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Daredia S, Bozack AK, Riddell CA, Gunier R, Harley KG, Bradman A, Eskenazi B, Holland N, Deardorff J, Cardenas A. Prenatal Maternal Occupation and Child Epigenetic Age Acceleration in an Agricultural Region: NIMHD Social Epigenomics Program. JAMA Netw Open 2024; 7:e2421824. [PMID: 39073821 PMCID: PMC11287394 DOI: 10.1001/jamanetworkopen.2024.21824] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/13/2023] [Accepted: 03/05/2024] [Indexed: 07/30/2024] Open
Abstract
Importance Research on fetal epigenetic programming suggests that the intrauterine environment can have long-term effects on offspring disease susceptibility. Objective To examine the association between prenatal maternal occupation and child epigenetic age acceleration (EAA) among a farmworker community. Design, Setting, and Participants This cohort study included participants in the Center for the Health Assessment of Mothers and Children of Salinas, a prospective, Latino, prebirth cohort. Pregnant women were recruited from October 1, 1999, to October 1, 2000, from 6 community clinics in California's Salinas Valley agricultural region. Participants were 18 years or older, English or Spanish speaking, Medicaid eligible, and at 20 weeks' gestation or earlier at enrollment. Mother-child pairs who had blood DNA methylation measured at the ages of 7, 9, and 14 years were included. Data were analyzed from July 2021 to November 2023. Exposures Prenatal maternal occupation was ascertained through study interviews conducted during prenatal visits and shortly after delivery. Main Outcomes and Measures Child EAA at 7, 9, and 14 years of age was estimated using DNA methylation-based epigenetic age biomarkers. Three EAA measures were calculated: the Horvath EAA, skin and blood EAA, and intrinsic EAA. Linear mixed-effects models were used to estimate longitudinal associations of prenatal maternal occupation and child EAA, adjusting for confounders and prenatal organophosphate pesticide exposure. Results Analyses included 290 mother-child pairs (mean [SD] maternal age at delivery, 26.5 [5.2] years; 152 [52.4%] female infants); 254 mothers (87.6%) were born in Mexico, 33 (11.4%) in the US, and 3 (1.0%) in other countries; and 179 families (61.7%) were below the federal poverty line during pregnancy. Mothers reported engaging in several types of work during pregnancy, including agricultural fieldwork (90 [31.0%]), other agricultural work (40 [13.8%]), nonagricultural work (53 [18.3%]), or no work (107 [36.9%]). Children whose mothers worked in agricultural fields during pregnancy had a mean of 0.66 (95% CI, 0.17-1.15) years of greater Horvath EAA, 0.62 (95% CI, 0.31-0.94) years of greater skin and blood EAA, and 0.45 (95% CI, 0.07-0.83) years of greater intrinsic EAA compared with children whose mothers did not work during pregnancy. Conclusions and Relevance In this cohort study, prenatal maternal agricultural fieldwork was associated with accelerated childhood epigenetic aging independent of organophosphate pesticide exposure. Future research on which factors related to agricultural fieldwork accelerate aging in the next generation can inform targeted prevention programs and policies that protect children's health.
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Affiliation(s)
- Saher Daredia
- Division of Epidemiology, School of Public Health, University of California, Berkeley
| | - Anne K. Bozack
- Department of Epidemiology and Population Health, School of Medicine, Stanford University, Stanford, California
| | - Corinne A. Riddell
- Division of Epidemiology, School of Public Health, University of California, Berkeley
- Division of Biostatistics, School of Public Health, University of California, Berkeley
| | - Robert Gunier
- Center for Environmental Research and Community Health, School of Public Health, University of California, Berkeley
| | - Kim G. Harley
- Division of Epidemiology, School of Public Health, University of California, Berkeley
- Center for Environmental Research and Community Health, School of Public Health, University of California, Berkeley
- Division of Community Health Sciences, School of Public Health, University of California, Berkeley
| | - Asa Bradman
- Center for Environmental Research and Community Health, School of Public Health, University of California, Berkeley
- Department of Public Health, University of California, Merced
| | - Brenda Eskenazi
- Division of Epidemiology, School of Public Health, University of California, Berkeley
- Center for Environmental Research and Community Health, School of Public Health, University of California, Berkeley
- Division of Environmental Health Sciences, School of Public Health, University of California, Berkeley
| | - Nina Holland
- Center for Environmental Research and Community Health, School of Public Health, University of California, Berkeley
- Division of Environmental Health Sciences, School of Public Health, University of California, Berkeley
| | - Julianna Deardorff
- Center for Environmental Research and Community Health, School of Public Health, University of California, Berkeley
- Division of Community Health Sciences, School of Public Health, University of California, Berkeley
| | - Andres Cardenas
- Department of Epidemiology and Population Health, School of Medicine, Stanford University, Stanford, California
- Department of Pediatrics, School of Medicine, Stanford University, Stanford, California
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Humaira Amanullah F, Alam T, El Hajj N, Bejaoui Y. The impact of COVID-19 on "biological aging". Front Immunol 2024; 15:1399676. [PMID: 38919619 PMCID: PMC11197383 DOI: 10.3389/fimmu.2024.1399676] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2024] [Accepted: 05/24/2024] [Indexed: 06/27/2024] Open
Abstract
The global impact of the SARS-CoV-2 pandemic has been unprecedented, posing a significant public health challenge. Chronological age has been identified as a key determinant for severe outcomes associated with SARS-CoV-2 infection. Epigenetic age acceleration has previously been observed in various diseases including human immunodeficiency virus (HIV), Cytomegalovirus (CMV), cardiovascular diseases, and cancer. However, a comprehensive review of this topic is still missing in the field. In this review, we explore and summarize the research work focusing on biological aging markers, i.e., epigenetic age and telomere attrition in COVID-19 patients. From the reviewed articles, we identified a consistent pattern of epigenetic age dysregulation and shortened telomere length, revealing the impact of COVID-19 on epigenetic aging and telomere attrition.
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Affiliation(s)
| | - Tanvir Alam
- College of Science and Engineering, Hamad Bin Khalifa University, Qatar Foundation, Doha, Qatar
| | - Nady El Hajj
- College of Health and Life Sciences, Hamad Bin Khalifa University, Qatar Foundation, Doha, Qatar
- College of Science and Engineering, Hamad Bin Khalifa University, Qatar Foundation, Doha, Qatar
| | - Yosra Bejaoui
- College of Health and Life Sciences, Hamad Bin Khalifa University, Qatar Foundation, Doha, Qatar
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Salontaji K, Haftorn KL, Sanders F, Page CM, Walton E, Felix JF, Bekkhus M, Bohlin J, Tiemeier H, Cecil CAM. Gestational epigenetic age and ADHD symptoms in childhood: a prospective, multi-cohort study. Mol Psychiatry 2024:10.1038/s41380-024-02544-2. [PMID: 38561466 DOI: 10.1038/s41380-024-02544-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 04/04/2024]
Abstract
Epigenetic age acceleration (EAA), defined as the difference between chronological age and epigenetically predicted age, was calculated from multiple gestational epigenetic clocks (Bohlin, EPIC overlap, and Knight) using DNA methylation levels from cord blood in three large population-based birth cohorts: the Generation R Study (The Netherlands), the Avon Longitudinal Study of Parents and Children (United Kingdom), and the Norwegian Mother, Father and Child Cohort Study (Norway). We hypothesized that a lower EAA associates prospectively with increased ADHD symptoms. We tested our hypotheses in these three cohorts and meta-analyzed the results (n = 3383). We replicated previous research on the association between gestational age (GA) and ADHD. Both clinically measured gestational age as well as epigenetic age measures at birth were negatively associated with ADHD symptoms at ages 5-7 years (clinical GA: β = -0.04, p < 0.001, Bohlin: β = -0.05, p = 0.01; EPIC overlap: β = -0.05, p = 0.01; Knight: β = -0.01, p = 0.26). Raw EAA (difference between clinical and epigenetically estimated gestational age) was positively associated with ADHD in our main model, whereas residual EAA (raw EAA corrected for clinical gestational age) was not associated with ADHD symptoms across cohorts. Overall, findings support a link between lower gestational age (either measured clinically or using epigenetic-derived estimates) and ADHD symptoms. Epigenetic age acceleration does not, however, add unique information about ADHD risk independent of clinically estimated gestational age at birth.
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Affiliation(s)
- Kristina Salontaji
- Department of Child and Adolescent Psychiatry/Psychology, Erasmus Medical Centre, University Medical Center Rotterdam, Rotterdam, The Netherlands
- The Generation R Study Group, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Kristine L Haftorn
- Centre for Fertility and Health, Norwegian Institute of Public Health, Oslo, Norway
| | - Faye Sanders
- Department of Psychology, University of Bath, Bath, United Kingdom
| | - Christian M Page
- Centre for Fertility and Health, Norwegian Institute of Public Health, Oslo, Norway
- Department of Physical Health and Ageing, Division of Mental and Physical Health, Norwegian Institute of Public Health, Oslo, Norway
| | - Esther Walton
- Department of Psychology, University of Bath, Bath, United Kingdom
| | - Janine F Felix
- The Generation R Study Group, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
- Department of Pediatrics, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Mona Bekkhus
- Promenta research centre, Department of Psychology, University of Oslo, Oslo, Norway
| | - Jon Bohlin
- Centre for Fertility and Health, Norwegian Institute of Public Health, Oslo, Norway
- Department for methods development and analysis, section for modeling and bioinformatics, Division for infectious diseases, Norwegian Institute of Public Health, Oslo, Norway
| | - Henning Tiemeier
- Department of Child and Adolescent Psychiatry/Psychology, Erasmus Medical Centre, University Medical Center Rotterdam, Rotterdam, The Netherlands
- Department of Social and Behavioral Sciences, Harvard T.H. Chan School of Medicine, Boston, MA, USA
| | - Charlotte A M Cecil
- Department of Child and Adolescent Psychiatry/Psychology, Erasmus Medical Centre, University Medical Center Rotterdam, Rotterdam, The Netherlands.
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands.
- Molecular Epidemiology, Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, The Netherlands.
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Bozack AK, Rifas-Shiman SL, Baccarelli AA, Wright RO, Gold DR, Oken E, Hivert MF, Cardenas A. Associations of prenatal one-carbon metabolism nutrients and metals with epigenetic aging biomarkers at birth and in childhood in a US cohort. Aging (Albany NY) 2024; 16:3107-3136. [PMID: 38412256 PMCID: PMC10929819 DOI: 10.18632/aging.205602] [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: 10/31/2023] [Accepted: 01/29/2024] [Indexed: 02/29/2024]
Abstract
Epigenetic gestational age acceleration (EGAA) at birth and epigenetic age acceleration (EAA) in childhood may be biomarkers of the intrauterine environment. We investigated the extent to which first-trimester folate, B12, 5 essential, and 7 non-essential metals in maternal circulation are associated with EGAA and EAA in early life. Bohlin EGAA and Horvath pan-tissue and skin and blood EAA were calculated using DNA methylation measured in cord blood (N=351) and mid-childhood blood (N=326; median age = 7.7 years) in the Project Viva pre-birth cohort. A one standard deviation increase in individual essential metals (copper, manganese, and zinc) was associated with 0.94-1.2 weeks lower Horvath EAA at birth, and patterns of exposures identified by exploratory factor analysis suggested that a common source of essential metals was associated with Horvath EAA. We also observed evidence nonlinear associations of zinc with Bohlin EGAA, magnesium and lead with Horvath EAA, and cesium with skin and blood EAA at birth. Overall, associations at birth did not persist in mid-childhood; however, arsenic was associated with greater EAA at birth and in childhood. Prenatal metals, including essential metals and arsenic, are associated with epigenetic aging in early life, which might be associated with future health.
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Affiliation(s)
- Anne K. Bozack
- Department of Epidemiology and Population Health, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Sheryl L. Rifas-Shiman
- Division of Chronic Disease Research Across the Lifecourse, Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, MA 02215, USA
| | - Andrea A. Baccarelli
- Department of Environmental Health Sciences, Mailman School of Public Health, Columbia University, New York City, NY 10032, USA
| | - Robert O. Wright
- Department of Environmental Medicine and Institute for Exposomic Research, Icahn School of Medicine at Mount Sinai, New York City, NY 10029, USA
| | - Diane R. Gold
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Harvard University, Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115, USA
| | - Emily Oken
- Division of Chronic Disease Research Across the Lifecourse, Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, MA 02215, USA
| | - Marie-France Hivert
- Division of Chronic Disease Research Across the Lifecourse, Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, MA 02215, USA
| | - Andres Cardenas
- Department of Epidemiology and Population Health and Department of Pediatrics, Stanford University School of Medicine, Stanford, CA 94305, USA
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Polinski KJ, Robinson SL, Putnick DL, Guan W, Gleason JL, Mumford SL, Sundaram R, Mendola P, London S, Yeung EH. Epigenetic gestational age and the relationship with developmental milestones in early childhood. Hum Mol Genet 2023; 32:1565-1574. [PMID: 36617164 PMCID: PMC10117157 DOI: 10.1093/hmg/ddac302] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2022] [Revised: 12/09/2022] [Accepted: 12/12/2022] [Indexed: 01/09/2023] Open
Abstract
Shorter gestational age (GA) is a risk factor of developmental delay. GA is usually estimated clinically from last menstrual period and ultrasound. DNA methylation (DNAm) estimates GA using sets of cytosine-guanine-sites coupled with a clock algorithm. Therefore, DNAm-estimated GA may better reflect biological maturation. A DNAm GA greater than clinical GA, known as gestational age acceleration (GAA), may indicate epigenetic maturity and holds potential as an early biomarker for developmental delay risk. We used data from the Upstate KIDS Study to examine associations of DNAm GA and developmental delay within the first 3 years based on the Ages & Stages Questionnaire® (n = 1010). We estimated DNAm GA using two clocks specific to the Illumina Methylation EPIC 850K, the Haftorn clock and one developed from the Effects of Aspirin in Gestation and Reproduction study, in which women were followed to detect pregnancy at the earliest time possible. Among singletons, each week increase in DNAm GA was protective for overall delay (odds ratio:0.74; 95% confidence interval:0.61-0.90) and delay in all domains except for problem-solving skills. Among twins, we observed similar point estimates but lower precision. Results were similar for clinical GA. GAA was largely not associated with developmental delays. In summary, either DNAm GA or clinical GA at birth, but not epigenetic maturity (i.e. GAA), was associated with decreased odds of developmental delay in early childhood. Our study does not support using DNAm GA or GAA as separate risk factors for future risk of developmental delay within the first 3 years of age.
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Affiliation(s)
- Kristen J Polinski
- Epidemiology Branch, Division of Population Health Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, Bethesda, MD 20817, USA
| | - Sonia L Robinson
- Epidemiology Branch, Division of Population Health Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, Bethesda, MD 20817, USA
| | - Diane L Putnick
- Epidemiology Branch, Division of Population Health Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, Bethesda, MD 20817, USA
| | - Weihua Guan
- Division of Biostatistics, School of Public Health, University of Minnesota, Minneapolis, MN 55455, USA
| | - Jessica L Gleason
- Epidemiology Branch, Division of Population Health Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, Bethesda, MD 20817, USA
| | - Sunni L Mumford
- Epidemiology Branch, Division of Population Health Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, Bethesda, MD 20817, USA
- Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Rajeshwari Sundaram
- Epidemiology Branch, Division of Population Health Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, Bethesda, MD 20817, USA
| | - Pauline Mendola
- Department of Epidemiology and Environmental Health, School of Public Health and Health Professions, University at Buffalo, Buffalo, NY 14214, USA
| | - Stephanie London
- Epidemiology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Department of Health and Human Services, Research Triangle Park, NC 27709, USA
| | - Edwina H Yeung
- Epidemiology Branch, Division of Population Health Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, Bethesda, MD 20817, USA
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Bozack AK, Rifas-Shiman SL, Gold DR, Laubach ZM, Perng W, Hivert MF, Cardenas A. DNA methylation age at birth and childhood: performance of epigenetic clocks and characteristics associated with epigenetic age acceleration in the Project Viva cohort. Clin Epigenetics 2023; 15:62. [PMID: 37046280 PMCID: PMC10099681 DOI: 10.1186/s13148-023-01480-2] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2022] [Accepted: 04/05/2023] [Indexed: 04/14/2023] Open
Abstract
BACKGROUND Epigenetic age acceleration (EAA) and epigenetic gestational age acceleration (EGAA) are biomarkers of physiological development and may be affected by the perinatal environment. The aim of this study was to evaluate performance of epigenetic clocks and to identify biological and sociodemographic correlates of EGAA and EAA at birth and in childhood. In the Project Viva pre-birth cohort, DNA methylation was measured in nucleated cells in cord blood (leukocytes and nucleated red blood cells, N = 485) and leukocytes in early (N = 120, median age = 3.2 years) and mid-childhood (N = 460, median age = 7.7 years). We calculated epigenetic gestational age (EGA; Bohlin and Knight clocks) and epigenetic age (EA; Horvath and skin & blood clocks), and respective measures of EGAA and EAA. We evaluated the performance of clocks relative to chronological age using correlations and median absolute error. We tested for associations of maternal-child characteristics with EGAA and EAA using mutually adjusted linear models controlling for estimated cell type proportions. We also tested associations of Horvath EA at birth with childhood EAA. RESULTS Bohlin EGA was strongly correlated with chronological gestational age (Bohlin EGA r = 0.82, p < 0.001). Horvath and skin & blood EA were weakly correlated with gestational age, but moderately correlated with chronological age in childhood (r = 0.45-0.65). Maternal smoking during pregnancy was associated with higher skin & blood EAA at birth [B (95% CI) = 1.17 weeks (- 0.09, 2.42)] and in early childhood [0.34 years (0.03, 0.64)]. Female newborns and children had lower Bohlin EGAA [- 0.17 weeks (- 0.30, - 0.04)] and Horvath EAA at birth [B (95% CI) = - 2.88 weeks (- 4.41, - 1.35)] and in childhood [early childhood: - 0.3 years (- 0.60, 0.01); mid-childhood: - 0.48 years (- 0.77, - 0.18)] than males. When comparing self-reported Asian, Black, Hispanic, and more than one race or other racial/ethnic groups to White, we identified significant differences in EGAA and EAA at birth and in mid-childhood, but associations varied across clocks. Horvath EA at birth was positively associated with childhood Horvath and skin & blood EAA. CONCLUSIONS Maternal smoking during pregnancy and child sex were associated with EGAA and EAA at multiple timepoints. Further research may provide insight into the relationship between perinatal factors, pediatric epigenetic aging, and health and development across the lifespan.
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Affiliation(s)
- Anne K Bozack
- Department of Epidemiology and Population Health, Stanford University, Research Park, 1701 Page Mill Road, Stanford, CA, USA
| | - Sheryl L Rifas-Shiman
- Division of Chronic Disease Research Across the Lifecourse, Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, MA, USA
| | - Diane R Gold
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Channing Division of Network Medicine, Department of Medicine, Harvard Medical School and Brigham and Women's Hospital, Boston, MA, USA
| | - Zachary M Laubach
- Department of Ecology and Evolutionary Biology (EEB), University of Colorado Boulder, Boulder, CO, USA
| | - Wei Perng
- Department of Epidemiology, Colorado School of Public Health and Lifecourse Epidemiology of Adiposity and Diabetes (LEAD) Center, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Marie-France Hivert
- Division of Chronic Disease Research Across the Lifecourse, Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, MA, USA
- Diabetes Unit, Massachusetts General Hospital, Boston, MA, USA
| | - Andres Cardenas
- Department of Epidemiology and Population Health, Stanford University, Research Park, 1701 Page Mill Road, Stanford, CA, USA.
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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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Caro JC, Holuka C, Menta G, Turner JD, Vögele C, D'Ambrosio C. Children's internalizing behavior development is heterogeneously associated with the pace of epigenetic aging. Biol Psychol 2023; 176:108463. [PMID: 36436681 DOI: 10.1016/j.biopsycho.2022.108463] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2022] [Revised: 11/15/2022] [Accepted: 11/17/2022] [Indexed: 11/27/2022]
Abstract
BACKGROUND Internalizing behaviors are an indicator of children's psychological and emotional development, predicting future mental disorders. Recent studies have identified associations between DNA methylation (DNAm) and internalizing behaviors. This prospective study aimed at exploring the associations between pace of biological aging and the developmental trajectories of internalizing behaviors. METHODS Participants were children from the Avon Longitudinal Study of Parents and Children (ALSPAC) cohort (N = 974). Measures of DNA methylation were collected at birth, age 7 and ages 15-17. The pace of aging was estimated using the DunedinPoAm algorithm (PoAm). Internalizing behaviors reported by caregivers between ages 4 and 16 using the Strengths and Difficulties Questionnaire. To explore heterogeneity in the association between PoAm and internalizing behaviors we use Poisson quantile regression in cross-section heterogeneity and longitudinal latent class analysis over the childhood and adolescence. RESULTS Internalizing behavior trajectories were identified: low-risk, childhood limited, late onset and early onset (persistent). Accelerated aging at birth was negatively associated with internalizing behaviors in early childhood but positively correlated during adolescence. Higher PoAm at birth increased chance of low-risk profile, while decreasing likelihood of childhood limited trajectory. PoAm at age 15 was negatively associated with childhood limited profile and positively linked to late onset trajectories. Associations were larger at higher values of internalizing symptoms. CONCLUSIONS The heterogeneity in the association between biological age acceleration and internalizing behaviors suggests a complex dynamic relationship, particularly in children with high or increased risk of adverse mental health outcomes.
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Affiliation(s)
- Juan Carlos Caro
- Department of Behavioral and Cognitive Sciences, University of Luxembourg, Luxembourg.
| | - Cyrielle Holuka
- Department of Infection and Immunity, Luxembourg Institute of Health, Luxembourg; Faculty of Sciences, University of Luxembourg, Luxembourg
| | - Giorgia Menta
- Luxembourg Institute of Socio-Economic Research (LISER), Luxembourg
| | - Jonathan D Turner
- Department of Infection and Immunity, Luxembourg Institute of Health, Luxembourg
| | - Claus Vögele
- Department of Behavioral and Cognitive Sciences, University of Luxembourg, Luxembourg
| | - Conchita D'Ambrosio
- Department of Behavioral and Cognitive Sciences, University of Luxembourg, Luxembourg
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Kankaanpää A, Tolvanen A, Heikkinen A, Kaprio J, Ollikainen M, Sillanpää E. The role of adolescent lifestyle habits in biological aging: A prospective twin study. eLife 2022; 11:80729. [PMID: 36345722 PMCID: PMC9642990 DOI: 10.7554/elife.80729] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2022] [Accepted: 10/01/2022] [Indexed: 11/09/2022] Open
Abstract
Background: Adolescence is a stage of fast growth and development. Exposures during puberty can have long-term effects on health in later life. This study aims to investigate the role of adolescent lifestyle in biological aging. Methods: The study participants originated from the longitudinal FinnTwin12 study (n = 5114). Adolescent lifestyle-related factors, including body mass index (BMI), leisure-time physical activity, smoking, and alcohol use, were based on self-reports and measured at ages 12, 14, and 17 years. For a subsample, blood-based DNA methylation (DNAm) was used to assess biological aging with six epigenetic aging measures in young adulthood (21–25 years, n = 824). A latent class analysis was conducted to identify patterns of lifestyle behaviors in adolescence, and differences between the subgroups in later biological aging were studied. Genetic and environmental influences on biological aging shared with lifestyle behavior patterns were estimated using quantitative genetic modeling. Results: We identified five subgroups of participants with different adolescent lifestyle behavior patterns. When DNAm GrimAge, DunedinPoAm, and DunedinPACE estimators were used, the class with the unhealthiest lifestyle and the class of participants with high BMI were biologically older than the classes with healthier lifestyle habits. The differences in lifestyle-related factors were maintained into young adulthood. Most of the variation in biological aging shared with adolescent lifestyle was explained by common genetic factors. Conclusions: These findings suggest that an unhealthy lifestyle during pubertal years is associated with accelerated biological aging in young adulthood. Genetic pleiotropy may largely explain the observed associations. Funding: This work was supported by the Academy of Finland (213506, 265240, 263278, 312073 to J.K., 297908 to M.O. and 341750, 346509 to E.S.), EC FP5 GenomEUtwin (J.K.), National Institutes of Health/National Heart, Lung, and Blood Institute (grant HL104125), EC MC ITN Project EPITRAIN (J.K. and M.O.), the University of Helsinki Research Funds (M.O.), Sigrid Juselius Foundation (J.K. and M.O.), Yrjö Jahnsson Foundation (6868), Juho Vainio Foundation (E.S.) and Päivikki and Sakari Sohlberg foundation (E.S.). For most animals, events that occur early in life can have a lasting impact on individuals’ health. In humans, adolescence is a particularly vulnerable time when rapid growth and development collide with growing independence and experimentation. An unhealthy lifestyle during this period of rapid cell growth can contribute to later health problems like heart disease, lung disease, and premature death. This is due partly to accelerated biological aging, where the body deteriorates faster than what would be expected for an individual’s chronological age. One way to track the effects of lifestyle on biological aging is by measuring epigenetic changes. Epigenetic changes consist on adding or removing chemical ‘tags’ on genes. These tags can switch the genes on or off without changing their sequences. Scientists can measure certain epigenetic changes by measuring the levels of methylated DNA – DNA with a chemical ‘tag’ known as a methyl group – in blood samples. Several algorithms – known as ‘epigenetic clocks’ – are available that estimate how fast an individual is aging biologically based on DNA methylation. Kankaanpää et al. show that unhealthy lifestyles during adolescence may lead to accelerated aging in early adulthood. For their analysis, Kankaanpää et al. used data on the levels of DNA methylation in blood samples from 824 twins between 21 and 25 years old. The twins were participants in the FinnTwin12 study and had completed a survey about their lifestyles at ages 12, 14, and 17. Kankaanpää et al. classified individuals into five groups depending on their lifestyles. The first three groups, which included most of the twins, contained individuals that led relatively healthy lives. The fourth group contained individuals with a higher body mass index based on their height and weight. Finally, the last group included individuals with unhealthy lifestyles who binge drank, smoked and did not exercise. After estimating the biological ages for all of the participants, Kankaanpää et al. found that both the individuals with higher body mass indices and those in the group with unhealthy lifestyles aged faster than those who reported healthier lifestyles. However, the results varied depending on which epigenetic clock Kankaanpää et al. used to measure biological aging: clocks that had been developed earlier showed fewer differences in aging between groups; while newer clocks consistently found that individuals in the higher body mass index and unhealthy groups were older. Kankaanpää et al. also showed that shared genetic factors explained both unhealthy lifestyles and accelerated biological aging. The experiments performed by Kankaanpää et al. provide new insights into the vital role of an individual’s genetics in unhealthy lifestyles and cellular aging. These insights might help scientists identify at risk individuals early in life and try to prevent accelerated aging.
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Affiliation(s)
- Anna Kankaanpää
- Gerontology Research Center (GEREC), Faculty of Sport and Health Sciences, University of Jyväskylä
| | - Asko Tolvanen
- Methodology Center for Human Sciences, University of Jyväskylä
| | - Aino Heikkinen
- Institute for Molecular Medicine Finland (FIMM), HiLife, University of Helsinki
| | - Jaakko Kaprio
- Institute for Molecular Medicine Finland (FIMM), HiLife, University of Helsinki
| | - Miina Ollikainen
- Institute for Molecular Medicine Finland (FIMM), HiLife, University of Helsinki
| | - Elina Sillanpää
- Gerontology Research Center (GEREC), Faculty of Sport and Health Sciences, University of Jyväskylä
- Institute for Molecular Medicine Finland (FIMM), HiLife, University of Helsinki
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10
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Bolhuis E, Belsky J, Frankenhuis WE, Shalev I, Hastings WJ, Tollenaar MS, O’Donnell KJ, McGill MG, Pokhvisneva I, Lin DT, MacIsaac JL, Kobor MS, de Weerth C, Beijers R. Attachment insecurity and the biological embedding of reproductive strategies: Investigating the role of cellular aging. Biol Psychol 2022; 175:108446. [DOI: 10.1016/j.biopsycho.2022.108446] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2021] [Revised: 10/15/2022] [Accepted: 10/16/2022] [Indexed: 11/02/2022]
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11
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Kuzawa CW, Ryan CP, Adair LS, Lee NR, Carba DB, MacIsaac JL, Dever K, Atashzay P, Kobor MS, McDade TW. Birth weight and maternal energy status during pregnancy as predictors of epigenetic age acceleration in young adults from metropolitan Cebu, Philippines. Epigenetics 2022; 17:1535-1545. [PMID: 35574972 PMCID: PMC9586628 DOI: 10.1080/15592294.2022.2070105] [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] [Indexed: 12/15/2022] Open
Abstract
Epigenetic clocks quantify regular changes in DNA methylation that occur with age, or in relation to biomarkers of ageing, and are strong predictors of morbidity and mortality. Here, we assess whether measures of fetal nutrition and growth that predict adult chronic disease also predict accelerated biological ageing in young adulthood using a suite of commonly used epigenetic clocks. Data come from the Cebu Longitudinal Health and Nutrition Survey (CLHNS), a long-running cohort followed since birth in metropolitan Cebu, Philippines. Past work has shown that birth weight (BW) and the mother's arm fat during pregnancy (a measure of pregnancy energy status) relate inversely to health outcomes in the CLHNS but primarily in males. Genome-wide DNA methylation was assessed in whole blood using the Infinium EPIC array. Participants included males (n=895) and females (n=803) measured in 2005 (20.8-22.5 years). Clocks included the Hannum and Horvath clocks trained on chronological age, the DNAmPhenoAge and DNAmGrimAge clocks trained on clinical biomarkers, the Dunedin pace of ageing (DunedinPACE) clock trained on longitudinal changes in ageing biomarkers, and the DNAmTL clock trained on leukocyte telomere length. In males, lower BW predicted advanced biological ageing using the Hannum, DNAmPhenoAge, DunedinPoAm, and DNAmTL clocks. In contrast, BW did not predict any clock in female participants. Participants' mothers' pregnancy arm fat only predicted DNAmTL in males. These findings suggest that epigenetic clocks are a useful tool for gauging long-term outcomes predicted by fetal growth, and add to existing evidence in the CLHNS for sex differences in these relationships.
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Affiliation(s)
- Christopher W Kuzawa
- Department of Anthropology, Northwestern University, Evanston, USA.,Institute for Policy Research, Northwestern University, Evanston, USA
| | - Calen P Ryan
- Butler Columbia Aging Center, Department of Epidemiology, Columbia University Mailman School of Public Health
| | - Linda S Adair
- Department of Nutrition, Gillings School of Global Public Health, University of North Carolina at Chapel Hill
| | - Nanette R Lee
- USC-Office of Population Studies Foundation, University of San Carlos, Talamban, Cebu City
| | - Delia B Carba
- USC-Office of Population Studies Foundation, University of San Carlos, Talamban, Cebu City
| | - Julia L MacIsaac
- Department of Medical Genetics, Faculty of Medicine, University of British Columbia, Vancouver, British Columbia, Canada.,BC Children's Hospital Research Institute, University of British Columbia, Vancouver, British Columbia, Canada.,Centre for Molecular Medicine and Therapeutics, University of British Columbia, Vancouver, Canada
| | - Kristy Dever
- Department of Medical Genetics, Faculty of Medicine, University of British Columbia, Vancouver, British Columbia, Canada.,BC Children's Hospital Research Institute, University of British Columbia, Vancouver, British Columbia, Canada.,Centre for Molecular Medicine and Therapeutics, University of British Columbia, Vancouver, Canada
| | - Parmida Atashzay
- Department of Medical Genetics, Faculty of Medicine, University of British Columbia, Vancouver, British Columbia, Canada.,BC Children's Hospital Research Institute, University of British Columbia, Vancouver, British Columbia, Canada.,Centre for Molecular Medicine and Therapeutics, University of British Columbia, Vancouver, Canada
| | - Michael S Kobor
- Department of Medical Genetics, Faculty of Medicine, University of British Columbia, Vancouver, British Columbia, Canada.,BC Children's Hospital Research Institute, University of British Columbia, Vancouver, British Columbia, Canada.,Centre for Molecular Medicine and Therapeutics, University of British Columbia, Vancouver, Canada
| | - Thomas W McDade
- Department of Anthropology, Northwestern University, Evanston, USA.,Institute for Policy Research, Northwestern University, Evanston, USA
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12
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Reimann B, Martens DS, Wang C, Ghantous A, Herceg Z, Plusquin M, Nawrot TS. Interrelationships and determinants of aging biomarkers in cord blood. J Transl Med 2022; 20:353. [PMID: 35945616 PMCID: PMC9361565 DOI: 10.1186/s12967-022-03541-1] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2022] [Accepted: 07/17/2022] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Increasing evidence supports the concept of prenatal programming as an early factor in the aging process. DNA methylation age (DNAm age), global genome-wide DNA methylation (global methylation), telomere length (TL), and mitochondrial DNA content (mtDNA content) have independently been shown to be markers of aging, but their interrelationship and determinants at birth remain uncertain. METHODS We assessed the inter-correlation between the aging biomarkers DNAm age, global methylation, TL and mtDNA content using Pearson's correlation in 190 cord blood samples of the ENVIRONAGE birth cohort. TL and mtDNA content was measured via qPCR, while the DNA methylome was determined using the human 450K methylation Illumina microarray. Subsequently, DNAm age was calculated according to Horvath's epigenetic clock, and mean global, promoter, gene-body, and intergenic DNA methylation were determined. Path analysis, a form of structural equation modeling, was performed to disentangle the complex causal relationships among the aging biomarkers and their potential determinants. RESULTS DNAm age was inversely correlated with global methylation (r = -0.64, p < 0.001) and mtDNA content (r = - 0.16, p = 0.027). Cord blood TL was correlated with mtDNA content (r = 0.26, p < 0.001) but not with global methylation or DNAm age. Path analysis showed the strongest effect for global methylation on DNAm age with a decrease of 0.64 standard deviations (SD) in DNAm age for each SD (0.01%) increase in global methylation (p < 0.001). Among the applied covariates, newborn sex and season of delivery were the strongest determinants of aging biomarkers. CONCLUSIONS We provide insight into molecular aging signatures at the start of life, including their interrelations and determinants, showing that cord blood DNAm age is inversely associated with global methylation and mtDNA content but not with newborn telomere length. Our findings demonstrate that cord blood TL and DNAm age relate to different pathways/mechanisms of biological aging and can be influenced by environmental factors already at the start of life. These findings are relevant for understanding fetal programming and for the early prevention of noncommunicable diseases.
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Affiliation(s)
- Brigitte Reimann
- Centre for Environmental Sciences, Hasselt University, Hasselt, Belgium
| | - Dries S Martens
- Centre for Environmental Sciences, Hasselt University, Hasselt, Belgium
| | - Congrong Wang
- Centre for Environmental Sciences, Hasselt University, Hasselt, Belgium
| | - Akram Ghantous
- Epigenomics and Mechanisms Branch, International Agency for Research On Cancer (IARC), Lyon, France
| | - Zdenko Herceg
- Epigenomics and Mechanisms Branch, International Agency for Research On Cancer (IARC), Lyon, France
| | - Michelle Plusquin
- Centre for Environmental Sciences, Hasselt University, Hasselt, Belgium.
| | - Tim S Nawrot
- Centre for Environmental Sciences, Hasselt University, Hasselt, Belgium
- School of Public Health, Occupational and Environmental Medicine, KU Leuven, Leuven, Belgium
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13
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Common Ground between Biological Rhythms and Forensics. BIOLOGY 2022; 11:biology11071071. [PMID: 36101448 PMCID: PMC9312156 DOI: 10.3390/biology11071071] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/08/2022] [Revised: 07/12/2022] [Accepted: 07/14/2022] [Indexed: 11/16/2022]
Abstract
Simple Summary Biological clocks regulate the timing of numerous body functions in adaption to daily repeating cycles in the environment, such as the sleep–wake phases that are trained by the cycling changes of night and day light. The identification of a deceased victim is a critical component in a forensic investigation, but it can be significantly hampered by the condition of the dead body and the lack of personal records and documents. This review links current knowledge on the molecular mechanisms of biological rhythms to forensically relevant aspects, including the time period since death, cause of death, the use of insects for forensics, sex and age of a person, ethnic background and development. Putting these findings in context demonstrates how the analysis of molecular clock analysis could be used as tool for future personal identification in forensic investigations. Abstract Biological clocks set the timing for a large number of essential processes in the living human organism. After death, scientific evidence is required in forensic investigations in order to collect as much information as possible on the death circumstances and personal identifiers of the deceased victim. We summarize the associations between the molecular mechanisms of biological rhythms and forensically relevant aspects, including post-mortem interval and cause of death, entomological findings, sex, age, ethnicity and development. Given their importance during lifetime, biological rhythms could be potential tools to draw conclusions on the death circumstances and the identity of a deceased person by mechanistic investigations of the different biological clocks in a forensic context. This review puts the known effects of biological rhythms on the functions of the human organism in context with potential applications in forensic fields of interest, such as personal identification, entomology as well as the determination of the post-mortem interval and cause of death.
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14
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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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15
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Koemel NA, Skilton MR. Epigenetic Aging in Early Life: Role of Maternal and Early Childhood Nutrition. Curr Nutr Rep 2022; 11:318-328. [PMID: 35192186 PMCID: PMC9174131 DOI: 10.1007/s13668-022-00402-7] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 02/05/2022] [Indexed: 12/20/2022]
Abstract
PURPOSE OF REVIEW Early life presents a pivotal period during which nutritional exposures are more likely to cause epigenetic modifications, which may impact an individual's health during adulthood. This article reviews the current evidence regarding maternal and early childhood nutritional exposures and their role in epigenetic aging. RECENT FINDINGS Maternal and early life consumption of diets higher in fiber, antioxidants, polyphenols, B vitamins, vitamin D, and ω-3 fatty acids is associated with slower epigenetic aging. Conversely, diets higher in glycemic load, fat, saturated fat, and ω-6 fatty acids demonstrate a positive association with epigenetic aging. Maternal and early life nutrition directly and indirectly influences epigenetic aging via changes in one-carbon metabolism, cardiometabolic health, and the microbiome. Clinical trials are warranted to determine the specific foods, dietary patterns, and dietary supplements that will normalize or lower epigenetic aging across the life course.
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Affiliation(s)
- Nicholas A. Koemel
- The Boden Initiative, Charles Perkins Centre, The University of Sydney, Sydney, Australia
- Sydney Medical School, Faculty of Medicine and Health, The University of Sydney, Sydney, Australia
| | - Michael R. Skilton
- The Boden Initiative, Charles Perkins Centre, The University of Sydney, Sydney, Australia
- Sydney Medical School, Faculty of Medicine and Health, The University of Sydney, Sydney, Australia
- Sydney Institute for Women, Children and Their Families, Sydney Local Health District, Sydney, Australia
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16
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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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17
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How to Slow Down the Ticking Clock: Age-Associated Epigenetic Alterations and Related Interventions to Extend Life Span. Cells 2022; 11:cells11030468. [PMID: 35159278 PMCID: PMC8915189 DOI: 10.3390/cells11030468] [Citation(s) in RCA: 26] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2022] [Accepted: 01/26/2022] [Indexed: 02/04/2023] Open
Abstract
Epigenetic alterations pose one major hallmark of organismal aging. Here, we provide an overview on recent findings describing the epigenetic changes that arise during aging and in related maladies such as neurodegeneration and cancer. Specifically, we focus on alterations of histone modifications and DNA methylation and illustrate the link with metabolic pathways. Age-related epigenetic, transcriptional and metabolic deregulations are highly interconnected, which renders dissociating cause and effect complicated. However, growing amounts of evidence support the notion that aging is not only accompanied by epigenetic alterations, but also at least in part induced by those. DNA methylation clocks emerged as a tool to objectively determine biological aging and turned out as a valuable source in search of factors positively and negatively impacting human life span. Moreover, specific epigenetic signatures can be used as biomarkers for age-associated disorders or even as targets for therapeutic approaches, as will be covered in this review. Finally, we summarize recent potential intervention strategies that target epigenetic mechanisms to extend healthy life span and provide an outlook on future developments in the field of longevity research.
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18
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Nwanaji-Enwerem JC, Van Der Laan L, Kogut K, Eskenazi B, Holland N, Deardorff J, Cardenas A. Maternal adverse childhood experiences before pregnancy are associated with epigenetic aging changes in their children. Aging (Albany NY) 2021; 13:25653-25669. [PMID: 34923483 PMCID: PMC8751604 DOI: 10.18632/aging.203776] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2021] [Accepted: 11/24/2021] [Indexed: 02/06/2023]
Abstract
Emerging research suggests associations of physical and psychosocial stressors with epigenetic aging. Although this work has included early-life exposures, data on maternal exposures and epigenetic aging of their children remain sparse. Using longitudinally collected data from the California, Salinas Valley CHAMACOS study, we examined relationships between maternal Adverse Childhood Experiences (ACEs) reported up to 18 years of life, prior to pregnancy, with eight measures (Horvath, Hannum, SkinBloodClock, Intrinsic, Extrinsic, PhenoAge, GrimAge, and DNAm telomere length) of blood leukocyte epigenetic age acceleration (EAA) in their children at ages 7, 9, and 14 years (N = 238 participants with 483 observations). After adjusting for maternal chronological age at delivery, pregnancy smoking/alcohol use, parity, child gestational age, and estimated leukocyte proportions, higher maternal ACEs were significantly associated with at least a 0.76-year increase in child Horvath and Intrinsic EAA. Higher maternal ACEs were also associated with a 0.04 kb greater DNAm estimate of telomere length of children. Overall, our data suggests that maternal preconception ACEs are associated with biological aging in their offspring in childhood and that preconception ACEs have differential relationships with EAA measures, suggesting different physiologic utilities of EEA measures. Studies are necessary to confirm these findings and to elucidate potential pathways to explain these relationships, which may include intergenerational epigenetic inheritance and persistent physical and social exposomes.
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Affiliation(s)
- Jamaji C Nwanaji-Enwerem
- Gangarosa Department of Environmental Health, Emory Rollins School of Public Health, Atlanta, GA 30322, USA.,Department of Emergency Medicine, Emory University School of Medicine, Atlanta, GA 30303, USA.,Division of Environmental Health Sciences, School of Public Health, University of California, Berkeley, CA 94720, USA.,Center for Computational Biology, School of Public Health, University of California, Berkeley, CA 94720, USA
| | - Lars Van Der Laan
- Division of Environmental Health Sciences, School of Public Health, University of California, Berkeley, CA 94720, USA.,Center for Computational Biology, School of Public Health, University of California, Berkeley, CA 94720, USA
| | - Katherine Kogut
- Center for Environmental Research of Community Health, CERCH, School of Public Health, University of California, Berkeley, CA 94720, USA
| | - Brenda Eskenazi
- Division of Environmental Health Sciences, School of Public Health, University of California, Berkeley, CA 94720, USA.,Center for Computational Biology, School of Public Health, University of California, Berkeley, CA 94720, USA.,Center for Environmental Research of Community Health, CERCH, School of Public Health, University of California, Berkeley, CA 94720, USA.,Community Health Sciences Division, School of Public Health, University of California, Berkeley, CA 94720, USA
| | - Nina Holland
- Division of Environmental Health Sciences, School of Public Health, University of California, Berkeley, CA 94720, USA.,Center for Computational Biology, School of Public Health, University of California, Berkeley, CA 94720, USA.,Center for Environmental Research of Community Health, CERCH, School of Public Health, University of California, Berkeley, CA 94720, USA
| | - Julianna Deardorff
- Center for Environmental Research of Community Health, CERCH, School of Public Health, University of California, Berkeley, CA 94720, USA.,Community Health Sciences Division, School of Public Health, University of California, Berkeley, CA 94720, USA
| | - Andres Cardenas
- Division of Environmental Health Sciences, School of Public Health, University of California, Berkeley, CA 94720, USA.,Center for Computational Biology, School of Public Health, University of California, Berkeley, CA 94720, USA.,Center for Environmental Research of Community Health, CERCH, School of Public Health, University of California, Berkeley, CA 94720, USA
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19
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Monasso GS, Jaddoe VWV, Küpers LK, Felix JF. Epigenetic age acceleration and cardiovascular outcomes in school-age children: The Generation R Study. Clin Epigenetics 2021; 13:205. [PMID: 34784966 PMCID: PMC8597298 DOI: 10.1186/s13148-021-01193-4] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2021] [Accepted: 10/31/2021] [Indexed: 12/14/2022] Open
Abstract
BACKGROUND Hypertension and atherosclerosis may partly originate in early life. Altered epigenetic aging may be a mechanism underlying associations of early-life exposures and the development of cardiovascular risk factors in childhood. A discrepancy between chronological age and age predicted from neonatal DNA methylation data is referred to as age acceleration. It may either be positive, if DNA methylation age is older than clinical age, or negative, if DNA methylation age is younger than chronological age. We examined associations of age acceleration at birth ('gestational age acceleration'), and of age acceleration at school-age, with blood pressure and with intima-media thickness and distensibility of the common carotid artery, as markers of vascular structure and function, respectively, measured at age 10 years. RESULTS This study was embedded in the Generation R Study, a population-based prospective cohort study. We included 1115 children with information on cord blood DNA methylation and blood pressure, carotid intima-media thickness or carotid distensibility. Gestational age acceleration was calculated using the Bohlin epigenetic clock, which was developed specifically for cord blood DNA methylation data. It predicts gestational age based on methylation levels of 96 CpGs from HumanMethylation450 BeadChip. We observed no associations of gestational age acceleration with blood pressure, carotid intima-media thickness or carotid distensibility at age 10 years. In analyses among children with peripheral blood DNA methylation measured at age 6 (n = 470) and 10 (n = 449) years, we also observed no associations of age acceleration at these ages with the same cardiovascular outcomes, using the 'skin and blood clock,' which predicts age based on methylation levels at 391 CpGs from HumanMethylation450 BeadChip. CONCLUSIONS Our findings do not provide support for the hypothesis that altered epigenetic aging during the earliest phase of life is involved in the development of cardiovascular risk factors in childhood.
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Affiliation(s)
- Giulietta S Monasso
- The Generation R Study Group (Na-2918), Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
- Department of Pediatrics, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Vincent W V Jaddoe
- The Generation R Study Group (Na-2918), Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
- Department of Pediatrics, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Leanne K Küpers
- The Generation R Study Group (Na-2918), Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
- Department of Pediatrics, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
- Division of Human Nutrition and Health, Wageningen University, Wageningen, The Netherlands
| | - Janine F Felix
- The Generation R Study Group (Na-2918), Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands.
- Department of Pediatrics, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands.
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20
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Bertucci EM, Mason MW, Rhodes OE, Parrott BB. Exposure to ionizing radiation disrupts normal epigenetic aging in Japanese medaka. Aging (Albany NY) 2021; 13:22752-22771. [PMID: 34644261 PMCID: PMC8544305 DOI: 10.18632/aging.203624] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2021] [Accepted: 09/03/2021] [Indexed: 02/06/2023]
Abstract
Alterations to the epigenome are a hallmark of biological aging and age-dependent patterning of the DNA methylome ("epigenetic aging") can be modeled to produce epigenetic age predictors. Rates of epigenetic aging vary amongst individuals and correlate to the onset of age-related disease and all-cause mortality. Yet, the origins of epigenetic-to-chronological age discordance are not empirically resolved. Here, we investigate the relationship between aging, DNA methylation, and environmental exposures in Japanese medaka (Oryzias latipes). We find age-associated DNA methylation patterning enriched in genomic regions of low CpG density and that, similar to mammals, most age-related changes occur during early life. We construct an epigenetic clock capable of predicting chronological age with a mean error of 61.1 days (~8.4% of average lifespan). To test the role of environmental factors in driving epigenetic age variation, we exposed medaka to chronic, environmentally relevant doses of ionizing radiation. Because most organisms share an evolutionary history with ionizing radiation, we hypothesized that exposure would reveal fundamental insights into environment-by-epigenetic aging interactions. Radiation exposure disrupted epigenetic aging by accelerating and decelerating normal age-associated patterning and was most pronounced in cytosines that were moderately associated with age. These findings empirically demonstrate the role of DNA methylation in integrating environmental factors into aging trajectories.
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Affiliation(s)
- Emily M. Bertucci
- Odum School of Ecology, University of Georgia, Athens, GA 30602, USA
- Savannah River Ecology Laboratory, University of Georgia, Aiken, SC 29802, USA
| | - Marilyn W. Mason
- Savannah River Ecology Laboratory, University of Georgia, Aiken, SC 29802, USA
| | - Olin E. Rhodes
- Odum School of Ecology, University of Georgia, Athens, GA 30602, USA
- Savannah River Ecology Laboratory, University of Georgia, Aiken, SC 29802, USA
| | - Benjamin B. Parrott
- Odum School of Ecology, University of Georgia, Athens, GA 30602, USA
- Savannah River Ecology Laboratory, University of Georgia, Aiken, SC 29802, USA
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21
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de Prado-Bert P, Ruiz-Arenas C, Vives-Usano M, Andrusaityte S, Cadiou S, Carracedo Á, Casas M, Chatzi L, Dadvand P, González JR, Grazuleviciene R, Gutzkow KB, Haug LS, Hernandez-Ferrer C, Keun HC, Lepeule J, Maitre L, McEachan R, Nieuwenhuijsen MJ, Pelegrí D, Robinson O, Slama R, Vafeiadi M, Sunyer J, Vrijheid M, Bustamante M. The early-life exposome and epigenetic age acceleration in children. ENVIRONMENT INTERNATIONAL 2021; 155:106683. [PMID: 34144479 DOI: 10.1016/j.envint.2021.106683] [Citation(s) in RCA: 42] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/04/2021] [Revised: 06/01/2021] [Accepted: 06/01/2021] [Indexed: 06/12/2023]
Abstract
The early-life exposome influences future health and accelerated biological aging has been proposed as one of the underlying biological mechanisms. We investigated the association between more than 100 exposures assessed during pregnancy and in childhood (including indoor and outdoor air pollutants, built environment, green environments, tobacco smoking, lifestyle exposures, and biomarkers of chemical pollutants), and epigenetic age acceleration in 1,173 children aged 7 years old from the Human Early-Life Exposome project. Age acceleration was calculated based on Horvath's Skin and Blood clock using child blood DNA methylation measured by Infinium HumanMethylation450 BeadChips. We performed an exposure-wide association study between prenatal and childhood exposome and age acceleration. Maternal tobacco smoking during pregnancy was nominally associated with increased age acceleration. For childhood exposures, indoor particulate matter absorbance (PMabs) and parental smoking were nominally associated with an increase in age acceleration. Exposure to the organic pesticide dimethyl dithiophosphate and the persistent pollutant polychlorinated biphenyl-138 (inversely associated with child body mass index) were protective for age acceleration. None of the associations remained significant after multiple-testing correction. Pregnancy and childhood exposure to tobacco smoke and childhood exposure to indoor PMabs may accelerate epigenetic aging from an early age.
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Affiliation(s)
- Paula de Prado-Bert
- ISGlobal, Dr. Aiguader 88, 08003 Barcelona, Spain; Universitat Pompeu Fabra (UPF), Barcelona, Spain; CIBER Epidemiología y Salud Pública (CIBERESP), Madrid, Spain
| | - Carlos Ruiz-Arenas
- ISGlobal, Dr. Aiguader 88, 08003 Barcelona, Spain; Universitat Pompeu Fabra (UPF), Barcelona, Spain; CIBER Epidemiología y Salud Pública (CIBERESP), Madrid, Spain
| | - Marta Vives-Usano
- ISGlobal, Dr. Aiguader 88, 08003 Barcelona, Spain; Universitat Pompeu Fabra (UPF), Barcelona, Spain; Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology, Dr. Aiguader 88, Barcelona 08003, Spain
| | - Sandra Andrusaityte
- Department of Environmental Sciences, Vytautas Magnus University, K. Donelaicio Street 58, 44248 Kaunas, Lithuania
| | - Solène Cadiou
- University Grenoble Alpes, Inserm, CNRS, Team of Environmental Epidemiology Applied to Reproduction and Respiratory Health, IAB, 38000 Grenoble, France
| | - Ángel Carracedo
- Grupo de Medicina Xenómica, Fundación Pública Galega de Medicina Xenómica, Instituto de Investigación Sanitaria de Santiago de Compostela (IDIS), SERGAS, Rúa Choupana s/n, 15706 Santiago de Compostela, Spain; Centro de Investigación en Red de Enfermedades Raras (CIBERER) y Centro Nacional de Genotipado (CEGEN-PRB3-ISCIII), Universidade de Santiago de Compostela, Praza do Obradoiro s/n, 15782 Santiago de Compostela, Spain
| | - Maribel Casas
- ISGlobal, Dr. Aiguader 88, 08003 Barcelona, Spain; Universitat Pompeu Fabra (UPF), Barcelona, Spain; CIBER Epidemiología y Salud Pública (CIBERESP), Madrid, Spain
| | - Leda Chatzi
- Department of Preventive Medicine, Keck School of Medicine, University of Southern California, USA; Department of Social Medicine, School of Medicine, University of Crete, Heraklion, Greece
| | - Payam Dadvand
- ISGlobal, Dr. Aiguader 88, 08003 Barcelona, Spain; Universitat Pompeu Fabra (UPF), Barcelona, Spain; CIBER Epidemiología y Salud Pública (CIBERESP), Madrid, Spain
| | - Juan R González
- ISGlobal, Dr. Aiguader 88, 08003 Barcelona, Spain; Universitat Pompeu Fabra (UPF), Barcelona, Spain; CIBER Epidemiología y Salud Pública (CIBERESP), Madrid, Spain
| | - Regina Grazuleviciene
- Department of Environmental Sciences, Vytautas Magnus University, K. Donelaicio Street 58, 44248 Kaunas, Lithuania
| | - Kristine B Gutzkow
- Department of Environmental Health, Norwegian Institute of Public Health, Oslo, Norway
| | - Line S Haug
- Department of Environmental Health, Norwegian Institute of Public Health, Oslo, Norway
| | - Carles Hernandez-Ferrer
- ISGlobal, Dr. Aiguader 88, 08003 Barcelona, Spain; CNAG-CRG, Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology, Baldiri Reixac 4, Barcelona 08028, Spain
| | - Hector C Keun
- Division of Systems Medicine, Department of Metabolism, Digestion and Reproduction, Imperial College London, South Kensington Campus, London SW7 2AZ, UK
| | - Johanna Lepeule
- University Grenoble Alpes, Inserm, CNRS, Team of Environmental Epidemiology Applied to Reproduction and Respiratory Health, IAB, 38000 Grenoble, France
| | - Léa Maitre
- ISGlobal, Dr. Aiguader 88, 08003 Barcelona, Spain; Universitat Pompeu Fabra (UPF), Barcelona, Spain; CIBER Epidemiología y Salud Pública (CIBERESP), Madrid, Spain
| | - Rosie McEachan
- Bradford Institute for Health Research, Bradford Royal Infirmary, Bradford, UK
| | - Mark J Nieuwenhuijsen
- ISGlobal, Dr. Aiguader 88, 08003 Barcelona, Spain; Universitat Pompeu Fabra (UPF), Barcelona, Spain; CIBER Epidemiología y Salud Pública (CIBERESP), Madrid, Spain
| | - Dolors Pelegrí
- ISGlobal, Dr. Aiguader 88, 08003 Barcelona, Spain; Universitat Pompeu Fabra (UPF), Barcelona, Spain; CIBER Epidemiología y Salud Pública (CIBERESP), Madrid, Spain
| | - Oliver Robinson
- MRC Centre for Environment and Health, School of Public Health, Imperial College London, St Marys Hospital Campus, London W21PG, UK
| | - Rémy Slama
- University Grenoble Alpes, Inserm, CNRS, Team of Environmental Epidemiology Applied to Reproduction and Respiratory Health, IAB, 38000 Grenoble, France
| | - Marina Vafeiadi
- Department of Social Medicine, School of Medicine, University of Crete, Heraklion, Greece
| | - Jordi Sunyer
- ISGlobal, Dr. Aiguader 88, 08003 Barcelona, Spain; Universitat Pompeu Fabra (UPF), Barcelona, Spain; CIBER Epidemiología y Salud Pública (CIBERESP), Madrid, Spain
| | - Martine Vrijheid
- ISGlobal, Dr. Aiguader 88, 08003 Barcelona, Spain; Universitat Pompeu Fabra (UPF), Barcelona, Spain; CIBER Epidemiología y Salud Pública (CIBERESP), Madrid, Spain
| | - Mariona Bustamante
- ISGlobal, Dr. Aiguader 88, 08003 Barcelona, Spain; Universitat Pompeu Fabra (UPF), Barcelona, Spain; Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology, Dr. Aiguader 88, Barcelona 08003, Spain.
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22
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Simpson DJ, Chandra T. Epigenetic age prediction. Aging Cell 2021; 20:e13452. [PMID: 34415665 PMCID: PMC8441394 DOI: 10.1111/acel.13452] [Citation(s) in RCA: 59] [Impact Index Per Article: 19.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2021] [Revised: 07/21/2021] [Accepted: 07/27/2021] [Indexed: 12/14/2022] Open
Abstract
Advanced age is the main common risk factor for cancer, cardiovascular disease and neurodegeneration. Yet, more is known about the molecular basis of any of these groups of diseases than the changes that accompany ageing itself. Progress in molecular ageing research was slow because the tools predicting whether someone aged slowly or fast (biological age) were unreliable. To understand ageing as a risk factor for disease and to develop interventions, the molecular ageing field needed a quantitative measure; a clock for biological age. Over the past decade, a number of age predictors utilising DNA methylation have been developed, referred to as epigenetic clocks. While they appear to estimate biological age, it remains unclear whether the methylation changes used to train the clocks are a reflection of other underlying cellular or molecular processes, or whether methylation itself is involved in the ageing process. The precise aspects of ageing that the epigenetic clocks capture remain hidden and seem to vary between predictors. Nonetheless, the use of epigenetic clocks has opened the door towards studying biological ageing quantitatively, and new clocks and applications, such as forensics, appear frequently. In this review, we will discuss the range of epigenetic clocks available, their strengths and weaknesses, and their applicability to various scientific queries.
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Affiliation(s)
- Daniel J. Simpson
- MRC Human Genetics UnitMRC Institute of Genetics and Molecular MedicineUniversity of EdinburghEdinburghUK
| | - Tamir Chandra
- MRC Human Genetics UnitMRC Institute of Genetics and Molecular MedicineUniversity of EdinburghEdinburghUK
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23
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Maddock J, Castillo-Fernandez J, Wong A, Ploubidis GB, Kuh D, Bell JT, Hardy R. Childhood growth and development and DNA methylation age in mid-life. Clin Epigenetics 2021; 13:155. [PMID: 34372922 PMCID: PMC8351141 DOI: 10.1186/s13148-021-01138-x] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2021] [Accepted: 07/20/2021] [Indexed: 01/03/2023] Open
Abstract
BACKGROUND In the first study of its kind, we examine the association between growth and development in early life and DNAm age biomarkers in mid-life. METHODS Participants were from the Medical Research Council National Survey of Health and Development (n = 1376). Four DNAm age acceleration (AgeAccel) biomarkers were measured when participants were aged 53 years: AgeAccelHannum; AgeAccelHorvath; AgeAccelLevine; and AgeAccelGrim. Exposure variables included: relative weight gain (standardised residuals from models of current weight z-score on current height, and previous weight and height z-scores); and linear growth (standardised residuals from models of current height z-score on previous height and weight z-scores) during infancy (0-2 years, weight gain only), early childhood (2-4 years), middle childhood (4-7 years) and late childhood to adolescence (7-15 years); age at menarche; and pubertal stage for men at 14-15 years. The relationship between relative weight gain and linear growth and AgeAccel was investigated using conditional growth models. We replicated analyses from the late childhood to adolescence period and pubertal timing among 240 participants from The National Child and Development Study (NCDS). RESULTS A 1SD increase in relative weight gain in late childhood to adolescence was associated with 0.50 years (95% CI 0.20, 0.79) higher AgeAccelGrim. Although the CI includes the null, the estimate was similar in NCDS [0.57 years (95% CI - 0.01, 1.16)] There was no strong evidence that relative weight gain and linear growth in childhood was associated with any other AgeAccel biomarker. There was no relationship between pubertal timing in men and AgeAccel biomarkers. Women who reached menarche ≥ 12 years had 1.20 years (95% CI 0.15, 2.24) higher AgeAccelGrim on average than women who reached menarche < 12 years; however, this was not replicated in NCDS and was not statistically significant after Bonferroni correction. CONCLUSIONS Our findings generally do not support an association between growth and AgeAccel biomarkers in mid-life. However, we found rapid weight gain during pubertal development, previously related to higher cardiovascular disease risk, to be associated with older AgeAccelGrim. Given this is an exploratory study, this finding requires replication.
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Affiliation(s)
- Jane Maddock
- MRC Unit for Lifelong Health and Ageing at UCL, Faculty of Population Health, University College London, 1-19 Torrington Place, London, WC1E 7HB, UK.
| | | | - Andrew Wong
- MRC Unit for Lifelong Health and Ageing at UCL, Faculty of Population Health, University College London, 1-19 Torrington Place, London, WC1E 7HB, UK
| | - George B Ploubidis
- Centre for Longitudinal Studies, UCL Social Research Institute, University College London, London, UK
| | - Diana Kuh
- MRC Unit for Lifelong Health and Ageing at UCL, Faculty of Population Health, University College London, 1-19 Torrington Place, London, WC1E 7HB, UK
| | - Jordana T Bell
- Department of Twin Research and Genetic Epidemiology, King's College London, London, UK
| | - Rebecca Hardy
- CLOSER, UCL Institute of Education, University College London, London, WC1H 0NU, UK
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24
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Tekola-Ayele F. Invited Commentary: Epigenetic Clocks and Obesity-Towards the Next Frontier Using Integrative Approaches and Early-Life Models. Am J Epidemiol 2021; 190:994-997. [PMID: 33693471 DOI: 10.1093/aje/kwaa252] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2020] [Revised: 10/13/2020] [Accepted: 11/04/2020] [Indexed: 12/20/2022] Open
Abstract
Why people of the same age show differences in age-related functional decline and whether biological aging can be slowed down through lifestyle changes and therapeutics are active research topics. Molecular tools that predict biological age based on DNA methylation markers, known as epigenetic clocks, are facilitating these efforts. In this issue, Kresovich et al. (Am J Epidemiol. 2021;190(6):984-993) investigated a cohort of non-Hispanic White women, demonstrating positive relationships between adiposity measures and the ticking rate of epigenetic clocks in blood. This commentary emphasizes that integrating molecular and genetic epidemiology approaches is crucial to dissecting the complex relationship between obesity and epigenetic aging. The early-life period is explored as a unique opportunity to gain novel insights into links between developmental processes and aging in later life. Last, the landscape of the next frontier in aging research is described in light of the imperative for transdisciplinary approaches to outline a shared vision and public health implementation dilemmas.
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25
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Kresovich JK, Garval EL, Martinez Lopez AM, Xu Z, Niehoff NM, White AJ, Sandler DP, Taylor JA. Associations of Body Composition and Physical Activity Level With Multiple Measures of Epigenetic Age Acceleration. Am J Epidemiol 2021; 190:984-993. [PMID: 33693587 DOI: 10.1093/aje/kwaa251] [Citation(s) in RCA: 47] [Impact Index Per Article: 15.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2019] [Revised: 09/02/2020] [Accepted: 09/08/2020] [Indexed: 12/22/2022] Open
Abstract
Epigenetic clocks use DNA methylation to estimate biological age. Whether body composition and physical activity are associated with these clocks is not well understood. Using blood samples collected at enrollment (2003-2009) from 2,758 women in the US nationwide Sister Study, we calculated 6 epigenetic age acceleration metrics using 4 epigenetic clocks (Hannum, Horvath, PhenoAge, GrimAge). Recreational physical activity was self-reported, and adiposity measures were assessed by trained medical examiners (body mass index (BMI), waist-to-hip ratio (WtH), waist circumference). In cross-sectional analyses, all adiposity measures were associated with epigenetic age acceleration. The strongest association was for BMI and PhenoAge, a measure of biological age that correlates with chronic disease (BMI of ≥35.0 vs. 18.5-24.9, β = 3.15 years, 95% confidence interval (CI): 2.41, 3.90; P for trend < 0.001). In a mutual-adjustment model, both were associated with PhenoAge age acceleration (BMI of ≥35.0 vs. 18.5-24.9, β = 2.69 years, 95% CI: 1.90, 3.48; P for trend < 0.001; quartile 4 vs.1 WtH, β = 1.00 years, 95% CI: 0.34, 1.65; P for trend < 0.008). After adjustment, physical activity was associated only with GrimAge (quartile 4 vs. 1, β = -0.42 years, 95% CI: -0.70, -0.14; P for trend = 0.001). Physical activity attenuated the waist circumference associations with PhenoAge and GrimAge. Excess adiposity was associated with epigenetic age acceleration; physical activity might attenuate associations with waist circumference.
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26
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Combined healthy lifestyle score and risk of epigenetic aging: a discordant monozygotic twin study. Aging (Albany NY) 2021; 13:14039-14052. [PMID: 34032609 PMCID: PMC8202852 DOI: 10.18632/aging.203022] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2021] [Accepted: 04/02/2021] [Indexed: 01/24/2023]
Abstract
We investigated whether lifestyle influences epigenetic aging in 143 monozygotic twin pairs discordant for the combined healthy lifestyle score. Twins were scored for four lifestyle factors as unhealthy or healthy; non-smoker, moderate drinker, adequate fruit and vegetable intake, and sufficient physical activity. The combined healthy lifestyle score was calculated for each participant by summing the binary score for each factor. Individual and co-twin analyses were used to assess the relationship between single or combined lifestyle scores, along with DNA methylation age acceleration (AA) calculated using Horvath’s and Li’s epigenetic clocks, focusing on AA and intrinsic epigenetic age acceleration (IEAA) measures. Compared with the twins that scored no or one healthy lifestyle point, those who scored four healthy lifestyle points had lower Li_IEAA with similar results observed in the co-twin analysis. No significant relationships were found in analyses based on Horvath’s clock, although the direction of correlations was consistent with that determined using Li’s clock. Smoking and drinking did not significantly affect DNA methylation AA; however, physical activity and intake of vegetables and fruits did, although the influence varied depending on the epigenetic clock. Our findings suggest that a healthy lifestyle may be an important way to delay aging and prevent age-related diseases.
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27
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Petersen CL, Christensen BC, Batsis JA. Weight management intervention identifies association of decreased DNA methylation age with improved functional age measures in older adults with obesity. Clin Epigenetics 2021; 13:46. [PMID: 33653394 PMCID: PMC7927264 DOI: 10.1186/s13148-021-01031-7] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2020] [Accepted: 02/14/2021] [Indexed: 11/26/2022] Open
Abstract
Background Assessing functional ability is an important component of understanding healthy aging. Objective measures of functional ability include grip strength, gait speed, sit-to-stand time, and 6-min walk distance. Using samples from a weight loss clinical trial in older adults with obesity, we examined the association between changes in physical function and DNA-methylation-based biological age at baseline and 12 weeks in 16 individuals. Peripheral blood DNA methylation was measured (pre/post) with the Illumina HumanMethylationEPIC array and the Hannum, Horvath, and PhenoAge DNA methylation age clocks were used. Linear regression models adjusted for chronological age and sex tested the relationship between DNA methylation age and grip strength, gait speed, sit-to-stand, and 6-min walk. Results Participant mean weight loss was 4.6 kg, and DNA methylation age decreased 0.8, 1.1, and 0.5 years using the Hannum, Horvath, and PhenoAge DNA methylation clocks respectively. Mean grip strength increased 3.2 kg. Decreased Hannum methylation age was significantly associated with increased grip strength (β = −0.30, p = 0.04), and increased gait speed (β = 0.02, p = 0.05), in adjusted models. Similarly, decreased methylation age using the PhenoAge clock was associated with significantly increased gait speed (β = 0.02, p = 0.04). A decrease in Horvath DNA methylation age and increase in physical functional ability did not demonstrate a significant association. Conclusions The observed relationship between increased physical functional ability and decreased biological age using DNA methylation clocks demonstrate the potential utility of DNA methylation clocks to assess interventional approaches to improve health in older obese adults. Trial registration: National Institute on Aging (NIA), NCT03104192. Posted April 7, 2017, https://clinicaltrials.gov/ct2/show/NCT03104192
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Affiliation(s)
- Curtis L Petersen
- The Dartmouth Institute for Health Policy, Williamson Translational Research Bld, 5., 1 Medical Center Drive, Lebanon, NH, 03766, USA. .,Quantitative Biomedical Sciences Program, Dartmouth, Hanover, NH, USA.
| | - Brock C Christensen
- Department of Epidemiology, Geisel School of Medicine at Dartmouth, Lebanon, NH, USA.,Department of Molecular and Systems Biology at Dartmouth, Lebanon, NH, USA
| | - John A Batsis
- The Dartmouth Institute for Health Policy, Williamson Translational Research Bld, 5., 1 Medical Center Drive, Lebanon, NH, 03766, USA.,Department of Medicine, Geisel School of Medicine at Dartmouth, Hanover, NH, USA.,Section of General Internal Medicine, Dartmouth-Hitchcock Medical Center, Lebanon, NH, USA.,Division of Geriatric Medicine, School of Medicine, and Department of Nutrition, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
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28
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DNA methylation perturbations may link altered development and aging in the lung. Aging (Albany NY) 2021; 13:1742-1764. [PMID: 33468710 PMCID: PMC7880367 DOI: 10.18632/aging.202544] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2020] [Accepted: 12/18/2020] [Indexed: 12/12/2022]
Abstract
Fetal perturbations in DNA methylation during lung development may reveal insights into the enduring impacts on adult lung health and disease during aging that have not been explored altogether before. We studied the association between genome-wide DNA-methylation and post-conception age in fetal-lung (n=78, 42 exposed to in-utero-smoke (IUS)) tissue and chronological age in adult-lung tissue (n=160, 114 with Chronic Obstructive Pulmonary Disease) using multi-variate linear regression models with covariate adjustment and tested for effect modification by phenotypes. Overlapping age-associations were evaluated for functional and tissue-specific enrichment using the Genotype-Tissue-Expression (GTEx) project. We identified 244 age-associated differentially methylated positions and 878 regions overlapping between fetal and adult-lung tissues. Hyper-methylated CpGs (96%) were enriched in transcription factor activity (FDR adjusted P=2x10-33) and implicated in developmental processes including embryonic organ morphogenesis, neurogenesis and growth delay. Hypo-methylated CpGs (2%) were enriched in oxido-reductase activity and VEGFA-VEGFR2 Signaling. Twenty-one age-by-sex and eleven age-by-pack-years interactions were statistically significant (FDR<0.05) in adult-lung tissue. DNA methylation in transcription factors during development in fetal lung recapitulates in adult-lung tissue with aging. These findings reveal molecular mechanisms and pathways that may link disrupted development in early-life and age-associated lung diseases.
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29
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Hamlat EJ, Prather AA, Horvath S, Belsky J, Epel ES. Early life adversity, pubertal timing, and epigenetic age acceleration in adulthood. Dev Psychobiol 2021; 63:890-902. [PMID: 33423276 DOI: 10.1002/dev.22085] [Citation(s) in RCA: 39] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2020] [Revised: 09/05/2020] [Accepted: 12/07/2020] [Indexed: 12/29/2022]
Abstract
BACKGROUND Given associations linking early life adversity, pubertal timing, and biological aging, we examined the direct and indirect effects of early life trauma on adult biological aging (via age of menarche). METHODS Participants were premenopausal women (N = 183). Path models evaluated whether early life trauma predicted early pubertal timing and thereby, adult epigenetic age acceleration (indexed via four epigenetic clocks: Horvath DNAm Age, Hannum DNAm Age, DNAm PhenoAge, and DNAm GrimAge). Secondary analyses explored the effects of type of trauma (abuse and neglect) and adult chronic stress status (caregiver of child with autism and non-caregiver). RESULTS Early life trauma and earlier age at menarche independently predicted accelerated aging based on one of the four epigenetic clocks, DNAm GrimAge, though early life trauma was not associated with age of menarche. Childhood abuse, but not neglect, predicted faster epigenetic aging; results did not differ by chronic stress status. CONCLUSIONS Early trauma and early menarche appear to exert independent effects on DNAm GrimAge, which has been shown to be the strongest epigenetic predictor of mortality risk. This study identifies a potential correlate or determinant of accelerated epigenetic aging-menarcheal age. Future research should address the limitations of this study by using racially diverse samples.
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Affiliation(s)
| | | | | | - Jay Belsky
- University of California, Davis, CA, USA
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30
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Ryan J, Wrigglesworth J, Loong J, Fransquet PD, Woods RL. A Systematic Review and Meta-analysis of Environmental, Lifestyle, and Health Factors Associated With DNA Methylation Age. J Gerontol A Biol Sci Med Sci 2020; 75:481-494. [PMID: 31001624 DOI: 10.1093/gerona/glz099] [Citation(s) in RCA: 68] [Impact Index Per Article: 17.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2019] [Indexed: 02/07/2023] Open
Abstract
DNA methylation (DNAm) algorithms of biological age provide a robust estimate of an individual's chronological age and can predict their risk of age-related disease and mortality. This study reviewed the evidence that environmental, lifestyle and health factors are associated with the Horvath and Hannum epigenetic clocks. A systematic search identified 61 studies. Chronological age was correlated with DNAm age in blood (median .83, range .13-.99). In a meta-analysis body mass index (BMI) was associated with increased DNAm age (Hannum β: 0.07, 95% CI 0.04 to 0.10; Horvath β: 0.06, 95% CI 0.02 to 0.10), but there was no association with smoking (Hannum β: 0.12, 95% CI -0.50 to 0.73; Horvath β:0.18, 95% CI -0.10 to 0.46). DNAm age was positively associated with frailty (three studies, n = 3,093), and education was negatively associated with the Hannum estimate of DNAm age specifically (four studies, n = 13,955). For most other exposures, findings were too inconsistent to draw conclusions. In conclusion, BMI was positively associated with biological aging measured using DNAm, with some evidence that frailty also increased aging. More research is needed to provide conclusive evidence regarding other exposures. This field of research has the potential to provide further insights into how to promote slower biological aging and ultimately prolong healthy life.
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Affiliation(s)
- Joanne Ryan
- School of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria, Australia.,INSERM, Univ Montpellier, Neuropsychiatry, Epidemiological and Clinical Research, Montpellier, France
| | - Jo Wrigglesworth
- School of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria, Australia
| | - Jun Loong
- School of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria, Australia
| | - Peter D Fransquet
- School of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria, Australia
| | - Robyn L Woods
- School of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria, Australia
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31
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He X, Liu J, Liu B, Shi J. The use of DNA methylation clock in aging research. Exp Biol Med (Maywood) 2020; 246:436-446. [PMID: 33175612 DOI: 10.1177/1535370220968802] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/28/2022] Open
Abstract
One of the key characteristics of aging is a progressive loss of physiological integrity, which weakens bodily functions and increases the risk of death. A robust biomarker is important for the assessment of biological age, the rate of aging, and a person's health status. DNA methylation clocks, novel biomarkers of aging, are composed of a group of cytosine-phosphate-guanine dinucleotides, the DNA methylation status of which can be used to accurately measure subjective age. These clocks are considered accurate biomarkers of chronological age for humans and other vertebrates. Numerous studies have demonstrated these clocks to quantify the rate of biological aging and the effects of longevity and anti-aging interventions. In this review, we describe the purpose and use of DNA methylation clocks in aging research.
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Affiliation(s)
- Xi He
- Key Laboratory of Basic Pharmacology of Ministry of Education and Joint International Research Laboratory of Ethnomedicine of Ministry of Education, 66367Zunyi Medical University, Zunyi 563003, China
| | - Jiaojiao Liu
- Key Laboratory of Basic Pharmacology of Ministry of Education and Joint International Research Laboratory of Ethnomedicine of Ministry of Education, 66367Zunyi Medical University, Zunyi 563003, China
| | - Bo Liu
- Key Laboratory of Basic Pharmacology of Ministry of Education and Joint International Research Laboratory of Ethnomedicine of Ministry of Education, 66367Zunyi Medical University, Zunyi 563003, China
| | - Jingshan Shi
- Key Laboratory of Basic Pharmacology of Ministry of Education and Joint International Research Laboratory of Ethnomedicine of Ministry of Education, 66367Zunyi Medical University, Zunyi 563003, China
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32
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Li S, Nguyen TL, Wong EM, Dugué PA, Dite GS, Armstrong NJ, Craig JM, Mather KA, Sachdev PS, Saffery R, Sung J, Tan Q, Thalamuthu A, Milne RL, Giles GG, Southey MC, Hopper JL. Genetic and environmental causes of variation in epigenetic aging across the lifespan. Clin Epigenetics 2020; 12:158. [PMID: 33092643 PMCID: PMC7583207 DOI: 10.1186/s13148-020-00950-1] [Citation(s) in RCA: 24] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2020] [Accepted: 10/13/2020] [Indexed: 12/14/2022] Open
Abstract
Background DNA methylation-based biological age (DNAm age) is an important biomarker for adult health. Studies in specific age ranges have found widely varying results about its genetic and environmental causes of variation. However, these studies are not able to provide a comprehensive view of the causes of variation over the lifespan.
Results In order to investigate the genetic and environmental causes of DNAm age variation across the lifespan, we pooled genome-wide DNA methylation data for 4217 people aged 0–92 years from 1871 families. DNAm age was calculated using the Horvath epigenetic clock. We estimated familial correlations in DNAm age for monozygotic (MZ) twin, dizygotic (DZ) twin, sibling, parent–offspring, and spouse pairs by cohabitation status. Genetic and environmental variance components models were fitted and compared. We found that twin pair correlations were − 0.12 to 0.18 around birth, not different from zero (all P > 0.29). For all pairs of relatives, their correlations increased with time spent living together (all P < 0.02) at different rates (MZ > DZ and siblings > parent–offspring; P < 0.001) and decreased with time spent living apart (P = 0.02) at similar rates. These correlation patterns were best explained by cohabitation-dependent shared environmental factors, the effects of which were 1.41 (95% confidence interval [CI] 1.16 to 1.66) times greater for MZ pairs than for DZ and sibling pairs, and the latter were 2.03 (95% CI 1.13 to 9.47) times greater than for parent–offspring pairs. Genetic factors explained 13% (95% CI − 10 to 35%) of variation (P = 0.27). Similar results were found for another two epigenetic clocks, suggesting that our observations are robust to how DNAm age is measured. In addition, results for the other clocks were consistent with there also being a role for prenatal environmental factors in determining their variation. Conclusions Variation in DNAm age is mostly caused by environmental factors, including those shared to different extents by relatives while living together and whose effects persist into old age. The equal environment assumption of the classic twin study might not hold for epigenetic aging.
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Affiliation(s)
- Shuai Li
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Parkville, VIC, 3051, Australia.,Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK.,Precision Medicine, School of Clinical Sciences At Monash Health, Monash University, Clayton, VIC, Australia
| | - Tuong L Nguyen
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Parkville, VIC, 3051, Australia
| | - Ee Ming Wong
- Precision Medicine, School of Clinical Sciences At Monash Health, Monash University, Clayton, VIC, Australia.,Department of Clinical Pathology, The University of Melbourne, Melbourne, VIC, Australia
| | - Pierre-Antoine Dugué
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Parkville, VIC, 3051, Australia.,Precision Medicine, School of Clinical Sciences At Monash Health, Monash University, Clayton, VIC, Australia.,Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, Australia
| | - Gillian S Dite
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Parkville, VIC, 3051, Australia
| | | | - Jeffrey M Craig
- Centre for Molecular and Medical Research, School of Medicine, Faculty of Health, Deakin University, Waurn Ponds, VIC, Australia
| | - Karen A Mather
- Centre for Healthy Brain Ageing (CHeBA), School of Psychiatry, University of New South Wales, Sydney, NSW, Australia.,Neuropsychiatric Institute, Prince of Wales Hospital, Randwick, NSW, Australia
| | - Perminder S Sachdev
- Centre for Healthy Brain Ageing (CHeBA), School of Psychiatry, University of New South Wales, Sydney, NSW, Australia.,Neuropsychiatric Institute, Prince of Wales Hospital, Randwick, NSW, Australia
| | - Richard Saffery
- Murdoch Childrens Research Institute, Parkville, VIC, Australia
| | - Joohon Sung
- Institute of Health and Environment, Seoul National University, 1 Gwanak-ro, Gwanak-gu, Seoul, 151-742, Korea
| | - Qihua Tan
- Epidemiology and Biostatistics, Department of Public Health, University of Southern Denmark, Odense, Denmark
| | - Anbupalam Thalamuthu
- Centre for Healthy Brain Ageing (CHeBA), School of Psychiatry, University of New South Wales, Sydney, NSW, Australia
| | - Roger L Milne
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Parkville, VIC, 3051, Australia.,Precision Medicine, School of Clinical Sciences At Monash Health, Monash University, Clayton, VIC, Australia.,Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, Australia
| | - Graham G Giles
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Parkville, VIC, 3051, Australia.,Precision Medicine, School of Clinical Sciences At Monash Health, Monash University, Clayton, VIC, Australia.,Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, Australia
| | - Melissa C Southey
- Precision Medicine, School of Clinical Sciences At Monash Health, Monash University, Clayton, VIC, Australia.,Department of Clinical Pathology, The University of Melbourne, Melbourne, VIC, Australia.,Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, Australia
| | - John L Hopper
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Parkville, VIC, 3051, Australia.
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McKenna BG, Hendrix CL, Brennan PA, Smith AK, Stowe ZN, Newport DJ, Knight AK. Maternal prenatal depression and epigenetic age deceleration: testing potentially confounding effects of prenatal stress and SSRI use. Epigenetics 2020; 16:327-337. [PMID: 32660321 DOI: 10.1080/15592294.2020.1795604] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/13/2023] Open
Abstract
Previous studies suggest epigenetic alterations may contribute to the association between maternal prenatal depression and adverse offspring outcomes. Developmental researchers have recently begun to examine these associations in relation to epigenetic age acceleration/deceleration, a biomarker of developmental risk that reflects the deviation between epigenetic age and chronological age. In the perinatal period, preliminary studies indicate that maternal prenatal depression may lead to epigenetic age deceleration in newborns, which may predict adverse developmental outcomes. The present study examined the relationship between maternal prenatal exposures (i.e., depression, stress, and SSRI use) and offspring epigenetic age deceleration in 303 mother-offspring dyads. Women were recruited in the first trimester of pregnancy and followed longitudinally until delivery. Maternal depression, perceived stress, and SSRI use were assessed at each prenatal visit. Newborn epigenetic age was determined via cord blood samples. Results indicated maternal prenatal stress was not associated with newborn epigenetic age deceleration (ΔR2 = 0.002; p = 0.37). Maternal prenatal depression was associated with decelerated epigenetic age (ΔR2 = 0.01, p = 0.04), but this relationship did not hold when accounting for maternal use of SSRIs (ΔR2 = 0.002, p = 0.43). Conversely, maternal SSRI use significantly predicted newborn epigenetic age deceleration over and above the influence of maternal depression (ΔR2 = 0.03, p = 0.001). These findings suggest maternal prenatal SSRI use may significantly contribute to the previously documented association between maternal prenatal depression and epigenetic age deceleration. Further studies are needed to examine how these epigenetic differences at birth may contribute to adverse outcomes in later development.
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Affiliation(s)
| | | | | | - Alicia K Smith
- Department of Gynecology and Obstetrics, Emory University , Atlanta, GA, USA.,Department of Psychiatry and Behavioral Sciences, Emory University , Atlanta, GA, USA
| | - Zachary N Stowe
- Department of Psychiatry, University of Wisconsin , Madison, WI, USA
| | - D Jeffrey Newport
- Department of Psychiatry, University of Texas at Austin , Austin, TX, USA
| | - Anna K Knight
- Department of Gynecology and Obstetrics, Emory University , Atlanta, GA, USA
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34
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Ross KM, Carroll J, Horvath S, Hobel CJ, Coussons-Read ME, Schetter CD. Immune epigenetic age in pregnancy and 1 year after birth: Associations with weight change. Am J Reprod Immunol 2020; 83:e13229. [PMID: 32061136 PMCID: PMC8401279 DOI: 10.1111/aji.13229] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2019] [Revised: 01/24/2020] [Accepted: 01/27/2020] [Indexed: 12/21/2022] Open
Abstract
PROBLEM Epigenetic age indices are markers of biological aging determined from DNA methylation patterns. Accelerated epigenetic age predicts morbidity and mortality. Women tend to demonstrate slower blood epigenetic aging compared to men, possibly due to female-specific hormones and reproductive milestones. Pregnancy and the post-partum period are critical reproductive periods that have not been studied yet with respect to epigenetic aging. The purpose of this paper was to examine whether pregnancy itself and an important pregnancy-related variable, changes in body mass index (BMI) between pregnancy and the post-partum period, are associated with epigenetic aging. METHOD OF STUDY A pilot sample of 35 women was recruited as part of the Healthy Babies Before Birth (HB3) project. Whole blood samples were collected at mid-pregnancy and 1 year post-partum. DNA methylation at both time points was assayed using Infinium 450K and EPIC chips. Epigenetic age indices were calculated using an online calculator. RESULTS Paired-sample t-tests were used to test differences in epigenetic age indices from pregnancy to 1 year after birth. Over this critical time span, women became younger with respect to phenotypic epigenetic age, GrimAge, DNAm PAI-1, and epigenetic age indices linked to aging-related shifts in immune cell populations, known as extrinsic epigenetic age. Post-partum BMI retention, but not prenatal BMI increases, predicted accelerated epigenetic aging. CONCLUSION Women appear to become younger from pregnancy to the post-partum period based on specific epigenetic age indices. Further, BMI at 1 year after birth that reflects weight retention predicted greater epigenetic aging during this period.
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Affiliation(s)
- Kharah M. Ross
- Centre for Social Sciences, Athabasca University, Athabasca, AB, Canada
| | - Judith Carroll
- Department of Psychiatry and Biobehavioral Sciences, Cousins Center for Psychoneuroimmunology, David Geffen School of Medicine, Semel Institute for Neuroscience and Human Behavior, University of California – Los Angeles, Los Angeles, CA, USA
| | - Steve Horvath
- Department of Biostatistics, University of California – Los Angeles, Los Angeles, CA, USA
| | - Calvin J. Hobel
- Department of Obstetrics and Gynecology, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Mary E. Coussons-Read
- Psychology Department, University of Colorado – Colorado Springs, Colorado Springs, CO, USA
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35
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Raj K, Horvath S. Current perspectives on the cellular and molecular features of epigenetic ageing. Exp Biol Med (Maywood) 2020; 245:1532-1542. [PMID: 32276545 DOI: 10.1177/1535370220918329] [Citation(s) in RCA: 34] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022] Open
Abstract
IMPACT STATEMENT The field of epigenetic ageing is relatively new, and the speed of its expansion presents a challenge in keeping abreast with new discoveries and their implications. Several reviews have already addressed the great number of pathologies, health conditions, life-style, and external stressors that are associated with changes to the rate of epigenetic ageing. While these associations highlight and affirm the ability of epigenetic clock to capture biologically meaningful changes associated with age, they do not inform us about the underlying mechanisms. In this very early period since the development of the clock, there have been rather limited experimental research that are aimed at uncovering the mechanism. Hence, the perspective that we proffer is derived from available but nevertheless limited lines of evidence that together provide a seemingly coherent narrative that can be tested. This, we believe would be helpful towards uncovering the workings of the epigenetic clock.
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Affiliation(s)
- Kenneth Raj
- Radiation Effects Department, Centre for Radiation, Chemical and Environmental Hazards, Public Health England, Chilton, Didcot, Oxfordshire OX11 0RQ, UK
| | - Steve Horvath
- Department of Human Genetics, David Geffen School of Medicine, University of California Los Angeles, CA 90095, USA and Department of Biostatistics, Fielding School of Public Health, University of California Los Angeles, CA 90095, USA
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36
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Marini S, Davis KA, Soare TW, Zhu Y, Suderman MJ, Simpkin AJ, Smith ADAC, Wolf EJ, Relton CL, Dunn EC. Adversity exposure during sensitive periods predicts accelerated epigenetic aging in children. Psychoneuroendocrinology 2020; 113:104484. [PMID: 31918390 PMCID: PMC7832214 DOI: 10.1016/j.psyneuen.2019.104484] [Citation(s) in RCA: 70] [Impact Index Per Article: 17.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/22/2019] [Revised: 10/11/2019] [Accepted: 10/11/2019] [Indexed: 12/30/2022]
Abstract
OBJECTIVES Exposure to adversity has been linked to accelerated biological aging, which in turn has been shown to predict numerous physical and mental health problems. In recent years, measures of DNA methylation-based epigenetic age--known as "epigenetic clocks"--have been used to estimate accelerated epigenetic aging. Although a small number of studies have found an effect of adversity exposure on epigenetic age in children, none have investigated if there are "sensitive periods" when adversity is most impactful. METHODS Using data from the Avon Longitudinal Study of Parents and Children (ALSPAC; n = 973), we tested the prospective association between repeated measures of childhood exposure to seven types of adversity on epigenetic age assessed at age 7.5 using the Horvath and Hannum epigenetic clocks. With a Least Angle Regression variable selection procedure, we evaluated potential sensitive period effects. RESULTS We found that exposure to abuse, financial hardship, or neighborhood disadvantage during sensitive periods in early and middle childhood best explained variability in the deviation of Hannum-based epigenetic age from chronological age, even after considering the role of adversity accumulation and recency. Secondary sex-stratified analyses identified particularly strong sensitive period effects. These effects were undetected in analyses comparing children "exposed" versus "unexposed" to adversity. We did not identify any associations between adversity and epigenetic age using the Horvath epigenetic clock. CONCLUSIONS Our results suggest that adversity may alter methylation processes in ways that either directly or indirectly perturb normal cellular aging and that these effects may be heightened during specific life stages.
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Affiliation(s)
- Sandro Marini
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, 02114, USA
| | - Kathryn A Davis
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, 02114, USA
| | - Thomas W Soare
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, 02114, USA; Stanley Center for Psychiatric Research, The Broad Institute of Harvard and MIT, Cambridge, MA, 02142, USA; Department of Psychiatry, Harvard Medical School, Boston, MA, 02115, USA
| | - Yiwen Zhu
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, 02114, USA
| | - Matthew J Suderman
- MRC Integrative Epidemiology Unit, School of Social and Community Medicine, University of Bristol, Bristol, BSB 1TH, UK
| | - Andrew J Simpkin
- MRC Integrative Epidemiology Unit, School of Social and Community Medicine, University of Bristol, Bristol, BSB 1TH, UK; School of Mathematics, Statistics and Applied Mathematics, National University of Ireland, Galway, H91TK33, Ireland
| | - Andrew D A C Smith
- Applied Statistics Group, University of the West of England, Bristol, BS16 1QY, UK
| | - Erika J Wolf
- National Center for PTSD at VA Boston Healthcare System, Boston, MA, 02130, USA; Boston University School of Medicine, Department of Psychiatry, Boston, MA, 02118, USA
| | - Caroline L Relton
- MRC Integrative Epidemiology Unit, School of Social and Community Medicine, University of Bristol, Bristol, BSB 1TH, UK; Institute of Genetic Medicine, University of Newcastle, Newcastle upon Tyne, NE1 3BZ, UK
| | - Erin C Dunn
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, 02114, USA; Stanley Center for Psychiatric Research, The Broad Institute of Harvard and MIT, Cambridge, MA, 02142, USA; Department of Psychiatry, Harvard Medical School, Boston, MA, 02115, USA; McCance Center for Brain Health at Massachusetts General Hospital, Boston, MA, 02114, USA.
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37
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Bright HD, Howe LD, Khouja JN, Simpkin AJ, Suderman M, O'Keeffe LM. Epigenetic gestational age and trajectories of weight and height during childhood: a prospective cohort study. Clin Epigenetics 2019; 11:194. [PMID: 31842976 PMCID: PMC6916215 DOI: 10.1186/s13148-019-0761-7] [Citation(s) in RCA: 20] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2019] [Accepted: 10/09/2019] [Indexed: 11/21/2022] Open
Abstract
Background Differences between an individual’s estimated epigenetic gestational age (EGA) and their actual gestational age (GA) are defined as gestational age acceleration (GAA). GAA is associated with increased birthweight and birth length. Whether these associations persist through childhood is yet to be investigated. Methods We examined the association between GAA and trajectories of height and weight from birth to 10 years (n = 785) in a British birth cohort study, the Avon Longitudinal Study of Parents and Children (ALSPAC). EGA of participants was estimated using DNA methylation data from cord blood using a recently developed prediction model. GAA of participants, measured in weeks, was calculated as the residuals from a regression model of EGA on actual GA. Analyses were performed using linear spline multilevel models and adjusted for maternal age, maternal pre-pregnancy BMI, maternal smoking during pregnancy, and maternal education. Results In adjusted analyses, offspring with a one-week greater GAA were born on average 0.14 kg heavier (95% confidence interval (CI) 0.09, 0.19) and 0.55 cm taller (95% CI 0.33, 0.78) at birth. These differences in weight persisted up to approximately age 9 months but thereafter began to attenuate. From age 5 years onwards, the association between GAA and weight reversed such that GAA was associated with lower weight and this association strengthened with age (mean difference at age 10 years − 0.60 kg, 95% CI − 1.19, − 0.01). Differences in height persisted only up to age 9 months (mean difference at 9 months 0.15 cm, 95% CI − 0.09, 0.39). From age 9 months to age 10 years, offspring with a one-week greater GAA were of comparable height with those with no GAA (mean difference at age 10 years − 0.07 cm, 95% CI − 0.64, 0.50). Conclusions Gestational age acceleration is associated with increased birth weight and length and these differences persist to age 9 months. From age 5 years onwards, the association of GAA and weight reverses such that by age 10 years, greater GAA is associated with lower childhood weight. Further work is required to examine whether the weight effects of GAA strengthen through adolescence and into early adulthood.
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Affiliation(s)
- Harold D Bright
- Bristol Medical School, Faculty of Health Sciences, University of Bristol, First Floor, 5 Tyndall Avenue, Bristol, BS8 1UD, UK.
| | - Laura D Howe
- MRC Integrative Epidemiology Unit at the University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS8 2BN, UK.,Population Health Sciences, Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS8 2BN, UK
| | - Jasmine N Khouja
- MRC Integrative Epidemiology Unit at the University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS8 2BN, UK.,Population Health Sciences, Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS8 2BN, UK.,School of Psychological Science at the University of Bristol, 12a Priory Road, Bristol, BS8 1TU, UK
| | - Andrew J Simpkin
- School of Mathematics, Statistics and Applied Mathematics, National University of Ireland, University Road, Galway, H91 TK33, Ireland
| | - Matthew Suderman
- MRC Integrative Epidemiology Unit at the University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS8 2BN, UK.,Population Health Sciences, Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS8 2BN, UK
| | - Linda M O'Keeffe
- MRC Integrative Epidemiology Unit at the University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS8 2BN, UK.,Population Health Sciences, Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS8 2BN, UK
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Bell CG, Lowe R, Adams PD, Baccarelli AA, Beck S, Bell JT, Christensen BC, Gladyshev VN, Heijmans BT, Horvath S, Ideker T, Issa JPJ, Kelsey KT, Marioni RE, Reik W, Relton CL, Schalkwyk LC, Teschendorff AE, Wagner W, Zhang K, Rakyan VK. DNA methylation aging clocks: challenges and recommendations. Genome Biol 2019; 20:249. [PMID: 31767039 PMCID: PMC6876109 DOI: 10.1186/s13059-019-1824-y] [Citation(s) in RCA: 437] [Impact Index Per Article: 87.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/04/2019] [Accepted: 09/16/2019] [Indexed: 12/15/2022] Open
Abstract
Epigenetic clocks comprise a set of CpG sites whose DNA methylation levels measure subject age. These clocks are acknowledged as a highly accurate molecular correlate of chronological age in humans and other vertebrates. Also, extensive research is aimed at their potential to quantify biological aging rates and test longevity or rejuvenating interventions. Here, we discuss key challenges to understand clock mechanisms and biomarker utility. This requires dissecting the drivers and regulators of age-related changes in single-cell, tissue- and disease-specific models, as well as exploring other epigenomic marks, longitudinal and diverse population studies, and non-human models. We also highlight important ethical issues in forensic age determination and predicting the trajectory of biological aging in an individual.
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Affiliation(s)
- Christopher G Bell
- William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, UK.
| | - Robert Lowe
- The Blizard Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, UK.
| | - Peter D Adams
- Sanford Burnham Prebys Medical Discovery Institute, La Jolla, CA, USA.
- Beatson Institute for Cancer Research and University of Glasgow, Glasgow, UK.
| | - Andrea A Baccarelli
- Department of Environmental Health Sciences, Mailman School of Public Health, Columbia University, New York, NY, USA.
| | - Stephan Beck
- Medical Genomics, Paul O'Gorman Building, UCL Cancer Institute, University College London, London, UK.
| | - Jordana T Bell
- Department of Twin Research and Genetic Epidemiology, King's College London, London, UK.
| | - Brock C Christensen
- Department of Epidemiology, Geisel School of Medicine, Dartmouth College, Lebanon, NH, USA.
- Department of Molecular and Systems Biology, Geisel School of Medicine, Dartmouth College, Lebanon, NH, USA.
- Department of Community and Family Medicine, Geisel School of Medicine, Dartmouth College, Lebanon, NH, USA.
| | - Vadim N Gladyshev
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA.
| | - Bastiaan T Heijmans
- Molecular Epidemiology, Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, the Netherlands.
| | - Steve Horvath
- Department of Human Genetics, Gonda Research Center, David Geffen School of Medicine, Los Angeles, CA, USA.
- Department of Biostatistics, School of Public Health, University of California-Los Angeles, Los Angeles, CA, USA.
| | - Trey Ideker
- San Diego Center for Systems Biology, University of California-San Diego, San Diego, CA, USA.
| | - Jean-Pierre J Issa
- Fels Institute for Cancer Research, Lewis Katz School of Medicine, Temple University, Philadelphia, PA, USA.
| | - Karl T Kelsey
- Department of Epidemiology, Brown University, Providence, RI, USA.
- Department of Pathology and Laboratory Medicine, Brown University, Providence, RI, USA.
| | - Riccardo E Marioni
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK.
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK.
| | - Wolf Reik
- Epigenetics Programme, The Babraham Institute, Cambridge, UK.
- The Wellcome Trust Sanger Institute, Cambridge, UK.
| | - Caroline L Relton
- Medical Research Council Integrative Epidemiology Unit (MRC IEU), School of Social and Community Medicine, University of Bristol, Bristol, UK.
| | | | - Andrew E Teschendorff
- CAS Key Laboratory of Computational Biology, CAS-MPG Partner Institute for Computational Biology, Shanghai Institute of Nutrition and Health, Shanghai Institutes for Biological Sciences, University of Chinese Academy of Sciences, Chinese Academy of Sciences, 320 Yue Yang Road, Shanghai, 200031, China.
- UCL Cancer Institute, Paul O'Gorman Building, University College London, 72 Huntley Street, London, WC1E 6BT, UK.
| | - Wolfgang Wagner
- Helmholtz-Institute for Biomedical Engineering, Stem Cell Biology and Cellular Engineering, RWTH Aachen Faculty of Medicine, Aachen, Germany.
| | - Kang Zhang
- Faculty of Medicine, Macau University of Science and Technology, Taipa, Macau.
| | - Vardhman K Rakyan
- The Blizard Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, UK.
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Horvath S, Oshima J, Martin GM, Lu AT, Quach A, Cohen H, Felton S, Matsuyama M, Lowe D, Kabacik S, Wilson JG, Reiner AP, Maierhofer A, Flunkert J, Aviv A, Hou L, Baccarelli AA, Li Y, Stewart JD, Whitsel EA, Ferrucci L, Matsuyama S, Raj K. Epigenetic clock for skin and blood cells applied to Hutchinson Gilford Progeria Syndrome and ex vivo studies. Aging (Albany NY) 2019; 10:1758-1775. [PMID: 30048243 PMCID: PMC6075434 DOI: 10.18632/aging.101508] [Citation(s) in RCA: 334] [Impact Index Per Article: 66.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2018] [Accepted: 07/21/2018] [Indexed: 01/01/2023]
Abstract
DNA methylation (DNAm)-based biomarkers of aging have been developed for many tissues and organs. However, these biomarkers have sub-optimal accuracy in fibroblasts and other cell types used in ex vivo studies. To address this challenge, we developed a novel and highly robust DNAm age estimator (based on 391 CpGs) for human fibroblasts, keratinocytes, buccal cells, endothelial cells, lymphoblastoid cells, skin, blood, and saliva samples. High age correlations can also be observed in sorted neurons, glia, brain, liver, and even bone samples. Gestational age correlates with DNAm age in cord blood. When used on fibroblasts from Hutchinson Gilford Progeria Syndrome patients, this age estimator (referred to as the skin & blood clock) uncovered an epigenetic age acceleration with a magnitude that is below the sensitivity levels of other DNAm-based biomarkers. Furthermore, this highly sensitive age estimator accurately tracked the dynamic aging of cells cultured ex vivo and revealed that their proliferation is accompanied by a steady increase in epigenetic age. The skin & blood clock predicts lifespan and it relates to many age-related conditions. Overall, this biomarker is expected to become useful for forensic applications (e.g. blood or buccal swabs) and for a quantitative ex vivo human cell aging assay.
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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
| | - Junko Oshima
- Department of Pathology, University of Washington, Seattle, WA 98195, USA.,Department of Clinical Cell Biology and Medicine, Graduate School of Medicine, Chiba University, Chiba, Japan
| | - George M Martin
- Department of Pathology, University of Washington, Seattle, WA 98195, USA
| | - Ake T Lu
- Department of Human Genetics, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA 90095, USA
| | - Austin Quach
- Department of Human Genetics, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA 90095, USA
| | - Howard Cohen
- Elizabeth House, Warlingham, Surrey CR6 9LF, United Kingdom
| | - Sarah Felton
- Department of Dermatology, Oxford University Hospitals NHS Foundation Trust, Oxford OX3 7LJ, United Kingdom
| | - Mieko Matsuyama
- Department of Medicine, Case Western Reserve University, Cleveland, OH 44106, USA
| | - Donna Lowe
- Radiation Effects Department, Centre for Radiation, Chemical and Environmental Hazards, Public Health England, Chilton, Didcot, Oxfordshire OX11 0RQ, United Kingdom
| | - Sylwia Kabacik
- Radiation Effects Department, Centre for Radiation, Chemical and Environmental Hazards, Public Health England, Chilton, Didcot, Oxfordshire OX11 0RQ, United Kingdom
| | - James G Wilson
- Department of Physiology and Biophysics, University of Mississippi Medical Center, Jackson, MS 39216, USA
| | - Alex P Reiner
- Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA
| | - Anna Maierhofer
- Institute of Human Genetics, Julius Maximilians University, Würzburg, Germany
| | - Julia Flunkert
- Institute of Human Genetics, Julius Maximilians University, Würzburg, Germany
| | - Abraham Aviv
- Center of Development and Aging, New Jersey Medical School, Rutgers State University of New Jersey, Newark, NJ 07103, USA
| | - Lifang Hou
- Center for Population Epigenetics, Robert H. Lurie Comprehensive Cancer Center and Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL 60611, USA
| | - Andrea A Baccarelli
- Laboratory of Environmental Epigenetics, Departments of Environmental Health Sciences and Epidemiology, Columbia University Mailman School of Public Health, New York, NY 10032, USA
| | - Yun Li
- Departments of Genetics, Biostatistics, Computer Science, University of North Carolina, Chapel Hill, NC 27599, USA
| | - James D Stewart
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC 27599, USA
| | - Eric A Whitsel
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC 27599, USA.,Department of Medicine, School of Medicine, University of North Carolina, Chapel Hill, NC 27516, USA
| | - Luigi Ferrucci
- Longitudinal Studies Section, Translational Gerontology Branch, National Institute on Aging, National Institutes of Health, Baltimore, MD 21224, USA
| | - Shigemi Matsuyama
- Department of Medicine, Case Western Reserve University, Cleveland, OH 44106, USA.,Department of Pathology and Pharmacology, Case Comprehensive Centre, Case Western Reserve University, Cleveland, OH 44106, USA
| | - Kenneth Raj
- Radiation Effects Department, Centre for Radiation, Chemical and Environmental Hazards, Public Health England, Chilton, Didcot, Oxfordshire OX11 0RQ, United Kingdom
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40
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Curtis SW, Cobb DO, Kilaru V, Terrell ML, Marder ME, Barr DB, Marsit CJ, Marcus M, Conneely KN, Smith AK. Environmental exposure to polybrominated biphenyl (PBB) associates with an increased rate of biological aging. Aging (Albany NY) 2019; 11:5498-5517. [PMID: 31375641 PMCID: PMC6710070 DOI: 10.18632/aging.102134] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2019] [Accepted: 07/26/2019] [Indexed: 12/13/2022]
Abstract
Advanced age increases risk for cancer, cardiovascular disease, and all-cause mortality. However, people do not age at the same rate, and biological age (frequently measured through DNA methylation) can be older than chronological age. Environmental factors have been associated with the rate of biological aging, but it is not known whether persistent endocrine-disrupting compounds (EDCs) like polybrominated biphenyl (PBB) would associate with age acceleration. Three different epigenetic age acceleration measures (intrinsic, extrinsic, and phenotypic) were calculated from existing epigenetic data in whole blood from a population highly exposed to PBB (N=658). Association between serum PBB concentration and these measures was tested, controlling for sex, lipid levels, and estimated cell type proportions. Higher PBB levels associated with increased age acceleration (intrinsic: β=0.24, 95%CI=0.01-0.46, p = 0.03; extrinsic: β=0.39, 95%CI=0.12-0.65, p = 0.004; and phenotypic: β=0.30, 95%CI=0.05-0.54, p = 0.01). Neither age when exposed to PBB nor sex statistically interacted with PBB to predict age acceleration, but, in stratified analyses, the association between PBB and age acceleration was only in people exposed before finishing puberty and in men. This suggests that EDCs can associate with the biological aging process, and further studies are warranted to investigate other environmental pollutants' effect on aging.
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Affiliation(s)
- Sarah W. Curtis
- Genetics and Molecular Biology Program, Laney Graduate School, Emory University, Atlanta, GA 30322, USA
| | - Dawayland O. Cobb
- Department of Gynecology and Obstetrics, School of Medicine, Emory University, Atlanta, GA 30322, USA
| | - Varun Kilaru
- Department of Gynecology and Obstetrics, School of Medicine, Emory University, Atlanta, GA 30322, USA
| | - Metrecia L. Terrell
- Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, GA 30322, USA
| | - M. Elizabeth Marder
- Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, GA 30322, USA
| | - Dana Boyd Barr
- Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, GA 30322, USA
| | - Carmen J. Marsit
- Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, GA 30322, USA
| | - Michele Marcus
- Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, GA 30322, USA
- Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, GA 30322, USA
- Department of Pediatrics, School of Medicine, Emory University, Atlanta, GA 30322, USA
| | - Karen N. Conneely
- Department of Human Genetics, School of Medicine, Emory University, Atlanta, GA 30322, USA
| | - Alicia K. Smith
- Department of Gynecology and Obstetrics, School of Medicine, Emory University, Atlanta, GA 30322, USA
- Department of Psychiatry and Behavioral Sciences, School of Medicine, Emory University, Atlanta, GA 30322, USA
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41
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Everson TM, Marsit CJ, Michael O'Shea T, Burt A, Hermetz K, Carter BS, Helderman J, Hofheimer JA, McGowan EC, Neal CR, Pastyrnak SL, Smith LM, Soliman A, DellaGrotta SA, Dansereau LM, Padbury JF, Lester BM. Epigenome-wide Analysis Identifies Genes and Pathways Linked to Neurobehavioral Variation in Preterm Infants. Sci Rep 2019; 9:6322. [PMID: 31004082 PMCID: PMC6474865 DOI: 10.1038/s41598-019-42654-4] [Citation(s) in RCA: 30] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2018] [Accepted: 04/03/2019] [Indexed: 02/07/2023] Open
Abstract
Neonatal molecular biomarkers of neurobehavioral responses (measures of brain-behavior relationships), when combined with neurobehavioral performance measures, could lead to better predictions of long-term developmental outcomes. To this end, we examined whether variability in buccal cell DNA methylation (DNAm) associated with neurobehavioral profiles in a cohort of infants born less than 30 weeks postmenstrual age (PMA) and participating in the Neonatal Neurobehavior and Outcomes in Very Preterm Infants (NOVI) Study (N = 536). We tested whether epigenetic age, age acceleration, or DNAm levels at individual loci differed between infants based on their NICU Network Neurobehavioral Scale (NNNS) profile classifications. We adjusted for recruitment site, infant sex, PMA, and tissue heterogeneity. Infants with an optimally well-regulated NNNS profile had older epigenetic age compared to other NOVI infants (β1 = 0.201, p-value = 0.026), but no significant difference in age acceleration. In contrast, infants with an atypical NNNS profile had differential methylation at 29 CpG sites (FDR < 10%). Some of the genes annotated to these CpGs included PLA2G4E, TRIM9, GRIK3, and MACROD2, which have previously been associated with neurological structure and function, or with neurobehavioral disorders. These findings contribute to the existing evidence that neonatal epigenetic variations may be informative for infant neurobehavior.
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Affiliation(s)
- Todd M Everson
- Department of Environmental Health, Emory University Rollins School of Public Health, Atlanta, GA, United States.
| | - Carmen J Marsit
- Department of Environmental Health, Emory University Rollins School of Public Health, Atlanta, GA, United States
| | - T Michael O'Shea
- Department of Pediatrics, University of North Carolina School of Medicine, Chapel Hill, NC, United States
| | - Amber Burt
- Department of Environmental Health, Emory University Rollins School of Public Health, Atlanta, GA, United States
| | - Karen Hermetz
- Department of Environmental Health, Emory University Rollins School of Public Health, Atlanta, GA, United States
| | - Brian S Carter
- Department of Pediatrics-Neonatology, Children's Mercy Hospital, Kansas City, MO, United States
| | - Jennifer Helderman
- Department of Pediatrics, Wake Forest School of Medicine, Winston Salem, NC, United States
| | - Julie A Hofheimer
- Department of Pediatrics, University of North Carolina School of Medicine, Chapel Hill, NC, United States
| | - Elisabeth C McGowan
- Department of Pediatrics, Brown Alpert Medical School and Women and Infants Hospital, Providence, RI, United States
| | - Charles R Neal
- Department of Pediatrics, University of Hawaii John A. Burns School of Medicine, Honolulu, HI, United States
| | - Steven L Pastyrnak
- Department of Pediatrics, Spectrum Health-Helen Devos Hospital, Grand Rapids, MI, United States
| | - Lynne M Smith
- Department of Pediatrics, Harbor-UCLA Medical Center, Torrance, CA, United States
| | - Antoine Soliman
- Department of Pediatrics, Miller Children's and Women's Hospital Long Beach, Long Beach, CA, United States
| | - Sheri A DellaGrotta
- Brown Center for the Study of Children at Risk, Brown Alpert Medical School and Women and Infants Hospital, Providence, RI, United States
| | - Lynne M Dansereau
- Brown Center for the Study of Children at Risk, Brown Alpert Medical School and Women and Infants Hospital, Providence, RI, United States
| | - James F Padbury
- Department of Pediatrics, Brown Alpert Medical School and Women and Infants Hospital, Providence, RI, United States
| | - Barry M Lester
- Department of Pediatrics, Brown Alpert Medical School and Women and Infants Hospital, Providence, RI, United States
- Brown Center for the Study of Children at Risk, Brown Alpert Medical School and Women and Infants Hospital, Providence, RI, United States
- Department of Psychiatry and Human Behavior, Brown Alpert Medical School, Providence, RI, United States
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42
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Epigenetic age acceleration is associated with allergy and asthma in children in Project Viva. J Allergy Clin Immunol 2019; 143:2263-2270.e14. [PMID: 30738172 DOI: 10.1016/j.jaci.2019.01.034] [Citation(s) in RCA: 39] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2018] [Revised: 01/14/2019] [Accepted: 01/17/2019] [Indexed: 01/10/2023]
Abstract
BACKGROUND Epigenetic clocks have been suggested to capture one feature of the complexity between aging and the epigenome. However, little is known about the epigenetic clock in childhood allergy and asthma. OBJECTIVE We sought to examine associations of DNA methylation age (DNAmAge) and epigenetic age acceleration with childhood allergy and asthma. METHODS We calculated DNAmAge and age acceleration at birth, early childhood, and midchildhood based on the IlluminaHumanMethylation450BeadChip in Project Viva. We evaluated epigenetic clock associations with allergy and asthma using covariate-adjusted linear and logistic regressions. We attempted to replicate our findings in the Genetics of Asthma in Costa Rica Study. RESULTS At midchildhood (mean age, 7.8 years) in Project Viva, DNAmAge and age acceleration were cross-sectionally associated with greater total serum IgE levels and greater odds of atopic sensitization. Every 1-year increase in intrinsic epigenetic age acceleration was associated with a 1.22 (95% CI, 1.07-1.39), 1.17 (95% CI, 1.03-1.34), and 1.29 (95% CI, 1.12-1.49) greater odds of atopic sensitization and environmental and food allergen sensitization. DNAmAge and extrinsic epigenetic age acceleration were also cross-sectionally associated with current asthma at midchildhood. DNAmAge and age acceleration at birth and early childhood were not associated with midchildhood allergy or asthma. The midchildhood association between age acceleration and atopic sensitization were replicated in an independent data set. CONCLUSIONS Because the epigenetic clock might reflect immune and developmental components of biological aging, our study suggests pathways through which molecular epigenetic mechanisms of immunity, development, and maturation can interact along the age axis and associate with childhood allergy and asthma by midchildhood.
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43
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Wu Y, Peterson KE, Sánchez BN, Dolinoy DC, Mercado-Garcia A, Téllez-Rojo MM, Goodrich JM. Association of blood leukocyte DNA methylation at LINE-1 and growth-related candidate genes with pubertal onset and progression. Epigenetics 2018; 13:1222-1233. [PMID: 30582410 PMCID: PMC6986794 DOI: 10.1080/15592294.2018.1556198] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2018] [Revised: 10/01/2018] [Accepted: 11/21/2018] [Indexed: 01/15/2023] Open
Abstract
Puberty is a developmentally plastic phase. Variations in pubertal tempo have implications for the risk of later adult diseases. Influences on pubertal tempo have been widely discussed, but the underlying biological mechanisms remain unclear. Epigenetic modifications are known to regulate development processes; they could play an important role in affecting pubertal outcomes. We conducted a population-based analysis to investigate the association of peripubertal blood DNA methylation at LINE-1 and growth-related candidate genes with pubertal onset and progression in healthy adolescents. The analytic sample included 114 males and 129 females aged 10 to 18 years. DNA methylation at growth-related candidate loci IGF2, H19, HSD11B2, as well as LINE-1 repetitive elements were quantified. Cox survival and ordinal regression models were used to examine sex- and locus-specific associations of epigenetic markers with pubertal development using physician-assessed Tanner stages and self-reported menarche, adjusted for covariates. Among boys, DNA methylation at H19 was associated with later pubarche. HSD11B2 methylation was associated with earlier onset of pubic hair and genitalia development and slower pubertal progression. IGF2 was associated with later onset of genital development. Among girls, LINE-1 methylation was associated with later onset of breast development. For each percent increase of methylation at H19, there was 5% increased odds in the earlier onset of breast development. DNA methylation of IGF2 was associated with earlier onset of pubic hair. DNA methylation at genes known to influence early-life growth may also influence pubertal outcomes.
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Affiliation(s)
- Yue Wu
- Department of Nutritional Sciences, University of Michigan School of Public Health, Ann Arbor, MI, USA
| | - Karen E. Peterson
- Department of Nutritional Sciences, University of Michigan School of Public Health, Ann Arbor, MI, USA
- Center for Human Growth and Development, University of Michigan, Ann Arbor, MI, USA
| | - Brisa N. Sánchez
- Department of Biostatistics, University of Michigan School of Public Health, Ann Arbor, MI, USA
| | - Dana C. Dolinoy
- Department of Nutritional Sciences, University of Michigan School of Public Health, Ann Arbor, MI, USA
- Center for Human Growth and Development, University of Michigan, Ann Arbor, MI, USA
- Department of Environmental Health Sciences, University of Michigan School of Public Health, Ann Arbor, MI, USA
| | - Adriana Mercado-Garcia
- Center for Research on Nutrition and Health, National Institute of Public Health, Cuernavaca, Morelos, México
| | - Martha M. Téllez-Rojo
- Center for Research on Nutrition and Health, National Institute of Public Health, Cuernavaca, Morelos, México
| | - Jaclyn M. Goodrich
- Department of Environmental Health Sciences, University of Michigan School of Public Health, Ann Arbor, MI, USA
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44
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Abstract
Research in the field of gerontology has traditionally focused on later life stages. There is increasing evidence, however, that both the rate of age-related functional decline and the later-life health status can be programmed during early development. The central role of epigenetic mechanisms (methylation of DNA, histone modifications and regulation by non-coding RNAs) in mediating these long-term effects has been elucidated. Both rate and direction of age-associated change of epigenetic patterns (“epigenetic drift”) were shown to be largely dependent on early-life environmental conditions. Inter-individual divergences in epigenetic profiles may arise following the stochastic errors in maintaining epigenetic marks, but they may also be adaptively mediated by specific environmental cues. Recent cohort studies indicate that ticking rate of epigenetic clock, estimated by a DNA methylation-based methods, may be developmentally adjusted, and that individual’s discrepancies among epigenetic and chronological age would be likely programmed early in development. In this Perspective article, recent findings suggesting the importance of early-life determinants for life-course dynamics of epigenetic drift are summarized and discussed.
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45
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Suarez A, Lahti J, Czamara D, Lahti-Pulkkinen M, Girchenko P, Andersson S, Strandberg TE, Reynolds RM, Kajantie E, Binder EB, Raikkonen K. The epigenetic clock and pubertal, neuroendocrine, psychiatric, and cognitive outcomes in adolescents. Clin Epigenetics 2018; 10:96. [PMID: 30021623 PMCID: PMC6052515 DOI: 10.1186/s13148-018-0528-6] [Citation(s) in RCA: 35] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2018] [Accepted: 07/06/2018] [Indexed: 01/17/2023] Open
Abstract
BACKGROUND Molecular aging biomarkers, such as epigenetic age predictors, predict risk factors of premature aging, and morbidity/mortality more accurately than chronological age in middle-aged and elderly populations. Yet, it remains elusive if such biomarkers are associated with aging-related outcomes earlier in life when individuals begin to diverge in aging trajectories. We tested if the Horvath epigenetic age predictor is associated with pubertal, neuroendocrine, psychiatric, and cognitive aging-related outcomes in a sample of 239 adolescents, 11.0-13.2 years-old. RESULTS Each year increase in epigenetic age acceleration (AA) was associated with 0.06 SD units higher weight-for-age, 0.08 SD units taller height-for-age, -0.09 SD units less missed from the expected adult height, 13 and 16% higher odds, respectively, for each stage increase in breast/genitals development on the Tanner Staging Questionnaire and pubertal stage on the Pubertal Development Scale, 4.2% higher salivary cortisol upon awakening, and 18 to 34% higher odds for internalizing and thought problems on the Child Behavior Checklist (p values < 0.045). AA was not significantly associated with cognition. CONCLUSIONS Our findings suggest that already in adolescence, AA is associated with physiological age acceleration, which may index risk of earlier aging. AA may identify individuals for preventive interventions decades before aging-related diseases become manifest.
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Affiliation(s)
- Anna Suarez
- Department of Psychology and Logopedics, University of Helsinki, Haartmaninkatu 3, PO Box 21, FI-00014, Helsinki, Finland.,Helsinki Collegium of Advanced Studies, University of Helsinki, 00014, Helsinki, Finland
| | - Jari Lahti
- Department of Psychology and Logopedics, University of Helsinki, Haartmaninkatu 3, PO Box 21, FI-00014, Helsinki, Finland
| | - Darina Czamara
- Department of Translational Research in Psychiatry, Department of Psychiatry and Behavioral Sciences, Max-Planck Institute of Psychiatry, 80804, Munich, Germany
| | - Marius Lahti-Pulkkinen
- Department of Psychology and Logopedics, University of Helsinki, Haartmaninkatu 3, PO Box 21, FI-00014, Helsinki, Finland
| | - Polina Girchenko
- Department of Psychology and Logopedics, University of Helsinki, Haartmaninkatu 3, PO Box 21, FI-00014, Helsinki, Finland
| | - Sture Andersson
- Children's Hospital, Helsinki University Central Hospital and University of Helsinki, 00029, Helsinki, Finland
| | - Timo E Strandberg
- Center for Life Course Health Research, University of Helsinki, Geriatrics, Helsinki University Hospital, University of Oulu, 00029, Helsinki, Finland
| | - Rebecca M Reynolds
- BHF Centre for Cardiovascular Science, Queen's Medical Research Institute, University of Edinburgh, Edinburgh, EH16 4TJ, UK
| | - Eero Kajantie
- National Institute for Health and Welfare, Helsinki and Oulu, 00271, Helsinki, Finland.,Children's Hospital, Helsinki University Central Hospital and University of Helsinki, 00029, Helsinki, Finland
| | - Elisabeth B Binder
- Department of Translational Research in Psychiatry, Department of Psychiatry and Behavioral Sciences, Max-Planck Institute of Psychiatry, 80804, Munich, Germany.,Department of Psychiatry and Behavioral Sciences, School of Medicine, Emory University, Atlanta, 30322, USA
| | - Katri Raikkonen
- Department of Psychology and Logopedics, University of Helsinki, Haartmaninkatu 3, PO Box 21, FI-00014, Helsinki, Finland.
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46
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Levine ME, Lu AT, Quach A, Chen BH, Assimes TL, Bandinelli S, Hou L, Baccarelli AA, Stewart JD, Li Y, Whitsel EA, Wilson JG, Reiner AP, Aviv A, Lohman K, Liu Y, Ferrucci L, Horvath S. An epigenetic biomarker of aging for lifespan and healthspan. Aging (Albany NY) 2018; 10:573-591. [PMID: 29676998 PMCID: PMC5940111 DOI: 10.18632/aging.101414] [Citation(s) in RCA: 1351] [Impact Index Per Article: 225.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2018] [Accepted: 04/08/2018] [Indexed: 04/08/2023]
Abstract
Identifying reliable biomarkers of aging is a major goal in geroscience. While the first generation of epigenetic biomarkers of aging were developed using chronological age as a surrogate for biological age, we hypothesized that incorporation of composite clinical measures of phenotypic age that capture differences in lifespan and healthspan may identify novel CpGs and facilitate the development of a more powerful epigenetic biomarker of aging. Using an innovative two-step process, we develop a new epigenetic biomarker of aging, DNAm PhenoAge, that strongly outperforms previous measures in regards to predictions for a variety of aging outcomes, including all-cause mortality, cancers, healthspan, physical functioning, and Alzheimer's disease. While this biomarker was developed using data from whole blood, it correlates strongly with age in every tissue and cell tested. Based on an in-depth transcriptional analysis in sorted cells, we find that increased epigenetic, relative to chronological age, is associated with increased activation of pro-inflammatory and interferon pathways, and decreased activation of transcriptional/translational machinery, DNA damage response, and mitochondrial signatures. Overall, this single epigenetic biomarker of aging is able to capture risks for an array of diverse outcomes across multiple tissues and cells, and provide insight into important pathways in aging.
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Affiliation(s)
- Morgan E. Levine
- Department of Human Genetics, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA 90095, USA
| | - Ake T. Lu
- Department of Human Genetics, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA 90095, USA
| | - Austin Quach
- Department of Human Genetics, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA 90095, USA
| | - Brian H. Chen
- Longitudinal Studies Section, Translational Gerontology Branch, National Institute on Aging, National Institutes of Health, USA. Baltimore, MD 21224, USA
| | | | | | - Lifang Hou
- Center for Population Epigenetics, Robert H. Lurie Comprehensive Cancer Center and Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL 60611, USA
| | - Andrea A. Baccarelli
- Laboratory of Environmental Epigenetics, Departments of Environmental Health Sciences and Epidemiology, Columbia University Mailman School of Public Health, New York, NY 10032, USA
| | - James D. Stewart
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC 27599, USA
| | - Yun Li
- Department of Genetics, Department of Biostatistics, Department of Computer Science, University of North Carolina, Chapel Hill, NC 27599, USA
| | - Eric A. Whitsel
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC 27599, USA
- Department of Medicine, School of Medicine, University of North Carolina, Chapel Hill, NC 27599, USA
| | - James G Wilson
- Department of Physiology and Biophysics, University of Mississippi Medical Center, Jackson, MS 39216, USA
| | - Alex P Reiner
- Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA
| | - Abraham Aviv
- Center of Human Development and Aging, New Jersey Medical School, Rutgers State University of New Jersey, Newark, NJ 07103, USA
| | - Kurt Lohman
- Center of Human Development and Aging, New Jersey Medical School, Rutgers State University of New Jersey, Newark, NJ 07103, USA
| | - Yongmei Liu
- Department of Epidemiology & Prevention, Division of Public Health Sciences, Wake Forrest School of Medicine, Winston-Salem, NC 27157, USA
| | - Luigi Ferrucci
- Longitudinal Studies Section, Translational Gerontology Branch, National Institute on Aging, National Institutes of Health, USA. Baltimore, MD 21224, USA
| | - 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
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47
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Binder AM, Corvalan C, Mericq V, Pereira A, Santos JL, Horvath S, Shepherd J, Michels KB. Faster ticking rate of the epigenetic clock is associated with faster pubertal development in girls. Epigenetics 2018; 13:85-94. [PMID: 29235933 DOI: 10.1080/15592294.2017.1414127] [Citation(s) in RCA: 71] [Impact Index Per Article: 11.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022] Open
Abstract
Epigenetic age is an indicator of biological aging, capturing the impact of environmental and behavioral influences across time on cellular function. Deviance between epigenetic age and chronological age (AgeAccel) is a predictor of health. Pubertal timing has similarly been associated with cancer risk and mortality rate among females. We examined the association between AgeAccel and pubertal timing and adolescent breast composition in the longitudinal Growth and Obesity Cohort Study. AgeAccel was estimated in whole blood using the Horvath method at breast Tanner 2 (B2) and 4 (B4). Total breast volume, absolute fibro-glandular volume (FGV), and %FGV were evaluated at B4 using dual X-ray absorptiometry. The impact of AgeAccel (mean: 0; SD: 3.78) across puberty on the time to breast development (thelarche), menarche, and pubertal tempo (thelarche to menarche) was estimated using accelerated failure time models; generalized estimating equations were used to evaluate associations with breast density. A five-year increase in average adolescent AgeAccel was associated with a significant decrease in time to menarche [hazard ratio (HR): 1.37; 95% confidence interval (CI): 1.04, 1.80] adjusting for birth weight, maternal pre-pregnancy body mass index, maternal height, maternal education, B2 height, fat percentage, and cell composition. AgeAccel displayed a stronger inverse association with pubertal tempo (HR: 1.48; 95% CI: 1.10, 1.99). A five-year increase in AgeAccel was associated with 5% greater %FGV, adjusting for B4 percent body fat, and maternal traits (95% CI: 1.01, 1.10). Our study provides unique insight into the influence of AgeAccel on pubertal development in girls, which may have implications for adult health.
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Affiliation(s)
- Alexandra M Binder
- a Department of Epidemiology , Fielding School of Public Health, University of California , Los Angeles , 650 Charles E Young Drive South, Los Angeles , CA 90095 , USA
| | - Camila Corvalan
- b Institute of Nutrition and Food Technology , University of Chile , Av el Libano 5524, Santiago , Chile
| | - Verónica Mericq
- c Institute of Maternal and Child Research , University of Chile , Santa Rosa 1234, 2° piso, Santiago , Chile
| | - Ana Pereira
- b Institute of Nutrition and Food Technology , University of Chile , Av el Libano 5524, Santiago , Chile
| | - José Luis Santos
- d Department of Nutrition , Diabetes and Metabolism, School of Medicine, Pontificia Universidad Católica de Chile , Av Libertador Bernardo O'Higgins 340, Santiago , Chile
| | - Steve Horvath
- e Department of Biostatistics , School of Public Health, and Department of Human Genetics, Gonda Research Center , David Geffen School of Medicine, University of California, Los Angeles , 695 Charles E Young Drive South, Los Angeles , CA 90095 , USA
| | - John Shepherd
- f Department of Radiology and Biomedical Imaging , University of California, San Francisco , 400 Parnassus Avenue, San Francisco , CA 94117 , USA
| | - Karin B Michels
- a Department of Epidemiology , Fielding School of Public Health, University of California , Los Angeles , 650 Charles E Young Drive South, Los Angeles , CA 90095 , USA
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48
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Lu AT, Xue L, Salfati EL, Chen BH, Ferrucci L, Levy D, Joehanes R, Murabito JM, Kiel DP, Tsai PC, Yet I, Bell JT, Mangino M, Tanaka T, McRae AF, Marioni RE, Visscher PM, Wray NR, Deary IJ, Levine ME, Quach A, Assimes T, Tsao PS, Absher D, Stewart JD, Li Y, Reiner AP, Hou L, Baccarelli AA, Whitsel EA, Aviv A, Cardona A, Day FR, Wareham NJ, Perry JRB, Ong KK, Raj K, Lunetta KL, Horvath S. GWAS of epigenetic aging rates in blood reveals a critical role for TERT. Nat Commun 2018; 9:387. [PMID: 29374233 PMCID: PMC5786029 DOI: 10.1038/s41467-017-02697-5] [Citation(s) in RCA: 117] [Impact Index Per Article: 19.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2017] [Accepted: 12/19/2017] [Indexed: 02/02/2023] Open
Abstract
DNA methylation age is an accurate biomarker of chronological age and predicts lifespan, but its underlying molecular mechanisms are unknown. In this genome-wide association study of 9907 individuals, we find gene variants mapping to five loci associated with intrinsic epigenetic age acceleration (IEAA) and gene variants in three loci associated with extrinsic epigenetic age acceleration (EEAA). Mendelian randomization analysis suggests causal influences of menarche and menopause on IEAA and lipoproteins on IEAA and EEAA. Variants associated with longer leukocyte telomere length (LTL) in the telomerase reverse transcriptase gene (TERT) paradoxically confer higher IEAA (P < 2.7 × 10-11). Causal modeling indicates TERT-specific and independent effects on LTL and IEAA. Experimental hTERT-expression in primary human fibroblasts engenders a linear increase in DNA methylation age with cell population doubling number. Together, these findings indicate a critical role for hTERT in regulating the epigenetic clock, in addition to its established role of compensating for cell replication-dependent telomere shortening.
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Affiliation(s)
- Ake T Lu
- Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, 90095, USA
| | - Luting Xue
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, 02118, USA
| | - Elias L Salfati
- Department of Medicine, Stanford University School of Medicine, Stanford, CA, 94305, USA
| | - Brian H Chen
- Intramural Research Program, National Institute on Aging, National Institutes of Health, Baltimore, MD, 21224, USA
- National Heart, Lung and Blood Institute, Bethesda, MD, 20824-0105, USA
| | - Luigi Ferrucci
- Intramural Research Program, National Institute on Aging, National Institutes of Health, Baltimore, MD, 21224, USA
| | - Daniel Levy
- National Heart, Lung and Blood Institute, Bethesda, MD, 20824-0105, USA
| | - Roby Joehanes
- National Heart, Lung and Blood Institute, Bethesda, MD, 20824-0105, USA
| | - Joanne M Murabito
- Department of Medicine, Section of General Medicine, Boston University School of Medicine, Boston, MA, 02118, USA
| | - Douglas P Kiel
- Institute for Aging Research, Hebrew SeniorLife, Beth Israel Deaconess Medical Centre, Harvard Medical School, Boston, MA, 02215, USA
| | - Pei-Chien Tsai
- Department of Twin Research and Genetic Epidemiology, Kings College London, London, SE1 7EH, UK
| | - Idil Yet
- Department of Twin Research and Genetic Epidemiology, Kings College London, London, SE1 7EH, UK
| | - Jordana T Bell
- Department of Twin Research and Genetic Epidemiology, Kings College London, London, SE1 7EH, UK
| | - Massimo Mangino
- Department of Twin Research and Genetic Epidemiology, Kings College London, London, SE1 7EH, UK
| | - Toshiko Tanaka
- Intramural Research Program, National Institute on Aging, National Institutes of Health, Baltimore, MD, 21224, USA
| | - Allan F McRae
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, 4072, QLD, Australia
- Queensland Brain Institute, The University of Queensland, Brisbane, 4072, QLD, Australia
| | - Riccardo E Marioni
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, 4072, QLD, Australia
- Centre for Cognitive Aging and Cognitive Epidemiology, Department of Psychology, University of Edinburgh, 7 George Square, Edinburgh, EH8 9JZ, UK
- Medical Genetics Section, Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU, UK
| | - Peter M Visscher
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, 4072, QLD, Australia
- Queensland Brain Institute, The University of Queensland, Brisbane, 4072, QLD, Australia
| | - Naomi R Wray
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, 4072, QLD, Australia
- Queensland Brain Institute, The University of Queensland, Brisbane, 4072, QLD, Australia
| | - Ian J Deary
- Centre for Cognitive Aging and Cognitive Epidemiology, Department of Psychology, University of Edinburgh, 7 George Square, Edinburgh, EH8 9JZ, UK
| | - Morgan E Levine
- Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, 90095, USA
| | - Austin Quach
- Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, 90095, USA
| | - Themistocles Assimes
- Department of Medicine, Stanford University School of Medicine, Stanford, CA, 94305, USA
| | - Philip S Tsao
- Department of Medicine, Stanford University School of Medicine, Stanford, CA, 94305, USA
- VA Palo Alto Health Care System, Palo Alto, CA, 94304, USA
| | - Devin Absher
- HudsonAlpha Institute for Biotechnology, Huntsville, AL, 35806, USA
| | - James D Stewart
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC, 27599, USA
| | - Yun Li
- Department of Genetics, School of Medicine, University of North Carolina, Chapel Hill, NC, 27599, USA
- Department of Biostatistics, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC, 27599, USA
| | - Alex P Reiner
- Fred Hutchinson Cancer Research Center Box 358080, WHI Clinical Coordinating Ctr/Public Health Sciences M3-A4, Seattle, WA, 98109, USA
| | - Lifang Hou
- Department of Preventive Medicine, Feinberg School of Medicine, Northwestern University Chicago, Evanston, IL, 60611, USA
- Center for Population Epigenetics, Robert H. Lurie Comprehensive Cancer Center, Feinberg School of Medicine, Northwestern University Chicago, Evanston, IL, 60611, USA
| | - Andrea A Baccarelli
- Laboratory of Environmental Epigenetics, Departments of Environmental Health Sciences Epidemiology, Columbia University Mailman School of Public Health, New York, NY, 10032, USA
| | - Eric A Whitsel
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC, 27599, USA
- Department of Medicine, School of Medicine, University of North Carolina, Chapel Hill, NC, 27516, USA
| | - Abraham Aviv
- The Center for Human Development and Aging, University of Medicine and Dentistry, New Jersey Medical School, Rutgers, Newark, NJ, 07103, USA
| | - Alexia Cardona
- Medical Research Council (MRC) Epidemiology Unit, University of Cambridge School of Clinical Medicine, Institute of Metabolic Science, Cambridge Biomedical Campus, Cambridge, CB2 0SL, UK
| | - Felix R Day
- Medical Research Council (MRC) Epidemiology Unit, University of Cambridge School of Clinical Medicine, Institute of Metabolic Science, Cambridge Biomedical Campus, Cambridge, CB2 0SL, UK
| | - Nicholas J Wareham
- Medical Research Council (MRC) Epidemiology Unit, University of Cambridge School of Clinical Medicine, Institute of Metabolic Science, Cambridge Biomedical Campus, Cambridge, CB2 0SL, UK
| | - John R B Perry
- Medical Research Council (MRC) Epidemiology Unit, University of Cambridge School of Clinical Medicine, Institute of Metabolic Science, Cambridge Biomedical Campus, Cambridge, CB2 0SL, UK
| | - Ken K Ong
- Medical Research Council (MRC) Epidemiology Unit, University of Cambridge School of Clinical Medicine, Institute of Metabolic Science, Cambridge Biomedical Campus, Cambridge, CB2 0SL, UK
- Department of Paediatrics, University of Cambridge School of Clinical Medicine, Cambridge Biomedical Campus, Cambridge, CB2 0SP, UK
| | - Kenneth Raj
- Radiation Effects Department, Centre for Radiation, Chemical and Environmental Hazards, Public Health England, Chilton, Didcot, Oxfordshire, OX11 0RQ, UK
| | - Kathryn L Lunetta
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, 02118, USA
| | - Steve Horvath
- Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, 90095, USA.
- Biostatistics, School of Public Health, University of California, Los Angeles, Los Angeles, CA, 90095, USA.
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49
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Dugué PA, Bassett JK, Joo JE, Jung CH, Ming Wong E, Moreno-Betancur M, Schmidt D, Makalic E, Li S, Severi G, Hodge AM, Buchanan DD, English DR, Hopper JL, Southey MC, Giles GG, Milne RL. DNA methylation-based biological aging and cancer risk and survival: Pooled analysis of seven prospective studies. Int J Cancer 2017; 142:1611-1619. [PMID: 29197076 DOI: 10.1002/ijc.31189] [Citation(s) in RCA: 116] [Impact Index Per Article: 16.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2017] [Revised: 11/03/2017] [Accepted: 11/21/2017] [Indexed: 12/23/2022]
Abstract
The association between aging and cancer is complex. Recent studies have developed measures of biological aging based on DNA methylation and called them "age acceleration." We aimed to assess the associations of age acceleration with risk of and survival from seven common cancers. Seven case-control studies of DNA methylation and colorectal, gastric, kidney, lung, prostate and urothelial cancer and B-cell lymphoma nested in the Melbourne Collaborative Cohort Study were conducted. Cancer cases, vital status and cause of death were ascertained through linkage with cancer and death registries. Conditional logistic regression and Cox models were used to estimate odds ratios (OR) and hazard ratios (HR) and 95% confidence intervals (CI) for associations of five age acceleration measures derived from the Human Methylation 450 K Beadchip assay with cancer risk (N = 3,216 cases) and survival (N = 1,726 deaths), respectively. Epigenetic aging was associated with increased cancer risk, ranging from 4% to 9% per five-year age acceleration for the 5 measures considered. Heterogeneity by study was observed, with stronger associations for risk of kidney cancer and B-cell lymphoma. An associated increased risk of death following cancer diagnosis ranged from 2% to 6% per five-year age acceleration, with no evidence of heterogeneity by cancer site. Cancer risk and mortality were increased by 15-30% for the fourth versus first quartile of age acceleration. DNA methylation-based measures of biological aging are associated with increased cancer risk and shorter cancer survival, independently of major health risk factors.
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Affiliation(s)
- Pierre-Antoine Dugué
- Cancer Epidemiology and Intelligence Division, Cancer Council Victoria, Melbourne, Victoria, Australia.,Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Parkville, Victoria, Australia
| | - Julie K Bassett
- Cancer Epidemiology and Intelligence Division, Cancer Council Victoria, Melbourne, Victoria, Australia
| | - JiHoon E Joo
- Genetic Epidemiology Laboratory, Department of Pathology, The University of Melbourne, Parkville, Victoria, Australia
| | - Chol-Hee Jung
- Melbourne Bioinformatics, The University of Melbourne, Parkville, Victoria, Australia
| | - Ee Ming Wong
- Genetic Epidemiology Laboratory, Department of Pathology, The University of Melbourne, Parkville, Victoria, Australia
| | - Margarita Moreno-Betancur
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Parkville, Victoria, Australia.,Clinical Epidemiology and Biostatistics Unit, Murdoch Children's Research Institute, Melbourne, Victoria, Australia
| | - Daniel Schmidt
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Parkville, Victoria, Australia
| | - Enes Makalic
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Parkville, Victoria, Australia
| | - Shuai Li
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Parkville, Victoria, Australia
| | - Gianluca Severi
- Cancer Epidemiology and Intelligence Division, Cancer Council Victoria, Melbourne, Victoria, Australia.,Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Parkville, Victoria, Australia.,Centre de Recherche en Épidémiologie et Santé des Populations (CESP, Inserm U1018), Université Paris-Saclay, UPS, USQ, Gustave Roussy, Villejuif, France.,Human Genetics Foundation (HuGeF), Turin, Italy
| | - Allison M Hodge
- Cancer Epidemiology and Intelligence Division, Cancer Council Victoria, Melbourne, Victoria, Australia.,Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Parkville, Victoria, Australia
| | - Daniel D Buchanan
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Parkville, Victoria, Australia.,Colorectal Oncogenomics Group, Genetic Epidemiology Laboratory, Department of Pathology, The University of Melbourne, Parkville, Victoria, Australia.,Genetic Medicine and Familial Cancer Centre, Royal Melbourne Hospital, Parkville, Victoria, Australia
| | - Dallas R English
- Cancer Epidemiology and Intelligence Division, Cancer Council Victoria, Melbourne, Victoria, Australia.,Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Parkville, Victoria, Australia
| | - John L Hopper
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Parkville, Victoria, Australia
| | - Melissa C Southey
- Cancer Epidemiology and Intelligence Division, Cancer Council Victoria, Melbourne, Victoria, Australia.,Genetic Epidemiology Laboratory, Department of Pathology, The University of Melbourne, Parkville, Victoria, Australia
| | - Graham G Giles
- Cancer Epidemiology and Intelligence Division, Cancer Council Victoria, Melbourne, Victoria, Australia.,Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Parkville, Victoria, Australia
| | - Roger L Milne
- Cancer Epidemiology and Intelligence Division, Cancer Council Victoria, Melbourne, Victoria, Australia.,Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Parkville, Victoria, Australia
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50
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Abstract
AbstractAnimal models of early postnatal mother–infant interactions have highlighted the importance of tactile contact for biobehavioral outcomes via the modification of DNA methylation (DNAm). The role of normative variation in contact in early human development has yet to be explored. In an effort to translate the animal work on tactile contact to humans, we applied a naturalistic daily diary strategy to assess the link between maternal contact with infants and epigenetic signatures in children 4–5 years later, with respect to multiple levels of child-level factors, including genetic variation and infant distress. We first investigated DNAm at four candidate genes: the glucocorticoid receptor gene, nuclear receptor subfamily 3, group C, member 1 (NR3C1), μ-opioid receptor M1 (OPRM1) and oxytocin receptor (OXTR; related to the neurobiology of social bonds), and brain-derived neurotrophic factor (BDNF; involved in postnatal plasticity). Although no candidate gene DNAm sites significantly associated with early postnatal contact, when we next examined DNAm across the genome, differentially methylated regions were identified between high and low contact groups. Using a different application of epigenomic information, we also quantified epigenetic age, and report that for infants who received low contact from caregivers, greater infant distress was associated with younger epigenetic age. These results suggested that early postnatal contact has lasting associations with child biology.
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