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Moqri M, Herzog C, Poganik JR, Ying K, Justice JN, Belsky DW, Higgins-Chen AT, Chen BH, Cohen AA, Fuellen G, Hägg S, Marioni RE, Widschwendter M, Fortney K, Fedichev PO, Zhavoronkov A, Barzilai N, Lasky-Su J, Kiel DP, Kennedy BK, Cummings S, Slagboom PE, Verdin E, Maier AB, Sebastiano V, Snyder MP, Gladyshev VN, Horvath S, Ferrucci L. Validation of biomarkers of aging. Nat Med 2024; 30:360-372. [PMID: 38355974 PMCID: PMC11090477 DOI: 10.1038/s41591-023-02784-9] [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: 09/07/2023] [Accepted: 12/19/2023] [Indexed: 02/16/2024]
Abstract
The search for biomarkers that quantify biological aging (particularly 'omic'-based biomarkers) has intensified in recent years. Such biomarkers could predict aging-related outcomes and could serve as surrogate endpoints for the evaluation of interventions promoting healthy aging and longevity. However, no consensus exists on how biomarkers of aging should be validated before their translation to the clinic. Here, we review current efforts to evaluate the predictive validity of omic biomarkers of aging in population studies, discuss challenges in comparability and generalizability and provide recommendations to facilitate future validation of biomarkers of aging. Finally, we discuss how systematic validation can accelerate clinical translation of biomarkers of aging and their use in gerotherapeutic clinical trials.
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Affiliation(s)
- Mahdi Moqri
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Department of Genetics, School of Medicine, Stanford University, Stanford, CA, USA
- Department of Obstetrics and Gynecology, School of Medicine, Stanford University, Stanford, CA, USA
| | - Chiara Herzog
- European Translational Oncology Prevention and Screening Institute, Universität Innsbruck, Innsbruck, Austria
| | - Jesse R Poganik
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Kejun Ying
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- T.H. Chan School of Public Health, Harvard University, Boston, MA, USA
| | - Jamie N Justice
- Department of Internal Medicine, Section on Gerontology and Geriatric Medicine, Wake Forest University School of Medicine, Winston-Salem, NC, USA
| | - Daniel W Belsky
- Department of Epidemiology, Butler Columbia Aging Center, Mailman School of Public Health, Columbia University, New York, NY, USA
| | | | - Brian H Chen
- Herbert Wertheim School of Public Health and Human Longevity Science, University of California San Diego, San Diego, CA, USA
| | - Alan A Cohen
- Department of Environmental Health Sciences, Butler Columbia Aging Center, Mailman School of Public Health, Columbia University, New York, NY, USA
| | - Georg Fuellen
- Institute for Biostatistics and Informatics in Medicine and Ageing Research, Rostock University Medical Center, Rostock, Germany
- School of Medicine, University College Dublin, Dublin, Ireland
| | - Sara Hägg
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Riccardo E Marioni
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
| | - Martin Widschwendter
- European Translational Oncology Prevention and Screening Institute, Universität Innsbruck, Innsbruck, Austria
- Department of Women's Cancer, EGA Institute for Women's Health, University College London, London, UK
- Department of Women's and Children's Health, Division of Obstetrics and Gynaecology, Karolinska Institutet, Stockholm, Sweden
| | | | | | | | - Nir Barzilai
- Institute for Aging Research, Albert Einstein College of Medicine, Bronx, NY, USA
| | - Jessica Lasky-Su
- Department of Network Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Douglas P Kiel
- Musculoskeletal Research Center, Hinda and Arthur Marcus Institute for Aging Research and Department of Medicine, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA, USA
| | - Brian K Kennedy
- Healthy Longevity Translational Research Programme, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
- Healthy Longevity Translational Research Program, Yong Loo Lin School of Medicine, National University of Singapore, Centre for Healthy Longevity, @AgeSingapore, National University Health System, Singapore, Singapore
| | - Steven Cummings
- San Francisco Coordinating Center, California Pacific Medical Center Research Institute, San Francisco, CA, USA
- Department of Epidemiology and Biostatistics, University of California, San Francisco, San Francisco, CA, USA
| | - P Eline Slagboom
- Section of Molecular Epidemiology, Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, the Netherlands
| | - Eric Verdin
- Buck Institute for Research on Aging, Novato, CA, USA
| | - Andrea B Maier
- Healthy Longevity Translational Research Program, Yong Loo Lin School of Medicine, National University of Singapore, Centre for Healthy Longevity, @AgeSingapore, National University Health System, Singapore, Singapore
- Department of Human Movement Sciences, @AgeAmsterdam, Amsterdam Movement Sciences, Faculty of Behavioural and Movement Sciences, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
| | - Vittorio Sebastiano
- Department of Obstetrics and Gynecology, School of Medicine, Stanford University, Stanford, CA, USA
| | - Michael P Snyder
- Department of Genetics, School of Medicine, Stanford University, Stanford, CA, USA
| | - Vadim N Gladyshev
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
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2
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Liu R, Zhao E, Yu H, Yuan C, Abbas MN, Cui H. Methylation across the central dogma in health and diseases: new therapeutic strategies. Signal Transduct Target Ther 2023; 8:310. [PMID: 37620312 PMCID: PMC10449936 DOI: 10.1038/s41392-023-01528-y] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2023] [Revised: 05/23/2023] [Accepted: 05/25/2023] [Indexed: 08/26/2023] Open
Abstract
The proper transfer of genetic information from DNA to RNA to protein is essential for cell-fate control, development, and health. Methylation of DNA, RNAs, histones, and non-histone proteins is a reversible post-synthesis modification that finetunes gene expression and function in diverse physiological processes. Aberrant methylation caused by genetic mutations or environmental stimuli promotes various diseases and accelerates aging, necessitating the development of therapies to correct the disease-driver methylation imbalance. In this Review, we summarize the operating system of methylation across the central dogma, which includes writers, erasers, readers, and reader-independent outputs. We then discuss how dysregulation of the system contributes to neurological disorders, cancer, and aging. Current small-molecule compounds that target the modifiers show modest success in certain cancers. The methylome-wide action and lack of specificity lead to undesirable biological effects and cytotoxicity, limiting their therapeutic application, especially for diseases with a monogenic cause or different directions of methylation changes. Emerging tools capable of site-specific methylation manipulation hold great promise to solve this dilemma. With the refinement of delivery vehicles, these new tools are well positioned to advance the basic research and clinical translation of the methylation field.
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Affiliation(s)
- Ruochen Liu
- State Key Laboratory of Resource Insects, Medical Research Institute, Southwest University, Chongqing, 400715, China
- Jinfeng Laboratory, Chongqing, 401329, China
- Chongqing Engineering and Technology Research Center for Silk Biomaterials and Regenerative Medicine, Chongqing, 400716, China
- Engineering Research Center for Cancer Biomedical and Translational Medicine, Southwest University, Chongqing, 400715, China
| | - Erhu Zhao
- State Key Laboratory of Resource Insects, Medical Research Institute, Southwest University, Chongqing, 400715, China
- Jinfeng Laboratory, Chongqing, 401329, China
- Chongqing Engineering and Technology Research Center for Silk Biomaterials and Regenerative Medicine, Chongqing, 400716, China
- Engineering Research Center for Cancer Biomedical and Translational Medicine, Southwest University, Chongqing, 400715, China
| | - Huijuan Yu
- State Key Laboratory of Resource Insects, Medical Research Institute, Southwest University, Chongqing, 400715, China
| | - Chaoyu Yuan
- State Key Laboratory of Resource Insects, Medical Research Institute, Southwest University, Chongqing, 400715, China
| | - Muhammad Nadeem Abbas
- State Key Laboratory of Resource Insects, Medical Research Institute, Southwest University, Chongqing, 400715, China
- Jinfeng Laboratory, Chongqing, 401329, China
- Chongqing Engineering and Technology Research Center for Silk Biomaterials and Regenerative Medicine, Chongqing, 400716, China
- Engineering Research Center for Cancer Biomedical and Translational Medicine, Southwest University, Chongqing, 400715, China
| | - Hongjuan Cui
- State Key Laboratory of Resource Insects, Medical Research Institute, Southwest University, Chongqing, 400715, China.
- Jinfeng Laboratory, Chongqing, 401329, China.
- Chongqing Engineering and Technology Research Center for Silk Biomaterials and Regenerative Medicine, Chongqing, 400716, China.
- Engineering Research Center for Cancer Biomedical and Translational Medicine, Southwest University, Chongqing, 400715, China.
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3
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Bernabeu E, McCartney DL, Gadd DA, Hillary RF, Lu AT, Murphy L, Wrobel N, Campbell A, Harris SE, Liewald D, Hayward C, Sudlow C, Cox SR, Evans KL, Horvath S, McIntosh AM, Robinson MR, Vallejos CA, Marioni RE. Refining epigenetic prediction of chronological and biological age. Genome Med 2023; 15:12. [PMID: 36855161 PMCID: PMC9976489 DOI: 10.1186/s13073-023-01161-y] [Citation(s) in RCA: 22] [Impact Index Per Article: 22.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2022] [Accepted: 02/06/2023] [Indexed: 03/02/2023] Open
Abstract
BACKGROUND Epigenetic clocks can track both chronological age (cAge) and biological age (bAge). The latter is typically defined by physiological biomarkers and risk of adverse health outcomes, including all-cause mortality. As cohort sample sizes increase, estimates of cAge and bAge become more precise. Here, we aim to develop accurate epigenetic predictors of cAge and bAge, whilst improving our understanding of their epigenomic architecture. METHODS First, we perform large-scale (N = 18,413) epigenome-wide association studies (EWAS) of chronological age and all-cause mortality. Next, to create a cAge predictor, we use methylation data from 24,674 participants from the Generation Scotland study, the Lothian Birth Cohorts (LBC) of 1921 and 1936, and 8 other cohorts with publicly available data. In addition, we train a predictor of time to all-cause mortality as a proxy for bAge using the Generation Scotland cohort (1214 observed deaths). For this purpose, we use epigenetic surrogates (EpiScores) for 109 plasma proteins and the 8 component parts of GrimAge, one of the current best epigenetic predictors of survival. We test this bAge predictor in four external cohorts (LBC1921, LBC1936, the Framingham Heart Study and the Women's Health Initiative study). RESULTS Through the inclusion of linear and non-linear age-CpG associations from the EWAS, feature pre-selection in advance of elastic net regression, and a leave-one-cohort-out (LOCO) cross-validation framework, we obtain cAge prediction with a median absolute error equal to 2.3 years. Our bAge predictor was found to slightly outperform GrimAge in terms of the strength of its association to survival (HRGrimAge = 1.47 [1.40, 1.54] with p = 1.08 × 10-52, and HRbAge = 1.52 [1.44, 1.59] with p = 2.20 × 10-60). Finally, we introduce MethylBrowsR, an online tool to visualise epigenome-wide CpG-age associations. CONCLUSIONS The integration of multiple large datasets, EpiScores, non-linear DNAm effects, and new approaches to feature selection has facilitated improvements to the blood-based epigenetic prediction of biological and chronological age.
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Affiliation(s)
- Elena Bernabeu
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
| | - Daniel L McCartney
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
| | - Danni A Gadd
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
| | - Robert F Hillary
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
| | - Ake T Lu
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, CA, USA
- Altos Labs, San Diego, USA
| | - Lee Murphy
- Edinburgh Clinical Research Facility, University of Edinburgh, Edinburgh, UK
| | - Nicola Wrobel
- Edinburgh Clinical Research Facility, University of Edinburgh, Edinburgh, UK
| | - Archie Campbell
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
| | - Sarah E Harris
- Department of Psychology, Lothian Birth Cohorts, University of Edinburgh, Edinburgh, UK
| | - David Liewald
- Department of Psychology, Lothian Birth Cohorts, University of Edinburgh, Edinburgh, UK
| | - Caroline Hayward
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
- Medical Research Council Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
| | - Cathie Sudlow
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
- BHF Data Science Centre, Health Data Research UK, London, UK
- Edinburgh Medical School, Usher Institute, University of Edinburgh, Edinburgh, UK
| | - Simon R Cox
- Department of Psychology, Lothian Birth Cohorts, University of Edinburgh, Edinburgh, UK
| | - Kathryn L Evans
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
| | - Steve Horvath
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, CA, USA
- Altos Labs, San Diego, USA
| | - Andrew M McIntosh
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
- Division of Psychiatry, University of Edinburgh, Royal Edinburgh Hospital, Edinburgh, UK
| | | | - Catalina A Vallejos
- Medical Research Council Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
- The Alan Turing Institute, London, UK
| | - Riccardo E Marioni
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK.
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4
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Innate immunity dysregulation in aging eye and therapeutic interventions. Ageing Res Rev 2022; 82:101768. [PMID: 36280210 DOI: 10.1016/j.arr.2022.101768] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2022] [Revised: 09/29/2022] [Accepted: 10/20/2022] [Indexed: 01/31/2023]
Abstract
The prevalence of eye diseases increases considerably with age, resulting in significant vision impairment. Although the pathobiology of age-related eye diseases has been studied extensively, the contribution of immune-related changes due to aging remains elusive. In the eye, tissue-resident cells and infiltrating immune cells regulate innate responses during injury or infection. But due to aging, these cells lose their protective functions and acquire pathological phenotypes. Thus, dysregulated ocular innate immunity in the elderly increases the susceptibility and severity of eye diseases. Herein, we emphasize the impact of aging on the ocular innate immune system in the pathogenesis of infectious and non-infectious eye diseases. We discuss the role of age-related alterations in cellular metabolism, epigenetics, and cellular senescence as mechanisms underlying altered innate immune functions. Finally, we describe approaches to restore protective innate immune functions in the aging eye. Overall, the review summarizes our current understanding of innate immune functions in eye diseases and their dysregulation during aging.
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5
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Ruiz-Arenas C, Hernandez-Ferrer C, Vives-Usano M, Marí S, Quintela I, Mason D, Cadiou S, Casas M, Andrusaityte S, Gutzkow KB, Vafeiadi M, Wright J, Lepeule J, Grazuleviciene R, Chatzi L, Carracedo Á, Estivill X, Marti E, Escaramís G, Vrijheid M, González JR, Bustamante M. Identification of autosomal cis expression quantitative trait methylation (cis eQTMs) in children's blood. eLife 2022; 11:65310. [PMID: 35302492 PMCID: PMC8933004 DOI: 10.7554/elife.65310] [Citation(s) in RCA: 18] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2020] [Accepted: 02/11/2022] [Indexed: 12/12/2022] Open
Abstract
Background The identification of expression quantitative trait methylation (eQTMs), defined as associations between DNA methylation levels and gene expression, might help the biological interpretation of epigenome-wide association studies (EWAS). We aimed to identify autosomal cis eQTMs in children's blood, using data from 832 children of the Human Early Life Exposome (HELIX) project. Methods Blood DNA methylation and gene expression were measured with the Illumina 450K and the Affymetrix HTA v2 arrays, respectively. The relationship between methylation levels and expression of nearby genes (1 Mb window centered at the transcription start site, TSS) was assessed by fitting 13.6 M linear regressions adjusting for sex, age, cohort, and blood cell composition. Results We identified 39,749 blood autosomal cis eQTMs, representing 21,966 unique CpGs (eCpGs, 5.7% of total CpGs) and 8,886 unique transcript clusters (eGenes, 15.3% of total transcript clusters, equivalent to genes). In 87.9% of these cis eQTMs, the eCpG was located at <250 kb from eGene's TSS; and 58.8% of all eQTMs showed an inverse relationship between the methylation and expression levels. Only around half of the autosomal cis-eQTMs eGenes could be captured through annotation of the eCpG to the closest gene. eCpGs had less measurement error and were enriched for active blood regulatory regions and for CpGs reported to be associated with environmental exposures or phenotypic traits. In 40.4% of the eQTMs, the CpG and the eGene were both associated with at least one genetic variant. The overlap of autosomal cis eQTMs in children's blood with those described in adults was small (13.8%), and age-shared cis eQTMs tended to be proximal to the TSS and enriched for genetic variants. Conclusions This catalogue of autosomal cis eQTMs in children's blood can help the biological interpretation of EWAS findings and is publicly available at https://helixomics.isglobal.org/ and at Dryad (doi:10.5061/dryad.fxpnvx0t0). Funding The study has received funding from the European Community's Seventh Framework Programme (FP7/2007-206) under grant agreement no 308333 (HELIX project); the H2020-EU.3.1.2. - Preventing Disease Programme under grant agreement no 874583 (ATHLETE project); from the European Union's Horizon 2020 research and innovation programme under grant agreement no 733206 (LIFECYCLE project), and from the European Joint Programming Initiative "A Healthy Diet for a Healthy Life" (JPI HDHL and Instituto de Salud Carlos III) under the grant agreement no AC18/00006 (NutriPROGRAM project). The genotyping was supported by the projects PI17/01225 and PI17/01935, funded by the Instituto de Salud Carlos III and co-funded by European Union (ERDF, "A way to make Europe") and the Centro Nacional de Genotipado-CEGEN (PRB2-ISCIII). BiB received core infrastructure funding from the Wellcome Trust (WT101597MA) and a joint grant from the UK Medical Research Council (MRC) and Economic and Social Science Research Council (ESRC) (MR/N024397/1). INMA data collections were supported by grants from the Instituto de Salud Carlos III, CIBERESP, and the Generalitat de Catalunya-CIRIT. KANC was funded by the grant of the Lithuanian Agency for Science Innovation and Technology (6-04-2014_31V-66). The Norwegian Mother, Father and Child Cohort Study is supported by the Norwegian Ministry of Health and Care Services and the Ministry of Education and Research. The Rhea project was financially supported by European projects (EU FP6-2003-Food-3-NewGeneris, EU FP6. STREP Hiwate, EU FP7 ENV.2007.1.2.2.2. Project No 211250 Escape, EU FP7-2008-ENV-1.2.1.4 Envirogenomarkers, EU FP7-HEALTH-2009- single stage CHICOS, EU FP7 ENV.2008.1.2.1.6. Proposal No 226285 ENRIECO, EU- FP7- HEALTH-2012 Proposal No 308333 HELIX), and the Greek Ministry of Health (Program of Prevention of obesity and neurodevelopmental disorders in preschool children, in Heraklion district, Crete, Greece: 2011-2014; "Rhea Plus": Primary Prevention Program of Environmental Risk Factors for Reproductive Health, and Child Health: 2012-15). We acknowledge support from the Spanish Ministry of Science and Innovation through the "Centro de Excelencia Severo Ochoa 2019-2023" Program (CEX2018-000806-S), and support from the Generalitat de Catalunya through the CERCA Program. MV-U and CR-A were supported by a FI fellowship from the Catalan Government (FI-DGR 2015 and #016FI_B 00272). MC received funding from Instituto Carlos III (Ministry of Economy and Competitiveness) (CD12/00563 and MS16/00128).
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Affiliation(s)
- Carlos Ruiz-Arenas
- Centro de Investigación Biomédica en Red de Enfermedades Raras (CIBERER), Barcelona, Spain.,Universitat Pompeu Fabra (UPF), Barcelona, Spain
| | - Carles Hernandez-Ferrer
- Universitat Pompeu Fabra (UPF), Barcelona, Spain.,Centro Nacional de Análisis Genómico (CNAG-CRG), Center for Genomic Regulation, Barcelona Institute of Science and Technology (BIST), Barcelona, Spain.,ISGlobal, Barcelona, Spain
| | - Marta Vives-Usano
- Universitat Pompeu Fabra (UPF), Barcelona, Spain.,ISGlobal, Barcelona, Spain.,Center for Genomic Regulation (CRG), Barcelona Institute of Science and Technology, Barcelona, Spain
| | - Sergi Marí
- Universitat Pompeu Fabra (UPF), Barcelona, Spain.,ISGlobal, Barcelona, Spain.,CIBER Epidemiología y Salud Pública (CIBERESP), Barcelona, Spain
| | - Ines Quintela
- Medicine Genomics Group, University of Santiago de Compostela, Santiago de Compostela, Spain
| | - Dan Mason
- Bradford Institute for Health Research, Bradford Teaching Hospitals NHS Foundation Trust, Bradford, United Kingdom
| | - Solène Cadiou
- University Grenoble Alpes, Inserm, CNRS, Team of Environmental Epidemiology Applied to Reproduction and Respiratory Health, Grenoble, France
| | - Maribel Casas
- Universitat Pompeu Fabra (UPF), Barcelona, Spain.,ISGlobal, Barcelona, Spain
| | - Sandra Andrusaityte
- Department of Environmental Science, Vytautas Magnus University, Kaunas, Lithuania
| | | | - Marina Vafeiadi
- Universitat Pompeu Fabra (UPF), Barcelona, Spain.,ISGlobal, Barcelona, Spain.,Department of Social Medicine, University of Crete, Crete, Greece
| | - John Wright
- Bradford Institute for Health Research, Bradford Teaching Hospitals NHS Foundation Trust, Bradford, United Kingdom
| | - Johanna Lepeule
- University Grenoble Alpes, Inserm, CNRS, Team of Environmental Epidemiology Applied to Reproduction and Respiratory Health, Grenoble, France
| | | | - Leda Chatzi
- Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, Los Angeles, United States
| | - Ángel Carracedo
- Medicine Genomics Group, CIBERER, University of Santiago de Compostela, Santiago de Compostela, Spain.,Galician Foundation of Genomic Medicine, Santiago de Compostela, Spain
| | - Xavier Estivill
- Quantitative Genomics Medicine Laboratories (qGenomics), Esplugues del Llobrega, Barcelona, Spain
| | - Eulàlia Marti
- CIBER Epidemiología y Salud Pública (CIBERESP), Barcelona, Spain.,Departament de Biomedicina, Institut de Neurociències, Universitat de Barcelona, Barcelona, Spain
| | - Geòrgia Escaramís
- CIBER Epidemiología y Salud Pública (CIBERESP), Barcelona, Spain.,Departament de Biomedicina, Institut de Neurociències, Universitat de Barcelona, Barcelona, Spain
| | - Martine Vrijheid
- Universitat Pompeu Fabra (UPF), Barcelona, Spain.,ISGlobal, Barcelona, Spain.,CIBER Epidemiología y Salud Pública (CIBERESP), Barcelona, Spain
| | - Juan R González
- Universitat Pompeu Fabra (UPF), Barcelona, Spain.,ISGlobal, Barcelona, Spain.,CIBER Epidemiología y Salud Pública (CIBERESP), Barcelona, Spain
| | - Mariona Bustamante
- Universitat Pompeu Fabra (UPF), Barcelona, Spain.,ISGlobal, Barcelona, Spain.,CIBER Epidemiología y Salud Pública (CIBERESP), Barcelona, Spain
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6
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How to Slow Down the Ticking Clock: Age-Associated Epigenetic Alterations and Related Interventions to Extend Life Span. Cells 2022; 11:cells11030468. [PMID: 35159278 PMCID: PMC8915189 DOI: 10.3390/cells11030468] [Citation(s) in RCA: 26] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2022] [Accepted: 01/26/2022] [Indexed: 02/04/2023] Open
Abstract
Epigenetic alterations pose one major hallmark of organismal aging. Here, we provide an overview on recent findings describing the epigenetic changes that arise during aging and in related maladies such as neurodegeneration and cancer. Specifically, we focus on alterations of histone modifications and DNA methylation and illustrate the link with metabolic pathways. Age-related epigenetic, transcriptional and metabolic deregulations are highly interconnected, which renders dissociating cause and effect complicated. However, growing amounts of evidence support the notion that aging is not only accompanied by epigenetic alterations, but also at least in part induced by those. DNA methylation clocks emerged as a tool to objectively determine biological aging and turned out as a valuable source in search of factors positively and negatively impacting human life span. Moreover, specific epigenetic signatures can be used as biomarkers for age-associated disorders or even as targets for therapeutic approaches, as will be covered in this review. Finally, we summarize recent potential intervention strategies that target epigenetic mechanisms to extend healthy life span and provide an outlook on future developments in the field of longevity research.
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7
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Epigenetic Clock: DNA Methylation in Aging. Stem Cells Int 2020; 2020:1047896. [PMID: 32724310 PMCID: PMC7366189 DOI: 10.1155/2020/1047896] [Citation(s) in RCA: 27] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2020] [Revised: 06/11/2020] [Accepted: 06/20/2020] [Indexed: 02/07/2023] Open
Abstract
Aging, which is accompanied by decreased organ function and increased disease incidence, limits human lifespan and has attracted investigators for thousands of years. In recent decades, with the rapid development of biology, scientists have shown that epigenetic modifications, especially DNA methylation, are key regulators involved in this process. Regular fluctuations in global DNA methylation levels have been shown to accurately estimate biological age and disease prognosis. In this review, we discuss recent findings regarding the relationship between variations in DNA methylation level patterns and aging. In addition, we introduce the known mechanisms by which DNA methylation regulators affect aging and related diseases. As more studies uncover the mechanisms by which DNA methylation regulates aging, antiaging interventions and treatments for related diseases may be developed that enable human life extension.
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8
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Saare M, Tserel L, Haljasmägi L, Taalberg E, Peet N, Eimre M, Vetik R, Kingo K, Saks K, Tamm R, Milani L, Kisand K, Peterson P. Monocytes present age-related changes in phospholipid concentration and decreased energy metabolism. Aging Cell 2020; 19:e13127. [PMID: 32107839 PMCID: PMC7189998 DOI: 10.1111/acel.13127] [Citation(s) in RCA: 33] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2019] [Revised: 01/21/2020] [Accepted: 02/07/2020] [Indexed: 12/27/2022] Open
Abstract
Age‐related changes at the cellular level include the dysregulation of metabolic and signaling pathways. Analyses of blood leukocytes have revealed a set of alterations that collectively lower their ability to fight infections and resolve inflammation later in life. We studied the transcriptomic, epigenetic, and metabolomic profiles of monocytes extracted from younger adults and individuals over the age of 65 years to map major age‐dependent changes in their cellular physiology. We found that the monocytes from older persons displayed a decrease in the expression of ribosomal and mitochondrial protein genes and exhibited hypomethylation at the HLA class I locus. Additionally, we found elevated gene expression associated with cell motility, including the CX3CR1 and ARID5B genes, which have been associated with the development of atherosclerosis. Furthermore, the downregulation of two genes, PLA2G4B and ALOX15B, which belong to the arachidonic acid metabolism pathway involved in phosphatidylcholine conversion to anti‐inflammatory lipoxins, correlated with increased phosphatidylcholine content in monocytes from older individuals. We found age‐related changes in monocyte metabolic fitness, including reduced mitochondrial function and increased glycose consumption without the capacity to upregulate it during increased metabolic needs, and signs of increased oxidative stress and DNA damage. In conclusion, our results complement existing findings and elucidate the metabolic alterations that occur in monocytes during aging.
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Affiliation(s)
- Mario Saare
- Molecular Pathology Research Group Institute of Biomedicine and Translational Medicine University of Tartu Tartu Estonia
| | - Liina Tserel
- Molecular Pathology Research Group Institute of Biomedicine and Translational Medicine University of Tartu Tartu Estonia
| | - Liis Haljasmägi
- Molecular Pathology Research Group Institute of Biomedicine and Translational Medicine University of Tartu Tartu Estonia
| | - Egon Taalberg
- Department of Biochemistry Institute of Biomedicine and Translational Medicine University of Tartu Tartu Estonia
| | - Nadežda Peet
- Department of Pathophysiology Institute of Biomedicine and Translational Medicine University of Tartu Tartu Estonia
| | - Margus Eimre
- Department of Pathophysiology Institute of Biomedicine and Translational Medicine University of Tartu Tartu Estonia
| | - Rait Vetik
- Molecular Pathology Research Group Institute of Biomedicine and Translational Medicine University of Tartu Tartu Estonia
| | - Külli Kingo
- Department of Dermatology and Venereology Institute of Clinical Medicine University of Tartu Tartu Estonia
- Clinic of Dermatology Tartu University Hospital Tartu Estonia
| | - Kai Saks
- Department of Internal Medicine Institute of Clinical Medicine University of Tartu Tartu Estonia
| | - Riin Tamm
- Laboratory of Immune Analysis, United Laboratories Tartu University Hospital Tartu Estonia
| | - Lili Milani
- Estonian Genome Center Institute of Genomics University of Tartu Tartu Estonia
| | - Kai Kisand
- Molecular Pathology Research Group Institute of Biomedicine and Translational Medicine University of Tartu Tartu Estonia
| | - Pärt Peterson
- Molecular Pathology Research Group Institute of Biomedicine and Translational Medicine University of Tartu Tartu Estonia
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9
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Johnson ND, Huang L, Li R, Li Y, Yang Y, Kim HR, Grant C, Wu H, Whitsel EA, Kiel DP, Baccarelli AA, Jin P, Murabito JM, Conneely KN. Age-related DNA hydroxymethylation is enriched for gene expression and immune system processes in human peripheral blood. Epigenetics 2019; 15:294-306. [PMID: 31506003 DOI: 10.1080/15592294.2019.1666651] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/10/2023] Open
Abstract
DNA methylation (DNAm) has a well-established association with age in many tissues, including peripheral blood mononuclear cells (PBMCs). Compared to DNAm, the closely related epigenetic modification known as DNA hydroxymethylation (DNAhm) was much more recently discovered in mammals. Preliminary investigations have observed a positive correlation between gene body DNAhm and cis-gene expression. While some of these studies have observed an association between age and global DNAhm, none have investigated region-specific age-related DNAhm in human blood samples. In this study, we investigated DNAhm and gene expression in PBMCs of 10 young and 10 old, healthy female volunteers. Thousands of regions were differentially hydroxymethylated in the old vs. young individuals in gene bodies, exonic regions, enhancers, and promoters. Consistent with previous work, we observed directional consistency between age-related differences in DNAhm and gene expression. Further, age-related DNAhm and genes with high levels of DNAhm were enriched for immune system processes which may support a role of age-related DNAhm in immunosenescence.
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Affiliation(s)
- Nicholas D Johnson
- Department of Human Genetics, Emory University, Atlanta, GA, USA.,Population Biology, Ecology, and Evolution Program, Emory University, Atlanta, GA, USA
| | - Luoxiu Huang
- Department of Human Genetics, Emory University, Atlanta, GA, USA
| | - Ronghua Li
- Department of Human Genetics, Emory University, Atlanta, GA, USA
| | - Yun Li
- Department of Genetics, University of North Carolina, Chapel Hill, NC, USA.,Department of Biostatistics, Department of Computer Science, University of North Carolina, Chapel Hill, NC, USA
| | - Yuchen Yang
- Department of Genetics, University of North Carolina, Chapel Hill, NC, USA
| | - Hye Rim Kim
- Department of Human Genetics, Emory University, Atlanta, GA, USA.,Cancer Biology Graduate Program, Emory University, Atlanta, GA, USA
| | - Crystal Grant
- Department of Human Genetics, Emory University, Atlanta, GA, USA.,Genetics and Molecular Biology Graduate Program, Emory University, Atlanta, GA, USA
| | - Hao Wu
- Department of Biostatistics and Bioinformatics, Emory University, Atlanta, GA, USA
| | - Eric A Whitsel
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC, USA.,Department of Medicine, School of Medicine, University of North Carolina, Chapel Hill, NC, USA
| | - Douglas P Kiel
- Hebrew SeniorLife, Department of Medicine Beth Israel Deaconess Medical Center and Harvard Medical School, Hinda and Arthur Marcus Institute for Aging Research, Boston, MA, USA
| | - Andrea A Baccarelli
- Department of Environmental Health Sciences, Mailman School of Public Health, Columbia University, New York, NY, USA
| | - Peng Jin
- Department of Human Genetics, Emory University, Atlanta, GA, USA
| | - Joanne M Murabito
- National Heart Lung and Blood Institute's and Boston University's Framingham Heart Study, Framingham, MA, USA.,Section of General Internal Medicine, Department of Medicine, Boston University School of Medicine, Boston, MA, USA
| | - Karen N Conneely
- Department of Human Genetics, Emory University, Atlanta, GA, USA.,Population Biology, Ecology, and Evolution Program, Emory University, Atlanta, GA, USA
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10
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Zhang Q, Vallerga CL, Walker RM, Lin T, Henders AK, Montgomery GW, He J, Fan D, Fowdar J, Kennedy M, Pitcher T, Pearson J, Halliday G, Kwok JB, Hickie I, Lewis S, Anderson T, Silburn PA, Mellick GD, Harris SE, Redmond P, Murray AD, Porteous DJ, Haley CS, Evans KL, McIntosh AM, Yang J, Gratten J, Marioni RE, Wray NR, Deary IJ, McRae AF, Visscher PM. Improved precision of epigenetic clock estimates across tissues and its implication for biological ageing. Genome Med 2019; 11:54. [PMID: 31443728 PMCID: PMC6708158 DOI: 10.1186/s13073-019-0667-1] [Citation(s) in RCA: 137] [Impact Index Per Article: 27.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2019] [Accepted: 08/16/2019] [Indexed: 12/13/2022] Open
Abstract
BACKGROUND DNA methylation changes with age. Chronological age predictors built from DNA methylation are termed 'epigenetic clocks'. The deviation of predicted age from the actual age ('age acceleration residual', AAR) has been reported to be associated with death. However, it is currently unclear how a better prediction of chronological age affects such association. METHODS In this study, we build multiple predictors based on training DNA methylation samples selected from 13,661 samples (13,402 from blood and 259 from saliva). We use the Lothian Birth Cohorts of 1921 (LBC1921) and 1936 (LBC1936) to examine whether the association between AAR (from these predictors) and death is affected by (1) improving prediction accuracy of an age predictor as its training sample size increases (from 335 to 12,710) and (2) additionally correcting for confounders (i.e., cellular compositions). In addition, we investigated the performance of our predictor in non-blood tissues. RESULTS We found that in principle, a near-perfect age predictor could be developed when the training sample size is sufficiently large. The association between AAR and mortality attenuates as prediction accuracy increases. AAR from our best predictor (based on Elastic Net, https://github.com/qzhang314/DNAm-based-age-predictor ) exhibits no association with mortality in both LBC1921 (hazard ratio = 1.08, 95% CI 0.91-1.27) and LBC1936 (hazard ratio = 1.00, 95% CI 0.79-1.28). Predictors based on small sample size are prone to confounding by cellular compositions relative to those from large sample size. We observed comparable performance of our predictor in non-blood tissues with a multi-tissue-based predictor. CONCLUSIONS This study indicates that the epigenetic clock can be improved by increasing the training sample size and that its association with mortality attenuates with increased prediction of chronological age.
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Affiliation(s)
- Qian Zhang
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, Queensland, 4072, Australia
| | - Costanza L Vallerga
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, Queensland, 4072, Australia
| | - Rosie M Walker
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU, UK
| | - Tian Lin
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, Queensland, 4072, Australia
| | - Anjali K Henders
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, Queensland, 4072, Australia
| | - Grant W Montgomery
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, Queensland, 4072, Australia
| | - Ji He
- Department of Neurology, Peking University, Third Hospital, No. 49, North Garden Road, Haidian District, Beijing, 100191, China
| | - Dongsheng Fan
- Department of Neurology, Peking University, Third Hospital, No. 49, North Garden Road, Haidian District, Beijing, 100191, China
| | - Javed Fowdar
- Griffith Institute for Drug Discovery (GRIDD), Griffith University, Brisbane, Australia
| | - Martin Kennedy
- Department of Pathology and Biomedical Science, University of Otago, Christchurch, New Zealand
| | - Toni Pitcher
- New Zealand Brain Research Institute, Christchurch, New Zealand
- Department of Medicine, University of Otago, Christchurch, New Zealand
| | - John Pearson
- Department of Pathology and Biomedical Science, University of Otago, Christchurch, New Zealand
| | - Glenda Halliday
- Brain and Mind Centre, Sydney Medical School, The University of Sydney, Sydney, Australia
| | - John B Kwok
- Brain and Mind Centre, Sydney Medical School, The University of Sydney, Sydney, Australia
| | - Ian Hickie
- Brain and Mind Centre, Sydney Medical School, The University of Sydney, Sydney, Australia
| | - Simon Lewis
- Brain and Mind Centre, Sydney Medical School, The University of Sydney, Sydney, Australia
| | - Tim Anderson
- New Zealand Brain Research Institute, Christchurch, New Zealand
- Department of Medicine, University of Otago, Christchurch, New Zealand
| | - Peter A Silburn
- Queensland Brain Institute, The University of Queensland, Brisbane, Queensland, 4072, Australia
| | - George D Mellick
- Griffith Institute for Drug Discovery (GRIDD), Griffith University, Brisbane, Australia
| | - Sarah E Harris
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU, UK
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, EH8 9JZ, UK
| | - Paul Redmond
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, EH8 9JZ, UK
| | - Alison D Murray
- Aberdeen Biomedical Imaging Centre, University of Aberdeen, Lilian Sutton Building, Foresterhill, Aberdeen, AB25 2ZD, UK
| | - David J Porteous
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU, UK
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, EH8 9JZ, UK
| | - Christopher S Haley
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU, UK
| | - Kathryn L Evans
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU, UK
| | - Andrew M McIntosh
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU, UK
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, EH8 9JZ, UK
- Division of Psychiatry, University of Edinburgh, Royal Edinburgh Hospital, Edinburgh, EH10 5HF, UK
| | - Jian Yang
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, Queensland, 4072, Australia
| | - Jacob Gratten
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, Queensland, 4072, Australia
- Queensland Brain Institute, The University of Queensland, Brisbane, Queensland, 4072, Australia
| | - Riccardo E Marioni
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU, UK
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, EH8 9JZ, UK
| | - Naomi R Wray
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, Queensland, 4072, Australia
- Queensland Brain Institute, The University of Queensland, Brisbane, Queensland, 4072, Australia
| | - Ian J Deary
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, EH8 9JZ, UK
- Department of Psychology, University of Edinburgh, Edinburgh, EH8 9JZ, UK
| | - Allan F McRae
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, Queensland, 4072, Australia
| | - Peter M Visscher
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, Queensland, 4072, Australia.
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11
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Sturm G, Cardenas A, Bind MA, Horvath S, Wang S, Wang Y, Hägg S, Hirano M, Picard M. Human aging DNA methylation signatures are conserved but accelerated in cultured fibroblasts. Epigenetics 2019; 14:961-976. [PMID: 31156022 DOI: 10.1080/15592294.2019.1626651] [Citation(s) in RCA: 27] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023] Open
Abstract
Aging is associated with progressive and site-specific changes in DNA methylation (DNAm). These global changes are captured by DNAm clocks that accurately predict chronological age in humans but relatively little is known about how clocks perform in vitro. Here we culture primary human fibroblasts across the cellular lifespan (~6 months) and use four different DNAm clocks to show that age-related DNAm signatures are conserved and accelerated in vitro. The Skin & Blood clock shows the best linear correlation with chronological time (r = 0.90), including during replicative senescence. Although similar in nature, the rate of epigenetic aging is approximately 62x times faster in cultured cells than in the human body. Consistent with in vivo data, cells aged under hyperglycemic conditions exhibit an approximately three years elevation in baseline DNAm age. Moreover, candidate gene-based analyses further corroborate the conserved but accelerated biological aging process in cultured fibroblasts. Fibroblasts mirror the established DNAm topology of the age-related ELOVL2 gene in human blood and the rapid hypermethylation of its promoter cg16867657, which correlates with a linear decrease in ELOVL2 mRNA levels across the lifespan. Using generalized additive modeling on twelve timepoints across the lifespan, we also show how single CpGs exhibit loci-specific, linear and nonlinear trajectories that reach rates up to -47% (hypomethylation) to +23% (hypermethylation) per month. Together, these high-temporal resolution global, gene-specific, and single CpG data highlight the conserved and accelerated nature of epigenetic aging in cultured fibroblasts, which may constitute a system to evaluate age-modifying interventions across the lifespan.
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Affiliation(s)
- Gabriel Sturm
- a Department of Psychiatry, Division of Behavioral Medicine, Columbia University Irving Medical Center , New York , NY , USA
| | - Andres Cardenas
- b Division of Environmental Health Sciences, University of California, Berkeley, School of Public Health , Berkeley , CA , USA
| | - Marie-Abèle Bind
- c Department of Statistics, Harvard University , Cambridge , MA , USA
| | - Steve Horvath
- d Human Genetics, David Geffen School of Medicine, University of California Los Angeles , Los Angeles , CA , USA
| | - Shuang Wang
- e Department of Biostatistics, Mailman School of Public Health, Columbia University Medical Center , New York , NY , USA
| | - Yunzhang Wang
- f Department of Medical Epidemiology and Biostatistics, Karolinska Institutet , Stockholm , Sweden
| | - Sara Hägg
- f Department of Medical Epidemiology and Biostatistics, Karolinska Institutet , Stockholm , Sweden
| | - Michio Hirano
- g Department of Neurology, H. Houston Merritt Center, Columbia Translational Neuroscience Initiative, Columbia University Irving Medical Center , New York , NY , USA
| | - Martin Picard
- a Department of Psychiatry, Division of Behavioral Medicine, Columbia University Irving Medical Center , New York , NY , USA.,g Department of Neurology, H. Houston Merritt Center, Columbia Translational Neuroscience Initiative, Columbia University Irving Medical Center , New York , NY , USA.,h Columbia Aging Center, Columbia University Mailman School of Public Health , New York , NY , USA
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12
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Tian CH, Dai J, Zhang W, Liu Y, Yang Y. Expression of IL-17 and its gene promoter methylation status are associated with the progression of chronic hepatitis B virus infection. Medicine (Baltimore) 2019; 98:e15924. [PMID: 31169710 PMCID: PMC6571420 DOI: 10.1097/md.0000000000015924] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/25/2022] Open
Abstract
To explore interleukin-17 (IL-17) and its epigenetic regulation during the progression of chronic hepatitis B virus (HBV) infection.A total of 162 patients with chronic HBV infection, including 75 with chronic hepatitis B (CHB), 54 with hepatitis B-associated liver cirrhosis and 33 with hepatitis B-associated hepatocellular carcinoma (HBV-HCC), were enrolled in this study. Thirty healthy adults of the same ethnicity were enrolled in the control group. Whole venous blood was obtained from the patients and normal controls (n = 30). Clinical and laboratory parameters were assessed, and we performed enzyme-linked immunosorbent assay and quantitative real-time PCR to measure the serum levels and relative mRNA expression of IL-17, respectively. IL-17 promoter methylation in peripheral blood mononuclear cells was assessed by methylation-specific PCR. We analyzed the serum and mRNA levels of IL-17 and IL-17 promoter methylation in the 4 groups as well as the effect of methylation on serum IL-17 levels. Correlations between the IL-17 promoter methylation status and clinical parameters were analyzed by Spearman correlation analysis.Compared to the normal control group, the patient groups exhibited significantly higher serum and relative mRNA levels of IL-17. The methylation distribution among the patients was significantly lower than that among the normal controls (P < .05), with the HBV-HCC group showing the lowest IL-17 gene methylation frequency. The average IL-17 promoter CG methylation level was negatively correlated with IL-17 mRNA expression (r = -0.39, P = .03), and negative correlations between IL-17 promoter methylation and prothrombin time activity (r = -0.585, P = .035), alanine aminotransferase (r = -0.522, P < .01), aspartate aminotransferase (r = -0.315, P < .05), and the model for end-stage liver disease score (r = -0.461, P < .05) were observed. IL-17 serum levels in the methylated-promoter groups were significantly lower than those in the unmethylated-promoter groups.IL-17 expression and promoter methylation were associated with chronic HBV infection progression, especially in the HBV-HCC group. The IL-17 promoter status may help clinicians initiate the correct treatment strategy at the CHB stage.
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Affiliation(s)
- Cui-Huan Tian
- Health Management Center, QiLu Hospital of Shandong University, Jinan, Shandong Province
- School of Medicine, Shandong University
| | - Jun Dai
- Health Management Center, QiLu Hospital of Shandong University, Jinan, Shandong Province
| | - Wei Zhang
- Health Management Center, QiLu Hospital of Shandong University, Jinan, Shandong Province
| | - Yan Liu
- Jinan Infectious Disease Hospital, Jinan, Shandong Province, China
| | - Yan Yang
- Health Management Center, QiLu Hospital of Shandong University, Jinan, Shandong Province
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13
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The role of DNA methylation and hydroxymethylation in immunosenescence. Ageing Res Rev 2019; 51:11-23. [PMID: 30769150 DOI: 10.1016/j.arr.2019.01.011] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2018] [Revised: 01/23/2019] [Accepted: 01/24/2019] [Indexed: 12/12/2022]
Abstract
A healthy functioning immune system is critical to stave off infectious diseases, but as humans and other organisms age, their immune systems decline. As a result, diseases that were readily thwarted in early life pose nontrivial harm and can even be deadly in late life. Immunosenescence is defined as the general deterioration of the immune system with age, and it is characterized by functional changes in hematopoietic stem cells (HSCs) and specific blood cell types as well as changes in levels of numerous factors, particularly those involved in inflammation. Potential mechanisms underlying immunosenescence include epigenetic changes such as changes in DNA methylation (DNAm) and DNA hydroxymethylation (DNAhm) that occur with age. The purpose of this review is to describe what is currently known about the relationship between immunosenescence and the age-related changes to DNAm and DNAhm, and to discuss experimental approaches best suited to fill gaps in our understanding.
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14
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Keenan CR, Allan RS. Epigenomic drivers of immune dysfunction in aging. Aging Cell 2019; 18:e12878. [PMID: 30488545 PMCID: PMC6351880 DOI: 10.1111/acel.12878] [Citation(s) in RCA: 39] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2018] [Revised: 09/26/2018] [Accepted: 10/18/2018] [Indexed: 12/17/2022] Open
Abstract
Aging inevitably leads to reduced immune function, leaving the elderly more susceptible to infections, less able to respond to pathogen challenges, and less responsive to preventative vaccinations. No cell type is exempt from the ravages of age, and extensive studies have found age-related alterations in the frequencies and functions of both stem and progenitor cells, as well as effector cells of both the innate and adaptive immune systems. The intrinsic functional reduction in immune competence is also associated with low-grade chronic inflammation, termed "inflamm-aging," which further perpetuates immune dysfunction. While many of these age-related cellular changes are well characterized, understanding the molecular changes that underpin the functional decline has proven more difficult. Changes in chromatin are increasingly appreciated as a causative mechanism of cellular and organismal aging across species. These changes include increased genomic instability through loss of heterochromatin and increased DNA damage, telomere attrition, and epigenetic alterations. In this review, we discuss the connections between chromatin, immunocompetence, and the loss of function associated with mammalian immune aging. Through understanding the molecular events which underpin the phenotypic changes observed in the aged immune system, it is hoped that the aged immune system can be restored to provide youthful immunity once more.
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Affiliation(s)
- Christine R. Keenan
- The Walter and Eliza Hall Institute of Medical Research Parkville Victoria Australia
- Department of Medical Biology The University of Melbourne Parkville Victoria Australia
| | - Rhys S. Allan
- The Walter and Eliza Hall Institute of Medical Research Parkville Victoria Australia
- Department of Medical Biology The University of Melbourne Parkville Victoria Australia
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15
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Husquin LT, Rotival M, Fagny M, Quach H, Zidane N, McEwen LM, MacIsaac JL, Kobor MS, Aschard H, Patin E, Quintana-Murci L. Exploring the genetic basis of human population differences in DNA methylation and their causal impact on immune gene regulation. Genome Biol 2018; 19:222. [PMID: 30563547 PMCID: PMC6299574 DOI: 10.1186/s13059-018-1601-3] [Citation(s) in RCA: 76] [Impact Index Per Article: 12.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2018] [Accepted: 12/04/2018] [Indexed: 12/12/2022] Open
Abstract
BACKGROUND DNA methylation is influenced by both environmental and genetic factors and is increasingly thought to affect variation in complex traits and diseases. Yet, the extent of ancestry-related differences in DNA methylation, their genetic determinants, and their respective causal impact on immune gene regulation remain elusive. RESULTS We report extensive population differences in DNA methylation between 156 individuals of African and European descent, detected in primary monocytes that are used as a model of a major innate immunity cell type. Most of these differences (~ 70%) are driven by DNA sequence variants nearby CpG sites, which account for ~ 60% of the variance in DNA methylation. We also identify several master regulators of DNA methylation variation in trans, including a regulatory hub nearby the transcription factor-encoding CTCF gene, which contributes markedly to ancestry-related differences in DNA methylation. Furthermore, we establish that variation in DNA methylation is associated with varying gene expression levels following mostly, but not exclusively, a canonical model of negative associations, particularly in enhancer regions. Specifically, we find that DNA methylation highly correlates with transcriptional activity of 811 and 230 genes, at the basal state and upon immune stimulation, respectively. Finally, using a Bayesian approach, we estimate causal mediation effects of DNA methylation on gene expression in ~ 20% of the studied cases, indicating that DNA methylation can play an active role in immune gene regulation. CONCLUSION Using a system-level approach, our study reveals substantial ancestry-related differences in DNA methylation and provides evidence for their causal impact on immune gene regulation.
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Affiliation(s)
- Lucas T. Husquin
- Unit of Human Evolutionary Genetics, Institut Pasteur, 75015 Paris, France
- Centre National de la Recherche Scientifique (CNRS) UMR2000, 75015 Paris, France
- Center of Bioinformatics, Biostatistics and Integrative Biology, Institut Pasteur, 75015 Paris, France
| | - Maxime Rotival
- Unit of Human Evolutionary Genetics, Institut Pasteur, 75015 Paris, France
- Centre National de la Recherche Scientifique (CNRS) UMR2000, 75015 Paris, France
- Center of Bioinformatics, Biostatistics and Integrative Biology, Institut Pasteur, 75015 Paris, France
| | - Maud Fagny
- Laboratory for Epigenetics & Environment, Centre National de Recherche en Génomique Humaine (CNRGH), CEA-Institut de Biologie François Jacob, 91000 Evry, France
| | - Hélène Quach
- Unit of Human Evolutionary Genetics, Institut Pasteur, 75015 Paris, France
- Centre National de la Recherche Scientifique (CNRS) UMR2000, 75015 Paris, France
- Center of Bioinformatics, Biostatistics and Integrative Biology, Institut Pasteur, 75015 Paris, France
| | - Nora Zidane
- Unit of Human Evolutionary Genetics, Institut Pasteur, 75015 Paris, France
- Centre National de la Recherche Scientifique (CNRS) UMR2000, 75015 Paris, France
- Center of Bioinformatics, Biostatistics and Integrative Biology, Institut Pasteur, 75015 Paris, France
| | - Lisa M. McEwen
- Department of Medical Genetics, University of British Columbia, Centre for Molecular Medicine and Therapeutics, BC Children’s Hospital Research Institute, Vancouver, BC Canada
| | - Julia L. MacIsaac
- Department of Medical Genetics, University of British Columbia, Centre for Molecular Medicine and Therapeutics, BC Children’s Hospital Research Institute, Vancouver, BC Canada
| | - Michael S. Kobor
- Department of Medical Genetics, University of British Columbia, Centre for Molecular Medicine and Therapeutics, BC Children’s Hospital Research Institute, Vancouver, BC Canada
| | - Hugues Aschard
- Center of Bioinformatics, Biostatistics and Integrative Biology, Institut Pasteur, 75015 Paris, France
| | - Etienne Patin
- Unit of Human Evolutionary Genetics, Institut Pasteur, 75015 Paris, France
- Centre National de la Recherche Scientifique (CNRS) UMR2000, 75015 Paris, France
- Center of Bioinformatics, Biostatistics and Integrative Biology, Institut Pasteur, 75015 Paris, France
| | - Lluis Quintana-Murci
- Unit of Human Evolutionary Genetics, Institut Pasteur, 75015 Paris, France
- Centre National de la Recherche Scientifique (CNRS) UMR2000, 75015 Paris, France
- Center of Bioinformatics, Biostatistics and Integrative Biology, Institut Pasteur, 75015 Paris, France
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16
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Jasiulionis MG. Abnormal Epigenetic Regulation of Immune System during Aging. Front Immunol 2018; 9:197. [PMID: 29483913 PMCID: PMC5816044 DOI: 10.3389/fimmu.2018.00197] [Citation(s) in RCA: 51] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2017] [Accepted: 01/23/2018] [Indexed: 12/15/2022] Open
Abstract
Epigenetics refers to the study of mechanisms controlling the chromatin structure, which has fundamental role in the regulation of gene expression and genome stability. Epigenetic marks, such as DNA methylation and histone modifications, are established during embryonic development and epigenetic profiles are stably inherited during mitosis, ensuring cell differentiation and fate. Under the effect of intrinsic and extrinsic factors, such as metabolic profile, hormones, nutrition, drugs, smoke, and stress, epigenetic marks are actively modulated. In this sense, the lifestyle may affect significantly the epigenome, and as a result, the gene expression profile and cell function. Epigenetic alterations are a hallmark of aging and diseases, such as cancer. Among biological systems compromised with aging is the decline of immune response. Different regulators of immune response have their promoters and enhancers susceptible to the modulation by epigenetic marks, which is fundamental to the differentiation and function of immune cells. Consistent evidence has showed the regulation of innate immune cells, and T and B lymphocytes by epigenetic mechanisms. Therefore, age-dependent alterations in epigenetic marks may result in the decline of immune function and this might contribute to the increased incidence of diseases in old people. In order to maintain health, we need to better understand how to avoid epigenetic alterations related to immune aging. In this review, the contribution of epigenetic mechanisms to the loss of immune function during aging will be discussed, and the promise of new means of disease prevention and management will be pointed.
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Affiliation(s)
- Miriam G Jasiulionis
- Laboratory of Ontogeny and Epigenetics, Pharmacology Department, Universidade Federal de São Paulo, São Paulo, Brazil
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