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Fingelkurts AA, Fingelkurts AA. Turning Back the Clock: A Retrospective Single-Blind Study on Brain Age Change in Response to Nutraceuticals Supplementation vs. Lifestyle Modifications. Brain Sci 2023; 13:brainsci13030520. [PMID: 36979330 PMCID: PMC10046544 DOI: 10.3390/brainsci13030520] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2023] [Revised: 03/17/2023] [Accepted: 03/19/2023] [Indexed: 03/30/2023] Open
Abstract
BACKGROUND There is a growing consensus that chronological age (CA) is not an accurate indicator of the aging process and that biological age (BA) instead is a better measure of an individual's risk of age-related outcomes and a more accurate predictor of mortality than actual CA. In this context, BA measures the "true" age, which is an integrated result of an individual's level of damage accumulation across all levels of biological organization, along with preserved resources. The BA is plastic and depends upon epigenetics. Brain state is an important factor contributing to health- and lifespan. METHODS AND OBJECTIVE Quantitative electroencephalography (qEEG)-derived brain BA (BBA) is a suitable and promising measure of brain aging. In the present study, we aimed to show that BBA can be decelerated or even reversed in humans (N = 89) by using customized programs of nutraceutical compounds or lifestyle changes (mean duration = 13 months). RESULTS We observed that BBA was younger than CA in both groups at the end of the intervention. Furthermore, the BBA of the participants in the nutraceuticals group was 2.83 years younger at the endpoint of the intervention compared with their BBA score at the beginning of the intervention, while the BBA of the participants in the lifestyle group was only 0.02 years younger at the end of the intervention. These results were accompanied by improvements in mental-physical health comorbidities in both groups. The pre-intervention BBA score and the sex of the participants were considered confounding factors and analyzed separately. CONCLUSIONS Overall, the obtained results support the feasibility of the goal of this study and also provide the first robust evidence that halting and reversal of brain aging are possible in humans within a reasonable (practical) timeframe of approximately one year.
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Faul JD, Kim JK, Levine ME, Thyagarajan B, Weir DR, Crimmins EM. Epigenetic-based age acceleration in a representative sample of older Americans: Associations with aging-related morbidity and mortality. Proc Natl Acad Sci U S A 2023; 120:e2215840120. [PMID: 36802439 PMCID: PMC9992763 DOI: 10.1073/pnas.2215840120] [Citation(s) in RCA: 39] [Impact Index Per Article: 39.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2022] [Accepted: 01/12/2023] [Indexed: 02/23/2023] Open
Abstract
Biomarkers developed from DNA methylation (DNAm) data are of growing interest as predictors of health outcomes and mortality in older populations. However, it is unknown how epigenetic aging fits within the context of known socioeconomic and behavioral associations with aging-related health outcomes in a large, population-based, and diverse sample. This study uses data from a representative, panel study of US older adults to examine the relationship between DNAm-based age acceleration measures in the prediction of cross-sectional and longitudinal health outcomes and mortality. We examine whether recent improvements to these scores, using principal component (PC)-based measures designed to remove some of the technical noise and unreliability in measurement, improve the predictive capability of these measures. We also examine how well DNAm-based measures perform against well-known predictors of health outcomes such as demographics, SES, and health behaviors. In our sample, age acceleration calculated using "second and third generation clocks," PhenoAge, GrimAge, and DunedinPACE, is consistently a significant predictor of health outcomes including cross-sectional cognitive dysfunction, functional limitations and chronic conditions assessed 2 y after DNAm measurement, and 4-y mortality. PC-based epigenetic age acceleration measures do not significantly change the relationship of DNAm-based age acceleration measures to health outcomes or mortality compared to earlier versions of these measures. While the usefulness of DNAm-based age acceleration as a predictor of later life health outcomes is quite clear, other factors such as demographics, SES, mental health, and health behaviors remain equally, if not more robust, predictors of later life outcomes.
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Affiliation(s)
- Jessica D. Faul
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI48104
| | - Jung Ki Kim
- Davis School of Gerontology, University of Southern California, Los Angeles, CA90089
| | - Morgan E. Levine
- Department of Pathology, Yale School of Medicine, New Haven, CT06510
| | - Bharat Thyagarajan
- Department of Laboratory Medicine and Pathology, University of Minnesota Medical School, Minneapolis, MN55455
| | - David R. Weir
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI48104
| | - Eileen M. Crimmins
- Davis School of Gerontology, University of Southern California, Los Angeles, CA90089
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Li Z, Zong X, Li D, He Y, Tang J, Hu M, Chen X. Epigenetic clock analysis of blood samples in drug-naive first-episode schizophrenia patients. BMC Psychiatry 2023; 23:45. [PMID: 36650462 PMCID: PMC9843886 DOI: 10.1186/s12888-023-04533-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/09/2022] [Accepted: 01/06/2023] [Indexed: 01/18/2023] Open
Abstract
BACKGROUND Schizophrenia (SCZ) is a severe and chronic psychiatric disorder with premature age-related physiological changes. However, numerous previous studies examined the epigenetic age acceleration in SCZ patients and yielded inconclusive results. In this study, we propose to explore the epigenetic age acceleration in drug-naive first-episode SCZ (FSCZ) patients and investigate whether epigenetic age acceleration is associated with antipsychotic treatment, psychotic symptoms, cognition, and subcortical volumes. METHODS We assessed the epigenetic age in 38 drug-naive FSCZ patients and 38 healthy controls by using three independent clocks, including Horvath, Hannum and Levine algorithms. The epigenetic age measurements in SCZ patients were repeated after receiving 8 weeks risperidone monotherapy. RESULTS Our findings showed significantly positive correlations between epigenetic ages assessed by three clocks and chronological age in both FSCZ patients and healthy controls. Compared with healthy controls, drug-naive FSCZ patients have a significant epigenetic age deceleration in Horvath clock (p = 0.01), but not in Hannum clock (p = 0.07) and Levine clock (p = 0.43). The epigenetic ages of Hannum clock (p = 0.002) and Levine clock (p = 0.01) were significantly accelerated in SCZ patients after 8-week risperidone treatment. However, no significant associations between epigenetic age acceleration and psychotic symptoms, cognitive function, as well as subcortical volumes were observed in FSCZ patients. CONCLUSION These results demonstrate that distinct epigenetic clocks are sensitive to different aspects of aging process. Further investigations with comprehensive epigenetic clock analyses and large samples are required to confirm our findings.
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Affiliation(s)
- Zongchang Li
- grid.216417.70000 0001 0379 7164Department of Psychiatry, and National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital, Central South University, No 139 Renmin Road, Changsha, Hunan 410011 P. R. China ,grid.216417.70000 0001 0379 7164China National Technology Institute on Mental Disorders & Hunan Key Laboratory of Psychiatry and Mental Health, Mental Health Institute of the Second Xiangya Hospital, Central South University, Changsha, P. R. China
| | - Xiaofen Zong
- grid.412632.00000 0004 1758 2270Department of Psychiatry, Renmin Hospital of Wuhan University, Wuhan, P. R. China
| | - David Li
- grid.216417.70000 0001 0379 7164Department of Psychiatry, and National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital, Central South University, No 139 Renmin Road, Changsha, Hunan 410011 P. R. China
| | - Ying He
- grid.216417.70000 0001 0379 7164Department of Psychiatry, and National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital, Central South University, No 139 Renmin Road, Changsha, Hunan 410011 P. R. China ,grid.216417.70000 0001 0379 7164China National Technology Institute on Mental Disorders & Hunan Key Laboratory of Psychiatry and Mental Health, Mental Health Institute of the Second Xiangya Hospital, Central South University, Changsha, P. R. China
| | - Jinsong Tang
- grid.13402.340000 0004 1759 700XDepartment of Psychiatry, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, P. R. China
| | - Maolin Hu
- Department of Psychiatry, Renmin Hospital of Wuhan University, Wuhan, P. R. China.
| | - Xiaogang Chen
- Department of Psychiatry, and National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital, Central South University, No 139 Renmin Road, Changsha, Hunan, 410011, P. R. China. .,China National Technology Institute on Mental Disorders & Hunan Key Laboratory of Psychiatry and Mental Health, Mental Health Institute of the Second Xiangya Hospital, Central South University, Changsha, P. R. China.
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Dobewall H, Keltikangas-Järvinen L, Marttila S, Mishra PP, Saarinen A, Cloninger CR, Zwir I, Kähönen M, Hurme M, Raitakari O, Lehtimäki T, Hintsanen M. The relationship of trait-like compassion with epigenetic aging: The population-based prospective Young Finns Study. Front Psychiatry 2023; 14:1018797. [PMID: 37143783 PMCID: PMC10151573 DOI: 10.3389/fpsyt.2023.1018797] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/13/2022] [Accepted: 03/17/2023] [Indexed: 05/06/2023] Open
Abstract
Introduction Helping others within and beyond the family has been related to living a healthy and long life. Compassion is a prosocial personality trait characterized by concern for another person who is suffering and the motivation to help. The current study examines whether epigenetic aging is a potential biological mechanism that explains the link between prosociality and longevity. Methods We used data from the Young Finns Study that follows six birth-cohorts from age 3-18 to 19-49. Trait-like compassion for others was measured with the Temperament and Character Inventory in the years 1997 and 2001. Epigenetic age acceleration and telomere length were measured with five DNA methylation (DNAm) indicators (DNAmAgeHorvath, IEAA_Hannum, EEAA_Hannum, DNAmPhenoAge, and DNAmTL) based on blood drawn in 2011. We controlled for sex, socioeconomic status in childhood and adulthood, and body-mass index. Results and discussion An association between higher compassion in 1997 and a less accelerated DNAmPhenoAge, which builds on previous work on phenotypic aging, approached statistical significance in a sex-adjusted model (n = 1,030; b = -0.34; p = 0.050). Compassion in 1997 predicted less accelerated epigenetic aging over and above the control variables (n = 843; b = -0.47; p = 0.016). There was no relationship between compassion in 2001 (n = 1108/910) and any of the other four studied epigenetic aging indicators. High compassion for others might indeed influence whether an individual's biological age is lower than their chronological age. The conducted robustness checks partially support this conclusion, yet cannot rule out that there might be a broader prosocial trait behind the findings. The observed associations are interesting but should be interpreted as weak requiring replication.
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Affiliation(s)
- Henrik Dobewall
- Faculty of Education, VISE Research Unit, Faculty of Education and Psychology, University of Oulu, Oulu, Finland
- Finnish Institute for Health and Welfare, Helsinki, Finland
- *Correspondence: Henrik Dobewall,
| | | | - Saara Marttila
- Molecular Epidemiology, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
- Gerontology Research Center, Tampere University, Tampere, Finland
| | - Pashupati P. Mishra
- Molecular Epidemiology, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
- Fimlab Laboratories and Finnish Cardiovascular Research Center - Tampere, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - Aino Saarinen
- Department of Psychology and Logopedics, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - C. Robert Cloninger
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, United States
| | - Igor Zwir
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, United States
- Department of Computer Science, University of Granada, Granada, Spain
| | - Mika Kähönen
- Department of Clinical Physiology, Tampere University Hospital and Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - Mikko Hurme
- Department of Microbiology and Immunology, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - Olli Raitakari
- Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland
- Department of Clinical Physiology and Nuclear Medicine, Turku University Hospital, Turku, Finland
- Centre for Population Health Research, University of Turku and Turku University Hospital, Turku, Finland
| | - Terho Lehtimäki
- Molecular Epidemiology, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
- Fimlab Laboratories and Finnish Cardiovascular Research Center - Tampere, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - Mirka Hintsanen
- Faculty of Education, VISE Research Unit, Faculty of Education and Psychology, University of Oulu, Oulu, Finland
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Vyas CM, Sadreyev RI, Gatchel JR, Kang JH, Reynolds CF, Mischoulon D, Chang G, Hazra A, Manson JE, Blacker D, Vivo ID, Okereke OI. Pilot Study of Second-Generation DNA Methylation Epigenetic Markers in Relation to Cognitive and Neuropsychiatric Symptoms in Older Adults. J Alzheimers Dis 2023; 93:1563-1575. [PMID: 37212116 PMCID: PMC10336852 DOI: 10.3233/jad-230093] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/23/2023]
Abstract
BACKGROUND Associations between epigenetic aging with cognitive aging and neuropsychiatric measures are not well-understood. OBJECTIVE 1) To assess cross-sectional correlations between second-generation DNA methylation (DNAm)-based clocks of healthspan and lifespan (i.e., GrimAge, PhenoAge, and DNAm-based estimator of telomere length [DNAmTL]) and cognitive and neuropsychiatric measures; 2) To examine longitudinal associations between change in DNAm markers and change in cognition over 2 years. METHODS Participants were members of VITAL-DEP (VITamin D and OmegA-3 TriaL- Depression Endpoint Prevention) study. From previously ascertained cognitive groups (i.e., cognitively normal and mild cognitive impairment), we randomly selected 45 participants, aged≥60 years, who completed in-person neuropsychiatric assessments at baseline and 2 years. The primary outcome was global cognitive score (averaging z-scores of 9 tests). Neuropsychiatric Inventory severity scores were mapped from neuropsychiatric symptoms (NPS) from psychological scales and structured diagnostic interviews. DNAm was assayed using Illumina MethylationEPIC 850K BeadChip at baseline and 2 years. We calculated baseline partial Spearman correlations between DNAm markers and cognitive and NPS measures. We constructed multivariable linear regression models to examine longitudinal relations between DNAm markers and cognition. RESULTS At baseline, we observed a suggestive negative correlation between GrimAge clock markers and global cognition but no signal between DNAm markers and NPS measures. Over 2 years: each 1-year increase in DNAmGrimAge was significantly associated with faster declines in global cognition; each 100-base pair increase in DNAmTL was significantly associated with better global cognition. CONCLUSION We found preliminary evidence of cross-sectional and longitudinal associations between DNAm markers and global cognition.
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Affiliation(s)
- Chirag M. Vyas
- Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Ruslan I. Sadreyev
- Department of Molecular Biology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Jennifer R. Gatchel
- Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
- Division of Geriatric Psychiatry, McLean Hospital, Harvard Medical School, Belmont, MA, USA
| | - Jae H. Kang
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
| | - Charles F. Reynolds
- Department of Psychiatry, UPMC and University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - David Mischoulon
- Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Grace Chang
- Department of Psychiatry, VA Boston Healthcare System and Harvard Medical School, Boston, MA, USA
| | - Aditi Hazra
- Division of Preventive Medicine, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
| | - JoAnn E. Manson
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
- Division of Preventive Medicine, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
- Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, MA, USA
| | - Deborah Blacker
- Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
- Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, MA, USA
| | - Immaculata De Vivo
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
- Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, MA, USA
| | - Olivia I. Okereke
- Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
- Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, MA, USA
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Cabrera-Mendoza B, Stertz L, Najera K, Selvaraj S, Teixeira AL, Meyer TD, Fries GR, Walss-Bass C. Within subject cross-tissue analyzes of epigenetic clocks in substance use disorder postmortem brain and blood. Am J Med Genet B Neuropsychiatr Genet 2023; 192:13-27. [PMID: 36056652 PMCID: PMC9742183 DOI: 10.1002/ajmg.b.32920] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/01/2021] [Revised: 06/22/2022] [Accepted: 08/16/2022] [Indexed: 12/14/2022]
Abstract
There is a possible accelerated biological aging in patients with substance use disorders (SUD). The evaluation of epigenetic clocks, which are accurate estimators of biological aging based on DNA methylation changes, has been limited to blood tissue in patients with SUD. Consequently, the impact of biological aging in the brain of individuals with SUD remains unknown. In this study, we evaluated multiple epigenetic clocks (DNAmAge, DNAmAgeHannum, DNAmAgeSkinBlood, DNAmPhenoAge, DNAmGrimAge, and DNAmTL) in individuals with SUD (n = 42), including alcohol (n = 10), opioid (n = 19), and stimulant use disorder (n = 13), and controls (n = 10) in postmortem brain (prefrontal cortex) and blood tissue obtained from the same individuals. We found a higher DNAmPhenoAge (β = 0.191, p-value = 0.0104) and a nominally lower DNAmTL (β = -0.149, p-value = 0.0603) in blood from individuals with SUD compared to controls. SUD subgroup analysis showed a nominally lower brain DNAmTL in subjects with alcohol use disorder, compared to stimulant use disorder and controls (β = 0.0150, p-value = 0.087). Cross-tissue analyzes indicated a lower blood DNAmTL and a higher blood DNAmAge compared to their respective brain values in the SUD group. This study highlights the relevance of tissue specificity in biological aging studies and suggests that peripheral measures of epigenetic clocks in SUD may depend on the specific type of drug used.
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Affiliation(s)
- Brenda Cabrera-Mendoza
- PECEM, Faculty of Medicine, Universidad Nacional
Autónoma de México, Mexico City, 04510, Mexico
| | - Laura Stertz
- Louis A. Faillace, MD, Department of Psychiatry and
Behavioral Sciences, McGovern Medical School, University of Texas Health Science
Center at Houston, Houston, TX, 77054, USA
| | - Katherine Najera
- Louis A. Faillace, MD, Department of Psychiatry and
Behavioral Sciences, McGovern Medical School, University of Texas Health Science
Center at Houston, Houston, TX, 77054, USA
| | - Sudhakar Selvaraj
- Louis A. Faillace, MD, Department of Psychiatry and
Behavioral Sciences, McGovern Medical School, University of Texas Health Science
Center at Houston, Houston, TX, 77054, USA
| | - Antonio L. Teixeira
- Louis A. Faillace, MD, Department of Psychiatry and
Behavioral Sciences, McGovern Medical School, University of Texas Health Science
Center at Houston, Houston, TX, 77054, USA
| | - Thomas D. Meyer
- Louis A. Faillace, MD, Department of Psychiatry and
Behavioral Sciences, McGovern Medical School, University of Texas Health Science
Center at Houston, Houston, TX, 77054, USA
| | - Gabriel R. Fries
- Louis A. Faillace, MD, Department of Psychiatry and
Behavioral Sciences, McGovern Medical School, University of Texas Health Science
Center at Houston, Houston, TX, 77054, USA
- Center for Precision Health, School of Biomedical
Informatics, University of Texas Health Science Center at Houston, Houston, TX,
77054, USA
| | - Consuelo Walss-Bass
- Louis A. Faillace, MD, Department of Psychiatry and
Behavioral Sciences, McGovern Medical School, University of Texas Health Science
Center at Houston, Houston, TX, 77054, USA
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Paparazzo E, Geracitano S, Lagani V, Bartolomeo D, Aceto MA, D’Aquila P, Citrigno L, Bellizzi D, Passarino G, Montesanto A. A Blood-Based Molecular Clock for Biological Age Estimation. Cells 2022; 12:cells12010032. [PMID: 36611826 PMCID: PMC9818068 DOI: 10.3390/cells12010032] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2022] [Revised: 12/05/2022] [Accepted: 12/19/2022] [Indexed: 12/24/2022] Open
Abstract
In the last decade, extensive efforts have been made to identify biomarkers of biological age. DNA methylation levels of ELOVL fatty acid elongase 2 (ELOVL2) and the signal joint T-cell receptor rearrangement excision circles (sjTRECs) represent the most promising candidates. Although these two non-redundant biomarkers echo important biological aspects of the ageing process in humans, a well-validated molecular clock exploiting these powerful candidates has not yet been formulated. The present study aimed to develop a more accurate molecular clock in a sample of 194 Italian individuals by re-analyzing the previously obtained EVOLV2 methylation data together with the amount of sjTRECs in the same blood samples. The proposed model showed a high prediction accuracy both in younger individuals with an error of about 2.5 years and in older subjects where a relatively low error was observed if compared with those reported in previously published studies. In conclusion, an easy, cost-effective and reliable model to measure the individual rate and the quality of aging in human population has been proposed. Further studies are required to validate the model and to extend its use in an applicative context.
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Affiliation(s)
- Ersilia Paparazzo
- Department of Biology, Ecology and Earth Sciences, University of Calabria, 87036 Rende, Italy
| | - Silvana Geracitano
- Department of Biology, Ecology and Earth Sciences, University of Calabria, 87036 Rende, Italy
| | - Vincenzo Lagani
- Biological and Environmental Sciences and Engineering Division (BESE), King Abdullah University of Science and Technology KAUST, Thuwal 23952, Saudi Arabia
- Institute of Chemical Biology, Ilia State University, 0162 Tbilisi, Georgia
- SDAIA-KAUST Center of Excellence in Data Science and Artificial Intelligence, Thuwal 23952, Saudi Arabia
| | - Denise Bartolomeo
- Department of Biology, Ecology and Earth Sciences, University of Calabria, 87036 Rende, Italy
| | - Mirella Aurora Aceto
- Department of Biology, Ecology and Earth Sciences, University of Calabria, 87036 Rende, Italy
| | - Patrizia D’Aquila
- Department of Biology, Ecology and Earth Sciences, University of Calabria, 87036 Rende, Italy
| | - Luigi Citrigno
- National Research Council (CNR)—Institute for Biomedical Research and Innovation—(IRIB), 87050 Mangone, Italy
| | - Dina Bellizzi
- Department of Biology, Ecology and Earth Sciences, University of Calabria, 87036 Rende, Italy
| | - Giuseppe Passarino
- Department of Biology, Ecology and Earth Sciences, University of Calabria, 87036 Rende, Italy
- Correspondence: (G.P.); (A.M.)
| | - Alberto Montesanto
- Department of Biology, Ecology and Earth Sciences, University of Calabria, 87036 Rende, Italy
- Correspondence: (G.P.); (A.M.)
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Deryabin PI, Borodkina AV. Epigenetic clocks provide clues to the mystery of uterine ageing. Hum Reprod Update 2022; 29:259-271. [PMID: 36515535 DOI: 10.1093/humupd/dmac042] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2022] [Revised: 11/28/2022] [Indexed: 12/15/2022] Open
Abstract
BACKGROUND Rising maternal ages and age-related fertility decline are a global challenge for modern reproductive medicine. Clinicians and researchers pay specific attention to ovarian ageing and hormonal insufficiency in this regard. However, uterine ageing is often left out of the picture, with the majority of reproductive clinicians being close to unanimous on the absence of age-related functional decline in the uterine tissues. Therefore, most existing techniques to treat an age-related decline in implantation rates are based primarily on hormonal supplementation and oocyte donation. Solving the issue of uterine ageing might lead to an adjustment to these methods. OBJECTIVE AND RATIONALE A focus on uterine ageing and the possibility of slowing it emerged with the development of the information theory of ageing, which identifies genomic instability and erosion of the epigenetic landscape as important drivers of age-related decline in the functionality of most cells and tissues. Age-related smoothing of this landscape and a decline in tissue function can be assessed by measuring the ticking of epigenetic clocks. Within this review, we explore whether the uterus experiences age-related alterations using this elegant approach. We analyse existing data on epigenetic clocks in the endometrium, highlight approaches to improve the accuracy of the clocks in this cycling tissue, speculate on the endometrial pathologies whose progression might be predicted by the altered speed of epigenetic clocks and discuss the possibilities of slowing down the ticking of these clocks. SEARCH METHODS Data for this review were identified by searches of Medline, PubMed and Google Scholar. References from relevant articles using the search terms 'ageing', 'maternal age', 'female reproduction', 'uterus', 'endometrium', 'implantation', 'decidualization', 'epigenetic clock', 'biological age', 'DNA methylation', 'fertility' and 'infertility' were selected. A total of 95 articles published in English between 1985 and 2022 were included, six of which describe the use of the epigenetic clock to evaluate uterine/endometrium ageing. OUTCOMES Application of the Horvath and DNAm PhenoAge epigenetic clocks demonstrated a poor correlation with chronological age in the endometrium. Several approaches were suggested to enhance the predictive power of epigenetic clocks for the endometrium. The first was to increase the number of samples in the training dataset, as for the Zang clock, or to use more sophisticated clock-building algorithms, as for the AltumAge clock. The second method is to adjust the clocks according to the dynamic nature of the endometrium. Using either approach revealed a strong correlation with chronological age in the endometrium, providing solid evidence for age-related functional decline in this tissue. Furthermore, age acceleration/deceleration, as estimated by epigenetic clocks, might be a promising tool to predict or to gain insights into the origin of various endometrial pathologies, including recurrent implantation failure, cancer and endometriosis. Finally, there are several strategies to slow down or even reverse epigenetic clocks that might be applied to reduce the risk of age-related uterine impairments. WIDER IMPLICATIONS The uterine factor should be considered, along with ovarian issues, to correct for the decline in female fertility with age. Epigenetic clocks can be tested to gain a deeper understanding of various endometrial disorders.
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Affiliation(s)
- Pavel I Deryabin
- Mechanisms of Cellular Senescence Group, Institute of Cytology of the Russian Academy of Sciences, Saint-Petersburg, Russia
| | - Aleksandra V Borodkina
- Mechanisms of Cellular Senescence Group, Institute of Cytology of the Russian Academy of Sciences, Saint-Petersburg, Russia
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Cheong Y, Nishitani S, Yu J, Habata K, Kamiya T, Shiotsu D, Omori IM, Okazawa H, Tomoda A, Kosaka H, Jung M. The effects of epigenetic age and its acceleration on surface area, cortical thickness, and volume in young adults. Cereb Cortex 2022; 32:5654-5663. [PMID: 35196707 DOI: 10.1093/cercor/bhac043] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2021] [Revised: 01/20/2022] [Accepted: 01/21/2022] [Indexed: 01/25/2023] Open
Abstract
DNA methylation age has been used in recent studies as an epigenetic marker of accelerated cellular aging, whose contribution to the brain structural changes was lately acknowledged. We aimed to characterize the association of epigenetic age (i.e. estimated DNA methylation age) and its acceleration with surface area, cortical thickness, and volume in healthy young adults. Using the multi-tissue method (Horvath S. DNA methylation age of human tissues and cell types. 2013. Genome Biol 14), epigenetic age was computed with saliva sample. Epigenetic age acceleration was derived from residuals after adjusting epigenetic age for chronological age. Multiple regression models were computed for 148 brain regions for surface area, cortical thickness, and volume using epigenetic age or accelerated epigenetic age as a predictor and controlling for sex. Epigenetic age was associated with surface area reduction of the left insula. It was also associated with cortical thinning and volume reduction in multiple regions, with prominent changes of cortical thickness in the left temporal regions and of volume in the bilateral orbital gyri. Finally, accelerated epigenetic age was negatively associated with right cuneus gyrus volume. Our findings suggest that understanding the mechanisms of epigenetic age acceleration in young individuals may yield valuable insights into the relationship between epigenetic aging and the cortical change and on the early development of neurocognitive pathology among young adults.
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Affiliation(s)
- Yongjeon Cheong
- Cognitive Science Research Group, Korea Brain Research Institute, Daegu 41062, South Korea
| | - Shota Nishitani
- Research Center for Child Mental Development, University of Fukui, Eiheiji, Fukui 910-1193, Japan.,Division of Developmental Higher Brain Functions, United Graduate School of Child Development, Osaka University, Kanazawa University, Hamamatsu University School of Medicine, Chiba University, and University of Fukui, Osaka 565-0871, Japan
| | - Jinyoung Yu
- Cognitive Science Research Group, Korea Brain Research Institute, Daegu 41062, South Korea
| | - Kaie Habata
- Department of Neuropsychiatry, University of Fukui, 23-3 Matsuokashimoaizuki, Eiheiji, Fukui 910-1193, Japan
| | - Taku Kamiya
- Department of Neuropsychiatry, University of Fukui, 23-3 Matsuokashimoaizuki, Eiheiji, Fukui 910-1193, Japan
| | - Daichi Shiotsu
- Department of Neuropsychiatry, University of Fukui, 23-3 Matsuokashimoaizuki, Eiheiji, Fukui 910-1193, Japan
| | - Ichiro M Omori
- Department of Neuropsychiatry, University of Fukui, 23-3 Matsuokashimoaizuki, Eiheiji, Fukui 910-1193, Japan
| | - Hidehiko Okazawa
- Department of Neuropsychiatry, University of Fukui, 23-3 Matsuokashimoaizuki, Eiheiji, Fukui 910-1193, Japan.,Biomedical Imaging Research Center, University of Fukui, Eiheiji, Fukui 910-1193, Japan
| | - Akemi Tomoda
- Research Center for Child Mental Development, University of Fukui, Eiheiji, Fukui 910-1193, Japan.,Division of Developmental Higher Brain Functions, United Graduate School of Child Development, Osaka University, Kanazawa University, Hamamatsu University School of Medicine, Chiba University, and University of Fukui, Osaka 565-0871, Japan
| | - Hirotaka Kosaka
- Research Center for Child Mental Development, University of Fukui, Eiheiji, Fukui 910-1193, Japan.,Division of Developmental Higher Brain Functions, United Graduate School of Child Development, Osaka University, Kanazawa University, Hamamatsu University School of Medicine, Chiba University, and University of Fukui, Osaka 565-0871, Japan.,Department of Neuropsychiatry, University of Fukui, 23-3 Matsuokashimoaizuki, Eiheiji, Fukui 910-1193, Japan
| | - Minyoung Jung
- Cognitive Science Research Group, Korea Brain Research Institute, Daegu 41062, South Korea
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Biological Age Predictors: The Status Quo and Future Trends. Int J Mol Sci 2022; 23:ijms232315103. [PMID: 36499430 PMCID: PMC9739540 DOI: 10.3390/ijms232315103] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2022] [Revised: 11/28/2022] [Accepted: 11/29/2022] [Indexed: 12/03/2022] Open
Abstract
There is no single universal biomarker yet to estimate overall health status and longevity prospects. Moreover, a consensual approach to the very concept of aging and the means of its assessment are yet to be developed. Markers of aging could facilitate effective health control, more accurate life expectancy estimates, and improved health and quality of life. Clinicians routinely use several indicators that could be biomarkers of aging. Duly validated in a large cohort, models based on a combination of these markers could provide a highly accurate assessment of biological age and the pace of aging. Biological aging is a complex characteristic of chronological age (usually), health-to-age concordance, and medically estimated life expectancy. This study is a review of the most promising techniques that could soon be used in routine clinical practice. Two main selection criteria were applied: a sufficient sample size and reliability based on validation. The selected biological age calculators were grouped according to the type of biomarker used: (1) standard clinical and laboratory markers; (2) molecular markers; and (3) epigenetic markers. The most accurate were the calculators, which factored in a variety of biomarkers. Despite their demonstrated effectiveness, most of them require further improvement and cannot yet be considered for use in standard clinical practice. To illustrate their clinical application, we reviewed their use during the COVID-19 pandemic.
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Engelbrecht HR, Merrill SM, Gladish N, MacIsaac JL, Lin DTS, Ecker S, Chrysohoou CA, Pes GM, Kobor MS, Rehkopf DH. Sex differences in epigenetic age in Mediterranean high longevity regions. FRONTIERS IN AGING 2022; 3:1007098. [PMID: 36506464 PMCID: PMC9726738 DOI: 10.3389/fragi.2022.1007098] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/29/2022] [Accepted: 10/21/2022] [Indexed: 11/24/2022]
Abstract
Sex differences in aging manifest in disparities in disease prevalence, physical health, and lifespan, where women tend to have greater longevity relative to men. However, in the Mediterranean Blue Zones of Sardinia (Italy) and Ikaria (Greece) are regions of centenarian abundance, male-female centenarian ratios are approximately one, diverging from the typical trend and making these useful regions in which to study sex differences of the oldest old. Additionally, these regions can be investigated as examples of healthy aging relative to other populations. DNA methylation (DNAm)-based predictors have been developed to assess various health biomarkers, including biological age, Pace of Aging, serum interleukin-6 (IL-6), and telomere length. Epigenetic clocks are biological age predictors whose deviation from chronological age has been indicative of relative health differences between individuals, making these useful tools for interrogating these differences in aging. We assessed sex differences between the Horvath, Hannum, GrimAge, PhenoAge, Skin and Blood, and Pace of Aging predictors from individuals in two Mediterranean Blue Zones and found that men displayed positive epigenetic age acceleration (EAA) compared to women according to all clocks, with significantly greater rates according to GrimAge (β = 3.55; p = 1.22 × 10-12), Horvath (β = 1.07; p = 0.00378) and the Pace of Aging (β = 0.0344; p = 1.77 × 10-08). Other DNAm-based biomarkers findings indicated that men had lower DNAm-predicted serum IL-6 scores (β = -0.00301, p = 2.84 × 10-12), while women displayed higher DNAm-predicted proportions of regulatory T cells than men from the Blue Zone (p = 0.0150, 95% Confidence Interval [0.00131, 0.0117], Cohen's d = 0.517). All clocks showed better correlations with chronological age in women from the Blue Zones than men, but all clocks showed large mean absolute errors (MAE >30 years) in both sexes, except for PhenoAge (MAE <5 years). Thus, despite their equal survival to older ages in these Mediterranean Blue Zones, men in these regions remain biologically older by most measured DNAm-derived metrics than women, with the exception of the IL-6 score and proportion of regulatory T cells.
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Affiliation(s)
- Hannah-Ruth Engelbrecht
- Edwin S. H. Leong Healthy Aging Program, Faculty of Medicine, University of British Columbia, Vancouver, BC, Canada,Department of Medical Genetics, Faculty of Medicine, University of British Columbia, Vancouver, BC, Canada,British Columbia Children’s Hospital Research Institute, University of British Columbia, Vancouver, BC, Canada,Centre for Molecular Medicine and Therapeutics, University of British Columbia, Vancouver, BC, Canada
| | - Sarah M. Merrill
- Edwin S. H. Leong Healthy Aging Program, Faculty of Medicine, University of British Columbia, Vancouver, BC, Canada,Department of Medical Genetics, Faculty of Medicine, University of British Columbia, Vancouver, BC, Canada,British Columbia Children’s Hospital Research Institute, University of British Columbia, Vancouver, BC, Canada,Centre for Molecular Medicine and Therapeutics, University of British Columbia, Vancouver, BC, Canada
| | - Nicole Gladish
- Department of Epidemiology and Population Health, School of Medicine, Stanford University, Palo Alto, CA, United States
| | - Julie L. MacIsaac
- Department of Medical Genetics, Faculty of Medicine, University of British Columbia, Vancouver, BC, Canada,British Columbia Children’s Hospital Research Institute, University of British Columbia, Vancouver, BC, Canada,Centre for Molecular Medicine and Therapeutics, University of British Columbia, Vancouver, BC, Canada
| | - David T. S. Lin
- Department of Medical Genetics, Faculty of Medicine, University of British Columbia, Vancouver, BC, Canada,British Columbia Children’s Hospital Research Institute, University of British Columbia, Vancouver, BC, Canada,Centre for Molecular Medicine and Therapeutics, University of British Columbia, Vancouver, BC, Canada
| | - Simone Ecker
- UCL Cancer Institute, University College London, London, United Kingdom
| | | | - Giovanni M. Pes
- Department of Clinical and Experimental Medicine, University of Sassari, Sassari, Italy
| | - Michael S. Kobor
- Edwin S. H. Leong Healthy Aging Program, Faculty of Medicine, University of British Columbia, Vancouver, BC, Canada,Department of Medical Genetics, Faculty of Medicine, University of British Columbia, Vancouver, BC, Canada,British Columbia Children’s Hospital Research Institute, University of British Columbia, Vancouver, BC, Canada,Centre for Molecular Medicine and Therapeutics, University of British Columbia, Vancouver, BC, Canada,*Correspondence: Michael S. Kobor, ; David H. Rehkopf,
| | - David H. Rehkopf
- Department of Epidemiology and Population Health, School of Medicine, Stanford University, Palo Alto, CA, United States,*Correspondence: Michael S. Kobor, ; David H. Rehkopf,
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Reed RG, Carroll JE, Marsland AL, Manuck SB. DNA methylation-based measures of biological aging and cognitive decline over 16-years: preliminary longitudinal findings in midlife. Aging (Albany NY) 2022; 14:9423-9444. [PMID: 36374219 PMCID: PMC9792211 DOI: 10.18632/aging.204376] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2022] [Accepted: 10/29/2022] [Indexed: 11/13/2022]
Abstract
DNA methylation-based (DNAm) measures of biological aging associate with increased risk of morbidity and mortality, but their links with cognitive decline are less established. This study examined changes over a 16-year interval in epigenetic clocks (the traditional and principal components [PC]-based Horvath, Hannum, PhenoAge, GrimAge) and pace of aging measures (Dunedin PoAm, Dunedin PACE) in 48 midlife adults enrolled in the longitudinal arm of the Adult Health and Behavior project (56% Female, baseline AgeM = 44.7 years), selected for discrepant cognitive trajectories. Cognitive Decliners (N = 24) were selected based on declines in a composite score derived from neuropsychological tests and matched with participants who did not show any decline, Maintainers (N = 24). Multilevel models with repeated DNAm measures within person tested the main effects of time, group, and group by time interactions. DNAm measures significantly increased over time generally consistent with elapsed time between study visits. There were also group differences: overall, Cognitive Decliners had an older PC-GrimAge and faster pace of aging (Dunedin PoAm, Dunedin PACE) than Cognitive Maintainers. There were no significant group by time interactions, suggesting accelerated epigenetic aging in Decliners remained constant over time. Older PC-GrimAge and faster pace of aging may be particularly sensitive to cognitive decline in midlife.
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Affiliation(s)
- Rebecca G. Reed
- Department of Psychology, Dietrich School of Arts and Sciences, University of Pittsburgh, Pittsburgh, PA 15260, USA
| | - Judith E. Carroll
- Cousins Center for Psychoneuroimmunology, Department of Psychiatry and Biobehavioral Science, Jane and Terry Semel Institute for Neuroscience and Human Behavior, David Geffen School of Medicine, University of California, Los Angeles, CA 90095, USA
| | - Anna L. Marsland
- Department of Psychology, Dietrich School of Arts and Sciences, University of Pittsburgh, Pittsburgh, PA 15260, USA
| | - Stephen B. Manuck
- Department of Psychology, Dietrich School of Arts and Sciences, University of Pittsburgh, Pittsburgh, PA 15260, USA
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Epigenome-Wide Association Study in Peripheral Tissues Highlights DNA Methylation Profiles Associated with Episodic Memory Performance in Humans. Biomedicines 2022; 10:biomedicines10112798. [PMID: 36359320 PMCID: PMC9687249 DOI: 10.3390/biomedicines10112798] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2022] [Revised: 10/24/2022] [Accepted: 10/26/2022] [Indexed: 11/06/2022] Open
Abstract
The decline in episodic memory (EM) performance is a hallmark of cognitive aging and an early clinical sign in Alzheimer’s disease (AD). In this study, we conducted an epigenome-wide association study (EWAS) using DNA methylation (DNAm) profiles from buccal and blood samples for cross-sectional (n = 1019) and longitudinal changes in EM performance (n = 626; average follow-up time 5.4 years) collected under the auspices of the Lifebrain consortium project. The mean age of participants with cross-sectional data was 69 ± 11 years (30−90 years), with 50% being females. We identified 21 loci showing suggestive evidence of association (p < 1 × 10−5) with either or both EM phenotypes. Among these were SNCA, SEPW1 (both cross-sectional EM), ITPK1 (longitudinal EM), and APBA2 (both EM traits), which have been linked to AD or Parkinson’s disease (PD) in previous work. While the EM phenotypes were nominally significantly (p < 0.05) associated with poly-epigenetic scores (PESs) using EWASs on general cognitive function, none remained significant after correction for multiple testing. Likewise, estimating the degree of “epigenetic age acceleration” did not reveal significant associations with either of the two tested EM phenotypes. In summary, our study highlights several interesting candidate loci in which differential DNAm patterns in peripheral tissue are associated with EM performance in humans.
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Baranyi G, Deary IJ, McCartney DL, Harris SE, Shortt N, Reis S, Russ TC, Ward Thompson C, Vieno M, Cox SR, Pearce J. Life-course exposure to air pollution and biological ageing in the Lothian Birth Cohort 1936. ENVIRONMENT INTERNATIONAL 2022; 169:107501. [PMID: 36126422 DOI: 10.1016/j.envint.2022.107501] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/29/2022] [Revised: 08/31/2022] [Accepted: 09/01/2022] [Indexed: 06/15/2023]
Abstract
BACKGROUND Exposure to air pollution is associated with a range of diseases. Biomarkers derived from DNA methylation (DNAm) offer potential mechanistic insights into human health differences, connecting disease pathogenesis and biological ageing. However, little is known about sensitive periods during the life course where air pollution might have a stronger impact on DNAm, or whether effects accumulate over time. We examined associations between air pollution exposure across the life course and DNAm-based markers of biological ageing. METHODS Data were derived from the Scotland-based Lothian Birth Cohort 1936. Participants' residential history was linked to annual levels of fine particle (PM2.5), sulphur dioxide (SO2), nitrogen dioxide (NO2), and ozone (O3) around 1935, 1950, 1970, 1980, 1990, and 2001; pollutant concentrations were estimated using the EMEP4UK atmospheric chemistry transport model. Blood samples were obtained between ages of 70 and 80 years, and Horvath DNAmAge, Hannum DNAmAge, DNAmPhenoAge, DNAmGrimAge, and DNAm telomere length (DNAmTL) were computed. We applied the structured life-course modelling approach: least angle regression identified best-fit life-course models for a composite measure of air pollution (air quality index [AQI]), and mixed-effects regression estimated selected models for AQI and single pollutants. RESULTS We included 525 individuals with 1782 observations. In the total sample, increased air pollution around 1970 was associated with higher epigenetic age (AQI: b = 0.322 year, 95 %CI: 0.088, 0.555) measured with Horvath DNAmAge in late adulthood. We found shorter DNAmTL among males with higher air pollution around 1980 (AQI: b = -0.015 kilobase, 95 %CI: -0.027, -0.004) and among females with higher exposure around 1935 (AQI: b = -0.017 kilobase, 95 %CI: -0.028, -0.006). Findings were more consistent for the pollutants PM2.5, SO2 and NO2. DISCUSSION We tested the life-course relationship between air pollution and DNAm-based biomarkers. Air pollution around birth and in young-to-middle adulthood is linked to accelerated epigenetic ageing and telomere-associated ageing in later life.
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Affiliation(s)
- Gergő Baranyi
- Centre for Research on Environment, Society and Health, School of GeoSciences, The University of Edinburgh, Edinburgh, UK.
| | - Ian J Deary
- Lothian Birth Cohorts, Department of Psychology, The University of Edinburgh, Edinburgh, UK
| | - Daniel L McCartney
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, The University of Edinburgh, Edinburgh, UK
| | - Sarah E Harris
- Lothian Birth Cohorts, Department of Psychology, The University of Edinburgh, Edinburgh, UK
| | - Niamh Shortt
- Centre for Research on Environment, Society and Health, School of GeoSciences, The University of Edinburgh, Edinburgh, UK
| | - Stefan Reis
- UK Centre for Ecology & Hydrology (UKCEH), Bush Estate, Penicuik, UK; University of Exeter Medical School, Knowledge Spa, Truro TR1 3HD, UK; The University of Edinburgh, School of Chemistry, Edinburgh EH9 3BF, UK
| | - Tom C Russ
- Alzheimer Scotland Dementia Research Centre, The University of Edinburgh, Edinburgh, UK
| | | | - Massimo Vieno
- UK Centre for Ecology & Hydrology (UKCEH), Bush Estate, Penicuik, UK
| | - Simon R Cox
- Lothian Birth Cohorts, Department of Psychology, The University of Edinburgh, Edinburgh, UK
| | - Jamie Pearce
- Centre for Research on Environment, Society and Health, School of GeoSciences, The University of Edinburgh, Edinburgh, UK
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65
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Epigenetic clock: A promising biomarker and practical tool in aging. Ageing Res Rev 2022; 81:101743. [PMID: 36206857 DOI: 10.1016/j.arr.2022.101743] [Citation(s) in RCA: 40] [Impact Index Per Article: 20.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2022] [Revised: 09/13/2022] [Accepted: 09/30/2022] [Indexed: 01/31/2023]
Abstract
As a complicated process, aging is characterized by various changes at the cellular, subcellular and nuclear levels, one of which is epigenetic aging. With increasing awareness of the critical role that epigenetic alternations play in aging, DNA methylation patterns have been employed as a measure of biological age, currently referred to as the epigenetic clock. This review provides a comprehensive overview of the epigenetic clock as a biomarker of aging and a useful tool to manage healthy aging. In this burgeoning scientific field, various kinds of epigenetic clocks continue to emerge, including Horvath's clock, Hannum's clock, DNA PhenoAge, and DNA GrimAge. We hereby present the most classic epigenetic clocks, as well as their differences. Correlations of epigenetic age with morbidity, mortality and other factors suggest the potential of epigenetic clocks for risk prediction and identification in the context of aging. In particular, we summarize studies on promising age-reversing interventions, with epigenetic clocks employed as a practical tool in the efficacy evaluation. We also discuss how the lack of higher-quality information poses a major challenge, and offer some suggestions to address existing obstacles. Hopefully, our review will help provide an appropriate understanding of the epigenetic clocks, thereby enabling novel insights into the aging process and how it can be manipulated to promote healthy aging.
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Stevenson AJ, McCartney DL, Gadd DA, Shireby G, Hillary RF, King D, Tzioras M, Wrobel N, McCafferty S, Murphy L, McColl BW, Redmond P, Taylor AM, Harris SE, Russ TC, McIntosh AM, Mill J, Smith C, Deary IJ, Cox SR, Marioni RE, Spires‐Jones TL. A comparison of blood and brain-derived ageing and inflammation-related DNA methylation signatures and their association with microglial burdens. Eur J Neurosci 2022; 56:5637-5649. [PMID: 35362642 PMCID: PMC9525452 DOI: 10.1111/ejn.15661] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2021] [Revised: 03/18/2022] [Accepted: 03/29/2022] [Indexed: 12/31/2022]
Abstract
Inflammation and ageing-related DNA methylation patterns in the blood have been linked to a variety of morbidities, including cognitive decline and neurodegenerative disease. However, it is unclear how these blood-based patterns relate to patterns within the brain and how each associates with central cellular profiles. In this study, we profiled DNA methylation in both the blood and in five post mortem brain regions (BA17, BA20/21, BA24, BA46 and hippocampus) in 14 individuals from the Lothian Birth Cohort 1936. Microglial burdens were additionally quantified in the same brain regions. DNA methylation signatures of five epigenetic ageing biomarkers ('epigenetic clocks'), and two inflammatory biomarkers (methylation proxies for C-reactive protein and interleukin-6) were compared across tissues and regions. Divergent associations between the inflammation and ageing signatures in the blood and brain were identified, depending on region assessed. Four out of the five assessed epigenetic age acceleration measures were found to be highest in the hippocampus (β range = 0.83-1.14, p ≤ 0.02). The inflammation-related DNA methylation signatures showed no clear variation across brain regions. Reactive microglial burdens were found to be highest in the hippocampus (β = 1.32, p = 5 × 10-4 ); however, the only association identified between the blood- and brain-based methylation signatures and microglia was a significant positive association with acceleration of one epigenetic clock (termed DNAm PhenoAge) averaged over all five brain regions (β = 0.40, p = 0.002). This work highlights a potential vulnerability of the hippocampus to epigenetic ageing and provides preliminary evidence of a relationship between DNA methylation signatures in the brain and differences in microglial burdens.
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Affiliation(s)
- Anna J. Stevenson
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular MedicineUniversity of EdinburghEdinburghUK
- Centre for Discovery Brain SciencesUniversity of EdinburghEdinburghUK
| | - Daniel L. McCartney
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular MedicineUniversity of EdinburghEdinburghUK
| | - Danni A. Gadd
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular MedicineUniversity of EdinburghEdinburghUK
| | - Gemma Shireby
- University of Exeter Medical SchoolUniversity of ExeterExeterUK
| | - Robert F. Hillary
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular MedicineUniversity of EdinburghEdinburghUK
| | - Declan King
- Centre for Discovery Brain SciencesUniversity of EdinburghEdinburghUK
- UK Dementia Research InstituteUniversity of EdinburghEdinburghUK
| | - Makis Tzioras
- Centre for Discovery Brain SciencesUniversity of EdinburghEdinburghUK
- UK Dementia Research InstituteUniversity of EdinburghEdinburghUK
| | - Nicola Wrobel
- Edinburgh Clinical Research FacilityWestern General HospitalEdinburghUK
| | - Sarah McCafferty
- Edinburgh Clinical Research FacilityWestern General HospitalEdinburghUK
| | - Lee Murphy
- Edinburgh Clinical Research FacilityWestern General HospitalEdinburghUK
| | - Barry W. McColl
- Centre for Discovery Brain SciencesUniversity of EdinburghEdinburghUK
- UK Dementia Research InstituteUniversity of EdinburghEdinburghUK
| | - Paul Redmond
- Lothian Birth CohortsUniversity of EdinburghEdinburghUK
| | | | - Sarah E. Harris
- Lothian Birth CohortsUniversity of EdinburghEdinburghUK
- Department of PsychologyUniversity of EdinburghEdinburghUK
| | - Tom C. Russ
- Lothian Birth CohortsUniversity of EdinburghEdinburghUK
- Alzheimer Scotland Dementia Research Centre, 7 George SquareUniversity of EdinburghEdinburghUK
- Division of PsychiatryUniversity of Edinburgh, Royal Edinburgh HospitalEdinburghUK
| | - Andrew M. McIntosh
- Division of PsychiatryUniversity of Edinburgh, Royal Edinburgh HospitalEdinburghUK
| | - Jonathan Mill
- University of Exeter Medical SchoolUniversity of ExeterExeterUK
| | - Colin Smith
- Centre for Clinical Brain SciencesUniversity of EdinburghEdinburghUK
| | - Ian J. Deary
- Lothian Birth CohortsUniversity of EdinburghEdinburghUK
- Department of PsychologyUniversity of EdinburghEdinburghUK
| | - Simon R. Cox
- Lothian Birth CohortsUniversity of EdinburghEdinburghUK
- Department of PsychologyUniversity of EdinburghEdinburghUK
| | - Riccardo E. Marioni
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular MedicineUniversity of EdinburghEdinburghUK
- Lothian Birth CohortsUniversity of EdinburghEdinburghUK
| | - Tara L. Spires‐Jones
- Centre for Discovery Brain SciencesUniversity of EdinburghEdinburghUK
- UK Dementia Research InstituteUniversity of EdinburghEdinburghUK
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Niccodemi G, Menta G, Turner J, D'Ambrosio C. Pace of aging, family environment and cognitive skills in children and adolescents. SSM Popul Health 2022; 20:101280. [DOI: 10.1016/j.ssmph.2022.101280] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2022] [Revised: 09/16/2022] [Accepted: 10/29/2022] [Indexed: 11/08/2022] Open
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Fuggle NR, Laskou F, Harvey NC, Dennison EM. A review of epigenetics and its association with ageing of muscle and bone. Maturitas 2022; 165:12-17. [PMID: 35841774 DOI: 10.1016/j.maturitas.2022.06.014] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2022] [Revised: 06/21/2022] [Accepted: 06/30/2022] [Indexed: 10/31/2022]
Abstract
Ageing is defined as the 'increasing frailty of an organism with time that reduces the ability of that organism to deal with stress'. It has been suggested that epigenetics may underlie the observation that some individuals appear to age faster than others. Epigenetics is the study of changes which occur in an organism due to changes in expression of the genetic code rather than changes to the genetic code itself; that is, epigenetic mechanisms impact upon the function of DNA without changing the DNA sequence. It is important to recognise that epigenetic changes, in contrast to genetic changes, can vary according to different cell types and therefore can demonstrate significant tissue-specificity. There are different types of epigenetic mechanisms: histone modification, non-coding RNAs and DNA methylation. Epigenetic clocks have been developed using statistical techniques to identify the optimal combination of CpG sites (from methylation arrays) to correlate with chronological age. This review considers how epigenetic factors may affect rates of ageing of muscle and bone and provides an overview of current understanding in this area. We discuss studies using first-generation epigenetic clocks, as well as the second-generation iterations, which appear to show stronger associations with the ageing muscle phenotype. We also review epigenome-wide association studies that have been performed in various tissues examining relationships with osteoporosis and fracture. It is hoped that an understanding of this area will lead to interventions that might prevent or reduce rates of musculoskeletal ageing in later life.
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Affiliation(s)
- N R Fuggle
- MRC Lifecourse Epidemiology Centre, University of Southampton, SO16 6YD, United Kingdom of Great Britain and Northern Ireland
| | - F Laskou
- MRC Lifecourse Epidemiology Centre, University of Southampton, SO16 6YD, United Kingdom of Great Britain and Northern Ireland
| | - N C Harvey
- MRC Lifecourse Epidemiology Centre, University of Southampton, SO16 6YD, United Kingdom of Great Britain and Northern Ireland
| | - E M Dennison
- MRC Lifecourse Epidemiology Centre, University of Southampton, SO16 6YD, United Kingdom of Great Britain and Northern Ireland.
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Sugden K, Caspi A, Elliott ML, Bourassa KJ, Chamarti K, Corcoran DL, Hariri AR, Houts RM, Kothari M, Kritchevsky S, Kuchel GA, Mill JS, Williams BS, Belsky DW, Moffitt TE. Association of Pace of Aging Measured by Blood-Based DNA Methylation With Age-Related Cognitive Impairment and Dementia. Neurology 2022; 99:e1402-e1413. [PMID: 35794023 PMCID: PMC9576288 DOI: 10.1212/wnl.0000000000200898] [Citation(s) in RCA: 47] [Impact Index Per Article: 23.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2021] [Accepted: 05/13/2022] [Indexed: 01/07/2023] Open
Abstract
BACKGROUND AND OBJECTIVES DNA methylation algorithms are increasingly used to estimate biological aging; however, how these proposed measures of whole-organism biological aging relate to aging in the brain is not known. We used data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) and the Framingham Heart Study (FHS) Offspring Cohort to test the association between blood-based DNA methylation measures of biological aging and cognitive impairment and dementia in older adults. METHODS We tested 3 "generations" of DNA methylation age algorithms (first generation: Horvath and Hannum clocks; second generation: PhenoAge and GrimAge; and third generation: DunedinPACE, Dunedin Pace of Aging Calculated from the Epigenome) against the following measures of cognitive impairment in ADNI: clinical diagnosis of dementia and mild cognitive impairment, scores on Alzheimer disease (AD) / Alzheimer disease and related dementias (ADRD) screening tests (Alzheimer's Disease Assessment Scale, Mini-Mental State Examination, and Montreal Cognitive Assessment), and scores on cognitive tests (Rey Auditory Verbal Learning Test, Logical Memory test, and Trail Making Test). In an independent replication in the FHS Offspring Cohort, we further tested the longitudinal association between the DNA methylation algorithms and the risk of developing dementia. RESULTS In ADNI (N = 649 individuals), the first-generation (Horvath and Hannum DNA methylation age clocks) and the second-generation (PhenoAge and GrimAge) DNA methylation measures of aging were not consistently associated with measures of cognitive impairment in older adults. By contrast, a third-generation measure of biological aging, DunedinPACE, was associated with clinical diagnosis of Alzheimer disease (beta [95% CI] = 0.28 [0.08-0.47]), poorer scores on Alzheimer disease/ADRD screening tests (beta [Robust SE] = -0.10 [0.04] to 0.08[0.04]), and cognitive tests (beta [Robust SE] = -0.12 [0.04] to 0.10 [0.03]). The association between faster pace of aging, as measured by DunedinPACE, and risk of developing dementia was confirmed in a longitudinal analysis of the FHS Offspring Cohort (N = 2,264 individuals, hazard ratio [95% CI] = 1.27 [1.07-1.49]). DISCUSSION Third-generation blood-based DNA methylation measures of aging could prove valuable for measuring differences between individuals in the rate at which they age and in their risk for cognitive decline, and for evaluating interventions to slow aging.
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Affiliation(s)
- Karen Sugden
- From the Department of Psychology and Neuroscience (K.S., A.C., M.L.E., K.C., A.R.H., R.M.H., B.S.W., T.E.M.), and Center for Genomic and Computational Biology (K.S., A.C., B.S.W., T.E.M.), Duke University, Durham, NC; Department of Psychiatry and Behavioral Sciences (A.C., T.E.M.), Duke University School of Medicine, Durham, NC; Social, Genetic, and Developmental Psychiatry Centre (A.C, T.E.M.), Institute of Psychiatry, Psychology, and Neuroscience, King's College London, UK. Center for the Study of Aging and Human Development (K.J.B.), Duke University, Durham, NC; Department of Genetics (D.L.C.), University of North Carolina School of Medicine, Chapel Hill; Butler Columbia Aging Center (M.K., D.W.B.), Columbia University, New York, New York; Sticht Center for Healthy Aging and Alzheimer's Prevention (S.K.), Wake Forest School of Medicine, Winston-Salem, NC; UConn Center on Aging (G.A.K.), University of Connecticut, Farmington, Connecticut, USA; College of Medicine and Health (J.S.M.), University of Exeter Medical School, Devon, UK; and Department of Epidemiology (D.W.B.), Columbia University Mailman School of Public Health, New York, New York.
| | - Avshalom Caspi
- From the Department of Psychology and Neuroscience (K.S., A.C., M.L.E., K.C., A.R.H., R.M.H., B.S.W., T.E.M.), and Center for Genomic and Computational Biology (K.S., A.C., B.S.W., T.E.M.), Duke University, Durham, NC; Department of Psychiatry and Behavioral Sciences (A.C., T.E.M.), Duke University School of Medicine, Durham, NC; Social, Genetic, and Developmental Psychiatry Centre (A.C, T.E.M.), Institute of Psychiatry, Psychology, and Neuroscience, King's College London, UK. Center for the Study of Aging and Human Development (K.J.B.), Duke University, Durham, NC; Department of Genetics (D.L.C.), University of North Carolina School of Medicine, Chapel Hill; Butler Columbia Aging Center (M.K., D.W.B.), Columbia University, New York, New York; Sticht Center for Healthy Aging and Alzheimer's Prevention (S.K.), Wake Forest School of Medicine, Winston-Salem, NC; UConn Center on Aging (G.A.K.), University of Connecticut, Farmington, Connecticut, USA; College of Medicine and Health (J.S.M.), University of Exeter Medical School, Devon, UK; and Department of Epidemiology (D.W.B.), Columbia University Mailman School of Public Health, New York, New York
| | - Maxwell L Elliott
- From the Department of Psychology and Neuroscience (K.S., A.C., M.L.E., K.C., A.R.H., R.M.H., B.S.W., T.E.M.), and Center for Genomic and Computational Biology (K.S., A.C., B.S.W., T.E.M.), Duke University, Durham, NC; Department of Psychiatry and Behavioral Sciences (A.C., T.E.M.), Duke University School of Medicine, Durham, NC; Social, Genetic, and Developmental Psychiatry Centre (A.C, T.E.M.), Institute of Psychiatry, Psychology, and Neuroscience, King's College London, UK. Center for the Study of Aging and Human Development (K.J.B.), Duke University, Durham, NC; Department of Genetics (D.L.C.), University of North Carolina School of Medicine, Chapel Hill; Butler Columbia Aging Center (M.K., D.W.B.), Columbia University, New York, New York; Sticht Center for Healthy Aging and Alzheimer's Prevention (S.K.), Wake Forest School of Medicine, Winston-Salem, NC; UConn Center on Aging (G.A.K.), University of Connecticut, Farmington, Connecticut, USA; College of Medicine and Health (J.S.M.), University of Exeter Medical School, Devon, UK; and Department of Epidemiology (D.W.B.), Columbia University Mailman School of Public Health, New York, New York
| | - Kyle J Bourassa
- From the Department of Psychology and Neuroscience (K.S., A.C., M.L.E., K.C., A.R.H., R.M.H., B.S.W., T.E.M.), and Center for Genomic and Computational Biology (K.S., A.C., B.S.W., T.E.M.), Duke University, Durham, NC; Department of Psychiatry and Behavioral Sciences (A.C., T.E.M.), Duke University School of Medicine, Durham, NC; Social, Genetic, and Developmental Psychiatry Centre (A.C, T.E.M.), Institute of Psychiatry, Psychology, and Neuroscience, King's College London, UK. Center for the Study of Aging and Human Development (K.J.B.), Duke University, Durham, NC; Department of Genetics (D.L.C.), University of North Carolina School of Medicine, Chapel Hill; Butler Columbia Aging Center (M.K., D.W.B.), Columbia University, New York, New York; Sticht Center for Healthy Aging and Alzheimer's Prevention (S.K.), Wake Forest School of Medicine, Winston-Salem, NC; UConn Center on Aging (G.A.K.), University of Connecticut, Farmington, Connecticut, USA; College of Medicine and Health (J.S.M.), University of Exeter Medical School, Devon, UK; and Department of Epidemiology (D.W.B.), Columbia University Mailman School of Public Health, New York, New York
| | - Kartik Chamarti
- From the Department of Psychology and Neuroscience (K.S., A.C., M.L.E., K.C., A.R.H., R.M.H., B.S.W., T.E.M.), and Center for Genomic and Computational Biology (K.S., A.C., B.S.W., T.E.M.), Duke University, Durham, NC; Department of Psychiatry and Behavioral Sciences (A.C., T.E.M.), Duke University School of Medicine, Durham, NC; Social, Genetic, and Developmental Psychiatry Centre (A.C, T.E.M.), Institute of Psychiatry, Psychology, and Neuroscience, King's College London, UK. Center for the Study of Aging and Human Development (K.J.B.), Duke University, Durham, NC; Department of Genetics (D.L.C.), University of North Carolina School of Medicine, Chapel Hill; Butler Columbia Aging Center (M.K., D.W.B.), Columbia University, New York, New York; Sticht Center for Healthy Aging and Alzheimer's Prevention (S.K.), Wake Forest School of Medicine, Winston-Salem, NC; UConn Center on Aging (G.A.K.), University of Connecticut, Farmington, Connecticut, USA; College of Medicine and Health (J.S.M.), University of Exeter Medical School, Devon, UK; and Department of Epidemiology (D.W.B.), Columbia University Mailman School of Public Health, New York, New York
| | - David L Corcoran
- From the Department of Psychology and Neuroscience (K.S., A.C., M.L.E., K.C., A.R.H., R.M.H., B.S.W., T.E.M.), and Center for Genomic and Computational Biology (K.S., A.C., B.S.W., T.E.M.), Duke University, Durham, NC; Department of Psychiatry and Behavioral Sciences (A.C., T.E.M.), Duke University School of Medicine, Durham, NC; Social, Genetic, and Developmental Psychiatry Centre (A.C, T.E.M.), Institute of Psychiatry, Psychology, and Neuroscience, King's College London, UK. Center for the Study of Aging and Human Development (K.J.B.), Duke University, Durham, NC; Department of Genetics (D.L.C.), University of North Carolina School of Medicine, Chapel Hill; Butler Columbia Aging Center (M.K., D.W.B.), Columbia University, New York, New York; Sticht Center for Healthy Aging and Alzheimer's Prevention (S.K.), Wake Forest School of Medicine, Winston-Salem, NC; UConn Center on Aging (G.A.K.), University of Connecticut, Farmington, Connecticut, USA; College of Medicine and Health (J.S.M.), University of Exeter Medical School, Devon, UK; and Department of Epidemiology (D.W.B.), Columbia University Mailman School of Public Health, New York, New York
| | - Ahmad R Hariri
- From the Department of Psychology and Neuroscience (K.S., A.C., M.L.E., K.C., A.R.H., R.M.H., B.S.W., T.E.M.), and Center for Genomic and Computational Biology (K.S., A.C., B.S.W., T.E.M.), Duke University, Durham, NC; Department of Psychiatry and Behavioral Sciences (A.C., T.E.M.), Duke University School of Medicine, Durham, NC; Social, Genetic, and Developmental Psychiatry Centre (A.C, T.E.M.), Institute of Psychiatry, Psychology, and Neuroscience, King's College London, UK. Center for the Study of Aging and Human Development (K.J.B.), Duke University, Durham, NC; Department of Genetics (D.L.C.), University of North Carolina School of Medicine, Chapel Hill; Butler Columbia Aging Center (M.K., D.W.B.), Columbia University, New York, New York; Sticht Center for Healthy Aging and Alzheimer's Prevention (S.K.), Wake Forest School of Medicine, Winston-Salem, NC; UConn Center on Aging (G.A.K.), University of Connecticut, Farmington, Connecticut, USA; College of Medicine and Health (J.S.M.), University of Exeter Medical School, Devon, UK; and Department of Epidemiology (D.W.B.), Columbia University Mailman School of Public Health, New York, New York
| | - Renate M Houts
- From the Department of Psychology and Neuroscience (K.S., A.C., M.L.E., K.C., A.R.H., R.M.H., B.S.W., T.E.M.), and Center for Genomic and Computational Biology (K.S., A.C., B.S.W., T.E.M.), Duke University, Durham, NC; Department of Psychiatry and Behavioral Sciences (A.C., T.E.M.), Duke University School of Medicine, Durham, NC; Social, Genetic, and Developmental Psychiatry Centre (A.C, T.E.M.), Institute of Psychiatry, Psychology, and Neuroscience, King's College London, UK. Center for the Study of Aging and Human Development (K.J.B.), Duke University, Durham, NC; Department of Genetics (D.L.C.), University of North Carolina School of Medicine, Chapel Hill; Butler Columbia Aging Center (M.K., D.W.B.), Columbia University, New York, New York; Sticht Center for Healthy Aging and Alzheimer's Prevention (S.K.), Wake Forest School of Medicine, Winston-Salem, NC; UConn Center on Aging (G.A.K.), University of Connecticut, Farmington, Connecticut, USA; College of Medicine and Health (J.S.M.), University of Exeter Medical School, Devon, UK; and Department of Epidemiology (D.W.B.), Columbia University Mailman School of Public Health, New York, New York
| | - Meeraj Kothari
- From the Department of Psychology and Neuroscience (K.S., A.C., M.L.E., K.C., A.R.H., R.M.H., B.S.W., T.E.M.), and Center for Genomic and Computational Biology (K.S., A.C., B.S.W., T.E.M.), Duke University, Durham, NC; Department of Psychiatry and Behavioral Sciences (A.C., T.E.M.), Duke University School of Medicine, Durham, NC; Social, Genetic, and Developmental Psychiatry Centre (A.C, T.E.M.), Institute of Psychiatry, Psychology, and Neuroscience, King's College London, UK. Center for the Study of Aging and Human Development (K.J.B.), Duke University, Durham, NC; Department of Genetics (D.L.C.), University of North Carolina School of Medicine, Chapel Hill; Butler Columbia Aging Center (M.K., D.W.B.), Columbia University, New York, New York; Sticht Center for Healthy Aging and Alzheimer's Prevention (S.K.), Wake Forest School of Medicine, Winston-Salem, NC; UConn Center on Aging (G.A.K.), University of Connecticut, Farmington, Connecticut, USA; College of Medicine and Health (J.S.M.), University of Exeter Medical School, Devon, UK; and Department of Epidemiology (D.W.B.), Columbia University Mailman School of Public Health, New York, New York
| | - Stephen Kritchevsky
- From the Department of Psychology and Neuroscience (K.S., A.C., M.L.E., K.C., A.R.H., R.M.H., B.S.W., T.E.M.), and Center for Genomic and Computational Biology (K.S., A.C., B.S.W., T.E.M.), Duke University, Durham, NC; Department of Psychiatry and Behavioral Sciences (A.C., T.E.M.), Duke University School of Medicine, Durham, NC; Social, Genetic, and Developmental Psychiatry Centre (A.C, T.E.M.), Institute of Psychiatry, Psychology, and Neuroscience, King's College London, UK. Center for the Study of Aging and Human Development (K.J.B.), Duke University, Durham, NC; Department of Genetics (D.L.C.), University of North Carolina School of Medicine, Chapel Hill; Butler Columbia Aging Center (M.K., D.W.B.), Columbia University, New York, New York; Sticht Center for Healthy Aging and Alzheimer's Prevention (S.K.), Wake Forest School of Medicine, Winston-Salem, NC; UConn Center on Aging (G.A.K.), University of Connecticut, Farmington, Connecticut, USA; College of Medicine and Health (J.S.M.), University of Exeter Medical School, Devon, UK; and Department of Epidemiology (D.W.B.), Columbia University Mailman School of Public Health, New York, New York
| | - George A Kuchel
- From the Department of Psychology and Neuroscience (K.S., A.C., M.L.E., K.C., A.R.H., R.M.H., B.S.W., T.E.M.), and Center for Genomic and Computational Biology (K.S., A.C., B.S.W., T.E.M.), Duke University, Durham, NC; Department of Psychiatry and Behavioral Sciences (A.C., T.E.M.), Duke University School of Medicine, Durham, NC; Social, Genetic, and Developmental Psychiatry Centre (A.C, T.E.M.), Institute of Psychiatry, Psychology, and Neuroscience, King's College London, UK. Center for the Study of Aging and Human Development (K.J.B.), Duke University, Durham, NC; Department of Genetics (D.L.C.), University of North Carolina School of Medicine, Chapel Hill; Butler Columbia Aging Center (M.K., D.W.B.), Columbia University, New York, New York; Sticht Center for Healthy Aging and Alzheimer's Prevention (S.K.), Wake Forest School of Medicine, Winston-Salem, NC; UConn Center on Aging (G.A.K.), University of Connecticut, Farmington, Connecticut, USA; College of Medicine and Health (J.S.M.), University of Exeter Medical School, Devon, UK; and Department of Epidemiology (D.W.B.), Columbia University Mailman School of Public Health, New York, New York
| | - Jonathan S Mill
- From the Department of Psychology and Neuroscience (K.S., A.C., M.L.E., K.C., A.R.H., R.M.H., B.S.W., T.E.M.), and Center for Genomic and Computational Biology (K.S., A.C., B.S.W., T.E.M.), Duke University, Durham, NC; Department of Psychiatry and Behavioral Sciences (A.C., T.E.M.), Duke University School of Medicine, Durham, NC; Social, Genetic, and Developmental Psychiatry Centre (A.C, T.E.M.), Institute of Psychiatry, Psychology, and Neuroscience, King's College London, UK. Center for the Study of Aging and Human Development (K.J.B.), Duke University, Durham, NC; Department of Genetics (D.L.C.), University of North Carolina School of Medicine, Chapel Hill; Butler Columbia Aging Center (M.K., D.W.B.), Columbia University, New York, New York; Sticht Center for Healthy Aging and Alzheimer's Prevention (S.K.), Wake Forest School of Medicine, Winston-Salem, NC; UConn Center on Aging (G.A.K.), University of Connecticut, Farmington, Connecticut, USA; College of Medicine and Health (J.S.M.), University of Exeter Medical School, Devon, UK; and Department of Epidemiology (D.W.B.), Columbia University Mailman School of Public Health, New York, New York
| | - Benjamin S Williams
- From the Department of Psychology and Neuroscience (K.S., A.C., M.L.E., K.C., A.R.H., R.M.H., B.S.W., T.E.M.), and Center for Genomic and Computational Biology (K.S., A.C., B.S.W., T.E.M.), Duke University, Durham, NC; Department of Psychiatry and Behavioral Sciences (A.C., T.E.M.), Duke University School of Medicine, Durham, NC; Social, Genetic, and Developmental Psychiatry Centre (A.C, T.E.M.), Institute of Psychiatry, Psychology, and Neuroscience, King's College London, UK. Center for the Study of Aging and Human Development (K.J.B.), Duke University, Durham, NC; Department of Genetics (D.L.C.), University of North Carolina School of Medicine, Chapel Hill; Butler Columbia Aging Center (M.K., D.W.B.), Columbia University, New York, New York; Sticht Center for Healthy Aging and Alzheimer's Prevention (S.K.), Wake Forest School of Medicine, Winston-Salem, NC; UConn Center on Aging (G.A.K.), University of Connecticut, Farmington, Connecticut, USA; College of Medicine and Health (J.S.M.), University of Exeter Medical School, Devon, UK; and Department of Epidemiology (D.W.B.), Columbia University Mailman School of Public Health, New York, New York
| | - Daniel W Belsky
- From the Department of Psychology and Neuroscience (K.S., A.C., M.L.E., K.C., A.R.H., R.M.H., B.S.W., T.E.M.), and Center for Genomic and Computational Biology (K.S., A.C., B.S.W., T.E.M.), Duke University, Durham, NC; Department of Psychiatry and Behavioral Sciences (A.C., T.E.M.), Duke University School of Medicine, Durham, NC; Social, Genetic, and Developmental Psychiatry Centre (A.C, T.E.M.), Institute of Psychiatry, Psychology, and Neuroscience, King's College London, UK. Center for the Study of Aging and Human Development (K.J.B.), Duke University, Durham, NC; Department of Genetics (D.L.C.), University of North Carolina School of Medicine, Chapel Hill; Butler Columbia Aging Center (M.K., D.W.B.), Columbia University, New York, New York; Sticht Center for Healthy Aging and Alzheimer's Prevention (S.K.), Wake Forest School of Medicine, Winston-Salem, NC; UConn Center on Aging (G.A.K.), University of Connecticut, Farmington, Connecticut, USA; College of Medicine and Health (J.S.M.), University of Exeter Medical School, Devon, UK; and Department of Epidemiology (D.W.B.), Columbia University Mailman School of Public Health, New York, New York
| | - Terrie E Moffitt
- From the Department of Psychology and Neuroscience (K.S., A.C., M.L.E., K.C., A.R.H., R.M.H., B.S.W., T.E.M.), and Center for Genomic and Computational Biology (K.S., A.C., B.S.W., T.E.M.), Duke University, Durham, NC; Department of Psychiatry and Behavioral Sciences (A.C., T.E.M.), Duke University School of Medicine, Durham, NC; Social, Genetic, and Developmental Psychiatry Centre (A.C, T.E.M.), Institute of Psychiatry, Psychology, and Neuroscience, King's College London, UK. Center for the Study of Aging and Human Development (K.J.B.), Duke University, Durham, NC; Department of Genetics (D.L.C.), University of North Carolina School of Medicine, Chapel Hill; Butler Columbia Aging Center (M.K., D.W.B.), Columbia University, New York, New York; Sticht Center for Healthy Aging and Alzheimer's Prevention (S.K.), Wake Forest School of Medicine, Winston-Salem, NC; UConn Center on Aging (G.A.K.), University of Connecticut, Farmington, Connecticut, USA; College of Medicine and Health (J.S.M.), University of Exeter Medical School, Devon, UK; and Department of Epidemiology (D.W.B.), Columbia University Mailman School of Public Health, New York, New York
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70
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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: 14] [Impact Index Per Article: 7.0] [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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71
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Li M, Bao L, Zhu P, Wang S. Effect of metformin on the epigenetic age of peripheral blood in patients with diabetes mellitus. Front Genet 2022; 13:955835. [PMID: 36226195 PMCID: PMC9548538 DOI: 10.3389/fgene.2022.955835] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/29/2022] [Accepted: 08/19/2022] [Indexed: 11/16/2022] Open
Abstract
Background: Metformin has been proven to have an antiaging effect. However, studies on how metformin affects global epigenetic regulation and its effect on the epigenetic clock in diabetes mellitus (DM) patients are limited. This study aims to investigate the impact of metformin on the epigenetic age in subjects with type 2 DM. Results: We collected the peripheral blood of the metformin group and the no-metformin group of the 32 DM patients. Three previously established epigenetic clocks (Hannum, Horvath, and DNAmPhenoAge) were used to estimate the epigenetic age acceleration of the two groups. We defined biological age acceleration for each group by comparing the estimated biological age with the chronological age. Results were presented as follows: 1) all three epigenetic clocks were strongly correlated with chronological age. 2) We found a strong association between metformin intake and slower epigenetic aging by Horvath’s clock and Hannum’s clock. Conclusions: Here, we found an association between metformin intake and slower epigenetic aging.
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Affiliation(s)
- Man Li
- Department of Geriatrics, The Second Medical Center and National Clinical Research Center for Geriatric Diseases, Chinese PLA General Hospital, Beijing, China
| | - Litao Bao
- Institute of Gerontology, Second Medical Center, PLA General Hospital, Beijing, China
| | - Ping Zhu
- Department of Geriatrics, The Second Medical Center and National Clinical Research Center for Geriatric Diseases, Chinese PLA General Hospital, Beijing, China
| | - Shuxia Wang
- Department of Geriatrics, The Second Medical Center and National Clinical Research Center for Geriatric Diseases, Chinese PLA General Hospital, Beijing, China
- *Correspondence: Shuxia Wang,
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72
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Kim B, Vasanthakumar A, Li QS, Nudelman KN, Risacher SL, Davis JW, Idler K, Lee J, Seo SW, Waring JF, Saykin AJ, Nho K. Integrative analysis of DNA methylation and gene expression identifies genes associated with biological aging in Alzheimer's disease. ALZHEIMER'S & DEMENTIA (AMSTERDAM, NETHERLANDS) 2022; 14:e12354. [PMID: 36187194 PMCID: PMC9489162 DOI: 10.1002/dad2.12354] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/10/2022] [Revised: 08/01/2022] [Accepted: 08/01/2022] [Indexed: 11/17/2022]
Abstract
Introduction The acceleration of biological aging is a risk factor for Alzheimer's disease (AD). Here, we performed weighted gene co-expression network analysis (WGCNA) to identify modules and dysregulated genesinvolved in biological aging in AD. Methods We performed WGCNA to identify modules associated with biological clocks and hub genes of the module with the highest module significance. In addition, we performed differential expression analysis and association analysis with AD biomarkers. Results WGCNA identified five modules associated with biological clocks, with the module designated as "purple" showing the strongest association. Functional enrichment analysis revealed that the purple module was related to cell migration and death. Ten genes were identified as hub genes in purple modules, of which CX3CR1 was downregulated in AD and low levels of CX3CR1 expression were associated with AD biomarkers. Conclusion Network analysis identified genes associated with biological clocks, which suggests the genetic architecture underlying biological aging in AD. Highlights Examine links between Alzheimer's disease (AD) peripheral transcriptome and biological aging changes.Weighted gene co-expression network analysis (WGCNA) found five modules related to biological aging.Among the hub genes of the module, CX3CR1 was downregulated in AD.The CX3CR1 expression level was associated with cognitive performance and brain atrophy.
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Affiliation(s)
- Bo‐Hyun Kim
- Center for NeuroimagingDepartment of Radiology and Imaging SciencesIndiana University School of MedicineIndianapolisIndianaUSA
- Samsung Alzheimer Research CenterSamsung Medical CenterSeoulRepublic of Korea
- Department of Health Sciences and TechnologySHAISTSungkyunkwan UniversitySeoulRepublic of Korea
| | | | - Qingqin S. Li
- Neuroscience Therapeutic AreaJanssen Research & Development, LLCTitusvilleNew JerseyUSA
| | - Kelly N.H. Nudelman
- National Centralized Repository for Alzheimer's Disease and Related DementiasIndiana University School of MedicineIndianapolisIndianaUSA
- Indiana Alzheimer Disease CenterIndiana University School of MedicineIndianapolisIndianaUSA
- Department of Medical and Molecular GeneticsIndiana University School of MedicineIndianapolisIndianaUSA
| | - Shannon L. Risacher
- Center for NeuroimagingDepartment of Radiology and Imaging SciencesIndiana University School of MedicineIndianapolisIndianaUSA
- Indiana Alzheimer Disease CenterIndiana University School of MedicineIndianapolisIndianaUSA
| | | | - Kenneth Idler
- Genomics Research CenterAbbVieNorth ChicagoIllinoisUSA
| | - Jong‐Min Lee
- Department of Biomedical EngineeringHanyang UniversitySeoulRepublic of Korea
| | - Sang Won Seo
- Samsung Alzheimer Research CenterSamsung Medical CenterSeoulRepublic of Korea
- Department of NeurologySamsung Medical CenterSungkyunkwan University School of MedicineSeoulRepublic of Korea
- Department of Health Sciences and TechnologySHAISTSungkyunkwan UniversitySeoulRepublic of Korea
| | | | - Andrew J. Saykin
- Center for NeuroimagingDepartment of Radiology and Imaging SciencesIndiana University School of MedicineIndianapolisIndianaUSA
- Indiana Alzheimer Disease CenterIndiana University School of MedicineIndianapolisIndianaUSA
- Department of Medical and Molecular GeneticsIndiana University School of MedicineIndianapolisIndianaUSA
| | - Kwangsik Nho
- Center for NeuroimagingDepartment of Radiology and Imaging SciencesIndiana University School of MedicineIndianapolisIndianaUSA
- Indiana Alzheimer Disease CenterIndiana University School of MedicineIndianapolisIndianaUSA
- Center for Computational Biology and BioinformaticsIndiana University School of MedicineIndianapolisIndianaUSA
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Franzago M, Pilenzi L, Di Rado S, Vitacolonna E, Stuppia L. The epigenetic aging, obesity, and lifestyle. Front Cell Dev Biol 2022; 10:985274. [PMID: 36176280 PMCID: PMC9514048 DOI: 10.3389/fcell.2022.985274] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2022] [Accepted: 08/22/2022] [Indexed: 11/25/2022] Open
Abstract
The prevalence of obesity has dramatically increased worldwide over the past decades. Aging-related chronic conditions, such as type 2 diabetes and cardiovascular disease, are more prevalent in individuals with obesity, thus reducing their lifespan. Epigenetic clocks, the new metrics of biological age based on DNA methylation patterns, could be considered a reflection of the state of one’s health. Several environmental exposures and lifestyle factors can induce epigenetic aging accelerations, including obesity, thus leading to an increased risk of age-related diseases. The insight into the complex link between obesity and aging might have significant implications for the promotion of health and the mitigation of future disease risk. The present narrative review takes into account the interaction between epigenetic aging and obesity, suggesting that epigenome may be an intriguing target for age-related physiological changes and that its modification could influence aging and prolong a healthy lifespan. Therefore, we have focused on DNA methylation age as a clinical biomarker, as well as on the potential reversal of epigenetic age using a personalized diet- and lifestyle-based intervention.
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Affiliation(s)
- Marica Franzago
- Department of Medicine and Aging, School of Medicine and Health Sciences, G. d’Annunzio University, Chieti, Italy
- Center for Advanced Studies and Technology, G. d’Annunzio University, Chieti, Italy
| | - Lucrezia Pilenzi
- Center for Advanced Studies and Technology, G. d’Annunzio University, Chieti, Italy
- Department of Psychological Health and Territorial Sciences, School of Medicine and Health Sciences, G. d’Annunzio University, Chieti, Italy
| | - Sara Di Rado
- Center for Advanced Studies and Technology, G. d’Annunzio University, Chieti, Italy
| | - Ester Vitacolonna
- Department of Medicine and Aging, School of Medicine and Health Sciences, G. d’Annunzio University, Chieti, Italy
- Center for Advanced Studies and Technology, G. d’Annunzio University, Chieti, Italy
| | - Liborio Stuppia
- Center for Advanced Studies and Technology, G. d’Annunzio University, Chieti, Italy
- Department of Psychological Health and Territorial Sciences, School of Medicine and Health Sciences, G. d’Annunzio University, Chieti, Italy
- *Correspondence: Liborio Stuppia,
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Peterson JA, Meng L, Rani A, Sinha P, Johnson AJ, Huo Z, Foster TC, Fillingim RB, Cruz-Almeida Y. Epigenetic aging, knee pain and physical performance in community-dwelling middle-to-older age adults. Exp Gerontol 2022; 166:111861. [PMID: 35640781 PMCID: PMC9887947 DOI: 10.1016/j.exger.2022.111861] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2021] [Revised: 05/10/2022] [Accepted: 05/26/2022] [Indexed: 02/02/2023]
Abstract
Knee pain is a leading cause of disability in the aging population and may indirectly accelerate biological aging processes. Chronological aging increases the risk of developing of knee pain and knee pain reduces physical function; however, limited data exist on how epigenetic aging, a known hallmark of biological aging shown to predict health span and mortality, may influence this relationship. The purpose of this study was to examine whether decreased physical performance associated with knee pain is mediated by markers of epigenetic aging. Participants (57.91 ± 8.04 years) with low impact knee pain (n = 95), high impact knee pain (n = 53) and pain-free controls (n = 26) completed self-reported pain, a blood draw and a short physical performance battery (SPPB) that included balance, walking, and sit to stand tasks. We employed an epigenetic clock previously associated with knee pain and shown to predict overall mortality risk (DNAmGrimAge). Bootstrapped-mediation analyses were used to determine associations of DNAmGrimAge and SPPB between pain groups. Those with high impact and low impact pain had a biologically older epigenetic age (5.14y ± 5.66 and 1.32y ± 5.41, respectively). However, while there were direct effects of pain on overall physical performance, these were not explained by epigenetic aging. Epigenetic aging only mediated the effect of pain on balance performance. Future work is needed to examine pain's impact on biological aging processes including epigenetic aging and its ultimate effect on physical function measures known to predict health span and mortality.
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Affiliation(s)
- Jessica A Peterson
- Pain Research & Intervention Center of Excellence, University of Florida, Gainesville, FL, United States of America; Department of Community Dentistry and Behavioral Science, University of Florida, Gainesville, FL, United States of America
| | - Lingsong Meng
- Department of Biostatistics, University of Florida, Gainesville, FL, United States of America
| | - Asha Rani
- Department of Neuroscience, McKnight Brain Institute, University of Florida, Gainesville, FL, United States of America
| | - Puja Sinha
- Department of Neuroscience, McKnight Brain Institute, University of Florida, Gainesville, FL, United States of America
| | - Alisa J Johnson
- Pain Research & Intervention Center of Excellence, University of Florida, Gainesville, FL, United States of America; Department of Community Dentistry and Behavioral Science, University of Florida, Gainesville, FL, United States of America
| | - Zhiguang Huo
- Department of Biostatistics, University of Florida, Gainesville, FL, United States of America
| | - Thomas C Foster
- Department of Neuroscience, McKnight Brain Institute, University of Florida, Gainesville, FL, United States of America; Genetics and Genomics Program, University of Florida, Gainesville, FL, United States of America
| | - Roger B Fillingim
- Pain Research & Intervention Center of Excellence, University of Florida, Gainesville, FL, United States of America; Department of Community Dentistry and Behavioral Science, University of Florida, Gainesville, FL, United States of America
| | - Yenisel Cruz-Almeida
- Pain Research & Intervention Center of Excellence, University of Florida, Gainesville, FL, United States of America; Department of Community Dentistry and Behavioral Science, University of Florida, Gainesville, FL, United States of America; Department of Neuroscience, McKnight Brain Institute, University of Florida, Gainesville, FL, United States of America.
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75
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Alu hypomethylation in naturally and surgically postmenopausal women; a cross-sectional study. PLoS One 2022; 17:e0273403. [PMID: 36006936 PMCID: PMC9409535 DOI: 10.1371/journal.pone.0273403] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2022] [Accepted: 08/08/2022] [Indexed: 11/19/2022] Open
Abstract
Menopause, which may accelerate the hallmarks of the natural aging process, represents a point in time characterized by the permanent cessation of menstruation following the loss of ovarian estrogen production. Unlike natural menopause, which is characterized by a gradual decrease in estrogen production, when both ovaries are removed before the natural age of menopause, the onset of estrogen deprivation is abrupt. Further, a decrease in genome methylation frequently occurs in aging cells, and the major interspersed repetitive DNA elements in humans are Alu elements. In blood cells, Alu demethylation starts at an age of approximately 40 years, and increases with age. Here, we explored the Alu methylation levels corresponding to age-matched pre-menopausal, naturally postmenopausal, and surgically postmenopausal women aged 45–55 years (n = 60 in each group). Our results indicated that the body mass index (BMI), time-since-menopause, and Alu methylation levels corresponding to the three groups were significantly different. However, no correlations between Alu methylation level and BMI, time-since-menopause, or age were observed. Additionally, the Alu methylation level corresponding to the natural post-menopause group was significantly lower those corresponding to the pre-menopausal (p = 0.001) and surgical post-menopausal (p = 0.037) groups. In conclusion, Alu hypomethylation occurs in naturally postmenopausal women, implying that when women reach the age of natural menopause, the cell aging process may progress significantly with genome hypomethylation. These findings, notwithstanding, further studies are necessary to clarify whether bilateral oophorectomy before the age of menopause affects the cell aging process to a greater extent than natural menopause, and whether estrogen therapy or other interventions can delay cell aging in this regard.
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76
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Kular L, Klose D, Urdánoz-Casado A, Ewing E, Planell N, Gomez-Cabrero D, Needhamsen M, Jagodic M. Epigenetic clock indicates accelerated aging in glial cells of progressive multiple sclerosis patients. Front Aging Neurosci 2022; 14:926468. [PMID: 36092807 PMCID: PMC9454196 DOI: 10.3389/fnagi.2022.926468] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2022] [Accepted: 07/18/2022] [Indexed: 11/28/2022] Open
Abstract
Background Multiple sclerosis (MS) is a chronic inflammatory neurodegenerative disease of the central nervous system (CNS) characterized by irreversible disability at later progressive stages. A growing body of evidence suggests that disease progression depends on age and inflammation within the CNS. We aimed to investigate epigenetic aging in bulk brain tissue and sorted nuclei from MS patients using DNA methylation-based epigenetic clocks. Methods We applied Horvath’s multi-tissue and Shireby’s brain-specific Cortical clock on bulk brain tissue (n = 46), sorted neuronal (n = 54), and glial nuclei (n = 66) from post-mortem brain tissue of progressive MS patients and controls. Results We found a significant increase in age acceleration residuals, corresponding to 3.6 years, in glial cells of MS patients compared to controls (P = 0.0024) using the Cortical clock, which held after adjustment for covariates (Padj = 0.0263). The 4.8-year age acceleration found in MS neurons (P = 0.0054) did not withstand adjustment for covariates and no significant difference in age acceleration residuals was observed in bulk brain tissue between MS patients and controls. Conclusion While the findings warrant replication in larger cohorts, our study suggests that glial cells of progressive MS patients exhibit accelerated biological aging.
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Affiliation(s)
- Lara Kular
- Department of Clinical Neuroscience, Center for Molecular Medicine, Karolinska University Hospital, Karolinska Institutet, Stockholm, Sweden
- Lara Kular,
| | - Dennis Klose
- Department of Clinical Neuroscience, Center for Molecular Medicine, Karolinska University Hospital, Karolinska Institutet, Stockholm, Sweden
| | - Amaya Urdánoz-Casado
- Department of Clinical Neuroscience, Center for Molecular Medicine, Karolinska University Hospital, Karolinska Institutet, Stockholm, Sweden
- Neuroepigenetics Laboratory, Navarrabiomed, Hospital Universitario de Navarra (HUN), Universidad Pública de Navarra (UPNA), IdiSNA, Pamplona, Spain
| | - Ewoud Ewing
- Department of Clinical Neuroscience, Center for Molecular Medicine, Karolinska University Hospital, Karolinska Institutet, Stockholm, Sweden
| | - Nuria Planell
- Translational Bioinformatics Unit, Navarrabiomed, Hospital Universitario de Navarra (HUN), Universidad Pública de Navarra (UPNA), IdiSNA, Pamplona, Spain
| | - David Gomez-Cabrero
- Translational Bioinformatics Unit, Navarrabiomed, Hospital Universitario de Navarra (HUN), Universidad Pública de Navarra (UPNA), IdiSNA, Pamplona, Spain
- Unit of Computational Medicine, Department of Medicine, Center for Molecular Medicine, Karolinska University Hospital, Karolinska Institutet, Stockholm, Sweden
- Mucosal and Salivary Biology Division, King’s College London Dental Institute, London, United Kingdom
- Biological and Environmental Sciences and Engineering Division, King Abdullah University of Science and Technology, Thuwal, Saudi Arabia
| | - Maria Needhamsen
- Department of Clinical Neuroscience, Center for Molecular Medicine, Karolinska University Hospital, Karolinska Institutet, Stockholm, Sweden
| | - Maja Jagodic
- Department of Clinical Neuroscience, Center for Molecular Medicine, Karolinska University Hospital, Karolinska Institutet, Stockholm, Sweden
- *Correspondence: Maja Jagodic,
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Exploring Shared Effects of Multisensory Impairment, Physical Dysfunction, and Cognitive Impairment on Physical Activity: An Observational Study in a National Sample. J Aging Phys Act 2022; 30:572-580. [PMID: 34611055 PMCID: PMC9843725 DOI: 10.1123/japa.2021-0065] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2021] [Revised: 08/14/2021] [Accepted: 08/23/2021] [Indexed: 01/19/2023]
Abstract
Multisensory, physical, and cognitive dysfunction share age-related physiologic disturbances and may have common health effects. We determined whether the effect of multisensory impairment on physical activity (PA) is explained by physical (timed up and go) or cognitive (Short Portable Mental Status Questionnaire) dysfunction. A National Social Life, Health, and Aging Project participant subset (n = 507) underwent objective sensory testing in 2005-2006 and wrist accelerometry in 2010-2011. We related multisensory impairment to PA using multivariate mixed-effects linear regression and compared the effect magnitude after adjusting for physical then cognitive dysfunction. Worse multisensory impairment predicted lower PA across three scales (Global Sensory Impairment: β = -0.04, 95% confidence interval [-0.07, -0.02]; Total Sensory Burden: β = -0.01, 95% confidence interval [-0.03, -0.003]; and Number of Impaired Senses: β = -0.02, 95% confidence interval [-0.04, -0.004]). Effects were similar after accounting for physical and cognitive dysfunction. Findings suggest that sensory, physical, and cognitive dysfunction have unique mechanisms underlying their PA effects.
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Beydoun MA, Beydoun HA, Noren Hooten N, Maldonado AI, Weiss J, Evans MK, Zonderman AB. Epigenetic clocks and their association with trajectories in perceived discrimination and depressive symptoms among US middle-aged and older adults. Aging (Albany NY) 2022; 14:5311-5344. [PMID: 35776531 PMCID: PMC9320538 DOI: 10.18632/aging.204150] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2022] [Accepted: 06/01/2022] [Indexed: 11/30/2022]
Abstract
Background: Perceived discrimination may be associated with accelerated aging later in life, with depressive symptoms acting as potential mediator. Methods: A nationally representative sample of older adults was used [Health and Retirement Study 2010–2016, Age: 50–100 y in 2016, N = 2,806, 55.6% female, 82.3% Non-Hispanic White (NHW)] to evaluate associations of perceived discrimination measures [Experience of discrimination or EOD; and Reasons for Perceived discrimination or RPD) and depressive symptoms (DEP)] with 13 DNAm-based measures of epigenetic aging. Group-based trajectory and four-way mediation analyses were used. Results: Overall, and mostly among female and NHW participants, greater RPD in 2010–2012 had a significant adverse total effect on epigenetic aging [2016: DNAm GrimAge, DunedinPoAm38 (MPOA), Levine (PhenoAge) and Horvath 2], with 20–50% of this effect being explained by a pure indirect effect through DEP in 2014–2016. Among females, sustained elevated DEP (2010–2016) was associated with greater LIN DNAm age (β ± SE: +1.506 ± 0.559, p = 0.009, reduced model), patterns observed for elevated DEP (high vs. low) for GrimAge and MPOA DNAm markers. Overall and in White adults, the relationship of the Levine clock with perceived discrimination in general (both EOD and RPD) was mediated through elevated DEP. Conclusions: Sustained elevations in DEP and RPD were associated with select biological aging measures, consistently among women and White adults, with DEP acting as mediator in several RPD-EPICLOCK associations.
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Affiliation(s)
- May A Beydoun
- Laboratory of Epidemiology and Population Sciences, NIA/NIH/IRP, Baltimore, MD 21224, USA
| | - Hind A Beydoun
- Department of Research Programs, Fort Belvoir Community Hospital, Fort Belvoir, VA 22060, USA
| | - Nicole Noren Hooten
- Laboratory of Epidemiology and Population Sciences, NIA/NIH/IRP, Baltimore, MD 21224, USA
| | - Ana I Maldonado
- Department of Psychology, University of Maryland, Baltimore County, Catonsville, MD 21250, USA
| | - Jordan Weiss
- Department of Demography, University of California Berkeley, Berkeley, CA 94720, USA
| | - Michele K Evans
- Laboratory of Epidemiology and Population Sciences, NIA/NIH/IRP, Baltimore, MD 21224, USA
| | - Alan B Zonderman
- Laboratory of Epidemiology and Population Sciences, NIA/NIH/IRP, Baltimore, MD 21224, USA
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Jain P, Binder AM, Chen B, Parada H, Gallo LC, Alcaraz J, Horvath S, Bhatti P, Whitsel EA, Jordahl K, Baccarelli AA, Hou L, Stewart JD, Li Y, Justice JN, LaCroix AZ. Analysis of Epigenetic Age Acceleration and Healthy Longevity Among Older US Women. JAMA Netw Open 2022; 5:e2223285. [PMID: 35895062 PMCID: PMC9331104 DOI: 10.1001/jamanetworkopen.2022.23285] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/06/2023] Open
Abstract
IMPORTANCE Accelerated biological aging is associated with decreased physical capability and cognitive functioning, which are associated with increased risk of morbidity and mortality. OBJECTIVE We investigated associations between epigenetic age acceleration (EAA), a biomarker associated with aging, and healthy longevity among older women. DESIGN, SETTING, AND PARTICIPANTS This cohort study was a secondary analysis of participants in the Women's Health Initiative (WHI) who were eligible to survive to age 90 years by September 30, 2020. Participants were located in multiple centers. This study was restricted to women with genome-wide DNA methylation data, generated from baseline blood samples within 3 WHI ancillary studies. Median (IQR) follow-up times from baseline were 21.6 (19.6-22.9) years and 21.4 (19.8-22.7) years for women who survived to age 90 years with and without intact mobility, respectively, and 13.2 (8.8-16.7) for women who did not survive to age 90 years. Data were analyzed from December 2020 to July 2021. EXPOSURES EAA was estimated using 4 established "clocks": Horvath pantissue, Hannum, Pheno, and Grim. MAIN OUTCOMES AND MEASURES Using multinomial logistic regression, odds ratios (ORs) and 95% CIs were estimated for 3 healthy longevity outcomes for each clock: survival to age 90 years with intact mobility, survival to age 90 years without intact mobility, and no survival to age 90 years. RESULTS Among 1813 women, there were 464 women (mean [SD] age at baseline, 71.6 [3.5] years) who survived to age 90 years with intact mobility and cognitive functioning, 420 women (mean [SD] age at baseline, 71.3 [3.2] years) who survived to age 90 years without intact mobility and cognitive functioning, and 929 women (mean [SD] age at baseline, 70.2 [3.4] years) who did not survive to age 90 years. Women who survived to age 90 years with intact mobility and cognitive function were healthier at baseline compared with women who survived without those outcomes or who did not survive to age 90 years (eg, 143 women [30.8%] vs 101 women [24.0%] and 202 women [21.7%] with 0 chronic conditions). The odds of surviving to age 90 years with intact mobility were lower for every 1 SD increase in EAA compared with those who did not survive to age 90 years as measured by AgeAccelHorvath (OR, 0.82; 95% CI, 0.69-0.96; P = .01), AgeAccelHannum (OR, 0.67; 95% CI, 0.56-0.80; P < .001), AgeAccelPheno (OR, 0.60; 95% CI, 0.51-0.72; P < .001), and AgeAccelGrim (OR, 0.68; 95% CI, 0.55-0.84; P < .001). ORs were similar for women who survived to age 90 years with intact mobility and cognitive function (eg, AgeAccelHorvath: OR per 1 SD increase in EAA, 0.83; 95% CI, 0.71-0.98; P = .03) compared with women who did not survive to age 90 years. CONCLUSIONS AND RELEVANCE These findings suggest that EAA may be a valid biomarker associated with healthy longevity among older women and may be used for risk stratification and risk estimation of future functional and cognitive aging. Outcomes suggest that future studies may focus on the potential for public health interventions to counteract EAA and its association with poor health outcomes to lower disease burden while increasing longevity.
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Affiliation(s)
- Purva Jain
- Herbert Wertheim School of Public Health and Human Longevity Science, University of California San Diego, La Jolla
| | - Alexandra M. Binder
- Cancer Epidemiology Program, University of Hawaii Cancer Center, Honolulu
- Department of Epidemiology, Fielding School of Public Health, University of California, Los Angeles
| | - Brian Chen
- Herbert Wertheim School of Public Health and Human Longevity Science, University of California San Diego, La Jolla
| | - Humberto Parada
- Division of Epidemiology and Biostatistics, School of Public Health, San Diego State University
- Moores Cancer Center, University of California, San Diego, La Jolla
| | - Linda C. Gallo
- Division of Epidemiology and Biostatistics, School of Public Health, San Diego State University
| | - John Alcaraz
- Moores Cancer Center, University of California, San Diego, La Jolla
| | - Steve Horvath
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles
- Department of Biostatistics, School of Public Health, University of California, Los Angeles
| | - Parveen Bhatti
- Cancer Control Research, BC Cancer, Vancouver, British Columbia, Canada
| | - Eric A. Whitsel
- Department of Epidemiology, Gillings School of Public Health, Chapel Hill, North Carolina
- Department of Medicine, School of Medicine, University of North Carolina at Chapel Hill
| | - Kristina Jordahl
- Department of Epidemiology, School of Public Health, University of Washington, Seattle
| | - Andrea A. Baccarelli
- Department of Environmental Health Sciences, Mailman School of Public Health, Columbia University Irving Medical Center, New York, New York
| | - Lifang Hou
- Institute for Public Health and Medicine, Northwestern University, Chicago, Illinois
| | - James D. Stewart
- Department of Epidemiology, Gillings School of Public Health, Chapel Hill, North Carolina
- Department of Medicine, School of Medicine, University of North Carolina at Chapel Hill
| | - Yun Li
- Department of Genetics, University of North Carolina at Chapel Hill
- Department of Biostatistics, University of North Carolina at Chapel Hill
- Department of Computer Science, University of North Carolina at Chapel Hill
| | - Jamie N. Justice
- Sticht Center for Healthy Aging and Alzheimer’s Prevention, Section of Gerontology and Geriatric Medicine, Department of Internal Medicine, Wake Forest School of Medicine, Winston-Salem, North Carolina
| | - Andrea Z. LaCroix
- Herbert Wertheim School of Public Health and Human Longevity Science, University of California San Diego, La Jolla
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Song AY, Feinberg JI, Bakulski KM, Croen LA, Fallin MD, Newschaffer CJ, Hertz-Picciotto I, Schmidt RJ, Ladd-Acosta C, Volk HE. Prenatal Exposure to Ambient Air Pollution and Epigenetic Aging at Birth in Newborns. Front Genet 2022; 13:929416. [PMID: 35836579 PMCID: PMC9274082 DOI: 10.3389/fgene.2022.929416] [Citation(s) in RCA: 4] [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: 04/26/2022] [Accepted: 05/23/2022] [Indexed: 11/24/2022] Open
Abstract
In utero air pollution exposure has been associated with adverse birth outcomes, yet effects of air pollutants on regulatory mechanisms in fetal growth and critical windows of vulnerability during pregnancy are not well understood. There is evidence that epigenetic alterations may contribute to these effects. DNA methylation (DNAm) based age estimators have been developed and studied extensively with health outcomes in recent years. Growing literature suggests environmental factors, such as air pollution and smoking, can influence epigenetic aging. However, little is known about the effect of prenatal air pollution exposure on epigenetic aging. In this study, we leveraged existing data on prenatal air pollution exposure and cord blood DNAm from 332 mother-child pairs in the Early Autism Risk Longitudinal Investigation (EARLI) and Markers of Autism Risk in Babies-Learning Early Signs (MARBLES), two pregnancy cohorts enrolling women who had a previous child diagnosed with autism spectrum disorder, to assess the relationship of prenatal exposure to air pollution and epigenetic aging at birth. DNAm age was computed using existing epigenetic clock algorithms for cord blood tissue-Knight and Bohlin. Epigenetic age acceleration was defined as the residual of regressing chronological gestational age on DNAm age, accounting for cell type proportions. Multivariable linear regression models and distributed lag models (DLMs), adjusting for child sex, maternal race/ethnicity, study sites, year of birth, maternal education, were completed. In the single-pollutant analysis, we observed exposure to PM2.5, PM10, and O3 during preconception period and pregnancy period were associated with decelerated epigenetic aging at birth. For example, pregnancy average PM10 exposure (per 10 unit increase) was associated with epigenetic age deceleration at birth (weeks) for both Knight and Bohlin clocks (β = -0.62, 95% CI: -1.17, -0.06; β = -0.32, 95% CI: -0.63, -0.01, respectively). Weekly DLMs revealed that increasing PM2.5 during the first trimester and second trimester were associated with decelerated epigenetic aging and that increasing PM10 during the preconception period was associated with decelerated epigenetic aging, using the Bohlin clock estimate. Prenatal ambient air pollution exposure, particularly in early and mid-pregnancy, was associated with decelerated epigenetic aging at birth.
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Affiliation(s)
- Ashley Y. Song
- Department of Mental Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States
- Wendy Klag Center for Autism and Developmental Disabilities, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States
| | - Jason I. Feinberg
- Department of Mental Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States
- Wendy Klag Center for Autism and Developmental Disabilities, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States
| | - Kelly M. Bakulski
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, United States
| | - Lisa A. Croen
- Division of Research, Kaiser Permanente, Oakland, CA, United States
| | - M. Daniele Fallin
- Department of Mental Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States
- Wendy Klag Center for Autism and Developmental Disabilities, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States
| | - Craig J. Newschaffer
- College of Health and Human Development, Pennsylvania State University, State College, PA, United States
| | - Irva Hertz-Picciotto
- Department of Public Health Sciences, UC Davis, Davis CA and the UC Davis MIND Institute, Sacramento, CA, United States
| | - Rebecca J. Schmidt
- Department of Public Health Sciences, UC Davis, Davis CA and the UC Davis MIND Institute, Sacramento, CA, United States
| | - Christine Ladd-Acosta
- Department of Mental Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States
- Wendy Klag Center for Autism and Developmental Disabilities, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States
| | - Heather E. Volk
- Department of Mental Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States
- Wendy Klag Center for Autism and Developmental Disabilities, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States
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Perez NB, Vorderstrasse AA, Yu G, Melkus GD, Wright F, Ginsberg SD, Crusto CA, Sun YV, Taylor JY. Associations Between DNA Methylation Age Acceleration, Depressive Symptoms, and Cardiometabolic Traits in African American Mothers From the InterGEN Study. Epigenet Insights 2022; 15:25168657221109781. [PMID: 35784386 PMCID: PMC9247996 DOI: 10.1177/25168657221109781] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2022] [Accepted: 06/06/2022] [Indexed: 11/20/2022] Open
Abstract
Background African American women (AAW) have a high risk of both cardiometabolic (CM) illness and depressive symptoms. Depressive symptoms co-occur in individuals with CM illness at higher rates than the general population, and accelerated aging may explain this. In this secondary analysis, we examined associations between age acceleration; depressive symptoms; and CM traits (hypertension, diabetes mellitus [DM], and obesity) in a cohort of AAW. Methods Genomic and clinical data from the InterGEN cohort (n = 227) were used. Age acceleration was based on the Horvath method of DNA methylation (DNAm) age estimation. Accordingly, DNAm age acceleration (DNAm AA) was defined as the residuals from a linear regression of DNAm age on chronological age. Spearman's correlations, linear and logistic regression examined associations between DNAm AA, depressive symptoms, and CM traits. Results DNAm AA did not associate with total depressive symptom scores. DNAm AA correlated with specific symptoms including self-disgust/self-hate (-0.13, 95% CI -0.26, -0.01); difficulty with making decisions (-0.15, 95% CI -0.28, -0.02); and worry over physical health (0.15, 95% CI 0.02, 0.28), but were not statistically significant after multiple comparison correction. DNAm AA associated with obesity (0.08, 95% CI 1.02, 1.16), hypertension (0.08, 95% CI 1.01, 1.17), and DM (0.20, 95% CI 1.09, 1.40), after adjustment for potential confounders. Conclusions Associations between age acceleration and depressive symptoms may be highly nuanced and dependent on study design contexts. Factors other than age acceleration may explain the connection between depressive symptoms and CM traits. AAW with CM traits may be at increased risk of accelerated aging.
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Affiliation(s)
| | | | - Gary Yu
- Rory Meyers College of Nursing, New
York University, New York, NY, USA
| | | | - Fay Wright
- Rory Meyers College of Nursing, New
York University, New York, NY, USA
| | - Stephen D Ginsberg
- Center for Dementia Research, Nathan
Kline Institute, Orangeburg, NY, USA
- NYU Grossman School of Medicine, New
York, NY, USA
| | - Cindy A Crusto
- Yale School of Medicine, Orange, CT,
USA
- Department of Psychology, University of
Pretoria, Pretoria, South Africa
| | - Yan V Sun
- Emory University School of Public
Health, Atlanta, GA, USA
- Atlanta VA Health Care System, Decatur,
GA, USA
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82
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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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83
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Domingo-Relloso A, Riffo-Campos AL, Powers M, Tellez-Plaza M, Haack K, Brown RH, Umans JG, Fallin MD, Cole SA, Navas-Acien A, Sanchez TR. An epigenome-wide study of DNA methylation profiles and lung function among American Indians in the Strong Heart Study. Clin Epigenetics 2022; 14:75. [PMID: 35681244 PMCID: PMC9185990 DOI: 10.1186/s13148-022-01294-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/07/2022] [Accepted: 05/25/2022] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Epigenetic modifications, including DNA methylation (DNAm), are often related to environmental exposures, and are increasingly recognized as key processes in the pathogenesis of chronic lung disease. American Indian communities have a high burden of lung disease compared to the national average. The objective of this study was to investigate the association of DNAm and lung function in the Strong Heart Study (SHS). We conducted a cross-sectional study of American Indian adults, 45-74 years of age who participated in the SHS. DNAm was measured using the Illumina Infinium Human MethylationEPIC platform at baseline (1989-1991). Lung function was measured via spirometry, including forced expiratory volume in 1 s (FEV1) and forced vital capacity (FVC), at visit 2 (1993-1995). Airflow limitation was defined as FEV1 < 70% predicted and FEV1/FVC < 0.7, restriction was defined as FEV1/FVC > 0.7 and FVC < 80% predicted, and normal spirometry was defined as FEV1/FVC > 0.7, FEV1 > 70% predicted, FVC > 80% predicted. We used elastic-net models to select relevant CpGs for lung function and spirometry-defined lung disease. We also conducted bioinformatic analyses to evaluate the biological plausibility of the findings. RESULTS Among 1677 participants, 21.2% had spirometry-defined airflow limitation and 13.6% had spirometry-defined restrictive pattern lung function. Elastic-net models selected 1118 Differentially Methylated Positions (DMPs) as predictors of airflow limitation and 1385 for restrictive pattern lung function. A total of 12 DMPs overlapped between airflow limitation and restrictive pattern. EGFR, MAPK1 and PRPF8 genes were the most connected nodes in the protein-protein interaction network. Many of the DMPs targeted genes with biological roles related to lung function such as protein kinases. CONCLUSION We found multiple differentially methylated CpG sites associated with chronic lung disease. These signals could contribute to better understand molecular mechanisms involved in lung disease, as assessed systemically, as well as to identify patterns that could be useful for diagnostic purposes. Further experimental and longitudinal studies are needed to assess whether DNA methylation has a causal role in lung disease.
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Affiliation(s)
- Arce Domingo-Relloso
- Integrative Epidemiology Group, Department of Chronic Diseases Epidemiology, National Center for Epidemiology, Carlos III Health Institute, 28029, Madrid, Spain. .,Department of Environmental Health Sciences, Columbia University Mailman School of Public Health, New York, USA. .,Department of Statistics and Operations Research, University of Valencia, Valencia, Spain.
| | - Angela L Riffo-Campos
- Millennium Nucleus on Sociomedicine (SocioMed) and Vicerrectoría Académica, Universidad de La Frontera, Temuco, Chile.,Department of Computer Science, ETSE, University of Valencia, Valencia, Spain
| | - Martha Powers
- United States Environmental Protection Agency, Washington, DC, USA
| | - Maria Tellez-Plaza
- Integrative Epidemiology Group, Department of Chronic Diseases Epidemiology, National Center for Epidemiology, Carlos III Health Institute, 28029, Madrid, Spain
| | - Karin Haack
- Population Health Program, Texas Biomedical Research Institute, San Antonio, TX, USA
| | - Robert H Brown
- Department of Environmental Health and Engineering, Johns Hopkins Bloomberg School of Public Health, Baltimore, USA
| | - Jason G Umans
- MedStar Health Research Institute, Hyattsville, MD, USA.,Georgetown-Howard Universities Center for Clinical and Translational Science, Washington, DC, USA
| | - M Daniele Fallin
- Departments of Mental Health and Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, USA
| | - Shelley A Cole
- Population Health Program, Texas Biomedical Research Institute, San Antonio, TX, USA
| | - Ana Navas-Acien
- Department of Environmental Health Sciences, Columbia University Mailman School of Public Health, New York, USA
| | - Tiffany R Sanchez
- Department of Environmental Health Sciences, Columbia University Mailman School of Public Health, New York, USA
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84
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Milicic L, Vacher M, Porter T, Doré V, Burnham SC, Bourgeat P, Shishegar R, Doecke J, Armstrong NJ, Tankard R, Maruff P, Masters CL, Rowe CC, Villemagne VL, Laws SM. Comprehensive analysis of epigenetic clocks reveals associations between disproportionate biological ageing and hippocampal volume. GeroScience 2022; 44:1807-1823. [PMID: 35445885 PMCID: PMC9213584 DOI: 10.1007/s11357-022-00558-8] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2022] [Accepted: 03/30/2022] [Indexed: 12/21/2022] Open
Abstract
The concept of age acceleration, the difference between biological age and chronological age, is of growing interest, particularly with respect to age-related disorders, such as Alzheimer's Disease (AD). Whilst studies have reported associations with AD risk and related phenotypes, there remains a lack of consensus on these associations. Here we aimed to comprehensively investigate the relationship between five recognised measures of age acceleration, based on DNA methylation patterns (DNAm age), and cross-sectional and longitudinal cognition and AD-related neuroimaging phenotypes (volumetric MRI and Amyloid-β PET) in the Australian Imaging, Biomarkers and Lifestyle (AIBL) and the Alzheimer's Disease Neuroimaging Initiative (ADNI). Significant associations were observed between age acceleration using the Hannum epigenetic clock and cross-sectional hippocampal volume in AIBL and replicated in ADNI. In AIBL, several other findings were observed cross-sectionally, including a significant association between hippocampal volume and the Hannum and Phenoage epigenetic clocks. Further, significant associations were also observed between hippocampal volume and the Zhang and Phenoage epigenetic clocks within Amyloid-β positive individuals. However, these were not validated within the ADNI cohort. No associations between age acceleration and other Alzheimer's disease-related phenotypes, including measures of cognition or brain Amyloid-β burden, were observed, and there was no association with longitudinal change in any phenotype. This study presents a link between age acceleration, as determined using DNA methylation, and hippocampal volume that was statistically significant across two highly characterised cohorts. The results presented in this study contribute to a growing literature that supports the role of epigenetic modifications in ageing and AD-related phenotypes.
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Affiliation(s)
- Lidija Milicic
- Centre for Precision Health, Edith Cowan University, 270 Joondalup Drive, Joondalup, Western Australia, 6027, Australia
- Collaborative Genomics and Translation Group, School of Medical and Health Sciences, Edith Cowan University, Joondalup, Western Australia, 6027, Australia
| | - Michael Vacher
- Centre for Precision Health, Edith Cowan University, 270 Joondalup Drive, Joondalup, Western Australia, 6027, Australia
- Collaborative Genomics and Translation Group, School of Medical and Health Sciences, Edith Cowan University, Joondalup, Western Australia, 6027, Australia
- CSIRO Health and Biosecurity, Australian E-Health Research Centre, Floreat, Western Australia, 6014, Australia
| | - Tenielle Porter
- Centre for Precision Health, Edith Cowan University, 270 Joondalup Drive, Joondalup, Western Australia, 6027, Australia
- Collaborative Genomics and Translation Group, School of Medical and Health Sciences, Edith Cowan University, Joondalup, Western Australia, 6027, Australia
- School of Pharmacy and Biomedical Sciences, Faculty of Health Sciences, Curtin Health Innovation Research Institute, Curtin University, Bentley, Western Australia, 6102, Australia
| | - Vincent Doré
- Australian E-Health Research Centre, CSIRO, Parkville, Victoria, 3052, Australia
- Department of Molecular Imaging and Therapy and Centre for PET, Austin Health, Heidelberg, Victoria, Australia
| | - Samantha C Burnham
- Centre for Precision Health, Edith Cowan University, 270 Joondalup Drive, Joondalup, Western Australia, 6027, Australia
- Australian E-Health Research Centre, CSIRO, Parkville, Victoria, 3052, Australia
| | - Pierrick Bourgeat
- Australian E-Health Research Centre, CSIRO, Herston, Queensland, 4029, Australia
| | - Rosita Shishegar
- Australian E-Health Research Centre, CSIRO, Parkville, Victoria, 3052, Australia
- School of Psychological Sciences and Turner Institute for Brain and Mental Health, Monash University, Melbourne, VIC, Australia
| | - James Doecke
- Centre for Precision Health, Edith Cowan University, 270 Joondalup Drive, Joondalup, Western Australia, 6027, Australia
- Australian E-Health Research Centre, CSIRO, Herston, Queensland, 4029, Australia
| | - Nicola J Armstrong
- Department of Mathematics and Statistics, Curtin University, Bentley, Western Australia, Australia
| | - Rick Tankard
- School of Mathematics and Statistics, Murdoch University, Perth, Western Australia, Australia
| | - Paul Maruff
- Florey Institute of Neuroscience and Mental Health, The University of Melbourne, Parkville, VIC, 3052, Australia
- Cogstate Ltd, Melbourne, VIC, Australia
| | - Colin L Masters
- Florey Institute of Neuroscience and Mental Health, The University of Melbourne, Parkville, VIC, 3052, Australia
| | - Christopher C Rowe
- Department of Molecular Imaging and Therapy and Centre for PET, Austin Health, Heidelberg, Victoria, Australia
- Florey Institute of Neuroscience and Mental Health, The University of Melbourne, Parkville, VIC, 3052, Australia
| | - Victor L Villemagne
- Centre for Precision Health, Edith Cowan University, 270 Joondalup Drive, Joondalup, Western Australia, 6027, Australia
- Department of Molecular Imaging and Therapy and Centre for PET, Austin Health, Heidelberg, Victoria, Australia
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
| | - Simon M Laws
- Centre for Precision Health, Edith Cowan University, 270 Joondalup Drive, Joondalup, Western Australia, 6027, Australia.
- Collaborative Genomics and Translation Group, School of Medical and Health Sciences, Edith Cowan University, Joondalup, Western Australia, 6027, Australia.
- School of Pharmacy and Biomedical Sciences, Faculty of Health Sciences, Curtin Health Innovation Research Institute, Curtin University, Bentley, Western Australia, 6102, Australia.
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85
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Yousefi PD, Suderman M, Langdon R, Whitehurst O, Davey Smith G, Relton CL. DNA methylation-based predictors of health: applications and statistical considerations. Nat Rev Genet 2022; 23:369-383. [PMID: 35304597 DOI: 10.1038/s41576-022-00465-w] [Citation(s) in RCA: 69] [Impact Index Per Article: 34.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 02/18/2022] [Indexed: 12/12/2022]
Abstract
DNA methylation data have become a valuable source of information for biomarker development, because, unlike static genetic risk estimates, DNA methylation varies dynamically in relation to diverse exogenous and endogenous factors, including environmental risk factors and complex disease pathology. Reliable methods for genome-wide measurement at scale have led to the proliferation of epigenome-wide association studies and subsequently to the development of DNA methylation-based predictors across a wide range of health-related applications, from the identification of risk factors or exposures, such as age and smoking, to early detection of disease or progression in cancer, cardiovascular and neurological disease. This Review evaluates the progress of existing DNA methylation-based predictors, including the contribution of machine learning techniques, and assesses the uptake of key statistical best practices needed to ensure their reliable performance, such as data-driven feature selection, elimination of data leakage in performance estimates and use of generalizable, adequately powered training samples.
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Affiliation(s)
- Paul D Yousefi
- Medical Research Council Integrative Epidemiology Unit at the University of Bristol, University of Bristol, Bristol, UK
| | - Matthew Suderman
- Medical Research Council Integrative Epidemiology Unit at the University of Bristol, University of Bristol, Bristol, UK
| | - Ryan Langdon
- Medical Research Council Integrative Epidemiology Unit at the University of Bristol, University of Bristol, Bristol, UK
| | - Oliver Whitehurst
- Medical Research Council Integrative Epidemiology Unit at the University of Bristol, University of Bristol, Bristol, UK
| | - George Davey Smith
- Medical Research Council Integrative Epidemiology Unit at the University of Bristol, University of Bristol, Bristol, UK
| | - Caroline L Relton
- Medical Research Council Integrative Epidemiology Unit at the University of Bristol, University of Bristol, Bristol, UK.
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86
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Huan T, Nguyen S, Colicino E, Ochoa‐Rosales C, Hill WD, Brody JA, Soerensen M, Zhang Y, Baldassari A, Elhadad MA, Toshiko T, Zheng Y, Domingo‐Relloso A, Lee DH, Ma J, Yao C, Liu C, Hwang S, Joehanes R, Fornage M, Bressler J, van Meurs JB, Debrabant B, Mengel‐From J, Hjelmborg J, Christensen K, Vokonas P, Schwartz J, Gahrib SA, Sotoodehnia N, Sitlani CM, Kunze S, Gieger C, Peters A, Waldenberger M, Deary IJ, Ferrucci L, Qu Y, Greenland P, Lloyd‐Jones DM, Hou L, Bandinelli S, Voortman T, Hermann B, Baccarelli A, Whitsel E, Pankow JS, Levy D. Integrative analysis of clinical and epigenetic biomarkers of mortality. Aging Cell 2022; 21:e13608. [PMID: 35546478 PMCID: PMC9197414 DOI: 10.1111/acel.13608] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2021] [Revised: 03/03/2022] [Accepted: 03/24/2022] [Indexed: 01/28/2023] Open
Abstract
DNA methylation (DNAm) has been reported to be associated with many diseases and with mortality. We hypothesized that the integration of DNAm with clinical risk factors would improve mortality prediction. We performed an epigenome-wide association study of whole blood DNAm in relation to mortality in 15 cohorts (n = 15,013). During a mean follow-up of 10 years, there were 4314 deaths from all causes including 1235 cardiovascular disease (CVD) deaths and 868 cancer deaths. Ancestry-stratified meta-analysis of all-cause mortality identified 163 CpGs in European ancestry (EA) and 17 in African ancestry (AA) participants at p < 1 × 10-7 , of which 41 (EA) and 16 (AA) were also associated with CVD death, and 15 (EA) and 9 (AA) with cancer death. We built DNAm-based prediction models for all-cause mortality that predicted mortality risk after adjusting for clinical risk factors. The mortality prediction model trained by integrating DNAm with clinical risk factors showed an improvement in prediction of cancer death with 5% increase in the C-index in a replication cohort, compared with the model including clinical risk factors alone. Mendelian randomization identified 15 putatively causal CpGs in relation to longevity, CVD, or cancer risk. For example, cg06885782 (in KCNQ4) was positively associated with risk for prostate cancer (Beta = 1.2, PMR = 4.1 × 10-4 ) and negatively associated with longevity (Beta = -1.9, PMR = 0.02). Pathway analysis revealed that genes associated with mortality-related CpGs are enriched for immune- and cancer-related pathways. We identified replicable DNAm signatures of mortality and demonstrated the potential utility of CpGs as informative biomarkers for prediction of mortality risk.
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Affiliation(s)
- Tianxiao Huan
- The Framingham Heart StudyFraminghamMassachusettsUSA
- The Population Sciences BranchDivision of Intramural ResearchNational Heart, Lung, and Blood InstituteNational Institutes of HealthBethesdaMarylandUSA
- Department of Ophthalmology and Visual SciencesUniversity of Massachusetts Medical SchoolWorcesterMassachusettsUSA
| | - Steve Nguyen
- Division of Epidemiology & Community HealthSchool of Public HealthUniversity of MinnesotaMinneapolisMinnesotaUSA
| | - Elena Colicino
- Icahn School of Medicine at Mount SinaiNew YorkNew YorkUSA
| | - Carolina Ochoa‐Rosales
- Department of EpidemiologyErasmus University Medical CenterRotterdamthe Netherlands
- Centro de Vida Saludable de la Universidad de ConcepciónConcepciónChile
| | - W. David Hill
- Department of PsychologyLothian Birth CohortsUniversity of EdinburghEdinburghUK
| | - Jennifer A. Brody
- Cardiovascular Health Research UnitDepartment of MedicineUniversity of WashingtonSeattleWashingtonUSA
| | - Mette Soerensen
- Department of Public HealthEpidemiology, Biostatistics and BiodemographyUniversity of Southern DenmarkOdense CDenmark
- Department of Clinical Biochemistry and PharmacologyCenter for Individualized Medicine in Arterial DiseasesOdense University HospitalOdense CDenmark
- Department of Clinical GeneticsOdense University HospitalOdense CDenmark
| | - Yan Zhang
- Division of Clinical Epidemiology & Aging ResearchGerman Cancer Rsrch Ctr (DKFZ)HeidelbergGermany
| | - Antoine Baldassari
- Department of EpidemiologyGillings School of Global Public HealthUniversity of North CarolinaChapel HillNorth CarolinaUSA
| | - Mohamed Ahmed Elhadad
- Research Unit of Molecular EpidemiologyHelmholtz Zentrum MünchenGerman Research Center for Environmental HealthNeuherbergGermany
- Institute of EpidemiologyHelmholtz Zentrum MünchenGerman Research Center for Environmental HealthNeuherbergGermany
- German Research Center for Cardiovascular Disease (DZHK)Partner Site Munich Heart AllianceMunichGermany
| | - Tanaka Toshiko
- Translational Gerontology BranchNational Institute on AgingBaltimoreMarylandUSA
| | - Yinan Zheng
- Department of Preventive MedicineNorthwestern University Feinberg School of MedicineChicagoIllinoisUSA
| | - Arce Domingo‐Relloso
- Department of Chronic Diseases EpidemiologyNational Center for EpidemiologyCarlos III Health InstituteMadridSpain
- Department of Environmental Health SciencesColumbia University Mailman School of Public HealthNew YorkNew YorkUSA
- Department of Statistics and Operations ResearchUniversity of ValenciaValenciaSpain
| | - Dong Heon Lee
- The Framingham Heart StudyFraminghamMassachusettsUSA
- The Population Sciences BranchDivision of Intramural ResearchNational Heart, Lung, and Blood InstituteNational Institutes of HealthBethesdaMarylandUSA
| | - Jiantao Ma
- The Framingham Heart StudyFraminghamMassachusettsUSA
- The Population Sciences BranchDivision of Intramural ResearchNational Heart, Lung, and Blood InstituteNational Institutes of HealthBethesdaMarylandUSA
- Nutrition Epidemiology and Data ScienceFriedman School of Nutrition Science and PolicyTufts UniversityBostonMassachusettsUSA
| | - Chen Yao
- The Framingham Heart StudyFraminghamMassachusettsUSA
- The Population Sciences BranchDivision of Intramural ResearchNational Heart, Lung, and Blood InstituteNational Institutes of HealthBethesdaMarylandUSA
| | - Chunyu Liu
- Department of BiostatisticsBoston University School of Public HealthBostonMassachusettsUSA
| | - Shih‐Jen Hwang
- The Framingham Heart StudyFraminghamMassachusettsUSA
- The Population Sciences BranchDivision of Intramural ResearchNational Heart, Lung, and Blood InstituteNational Institutes of HealthBethesdaMarylandUSA
| | - Roby Joehanes
- The Framingham Heart StudyFraminghamMassachusettsUSA
- The Population Sciences BranchDivision of Intramural ResearchNational Heart, Lung, and Blood InstituteNational Institutes of HealthBethesdaMarylandUSA
| | - Myriam Fornage
- Human Genetics CenterSchool of Public HealthUniversity of Texas Health Science Center at HoustonHoustonTexasUSA
| | - Jan Bressler
- Department of Internal MedicineErasmusRotterdamthe Netherlands
| | | | - Birgit Debrabant
- Department of Public HealthEpidemiology, Biostatistics and BiodemographyUniversity of Southern DenmarkOdense CDenmark
| | - Jonas Mengel‐From
- Department of Public HealthEpidemiology, Biostatistics and BiodemographyUniversity of Southern DenmarkOdense CDenmark
- Department of Clinical GeneticsOdense University HospitalOdense CDenmark
| | - Jacob Hjelmborg
- Department of Public HealthEpidemiology, Biostatistics and BiodemographyUniversity of Southern DenmarkOdense CDenmark
| | - Kaare Christensen
- Department of Public HealthEpidemiology, Biostatistics and BiodemographyUniversity of Southern DenmarkOdense CDenmark
- Department of Clinical GeneticsOdense University HospitalOdense CDenmark
| | - Pantel Vokonas
- Veterans AffairsNormative Aging StudyBostonMassachusettsUSA
- Veterans AffairsBoston Healthcare SystemBostonMassachusettsUSA
- Boston University School of Public HealthBostonMassachusettsUSA
| | - Joel Schwartz
- Departments of Environmental Health and EpidemiologyHarvard TH Chan School of Public HealthBostonMassachusettsUSA
| | - Sina A. Gahrib
- Cardiovascular Health Research UnitDepartment of MedicineUniversity of WashingtonSeattleWashingtonUSA
- Department of PsychologyUniv of EdinburghEdinburghUK
| | - Nona Sotoodehnia
- Cardiovascular Health Research UnitDepartment of MedicineUniversity of WashingtonSeattleWashingtonUSA
| | - Colleen M. Sitlani
- Cardiovascular Health Research UnitDepartment of MedicineUniversity of WashingtonSeattleWashingtonUSA
| | - Sonja Kunze
- Research Unit of Molecular EpidemiologyHelmholtz Zentrum MünchenGerman Research Center for Environmental HealthNeuherbergGermany
- Institute of EpidemiologyHelmholtz Zentrum MünchenGerman Research Center for Environmental HealthNeuherbergGermany
| | - Christian Gieger
- Research Unit of Molecular EpidemiologyHelmholtz Zentrum MünchenGerman Research Center for Environmental HealthNeuherbergGermany
- Institute of EpidemiologyHelmholtz Zentrum MünchenGerman Research Center for Environmental HealthNeuherbergGermany
- German Research Center for Cardiovascular Disease (DZHK)Partner Site Munich Heart AllianceMunichGermany
| | - Annette Peters
- Institute of EpidemiologyHelmholtz Zentrum MünchenGerman Research Center for Environmental HealthNeuherbergGermany
- German Research Center for Cardiovascular Disease (DZHK)Partner Site Munich Heart AllianceMunichGermany
- German Center for Diabetes Research (DZD)München‐Neuherberg, NeuherbergGermany
- Institute of Medical Information Sciences, Biometry and EpidemiologyLudwig‐Maximilians‐UniversityMunichGermany
| | - Melanie Waldenberger
- Research Unit of Molecular EpidemiologyHelmholtz Zentrum MünchenGerman Research Center for Environmental HealthNeuherbergGermany
- Institute of EpidemiologyHelmholtz Zentrum MünchenGerman Research Center for Environmental HealthNeuherbergGermany
- German Research Center for Cardiovascular Disease (DZHK)Partner Site Munich Heart AllianceMunichGermany
| | - Ian J. Deary
- Division of PulmonaryCritical Care and Sleep MedicineCenter for Lung BiologyUniversity of WashingtonSeattleWashingtonUSA
| | - Luigi Ferrucci
- Translational Gerontology BranchNational Institute on AgingBaltimoreMarylandUSA
| | - Yishu Qu
- Department of Preventive MedicineNorthwestern University Feinberg School of MedicineChicagoIllinoisUSA
| | - Philip Greenland
- Department of Preventive MedicineNorthwestern University Feinberg School of MedicineChicagoIllinoisUSA
| | - Donald M. Lloyd‐Jones
- Department of Preventive MedicineNorthwestern University Feinberg School of MedicineChicagoIllinoisUSA
| | - Lifang Hou
- Department of Preventive MedicineNorthwestern University Feinberg School of MedicineChicagoIllinoisUSA
| | | | - Trudy Voortman
- Department of EpidemiologyErasmus University Medical CenterRotterdamthe Netherlands
| | - Brenner Hermann
- Division of Clinical Epidemiology & Aging ResearchGerman Cancer Rsrch Ctr (DKFZ)HeidelbergGermany
- Network Aging Research (NAR)University of HeidelbergHeidelbergGermany
| | - Andrea Baccarelli
- Precision Medicine ProgramDepartment of Environmental Health SciencesMailman School of Public HealthColumbia UniversityNew YorkNew YorkUSA
| | - Eric Whitsel
- Department of EpidemiologyGillings School of Global Public HealthUniversity of North CarolinaChapel HillNorth CarolinaUSA
- Department of MedicineSchool of MedicineUniversity of North CarolinaChapel HillNorth CarolinaUSA
| | - James S. Pankow
- Division of Epidemiology & Community HealthSchool of Public HealthUniversity of MinnesotaMinneapolisMinnesotaUSA
| | - Daniel Levy
- The Framingham Heart StudyFraminghamMassachusettsUSA
- The Population Sciences BranchDivision of Intramural ResearchNational Heart, Lung, and Blood InstituteNational Institutes of HealthBethesdaMarylandUSA
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Schmitz LL, Zhao W, Ratliff SM, Goodwin J, Miao J, Lu Q, Guo X, Taylor KD, Ding J, Liu Y, Levine M, Smith JA. The Socioeconomic Gradient in Epigenetic Ageing Clocks: Evidence from the Multi-Ethnic Study of Atherosclerosis and the Health and Retirement Study. Epigenetics 2022; 17:589-611. [PMID: 34227900 PMCID: PMC9235889 DOI: 10.1080/15592294.2021.1939479] [Citation(s) in RCA: 42] [Impact Index Per Article: 21.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2021] [Accepted: 06/02/2021] [Indexed: 12/25/2022] Open
Abstract
Epigenetic clocks have been widely used to predict disease risk in multiple tissues or cells. Their success as a measure of biological ageing has prompted research on the connection between epigenetic pathways of ageing and the socioeconomic gradient in health and mortality. However, studies examining social correlates of epigenetic ageing have yielded inconsistent results. We conducted a comprehensive, comparative analysis of associations between various dimensions of socioeconomic status (SES) (education, income, wealth, occupation, neighbourhood environment, and childhood SES) and eight epigenetic clocks in two well-powered US ageing studies: The Multi-Ethnic Study of Atherosclerosis (MESA) (n = 1,211) and the Health and Retirement Study (HRS) (n = 4,018). In both studies, we found robust associations between SES measures in adulthood and the GrimAge and DunedinPoAm clocks (Bonferroni-corrected p-value < 0.01). In the HRS, significant associations with the Levine and Yang clocks were also evident. These associations were only partially mediated by smoking, alcohol consumption, and obesity, which suggests that differences in health behaviours alone cannot explain the SES gradient in epigenetic ageing in older adults. Further analyses revealed concurrent associations between polygenic risk for accelerated intrinsic epigenetic ageing, SES, and the Levine clock, indicating that genetic risk and social disadvantage may contribute additively to faster biological aging.
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Affiliation(s)
- Lauren L. Schmitz
- Robert M. La Follette School of Public Affairs, University of Wisconsin-Madison, USA
| | - Wei Zhao
- Department of Epidemiology, School of Public Health, University of Michigan, USA
| | - Scott M. Ratliff
- Department of Epidemiology, School of Public Health, University of Michigan, USA
| | - Julia Goodwin
- Department of Sociology, University of Wisconsin-Madison, USA
| | - Jiacheng Miao
- Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, USA
| | - Qiongshi Lu
- Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, USA
- Department of Statistics, University of Wisconsin-Madison, USA
| | - Xiuqing Guo
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, USA
| | - Kent D. Taylor
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, USA
| | - Jingzhong Ding
- Gerontology and Geriatric Medicine, School of Medicine, Wake Forest University, USA
| | - Yongmei Liu
- Department of Medicine, School of Medicine, Duke University, USA
| | - Morgan Levine
- Department of Pathology, School of Medicine, Yale University, USA
| | - Jennifer A. Smith
- Department of Epidemiology, School of Public Health, University of Michigan, USA
- Survey Research Center, Institute for Social Research, University of Michigan, USA
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Guevara EE, Hopkins WD, Hof PR, Ely JJ, Bradley BJ, Sherwood CC. Epigenetic aging of the prefrontal cortex and cerebellum in humans and chimpanzees. Epigenetics 2022; 17:1774-1785. [PMID: 35603816 DOI: 10.1080/15592294.2022.2080993] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/03/2022] Open
Abstract
Epigenetic age has emerged as an important biomarker of biological aging. It has revealed that some tissues age faster than others, which is vital to understanding the complex phenomenon of aging and developing effective interventions. Previous studies have demonstrated that humans exhibit heterogeneity in pace of epigenetic aging among brain structures that are consistent with differences in structural and microanatomical deterioration. Here, we add comparative data on epigenetic brain aging for chimpanzees, humans' closest relatives. Such comparisons can further our understanding of which aspects of human aging are evolutionarily conserved or specific to our species, especially given that humans are distinguished by a long lifespan, large brain, and, potentially, more severe neurodegeneration with age. Specifically, we investigated epigenetic aging of the dorsolateral prefrontal cortex and cerebellum, of humans and chimpanzees by generating genome-wide CpG methylation data and applying established epigenetic clock algorithms to produce estimates of biological age for these tissues. We found that both species exhibit relatively slow epigenetic aging in the brain relative to blood. Between brain structures, humans show a faster rate of epigenetic aging in the dorsolateral prefrontal cortex compared to the cerebellum, which is consistent with previous findings. Chimpanzees, in contrast, show comparable rates of epigenetic aging in the two brain structures. Greater epigenetic change in the human dorsolateral prefrontal cortex compared to the cerebellum may reflect both the protracted development of this structure in humans and its greater age-related vulnerability to neurodegenerative pathology.
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Affiliation(s)
- Elaine E Guevara
- Department of Anthropology, University of North Carolina Wilmington, Wilmington, NC 28403, USA.,Department of Anthropology and Center for the Advanced Study of Human Paleobiology, The George Washington University, Washington, DC 20052, USA.,Department of Evolutionary Anthropology, Duke University, Durham, NC, 27708, USA
| | - William D Hopkins
- Keeling Center for Comparative Medicine and Research, University of Texas MD Anderson Cancer Center, Bastrop, TX 78602, USA
| | - Patrick R Hof
- Nash Family Department of Neuroscience, Friedman Brain Institute, and Ronald M. Loeb Center for Alzheimer's Disease, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA.,New York Consortium in Evolutionary Primatology, New York, NY 10124, USA
| | - John J Ely
- Department of Anthropology and Center for the Advanced Study of Human Paleobiology, The George Washington University, Washington, DC 20052, USA.,MAEBIOS, Alamogordo, NM 88310, USA
| | - Brenda J Bradley
- Department of Anthropology and Center for the Advanced Study of Human Paleobiology, The George Washington University, Washington, DC 20052, USA
| | - Chet C Sherwood
- Department of Anthropology and Center for the Advanced Study of Human Paleobiology, The George Washington University, Washington, DC 20052, USA
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89
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Tzemah-Shahar R, Hochner H, Iktilat K, Agmon M. What can we learn from physical capacity about biological age? A systematic review. Ageing Res Rev 2022; 77:101609. [PMID: 35306185 DOI: 10.1016/j.arr.2022.101609] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2022] [Revised: 03/02/2022] [Accepted: 03/14/2022] [Indexed: 01/16/2023]
Abstract
OBJECTIVE To systematically investigate the relationship between objective measures of physical capacity (e.g., cardio-respiratory fitness or daily step count) and biological age, measured in different ways. DATA SOURCE PubMed; SCOPUS - Elsevier API; and Web of Science - ISI 1984-present, as well as contextual search engines used to identify additional relevant publications. STUDY SELECTION Cross-sectional and longitudinal studies that assessed the association between objectively measured physical capacity and biological aging in adult individuals (age>18). RESULTS Analysis of 28 studies demonstrated that physical capacity is positively associated with biological aging; the most dominant measures of physical capacity are muscular strength or gait speed. The majority of the studies estimated biological aging by a single methodology - either Leukocyte Telomere Length or DNA methylation levels. CONCLUSIONS This systematic review of the objective physical capacity measures used to estimate aging finds that the current literature is limited insofar as it overlooks the potential contribution of many feasible markers. We recommend measuring physical capacity in the context of aging using a wide range of modifiable behavioral markers, beyond simple muscle strength or simple gait speed. Forming a feasible and diversified method for estimating physical capacity through which it will also be possible to estimate biological aging in wide population studies is essential for the development of interventions that may alleviate the burden of age-related disease.
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Affiliation(s)
- Roy Tzemah-Shahar
- The Cheryl Spencer Institute for Nursing Research, Faculty of Health and Social Welfare, University of Haifa, Haifa, Israel
| | - Hagit Hochner
- Epidemiology unit, Hebrew University School of Public Health, Jerusalem, Israel
| | - Khalil Iktilat
- Department of Gerontology, Faculty of Health and Social Welfare, University of Haifa, Haifa, Israel
| | - Maayan Agmon
- The Cheryl Spencer Institute for Nursing Research, Faculty of Health and Social Welfare, University of Haifa, Haifa, Israel
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90
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Mehta D, Bruenig D, Pierce J, Sathyanarayanan A, Stringfellow R, Miller O, Mullens AB, Shakespeare-Finch J. Recalibrating the epigenetic clock after exposure to trauma: The role of risk and protective psychosocial factors. J Psychiatr Res 2022; 149:374-381. [PMID: 34823878 DOI: 10.1016/j.jpsychires.2021.11.026] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/07/2021] [Revised: 11/10/2021] [Accepted: 11/17/2021] [Indexed: 10/19/2022]
Abstract
BACKGROUND Epigenetic aging is associated with a plethora of negative health outcomes and increased mortality. Yet, the dynamicity of epigenetic age after exposure to trauma and the factors that influence epigenetic age are not fully understood. This research evaluated longitudinal changes in epigenetic age before and after exposure to work-related trauma among paramedicine students. We further investigated psychological and social risk (psychological distress, posttraumatic stress disorder/PTSD symptom severity, professional quality of life) and protective factors (social support and organisational membership) that drive epigenetic aging at both time points. METHODS The study comprised of 80 samples of University paramedicine students including 40 individuals at two time points - t0 (baseline) and t1 (post-trauma exposure). Epigenome-wide analysis was performed from t0 and t1 saliva using the Illumina EPIC arrays that cover >860k probes. Data analysis was performed using R via generalized regression models. The epigenetic age was calculated based on the Horvath algorithm, GrimAge and SkinBloodAge were calculated using the Horvath online calculator, and p-value for significance was corrected using the FDR method for multiple testing corrections. RESULTS The epigenetic age at t0 and t1 were highly correlated with chronological age and with each other (r = 0.84-0.94). Baseline epigenetic age and follow-up epigenetic age were significantly associated with risk factors of psychological distress and PTSD symptom severity. Among the protective factors, a sense of psychological organisational membership at the start of the paramedicine course as measured at baseline significantly reduced epigenetic age at baseline and post-trauma exposure. On the other hand, receiving social support acted as a protective factor only after exposure to trauma (follow-up), decreasing epigenetic aging at follow-up. GrimAge acceleration at follow-up was significantly associated with increased PTSD symptom severity at baseline and follow-up. Moreover, increased social support at baseline and follow-up was associated with reduced follow-up GrimAge acceleration. CONCLUSION These results demonstrate that epigenetic aging is dynamic and changes after exposure to trauma. Additionally, results demonstrate that different risk and protective factors influence epigenetic aging at different times. In conclusion, the research identified risk and protective factors associated with epigenetic aging pre- and post-trauma exposure, with implications for health and well-being among individuals exposed to trauma.
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Affiliation(s)
- Divya Mehta
- Queensland University of Technology (QUT), Centre for Genomics and Personalised Health, Faculty of Health, Kelvin Grove, Queensland, 4059, Australia; Queensland University of Technology (QUT), School of Biomedical Sciences, Faculty of Health, Kelvin Grove, Queensland, 4059, Australia.
| | - Dagmar Bruenig
- Queensland University of Technology (QUT), Centre for Genomics and Personalised Health, Faculty of Health, Kelvin Grove, Queensland, 4059, Australia; Queensland University of Technology (QUT), School of Psychology and Counselling, Faculty of Health, Kelvin Grove, Queensland, 4059, Australia
| | - John Pierce
- Queensland University of Technology (QUT), School of Psychology and Counselling, Faculty of Health, Kelvin Grove, Queensland, 4059, Australia
| | - Anita Sathyanarayanan
- Queensland University of Technology (QUT), Centre for Genomics and Personalised Health, Faculty of Health, Kelvin Grove, Queensland, 4059, Australia; Queensland University of Technology (QUT), School of Biomedical Sciences, Faculty of Health, Kelvin Grove, Queensland, 4059, Australia
| | - Rachel Stringfellow
- Queensland University of Technology (QUT), School of Psychology and Counselling, Faculty of Health, Kelvin Grove, Queensland, 4059, Australia
| | - Olivia Miller
- Queensland University of Technology (QUT), School of Psychology and Counselling, Faculty of Health, Kelvin Grove, Queensland, 4059, Australia
| | - Amy B Mullens
- School of Psychology and Counselling, Centre for Health Research, Institute for Resilient Regions, University of Southern Queensland (USQ), 11 Salisbury Rd, Ipswich, QLD, 4305, Australia
| | - Jane Shakespeare-Finch
- Queensland University of Technology (QUT), School of Psychology and Counselling, Faculty of Health, Kelvin Grove, Queensland, 4059, Australia
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91
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Perazza LR, Brown-Borg HM, Thompson LV. Physiological Systems in Promoting Frailty. Compr Physiol 2022; 12:3575-3620. [PMID: 35578945 DOI: 10.1002/cphy.c210034] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
Frailty is a complex syndrome affecting a growing sector of the global population as medical developments have advanced human mortality rates across the world. Our current understanding of frailty is derived from studies conducted in the laboratory as well as the clinic, which have generated largely phenotypic information. Far fewer studies have uncovered biological underpinnings driving the onset and progression of frailty, but the stage is set to advance the field with preclinical and clinical assessment tools, multiomics approaches together with physiological and biochemical methodologies. In this article, we provide comprehensive coverage of topics regarding frailty assessment, preclinical models, interventions, and challenges as well as clinical frameworks and prevalence. We also identify central biological mechanisms that may be at play including mitochondrial dysfunction, epigenetic alterations, and oxidative stress that in turn, affect metabolism, stress responses, and endocrine and neuromuscular systems. We review the role of metabolic syndrome, insulin resistance and visceral obesity, focusing on glucose homeostasis, adenosine monophosphate-activated protein kinase (AMPK), mammalian target of rapamycin (mTOR), and nicotinamide adenine dinucleotide (NAD+ ) as critical players influencing the age-related loss of health. We further focus on how immunometabolic dysfunction associates with oxidative stress in promoting sarcopenia, a key contributor to slowness, weakness, and fatigue. We explore the biological mechanisms involved in stem cell exhaustion that affect regeneration and may contribute to the frailty-associated decline in resilience and adaptation to stress. Together, an overview of the interplay of aging biology with genetic, lifestyle, and environmental factors that contribute to frailty, as well as potential therapeutic targets to lower risk and slow the progression of ongoing disease is covered. © 2022 American Physiological Society. Compr Physiol 12:1-46, 2022.
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Affiliation(s)
- Laís R Perazza
- Department of Physical Therapy and Athletic Training, Boston University, Boston, Massachusetts, USA
| | - Holly M Brown-Borg
- Department of Biomedical Sciences, University of North Dakota, Grand Forks, North Dakota, USA
| | - LaDora V Thompson
- Department of Physical Therapy and Athletic Training, Boston University, Boston, Massachusetts, USA
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92
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Horvath S, Lin DTS, Kobor MS, Zoller JA, Said JW, Morgello S, Singer E, Yong WH, Jamieson BD, Levine AJ. HIV, pathology and epigenetic age acceleration in different human tissues. GeroScience 2022; 44:1609-1620. [PMID: 35411474 PMCID: PMC9213580 DOI: 10.1007/s11357-022-00560-0] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2022] [Accepted: 03/30/2022] [Indexed: 11/29/2022] Open
Abstract
Epigenetic clocks based on patterns of DNA methylation have great importance in understanding aging and disease; however, there are basic questions to be resolved in their application. It remains unknown whether epigenetic age acceleration (EAA) within an individual shows strong correlation between different primary tissue sites, the extent to which tissue pathology and clinical illness correlate with EAA in the target organ, and if EAA variability across tissues differs according to sex. Considering the outsized role of age-related illness in Human Immunodeficiency Virus-1 (HIV), these questions were pursued in a sample enriched for tissue from HIV-infected individuals. We used a custom methylation array to generate DNA methylation data from 661 samples representing 11 human tissues (adipose, blood, bone marrow, heart, kidney, liver, lung, lymph node, muscle, spleen and pituitary gland) from 133 clinically characterized, deceased individuals, including 75 infected with HIV. We developed a multimorbidity index based on the clinical disease history. Epigenetic age was moderately correlated across tissues. Blood had the greatest number and degree of correlation, most notably with spleen and bone marrow. However, blood did not correlate with epigenetic age of liver. EAA in liver was weakly correlated with EAA in kidney, adipose, lung and bone marrow. Clinically, hypertension was associated with EAA in several tissues, consistent with the multiorgan impacts of this illness. HIV infection was associated with positive age acceleration in kidney and spleen. Male sex was associated with increased epigenetic acceleration in several tissues. Preliminary evidence indicates that amyotrophic lateral sclerosis is associated with positive EAA in muscle tissue. Finally, greater multimorbidity was associated with greater EAA across all tissues. Blood alone will often fail to detect EAA in other tissues. While hypertension is associated with increased EAA in several tissues, many pathologies are associated with organ-specific age acceleration.
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Affiliation(s)
- Steve Horvath
- Department of Human Genetics, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, 90095, USA. .,Department of Biostatistics, Fielding School of Public Health, University of California Los Angeles, Los Angeles, CA, 90095, USA.
| | - David T S Lin
- Centre for Molecular Medicine and Therapeutics, BC Childrens Hospital Research Institute, Vancouver, Canada
| | - Michael S Kobor
- Centre for Molecular Medicine and Therapeutics, BC Childrens Hospital Research Institute, Vancouver, Canada
| | - Joseph A Zoller
- Department of Biostatistics, Fielding School of Public Health, University of California Los Angeles, Los Angeles, CA, 90095, USA
| | - Jonathan W Said
- Department of Pathology and Jonsson Comprehensive Cancer Center, David Geffen School of Medicine, Los Angeles, USA
| | - Susan Morgello
- Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, USA.,Departments of Neuroscience and Pathology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Elyse Singer
- Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, USA
| | - William H Yong
- Department of Pathology and Jonsson Comprehensive Cancer Center, David Geffen School of Medicine, Los Angeles, USA
| | - Beth D Jamieson
- Department of Medicine, David Geffen School of Medicine, University of California, Los Angeles, USA
| | - Andrew J Levine
- Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, USA
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93
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Mozhui K, Lu AT, Li CZ, Haghani A, Sandoval-Sierra JV, Wu Y, Williams RW, Horvath S. Genetic loci and metabolic states associated with murine epigenetic aging. eLife 2022; 11:e75244. [PMID: 35389339 PMCID: PMC9049972 DOI: 10.7554/elife.75244] [Citation(s) in RCA: 20] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2021] [Accepted: 04/01/2022] [Indexed: 11/25/2022] Open
Abstract
Changes in DNA methylation (DNAm) are linked to aging. Here, we profile highly conserved CpGs in 339 predominantly female mice belonging to the BXD family for which we have deep longevity and genomic data. We use a 'pan-mammalian' microarray that provides a common platform for assaying the methylome across mammalian clades. We computed epigenetic clocks and tested associations with DNAm entropy, diet, weight, metabolic traits, and genetic variation. We describe the multifactorial variance of methylation at these CpGs and show that high-fat diet augments the age-related changes. Entropy increases with age. The progression to disorder, particularly at CpGs that gain methylation over time, was predictive of genotype-dependent life expectancy. The longer-lived BXD strains had comparatively lower entropy at a given age. We identified two genetic loci that modulate epigenetic age acceleration (EAA): one on chromosome (Chr) 11 that encompasses the Erbb2/Her2 oncogenic region, and the other on Chr19 that contains a cytochrome P450 cluster. Both loci harbor genes associated with EAA in humans, including STXBP4, NKX2-3, and CUTC. Transcriptome and proteome analyses revealed correlations with oxidation-reduction, metabolic, and immune response pathways. Our results highlight concordant loci for EAA in humans and mice, and demonstrate a tight coupling between the metabolic state and epigenetic aging.
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Affiliation(s)
- Khyobeni Mozhui
- Department of Preventive Medicine, University of Tennessee Health Science Center, College of MedicineMemphisUnited States
- Department of Genetics, Genomics and Informatics, University of Tennessee Health Science Center, College of MedicineMemphisUnited States
| | - Ake T Lu
- Department of Human Genetics, David Geffen School of Medicine, University of California Los AngelesLos AngelesUnited States
| | - Caesar Z Li
- Department of Human Genetics, David Geffen School of Medicine, University of California Los AngelesLos AngelesUnited States
| | - Amin Haghani
- Department of Biostatistics, Fielding School of Public Health, University of California Los AngelesLos AngelesUnited States
| | - Jose Vladimir Sandoval-Sierra
- Department of Preventive Medicine, University of Tennessee Health Science Center, College of MedicineMemphisUnited States
| | - Yibo Wu
- YCI Laboratory for Next-Generation Proteomics, RIKEN Center for Integrative Medical SciencesYokohamaJapan
- University of GenevaGenevaSwitzerland
| | - Robert W Williams
- Department of Genetics, Genomics and Informatics, University of Tennessee Health Science Center, College of MedicineMemphisUnited States
| | - Steve Horvath
- Department of Human Genetics, David Geffen School of Medicine, University of California Los AngelesLos AngelesUnited States
- Department of Biostatistics, Fielding School of Public Health, University of California Los AngelesLos AngelesUnited States
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94
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Ratiner K, Abdeen SK, Goldenberg K, Elinav E. Utilization of Host and Microbiome Features in Determination of Biological Aging. Microorganisms 2022; 10:microorganisms10030668. [PMID: 35336242 PMCID: PMC8950177 DOI: 10.3390/microorganisms10030668] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2022] [Revised: 03/08/2022] [Accepted: 03/18/2022] [Indexed: 12/13/2022] Open
Abstract
The term ‘old age’ generally refers to a period characterized by profound changes in human physiological functions and susceptibility to disease that accompanies the final years of a person’s life. Despite the conventional definition of old age as exceeding the age of 65 years old, quantifying aging as a function of life years does not necessarily reflect how the human body ages. In contrast, characterizing biological (or physiological) aging based on functional parameters may better reflect a person’s temporal physiological status and associated disease susceptibility state. As such, differentiating ‘chronological aging’ from ‘biological aging’ holds the key to identifying individuals featuring accelerated aging processes despite having a young chronological age and stratifying them to tailored surveillance, diagnosis, prevention, and treatment. Emerging evidence suggests that the gut microbiome changes along with physiological aging and may play a pivotal role in a variety of age-related diseases, in a manner that does not necessarily correlate with chronological age. Harnessing of individualized gut microbiome data and integration of host and microbiome parameters using artificial intelligence and machine learning pipelines may enable us to more accurately define aging clocks. Such holobiont-based estimates of a person’s physiological age may facilitate prediction of age-related physiological status and risk of development of age-associated diseases.
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Affiliation(s)
- Karina Ratiner
- Immunology Department, Weizmann Institute of Science, 234 Herzl Street, Rehovot 7610001, Israel; (K.R.); (S.K.A.); (K.G.)
| | - Suhaib K. Abdeen
- Immunology Department, Weizmann Institute of Science, 234 Herzl Street, Rehovot 7610001, Israel; (K.R.); (S.K.A.); (K.G.)
| | - Kim Goldenberg
- Immunology Department, Weizmann Institute of Science, 234 Herzl Street, Rehovot 7610001, Israel; (K.R.); (S.K.A.); (K.G.)
| | - Eran Elinav
- Immunology Department, Weizmann Institute of Science, 234 Herzl Street, Rehovot 7610001, Israel; (K.R.); (S.K.A.); (K.G.)
- Division of Cancer-Microbiome Research, Deutsches Krebsforschungszentrum (DKFZ), Neuenheimer Feld 280, 69120 Heidelberg, Germany
- Correspondence:
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95
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Pérez RF, Alba-Linares JJ, Tejedor JR, Fernández AF, Calero M, Román-Domínguez A, Borrás C, Viña J, Ávila J, Medina M, Fraga MF. Blood DNA methylation patterns in older adults with evolving dementia. J Gerontol A Biol Sci Med Sci 2022; 77:1743-1749. [PMID: 35299244 PMCID: PMC9434456 DOI: 10.1093/gerona/glac068] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2021] [Indexed: 11/14/2022] Open
Abstract
Dementia and cognitive disorders are major aging-associated pathologies. The prevalence and severity of these conditions are influenced by both genetic and environmental factors. Reflecting this, epigenetic alterations have been associated with each of these processes, especially at the level of DNA methylation, and such changes may help explain the observed interindividual variability in the development of the 2 pathologies. However, the importance of epigenetic alterations in explaining their etiology is unclear because little is known about the timing of when they appear. Here, using Illumina MethylationEPIC arrays, we have longitudinally analyzed the peripheral blood methylomes of cognitively healthy older adults (>70 year), some of whom went on to develop dementia while others stayed healthy. We have characterized 34 individuals at the prediagnosis stage and at a 4-year follow-up in the postdiagnosis stage (total n = 68). Our results show multiple DNA methylation alterations linked to dementia status, particularly at the level of differentially methylated regions. These loci are associated with several dementia-related genes, including PON1, AP2A2, MAGI2, POT1, ITGAX, PACSIN1, SLC2A8, and EIF4E. We also provide validation of the previously reported epigenetic alteration of HOXB6 and PM20D1. Importantly, we show that most of these regions are already altered in the prediagnosis stage of individuals who go on to develop dementia. In conclusion, our observations suggest that dementia-associated epigenetic patterns that have specific biological features are already present before diagnosis, and thus may be important in the design of epigenetic biomarkers for disease detection based on peripheral tissues.
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Affiliation(s)
- Raúl Fernández Pérez
- Cancer Epigenetics and Nanomedicine Laboratory. Nanomaterials and Nanotechnology Research Center (CINN-CSIC). Health Research Institute of Asturias (ISPA-FINBA). Institute of Oncology of Asturias (IUOPA) and Department of Organisms and Systems Biology (B.O.S.), University of Oviedo, Oviedo, Spain. Rare Diseases CIBER (CIBERER) of the Carlos III Health Institute (ISCIII)
| | - Juan José Alba-Linares
- Cancer Epigenetics and Nanomedicine Laboratory. Nanomaterials and Nanotechnology Research Center (CINN-CSIC). Health Research Institute of Asturias (ISPA-FINBA). Institute of Oncology of Asturias (IUOPA) and Department of Organisms and Systems Biology (B.O.S.), University of Oviedo, Oviedo, Spain. Rare Diseases CIBER (CIBERER) of the Carlos III Health Institute (ISCIII)
| | - Juan Ramón Tejedor
- Cancer Epigenetics and Nanomedicine Laboratory. Nanomaterials and Nanotechnology Research Center (CINN-CSIC). Health Research Institute of Asturias (ISPA-FINBA). Institute of Oncology of Asturias (IUOPA) and Department of Organisms and Systems Biology (B.O.S.), University of Oviedo, Oviedo, Spain. Rare Diseases CIBER (CIBERER) of the Carlos III Health Institute (ISCIII)
| | - Agustín Fernández Fernández
- Cancer Epigenetics and Nanomedicine Laboratory. Nanomaterials and Nanotechnology Research Center (CINN-CSIC). Health Research Institute of Asturias (ISPA-FINBA). Institute of Oncology of Asturias (IUOPA) and Department of Organisms and Systems Biology (B.O.S.), University of Oviedo, Oviedo, Spain. Rare Diseases CIBER (CIBERER) of the Carlos III Health Institute (ISCIII)
| | - Miguel Calero
- Network Center for Biomedical Research in Neurodegenerative Diseases (CIBERNED), Madrid, Spain.,Chronic Disease Programme (UFIEC), Instituto de Salud Carlos III, Madrid, Spain.,CIEN Foundation, Queen Sofia Foundation Alzheimer Center, Madrid, Spain
| | - Aurora Román-Domínguez
- Freshage Research Group, Department of Physiology, Faculty of Medicine, University of Valencia and CIBERFES-ISCIII, Fundación Investigación Hospital Clínico Universitario/INCLIVA, Valencia, Spain
| | - Consuelo Borrás
- Freshage Research Group, Department of Physiology, Faculty of Medicine, University of Valencia and CIBERFES-ISCIII, Fundación Investigación Hospital Clínico Universitario/INCLIVA, Valencia, Spain
| | - José Viña
- Freshage Research Group, Department of Physiology, Faculty of Medicine, University of Valencia and CIBERFES-ISCIII, Fundación Investigación Hospital Clínico Universitario/INCLIVA, Valencia, Spain
| | - Jesús Ávila
- Network Center for Biomedical Research in Neurodegenerative Diseases (CIBERNED), Madrid, Spain.,Centro de Biología Molecular Severo Ochoa (CBMSO) CSIC-UAM, Madrid, Spain
| | - Miguel Medina
- Network Center for Biomedical Research in Neurodegenerative Diseases (CIBERNED), Madrid, Spain.,CIEN Foundation, Queen Sofia Foundation Alzheimer Center, Madrid, Spain
| | - Mario Fernández Fraga
- Cancer Epigenetics and Nanomedicine Laboratory. Nanomaterials and Nanotechnology Research Center (CINN-CSIC). Health Research Institute of Asturias (ISPA-FINBA). Institute of Oncology of Asturias (IUOPA) and Department of Organisms and Systems Biology (B.O.S.), University of Oviedo, Oviedo, Spain. Rare Diseases CIBER (CIBERER) of the Carlos III Health Institute (ISCIII)
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96
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Zheng Y, Habes M, Gonzales M, Pomponio R, Nasrallah I, Khan S, Vaughan DE, Davatzikos C, Seshadri S, Launer L, Sorond F, Sedaghat S, Wainwright D, Baccarelli A, Sidney S, Bryan N, Greenland P, Lloyd-Jones D, Yaffe K, Hou L. Mid-life epigenetic age, neuroimaging brain age, and cognitive function: coronary artery risk development in young adults (CARDIA) study. Aging (Albany NY) 2022; 14:1691-1712. [PMID: 35220276 PMCID: PMC8908939 DOI: 10.18632/aging.203918] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2021] [Accepted: 02/08/2022] [Indexed: 11/25/2022]
Abstract
The proportion of aging populations affected by dementia is increasing. There is an urgent need to identify biological aging markers in mid-life before symptoms of age-related dementia present for early intervention to delay the cognitive decline and the onset of dementia. In this cohort study involving 1,676 healthy participants (mean age 40) with up to 15 years of follow up, we evaluated the associations between cognitive function and two classes of novel biological aging markers: blood-based epigenetic aging and neuroimaging-based brain aging. Both accelerated epigenetic aging and brain aging were prospectively associated with worse cognitive outcomes. Specifically, every year faster epigenetic or brain aging was on average associated with 0.19-0.28 higher (worse) Stroop score, 0.04-0.05 lower (worse) RAVLT score, and 0.23-0.45 lower (worse) DSST (all false-discovery-rate-adjusted p <0.05). While epigenetic aging is a more stable biomarker with strong long-term predictive performance for cognitive function, brain aging biomarker may change more dynamically in temporal association with cognitive decline. The combined model using epigenetic and brain aging markers achieved the highest accuracy (AUC: 0.68, p<0.001) in predicting global cognitive function status. Accelerated epigenetic age and brain age at midlife may aid timely identification of individuals at risk for accelerated cognitive decline and promote the development of interventions to preserve optimal functioning across the lifespan.
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Affiliation(s)
- Yinan Zheng
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL 60611, USA
| | - Mohamad Habes
- Biggs Institute Neuroimaging Core, Glenn Biggs Institute for Neurodegenerative Disorders, University of Texas Health Science Center at San Antonio, San Antonio, TX 78229, USA
- Department of Radiology, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Mitzi Gonzales
- Biggs Institute Neuroimaging Core, Glenn Biggs Institute for Neurodegenerative Disorders, University of Texas Health Science Center at San Antonio, San Antonio, TX 78229, USA
| | - Raymond Pomponio
- Department of Radiology, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Ilya Nasrallah
- Department of Radiology, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Sadiya Khan
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL 60611, USA
- Division of Cardiology, Department of Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL 60611, USA
| | - Douglas E. Vaughan
- Feinberg Cardiovascular Research Institute, Northwestern University Feinberg School of Medicine, Chicago, IL 60611, USA
| | - Christos Davatzikos
- Department of Radiology, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Sudha Seshadri
- Biggs Institute Neuroimaging Core, Glenn Biggs Institute for Neurodegenerative Disorders, University of Texas Health Science Center at San Antonio, San Antonio, TX 78229, USA
- Department of Neurology, Boston University School of Medicine, Boston, MA 02118, USA
| | - Lenore Launer
- Laboratory of Epidemiology and Population Science, Intramural Research Program, National Institute on Aging, National Institutes of Health, Bethesda, MD 20892, USA
| | - Farzaneh Sorond
- Department of Neurology, Northwestern University Feinberg School of Medicine, Chicago, IL 60611, USA
| | - Sanaz Sedaghat
- Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, MN 55455, USA
| | - Derek Wainwright
- Departments of Neurological Surgery, Medicine-Hematology and Oncology, Microbiology-Immunology, Northwestern University Feinberg School of Medicine, Chicago, IL 60611, USA
| | - Andrea Baccarelli
- Department of Environmental Health Sciences, Columbia University Mailman School of Public Health, New York, NY 10032, USA
| | - Stephen Sidney
- Kaiser Permanente Division of Research, Oakland, CA 94612, USA
| | - Nick Bryan
- Department of Diagnostic Medicine, Dell Medical School, University of Texas at Austin, Austin, TX 78712, USA
| | - Philip Greenland
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL 60611, USA
| | - Donald Lloyd-Jones
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL 60611, USA
| | - Kristine Yaffe
- Departments of Psychiatry and Behavioral Sciences, University of California, San Francisco, CA 94143, USA
- Department of Neurology University of California, San Francisco, CA 94143, USA
- Department of Epidemiology and Biostatistics, University of California San Francisco, CA 94143, USA
- San Francisco VA Medical Center, San Francisco, CA 94143, USA
| | - Lifang Hou
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL 60611, USA
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97
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Barrett JE, Herzog C, Kim YN, Bartlett TE, Jones A, Evans I, Cibula D, Zikan M, Bjørge L, Harbeck N, Colombo N, Howell SJ, Rådestad AF, Gemzell-Danielsson K, Widschwendter M. Susceptibility to hormone-mediated cancer is reflected by different tick rates of the epithelial and general epigenetic clock. Genome Biol 2022; 23:52. [PMID: 35189945 PMCID: PMC8862470 DOI: 10.1186/s13059-022-02603-3] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2021] [Accepted: 01/05/2022] [Indexed: 12/11/2022] Open
Abstract
Background A variety of epigenetic clocks utilizing DNA methylation changes have been developed; these clocks are either tissue-independent or designed to predict chronological age based on blood or saliva samples. Whether discordant tick rates between tissue-specific and general epigenetic clocks play a role in health and disease has not yet been explored. Results Here we analyze 1941 cervical cytology samples, which contain a mixture of hormone-sensitive cervical epithelial cells and immune cells, and develop the WID general clock (Women’s IDentification of risk), an epigenetic clock that is shared by epithelial and immune cells and optimized for cervical samples. We then develop the WID epithelial clock and WID immune clock, which define epithelial- and immune-specific clocks, respectively. We find that the WID-relative-epithelial-age (WID-REA), defined as the difference between the epithelial and general clocks, is significantly reduced in cervical samples from pre-menopausal women with breast cancer (OR 2.7, 95% CI 1.28-5.72). We find the same effect in normal breast tissue samples from pre-menopausal women at high risk of breast cancer and show that potential risk reducing anti-progesterone drugs can reverse this. In post-menopausal women, this directionality is reversed. Hormone replacement therapy consistently leads to a significantly lower WID-REA in cancer-free women, but not in post-menopausal women with breast or ovarian cancer. Conclusions Our findings imply that there are multiple epigenetic clocks, many of which are tissue-specific, and that the differential tick rate between these clocks may be an informative surrogate measure of disease risk. Supplementary Information The online version contains supplementary material available at 10.1186/s13059-022-02603-3.
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Affiliation(s)
- James E Barrett
- European Translational Oncology Prevention and Screening (EUTOPS) Institute, Milser Str. 10, 6060, Hall in Tirol, Austria.,Research Institute for Biomedical Aging Research, Universität Innsbruck, 6020, Innsbruck, Austria
| | - Chiara Herzog
- European Translational Oncology Prevention and Screening (EUTOPS) Institute, Milser Str. 10, 6060, Hall in Tirol, Austria.,Research Institute for Biomedical Aging Research, Universität Innsbruck, 6020, Innsbruck, Austria
| | - Yoo-Na Kim
- European Translational Oncology Prevention and Screening (EUTOPS) Institute, Milser Str. 10, 6060, Hall in Tirol, Austria.,Research Institute for Biomedical Aging Research, Universität Innsbruck, 6020, Innsbruck, Austria
| | - Thomas E Bartlett
- Department of Statistical Science, University College London, WC1E 7HB, London, UK
| | - Allison Jones
- Department of Women's Cancer, UCL EGA Institute for Women's Health, University College London, Medical School Building, Room 340, 74 Huntley Street, WC1E 6AU, London, UK
| | - Iona Evans
- Department of Women's Cancer, UCL EGA Institute for Women's Health, University College London, Medical School Building, Room 340, 74 Huntley Street, WC1E 6AU, London, UK
| | - David Cibula
- Gynaecologic Oncology Center, Department of Obstetrics and Gynecology, First Faculty of Medicine, Charles University in Prague, General University Hospital in Prague, Prague, Czech Republic
| | - Michal Zikan
- Department of Gynecology and Obstetrics, Charles University in Prague, First Faculty of Medicine and University Hospital Bulovka, Prague, Czech Republic
| | - Line Bjørge
- Department of Obstetrics and Gynaecology, Haukeland University Hospital, Bergen, Norway.,Centre for Cancer Biomarkers CCBIO, Department of Clinical Science, University of Bergen, Bergen, Norway
| | - Nadia Harbeck
- Breast Center, Department of Obstetrics and Gynecology, University of Munich (LMU), Munich, Germany
| | - Nicoletta Colombo
- Istituto Europeo di Oncologia IRCCS, Milan, Italy.,University of Milano-Bicocca, Milan, Italy
| | - Sacha J Howell
- Breast Biology Group, Manchester Breast Centre, Division of Cancer Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK
| | - Angelique Flöter Rådestad
- Department of Women's and Children's Health, Karolinska Institutet and Karolinska University Hospital, Stockholm, Sweden
| | - Kristina Gemzell-Danielsson
- Department of Women's and Children's Health, Karolinska Institutet and Karolinska University Hospital, Stockholm, Sweden
| | - Martin Widschwendter
- European Translational Oncology Prevention and Screening (EUTOPS) Institute, Milser Str. 10, 6060, Hall in Tirol, Austria. .,Research Institute for Biomedical Aging Research, Universität Innsbruck, 6020, Innsbruck, Austria. .,Department of Women's Cancer, UCL EGA Institute for Women's Health, University College London, Medical School Building, Room 340, 74 Huntley Street, WC1E 6AU, London, UK. .,Department of Women's and Children's Health, Karolinska Institutet and Karolinska University Hospital, Stockholm, Sweden.
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98
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Xu Y, Lindh CH, Fletcher T, Jakobsson K, Engström K. Perfluoroalkyl substances influence DNA methylation in school-age children highly exposed through drinking water contaminated from firefighting foam: a cohort study in Ronneby, Sweden. ENVIRONMENTAL EPIGENETICS 2022; 8:dvac004. [PMID: 35308102 PMCID: PMC8931254 DOI: 10.1093/eep/dvac004] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/03/2021] [Accepted: 02/04/2022] [Indexed: 05/31/2023]
Abstract
Perfluoroalkyl substances (PFASs) are widespread synthetic substances with various adverse health effects. A potential mechanism of toxicity for PFASs is via epigenetic changes, such as DNA methylation. Previous studies have evaluated associations between PFAS exposure and DNA methylation among newborns and adults. However, no study has evaluated how PFASs influence DNA methylation among children of school age. In this exploratory study with school-age children exposed to PFASs through drinking water highly contaminated from firefighting foams, we aimed to investigate whether exposure to PFASs was associated with alteration in DNA methylation and epigenetic age acceleration. Sixty-three children aged 7-11 years from the Ronneby Biomarker Cohort (Sweden) were included. The children were either controls with only background exposure (n = 32; perfluorooctane sulfonic acid: median 2.8 and range 1-5 ng/ml) or those exposed to very high levels of PFASs (n = 31; perfluorooctane sulfonic acid: median 295 and range 190-464 ng/ml). These two groups were matched on sex, age, and body mass index. Genome-wide methylation of whole-blood DNA was analyzed using the Infinium MethylationEPIC BeadChip kit. Epigenetic age acceleration was derived from the DNA methylation data. Twelve differentially methylated positions and seven differentially methylated regions were found when comparing the high-exposure group to the control group. There were no differences in epigenetic age acceleration between these two groups (P = 0.66). We found that PFAS exposure was associated with DNA methylation at specific genomic positions and regions in children at school age, which may indicate a possible mechanism for linking PFAS exposure to health effects.
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Affiliation(s)
- Yiyi Xu
- School of Public Health and Community Medicine, Institute of Medicine, University of Gothenburg, Medicinaregatan 18A, Gothenburg 413 90, Sweden
| | - Christian H Lindh
- Department of Laboratory Medicine, Division of Occupational and Environmental Medicine, Lund University, Scheelevägen 2, Lund 223 63, Sweden
| | - Tony Fletcher
- Department of Social and Environmental Health Research, London School of Hygiene & Tropical Medicine, Keppel St, London WC1E 7HT, UK
| | - Kristina Jakobsson
- School of Public Health and Community Medicine, Institute of Medicine, University of Gothenburg, Medicinaregatan 18A, Gothenburg 413 90, Sweden
- Occupational and Environmental Medicine, Sahlgrenska University Hospital, Medicinaregatan 16 A, Gothenburg 413 90, Sweden
| | - Karin Engström
- **Correspondence address. Department of Laboratory Medicine, EPI@LUND, Division of Occupational and Environmental Medicine, Lund University, Biskopsgatan 9, Lund 223 62, Sweden. Tel: +46 46 222 16 38; E-mail:
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99
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Wang Z, Hui Q, Goldberg J, Smith N, Kaseer B, Murrah N, Levantsevych OM, Shallenberger L, Diggers E, Bremner JD, Vaccarino V, Sun YV. Association Between Posttraumatic Stress Disorder and Epigenetic Age Acceleration in a Sample of Twins. Psychosom Med 2022; 84:151-158. [PMID: 34629427 PMCID: PMC8831461 DOI: 10.1097/psy.0000000000001028] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/03/2023]
Abstract
OBJECTIVE Posttraumatic stress disorder (PTSD) has been related to accelerated biological aging processes, but objective evidence for this association is limited. DNA methylation (DNAm) age acceleration is a novel measure of biological aging that may help clarify if PTSD is related to biological aging processes. We aim to examine whether PTSD is associated with biological aging using a comprehensive set of DNAm age acceleration markers and to what extent the unshared environment contributes to the association. METHODS Using a cross-sectional co-twin control study design, we investigated the association of the clinical diagnosis and symptom severity of PTSD with six measurements of DNAm age acceleration based on epigenome-wide data derived from peripheral blood lymphocytes of 296 male twins from the Vietnam Era Twin Registry. RESULTS Twins with current PTSD had significantly advanced DNAm age acceleration compared with twins without PTSD for five of six measures of DNAm age acceleration. Across almost all measures of DNAm age acceleration, twins with current PTSD were "epigenetically older" than their twin brothers without PTSD: estimated differences ranged between 1.6 (95% confidence interval = 0.0-3.1) and 2.7 (95% confidence interval = 0.5-4.8) biological age year-equivalents. A higher Clinician-Administered PTSD Scale score was also associated with a higher within-pair DNAm age acceleration. Results remained consistent after adjustment for behavioral and cardiovascular risk factors. CONCLUSIONS PTSD is associated with epigenetic age acceleration, primarily through unshared environmental mechanisms as opposed to genetic or familial factors. These results suggest that PTSD is related to systemic processes relevant to biological aging.
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Affiliation(s)
- Zeyuan Wang
- Department of Epidemiology, Emory University Rollins School of Public Health, 1518 Clifton Road NE, Atlanta, GA
| | - Qin Hui
- Department of Epidemiology, Emory University Rollins School of Public Health, 1518 Clifton Road NE, Atlanta, GA
| | - Jack Goldberg
- Vietnam Era Twin Registry, Seattle Epidemiologic Research and Information Center, US Department of Veterans Affairs, Seattle, WA
| | - Nicholas Smith
- Vietnam Era Twin Registry, Seattle Epidemiologic Research and Information Center, US Department of Veterans Affairs, Seattle, WA
| | - Belal Kaseer
- Department of Epidemiology, Emory University Rollins School of Public Health, 1518 Clifton Road NE, Atlanta, GA
| | - Nancy Murrah
- Department of Epidemiology, Emory University Rollins School of Public Health, 1518 Clifton Road NE, Atlanta, GA
| | - Oleksiy M. Levantsevych
- Department of Epidemiology, Emory University Rollins School of Public Health, 1518 Clifton Road NE, Atlanta, GA
| | - Lucy Shallenberger
- Department of Epidemiology, Emory University Rollins School of Public Health, 1518 Clifton Road NE, Atlanta, GA
| | - Emily Diggers
- Department of Epidemiology, Emory University Rollins School of Public Health, 1518 Clifton Road NE, Atlanta, GA
| | - J. Douglas Bremner
- Departments of Psychiatry and Behavioral Sciences and Radiology and Imaging Sciences, Emory University School of Medicine, Atlanta, GA
- Atlanta VA Health Care System, 1670 Clairmont Road, Decatur, GA 30033, USA
| | - Viola Vaccarino
- Department of Epidemiology, Emory University Rollins School of Public Health, 1518 Clifton Road NE, Atlanta, GA
| | - Yan V. Sun
- Department of Epidemiology, Emory University Rollins School of Public Health, 1518 Clifton Road NE, Atlanta, GA
- Atlanta VA Health Care System, 1670 Clairmont Road, Decatur, GA 30033, USA
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100
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Zhao X, Golic FT, Harrison BR, Manoj M, Hoffman EV, Simon N, Johnson R, MacCoss MJ, McIntyre LM, Promislow DEL. The metabolome as a biomarker of aging in Drosophila melanogaster. Aging Cell 2022; 21:e13548. [PMID: 35019203 PMCID: PMC8844127 DOI: 10.1111/acel.13548] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2021] [Accepted: 11/12/2021] [Indexed: 12/15/2022] Open
Abstract
Many biomarkers have been shown to be associated not only with chronological age but also with functional measures of biological age. In human populations, it is difficult to show whether variation in biological age is truly predictive of life expectancy, as such research would require longitudinal studies over many years, or even decades. We followed adult cohorts of 20 Drosophila Genetic Reference Panel (DGRP) strains chosen to represent the breadth of lifespan variation, obtain estimates of lifespan, baseline mortality, and rate of aging, and associate these parameters with age‐specific functional traits including fecundity and climbing activity and with age‐specific targeted metabolomic profiles. We show that activity levels and metabolome‐wide profiles are strongly associated with age, that numerous individual metabolites show a strong association with lifespan, and that the metabolome provides a biological clock that predicts not only sample age but also future mortality rates and lifespan. This study with 20 genotypes and 87 metabolites, while relatively small in scope, establishes strong proof of principle for the fly as a powerful experimental model to test hypotheses about biomarkers and aging and provides further evidence for the potential value of metabolomic profiles as biomarkers of aging.
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Affiliation(s)
- Xiaqing Zhao
- Department of Lab Medicine and Pathology University of Washington School of Medicine Seattle US
| | - Forrest T. Golic
- Department of Lab Medicine and Pathology University of Washington School of Medicine Seattle US
| | - Benjamin R. Harrison
- Department of Lab Medicine and Pathology University of Washington School of Medicine Seattle US
| | - Meghna Manoj
- Department of Lab Medicine and Pathology University of Washington School of Medicine Seattle US
| | - Elise V. Hoffman
- Department of Lab Medicine and Pathology University of Washington School of Medicine Seattle US
| | - Neta Simon
- Department of Lab Medicine and Pathology University of Washington School of Medicine Seattle US
| | - Richard Johnson
- Department of Genome Sciences University of Washington School of Medicine Seattle US
| | - Michael J. MacCoss
- Department of Genome Sciences University of Washington School of Medicine Seattle US
| | - Lauren M. McIntyre
- Genetics Institute University of Florida Gainesville USA
- Department of Molecular Genetics and Microbiology University of Florida Gainesville USA
| | - Daniel E. L. Promislow
- Department of Lab Medicine and Pathology University of Washington School of Medicine Seattle US
- Department of Biology University of Washington Seattle US
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