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Miao K, Liu S, Cao W, Lv J, Yu C, Huang T, Sun D, Liao C, Pang Y, Hu R, Pang Z, Yu M, Wang H, Wu X, Liu Y, Gao W, Li L. Five years of change in adult twins: longitudinal changes of genetic and environmental influence on epigenetic clocks. BMC Med 2024; 22:289. [PMID: 38987783 PMCID: PMC11234599 DOI: 10.1186/s12916-024-03511-y] [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: 03/11/2024] [Accepted: 07/02/2024] [Indexed: 07/12/2024] Open
Abstract
BACKGROUND Epigenetic clocks were known as promising biomarkers of aging, including original clocks trained by individual CpG sites and principal component (PC) clocks trained by PCs of CpG sites. The effects of genetic and environmental factors on epigenetic clocks are still unclear, especially for PC clocks. METHODS We constructed univariate twin models in 477 same-sex twin pairs from the Chinese National Twin Registry (CNTR) to estimate the heritability of five epigenetic clocks (GrimAge, PhenoAge, DunedinPACE, PCGrimAge, and PCPhenoAge). Besides, we investigated the longitudinal changes of genetic and environmental influences on epigenetic clocks across 5 years in 134 same-sex twin pairs. RESULTS Heritability of epigenetic clocks ranged from 0.45 to 0.70, and those for PC clocks were higher than those for original clocks. For five epigenetic clocks, the longitudinal stability was moderate to high and was largely due to genetic effects. The genetic correlations between baseline and follow-up epigenetic clocks were moderate to high. Special unique environmental factors emerged both at baseline and at follow-up. PC clocks showed higher longitudinal stability and unique environmental correlations than original clocks. CONCLUSIONS For five epigenetic clocks, they have the potential to identify aging interventions. High longitudinal stability is mainly due to genetic factors, and changes of epigenetic clocks over time are primarily due to changes in unique environmental factors. Given the disparities in genetic and environmental factors as well as longitudinal stability between PC and original clocks, the results of studies with original clocks need to be further verified with PC clocks.
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Affiliation(s)
- Ke Miao
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, 100191, China
- Key Laboratory of Epidemiology of Major Diseases, (Peking University), Ministry of Education, Beijing, 100191, China
| | - Shunkai Liu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, 100191, China
- Key Laboratory of Epidemiology of Major Diseases, (Peking University), Ministry of Education, Beijing, 100191, China
| | - Weihua Cao
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, 100191, China
- Key Laboratory of Epidemiology of Major Diseases, (Peking University), Ministry of Education, Beijing, 100191, China
| | - Jun Lv
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, 100191, China
- Key Laboratory of Epidemiology of Major Diseases, (Peking University), Ministry of Education, Beijing, 100191, China
| | - Canqing Yu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, 100191, China
- Key Laboratory of Epidemiology of Major Diseases, (Peking University), Ministry of Education, Beijing, 100191, China
| | - Tao Huang
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, 100191, China
- Key Laboratory of Epidemiology of Major Diseases, (Peking University), Ministry of Education, Beijing, 100191, China
| | - Dianjianyi Sun
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, 100191, China
- Key Laboratory of Epidemiology of Major Diseases, (Peking University), Ministry of Education, Beijing, 100191, China
| | - Chunxiao Liao
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, 100191, China
- Key Laboratory of Epidemiology of Major Diseases, (Peking University), Ministry of Education, Beijing, 100191, China
| | - Yuanjie Pang
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, 100191, China
- Key Laboratory of Epidemiology of Major Diseases, (Peking University), Ministry of Education, Beijing, 100191, China
| | - Runhua Hu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, 100191, China
- Key Laboratory of Epidemiology of Major Diseases, (Peking University), Ministry of Education, Beijing, 100191, China
| | - Zengchang Pang
- Qingdao Center for Disease Control and Prevention, Qingdao, China
| | - Min Yu
- Zhejiang Center for Disease Control and Prevention, Hangzhou, China
| | - Hua Wang
- Jiangsu Center for Disease Control and Prevention, Nanjing, China
| | - Xianping Wu
- Sichuan Center for Disease Control and Prevention, Chengdu, China
| | - Yu Liu
- Heilongjiang Center for Disease Control and Prevention, Harbin, China
| | - Wenjing Gao
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, 100191, China.
- Key Laboratory of Epidemiology of Major Diseases, (Peking University), Ministry of Education, Beijing, 100191, China.
| | - Liming Li
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, 100191, China.
- Key Laboratory of Epidemiology of Major Diseases, (Peking University), Ministry of Education, Beijing, 100191, China.
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2
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Felt JM, Yusupov N, Harrington KD, Fietz J, Zhang Z“Z, Sliwinski MJ, Ram N, O'Donnell KJ, Meaney MJ, Putnam FW, Noll JG, Binder EB, Shenk CE. Epigenetic age acceleration as a biomarker for impaired cognitive abilities in adulthood following early life adversity and psychiatric disorders. Neurobiol Stress 2023; 27:100577. [PMID: 37885906 PMCID: PMC10597797 DOI: 10.1016/j.ynstr.2023.100577] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2023] [Revised: 09/20/2023] [Accepted: 09/23/2023] [Indexed: 10/28/2023] Open
Abstract
Background Early life adversity and psychiatric disorders are associated with earlier declines in neurocognitive abilities during adulthood. These declines may be preceded by changes in biological aging, specifically epigenetic age acceleration, providing an opportunity to uncover genome-wide biomarkers that identify individuals most likely to benefit from early screening and prevention. Methods Five unique epigenetic age acceleration clocks derived from peripheral blood were examined in relation to latent variables of general and speeded cognitive abilities across two independent cohorts: 1) the Female Growth and Development Study (FGDS; n = 86), a 30-year prospective cohort study of substantiated child sexual abuse and non-abused controls, and 2) the Biological Classification of Mental Disorders study (BeCOME; n = 313), an adult community cohort established based on psychiatric disorders. Results A faster pace of biological aging (DunedinPoAm) was associated with lower general cognitive abilities in both cohorts and slower speeded abilities in the BeCOME cohort. Acceleration in the Horvath clock was significantly associated with slower speeded abilities in the BeCOME cohort but not the FGDS. Acceleration in the Hannum clock and the GrimAge clock were not significantly associated with either cognitive ability. Accelerated PhenoAge was associated with slower speeded abilities in the FGDS but not the BeCOME cohort. Conclusions The present results suggest that epigenetic age acceleration has the potential to serve as a biomarker for neurocognitive decline in adults with a history of early life adversity or psychiatric disorders. Estimates of epigenetic aging may identify adults at risk of cognitive decline that could benefit from early neurocognitive screening.
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Affiliation(s)
- John M. Felt
- Center for Healthy Aging, The Pennsylvania State University, United States
| | - Natan Yusupov
- Department Genes and Environment, Max Planck Institute of Psychiatry - Munich, Germany
- International Max Planck Research School for Translational Psychiatry, Max Planck Institute of Psychiatry, Germany
| | | | - Julia Fietz
- Department Genes and Environment, Max Planck Institute of Psychiatry - Munich, Germany
- International Max Planck Research School for Translational Psychiatry, Max Planck Institute of Psychiatry, Germany
| | | | - Martin J. Sliwinski
- Center for Healthy Aging, The Pennsylvania State University, United States
- Department of Human Development and Family Studies, The Pennsylvania State University, United States
| | - Nilam Ram
- Department of Communications, Stanford University, United States
- Department of Psychology, Stanford University, United States
| | - Kieran J. O'Donnell
- Child Study Center, Yale University, United States
- Department of Obstetrics, Gynecology, and Reproductive Sciences, Yale University, United States
- The Douglas Hospital Research Centre, Department of Psychiatry, McGill University, Canada
- Child and Brain Development Program, Canadian Institute for Advanced Research, Canada
| | - BeCOME Working Group
- Department Genes and Environment, Max Planck Institute of Psychiatry - Munich, Germany
- Max Planck Institute of Psychiatry, Munich, Germany
| | - Michael J. Meaney
- The Douglas Hospital Research Centre, Department of Psychiatry, McGill University, Canada
- Child and Brain Development Program, Canadian Institute for Advanced Research, Canada
- Singapore Institute of Clinical Sciences, Singapore
| | - Frank W. Putnam
- Department of Psychiatry, University of North Carolina School of Medicine, United States
| | - Jennie G. Noll
- Department of Human Development and Family Studies, The Pennsylvania State University, United States
| | - Elisabeth B. Binder
- Department Genes and Environment, Max Planck Institute of Psychiatry - Munich, Germany
- Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, United States
| | - Chad E. Shenk
- Department of Human Development and Family Studies, The Pennsylvania State University, United States
- Department of Pediatrics, The Pennsylvania State University College of Medicine, United States
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3
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Watkins SH, Testa C, Chen JT, De Vivo I, Simpkin AJ, Tilling K, Diez Roux AV, Davey Smith G, Waterman PD, Suderman M, Relton C, Krieger N. Epigenetic clocks and research implications of the lack of data on whom they have been developed: a review of reported and missing sociodemographic characteristics. ENVIRONMENTAL EPIGENETICS 2023; 9:dvad005. [PMID: 37564905 PMCID: PMC10411856 DOI: 10.1093/eep/dvad005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/20/2023] [Revised: 06/17/2023] [Accepted: 07/13/2023] [Indexed: 08/12/2023]
Abstract
Epigenetic clocks are increasingly being used as a tool to assess the impact of a wide variety of phenotypes and exposures on healthy ageing, with a recent focus on social determinants of health. However, little attention has been paid to the sociodemographic characteristics of participants on whom these clocks have been based. Participant characteristics are important because sociodemographic and socioeconomic factors are known to be associated with both DNA methylation variation and healthy ageing. It is also well known that machine learning algorithms have the potential to exacerbate health inequities through the use of unrepresentative samples - prediction models may underperform in social groups that were poorly represented in the training data used to construct the model. To address this gap in the literature, we conducted a review of the sociodemographic characteristics of the participants whose data were used to construct 13 commonly used epigenetic clocks. We found that although some of the epigenetic clocks were created utilizing data provided by individuals from different ages, sexes/genders, and racialized groups, sociodemographic characteristics are generally poorly reported. Reported information is limited by inadequate conceptualization of the social dimensions and exposure implications of gender and racialized inequality, and socioeconomic data are infrequently reported. It is important for future work to ensure clear reporting of tangible data on the sociodemographic and socioeconomic characteristics of all the participants in the study to ensure that other researchers can make informed judgements about the appropriateness of the model for their study population.
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Affiliation(s)
- Sarah Holmes Watkins
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol BS8 2BN, UK
- Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol BS8 2BN, UK
| | - Christian Testa
- Department of Social and Behavioral Sciences, Harvard T.H. Chan School of Public Health, Harvard University, Boston, MA 02115, USA
| | - Jarvis T Chen
- Department of Social and Behavioral Sciences, Harvard T.H. Chan School of Public Health, Harvard University, Boston, MA 02115, USA
| | - Immaculata De Vivo
- Program in Genetic Epidemiology and Statistical Genetics, Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA
- Department of Medicine, Harvard Medical School, Brigham and Women’s Hospital, Boston, MA 02115, USA
| | - Andrew J Simpkin
- School of Medicine, National University of Ireland Galway, Galway H91 TK33, Ireland
| | - Kate Tilling
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol BS8 2BN, UK
- Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol BS8 2BN, UK
| | - Ana V Diez Roux
- Department of Epidemiology and Biostatistics and Urban Health Collaborative, Dornsife School of Public Health, Drexel University, Philadelphia, PA 19104, USA
| | - George Davey Smith
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol BS8 2BN, UK
- Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol BS8 2BN, UK
| | - Pamela D Waterman
- Department of Social and Behavioral Sciences, Harvard T.H. Chan School of Public Health, Harvard University, Boston, MA 02115, USA
| | - Matthew Suderman
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol BS8 2BN, UK
- Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol BS8 2BN, UK
| | - Caroline Relton
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol BS8 2BN, UK
- Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol BS8 2BN, UK
| | - Nancy Krieger
- Department of Social and Behavioral Sciences, Harvard T.H. Chan School of Public Health, Harvard University, Boston, MA 02115, USA
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Petrican R, Paine AL, Escott-Price V, Shelton KH. Overlapping brain correlates of superior cognition among children at genetic risk for Alzheimer's disease and/or major depressive disorder. Sci Rep 2023; 13:984. [PMID: 36653486 PMCID: PMC9849214 DOI: 10.1038/s41598-023-28057-6] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2022] [Accepted: 01/12/2023] [Indexed: 01/19/2023] Open
Abstract
Early life adversity (ELA) tends to accelerate neurobiological ageing, which, in turn, is thought to heighten vulnerability to both major depressive disorder (MDD) and Alzheimer's disease (AD). The two conditions are putatively related, with MDD representing either a risk factor or early symptom of AD. Given the substantial environmental susceptibility of both disorders, timely identification of their neurocognitive markers could facilitate interventions to prevent clinical onset. To this end, we analysed multimodal data from the Adolescent Brain and Cognitive Development study (ages 9-10 years). To disentangle genetic from correlated genetic-environmental influences, while also probing gene-adversity interactions, we compared adoptees, a group generally exposed to substantial ELA, with children raised by their biological families via genetic risk scores (GRS) from genome-wide association studies. AD and MDD GRSs predicted overlapping and widespread neurodevelopmental alterations associated with superior fluid cognition. Specifically, among adoptees only, greater AD GRS were related to accelerated structural maturation (i.e., cortical thinning) and higher MDD GRS were linked to delayed functional neurodevelopment, as reflected in compensatory brain activation on an inhibitory control task. Our study identifies compensatory mechanisms linked to MDD risk and highlights the potential cognitive benefits of accelerated maturation linked to AD vulnerability in late childhood.
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Affiliation(s)
- Raluca Petrican
- Institute of Population Health, Department of Psychology, University of Liverpool, Bedford Street South, Liverpool, L69 7ZA, UK.
| | - Amy L Paine
- School of Psychology, Cardiff University, 70 Park Place, Cardiff, CF10 3AT, UK
| | - Valentina Escott-Price
- Division of Neuroscience and Mental Health, School of Medicine, Cardiff University, Maindy Road, Cardiff, CF24 4HQ, UK
| | - Katherine H Shelton
- School of Psychology, Cardiff University, 70 Park Place, Cardiff, CF10 3AT, UK
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5
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Zhou A, Wu Z, Zaw Phyo AZ, Torres D, Vishwanath S, Ryan J. Epigenetic aging as a biomarker of dementia and related outcomes: a systematic review. Epigenomics 2022; 14:1125-1138. [PMID: 36154448 DOI: 10.2217/epi-2022-0209] [Citation(s) in RCA: 21] [Impact Index Per Article: 10.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022] Open
Abstract
Background: Biological aging may be a robust biomarker of dementia or cognitive performance. This systematic review synthesized the evidence for an association between epigenetic aging and dementia, mild cognitive impairment and cognitive function. Methods: A systematic search was conducted according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Results: 30 eligible articles were included. There was no strong evidence that accelerated epigenetic aging was associated with dementia/mild cognitive impairment (n = 7). There was some evidence of an association with poorer cognition (n = 20), particularly with GrimAge acceleration, but this was inconsistent and varied across cognitive domains. A meta-analysis was not performed due to high study heterogeneity. Conclusion: There is insufficient evidence to indicate that current epigenetic aging clocks can be clinically useful biomarkers of dementia or cognitive aging.
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Affiliation(s)
- Aoshuang Zhou
- Division of Epidemiology, Jockey Club School of Public Health & Primary Care, Chinese University of Hong Kong, Hong Kong, China
| | - Zimu Wu
- Biological Neuropsychiatry & Dementia Unit, School of Public Health & Preventive Medicine, Monash University, Melbourne, Victoria, 3004, Australia
| | - Aung Zaw Zaw Phyo
- Biological Neuropsychiatry & Dementia Unit, School of Public Health & Preventive Medicine, Monash University, Melbourne, Victoria, 3004, Australia
| | - Daniel Torres
- Biological Neuropsychiatry & Dementia Unit, School of Public Health & Preventive Medicine, Monash University, Melbourne, Victoria, 3004, Australia
| | - Swarna Vishwanath
- Biological Neuropsychiatry & Dementia Unit, School of Public Health & Preventive Medicine, Monash University, Melbourne, Victoria, 3004, Australia
| | - Joanne Ryan
- Biological Neuropsychiatry & Dementia Unit, School of Public Health & Preventive Medicine, Monash University, Melbourne, Victoria, 3004, Australia
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6
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Walhovd KB, Nyberg L, Lindenberger U, Amlien IK, Sørensen Ø, Wang Y, Mowinckel AM, Kievit RA, Ebmeier KP, Bartrés-Faz D, Kühn S, Boraxbekk CJ, Ghisletta P, Madsen KS, Baaré WFC, Zsoldos E, Magnussen F, Vidal-Piñeiro D, Penninx B, Fjell AM. Brain aging differs with cognitive ability regardless of education. Sci Rep 2022; 12:13886. [PMID: 35974034 PMCID: PMC9381768 DOI: 10.1038/s41598-022-17727-6] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2022] [Accepted: 07/29/2022] [Indexed: 11/23/2022] Open
Abstract
Higher general cognitive ability (GCA) is associated with lower risk of neurodegenerative disorders, but neural mechanisms are unknown. GCA could be associated with more cortical tissue, from young age, i.e. brain reserve, or less cortical atrophy in adulthood, i.e. brain maintenance. Controlling for education, we investigated the relative association of GCA with reserve and maintenance of cortical volume, -area and -thickness through the adult lifespan, using multiple longitudinal cognitively healthy brain imaging cohorts (n = 3327, 7002 MRI scans, baseline age 20-88 years, followed-up for up to 11 years). There were widespread positive relationships between GCA and cortical characteristics (level-level associations). In select regions, higher baseline GCA was associated with less atrophy over time (level-change associations). Relationships remained when controlling for polygenic scores for both GCA and education. Our findings suggest that higher GCA is associated with cortical volumes by both brain reserve and -maintenance mechanisms through the adult lifespan.
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Affiliation(s)
- Kristine B Walhovd
- Center for Lifespan Changes in Brain and Cognition, University of Oslo, Blindern, POB1094, 0317, Oslo, Norway.
- Department of Radiology and Nuclear Medicine, Oslo University Hospital, Oslo, Norway.
| | - Lars Nyberg
- Center for Lifespan Changes in Brain and Cognition, University of Oslo, Blindern, POB1094, 0317, Oslo, Norway
- Umeå Center for Functional Brain Imaging, Umeå University, Umeå, Sweden
| | - Ulman Lindenberger
- Center for Lifespan Psychology, Max Planck Institute for Human Development, Berlin, Germany
- Max Planck UCL Centre for Computational Psychiatry and Ageing Research, Berlin, Germany
- Max Planck UCL Centre for Computational Psychiatry and Ageing Research, London, UK
| | - Inge K Amlien
- Center for Lifespan Changes in Brain and Cognition, University of Oslo, Blindern, POB1094, 0317, Oslo, Norway
| | - Øystein Sørensen
- Center for Lifespan Changes in Brain and Cognition, University of Oslo, Blindern, POB1094, 0317, Oslo, Norway
| | - Yunpeng Wang
- Center for Lifespan Changes in Brain and Cognition, University of Oslo, Blindern, POB1094, 0317, Oslo, Norway
| | - Athanasia M Mowinckel
- Center for Lifespan Changes in Brain and Cognition, University of Oslo, Blindern, POB1094, 0317, Oslo, Norway
| | - Rogier A Kievit
- Cognitive Neuroscience Department, Donders Institute for Brain, Cognition and Behavior, The Netherlands, Radboud University Medical Center, Nijmegen, The Netherlands
| | | | - David Bartrés-Faz
- Department of Medicine, Faculty of Medicine and Health Sciences & Institute of Neurosciences, Universitat de Barcelona, and Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain
| | - Simone Kühn
- Center for Lifespan Psychology, Max Planck Institute for Human Development, Berlin, Germany
- Clinic and Policlinic for Psychiatry and Psychotherapy, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Carl-Johan Boraxbekk
- Umeå Center for Functional Brain Imaging, Umeå University, Umeå, Sweden
- Danish Research Centre for Magnetic Resonance (DRCMR), Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital - Amager and Hvidovre, Copenhagen, Denmark
- Department of Radiation Sciences, Diagnostic Radiology, Umeå University, Umeå, Sweden
- Institute of Sports Medicine Copenhagen (ISMC) and Department of Neurology, Copenhagen University Hospital Bispebjerg, Copenhagen, Denmark
- Institute for Clinical Medicine, Faculty of Medical and Health Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Paolo Ghisletta
- Faculty of Psychology and Educational Sciences, University of Geneva, Geneva, Switzerland
- UniDistance Suisse, Brig, Switzerland
- Swiss National Centre of Competence in Research LIVES, University of Geneva, Geneva, Switzerland
| | - Kathrine Skak Madsen
- Danish Research Centre for Magnetic Resonance (DRCMR), Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital - Amager and Hvidovre, Copenhagen, Denmark
- Radiography, Department of Technology, University College Copenhagen, Copenhagen, Denmark
| | - Willliam F C Baaré
- Danish Research Centre for Magnetic Resonance (DRCMR), Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital - Amager and Hvidovre, Copenhagen, Denmark
| | - Enikő Zsoldos
- Department of Psychiatry, University of Oxford, Oxford, UK
- Welcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, UK
| | - Fredrik Magnussen
- Center for Lifespan Changes in Brain and Cognition, University of Oslo, Blindern, POB1094, 0317, Oslo, Norway
| | - Didac Vidal-Piñeiro
- Center for Lifespan Changes in Brain and Cognition, University of Oslo, Blindern, POB1094, 0317, Oslo, Norway
| | - Brenda Penninx
- Amsterdam Neuroscience, Department of Psychiatry, Amsterdam UMC, Vrije Universiteit, Amsterdam, The Netherlands
| | - Anders M Fjell
- Center for Lifespan Changes in Brain and Cognition, University of Oslo, Blindern, POB1094, 0317, Oslo, Norway
- Department of Radiology and Nuclear Medicine, Oslo University Hospital, Oslo, Norway
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7
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Reale A, Tagliatesta S, Zardo G, Zampieri M. Counteracting aged DNA methylation states to combat ageing and age-related diseases. Mech Ageing Dev 2022; 206:111695. [PMID: 35760211 DOI: 10.1016/j.mad.2022.111695] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2022] [Revised: 06/09/2022] [Accepted: 06/22/2022] [Indexed: 12/18/2022]
Abstract
DNA methylation (DNAm) overwrites information about multiple extrinsic factors on the genome. Age is one of these factors. Age causes characteristic DNAm changes that are thought to be not only major drivers of normal ageing but also precursors to diseases, cancer being one of these. Although there is still much to learn about the relationship between ageing, age-related diseases and DNAm, we now know how to interpret some of the effects caused by age in the form of changes in methylation marks at specific loci. In fact, these changes form the basis of the so called "epigenetic clocks", which translate the genomic methylation profile into an "epigenetic age". Epigenetic age does not only estimate chronological age but can also predict the risk of chronic diseases and mortality. Epigenetic age is believed to be one of the most accurate metrics of biological age. Initial evidence has recently been gathered pointing to the possibility that the rate of epigenetic ageing can be slowed down or even reversed. In this review, we discuss some of the most relevant advances in this field. Expected outcome is that this approach can provide insights into how to preserve health and reduce the impact of ageing diseases in humans.
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Affiliation(s)
- Anna Reale
- Department of Experimental Medicine, Sapienza University of Rome, 00161 Rome, Italy.
| | - Stefano Tagliatesta
- Department of Biology and Biotechnology "Charles Darwin", Sapienza University of Rome, 00161 Rome, Italy.
| | - Giuseppe Zardo
- Department of Experimental Medicine, Sapienza University of Rome, 00161 Rome, Italy.
| | - Michele Zampieri
- Department of Experimental Medicine, Sapienza University of Rome, 00161 Rome, Italy.
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8
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Hillary RF, Stevenson AJ, Cox SR, McCartney DL, Harris SE, Seeboth A, Higham J, Sproul D, Taylor AM, Redmond P, Corley J, Pattie A, Hernández MDCV, Muñoz-Maniega S, Bastin ME, Wardlaw JM, Horvath S, Ritchie CW, Spires-Jones TL, McIntosh AM, Evans KL, Deary IJ, Marioni RE. An epigenetic predictor of death captures multi-modal measures of brain health. Mol Psychiatry 2021; 26:3806-3816. [PMID: 31796892 PMCID: PMC8550950 DOI: 10.1038/s41380-019-0616-9] [Citation(s) in RCA: 66] [Impact Index Per Article: 22.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/30/2019] [Revised: 11/14/2019] [Accepted: 11/20/2019] [Indexed: 11/08/2022]
Abstract
Individuals of the same chronological age exhibit disparate rates of biological ageing. Consequently, a number of methodologies have been proposed to determine biological age and primarily exploit variation at the level of DNA methylation (DNAm). A novel epigenetic clock, termed 'DNAm GrimAge' has outperformed its predecessors in predicting the risk of mortality as well as many age-related morbidities. However, the association between DNAm GrimAge and cognitive or neuroimaging phenotypes remains unknown. We explore these associations in the Lothian Birth Cohort 1936 (n = 709, mean age 73 years). Higher DNAm GrimAge was strongly associated with all-cause mortality over the eighth decade (Hazard Ratio per standard deviation increase in GrimAge: 1.81, P < 2.0 × 10-16). Higher DNAm GrimAge was associated with lower age 11 IQ (β = -0.11), lower age 73 general cognitive ability (β = -0.18), decreased brain volume (β = -0.25) and increased brain white matter hyperintensities (β = 0.17). There was tentative evidence for a longitudinal association between DNAm GrimAge and cognitive decline from age 70 to 79. Sixty-nine of 137 health- and brain-related phenotypes tested were significantly associated with GrimAge. Adjusting all models for childhood intelligence attenuated to non-significance a small number of associations (12/69 associations; 6 of which were cognitive traits), but not the association with general cognitive ability (33.9% attenuation). Higher DNAm GrimAge associates with lower cognitive ability and brain vascular lesions in older age, independently of early-life cognitive ability. This epigenetic predictor of mortality associates with different measures of brain health and may aid in the prediction of age-related cognitive decline.
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Affiliation(s)
- Robert F Hillary
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK
| | - Anna J Stevenson
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK
| | - Simon R Cox
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
- Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - Daniel L McCartney
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK
| | - Sarah E Harris
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
- Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - Anne Seeboth
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK
| | - Jon Higham
- Medical Research Council Human Genetics Unit, Medical Research Council Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK
| | - Duncan Sproul
- Medical Research Council Human Genetics Unit, Medical Research Council Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK
- Edinburgh Cancer Research Centre, Medical Research Council Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK
| | - Adele M Taylor
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
- Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - Paul Redmond
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
- Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - Janie Corley
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
- Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - Alison Pattie
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
- Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - Maria Del C Valdés Hernández
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
- Department of Neuroimaging Sciences, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - Susana Muñoz-Maniega
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
- Department of Neuroimaging Sciences, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - Mark E Bastin
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
- Department of Neuroimaging Sciences, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - Joanna M Wardlaw
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
- Department of Neuroimaging Sciences, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
- UK Dementia Research Institute, Edinburgh Medical School, University of Edinburgh, Edinburgh, UK
| | - Steve Horvath
- Department of Human Genetics, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California, USA
- Department of Biostatistics, Fielding School of Public Health, University of California Los Angeles, Los Angeles, California, USA
| | - Craig W Ritchie
- Edinburgh Dementia Prevention, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - Tara L Spires-Jones
- UK Dementia Research Institute, Edinburgh Medical School, University of Edinburgh, Edinburgh, UK
- Centre for Discovery Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - Andrew M McIntosh
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
- Division of Psychiatry, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - Kathryn L Evans
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
| | - Ian J Deary
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
- Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - Riccardo E Marioni
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK.
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK.
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9
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Higgins-Chen AT, Thrush KL, Levine ME. Aging biomarkers and the brain. Semin Cell Dev Biol 2021; 116:180-193. [PMID: 33509689 PMCID: PMC8292153 DOI: 10.1016/j.semcdb.2021.01.003] [Citation(s) in RCA: 32] [Impact Index Per Article: 10.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2020] [Revised: 01/18/2021] [Accepted: 01/19/2021] [Indexed: 12/15/2022]
Abstract
Quantifying biological aging is critical for understanding why aging is the primary driver of morbidity and mortality and for assessing novel therapies to counter pathological aging. In the past decade, many biomarkers relevant to brain aging have been developed using various data types and modeling techniques. Aging involves numerous interconnected processes, and thus many complementary biomarkers are needed, each capturing a different slice of aging biology. Here we present a hierarchical framework highlighting how these biomarkers are related to each other and the underlying biological processes. We review those measures most studied in the context of brain aging: epigenetic clocks, proteomic clocks, and neuroimaging age predictors. Many studies have linked these biomarkers to cognition, mental health, brain structure, and pathology during aging. We also delve into the challenges and complexities in interpreting these biomarkers and suggest areas for further innovation. Ultimately, a robust mechanistic understanding of these biomarkers will be needed to effectively intervene in the aging process to prevent and treat age-related disease.
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Affiliation(s)
- Albert T Higgins-Chen
- Department of Psychiatry, Yale University School of Medicine, 300 George St, Suite 901, New Haven, CT 06511, USA.
| | - Kyra L Thrush
- Program in Computational Biology and Bioinformatics, Yale University, 300 George St, Suite 501, New Haven, CT 06511, USA.
| | - Morgan E Levine
- Department of Pathology, Yale University School of Medicine, 310 Cedar Street, Suite LH 315A, New Haven, CT 06520, USA.
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10
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KANKAANPÄÄ ANNA, TOLVANEN ASKO, BOLLEPALLI SAILALITHA, LESKINEN TUIJA, KUJALA URHOM, KAPRIO JAAKKO, OLLIKAINEN MIINA, SILLANPÄÄ ELINA. Leisure-Time and Occupational Physical Activity Associates Differently with Epigenetic Aging. Med Sci Sports Exerc 2021; 53:487-495. [PMID: 32868581 PMCID: PMC7886335 DOI: 10.1249/mss.0000000000002498] [Citation(s) in RCA: 24] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
PURPOSE Greater leisure-time physical activity (LTPA) associates with healthier lives, but knowledge regarding occupational physical activity (OPA) is more inconsistent. DNA methylation (DNAm) patterns capture age-related changes in different tissues. We aimed to assess how LTPA and OPA are associated with three DNAm-based epigenetic age estimates, namely, DNAm age, PhenoAge, and GrimAge. METHODS The participants were young adult (21-25 yr, n = 285) and older (55-74 yr, n = 235) twin pairs, including 16 pairs with documented long-term LTPA discordance. Genome-wide DNAm from blood samples was used to compute DNAm age, PhenoAge, and GrimAge Age acceleration (Acc), which describes the difference between chronological and epigenetic ages. Physical activity was assessed with sport, leisure-time, and work indices based on the Baecke Questionnaire. Genetic and environmental variance components of epigenetic age Acc were estimated by quantitative genetic modeling. RESULTS Epigenetic age Acc was highly heritable in young adult and older twin pairs (~60%). Sport index was associated with slower and OPA with faster DNAm GrimAge Acc after adjusting the model for sex. Genetic factors and nonshared environmental factors in common with sport index explained 1.5%-2.7% and 1.9%-3.5%, respectively, of the variation in GrimAge Acc. The corresponding proportions considering OPA were 0.4%-1.8% and 0.7%-1.8%, respectively. However, these proportions were minor (<0.5%) after adjusting the model for smoking status. CONCLUSIONS LTPA associates with slower and OPA with faster epigenetic aging. However, adjusting the models for smoking status, which may reflect the accumulation of unhealthy lifestyle habits, attenuated the associations.
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Affiliation(s)
- ANNA KANKAANPÄÄ
- Gerontology Research Center, Faculty of Sport and Health Sciences, University of Jyväskylä, Jyväskylä, FINLAND
| | - ASKO TOLVANEN
- Methodology Center for Human Sciences, University of Jyväskylä, Jyväskylä, FINLAND
| | - SAILALITHA BOLLEPALLI
- Institute for Molecular Medicine Finland (FIMM), HiLife, University of Helsinki, Helsinki, FINLAND
| | - TUIJA LESKINEN
- Department of Public Health, University of Turku and Turku University Hospital, Turku, FINLAND
| | - URHO M. KUJALA
- Faculty of Sport and Health Sciences, University of Jyväskylä, Jyväskylä, FINLAND
| | - JAAKKO KAPRIO
- Institute for Molecular Medicine Finland (FIMM), HiLife, University of Helsinki, Helsinki, FINLAND
- Department of Public Health, University of Helsinki, Helsinki, FINLAND
| | - MIINA OLLIKAINEN
- Institute for Molecular Medicine Finland (FIMM), HiLife, University of Helsinki, Helsinki, FINLAND
- Department of Public Health, University of Helsinki, Helsinki, FINLAND
| | - ELINA SILLANPÄÄ
- Gerontology Research Center, Faculty of Sport and Health Sciences, University of Jyväskylä, Jyväskylä, FINLAND
- Institute for Molecular Medicine Finland (FIMM), HiLife, University of Helsinki, Helsinki, FINLAND
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11
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Wehrle FM, Caflisch J, Eichelberger DA, Haller G, Latal B, Largo RH, Kakebeeke TH, Jenni OG. The Importance of Childhood for Adult Health and Development-Study Protocol of the Zurich Longitudinal Studies. Front Hum Neurosci 2021; 14:612453. [PMID: 33633550 PMCID: PMC7901945 DOI: 10.3389/fnhum.2020.612453] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2020] [Accepted: 12/23/2020] [Indexed: 11/13/2022] Open
Abstract
Evidence is accumulating that individual and environmental factors in childhood and adolescence should be considered when investigating adult health and aging-related processes. The data required for this is gathered by comprehensive long-term longitudinal studies. This article describes the protocol of the Zurich Longitudinal Studies (ZLS), a set of three comprehensive cohort studies on child growth, health, and development that are currently expanding into adulthood. Between 1954 and 1961, 445 healthy infants were enrolled in the first ZLS cohort. Their physical, motor, cognitive, and social development and their environment were assessed comprehensively across childhood, adolescence, and into young adulthood. In the 1970s, two further cohorts were added to the ZLS and assessed with largely matched study protocols: Between 1974 and 1979, the second ZLS cohort included 265 infants (103 term-born and 162 preterm infants), and between 1970 and 2002, the third ZLS cohort included 327 children of participants of the first ZLS cohort. Since 2019, the participants of the three ZLS cohorts have been traced and invited to participate in a first wave of assessments in adulthood to investigate their current health and development. This article describes the ZLS study protocol and discusses opportunities, methodological and conceptual challenges, and limitations arising from a long-term longitudinal cohort recruited from a study about development in early life. In the future, the ZLS will provide data to investigate childhood antecedents of adult health outcomes and, ultimately, will help respond to the frequent call of scientists to shift the focus of aging research into the first decades of life and, thus, to take a lifespan perspective on aging.
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Affiliation(s)
- Flavia M. Wehrle
- Child Development Center, University Children's Hospital Zurich, Zurich, Switzerland
- Children's Research Center, University Children's Hospital Zurich, Zurich, Switzerland
| | - Jon Caflisch
- Child Development Center, University Children's Hospital Zurich, Zurich, Switzerland
- Children's Research Center, University Children's Hospital Zurich, Zurich, Switzerland
| | | | - Giulia Haller
- Child Development Center, University Children's Hospital Zurich, Zurich, Switzerland
| | - Beatrice Latal
- Child Development Center, University Children's Hospital Zurich, Zurich, Switzerland
- Children's Research Center, University Children's Hospital Zurich, Zurich, Switzerland
- University of Zurich, Zurich, Switzerland
| | - Remo H. Largo
- Child Development Center, University Children's Hospital Zurich, Zurich, Switzerland
| | - Tanja H. Kakebeeke
- Child Development Center, University Children's Hospital Zurich, Zurich, Switzerland
- Children's Research Center, University Children's Hospital Zurich, Zurich, Switzerland
| | - Oskar G. Jenni
- Child Development Center, University Children's Hospital Zurich, Zurich, Switzerland
- Children's Research Center, University Children's Hospital Zurich, Zurich, Switzerland
- University of Zurich, Zurich, Switzerland
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12
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Geary DC. Mitochondrial Functions, Cognition, and the Evolution of Intelligence: Reply to Commentaries and Moving Forward. J Intell 2020; 8:E42. [PMID: 33302466 PMCID: PMC7768403 DOI: 10.3390/jintelligence8040042] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2020] [Revised: 11/16/2020] [Accepted: 12/03/2020] [Indexed: 12/24/2022] Open
Abstract
In response to commentaries, I address questions regarding the proposal that general intelligence (g) is a manifestation of the functioning of intramodular and intermodular brain networks undergirded by the efficiency of mitochondrial functioning (Geary 2018). The core issues include the relative contribution of mitochondrial functioning to individual differences in g; studies that can be used to test associated hypotheses; and, the adaptive function of intelligence from an evolutionary perspective. I attempt to address these and related issues, as well as note areas in which other issues remain to be addressed.
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Affiliation(s)
- David C Geary
- Department of Psychological Sciences, Interdisciplinary Neuroscience, University of Missouri, Columbia, MO 65211-2500, USA
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13
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Hillary RF, Stevenson AJ, McCartney DL, Campbell A, Walker RM, Howard DM, Ritchie CW, Horvath S, Hayward C, McIntosh AM, Porteous DJ, Deary IJ, Evans KL, Marioni RE. Epigenetic measures of ageing predict the prevalence and incidence of leading causes of death and disease burden. Clin Epigenetics 2020; 12:115. [PMID: 32736664 PMCID: PMC7394682 DOI: 10.1186/s13148-020-00905-6] [Citation(s) in RCA: 95] [Impact Index Per Article: 23.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2020] [Accepted: 07/14/2020] [Indexed: 01/11/2023] Open
Abstract
BACKGROUND Individuals of the same chronological age display different rates of biological ageing. A number of measures of biological age have been proposed which harness age-related changes in DNA methylation profiles. These measures include five 'epigenetic clocks' which provide an index of how much an individual's biological age differs from their chronological age at the time of measurement. The five clocks encompass methylation-based predictors of chronological age (HorvathAge, HannumAge), all-cause mortality (DNAm PhenoAge, DNAm GrimAge) and telomere length (DNAm Telomere Length). A sixth epigenetic measure of ageing differs from these clocks in that it acts as a speedometer providing a single time-point measurement of the pace of an individual's biological ageing. This measure of ageing is termed DunedinPoAm. In this study, we test the association between these six epigenetic measures of ageing and the prevalence and incidence of the leading causes of disease burden and mortality in high-income countries (n ≤ 9537, Generation Scotland: Scottish Family Health Study). RESULTS DNAm GrimAge predicted incidence of clinically diagnosed chronic obstructive pulmonary disease (COPD), type 2 diabetes and ischemic heart disease after 13 years of follow-up (hazard ratios = 2.22, 1.52 and 1.41, respectively). DunedinPoAm predicted the incidence of COPD and lung cancer (hazard ratios = 2.02 and 1.45, respectively). DNAm PhenoAge predicted incidence of type 2 diabetes (hazard ratio = 1.54). DNAm Telomere Length associated with the incidence of ischemic heart disease (hazard ratio = 0.80). DNAm GrimAge associated with all-cause mortality, the prevalence of COPD and spirometry measures at the study baseline. These associations were present after adjusting for possible confounding risk factors including alcohol consumption, body mass index, deprivation, education and tobacco smoking and surpassed stringent Bonferroni-corrected significance thresholds. CONCLUSIONS Our data suggest that epigenetic measures of ageing may have utility in clinical settings to complement gold-standard methods for disease assessment and management.
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Affiliation(s)
- Robert F Hillary
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU, UK
| | - Anna J Stevenson
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU, UK
| | - Daniel L McCartney
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU, UK
| | - Archie Campbell
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU, UK
| | - Rosie M Walker
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU, UK
| | - David M Howard
- Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, SE5 8AF, UK.,Division of Psychiatry, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, EH16 4UX, UK
| | - Craig W Ritchie
- Edinburgh Dementia Prevention, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, EH16 4UX, UK
| | - Steve Horvath
- Department of Human Genetics, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, 90095-7088, USA.,Department of Biostatistics, Fielding School of Public Health, University of California Los Angeles, Los Angeles, 90095-1772, USA
| | - Caroline Hayward
- MRC Human Genetics Unit, 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.,Division of Psychiatry, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, EH16 4UX, UK
| | - David J Porteous
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU, UK
| | - Ian J Deary
- Lothian Birth Cohorts, University of Edinburgh, Edinburgh, EH8 9JZ, UK
| | - Kathryn L Evans
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU, UK
| | - Riccardo E Marioni
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU, UK.
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