2021] [Revised: 03/27/2022] [Accepted: 04/23/2022] [Indexed: 10/18/2022]
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Pouikli A, Tessarz P. Epigenetic alterations in stem cell ageing-a promising target for age-reversing interventions? Brief Funct Genomics 2022; 21:35-42. [PMID: 33738480 PMCID: PMC8789308 DOI: 10.1093/bfgp/elab010] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022] Open
Abstract
Ageing is accompanied by loss of tissue integrity and organismal homeostasis partly due to decline in stem cell function. The age-associated decrease in stem cell abundance and activity is often referred to as stem cell exhaustion and is considered one major hallmark of ageing. Importantly, stem cell proliferation and differentiation potential are tightly coupled to the cellular epigenetic state. Thus, research during the last years has started to investigate how the epigenome regulates stem cell function upon ageing. Here, we summarize the role of epigenetic regulation in stem cell fate decisions and we review the impact of age-related changes of the epigenome on stem cell activity. Finally, we discuss how targeted interventions on the epigenetic landscape might delay ageing and extend health-span.
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Affiliation(s)
| | - Peter Tessarz
- Corresponding author: Peter Tessarz, Max Planck Research Group ``Chromatin and Ageing'', Max Planck Institute for Biology of Ageing, Joseph-Stelzmann-Str. 9b, 50931 Cologne, Germany. Tel: +4922137970680; Fax: +492213797088680; E-mail:
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34
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Soda K. Overview of Polyamines as Nutrients for Human Healthy Long Life and Effect of Increased Polyamine Intake on DNA Methylation. Cells 2022; 11:cells11010164. [PMID: 35011727 PMCID: PMC8750749 DOI: 10.3390/cells11010164] [Citation(s) in RCA: 22] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2021] [Revised: 12/24/2021] [Accepted: 12/28/2021] [Indexed: 02/04/2023] Open
Abstract
Polyamines, spermidine and spermine, are synthesized in every living cell and are therefore contained in foods, especially in those that are thought to contribute to health and longevity. They have many physiological activities similar to those of antioxidant and anti-inflammatory substances such as polyphenols. These include antioxidant and anti-inflammatory properties, cell and gene protection, and autophagy activation. We have first reported that increased polyamine intake (spermidine much more so than spermine) over a long period increased blood spermine levels and inhibited aging-associated pathologies and pro-inflammatory status in humans and mice and extended life span of mice. However, it is unlikely that the life-extending effect of polyamines is exerted by the same bioactivity as polyphenols because most studies using polyphenols and antioxidants have failed to demonstrate their life-extending effects. Recent investigations revealed that aging-associated pathologies and lifespan are closely associated with DNA methylation, a regulatory mechanism of gene expression. There is a close relationship between polyamine metabolism and DNA methylation. We have shown that the changes in polyamine metabolism affect the concentrations of substances and enzyme activities involved in DNA methylation. I consider that the increased capability of regulation of DNA methylation by spermine is a key of healthy long life of humans.
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Affiliation(s)
- Kuniyasu Soda
- Department Cardiovascular Institute for Medical Research, Saitama Medical Center, Jichi Medical University, 1-847, Amanuma, Saitama-City 330-0834, Saitama, Japan
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35
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Abstract
The intestinal tract is the entry gate for nutrients and symbiotic organisms, being in constant contact with external environment. DNA methylation is one of the keys to how environmental conditions, diet and nutritional status included, shape functionality in the gut and systemically. This review aims to summarise findings on the importance of methylation to gut development, differentiation and function. Evidence to date on how external factors such as diet, dietary supplements, nutritional status and microbiota modifications modulate intestinal function through DNA methylation is also presented.
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36
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Zhao H, Ma D, Xie J, Sanchez O, Huang F, Yuan C. Live-Cell Probe for In Situ Single-Cell Monitoring of Mitochondrial DNA Methylation. ACS Sens 2021; 6:3575-3586. [PMID: 34586782 DOI: 10.1021/acssensors.1c00731] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Abstract
Mitochondria, as the center of energy production, play an important role in cell homeostasis by regulating the cellular metabolism and mediating the cellular response to stress. Epigenetic changes such as DNA and histone methylation have been increasingly recognized to play a significant role in homeostasis and stress response. The cross-talking between the metabolome and the epigenome has attracted significant attention in recent years but with a major focus on how metabolism contributes to epigenomic changes. Few studies have focused on how epigenetic modifications may alter the mitochondrial composition and activity. In this work, we designed a novel probe targeting methylated CpGs of mitochondrial DNA (mtDNA). We demonstrated the capability of our probe to reveal the spatial distribution of methylated mtDNA and capture the mtDNA methylation changes at a single-cell level. We were also able to track single-cell mtDNA and nDNA methylation simultaneously and discovered the unsynchronized dynamics of the nucleus and mitochondria. Our tool offers a unique opportunity to understand the epigenetic regulation of mtDNA and its dynamic response to the microenvironment and cellular changes.
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Affiliation(s)
- Han Zhao
- Davidson School of Chemical Engineering, Purdue University, West Lafayette, Indiana 47907, United States
| | - Donghan Ma
- Davidson School of Chemical Engineering, Purdue University, West Lafayette, Indiana 47907, United States
- Weldon School of Biomedical Engineering, Purdue University, West Lafayette, Indiana 47907, United States
| | - Junkai Xie
- Davidson School of Chemical Engineering, Purdue University, West Lafayette, Indiana 47907, United States
| | - Oscar Sanchez
- Davidson School of Chemical Engineering, Purdue University, West Lafayette, Indiana 47907, United States
| | - Fang Huang
- Weldon School of Biomedical Engineering, Purdue University, West Lafayette, Indiana 47907, United States
- Purdue University Center for Cancer Research, West Lafayette, Indiana 47907, United States
| | - Chongli Yuan
- Davidson School of Chemical Engineering, Purdue University, West Lafayette, Indiana 47907, United States
- Purdue University Center for Cancer Research, West Lafayette, Indiana 47907, United States
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37
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Garcia-Venzor A, Toiber D. SIRT6 Through the Brain Evolution, Development, and Aging. Front Aging Neurosci 2021; 13:747989. [PMID: 34720996 PMCID: PMC8548377 DOI: 10.3389/fnagi.2021.747989] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2021] [Accepted: 09/16/2021] [Indexed: 12/19/2022] Open
Abstract
During an organism's lifespan, two main phenomena are critical for the organism's survival. These are (1) a proper embryonic development, which permits the new organism to function with high fitness, grow and reproduce, and (2) the aging process, which will progressively undermine its competence and fitness for survival, leading to its death. Interestingly these processes present various similarities at the molecular level. Notably, as organisms became more complex, regulation of these processes became coordinated by the brain, and failure in brain activity is detrimental in both development and aging. One of the critical processes regulating brain health is the capacity to keep its genomic integrity and epigenetic regulation-deficiency in DNA repair results in neurodevelopmental and neurodegenerative diseases. As the brain becomes more complex, this effect becomes more evident. In this perspective, we will analyze how the brain evolved and became critical for human survival and the role Sirt6 plays in brain health. Sirt6 belongs to the Sirtuin family of histone deacetylases that control several cellular processes; among them, Sirt6 has been associated with the proper embryonic development and is associated with the aging process. In humans, Sirt6 has a pivotal role during brain aging, and its loss of function is correlated with the appearance of neurodegenerative diseases such as Alzheimer's disease. However, Sirt6 roles during brain development and aging, especially the last one, are not observed in all species. It appears that during the brain organ evolution, Sirt6 has gained more relevance as the brain becomes bigger and more complex, observing the most detrimental effect in the brains of Homo sapiens. In this perspective, we part from the evolution of the brain in metazoans, the biological similarities between brain development and aging, and the relevant functions of Sirt6 in these similar phenomena to conclude with the evidence suggesting a more relevant role of Sirt6 gained in the brain evolution.
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Affiliation(s)
- Alfredo Garcia-Venzor
- Department of Life Sciences, Ben-Gurion University of the Negev, Beer Sheva, Israel
- The Zlotowski Center for Neuroscience, Ben-Gurion University of the Negev, Beer Sheva, Israel
| | - Debra Toiber
- Department of Life Sciences, Ben-Gurion University of the Negev, Beer Sheva, Israel
- The Zlotowski Center for Neuroscience, Ben-Gurion University of the Negev, Beer Sheva, Israel
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Aging biological markers in a cohort of antipsychotic-naïve first-episode psychosis patients. Psychoneuroendocrinology 2021; 132:105350. [PMID: 34271521 DOI: 10.1016/j.psyneuen.2021.105350] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/27/2021] [Revised: 06/29/2021] [Accepted: 06/30/2021] [Indexed: 11/21/2022]
Abstract
Schizophrenia is a severe and multifactorial disorder with an unknown causative pathophysiology. Abnormalities in neurodevelopmental and aging processes have been reported. Relative telomere length (RTL) and DNA methylation age (DMA), well-known biomarkers for estimating biological age, are both commonly altered in patients with schizophrenia compared to healthy controls. However, few studies investigated these aging biomarkers in first-episode psychosis (FEP) and in antipsychotic-naïve patients. To cover the existing gap regarding DMA and RTL in FEP and antipsychotic treatment, we aimed to verify whether those aging markers could be associated with psychosis and treatment response. Thus, we evaluated these measures in the blood of FEP antipsychotic-naïve patients and healthy controls (HC), as well as the response to antipsychotics after 10 weeks of treatment with risperidone. RTL was measured in 392 subjects, being 80 FEP and 312 HC using qPCR, while DMA was analyzed in a subset of 60 HC, 60 FEP patients (antipsychotic-naïve) and 59 FEP-10W (after treatment) using the "Multi-tissue Predictor"and the Infinium HumanMethylation450 BeadChip Kit. We observed diminished DMA and longer RTL in FEP patients before treatment compared to healthy controls, indicating a decelerated aging process in those patients. We found no statistical difference between responder and non-responder patients at baseline for both markers. An increased DMA was observed in patients after 10 weeks of treatment, however, after adjusting for blood cell composition, no significant association remained. Our findings indicate a decelerated aging process in the early phases of the disease.
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Fairfield EA, Richardson DS, Daniels CL, Butler CL, Bell E, Taylor MI. Ageing European lobsters ( Homarus gammarus) using DNA methylation of evolutionarily conserved ribosomal DNA. Evol Appl 2021; 14:2305-2318. [PMID: 34603500 PMCID: PMC8477595 DOI: 10.1111/eva.13296] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2021] [Revised: 08/15/2021] [Accepted: 08/17/2021] [Indexed: 12/30/2022] Open
Abstract
Crustaceans are notoriously difficult to age because of their indeterminate growth and the moulting of their exoskeleton throughout life. The poor knowledge of population age structure in crustaceans therefore hampers accurate assessment of population dynamics and consequently sustainable fisheries management. Quantification of DNA methylation of the evolutionarily conserved ribosomal DNA (rDNA) may allow for age prediction across diverse species. However, the rDNA epigenetic clock remains to be tested in crustaceans, despite its potential to inform both ecological and evolutionary understanding, as well as conservation and management practices. Here, patterns of rDNA methylation with age were measured across 5154 bp of rDNA corresponding to 355 quality-filtered loci in the economically important European lobster (Homarus gammarus). Across 0- to 51-month-old lobsters (n = 155), there was a significant linear relationship between age and percentage rDNA methylation in claw tissue at 60% of quality-filtered loci (n = 214). An Elastic Net regression model using 46 loci allowed for the accurate and precise age estimation of individuals (R 2 = 0.98; standard deviation = 1.6 months). Applying this ageing model to antennal DNA from wild lobsters of unknown age (n = 38) resulted in predicted ages that are concordant with estimates of minimum size at age in the wild (mean estimated age = 40.1 months; range 32.8-55.7 months). Overall, the rDNA epigenetic clock shows potential as a novel, nonlethal ageing technique for European lobsters. However, further validation is required across a wider range of known-age individuals and tissue types before the model can be used in fisheries management.
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Affiliation(s)
| | | | | | | | - Ewen Bell
- The Centre for Environment, Fisheries and Aquaculture ScienceLowestoftUK
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Ji L, Jazwinski SM, Kim S. Frailty and Biological Age. Ann Geriatr Med Res 2021; 25:141-149. [PMID: 34399574 PMCID: PMC8497950 DOI: 10.4235/agmr.21.0080] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2021] [Accepted: 08/10/2021] [Indexed: 12/15/2022] Open
Abstract
A reliable model of biological age is instrumental in the field of geriatrics and gerontology. This model should account for the heterogeneity and plasticity of aging and also accurately predict aging-related adverse outcomes. Epigenetic age models are based on DNA methylation levels at selected genomic sites and can be significant predictors of mortality and healthy/unhealthy aging. However, the biological function of DNA methylation at selected sites is yet to be determined. Frailty is a syndrome resulting from decreased physiological reserves and resilience. The frailty index is a probability-based extension of the concept of frailty. Defined as the proportion of health deficits, the frailty index quantifies the progression of unhealthy aging. The frailty index is currently the best predictor of mortality. It is associated with various biological factors and provides insight into the biological processes of aging. Investigation of the multi-omics factors associated with the frailty index will provide further insight.
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Affiliation(s)
- Lixin Ji
- Tulane University School of Medicine, New Orleans, LA, USA
| | - S Michal Jazwinski
- Tulane Center for Aging & Department of Medicine, Tulane University Health Sciences Center, New Orleans, LA, USA
| | - Sangkyu Kim
- Tulane Center for Aging & Department of Medicine, Tulane University Health Sciences Center, New Orleans, LA, USA
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Sharma VK, Mehta V, Singh TG. Alzheimer's Disorder: Epigenetic Connection and Associated Risk Factors. Curr Neuropharmacol 2021; 18:740-753. [PMID: 31989902 PMCID: PMC7536832 DOI: 10.2174/1570159x18666200128125641] [Citation(s) in RCA: 55] [Impact Index Per Article: 18.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2019] [Revised: 11/26/2019] [Accepted: 01/27/2020] [Indexed: 12/13/2022] Open
Abstract
The gene based therapeutics and drug targets have shown incredible and appreciable advances in alleviating human sufferings and complexities. Epigenetics simply means above genetics or which controls the organism beyond genetics. At present it is very clear that all characteristics of an individual are not determined by DNA alone, rather the environment, stress, life style and nutrition play a vital part in determining the response of an organism. Thus, nature (genetic makeup) and nurture (exposure) play equally important roles in the responses observed, both at the cellular and organism levels. Epigenetics influence plethora of complications at cellular and molecular levels that includes cancer, metabolic and cardiovascular complications including neurological (psychosis) and neurodegenerative disorders (Alzheimer’s disease, Parkinson disease etc.). The epigenetic mechanisms include DNA methylation, histone modification and non coding RNA which have substantial impact on progression and pathways linked to Alzheimer’s disease. The epigenetic mechanism gets deregulated in Alzheimer’s disease and is characterized by DNA hyper methylation, deacetylation of histones and general repressed chromatin state which alter gene expression at the transcription level by upregulation, downregulation or silencing of genes. Thus, the processes or modulators of these epigenetic processes have shown vast potential as a therapeutic target in Alzheimer’s disease.
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Affiliation(s)
| | - Vineet Mehta
- Govt. College of Pharmacy, Rohru, District Shimla, Himachal Pradesh-171207, India
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Pappalardo XG, Barra V. Losing DNA methylation at repetitive elements and breaking bad. Epigenetics Chromatin 2021; 14:25. [PMID: 34082816 PMCID: PMC8173753 DOI: 10.1186/s13072-021-00400-z] [Citation(s) in RCA: 57] [Impact Index Per Article: 19.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2021] [Accepted: 05/21/2021] [Indexed: 02/08/2023] Open
Abstract
Background DNA methylation is an epigenetic chromatin mark that allows heterochromatin formation and gene silencing. It has a fundamental role in preserving genome stability (including chromosome stability) by controlling both gene expression and chromatin structure. Therefore, the onset of an incorrect pattern of DNA methylation is potentially dangerous for the cells. This is particularly important with respect to repetitive elements, which constitute the third of the human genome. Main body Repetitive sequences are involved in several cell processes, however, due to their intrinsic nature, they can be a source of genome instability. Thus, most repetitive elements are usually methylated to maintain a heterochromatic, repressed state. Notably, there is increasing evidence showing that repetitive elements (satellites, long interspersed nuclear elements (LINEs), Alus) are frequently hypomethylated in various of human pathologies, from cancer to psychiatric disorders. Repetitive sequences’ hypomethylation correlates with chromatin relaxation and unscheduled transcription. If these alterations are directly involved in human diseases aetiology and how, is still under investigation. Conclusions Hypomethylation of different families of repetitive sequences is recurrent in many different human diseases, suggesting that the methylation status of these elements can be involved in preservation of human health. This provides a promising point of view towards the research of therapeutic strategies focused on specifically tuning DNA methylation of DNA repeats.
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Affiliation(s)
- Xena Giada Pappalardo
- Department of Biomedical and Biotechnological Sciences (BIOMETEC), University of Catania, 95125, Catania, Italy.,National Council of Research, Institute for Biomedical Research and Innovation (IRIB), Unit of Catania, 95125, Catania, Italy
| | - Viviana Barra
- Department of Biological, Chemical and Pharmaceutical Sciences and Technologies (STEBICEF), University of Palermo, 90128, Palermo, Italy.
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Liu C, Yin Q, Li M, Fan Y, Shen C, Yang R. ACTB Methylation in Blood as a Potential Marker for the Pre-clinical Detection of Stroke: A Prospective Nested Case-Control Study. Front Neurosci 2021; 15:644943. [PMID: 34054407 PMCID: PMC8160447 DOI: 10.3389/fnins.2021.644943] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2020] [Accepted: 04/26/2021] [Indexed: 01/07/2023] Open
Abstract
Background Stroke is the second leading cause of death worldwide. If risk of stroke could be evaluated early or even at a preclinical stage, the mortality rate could be reduced dramatically. However, the identified genetic factors only account for 5-10% of the risk of stroke. Studies on the risk factors of stroke are urgently needed. We investigated the correlation between blood-based β-actin (ACTB) methylation and the risk of stroke in a prospective nested case-control study. Methods The methylation level of ACTB was quantitatively determined by mass spectrometry in 139 stroke cases who developed stroke within 2 years after recruitment and 147 age- and sex-matched controls who remained stroke-free in a median follow-up of 2.71 years. Results We observed a highly significant correlation between hypomethylation of one CpG site of ACTB and increased risk of stroke in an onset-time-dependent manner (for onset time ≤ 1.5 years: odds ratio (OR) per + 10% methylation = 0.76, P = 0.001; for onset time ≤ 1.32 years: OR per + 10% methylation = 0.59, P = 7.82 × 10-7; for onset time ≤ 1 year: OR per + 10% methylation = 0.43, P = 3.00 × 10-6), and the increased cumulative incidence of stroke (log-rank P = 3.13 × 10-7). Neighboring CpG sites showed an inverse correlation with age and drinking status in controls (P < 0.05) but not in stroke cases. Conclusion We firstly reported the blood-based ACTB methylation as a marker for the risk evaluation and preclinical detection of stroke, which can be further modified by age and drinking.
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Affiliation(s)
- Chunlan Liu
- Department of Epidemiology, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Qiming Yin
- Department of Epidemiology, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Mengxia Li
- Department of Epidemiology, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Yao Fan
- Division of Clinical Epidemiology, Affiliated Geriatric Hospital of Nanjing Medical University, Nanjing, China
| | - Chong Shen
- Department of Epidemiology, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Rongxi Yang
- Department of Epidemiology, School of Public Health, Nanjing Medical University, Nanjing, China
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Soda K, Uemura T, Sanayama H, Igarashi K, Fukui T. Polyamine-Rich Diet Elevates Blood Spermine Levels and Inhibits Pro-Inflammatory Status: An Interventional Study. Med Sci (Basel) 2021; 9:medsci9020022. [PMID: 33805535 PMCID: PMC8103277 DOI: 10.3390/medsci9020022] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2021] [Revised: 03/24/2021] [Accepted: 03/24/2021] [Indexed: 12/11/2022] Open
Abstract
The Japanese diet and the Mediterranean diet are rich in polyamines (spermidine and spermine). Increased polyamine intake elevated blood spermine levels, inhibited aging-associated pro-inflammatory status (increases in lymphocyte function-associated antigen-1 (LFA-1) on immune cells), suppressed aberrant gene methylation and extended the lifespan of mice. To test the effects of increased polyamine intake by humans, 30 healthy male volunteers were asked to eat polyamine-rich and ready-to-eat traditional Japanese food (natto) for 12 months. Natto with high polyamine content was used. Another 27 male volunteers were asked not to change their dietary pattern as a control group. The volunteers’ age of intervention and control groups ranged from 40 to 69 years (median 48.9 ± 7.9). Two subjects in the control group subsequently dropped out of the study. The estimated increases in spermidine and spermine intakes were 96.63 ± 47.70 and 22.00 ± 9.56 µmol per day in the intervention group, while no changes were observed in the control group. The mean blood spermine level in the intervention group gradually rose to 1.12 ± 0.29 times the pre-intervention level after 12 months, and were significantly higher (p = 0.019) than those in the control group. Blood spermidine did not increase in either group. LFA-1 on monocytes decreased gradually in the intervention group, and there was an inverse association between changes in spermine concentrations relative to spermidine and changes in LFA-1 levels. Contingency table analysis revealed that the odds ratio to decrease LFA-1 by increased polyamine intake was 3.927 (95% CI 1.116–13.715) (p = 0.032) when the effect of acute inflammation was excluded. The results in the study were similar to those of our animal experiments. Since methylation changes of the entire genome are associated with aging-associated pathologies and our previous studies showed that spermine-induced LFA-1 suppression was associated with the inhibition of aberrant gene methylation, the results suggest that dietary polyamine contributes to human health and longevity.
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Affiliation(s)
- Kuniyasu Soda
- Department Cardiovascular Institute for Medical Research, Saitama Medical Center, Jichi Medical University, 1-847, Amanuma, Saitama-City, Saitama 330-0834, Japan; (H.S.); (T.F.)
- Correspondence: ; Tel.: +81-48-647-2111
| | - Takeshi Uemura
- Amine Pharma Research Institute, Innovation Plaza at Chiba University, 1-8-15 Inohana, Chuo-ku, Chiba 260-0856, Japan; (T.U.); (K.I.)
| | - Hidenori Sanayama
- Department Cardiovascular Institute for Medical Research, Saitama Medical Center, Jichi Medical University, 1-847, Amanuma, Saitama-City, Saitama 330-0834, Japan; (H.S.); (T.F.)
| | - Kazuei Igarashi
- Amine Pharma Research Institute, Innovation Plaza at Chiba University, 1-8-15 Inohana, Chuo-ku, Chiba 260-0856, Japan; (T.U.); (K.I.)
- Graduate School of Pharmaceutical Sciences, Chiba University, 1-8-1 Inohana, Chuo-ku, Chiba 260-8675, Japan
| | - Taro Fukui
- Department Cardiovascular Institute for Medical Research, Saitama Medical Center, Jichi Medical University, 1-847, Amanuma, Saitama-City, Saitama 330-0834, Japan; (H.S.); (T.F.)
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Characterization of the effects of age and childhood maltreatment on ELOVL2 DNA methylation. Dev Psychopathol 2021; 34:864-874. [PMID: 33461631 DOI: 10.1017/s0954579420001972] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
DNA methylation of the elongation of very long chain fatty acids protein 2 (ELOVL2) was suggested as a biomarker of biological aging, while childhood maltreatment (CM) has been associated with accelerated biological aging. We investigated the association of age and CM experiences with ELOVL2 methylation in peripheral blood mononuclear cells (PBMC). Furthermore, we investigated ELOVL2 methylation in the umbilical cord blood mononuclear cells (UBMC) of newborns of mothers with and without CM. PBMC and UBMC were isolated from 113 mother-newborn dyads and genomic DNA was extracted. Mothers with and without CM experiences were recruited directly postpartum. Mass array spectrometry and pyrosequencing were used for methylation analyses of ELOVL2 intron 1, and exon 1 and 5' end, respectively. ELOVL2 5' end and intron 1 methylation increased with higher age but were not associated with CM experiences. On the contrary, overall ELOVL2 exon 1 methylation increased with higher CM, but these changes were minimal and did not increase with age. Maternal CM experiences and neonatal methylation of ELOVL2 intron 1 or exon 1 were not significantly correlated. Our study suggests region-specific effects of chronological age and experienced CM on ELOVL2 methylation and shows that the epigenetic biomarker for age within the ELOVL2 gene does not show accelerated biological aging years after CM exposure.
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Sławińska N, Krupa R. Molecular Aspects of Senescence and Organismal Ageing-DNA Damage Response, Telomeres, Inflammation and Chromatin. Int J Mol Sci 2021; 22:ijms22020590. [PMID: 33435578 PMCID: PMC7827783 DOI: 10.3390/ijms22020590] [Citation(s) in RCA: 24] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2020] [Revised: 12/30/2020] [Accepted: 01/03/2021] [Indexed: 02/07/2023] Open
Abstract
Cells can become senescent in response to stress. Senescence is a process characterised by a stable proliferative arrest. Sometimes it can be beneficial—for example, it can suppress tumour development or take part in tissue repair. On the other hand, studies show that it is also involved in the ageing process. DNA damage response (DDR) is triggered by DNA damage or telomere shortening during cell division. When left unresolved, it may lead to the activation of senescence. Senescent cells secrete certain proteins in larger quantities. This phenomenon is referred to as senescence-associated secretory phenotype (SASP). SASP can induce senescence in other cells; evidence suggests that overabundance of senescent cells contributes to ageing. SASP proteins include proinflammatory cytokines and metalloproteinases, which degrade the extracellular matrix. Shortening of telomeres is another feature associated with organismal ageing. Older organisms have shorter telomeres. Restoring telomerase activity in mice not only slowed but also partially reversed the symptoms of ageing. Changes in chromatin structure during senescence include heterochromatin formation or decondensation and loss of H1 histones. During organismal ageing, cells can experience heterochromatin loss, DNA demethylation and global histone loss. Cellular and organismal ageing are both complex processes with many aspects that are often related. The purpose of this review is to bring some of these aspects forward and provide details regarding them.
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Shchukina I, Bagaitkar J, Shpynov O, Loginicheva E, Porter S, Mogilenko DA, Wolin E, Collins P, Demidov G, Artomov M, Zaitsev K, Sidorov S, Camell C, Bambouskova M, Arthur L, Swain A, Panteleeva A, Dievskii A, Kurbatsky E, Tsurinov P, Chernyatchik R, Dixit VD, Jovanovic M, Stewart SA, Daly MJ, Dmitriev S, Oltz EM, Artyomov MN. Enhanced epigenetic profiling of classical human monocytes reveals a specific signature of healthy aging in the DNA methylome. NATURE AGING 2021; 1:124-141. [PMID: 34796338 PMCID: PMC8597198 DOI: 10.1038/s43587-020-00002-6] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/10/2020] [Accepted: 10/06/2020] [Indexed: 12/20/2022]
Abstract
The impact of healthy aging on molecular programming of immune cells is poorly understood. Here, we report comprehensive characterization of healthy aging in human classical monocytes, with a focus on epigenomic, transcriptomic, and proteomic alterations, as well as the corresponding proteomic and metabolomic data for plasma, using healthy cohorts of 20 young and 20 older males (~27 and ~64 years old on average). For each individual, we performed eRRBS-based DNA methylation profiling, which allowed us to identify a set of age-associated differentially methylated regions (DMRs) - a novel, cell-type specific signature of aging in DNA methylome. Hypermethylation events were associated with H3K27me3 in the CpG islands near promoters of lowly-expressed genes, while hypomethylated DMRs were enriched in H3K4me1 marked regions and associated with age-related increase of expression of the corresponding genes, providing a link between DNA methylation and age-associated transcriptional changes in primary human cells.
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Affiliation(s)
- Irina Shchukina
- Department of Pathology and Immunology, Washington University School of Medicine, Saint Louis, MO, USA
- These authors contributed equally: Irina Shchukina, Juhi Bagaitkar, Oleg Shpynov
| | - Juhi Bagaitkar
- Department of Oral Immunology and Infectious Diseases, University of Louisville, Louisville, KY, USA
- These authors contributed equally: Irina Shchukina, Juhi Bagaitkar, Oleg Shpynov
| | - Oleg Shpynov
- Department of Pathology and Immunology, Washington University School of Medicine, Saint Louis, MO, USA
- JetBrains Research, St. Petersburg, Russia
- These authors contributed equally: Irina Shchukina, Juhi Bagaitkar, Oleg Shpynov
| | - Ekaterina Loginicheva
- Department of Pathology and Immunology, Washington University School of Medicine, Saint Louis, MO, USA
| | - Sofia Porter
- Department of Pathology and Immunology, Washington University School of Medicine, Saint Louis, MO, USA
| | - Denis A. Mogilenko
- Department of Pathology and Immunology, Washington University School of Medicine, Saint Louis, MO, USA
| | - Erica Wolin
- Department of Biological Sciences, Columbia University, New York, NY, USA
| | - Patrick Collins
- Department of Pathology and Immunology, Washington University School of Medicine, Saint Louis, MO, USA
| | - German Demidov
- Department of Pathology and Immunology, Washington University School of Medicine, Saint Louis, MO, USA
- Bioinformatics and Genomics Program, Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology, Barcelona, Spain
- Universitat Pompeu Fabra (UPF), Barcelona, Spain
| | - Mykyta Artomov
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
- Broad Institute, Cambridge, MA, USA
| | - Konstantin Zaitsev
- Department of Pathology and Immunology, Washington University School of Medicine, Saint Louis, MO, USA
- Present address: Computer Technologies Department, ITMO University, St. Petersburg, Russia
| | - Sviatoslav Sidorov
- Yale Center for Research on Aging, Yale School of Medicine, New Haven, CT, USA
| | - Christina Camell
- Yale Center for Research on Aging, Yale School of Medicine, New Haven, CT, USA
| | - Monika Bambouskova
- Department of Pathology and Immunology, Washington University School of Medicine, Saint Louis, MO, USA
| | - Laura Arthur
- Department of Pathology and Immunology, Washington University School of Medicine, Saint Louis, MO, USA
| | - Amanda Swain
- Department of Pathology and Immunology, Washington University School of Medicine, Saint Louis, MO, USA
| | - Alexandra Panteleeva
- Department of Pathology and Immunology, Washington University School of Medicine, Saint Louis, MO, USA
| | | | | | - Petr Tsurinov
- Department of Pathology and Immunology, Washington University School of Medicine, Saint Louis, MO, USA
- JetBrains Research, St. Petersburg, Russia
| | - Roman Chernyatchik
- Department of Pathology and Immunology, Washington University School of Medicine, Saint Louis, MO, USA
- JetBrains Research, St. Petersburg, Russia
| | - Vishwa Deep Dixit
- Yale Center for Research on Aging, Yale School of Medicine, New Haven, CT, USA
| | - Marko Jovanovic
- Department of Biological Sciences, Columbia University, New York, NY, USA
| | - Sheila A. Stewart
- Department of Cell Biology and Physiology, Washington University School of Medicine, Saint Louis, MO, USA
| | - Mark J. Daly
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
- Broad Institute, Cambridge, MA, USA
- Institute for Molecular Medicine, Helsinki, Finland
| | | | - Eugene M. Oltz
- Department of Pathology and Immunology, Washington University School of Medicine, Saint Louis, MO, USA
| | - Maxim N. Artyomov
- Department of Pathology and Immunology, Washington University School of Medicine, Saint Louis, MO, USA
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Maulani C, Auerkari EI. Age estimation using DNA methylation technique in forensics: a systematic review. EGYPTIAN JOURNAL OF FORENSIC SCIENCES 2020. [DOI: 10.1186/s41935-020-00214-2] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022] Open
Abstract
AbstractBackgroundIn addition to the DNA sequence, epigenetic markers have become substantial forensic tools during the last decade. Estimating the age of an individual from human biological remains may provide information for a forensic investigation. Age estimation in molecular strategies can be obtained by telomere length, mRNa mutation, or by sjTRECs but the accuracy is not sufficient in forensic practice because of high margin error.Main bodyOne solution to this problem is to use DNA methylation methods. DNA methylation markers for tissue identification at age-associated CpG sites have been suggested as the most informative biomarkers for estimating the age of an unknown donor. This review aims to give an overview of DNA methylation profiling for estimating the age in cases of forensic relevance and the important aspects in determining the mean absolute deviation (MAD) or mean absolute error (MAE) of the estimated age. Online database searching was performed through PubMed, Scopus, and Google Scholar with keywords selected for forensic age estimation. Thirty-two studies were included in the review, with variable DNA samples but blood commonly as a source. Pyrosequencing and EpiTYPER were methods mostly used in DNA analysis. The MAD in the estimates from DNA methylation was about 3 to 5 years, which was better than other methods such as those based on telomere length or signal-joint T-cell receptor excision circles. The ELOVL2 gene was a commonly used DNA methylation marker in age estimation.ConclusionDNA methylation is a favorable candidate for estimating the age at the time of death in forensic profiling, with an uncertainty mean absolute deviation of about 3 to 5 years in the predicted age. The sample type, platform techniques used, and methods to construct age predictive models were important in determining the accuracy in mean absolute deviation or mean absolute error. The DNA methylation outcome suggests good potential to support conventional STR profiling in forensic cases.
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Dahan L, Rampon C, Florian C. Age-related memory decline, dysfunction of the hippocampus and therapeutic opportunities. Prog Neuropsychopharmacol Biol Psychiatry 2020; 102:109943. [PMID: 32298784 DOI: 10.1016/j.pnpbp.2020.109943] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/16/2019] [Revised: 04/01/2020] [Accepted: 04/01/2020] [Indexed: 12/13/2022]
Abstract
While the aging of the population is a sign of progress for societies, it also carries its load of negative aspects. Among them, cognitive decline and in particular memory loss is a common feature of non-pathological aging. Autobiographical memories, which rely on the hippocampus, are a primary target of age-related cognitive decline. Here, focusing on the neurobiological mechanisms of memory formation and storage, we describe how hippocampal functions are altered across time in non-pathological mammalian brains. Several hallmarks of aging have been well described over the last decades; among them, we consider altered synaptic communication and plasticity, reduction of adult neurogenesis and epigenetic alterations. Building on the neurobiological processes of cognitive aging that have been identified to date, we review some of the strategies based on lifestyle manupulation allowing to address age-related cognitive deficits.
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Affiliation(s)
- Lionel Dahan
- Centre de Recherches sur la Cognition Animale (CRCA), Centre de Biologie Intégrative (CBI), Université de Toulouse; CNRS, UPS, Toulouse Cedex 9, France
| | - Claire Rampon
- Centre de Recherches sur la Cognition Animale (CRCA), Centre de Biologie Intégrative (CBI), Université de Toulouse; CNRS, UPS, Toulouse Cedex 9, France
| | - Cédrick Florian
- Centre de Recherches sur la Cognition Animale (CRCA), Centre de Biologie Intégrative (CBI), Université de Toulouse; CNRS, UPS, Toulouse Cedex 9, France.
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Lau PY, Fung WK. Evaluation of marker selection methods and statistical models for chronological age prediction based on DNA methylation. Leg Med (Tokyo) 2020; 47:101744. [PMID: 32659707 DOI: 10.1016/j.legalmed.2020.101744] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2020] [Revised: 06/02/2020] [Accepted: 06/26/2020] [Indexed: 12/16/2022]
Abstract
In forensic investigation, retrieving biological information from DNA evidence is a promising field of interest. One of the applications is on the estimation of the age of the donor based on DNA methylation. A large number of studies focused on age prediction using the 450 K Human Methylation Beadchip. Various marker selection methods and prediction models have been considered. However, there is a lack of research evaluating different high-dimensional variable selection methods of CpG sites with various models for age prediction. The aim of this study is to evaluate four variable selection methods (forward selection, LASSO, elastic net and SCAD) combined with a classical statistical model and sophisticated machine learning models based on the mean absolute deviation (MAD) and the root-mean-square error (RMSE). We used publicly available 450 K data set containing 991 whole blood samples (age 19-101 years). We found that the multiple linear regression model with 16 markers selected from the forward selection method performed very well in age prediction (MAD = 3.76 years and RMSE = 5.01 years). On the other hand, the highly advanced ultrahigh dimensional variable selection methods and sophisticated machine learning algorithms appeared unnecessary for age prediction based on DNA methylation.
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Affiliation(s)
- Pui Yin Lau
- Department of Statistics and Actuarial Science, The University of Hong Kong, Pokfulam Road, Hong Kong, China
| | - Wing Kam Fung
- Department of Statistics and Actuarial Science, The University of Hong Kong, Pokfulam Road, Hong Kong, China.
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