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Chen J, Moubadder L, Clausing ES, Kezios KL, Conneely KN, Hüls A, Baccarelli A, Factor-Litvak P, Cirrillo P, Shelton RC, Link BG, Suglia SF. Associations of childhood, adolescence, and midlife cognitive function with DNA methylation age acceleration in midlife. Aging (Albany NY) 2024; 16:9350-9368. [PMID: 38874516 PMCID: PMC11210249 DOI: 10.18632/aging.205943] [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: 10/23/2023] [Accepted: 04/25/2024] [Indexed: 06/15/2024]
Abstract
Prior studies showed increased age acceleration (AgeAccel) is associated with worse cognitive function among old adults. We examine the associations of childhood, adolescence and midlife cognition with AgeAccel based on DNA methylation (DNAm) in midlife. Data are from 359 participants who had cognition measured in childhood and adolescence in the Child Health and Development study, and had cognition, blood based DNAm measured during midlife in the Disparities study. Childhood cognition was measured by Raven's Progressive Matrices and Peabody Picture Vocabulary Test (PPVT). Adolescent cognition was measured only by PPVT. Midlife cognition included Wechsler Test of Adult Reading (WTAR), Verbal Fluency (VF), Digit Symbol (DS). AgeAccel measures including Horvath, Hannum, PhenoAge, GrimAge and DunedinPACE were calculated from DNAm. Linear regressions adjusted for potential confounders were utilized to examine the association between each cognitive measure in relation to each AgeAccel. There are no significant associations between childhood cognition and midlife AgeAccel. A 1-unit increase in adolescent PPVT, which measures crystalized intelligence, is associated with 0.048-year decrease of aging measured by GrimAge and this association is attenuated after adjustment for adult socioeconomic status. Midlife crystalized intelligence measure WTAR is negatively associated with PhenoAge and DunedinPACE, and midlife fluid intelligence measure (DS) is negatively associated with GrimAge, PhenoAge and DunedinPACE. AgeAccel is not associated with VF in midlife. In conclusion, our study showed the potential role of cognitive functions at younger ages in the process of biological aging. We also showed a potential relationship of both crystalized and fluid intelligence with aging acceleration.
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Affiliation(s)
- Junyu Chen
- Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, GA 30322, USA
| | - Leah Moubadder
- Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, GA 30322, USA
| | - Elizabeth S. Clausing
- Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, GA 30322, USA
- School of Global Integrative Studies, University of Nebraska, Lincoln, NE 68508, USA
| | - Katrina L. Kezios
- Department of Epidemiology, Mailman School of Public Health, Columbia University, New York, NY 10032, USA
| | - Karen N. Conneely
- Department of Human Genetics, School of Medicine, Emory University, Atlanta, GA 30322, USA
| | - Anke Hüls
- Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, GA 30322, USA
- Gangarosa Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, GA 30322, USA
| | - Andrea Baccarelli
- Department of Environmental Health Sciences, Mailman School of Public Health, Columbia University, New York, NY 10032, USA
| | - Pam Factor-Litvak
- Department of Epidemiology, Mailman School of Public Health, Columbia University, New York, NY 10032, USA
| | - Piera Cirrillo
- Child Health and Development Studies, Public Health Institute, Washington, DC 20024, USA
| | - Rachel C. Shelton
- Department of Sociomedical Sciences, Mailman School of Public Health, Columbia University, New York, NY 10032, USA
| | - Bruce G. Link
- Department of Sociology, University of California Riverside, Riverside, CA 92507, USA
| | - Shakira F. Suglia
- Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, GA 30322, USA
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Hishikawa A, Nishimura ES, Yoshimoto N, Nakamichi R, Hama EY, Ito W, Maruki T, Nagashima K, Shimizu-Hirota R, Takaishi H, Itoh H, Hayashi K. Predicting exacerbation of renal function by DNA methylation clock and DNA damage of urinary shedding cells: a pilot study. Sci Rep 2024; 14:11530. [PMID: 38773208 PMCID: PMC11109093 DOI: 10.1038/s41598-024-62405-4] [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: 05/16/2024] [Indexed: 05/23/2024] Open
Abstract
Recent reports have shown the feasibility of measuring biological age from DNA methylation levels in blood cells from specific regions identified by machine learning, collectively known as the epigenetic clock or DNA methylation clock. While extensive research has explored the association of the DNA methylation clock with cardiovascular diseases, cancer, and Alzheimer's disease, its relationship with kidney diseases remains largely unexplored. In particular, it is unclear whether the DNA methylation clock could serve as a predictor of worsening kidney function. In this pilot study involving 20 subjects, we investigated the association between the DNA methylation clock and subsequent deterioration of renal function. Additionally, we noninvasively evaluated DNA damage in urinary shedding cells using a previously reported method to examine the correlation with the DNA methylation clock and worsening kidney function. Our findings revealed that patients with an accelerated DNA methylation clock exhibited increased DNA damage in urinary shedding cells, along with a higher rate of eGFR decline. Moreover, in cases of advanced CKD (G4-5), the DNA damage in urinary shedding cells was significantly increased, highlighting the interplay between elevated DNA damage and eGFR decline. This study suggests the potential role of the DNA methylation clock and urinary DNA damage as predictive markers for the progression of chronic kidney disease.
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Affiliation(s)
- Akihito Hishikawa
- Division of Nephrology, Endocrinology and Metabolism, Department of Internal Medicine, Keio University School of Medicine, 35 Shinanomachi, Shinjuku-Ku, Tokyo, 160-8582, Japan.
| | - Erina Sugita Nishimura
- Division of Nephrology, Endocrinology and Metabolism, Department of Internal Medicine, Keio University School of Medicine, 35 Shinanomachi, Shinjuku-Ku, Tokyo, 160-8582, Japan
| | - Norifumi Yoshimoto
- Division of Nephrology, Endocrinology and Metabolism, Department of Internal Medicine, Keio University School of Medicine, 35 Shinanomachi, Shinjuku-Ku, Tokyo, 160-8582, Japan
| | - Ran Nakamichi
- Division of Nephrology, Endocrinology and Metabolism, Department of Internal Medicine, Keio University School of Medicine, 35 Shinanomachi, Shinjuku-Ku, Tokyo, 160-8582, Japan
| | - Eriko Yoshida Hama
- Division of Nephrology, Endocrinology and Metabolism, Department of Internal Medicine, Keio University School of Medicine, 35 Shinanomachi, Shinjuku-Ku, Tokyo, 160-8582, Japan
| | - Wataru Ito
- Division of Nephrology, Endocrinology and Metabolism, Department of Internal Medicine, Keio University School of Medicine, 35 Shinanomachi, Shinjuku-Ku, Tokyo, 160-8582, Japan
| | - Tomomi Maruki
- Division of Nephrology, Endocrinology and Metabolism, Department of Internal Medicine, Keio University School of Medicine, 35 Shinanomachi, Shinjuku-Ku, Tokyo, 160-8582, Japan
| | - Kengo Nagashima
- Biostatistics Unit, Clinical and Translational Research Center, Keio University School of Medicine, Tokyo, Japan
| | - Ryoko Shimizu-Hirota
- Center for Preventive Medicine, Keio University School of Medicine, Tokyo, Japan
| | - Hiromasa Takaishi
- Center for Preventive Medicine, Keio University School of Medicine, Tokyo, Japan
| | - Hiroshi Itoh
- Center for Preventive Medicine, Keio University School of Medicine, Tokyo, Japan
| | - Kaori Hayashi
- Division of Nephrology, Endocrinology and Metabolism, Department of Internal Medicine, Keio University School of Medicine, 35 Shinanomachi, Shinjuku-Ku, Tokyo, 160-8582, Japan.
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Weston WC, Bind MA, Cascio WE, Devlin RB, Diaz-Sanchez D, Ward-Caviness CK. Accelerated aging and altered subclinical response to ozone exposure in young, healthy adults. ENVIRONMENTAL EPIGENETICS 2024; 10:dvae007. [PMID: 38846065 PMCID: PMC11155485 DOI: 10.1093/eep/dvae007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/02/2023] [Revised: 03/11/2024] [Accepted: 05/02/2024] [Indexed: 06/09/2024]
Abstract
Ozone exposure induces a myriad of adverse cardiopulmonary outcomes in humans. Although advanced age and chronic disease are factors that may exacerbate a person's negative response to ozone exposure, there are no molecular biomarkers of susceptibility. Here, we examine whether epigenetic age acceleration (EAA) is associated with responsiveness to short-term ozone exposure. Using data from a crossover-controlled exposure study (n = 17), we examined whether EAA, as measured in lung epithelial cells collected 24 h after clean air exposure, modifies the observed effect of ozone on autonomic function, cardiac electrophysiology, hemostasis, pulmonary function, and inflammation. EAA was assessed in lung epithelial cells extracted from bronchoalveolar lavage fluids, using the pan-tissue aging clock. We used two analytic approaches: (i) median regression to estimate the association between EAA and the estimated risk difference for subclinical responses to ozone and (ii) a block randomization approach to estimate EAA's effect modification of subclinical responses. For both approaches, we calculated Fisher-exact P-values, allowing us to bypass large sample size assumptions. In median regression analyses, accelerated epigenetic age modified associations between ozone and heart rate-corrected QT interval (QTc) ([Formula: see text]= 0.12, P-value = 0.007) and between ozone and C-reactive protein ([Formula: see text] = -0.18, P = 0.069). During block randomization, the directions of association remained consistent for QTc and C-reactive protein; however, the P-values weakened. Block randomization also revealed that responsiveness of plasminogen activator inhibitor-1 (PAI-1) to ozone exposure was modified by accelerated epigenetic aging (PAI-1 difference between accelerated aging-defined block groups = -0.54, P-value = 0.039). In conclusion, EAA is a potential biomarker for individuals with increased susceptibility to ozone exposure even among young, healthy adults.
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Affiliation(s)
- William C Weston
- Center for Public Health and Environmental Assessment, US Environmental Protection Agency, Chapel Hill, NC 27514, USA
- US Department of Energy, Oak Ridge Institute for Science and Education, Oak Ridge, TN 37830, USA
| | - Marie Abèle Bind
- Biostatistics Center, Massachusetts General Hospital, Boston, MA 02114, USA
- Department of Medicine, Harvard Medical School, Boston, MA 02115, USA
| | - Wayne E Cascio
- Center for Public Health and Environmental Assessment, US Environmental Protection Agency, Chapel Hill, NC 27514, USA
| | - Robert B Devlin
- Center for Public Health and Environmental Assessment, US Environmental Protection Agency, Chapel Hill, NC 27514, USA
| | - David Diaz-Sanchez
- Center for Public Health and Environmental Assessment, US Environmental Protection Agency, Chapel Hill, NC 27514, USA
| | - Cavin K Ward-Caviness
- Center for Public Health and Environmental Assessment, US Environmental Protection Agency, Chapel Hill, NC 27514, USA
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Schmidt S. Speeding Up Time: New Urinary Peptide Clock Associates Greater Air Pollution Exposures with Faster Biological Aging. ENVIRONMENTAL HEALTH PERSPECTIVES 2024; 132:44001. [PMID: 38568857 PMCID: PMC10990112 DOI: 10.1289/ehp14528] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/21/2023] [Accepted: 01/26/2024] [Indexed: 04/05/2024]
Abstract
A study in Belgium supports earlier findings on associations between higher air pollution exposures and markers of faster biological aging, this time by using urinary peptide levels instead of DNA-based markers.
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Chiu KC, Hsieh MS, Huang YT, Liu CY. Exposure to ambient temperature and heat index in relation to DNA methylation age: A population-based study in Taiwan. ENVIRONMENT INTERNATIONAL 2024; 186:108581. [PMID: 38507934 DOI: 10.1016/j.envint.2024.108581] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/01/2023] [Revised: 03/13/2024] [Accepted: 03/14/2024] [Indexed: 03/22/2024]
Abstract
BACKGROUND Climate change caused an increase in ambient temperature in the past decades. Exposure to high ambient temperature could result in biological aging, but relevant studies in a warm environment were lacking. We aimed to study the exposure effects of ambient temperature and heat index (HI) in relation to age acceleration in Taiwan, a subtropical island in Asia. METHODS The study included 2,084 participants from Taiwan Biobank. Daily temperature and relative humidity data were collected from weather monitoring stations. Individual residential exposure was estimated by ordinary kriging. Moving averages of ambient temperature and HI from 1 to 180 days prior to enrollment were calculated to estimate the exposure effects in multiple time periods. Age acceleration was defined as the difference between DNA methylation age and chronological age. DNA methylation age was calculated by the Horvath's, Hannum's, Weidner's, ELOVL2, FHL2, phenotypic (Pheno), Skin & blood, and GrimAge2 (Grim2) DNA methylation age algorithms. Multivariable linear regression models, generalized additive models (GAMs), and distributed lag non-linear models (DLNMs) were conducted to estimate the effects of ambient temperature and HI exposures in relation to age acceleration. RESULTS Exposure to high ambient temperature and HI were associated with increased age acceleration, and the associations were stronger in prolonged exposure. The heat stress days with maximum HI in caution (80-90°F), extreme caution (90-103°F), danger (103-124°F), and extreme danger (>124°F) were also associated with increased age acceleration, especially in the extreme danger days. Each extreme danger day was associated with 571.38 (95 % CI: 42.63-1100.13), 528.02 (95 % CI: 36.16-1019.87), 43.9 (95 % CI: 0.28-87.52), 16.82 (95 % CI: 2.36-31.28) and 15.52 (95 % CI: 2.17-28.88) days increase in the Horvath's, Hannum's, Weidner's, Pheno, and Skin & blood age acceleration, respectively. CONCLUSION High ambient temperature and HI may accelerate biological aging.
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Affiliation(s)
- Kuan-Chih Chiu
- Institute of Environmental and Occupational Health Sciences, College of Public Health, National Taiwan University, Taipei, Taiwan
| | - Ming-Shun Hsieh
- Department of Emergency Medicine, Taipei Veterans General Hospital, Taoyuan Branch, Taoyuan, Taiwan; Department of Emergency Medicine, Taipei Veterans General Hospital, Taipei, Taiwan; School of Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan
| | - Yen-Tsung Huang
- Institute of Statistical Science, Academia Sinica, Taipei, Taiwan; Department of Mathematics, College of Science, National Taiwan University, Taipei, Taiwan; Institute of Epidemiology and Preventive Medicine, College of Public Health, National Taiwan University, Taipei, Taiwan
| | - Chen-Yu Liu
- Institute of Environmental and Occupational Health Sciences, College of Public Health, National Taiwan University, Taipei, Taiwan; Department of Public Health, College of Public Health, National Taiwan University, Taipei, Taiwan; Population Health Research Center, National Taiwan University, Taipei, Taiwan.
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Laubach ZM, Bozack A, Aris IM, Slopen N, Tiemeier H, Hivert MF, Cardenas A, Perng W. Maternal prenatal social experiences and offspring epigenetic age acceleration from birth to mid-childhood. Ann Epidemiol 2024; 90:28-34. [PMID: 37839726 PMCID: PMC10842218 DOI: 10.1016/j.annepidem.2023.10.003] [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: 07/12/2023] [Revised: 09/27/2023] [Accepted: 10/10/2023] [Indexed: 10/17/2023]
Abstract
PURPOSE Investigate associations of maternal social experiences with offspring epigenetic age acceleration (EAA) from birth through mid-childhood among 205 mother-offspring dyads of minoritized racial and ethnic groups. METHODS We used linear regression to examine associations of maternal experiences of racial bias or discrimination (0 = none, 1-2 = intermediate, or 3+ = high), social support (tertile 1 = low, 2 = intermediate, 3 = high), and socioeconomic status index (tertile 1 = low, 2 = intermediate, 3 = high) during the prenatal period with offspring EAA according to Horvath's Pan-Tissue, Horvath's Skin and Blood, and Intrinsic EAA clocks at birth, 3 years, and 7 years. RESULTS In comparison to children of women who did not experience any racial bias or discrimination, those whose mothers reported highest levels of racial bias or discrimination had lower Pan-Tissue clock EAA in early (-0.50 years; 90% CI: -0.91, -0.09) and mid-childhood (-0.75 years; -1.41, -0.08). We observed similar associations for the Skin and Blood clock and Intrinsic EAA. Maternal experiences of discrimination were not associated with Pan-Tissue EAA at birth. Neither maternal social support nor socioeconomic status predicted offspring EAA. CONCLUSIONS Children whose mothers experienced higher racial bias or discrimination exhibited slower EAA. Future studies are warranted to confirm these findings and establish associations of early-life EAA with long-term health outcomes.
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Affiliation(s)
- Zachary M Laubach
- Department of Ecology and Evolutionary Biology (EBIO), University of Colorado Boulder
| | - Anne Bozack
- Department of Epidemiology and Population Health, Stanford University, Stanford, CA
| | - Izzuddin M Aris
- Division of Chronic Disease Research Across the Lifecourse (CORAL), Department of Population Medicine, Harvard Medical School, Boston, MA
| | - Natalie Slopen
- Department of Social and Behavioral Sciences, Harvard T.H. Chan School of Public Health, Boston, MA
| | - Henning Tiemeier
- Department of Social and Behavioral Sciences, Harvard T.H. Chan School of Public Health, Boston, MA
| | - Marie-France Hivert
- Division of Chronic Disease Research Across the Lifecourse (CORAL), Department of Population Medicine, Harvard Medical School, Boston, MA; Diabetes Unit, Massachusetts General Hospital, Boston, MA
| | - Andres Cardenas
- Department of Epidemiology and Population Health, Stanford University, Stanford, CA
| | - Wei Perng
- Lifecourse Epidemiology of Adiposity and Diabetes (LEAD Center), Department of Epidemiology, Colorado School of Public Health, Aurora, CO.
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Tournoy TK, Moons P, Daelman B, De Backer J. Biological Age in Congenital Heart Disease-Exploring the Ticking Clock. J Cardiovasc Dev Dis 2023; 10:492. [PMID: 38132660 PMCID: PMC10743752 DOI: 10.3390/jcdd10120492] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2023] [Revised: 12/08/2023] [Accepted: 12/08/2023] [Indexed: 12/23/2023] Open
Abstract
Over the past 50 years, there has been a major shift in age distribution of patients with congenital heart disease (CHD) thanks to significant advancements in medical and surgical treatment. Patients with CHD are, however, never cured and face unique challenges throughout their lives. In this review, we discuss the growing data suggesting accelerated aging in this population. Adults with CHD are more often and at a younger age confronted with age-related cardiovascular complications such as heart failure, arrhythmia, and coronary artery disease. These can be related to the original birth defect, complications of correction, or any residual defects. In addition, and less deductively, more systemic age-related complications are seen earlier, such as renal dysfunction, lung disease, dementia, stroke, and cancer. The occurrence of these complications at a younger age makes it imperative to further map out the aging process in patients across the spectrum of CHD. We review potential feasible markers to determine biological age and provide an overview of the current data. We provide evidence for an unmet need to further examine the aging paradigm as this stresses the higher need for care and follow-up in this unique, newly aging population. We end by exploring potential approaches to improve lifespan care.
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Affiliation(s)
- Tijs K. Tournoy
- Department of Cardiology, Ghent University Hospital, 9000 Ghent, Belgium;
| | - Philip Moons
- KU Leuven Department of Public Health and Primary Care, University of Leuven, 3000 Leuven, Belgium
- Institute of Health and Care Sciences, University of Gothenburg, 405 30 Gothenburg, Sweden
- Department of Pediatrics and Child Health, University of Cape Town, Cape Town 7700, South Africa
| | - Bo Daelman
- KU Leuven Department of Public Health and Primary Care, University of Leuven, 3000 Leuven, Belgium
| | - Julie De Backer
- Department of Cardiology, Ghent University Hospital, 9000 Ghent, Belgium;
- Center for Medical Genetics, Ghent University Hospital, 9000 Ghent, Belgium
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Jackson P, Kempf MC, Goodin BR, A. Hidalgo B, Aroke EN. Neighborhood Environment and Epigenetic Age: A Scoping Review. West J Nurs Res 2023; 45:1139-1149. [PMID: 37902222 PMCID: PMC10748459 DOI: 10.1177/01939459231208304] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/31/2023]
Abstract
BACKGROUND Interest in how the neighborhood environment impacts age-related health conditions has been increasing for decades. Epigenetic changes are environmentally derived modifications to the genome that alter the way genes function-thus altering health status. Epigenetic age, a biomarker for biological age, has been shown to be a useful predictor of several age-related health conditions. Consequently, its relation to the neighborhood environment has been the focus of a growing body of literature. OBJECTIVE We aimed to describe the scope of the evidence on the relationship between neighborhood environmental characteristics and epigenetic age. METHODS Using scoping review following methods established by Arksey and O'Malley, we first defined our research questions and searched the literature in PubMed, PsycINFO, and EMBASE. Next, we selected the literature to be included, and finally, we analyzed and summarized the information. RESULTS Nine articles met the inclusion criteria. Most studies examined deprivation as the neighborhood characteristic of interest. While all studies were observational in design, the articles included diverse participants, including men and women, adults and children, and multiple ethnicities. Results demonstrated a relationship between the neighborhood environment and epigenetic age, whether the characteristic of interest is socioeconomic or physical. CONCLUSIONS Overall, studies concluded there was a relationship between neighborhood characteristics and epigenetic age, whether the characteristic of interest was socioeconomic or physical. However, findings varied based on how the neighborhood characteristic and/or epigenetic age was measured. Furthermore, a paucity of investigations on physical characteristics was noticeable and warrants increased attention.
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Affiliation(s)
- Pamela Jackson
- School of Public Health, University of Alabama at Birmingham, Birmingham, AL, USA
| | | | - Burel R. Goodin
- Department of Anesthesiology, Washington University Pain Center, Washington University School of Medicine in St. Louis, St. Louis, MO, USA
| | - Bertha A. Hidalgo
- School of Public Health, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Edwin N. Aroke
- School of Nursing, University of Alabama at Birmingham, Birmingham, AL, USA
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Jia M, Agudelo Garcia PA, Ovando‐Ricardez JA, Tabib T, Bittar HT, Lafyatis RA, Mora AL, Benos PV, Rojas M. Transcriptional changes of the aging lung. Aging Cell 2023; 22:e13969. [PMID: 37706427 PMCID: PMC10577555 DOI: 10.1111/acel.13969] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2023] [Revised: 08/07/2023] [Accepted: 08/08/2023] [Indexed: 09/15/2023] Open
Abstract
Aging is a natural process associated with declined organ function and higher susceptibility to developing chronic diseases. A systemic single-cell type-based study provides a unique opportunity to understand the mechanisms behind age-related pathologies. Here, we use single-cell gene expression analysis comparing healthy young and aged human lungs from nonsmoker donors to investigate age-related transcriptional changes. Our data suggest that aging has a heterogenous effect on lung cells, as some populations are more transcriptionally dynamic while others remain stable in aged individuals. We found that monocytes and alveolar macrophages were the most transcriptionally affected populations. These changes were related to inflammation and regulation of the immune response. Additionally, we calculated the LungAge score, which reveals the diversity of lung cell types during aging. Changes in DNA damage repair, fatty acid metabolism, and inflammation are essential for age prediction. Finally, we quantified the senescence score in aged lungs and found that the more biased cells toward senescence are immune and progenitor cells. Our study provides a comprehensive and systemic analysis of the molecular signatures of lung aging. Our LungAge signature can be used to predict molecular signatures of physiological aging and to detect common signatures of age-related lung diseases.
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Affiliation(s)
- Minxue Jia
- Department of Computational and Systems BiologyUniversity of Pittsburgh School of MedicinePittsburghPennsylvaniaUSA
- Joint Carnegie Mellon ‐ University of Pittsburgh Computational Biology Ph.D. ProgramPittsburghPennsylvaniaUSA
| | | | | | - Tracy Tabib
- Division of Rheumatology and Clinical Immunology, Department of MedicineUniversity of Pittsburgh School of MedicinePittsburghPennsylvaniaUSA
| | - Humberto T. Bittar
- Division of Rheumatology and Clinical Immunology, Department of MedicineUniversity of Pittsburgh School of MedicinePittsburghPennsylvaniaUSA
| | - Robert A. Lafyatis
- Division of Rheumatology and Clinical Immunology, Department of MedicineUniversity of Pittsburgh School of MedicinePittsburghPennsylvaniaUSA
| | - Ana L. Mora
- Department of Internal MedicineOhio State UniversityColumbusOhioUSA
| | - Panayiotis V. Benos
- Department of Computational and Systems BiologyUniversity of Pittsburgh School of MedicinePittsburghPennsylvaniaUSA
- Joint Carnegie Mellon ‐ University of Pittsburgh Computational Biology Ph.D. ProgramPittsburghPennsylvaniaUSA
- Department of EpidemiologyUniversity of FloridaGainesvilleFloridaUSA
| | - Mauricio Rojas
- Department of Internal MedicineOhio State UniversityColumbusOhioUSA
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Korous KM, Surachman A, Rogers CR, Cuevas AG. Parental education and epigenetic aging in middle-aged and older adults in the United States: A life course perspective. Soc Sci Med 2023; 333:116173. [PMID: 37595421 PMCID: PMC10530379 DOI: 10.1016/j.socscimed.2023.116173] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2022] [Revised: 08/10/2023] [Accepted: 08/11/2023] [Indexed: 08/20/2023]
Abstract
Epigenetic aging is one plausible mechanism by which socioeconomic status (SES) contributes to disparities in morbidity and mortality. Although the association between SES and epigenetic aging is well documented, the role of parental education into adulthood remains understudied. We examined (1) if parental education was independently associated with epigenetic aging, (2) whether upward educational mobility buffered this association, and (3) if the benefit of parental education was differentiated by race/ethnicity. Secondary data analysis of a subsample (n = 3875) of Non-Hispanic [NH] Black, Hispanic, NH White, and NH other race participants from the Venous Blood Study within Health and Retirement Study were examined. Thirteen clocks based on DNA methylation of cytosine-phosphate-guanine sites were used to calculate epigenetic aging. Participants' education (personal) and their report of their respective parent's education (parental; mother's and/or father's) were included as independent variables; several potential confounders were also included. Direct associations and interactions between parental and personal education were estimated via survey-weighted generalized linear models; marginal means for epigenetic aging were estimated and contrasts were made between the education subcategories. Analyses were also stratified by race/ethnicity. Our results showed that higher parental education was independently associated with slower epigenetic aging among four clocks, whereas higher personal education magnified this association among four different epigenetic clocks. Participants with the lowest parental and personal education had higher marginal means (i.e., accelerated aging) compared to participants with the highest parental and personal education, and there was little evidence of upward mobility. These associations were more frequently observed among NH White participants, whereas fewer were observed for Hispanic and NH Black participants. Overall, our findings support that early-life circumstances may be biologically embedded through epigenetic aging, which may also limit the biological benefits associated with one's own education.
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Affiliation(s)
- Kevin M Korous
- Institute for Health & Equity, Medical College of Wisconsin, Milwaukee, WI, USA
| | - Agus Surachman
- Department of Epidemiology and Biostatistics, Dornsife School of Public Health, Drexel University, Philadelphia, PA, USA
| | - Charles R Rogers
- Institute for Health & Equity, Medical College of Wisconsin, Milwaukee, WI, USA
| | - Adolfo G Cuevas
- Social and Behavioral Sciences Department, School of Global Public Health, New York University, New York, NY, USA.
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Zhang ZZ, Moeckel C, Mustafa M, Pham H, Olson AE, Mehta D, Dorn LD, Engeland CG, Shenk CE. The association of epigenetic age acceleration and depressive and anxiety symptom severity among children recently exposed to substantiated maltreatment. J Psychiatr Res 2023; 165:7-13. [PMID: 37441927 PMCID: PMC10529086 DOI: 10.1016/j.jpsychires.2023.07.007] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/05/2023] [Revised: 07/06/2023] [Accepted: 07/07/2023] [Indexed: 07/15/2023]
Abstract
Child maltreatment is a major risk factor for both depressive and anxiety disorders. However, many children exposed to maltreatment never meet diagnostic threshold for either disorder while experiencing only transitory symptoms post-exposure. Recent research suggests DNA methylation adds predictive value in explaining variation in the onset and course of multiple psychiatric disorders following exposure to child maltreatment. Epigenetic age acceleration (EAA), the biological aging of cells not attributable to chronological aging, is a stress-sensitive biomarker capturing genome-wide variation in DNA methylation with the potential to identify children who have been maltreated at greatest risk for depressive and anxiety disorders. The current study examined two EAA clocks appropriate for the pediatric population, the Horvath and Pediatric Buccal Epigenetic (PedBE) clocks, and their associations with depressive and anxiety symptom severity following child maltreatment. Children (N = 71) 8-15 years of age, all of whom were exposed to substantiated child maltreatment in the 12 months prior to study entry, were enrolled. Risk modeling adjusting for several confounders revealed that EAA estimated via the Horvath clock was significantly associated with more severe depressive and anxiety symptoms. The PedBE clock was not associated with either depressive or anxiety symptom severity. Sensitivity analyses demonstrated that EAA via the Horvath clock robustly predicted depressive and anxiety symptom severity across multiple modeling scenarios. Our findings advance existing research suggesting EAA, as estimated with the Horvath clock, may be a promising biomarker for identifying children at greatest risk for more severe depressive and anxiety symptoms following maltreatment.
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Affiliation(s)
- Zhenyu Z Zhang
- Department of Psychology, The Pennsylvania State University, University Park, PA, USA.
| | - Camille Moeckel
- The Pennsylvania State University College of Medicine, Hershey, PA, USA.
| | - Manal Mustafa
- The Pennsylvania State University College of Medicine, Hershey, PA, USA.
| | - Hung Pham
- The Child Study Center, Yale University, New Haven, CT, USA.
| | - Anneke E Olson
- Department of Human Development and Family Studies, The Pennsylvania State University, University Park, PA, USA.
| | - Divya Mehta
- Centre for Genomics and Personalised Health, Queensland University of Technology, Brisbane, Queensland, Australia; School of Biomedical Sciences, Queensland University of Technology, Brisbane, Queensland, Australia.
| | - Lorah D Dorn
- Ross and Carol Nese College of Nursing, The Pennsylvania State University, University Park, PA, USA.
| | - Christopher G Engeland
- Ross and Carol Nese College of Nursing, The Pennsylvania State University, University Park, PA, USA; Department of Biobehavioral Health, The Pennsylvania State University, University Park, PA, USA.
| | - Chad E Shenk
- The Pennsylvania State University College of Medicine, Hershey, PA, USA; Department of Human Development and Family Studies, The Pennsylvania State University, University Park, PA, USA.
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12
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Maltby V, Xavier A, Ewing E, Campagna MP, Sampangi S, Scott RJ, Butzkueven H, Jokubaitis V, Kular L, Bos S, Slee M, van der Mei IA, Taylor BV, Ponsonby AL, Jagodic M, Lea R, Lechner-Scott J. Evaluation of Cell-Specific Epigenetic Age Acceleration in People With Multiple Sclerosis. Neurology 2023; 101:e679-e689. [PMID: 37541839 PMCID: PMC10437016 DOI: 10.1212/wnl.0000000000207489] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2022] [Accepted: 04/20/2023] [Indexed: 08/06/2023] Open
Abstract
BACKGROUND AND OBJECTIVES In multiple sclerosis (MS), accelerated aging of the immune system (immunosenescence) may be associated with disease onset or drive progression. DNA methylation (DNAm) is an epigenetic factor that varies among lymphocyte subtypes, and cell-specific DNAm is associated with MS. DNAm varies across the life span and can be used to accurately estimate biological age acceleration, which has been linked to a range of morbidities. The objective of this study was to test for cell-specific epigenetic age acceleration (EAA) in people with MS. METHODS This was a case-control study of EAA using existing DNAm data from several independent previously published studies. Data were included if .idat files from Illumina 450K or EPIC arrays were available for both a case with MS and an age-matched and sex-matched control, from the same study. Multifactor statistical modeling was performed to assess the primary outcome of EAA. We explored the relationship of EAA and MS, including interaction terms to identify immune cell-specific effects. Cell-sorted DNA methylation data from 3 independent datasets were used to validate findings. RESULTS We used whole blood DNA methylation data from 583 cases with MS and 643 non-MS controls to calculate EAA using the GrimAge algorithm. The MS group exhibited an increased EAA compared with controls (approximately 9 mths, 95% CI 3.6-14.4), p = 0.001). Statistical deconvolution showed that EAA is associated with MS in a B cell-dependent manner (β int = 1.7, 95% CI 0.3-2.8), p = 0.002), irrespective of B-cell proportions. Validation analysis using 3 independent datasets enriched for B cells showed an EAA increase of 5.1 years in cases with MS compared with that in controls (95% CI 2.8-7.4, p = 5.5 × 10-5). By comparison, there was no EAA difference in MS in a T cell-enriched dataset. We found that EAA was attributed to the DNAm surrogates for Beta-2-microglobulin (difference = 47,546, 95% CI 10,067-85,026; p = 7.2 × 10-5), and smoking pack-years (difference = 8.1, 95% CI 1.9-14.2, p = 0.002). DISCUSSION This study provides compelling evidence that B cells exhibit marked EAA in MS and supports the hypothesis that premature B-cell immune senescence plays a role in MS. Future MS studies should focus on age-related molecular mechanisms in B cells.
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Affiliation(s)
- Vicki Maltby
- From the School of Medicine and Public Health (V.M., R.L., J.L.-S.), University of Newcastle, University Drive, Callaghan; Immune Health Program (V.M., A.X., J.L.-S.), Hunter Medical Research Institute; Department of Neurology (V.M., J.L.-S.), John Hunter Hospital, New Lambton Heights; School of Biomedical Sciences and Pharmacy (A.X.), University of Newcastle, University Drive, Callaghan, Australia; Department of Clinical Neuroscience (E.E., L.K., M.J.), Karolinska Institutet, Center for Molecular Medicine, Karolinska University Hospital, Stockholm, Sweden; Department of Neuroscience (M.-P.C., S.S., H.B., V.J.), Central Clinical School, Monash University, Victoria; Division of Molecular Genetics (R.J.S.), Pathology North, John Hunter Hospital, New Lambton Heights; MSBase Foundation (H.B.), Melbourne, Australia; Institute of Clinical Medicine (S.B.), University of Oslo,; Department of Neurology (S.B.), Oslo University Hospital, Norway; Flinders University (M.S.), Adelaide; Menzies Institute for Medical Research (I.A.M., B.V.T.), University of Tasmania, Hobart; Florey Institute of Neuroscience and Mental Health (A.-L.P.), The University of Melbourne; Centre of Epidemiology and Biostatistics (A.-L.P.), School of Population and Global Health, University of Melbourne; Murdoch Children's Research Institute (A.-L.P.), Royal Children's Hospital, Melbourne; and Centre for Genomics and Personalized Health (R.L.), School of Biomedical Science, Queensland University of Technology, Kelvin Grove, Australia
| | - Alexandre Xavier
- From the School of Medicine and Public Health (V.M., R.L., J.L.-S.), University of Newcastle, University Drive, Callaghan; Immune Health Program (V.M., A.X., J.L.-S.), Hunter Medical Research Institute; Department of Neurology (V.M., J.L.-S.), John Hunter Hospital, New Lambton Heights; School of Biomedical Sciences and Pharmacy (A.X.), University of Newcastle, University Drive, Callaghan, Australia; Department of Clinical Neuroscience (E.E., L.K., M.J.), Karolinska Institutet, Center for Molecular Medicine, Karolinska University Hospital, Stockholm, Sweden; Department of Neuroscience (M.-P.C., S.S., H.B., V.J.), Central Clinical School, Monash University, Victoria; Division of Molecular Genetics (R.J.S.), Pathology North, John Hunter Hospital, New Lambton Heights; MSBase Foundation (H.B.), Melbourne, Australia; Institute of Clinical Medicine (S.B.), University of Oslo,; Department of Neurology (S.B.), Oslo University Hospital, Norway; Flinders University (M.S.), Adelaide; Menzies Institute for Medical Research (I.A.M., B.V.T.), University of Tasmania, Hobart; Florey Institute of Neuroscience and Mental Health (A.-L.P.), The University of Melbourne; Centre of Epidemiology and Biostatistics (A.-L.P.), School of Population and Global Health, University of Melbourne; Murdoch Children's Research Institute (A.-L.P.), Royal Children's Hospital, Melbourne; and Centre for Genomics and Personalized Health (R.L.), School of Biomedical Science, Queensland University of Technology, Kelvin Grove, Australia
| | - Ewoud Ewing
- From the School of Medicine and Public Health (V.M., R.L., J.L.-S.), University of Newcastle, University Drive, Callaghan; Immune Health Program (V.M., A.X., J.L.-S.), Hunter Medical Research Institute; Department of Neurology (V.M., J.L.-S.), John Hunter Hospital, New Lambton Heights; School of Biomedical Sciences and Pharmacy (A.X.), University of Newcastle, University Drive, Callaghan, Australia; Department of Clinical Neuroscience (E.E., L.K., M.J.), Karolinska Institutet, Center for Molecular Medicine, Karolinska University Hospital, Stockholm, Sweden; Department of Neuroscience (M.-P.C., S.S., H.B., V.J.), Central Clinical School, Monash University, Victoria; Division of Molecular Genetics (R.J.S.), Pathology North, John Hunter Hospital, New Lambton Heights; MSBase Foundation (H.B.), Melbourne, Australia; Institute of Clinical Medicine (S.B.), University of Oslo,; Department of Neurology (S.B.), Oslo University Hospital, Norway; Flinders University (M.S.), Adelaide; Menzies Institute for Medical Research (I.A.M., B.V.T.), University of Tasmania, Hobart; Florey Institute of Neuroscience and Mental Health (A.-L.P.), The University of Melbourne; Centre of Epidemiology and Biostatistics (A.-L.P.), School of Population and Global Health, University of Melbourne; Murdoch Children's Research Institute (A.-L.P.), Royal Children's Hospital, Melbourne; and Centre for Genomics and Personalized Health (R.L.), School of Biomedical Science, Queensland University of Technology, Kelvin Grove, Australia
| | - Maria-Pia Campagna
- From the School of Medicine and Public Health (V.M., R.L., J.L.-S.), University of Newcastle, University Drive, Callaghan; Immune Health Program (V.M., A.X., J.L.-S.), Hunter Medical Research Institute; Department of Neurology (V.M., J.L.-S.), John Hunter Hospital, New Lambton Heights; School of Biomedical Sciences and Pharmacy (A.X.), University of Newcastle, University Drive, Callaghan, Australia; Department of Clinical Neuroscience (E.E., L.K., M.J.), Karolinska Institutet, Center for Molecular Medicine, Karolinska University Hospital, Stockholm, Sweden; Department of Neuroscience (M.-P.C., S.S., H.B., V.J.), Central Clinical School, Monash University, Victoria; Division of Molecular Genetics (R.J.S.), Pathology North, John Hunter Hospital, New Lambton Heights; MSBase Foundation (H.B.), Melbourne, Australia; Institute of Clinical Medicine (S.B.), University of Oslo,; Department of Neurology (S.B.), Oslo University Hospital, Norway; Flinders University (M.S.), Adelaide; Menzies Institute for Medical Research (I.A.M., B.V.T.), University of Tasmania, Hobart; Florey Institute of Neuroscience and Mental Health (A.-L.P.), The University of Melbourne; Centre of Epidemiology and Biostatistics (A.-L.P.), School of Population and Global Health, University of Melbourne; Murdoch Children's Research Institute (A.-L.P.), Royal Children's Hospital, Melbourne; and Centre for Genomics and Personalized Health (R.L.), School of Biomedical Science, Queensland University of Technology, Kelvin Grove, Australia
| | - Sandeep Sampangi
- From the School of Medicine and Public Health (V.M., R.L., J.L.-S.), University of Newcastle, University Drive, Callaghan; Immune Health Program (V.M., A.X., J.L.-S.), Hunter Medical Research Institute; Department of Neurology (V.M., J.L.-S.), John Hunter Hospital, New Lambton Heights; School of Biomedical Sciences and Pharmacy (A.X.), University of Newcastle, University Drive, Callaghan, Australia; Department of Clinical Neuroscience (E.E., L.K., M.J.), Karolinska Institutet, Center for Molecular Medicine, Karolinska University Hospital, Stockholm, Sweden; Department of Neuroscience (M.-P.C., S.S., H.B., V.J.), Central Clinical School, Monash University, Victoria; Division of Molecular Genetics (R.J.S.), Pathology North, John Hunter Hospital, New Lambton Heights; MSBase Foundation (H.B.), Melbourne, Australia; Institute of Clinical Medicine (S.B.), University of Oslo,; Department of Neurology (S.B.), Oslo University Hospital, Norway; Flinders University (M.S.), Adelaide; Menzies Institute for Medical Research (I.A.M., B.V.T.), University of Tasmania, Hobart; Florey Institute of Neuroscience and Mental Health (A.-L.P.), The University of Melbourne; Centre of Epidemiology and Biostatistics (A.-L.P.), School of Population and Global Health, University of Melbourne; Murdoch Children's Research Institute (A.-L.P.), Royal Children's Hospital, Melbourne; and Centre for Genomics and Personalized Health (R.L.), School of Biomedical Science, Queensland University of Technology, Kelvin Grove, Australia
| | - Rodney J Scott
- From the School of Medicine and Public Health (V.M., R.L., J.L.-S.), University of Newcastle, University Drive, Callaghan; Immune Health Program (V.M., A.X., J.L.-S.), Hunter Medical Research Institute; Department of Neurology (V.M., J.L.-S.), John Hunter Hospital, New Lambton Heights; School of Biomedical Sciences and Pharmacy (A.X.), University of Newcastle, University Drive, Callaghan, Australia; Department of Clinical Neuroscience (E.E., L.K., M.J.), Karolinska Institutet, Center for Molecular Medicine, Karolinska University Hospital, Stockholm, Sweden; Department of Neuroscience (M.-P.C., S.S., H.B., V.J.), Central Clinical School, Monash University, Victoria; Division of Molecular Genetics (R.J.S.), Pathology North, John Hunter Hospital, New Lambton Heights; MSBase Foundation (H.B.), Melbourne, Australia; Institute of Clinical Medicine (S.B.), University of Oslo,; Department of Neurology (S.B.), Oslo University Hospital, Norway; Flinders University (M.S.), Adelaide; Menzies Institute for Medical Research (I.A.M., B.V.T.), University of Tasmania, Hobart; Florey Institute of Neuroscience and Mental Health (A.-L.P.), The University of Melbourne; Centre of Epidemiology and Biostatistics (A.-L.P.), School of Population and Global Health, University of Melbourne; Murdoch Children's Research Institute (A.-L.P.), Royal Children's Hospital, Melbourne; and Centre for Genomics and Personalized Health (R.L.), School of Biomedical Science, Queensland University of Technology, Kelvin Grove, Australia.
| | - Helmut Butzkueven
- From the School of Medicine and Public Health (V.M., R.L., J.L.-S.), University of Newcastle, University Drive, Callaghan; Immune Health Program (V.M., A.X., J.L.-S.), Hunter Medical Research Institute; Department of Neurology (V.M., J.L.-S.), John Hunter Hospital, New Lambton Heights; School of Biomedical Sciences and Pharmacy (A.X.), University of Newcastle, University Drive, Callaghan, Australia; Department of Clinical Neuroscience (E.E., L.K., M.J.), Karolinska Institutet, Center for Molecular Medicine, Karolinska University Hospital, Stockholm, Sweden; Department of Neuroscience (M.-P.C., S.S., H.B., V.J.), Central Clinical School, Monash University, Victoria; Division of Molecular Genetics (R.J.S.), Pathology North, John Hunter Hospital, New Lambton Heights; MSBase Foundation (H.B.), Melbourne, Australia; Institute of Clinical Medicine (S.B.), University of Oslo,; Department of Neurology (S.B.), Oslo University Hospital, Norway; Flinders University (M.S.), Adelaide; Menzies Institute for Medical Research (I.A.M., B.V.T.), University of Tasmania, Hobart; Florey Institute of Neuroscience and Mental Health (A.-L.P.), The University of Melbourne; Centre of Epidemiology and Biostatistics (A.-L.P.), School of Population and Global Health, University of Melbourne; Murdoch Children's Research Institute (A.-L.P.), Royal Children's Hospital, Melbourne; and Centre for Genomics and Personalized Health (R.L.), School of Biomedical Science, Queensland University of Technology, Kelvin Grove, Australia
| | - Vilija Jokubaitis
- From the School of Medicine and Public Health (V.M., R.L., J.L.-S.), University of Newcastle, University Drive, Callaghan; Immune Health Program (V.M., A.X., J.L.-S.), Hunter Medical Research Institute; Department of Neurology (V.M., J.L.-S.), John Hunter Hospital, New Lambton Heights; School of Biomedical Sciences and Pharmacy (A.X.), University of Newcastle, University Drive, Callaghan, Australia; Department of Clinical Neuroscience (E.E., L.K., M.J.), Karolinska Institutet, Center for Molecular Medicine, Karolinska University Hospital, Stockholm, Sweden; Department of Neuroscience (M.-P.C., S.S., H.B., V.J.), Central Clinical School, Monash University, Victoria; Division of Molecular Genetics (R.J.S.), Pathology North, John Hunter Hospital, New Lambton Heights; MSBase Foundation (H.B.), Melbourne, Australia; Institute of Clinical Medicine (S.B.), University of Oslo,; Department of Neurology (S.B.), Oslo University Hospital, Norway; Flinders University (M.S.), Adelaide; Menzies Institute for Medical Research (I.A.M., B.V.T.), University of Tasmania, Hobart; Florey Institute of Neuroscience and Mental Health (A.-L.P.), The University of Melbourne; Centre of Epidemiology and Biostatistics (A.-L.P.), School of Population and Global Health, University of Melbourne; Murdoch Children's Research Institute (A.-L.P.), Royal Children's Hospital, Melbourne; and Centre for Genomics and Personalized Health (R.L.), School of Biomedical Science, Queensland University of Technology, Kelvin Grove, Australia
| | - Lara Kular
- From the School of Medicine and Public Health (V.M., R.L., J.L.-S.), University of Newcastle, University Drive, Callaghan; Immune Health Program (V.M., A.X., J.L.-S.), Hunter Medical Research Institute; Department of Neurology (V.M., J.L.-S.), John Hunter Hospital, New Lambton Heights; School of Biomedical Sciences and Pharmacy (A.X.), University of Newcastle, University Drive, Callaghan, Australia; Department of Clinical Neuroscience (E.E., L.K., M.J.), Karolinska Institutet, Center for Molecular Medicine, Karolinska University Hospital, Stockholm, Sweden; Department of Neuroscience (M.-P.C., S.S., H.B., V.J.), Central Clinical School, Monash University, Victoria; Division of Molecular Genetics (R.J.S.), Pathology North, John Hunter Hospital, New Lambton Heights; MSBase Foundation (H.B.), Melbourne, Australia; Institute of Clinical Medicine (S.B.), University of Oslo,; Department of Neurology (S.B.), Oslo University Hospital, Norway; Flinders University (M.S.), Adelaide; Menzies Institute for Medical Research (I.A.M., B.V.T.), University of Tasmania, Hobart; Florey Institute of Neuroscience and Mental Health (A.-L.P.), The University of Melbourne; Centre of Epidemiology and Biostatistics (A.-L.P.), School of Population and Global Health, University of Melbourne; Murdoch Children's Research Institute (A.-L.P.), Royal Children's Hospital, Melbourne; and Centre for Genomics and Personalized Health (R.L.), School of Biomedical Science, Queensland University of Technology, Kelvin Grove, Australia
| | - Steffan Bos
- From the School of Medicine and Public Health (V.M., R.L., J.L.-S.), University of Newcastle, University Drive, Callaghan; Immune Health Program (V.M., A.X., J.L.-S.), Hunter Medical Research Institute; Department of Neurology (V.M., J.L.-S.), John Hunter Hospital, New Lambton Heights; School of Biomedical Sciences and Pharmacy (A.X.), University of Newcastle, University Drive, Callaghan, Australia; Department of Clinical Neuroscience (E.E., L.K., M.J.), Karolinska Institutet, Center for Molecular Medicine, Karolinska University Hospital, Stockholm, Sweden; Department of Neuroscience (M.-P.C., S.S., H.B., V.J.), Central Clinical School, Monash University, Victoria; Division of Molecular Genetics (R.J.S.), Pathology North, John Hunter Hospital, New Lambton Heights; MSBase Foundation (H.B.), Melbourne, Australia; Institute of Clinical Medicine (S.B.), University of Oslo,; Department of Neurology (S.B.), Oslo University Hospital, Norway; Flinders University (M.S.), Adelaide; Menzies Institute for Medical Research (I.A.M., B.V.T.), University of Tasmania, Hobart; Florey Institute of Neuroscience and Mental Health (A.-L.P.), The University of Melbourne; Centre of Epidemiology and Biostatistics (A.-L.P.), School of Population and Global Health, University of Melbourne; Murdoch Children's Research Institute (A.-L.P.), Royal Children's Hospital, Melbourne; and Centre for Genomics and Personalized Health (R.L.), School of Biomedical Science, Queensland University of Technology, Kelvin Grove, Australia
| | - Mark Slee
- From the School of Medicine and Public Health (V.M., R.L., J.L.-S.), University of Newcastle, University Drive, Callaghan; Immune Health Program (V.M., A.X., J.L.-S.), Hunter Medical Research Institute; Department of Neurology (V.M., J.L.-S.), John Hunter Hospital, New Lambton Heights; School of Biomedical Sciences and Pharmacy (A.X.), University of Newcastle, University Drive, Callaghan, Australia; Department of Clinical Neuroscience (E.E., L.K., M.J.), Karolinska Institutet, Center for Molecular Medicine, Karolinska University Hospital, Stockholm, Sweden; Department of Neuroscience (M.-P.C., S.S., H.B., V.J.), Central Clinical School, Monash University, Victoria; Division of Molecular Genetics (R.J.S.), Pathology North, John Hunter Hospital, New Lambton Heights; MSBase Foundation (H.B.), Melbourne, Australia; Institute of Clinical Medicine (S.B.), University of Oslo,; Department of Neurology (S.B.), Oslo University Hospital, Norway; Flinders University (M.S.), Adelaide; Menzies Institute for Medical Research (I.A.M., B.V.T.), University of Tasmania, Hobart; Florey Institute of Neuroscience and Mental Health (A.-L.P.), The University of Melbourne; Centre of Epidemiology and Biostatistics (A.-L.P.), School of Population and Global Health, University of Melbourne; Murdoch Children's Research Institute (A.-L.P.), Royal Children's Hospital, Melbourne; and Centre for Genomics and Personalized Health (R.L.), School of Biomedical Science, Queensland University of Technology, Kelvin Grove, Australia
| | - Ingrid A van der Mei
- From the School of Medicine and Public Health (V.M., R.L., J.L.-S.), University of Newcastle, University Drive, Callaghan; Immune Health Program (V.M., A.X., J.L.-S.), Hunter Medical Research Institute; Department of Neurology (V.M., J.L.-S.), John Hunter Hospital, New Lambton Heights; School of Biomedical Sciences and Pharmacy (A.X.), University of Newcastle, University Drive, Callaghan, Australia; Department of Clinical Neuroscience (E.E., L.K., M.J.), Karolinska Institutet, Center for Molecular Medicine, Karolinska University Hospital, Stockholm, Sweden; Department of Neuroscience (M.-P.C., S.S., H.B., V.J.), Central Clinical School, Monash University, Victoria; Division of Molecular Genetics (R.J.S.), Pathology North, John Hunter Hospital, New Lambton Heights; MSBase Foundation (H.B.), Melbourne, Australia; Institute of Clinical Medicine (S.B.), University of Oslo,; Department of Neurology (S.B.), Oslo University Hospital, Norway; Flinders University (M.S.), Adelaide; Menzies Institute for Medical Research (I.A.M., B.V.T.), University of Tasmania, Hobart; Florey Institute of Neuroscience and Mental Health (A.-L.P.), The University of Melbourne; Centre of Epidemiology and Biostatistics (A.-L.P.), School of Population and Global Health, University of Melbourne; Murdoch Children's Research Institute (A.-L.P.), Royal Children's Hospital, Melbourne; and Centre for Genomics and Personalized Health (R.L.), School of Biomedical Science, Queensland University of Technology, Kelvin Grove, Australia
| | - Bruce V Taylor
- From the School of Medicine and Public Health (V.M., R.L., J.L.-S.), University of Newcastle, University Drive, Callaghan; Immune Health Program (V.M., A.X., J.L.-S.), Hunter Medical Research Institute; Department of Neurology (V.M., J.L.-S.), John Hunter Hospital, New Lambton Heights; School of Biomedical Sciences and Pharmacy (A.X.), University of Newcastle, University Drive, Callaghan, Australia; Department of Clinical Neuroscience (E.E., L.K., M.J.), Karolinska Institutet, Center for Molecular Medicine, Karolinska University Hospital, Stockholm, Sweden; Department of Neuroscience (M.-P.C., S.S., H.B., V.J.), Central Clinical School, Monash University, Victoria; Division of Molecular Genetics (R.J.S.), Pathology North, John Hunter Hospital, New Lambton Heights; MSBase Foundation (H.B.), Melbourne, Australia; Institute of Clinical Medicine (S.B.), University of Oslo,; Department of Neurology (S.B.), Oslo University Hospital, Norway; Flinders University (M.S.), Adelaide; Menzies Institute for Medical Research (I.A.M., B.V.T.), University of Tasmania, Hobart; Florey Institute of Neuroscience and Mental Health (A.-L.P.), The University of Melbourne; Centre of Epidemiology and Biostatistics (A.-L.P.), School of Population and Global Health, University of Melbourne; Murdoch Children's Research Institute (A.-L.P.), Royal Children's Hospital, Melbourne; and Centre for Genomics and Personalized Health (R.L.), School of Biomedical Science, Queensland University of Technology, Kelvin Grove, Australia
| | - Anne-Louise Ponsonby
- From the School of Medicine and Public Health (V.M., R.L., J.L.-S.), University of Newcastle, University Drive, Callaghan; Immune Health Program (V.M., A.X., J.L.-S.), Hunter Medical Research Institute; Department of Neurology (V.M., J.L.-S.), John Hunter Hospital, New Lambton Heights; School of Biomedical Sciences and Pharmacy (A.X.), University of Newcastle, University Drive, Callaghan, Australia; Department of Clinical Neuroscience (E.E., L.K., M.J.), Karolinska Institutet, Center for Molecular Medicine, Karolinska University Hospital, Stockholm, Sweden; Department of Neuroscience (M.-P.C., S.S., H.B., V.J.), Central Clinical School, Monash University, Victoria; Division of Molecular Genetics (R.J.S.), Pathology North, John Hunter Hospital, New Lambton Heights; MSBase Foundation (H.B.), Melbourne, Australia; Institute of Clinical Medicine (S.B.), University of Oslo,; Department of Neurology (S.B.), Oslo University Hospital, Norway; Flinders University (M.S.), Adelaide; Menzies Institute for Medical Research (I.A.M., B.V.T.), University of Tasmania, Hobart; Florey Institute of Neuroscience and Mental Health (A.-L.P.), The University of Melbourne; Centre of Epidemiology and Biostatistics (A.-L.P.), School of Population and Global Health, University of Melbourne; Murdoch Children's Research Institute (A.-L.P.), Royal Children's Hospital, Melbourne; and Centre for Genomics and Personalized Health (R.L.), School of Biomedical Science, Queensland University of Technology, Kelvin Grove, Australia
| | - Maja Jagodic
- From the School of Medicine and Public Health (V.M., R.L., J.L.-S.), University of Newcastle, University Drive, Callaghan; Immune Health Program (V.M., A.X., J.L.-S.), Hunter Medical Research Institute; Department of Neurology (V.M., J.L.-S.), John Hunter Hospital, New Lambton Heights; School of Biomedical Sciences and Pharmacy (A.X.), University of Newcastle, University Drive, Callaghan, Australia; Department of Clinical Neuroscience (E.E., L.K., M.J.), Karolinska Institutet, Center for Molecular Medicine, Karolinska University Hospital, Stockholm, Sweden; Department of Neuroscience (M.-P.C., S.S., H.B., V.J.), Central Clinical School, Monash University, Victoria; Division of Molecular Genetics (R.J.S.), Pathology North, John Hunter Hospital, New Lambton Heights; MSBase Foundation (H.B.), Melbourne, Australia; Institute of Clinical Medicine (S.B.), University of Oslo,; Department of Neurology (S.B.), Oslo University Hospital, Norway; Flinders University (M.S.), Adelaide; Menzies Institute for Medical Research (I.A.M., B.V.T.), University of Tasmania, Hobart; Florey Institute of Neuroscience and Mental Health (A.-L.P.), The University of Melbourne; Centre of Epidemiology and Biostatistics (A.-L.P.), School of Population and Global Health, University of Melbourne; Murdoch Children's Research Institute (A.-L.P.), Royal Children's Hospital, Melbourne; and Centre for Genomics and Personalized Health (R.L.), School of Biomedical Science, Queensland University of Technology, Kelvin Grove, Australia
| | - Rodney Lea
- From the School of Medicine and Public Health (V.M., R.L., J.L.-S.), University of Newcastle, University Drive, Callaghan; Immune Health Program (V.M., A.X., J.L.-S.), Hunter Medical Research Institute; Department of Neurology (V.M., J.L.-S.), John Hunter Hospital, New Lambton Heights; School of Biomedical Sciences and Pharmacy (A.X.), University of Newcastle, University Drive, Callaghan, Australia; Department of Clinical Neuroscience (E.E., L.K., M.J.), Karolinska Institutet, Center for Molecular Medicine, Karolinska University Hospital, Stockholm, Sweden; Department of Neuroscience (M.-P.C., S.S., H.B., V.J.), Central Clinical School, Monash University, Victoria; Division of Molecular Genetics (R.J.S.), Pathology North, John Hunter Hospital, New Lambton Heights; MSBase Foundation (H.B.), Melbourne, Australia; Institute of Clinical Medicine (S.B.), University of Oslo,; Department of Neurology (S.B.), Oslo University Hospital, Norway; Flinders University (M.S.), Adelaide; Menzies Institute for Medical Research (I.A.M., B.V.T.), University of Tasmania, Hobart; Florey Institute of Neuroscience and Mental Health (A.-L.P.), The University of Melbourne; Centre of Epidemiology and Biostatistics (A.-L.P.), School of Population and Global Health, University of Melbourne; Murdoch Children's Research Institute (A.-L.P.), Royal Children's Hospital, Melbourne; and Centre for Genomics and Personalized Health (R.L.), School of Biomedical Science, Queensland University of Technology, Kelvin Grove, Australia
| | - Jeannette Lechner-Scott
- From the School of Medicine and Public Health (V.M., R.L., J.L.-S.), University of Newcastle, University Drive, Callaghan; Immune Health Program (V.M., A.X., J.L.-S.), Hunter Medical Research Institute; Department of Neurology (V.M., J.L.-S.), John Hunter Hospital, New Lambton Heights; School of Biomedical Sciences and Pharmacy (A.X.), University of Newcastle, University Drive, Callaghan, Australia; Department of Clinical Neuroscience (E.E., L.K., M.J.), Karolinska Institutet, Center for Molecular Medicine, Karolinska University Hospital, Stockholm, Sweden; Department of Neuroscience (M.-P.C., S.S., H.B., V.J.), Central Clinical School, Monash University, Victoria; Division of Molecular Genetics (R.J.S.), Pathology North, John Hunter Hospital, New Lambton Heights; MSBase Foundation (H.B.), Melbourne, Australia; Institute of Clinical Medicine (S.B.), University of Oslo,; Department of Neurology (S.B.), Oslo University Hospital, Norway; Flinders University (M.S.), Adelaide; Menzies Institute for Medical Research (I.A.M., B.V.T.), University of Tasmania, Hobart; Florey Institute of Neuroscience and Mental Health (A.-L.P.), The University of Melbourne; Centre of Epidemiology and Biostatistics (A.-L.P.), School of Population and Global Health, University of Melbourne; Murdoch Children's Research Institute (A.-L.P.), Royal Children's Hospital, Melbourne; and Centre for Genomics and Personalized Health (R.L.), School of Biomedical Science, Queensland University of Technology, Kelvin Grove, Australia.
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13
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Ni W, Nikolaou N, Ward-Caviness CK, Breitner S, Wolf K, Zhang S, Wilson R, Waldenberger M, Peters A, Schneider A. Associations between medium- and long-term exposure to air temperature and epigenetic age acceleration. ENVIRONMENT INTERNATIONAL 2023; 178:108109. [PMID: 37517177 PMCID: PMC10656697 DOI: 10.1016/j.envint.2023.108109] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/06/2023] [Revised: 07/12/2023] [Accepted: 07/20/2023] [Indexed: 08/01/2023]
Abstract
Climate change poses a serious threat to human health worldwide, while aging populations increase. However, no study has ever investigated the effects of air temperature on epigenetic age acceleration. This study involved 1,725 and 1,877 participants from the population-based KORA F4 (2006-2008) and follow-up FF4 (2013-2014) studies, respectively, conducted in Augsburg, Germany. The difference between epigenetic age and chronological age was referred to as epigenetic age acceleration and reflected by Horvath's epigenetic age acceleration (HorvathAA), Hannum's epigenetic age acceleration (HannumAA), PhenoAge acceleration (PhenoAA), GrimAge acceleration (GrimAA), and Epigenetic Skin and Blood Age acceleration (SkinBloodAA). Daily air temperature was estimated using hybrid spatiotemporal regression-based models. To explore the medium- and long-term effects of air temperature modeled in time and space on epigenetic age acceleration, we applied generalized estimating equations (GEE) with distributed lag non-linear models, and GEE, respectively. We found that high temperature exposure based on the 8-week moving average air temperature (97.5th percentile of temperature compared to median temperature) was associated with increased HorvathAA, HannumAA, GrimAA, and SkinBloodAA: 1.83 (95% CI: 0.29-3.37), 11.71 (95% CI: 8.91-14.50), 2.26 (95% CI: 1.03-3.50), and 5.02 (95% CI: 3.42-6.63) years, respectively. Additionally, we found consistent results with high temperature exposure based on the 4-week moving average air temperature was associated with increased HannumAA, GrimAA, and SkinBloodAA: 9.18 (95% CI: 6.60-11.76), 1.78 (95% CI: 0.66-2.90), and 4.07 (95% CI: 2.56-5.57) years, respectively. For the spatial variation in annual average temperature, a 1 °C increase was associated with an increase in all five measures of epigenetic age acceleration (HorvathAA: 0.41 [95% CI: 0.24-0.57], HannumAA: 2.24 [95% CI: 1.95-2.53], PhenoAA: 0.32 [95% CI: 0.05-0.60], GrimAA: 0.24 [95%: 0.11-0.37], and SkinBloodAA: 1.17 [95% CI: 1.00-1.35] years). In conclusion, our results provide first evidence that medium- and long-term exposures to high air temperature affect increases in epigenetic age acceleration.
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Affiliation(s)
- Wenli Ni
- Institute of Epidemiology, Helmholtz Zentrum München - German Research Center for Environmental Health (GmbH), Ingolstädter Landstraße 1, Neuherberg, Germany; Institute for Medical Information Processing, Biometry, and Epidemiology, Pettenkofer School of Public Health, LMU Munich, Munich, Germany.
| | - Nikolaos Nikolaou
- Institute of Epidemiology, Helmholtz Zentrum München - German Research Center for Environmental Health (GmbH), Ingolstädter Landstraße 1, Neuherberg, Germany; Institute for Medical Information Processing, Biometry, and Epidemiology, Pettenkofer School of Public Health, LMU Munich, Munich, Germany
| | - Cavin K Ward-Caviness
- Center for Public Health and Environmental Assessment, US Environmental Protection Agency, Chapel Hill, NC, USA
| | - Susanne Breitner
- Institute of Epidemiology, Helmholtz Zentrum München - German Research Center for Environmental Health (GmbH), Ingolstädter Landstraße 1, Neuherberg, Germany; Institute for Medical Information Processing, Biometry, and Epidemiology, Pettenkofer School of Public Health, LMU Munich, Munich, Germany
| | - Kathrin Wolf
- Institute of Epidemiology, Helmholtz Zentrum München - German Research Center for Environmental Health (GmbH), Ingolstädter Landstraße 1, Neuherberg, Germany
| | - Siqi Zhang
- Institute of Epidemiology, Helmholtz Zentrum München - German Research Center for Environmental Health (GmbH), Ingolstädter Landstraße 1, Neuherberg, Germany
| | - Rory Wilson
- Institute of Epidemiology, Helmholtz Zentrum München - German Research Center for Environmental Health (GmbH), Ingolstädter Landstraße 1, Neuherberg, Germany; Research Unit Molecular Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Melanie Waldenberger
- Institute of Epidemiology, Helmholtz Zentrum München - German Research Center for Environmental Health (GmbH), Ingolstädter Landstraße 1, Neuherberg, Germany; Research Unit Molecular Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany; German Centre for Cardiovascular Research (DZHK), Partner Site Munich Heart Alliance, Munich, Germany
| | - Annette Peters
- Institute of Epidemiology, Helmholtz Zentrum München - German Research Center for Environmental Health (GmbH), Ingolstädter Landstraße 1, Neuherberg, Germany; Institute for Medical Information Processing, Biometry, and Epidemiology, Pettenkofer School of Public Health, LMU Munich, Munich, Germany; German Centre for Cardiovascular Research (DZHK), Partner Site Munich Heart Alliance, Munich, Germany; German Center for Diabetes Research (DZD), München-Neuherberg, Germany
| | - Alexandra Schneider
- Institute of Epidemiology, Helmholtz Zentrum München - German Research Center for Environmental Health (GmbH), Ingolstädter Landstraße 1, Neuherberg, Germany
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14
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Nwanaji-Enwerem JC, Cardenas A, Gao X, Wang C, Vokonas P, Spiro A, Osborne AD, Kosheleva A, Hou L, Baccarelli AA, Schwartz J. Psychological Stress and Epigenetic Aging in Older Men: The VA Normative Aging Study. TRANSLATIONAL MEDICINE OF AGING 2023; 7:66-74. [PMID: 37576443 PMCID: PMC10416788 DOI: 10.1016/j.tma.2023.06.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/15/2023] Open
Abstract
Psychological stress remains an important risk factor for morbidity and mortality throughout the life course. However, there have been counterintuitive findings reported in previous studies of older persons that examine the relationships of perceived psychological stress with DNA methylation-based markers of aging, which also serve as predictors of morbidity and mortality (epigenetic age/clocks). We aimed to replicate and expand findings from existing work by examining relationships of self-reported stress with nine epigenetic clocks: Hannum, Horvath, Intrinsic, Extrinsic, SkinBloodClock, PhenoAge, GrimAge, DNAm Telomere Length, and Pace of Aging. We analyzed data from 607 male participants (mean age 73.2 years) of the VA Normative Aging Study with one to two study visits from 1999 to 2007 (observations = 956). Stress was assessed via the 14-item Perceived Stress Scale (PSS). Epigenetic age was calculated from DNA methylation measured in leukocytes with the HumanMethylation450 BeadChip. In linear mixed effects models adjusted for demographic/lifestyle/health factors, a standard deviation (sd) increase in PSS was associated with Horvath (β = -0.35-years, 95%CI: -0.61, -0.09, P=0.008) and Intrinsic (β = -0.40-years, 95%CI: -0.67, -0.13, P=0.004) epigenetic age deceleration. However, in models limited to participants with the highest levels of stress (≥ 75th-percentile), Horvath (β = 2.29-years, 95%CI: 0.16, 4.41, P=0.04) and Intrinsic (β = 2.06-years, 95%CI: -0.17, 4.28, P=0.07) age acceleration associations were observed. Our results reinforce the complexity of psychological stress and epigenetic aging relationships and lay a foundation for future studies that explore longitudinal relationships with other adult stress metrics and factors that can influence stress such as resilience measures.
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Affiliation(s)
- Jamaji C. Nwanaji-Enwerem
- Gangarosa Department of Environmental Health, Emory Rollins School of Public Health, Atlanta, GA, USA
- Department of Emergency Medicine, Emory University School of Medicine, Atlanta, GA, USA
| | - Andres Cardenas
- Department of Epidemiology and Population Health, Stanford School of Medicine, Stanford, CA, USA
| | - Xu Gao
- Department of Occupational and Environmental Health Sciences, Peking University, Beijing, China
| | - Cuicui Wang
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, and MD/PhD Program, Harvard Medical School, Boston, MA, USA
| | - Pantel Vokonas
- VA Normative Aging Study, Veterans Affairs Boston Healthcare System and the Department of Medicine, Boston University School of Medicine, Boston, MA, USA
| | - Avron Spiro
- Massachusetts Veterans Epidemiology and Research Information Center, VA Boston Healthcare System, Boston, MA, USA
- Department of Epidemiology, Boston University School of Public Health, Boston, MA, USA
- Department of Psychiatry, Boston University School of Medicine, Boston, MA, USA
| | - Anwar D. Osborne
- Department of Emergency Medicine, Emory University School of Medicine, Atlanta, GA, USA
| | - Anna Kosheleva
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, and MD/PhD Program, Harvard Medical School, Boston, MA, USA
| | - Lifang Hou
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL
| | - Andrea A. Baccarelli
- Department of Environmental Health Sciences, Columbia Mailman School of Public Health, New York, NY, USA
| | - Joel Schwartz
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, and MD/PhD Program, Harvard Medical School, Boston, MA, USA
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15
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Si J, Chen L, Yu C, Guo Y, Sun D, Pang Y, Millwood IY, Walters RG, Yang L, Chen Y, Du H, Feng S, Yang X, Avery D, Chen J, Chen Z, Liang L, Li L, Lv J. Healthy lifestyle, DNA methylation age acceleration, and incident risk of coronary heart disease. Clin Epigenetics 2023; 15:52. [PMID: 36978155 PMCID: PMC10045869 DOI: 10.1186/s13148-023-01464-2] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2022] [Accepted: 03/12/2023] [Indexed: 03/30/2023] Open
Abstract
BACKGROUND DNA methylation clocks emerged as a tool to determine biological aging and have been related to mortality and age-related diseases. Little is known about the association of DNA methylation age (DNAm age) with coronary heart disease (CHD), especially in the Asian population. RESULTS Methylation level of baseline blood leukocyte DNA was measured by Infinium Methylation EPIC BeadChip for 491 incident CHD cases and 489 controls in the prospective China Kadoorie Biobank. We calculated the methylation age using a prediction model developed among Chinese. The correlation between chronological age and DNAm age was 0.90. DNA methylation age acceleration (Δage) was defined as the residual of regressing DNA methylation age on the chronological age. After adjustment for multiple risk factors of CHD and cell type proportion, compared with participants in the bottom quartile of Δage, the OR (95% CI) for CHD was 1.84 (1.17, 2.89) for participants in the top quartile. One SD increment in Δage was associated with 30% increased risk of CHD (OR = 1.30; 95% CI 1.09, 1.56; Ptrend = 0.003). The average number of cigarette equivalents consumed per day and waist-to-hip ratio were positively associated with Δage; red meat consumption was negatively associated with Δage, characterized by accelerated aging in those who never or rarely consumed red meat (all P < 0.05). Further mediation analysis revealed that 10%, 5% and 18% of the CHD risk related to smoking, waist-to-hip ratio and never or rarely red meat consumption was mediated through methylation aging, respectively (all P for mediation effect < 0.05). CONCLUSIONS We first identified the association between DNAm age acceleration and incident CHD in the Asian population, and provided evidence that unfavorable lifestyle-induced epigenetic aging may play an important part in the underlying pathway to CHD.
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Affiliation(s)
- Jiahui Si
- Institute of Medical Technology, Health Science Center of Peking University, Beijing, China
- National Institute of Health Data Science at Peking University, Peking University, Beijing, China
| | - Lu Chen
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, 38 Xueyuan Road, Beijing, 100191, China
| | - Canqing Yu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, 38 Xueyuan Road, Beijing, 100191, China
- Center for Public Health and Epidemic Preparedness & Response, Peking University, 38 Xueyuan Road, Beijing, 100191, China
| | - Yu Guo
- Fuwai Hospital Chinese Academy of Medical Sciences, Beijing, China
| | - Dianjianyi Sun
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, 38 Xueyuan Road, Beijing, 100191, China
- Center for Public Health and Epidemic Preparedness & Response, Peking University, 38 Xueyuan Road, Beijing, 100191, China
| | - Yuanjie Pang
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, 38 Xueyuan Road, Beijing, 100191, China
- Center for Public Health and Epidemic Preparedness & Response, Peking University, 38 Xueyuan Road, Beijing, 100191, China
| | - Iona Y Millwood
- Medical Research Council Population Health Research Unit at the University of Oxford, Oxford, UK
- Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Robin G Walters
- Medical Research Council Population Health Research Unit at the University of Oxford, Oxford, UK
- Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Ling Yang
- Medical Research Council Population Health Research Unit at the University of Oxford, Oxford, UK
- Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Yiping Chen
- Medical Research Council Population Health Research Unit at the University of Oxford, Oxford, UK
- Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Huaidong Du
- Medical Research Council Population Health Research Unit at the University of Oxford, Oxford, UK
- Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Shixian Feng
- NCDs Prevention and Control Department, Henan CDC, Zhengzhou, Henan, China
| | - Xiaoming Yang
- Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Daniel Avery
- Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Junshi Chen
- China National Center for Food Safety Risk Assessment, Beijing, China
| | - Zhengming Chen
- Medical Research Council Population Health Research Unit at the University of Oxford, Oxford, UK
- Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Liming Liang
- Departments of Epidemiology and Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Liming Li
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, 38 Xueyuan Road, Beijing, 100191, China.
- Center for Public Health and Epidemic Preparedness & Response, Peking University, 38 Xueyuan Road, Beijing, 100191, China.
| | - Jun Lv
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, 38 Xueyuan Road, Beijing, 100191, China.
- Center for Public Health and Epidemic Preparedness & Response, Peking University, 38 Xueyuan Road, Beijing, 100191, China.
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16
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Campisi M, Mastrangelo G, Mielżyńska-Švach D, Hoxha M, Bollati V, Baccarelli AA, Carta A, Porru S, Pavanello S. The effect of high polycyclic aromatic hydrocarbon exposure on biological aging indicators. Environ Health 2023; 22:27. [PMID: 36927494 PMCID: PMC10022060 DOI: 10.1186/s12940-023-00975-y] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2023] [Accepted: 02/24/2023] [Indexed: 06/18/2023]
Abstract
BACKGROUND Aging represents a serious health and socioeconomic concern for our society. However, not all people age in the same way and air pollution has been shown to largely impact this process. We explored whether polycyclic aromatic hydrocarbons (PAHs), excellent fossil and wood burning tracers, accelerate biological aging detected by lymphocytes DNA methylation age (DNAmAge) and telomere length (TL), early nuclear DNA (nDNA) hallmarks of non-mitotic and mitotic cellular aging, and mitochondrial DNA copy number (mtDNAcn). METHODS The study population consisted of 49 male noncurrent-smoking coke-oven workers and 44 matched controls. Occupational and environmental sources of PAH exposures were evaluated by structured questionnaire and internal dose (urinary 1-pyrenol). We estimated Occup_PAHs, the product of 1-pyrenol and years of employment as coke-oven workers, and Environ_PAHs, from multiple items (diet, indoor and outdoor). Biological aging was determined by DNAmAge, via pyrosequencing, and by TL and mtDNAcn, via quantitative polymerase chain reaction. Genomic instability markers in lymphocytes as target dose [anti-benzo[a]pyrene diolepoxide (anti-BPDE)-DNA adduct], genetic instability (micronuclei), gene-specific (p53, IL6 and HIC1) and global (Alu and LINE-1 repeats) DNA methylation, and genetic polymorphisms (GSTM1) were also evaluated in the latent variable nDNA_changes. Structural equation modelling (SEM) analysis evaluated these multifaceted relationships. RESULTS In univariate analysis, biological aging was higher in coke-oven workers than controls as detected by higher percentage of subjects with biological age older than chronological age (AgeAcc ≥ 0, p = 0.007) and TL (p = 0.038), mtDNAcn was instead similar. Genomic instability, i.e., genotoxic and epigenetic alterations (LINE-1, p53 and Alu) and latent variable nDNA_changes were higher in workers (p < 0.001). In SEM analysis, DNAmAge and TL were positively correlated with Occup_PAHs (p < 0.0001). Instead, mtDNAcn is positively correlated with the latent variable nDNA_changes (p < 0.0001) which is in turn triggered by Occup_PAHs and Environ_PAHs. CONCLUSIONS Occupational PAHs exposure influences DNAmAge and TL, suggesting that PAHs target both non-mitotic and mitotic mechanisms and made coke-oven workers biologically older. Also, differences in mtDNAcn, which is modified through nDNA alterations, triggered by environmental and occupational PAH exposure, suggested a nuclear-mitochondrial core-axis of aging. By decreasing this risky gerontogenic exposure, biological aging and the consequent age-related diseases could be prevented.
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Affiliation(s)
- Manuela Campisi
- Occupational Medicine, Department of Cardio-Thoraco-Vascular Sciences and Public Health, University of Padua, Padua, Italy
| | - Giuseppe Mastrangelo
- Occupational Medicine, Department of Cardio-Thoraco-Vascular Sciences and Public Health, University of Padua, Padua, Italy
| | | | - Mirjam Hoxha
- Epidemiology, Epigenetics and Toxicology Lab, Dipartimento Di Scienze Cliniche E Di Comunità, Università Degli Studi Di Milano, Milan, Italia
| | - Valentina Bollati
- Epidemiology, Epigenetics and Toxicology Lab, Dipartimento Di Scienze Cliniche E Di Comunità, Università Degli Studi Di Milano, Milan, Italia
- UO Epidemiologia, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italia
| | - Andrea A Baccarelli
- Department of Environmental Health Sciences, Mailman School of Public Health, Columbia University, New York, NY, USA
| | - Angela Carta
- Department of Diagnostics and Public Health, University of Verona and Clinical Unit of Occupational Medicine, University Hospital of Verona, 37134, Verona, Italy
| | - Stefano Porru
- Department of Diagnostics and Public Health, University of Verona and Clinical Unit of Occupational Medicine, University Hospital of Verona, 37134, Verona, Italy
| | - Sofia Pavanello
- Occupational Medicine, Department of Cardio-Thoraco-Vascular Sciences and Public Health, University of Padua, Padua, Italy.
- Padua Hospital, Occupational Medicine Unit, Padua, Italy.
- University Center for Space Studies and Activities "Giuseppe Colombo" - CISAS. University of Padua, Padua, Italy.
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17
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Pan R, Wang J, Chang WW, Song J, Yi W, Zhao F, Zhang Y, Fang J, Du P, Cheng J, Li T, Su H, Shi X. Association of PM 2.5 Components with Acceleration of Aging: Moderating Role of Sex Hormones. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2023; 57:3772-3782. [PMID: 36811885 DOI: 10.1021/acs.est.2c09005] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/18/2023]
Abstract
Fine particulate matter (PM2.5) has been linked to aging risk, and a lack of knowledge about the relationships between PM2.5 components and aging risk impeded the development of healthy aging. Participants were recruited through a multicenter cross-sectional study in the Beijing-Tianjin-Hebei region in China. Middle-age and older males and menopausal women completed the collection of basic information, blood samples, and clinical examinations. The biological age was estimated by Klemera-Doubal method (KDM) algorithms based on clinical biomarkers. Multiple linear regression models were applied to quantify the associations and interactions while controlling for confounders, and a restricted cubic spline function estimated the corresponding dose-response curves of the relationships. Overall, KDM-biological age acceleration was associated with PM2.5 component exposure over the preceding year in both males and females, with calcium [females: 0.795 (95% CI: 0.451, 1.138); males: 0.712 (95% CI: 0.389, 1.034)], arsenic [females: 0.770 (95% CI: 0.641, 0.899); males: 0.661 (95% CI: 0.532, 0.791)], and copper [females: 0.401 (95% CI: 0.158, 0.644); males: 0.379 (95% CI: 0.122, 0.636)] having greater estimates of the effect than total PM2.5 mass. Additionally, we observed that the associations of specific PM2.5 components with aging were lower in the higher sex hormone scenario. Maintaining high levels of sex hormones may be a crucial barrier against PM2.5 component-related aging in the middle and older age groups.
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Affiliation(s)
- Rubing Pan
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei 230031, Anhui, China
- Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, Hefei 230031, Anhui, China
| | - Jiaonan Wang
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
| | - Wei-Wei Chang
- Department of Epidemiology and Health Statistics, School of Public Health, Wannan Medical College, Wuhu 241002, Anhui, China
| | - Jian Song
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei 230031, Anhui, China
- Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, Hefei 230031, Anhui, China
| | - Weizhuo Yi
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei 230031, Anhui, China
- Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, Hefei 230031, Anhui, China
| | - Feng Zhao
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
| | - Yi Zhang
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
| | - Jianlong Fang
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
| | - Peng Du
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
| | - Jian Cheng
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei 230031, Anhui, China
- Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, Hefei 230031, Anhui, China
| | - Tiantian Li
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
| | - Hong Su
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei 230031, Anhui, China
- Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, Hefei 230031, Anhui, China
| | - Xiaoming Shi
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
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18
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Chen L, Zhang Y, Yu C, Guo Y, Sun D, Pang Y, Pei P, Yang L, Millwood IY, Walters RG, Chen Y, Du H, Liu Y, Burgess S, Stevens R, Chen J, Chen Z, Li L, Lv J. Modeling biological age using blood biomarkers and physical measurements in Chinese adults. EBioMedicine 2023; 89:104458. [PMID: 36758480 PMCID: PMC9941058 DOI: 10.1016/j.ebiom.2023.104458] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2022] [Revised: 01/15/2023] [Accepted: 01/17/2023] [Indexed: 02/09/2023] Open
Abstract
BACKGROUND This study aimed to: 1) assess the associations of biological age acceleration based on Klemera and Doubal's method (KDM-AA) with long-term risk of all-cause mortality; and 2) compare the association of KDM-AA with all-cause mortality among participants potentially at different stages of the cardiovascular disease (CVD) continuum. METHODS The present study was based on a subpopulation of the China Kadoorie Biobank, with baseline survey during 2004-08. A total of 12,377 participants free of ischemic heart disease, stroke, or cancer at baseline were included, in which 8180 participants were identified to develop major coronary event (MCE), ischemic stroke (IS), intracerebral hemorrhage (ICH) or subarachnoid hemorrhage (SAH), and 4197 remained free of these cardiovascular diseases before 1 January 2014. These participants were followed up until 1 Jan 2018. KDM-AA was calculated by regressing biological age measurement, which was constructed based on baseline 16 physical and 9 biochemical markers using Klemera and Doubal's method, on chronological age. We estimated the associations of KDM-AA with the mortality risk using the hazard ratio (HR) and 95% confidence interval (CI) from Cox proportional hazard models. We assessed discrimination performance by Harrell's C-index and net reclassification index (NRI). FINDINGS The participants who developed MCE (mean KDM-AA = 0.1 year, standard deviation [SD] = 1.6 years) or ICH/SAH (0.3 ± 1.5 years) during subsequent follow-up showed accelerated aging at baseline compared to those of IS (0.0 ± 1.2 years) and control (-0.3 ± 1.3 years) groups. The KDM-AA was positively associated with long-term risk of all-cause mortality (HR = 1.20; 95% CI: 1.17, 1.23), and the association was robust for participants potentially at different stages of the CVD continuum. Adding KDM-AA improved mortality prediction compared to the model only with sociodemographic and lifestyle factors in whole participants, with the Harrell's C-index increasing from 0.813 (0.807, 0.819) to 0.821 (0.815, 0.826) (NRI = 0.011; 95% CI: 0.003, 0.019). INTERPRETATION In this middle-aged and elderly Chinese population, the KDM-AA is a promising measurement for biological age, and can capture the difference in cardiovascular health and predict the risk of all-cause mortality over a decade. FUNDING This work was supported by National Natural Science Foundation of China (82192904, 82192901, 82192900, 81941018). The CKB baseline survey and the first re-survey were supported by a grant from the Kadoorie Charitable Foundation Hong Kong. The long-term follow-up is supported by grants from the UK Wellcome Trust (212946/Z/18/Z, 202922/Z/16/Z, 104085/Z/14/Z, 088158/Z/09/Z), grants (2016YFC0900500) from the National Key R&D Program of China, National Natural Science Foundation of China (81390540, 91846303), and Chinese Ministry of Science and Technology (2011BAI09B01).
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Affiliation(s)
- Lu Chen
- Department of Epidemiology & Biostatistics, School of Public Health, Peking University, Beijing, 100191, China
| | - Yiqian Zhang
- Department of Epidemiology & Biostatistics, School of Public Health, Peking University, Beijing, 100191, China
| | - Canqing Yu
- Department of Epidemiology & Biostatistics, School of Public Health, Peking University, Beijing, 100191, China; Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing, 100191, China
| | - Yu Guo
- Fuwai Hospital Chinese Academy of Medical Sciences, Beijing, China
| | - Dianjianyi Sun
- Department of Epidemiology & Biostatistics, School of Public Health, Peking University, Beijing, 100191, China; Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing, 100191, China
| | - Yuanjie Pang
- Department of Epidemiology & Biostatistics, School of Public Health, Peking University, Beijing, 100191, China
| | - Pei Pei
- Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing, 100191, China
| | - Ling Yang
- Medical Research Council Population Health Research Unit at the University of Oxford, Oxford, United Kingdom; Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, United Kingdom
| | - Iona Y Millwood
- Medical Research Council Population Health Research Unit at the University of Oxford, Oxford, United Kingdom; Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, United Kingdom
| | - Robin G Walters
- Medical Research Council Population Health Research Unit at the University of Oxford, Oxford, United Kingdom; Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, United Kingdom
| | - Yiping Chen
- Medical Research Council Population Health Research Unit at the University of Oxford, Oxford, United Kingdom; Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, United Kingdom
| | - Huaidong Du
- Medical Research Council Population Health Research Unit at the University of Oxford, Oxford, United Kingdom; Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, United Kingdom
| | - Yongmei Liu
- Qingdao Centers for Disease Control and Prevention (CDC), Qingdao, China
| | - Sushila Burgess
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, United Kingdom
| | - Rebecca Stevens
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, United Kingdom
| | - Junshi Chen
- China National Center for Food Safety Risk Assessment, Beijing, China
| | - Zhengming Chen
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, United Kingdom
| | - Liming Li
- Department of Epidemiology & Biostatistics, School of Public Health, Peking University, Beijing, 100191, China; Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing, 100191, China
| | - Jun Lv
- Department of Epidemiology & Biostatistics, School of Public Health, Peking University, Beijing, 100191, China; Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing, 100191, China.
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19
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Yang GS, Yang K, Weaver MT, Lynch Kelly D, Dorsey SG, Jackson-Cook CK, Lyon DE. Exploring the relationship between DNA methylation age measures and psychoneurological symptoms in women with early-stage breast cancer. Support Care Cancer 2022; 31:65. [PMID: 36538110 DOI: 10.1007/s00520-022-07519-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2021] [Accepted: 11/14/2022] [Indexed: 12/24/2022]
Abstract
PURPOSE The epigenetic clock has been acknowledged as an indicator for molecular aging, but few studies have examined possible associations of DNA methylation (DNAm) age or age acceleration (AA) with symptom burden in individuals who are treated for cancer. This study explored the association of DNAm age or AA with psychoneurological (PN) symptoms, including cognitive impairment, fatigue, sleep disturbances, pain, and depressive symptoms, in breast cancer survivors over a 2-year period. METHODS We measured PN symptoms using reliable instruments and DNAm levels by Infinium HumanMethylation450K BeadChip (N = 72). DNAm age was calculated by the Horvath, Grim, and Hannum-based intrinsic and extrinsic age estimations. AA was defined by the residual regressing estimated epigenetic age on chronological age. Mixed regression models were fitted for AA and changes in AA to study the association over time. Separate linear regression models and a mixed-effects model were fitted for AA at each time point. RESULTS Horvath-AA, Grim-AA, and extrinsic epigenetic AA were significantly changed over time, while intrinsic epigenetic AA did not exhibit any temporal changes. Increased AA was associated with greater anxiety and fatigue, as well as worse cognitive memory, adjusting for race, BMI, income, chemotherapy, radiation therapy, and chronological age. Increased DNAm age was associated with greater anxiety over 2 years. CONCLUSION Our findings suggest DNAm age and AA may be associated with PN symptoms over the course of cancer treatment and survivorship. Some PN symptoms may be amenable to preventive interventions targeted to epigenetic clocks that influence aging-associated processes.
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Affiliation(s)
- Gee Su Yang
- University of Connecticut School of Nursing, Storrs, CT, USA
| | - Kai Yang
- Medical College of Wisconsin Department of Institute for Health and Equity Division of Biostatistics, Milwaukee, WI, USA
| | | | | | - Susan G Dorsey
- School of Nursing Department of Pain and Translational Symptom Science, University of Maryland, Baltimore, MD, USA
| | - Colleen K Jackson-Cook
- Department of Pathology & Department of Human and Molecular Genetics, Virginia Commonwealth University, Richmond, VA, USA
| | - Debra E Lyon
- University of Florida College of Nursing, Gainesville, FL, USA.
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20
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Jiang R, Hauser ER, Kwee LC, Shah SH, Regan JA, Huebner JL, Kraus VB, Kraus WE, Ward-Caviness CK. The association of accelerated epigenetic age with all-cause mortality in cardiac catheterization patients as mediated by vascular and cardiometabolic outcomes. Clin Epigenetics 2022; 14:165. [PMID: 36461124 PMCID: PMC9719253 DOI: 10.1186/s13148-022-01380-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2022] [Accepted: 11/16/2022] [Indexed: 12/04/2022] Open
Abstract
BACKGROUND Epigenetic age is a DNA methylation-based biomarker of aging that is accurate across the lifespan and a range of cell types. The difference between epigenetic age and chronological age, termed age acceleration (AA), is a strong predictor of lifespan and healthspan. The predictive capabilities of AA for all-cause mortality have been evaluated in the general population; however, its utility is less well evaluated in those with chronic conditions. Additionally, the pathophysiologic pathways whereby AA predicts mortality are unclear. We hypothesized that AA predicts mortality in individuals with underlying cardiovascular disease; and the association between AA and mortality is mediated, in part, by vascular and cardiometabolic measures. METHODS We evaluated 562 participants in an urban, three-county area of central North Carolina from the CATHGEN cohort, all of whom received a cardiac catheterization procedure. We analyzed three AA biomarkers, Horvath epigenetic age acceleration (HAA), phenotypic age acceleration (PhenoAA), and Grim age acceleration (GrimAA), by Cox regression models, to assess whether AAs were associated with all-cause mortality. We also evaluated if these associations were mediated by vascular and cardiometabolic outcomes, including left ventricular ejection fraction (LVEF), blood cholesterol concentrations, angiopoietin-2 (ANG2) protein concentration, peripheral artery disease, coronary artery disease, diabetes, and hypertension. The total effect, direct effect, indirect effect, and percentage mediated were estimated using pathway mediation tests with a regression adjustment approach. RESULTS PhenoAA (HR = 1.05, P < 0.0001), GrimAA (HR = 1.10, P < 0.0001) and HAA (HR = 1.03, P = 0.01) were all associated with all-cause mortality. The association of mortality and PhenoAA was partially mediated by ANG2, a marker of vascular function (19.8%, P = 0.016), and by diabetes (8.2%, P = 0.043). The GrimAA-mortality association was mediated by ANG2 (12.3%, P = 0.014), and showed weaker evidence for mediation by LVEF (5.3%, P = 0.065). CONCLUSIONS Epigenetic age acceleration remains strongly predictive of mortality even in individuals already burdened with cardiovascular disease. Mortality associations were mediated by ANG2, which regulates endothelial permeability and angiogenic functions, suggesting that specific vascular pathophysiology may link accelerated epigenetic aging with increased mortality risks.
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Affiliation(s)
- Rong Jiang
- grid.26009.3d0000 0004 1936 7961Department of Psychiatry and Behavioral Sciences, Duke University School of Medicine, Durham, NC USA
| | - Elizabeth R. Hauser
- grid.26009.3d0000 0004 1936 7961Duke Molecular Physiology Institute, Duke University School of Medicine, Durham, NC USA ,grid.26009.3d0000 0004 1936 7961Department of Biostatistics and Bioinformatics, Duke University School of Medicine, Durham, NC USA
| | - Lydia Coulter Kwee
- grid.26009.3d0000 0004 1936 7961Duke Molecular Physiology Institute, Duke University School of Medicine, Durham, NC USA
| | - Svati H. Shah
- grid.26009.3d0000 0004 1936 7961Duke Molecular Physiology Institute, Duke University School of Medicine, Durham, NC USA ,grid.26009.3d0000 0004 1936 7961Division of Cardiology, Department of Medicine, Duke University School of Medicine, Duke University, Durham, NC USA
| | - Jessica A. Regan
- grid.26009.3d0000 0004 1936 7961Duke Molecular Physiology Institute, Duke University School of Medicine, Durham, NC USA ,grid.26009.3d0000 0004 1936 7961Division of Cardiology, Department of Medicine, Duke University School of Medicine, Duke University, Durham, NC USA
| | - Janet L. Huebner
- grid.26009.3d0000 0004 1936 7961Duke Molecular Physiology Institute, Duke University School of Medicine, Durham, NC USA
| | - Virginia B. Kraus
- grid.26009.3d0000 0004 1936 7961Duke Molecular Physiology Institute, Duke University School of Medicine, Durham, NC USA ,grid.26009.3d0000 0004 1936 7961Division of Rheumatology, Department of Medicine, Duke University School of Medicine, Durham, NC USA
| | - William E. Kraus
- grid.26009.3d0000 0004 1936 7961Duke Molecular Physiology Institute, Duke University School of Medicine, Durham, NC USA ,grid.26009.3d0000 0004 1936 7961Division of Cardiology, Department of Medicine, Duke University School of Medicine, Duke University, Durham, NC USA
| | - Cavin K. Ward-Caviness
- grid.418698.a0000 0001 2146 2763Center for Public Health and Environmental Assessment, US Environmental Protection Agency, Chapel Hill, NC USA
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21
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Baranyi G, Deary IJ, McCartney DL, Harris SE, Shortt N, Reis S, Russ TC, Ward Thompson C, Vieno M, Cox SR, Pearce J. Life-course exposure to air pollution and biological ageing in the Lothian Birth Cohort 1936. ENVIRONMENT INTERNATIONAL 2022; 169:107501. [PMID: 36126422 DOI: 10.1016/j.envint.2022.107501] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/29/2022] [Revised: 08/31/2022] [Accepted: 09/01/2022] [Indexed: 06/15/2023]
Abstract
BACKGROUND Exposure to air pollution is associated with a range of diseases. Biomarkers derived from DNA methylation (DNAm) offer potential mechanistic insights into human health differences, connecting disease pathogenesis and biological ageing. However, little is known about sensitive periods during the life course where air pollution might have a stronger impact on DNAm, or whether effects accumulate over time. We examined associations between air pollution exposure across the life course and DNAm-based markers of biological ageing. METHODS Data were derived from the Scotland-based Lothian Birth Cohort 1936. Participants' residential history was linked to annual levels of fine particle (PM2.5), sulphur dioxide (SO2), nitrogen dioxide (NO2), and ozone (O3) around 1935, 1950, 1970, 1980, 1990, and 2001; pollutant concentrations were estimated using the EMEP4UK atmospheric chemistry transport model. Blood samples were obtained between ages of 70 and 80 years, and Horvath DNAmAge, Hannum DNAmAge, DNAmPhenoAge, DNAmGrimAge, and DNAm telomere length (DNAmTL) were computed. We applied the structured life-course modelling approach: least angle regression identified best-fit life-course models for a composite measure of air pollution (air quality index [AQI]), and mixed-effects regression estimated selected models for AQI and single pollutants. RESULTS We included 525 individuals with 1782 observations. In the total sample, increased air pollution around 1970 was associated with higher epigenetic age (AQI: b = 0.322 year, 95 %CI: 0.088, 0.555) measured with Horvath DNAmAge in late adulthood. We found shorter DNAmTL among males with higher air pollution around 1980 (AQI: b = -0.015 kilobase, 95 %CI: -0.027, -0.004) and among females with higher exposure around 1935 (AQI: b = -0.017 kilobase, 95 %CI: -0.028, -0.006). Findings were more consistent for the pollutants PM2.5, SO2 and NO2. DISCUSSION We tested the life-course relationship between air pollution and DNAm-based biomarkers. Air pollution around birth and in young-to-middle adulthood is linked to accelerated epigenetic ageing and telomere-associated ageing in later life.
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Affiliation(s)
- Gergő Baranyi
- Centre for Research on Environment, Society and Health, School of GeoSciences, The University of Edinburgh, Edinburgh, UK.
| | - Ian J Deary
- Lothian Birth Cohorts, Department of Psychology, The University of Edinburgh, Edinburgh, UK
| | - Daniel L McCartney
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, The University of Edinburgh, Edinburgh, UK
| | - Sarah E Harris
- Lothian Birth Cohorts, Department of Psychology, The University of Edinburgh, Edinburgh, UK
| | - Niamh Shortt
- Centre for Research on Environment, Society and Health, School of GeoSciences, The University of Edinburgh, Edinburgh, UK
| | - Stefan Reis
- UK Centre for Ecology & Hydrology (UKCEH), Bush Estate, Penicuik, UK; University of Exeter Medical School, Knowledge Spa, Truro TR1 3HD, UK; The University of Edinburgh, School of Chemistry, Edinburgh EH9 3BF, UK
| | - Tom C Russ
- Alzheimer Scotland Dementia Research Centre, The University of Edinburgh, Edinburgh, UK
| | | | - Massimo Vieno
- UK Centre for Ecology & Hydrology (UKCEH), Bush Estate, Penicuik, UK
| | - Simon R Cox
- Lothian Birth Cohorts, Department of Psychology, The University of Edinburgh, Edinburgh, UK
| | - Jamie Pearce
- Centre for Research on Environment, Society and Health, School of GeoSciences, The University of Edinburgh, Edinburgh, UK
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22
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Lodge EK, Dhingra R, Martin CL, Fry RC, White AJ, Ward-Caviness CK, Wani AH, Uddin M, Wildman DE, Galea S, Aiello AE. Serum lead, mercury, manganese, and copper and DNA methylation age among adults in Detroit, Michigan. ENVIRONMENTAL EPIGENETICS 2022; 8:dvac018. [PMID: 36330039 PMCID: PMC9620967 DOI: 10.1093/eep/dvac018] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 03/17/2022] [Revised: 09/03/2022] [Accepted: 09/19/2022] [Indexed: 06/16/2023]
Abstract
Although the effects of lead, mercury, manganese, and copper on individual disease processes are well understood, estimating the health effects of long-term exposure to these metals at the low concentrations often observed in the general population is difficult. In addition, the health effects of joint exposure to multiple metals are difficult to estimate. Biological aging refers to the integrative progression of multiple physiologic and molecular changes that make individuals more at risk of disease. Biomarkers of biological aging may be useful to estimate the population-level effects of metal exposure prior to the development of disease in the population. We used data from 290 participants in the Detroit Neighborhood Health Study to estimate the effect of serum lead, mercury, manganese, and copper on three DNA methylation-based biomarkers of biological aging (Horvath Age, PhenoAge, and GrimAge). We used mixed models and Bayesian kernel machine regression and controlled for participant sex, race, ethnicity, cigarette use, income, educational attainment, and block group poverty. We observed consistently positive estimates of the effects between lead and GrimAge acceleration and mercury and PhenoAge acceleration. In contrast, we observed consistently negative associations between manganese and PhenoAge acceleration and mercury and Horvath Age acceleration. We also observed curvilinear relationships between copper and both PhenoAge and GrimAge acceleration. Increasing total exposure to the observed mixture of metals was associated with increased PhenoAge and GrimAge acceleration and decreased Horvath Age acceleration. These findings indicate that an increase in serum lead or mercury from the 25th to 75th percentile is associated with a ∼0.25-year increase in two epigenetic markers of all-cause mortality in a population of adults in Detroit, Michigan. While few of the findings were statistically significant, their consistency and novelty warrant interest.
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Affiliation(s)
- Evans K Lodge
- *Correspondence address. Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, 135 Dauer Drive, Chapel Hill, NC 27599, USA. Tel: +574-339-0253; Fax: +919-966-2089; E-mail:
| | - Radhika Dhingra
- Department of Environmental Sciences and Engineering, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, 135 Dauer Dr, Chapel Hill, NC 27599, USA
- Institute for Environmental Health Solutions, University of North Carolina at Chapel Hill, 135 Dauer Dr, Chapel Hill, NC 27599, USA
| | - Chantel L Martin
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, 135 Dauer Dr, Chapel Hill, NC 27599, USA
- Carolina Population Center, University of North Carolina at Chapel Hill, 123 W Franklin St, Chapel Hill, NC 27516, USA
- Center for Environmental Health & Susceptibility, University of North Carolina at Chapel Hill, 135 Dauer Dr, Chapel Hill, NC 27599, USA
| | - Rebecca C Fry
- Department of Environmental Sciences and Engineering, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, 135 Dauer Dr, Chapel Hill, NC 27599, USA
- Center for Environmental Health & Susceptibility, University of North Carolina at Chapel Hill, 135 Dauer Dr, Chapel Hill, NC 27599, USA
| | - Alexandra J White
- Epidemiology Branch, National Institute of Environmental Health Sciences, A323 David P Rall Building, Research Triangle Park, NC 27709, USA
| | - Cavin K Ward-Caviness
- Center for Public Health and Environmental Assessment, US Environmental Protection Agency, 104 Mason Farm Rd, Chapel Hill, NC 27514, USA
| | - Agaz H Wani
- Genomics Program, College of Public Health, University of South Florida, 12901 Bruce B Downs Blvd, Tampa, FL 33612, USA
| | - Monica Uddin
- Genomics Program, College of Public Health, University of South Florida, 12901 Bruce B Downs Blvd, Tampa, FL 33612, USA
| | - Derek E Wildman
- Genomics Program, College of Public Health, University of South Florida, 12901 Bruce B Downs Blvd, Tampa, FL 33612, USA
| | - Sandro Galea
- School of Public Health, Boston University, 715 Albany St, Boston, MA 02118, USA
| | - Allison E Aiello
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, 135 Dauer Dr, Chapel Hill, NC 27599, USA
- Carolina Population Center, University of North Carolina at Chapel Hill, 123 W Franklin St, Chapel Hill, NC 27516, USA
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23
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Jeremian R, Malinowski A, Chaudhary Z, Srivastava A, Qian J, Zai C, Adanty C, Fischer CE, Burhan AM, Kennedy JL, Borlido C, Gerretsen P, Graff A, Remington G, Vincent JB, Strauss JS, De Luca V. Epigenetic age dysregulation in individuals with bipolar disorder and schizophrenia. Psychiatry Res 2022; 315:114689. [PMID: 35849977 DOI: 10.1016/j.psychres.2022.114689] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/28/2022] [Revised: 06/16/2022] [Accepted: 06/18/2022] [Indexed: 11/17/2022]
Abstract
Bipolar disorder (BD) and schizophrenia (SCZ) are debilitating disorders that are associated with significant burden and reduced quality of life. In this study, we leveraged microarray data derived from both the Illumina HumanMethylation450 platform to investigate the epigenetic age of individuals with SCZ (n = 40), BD (n = 40), and healthy controls (n = 38), across five epigenetic clocks. Various statistical metrics were used to identify discrepancies between epigenetic and chronological age across the three groups. We observed a significant increase in epigenetic age compared to chronological age in the BD group. Mean epigenetic age acceleration was also higher in individuals with bipolar disorder compared to healthy controls across four different epigenetic clocks (p<0.05). Despite the study's relatively small sample size, these findings suggest that both individuals with bipolar disorder and schizophrenia may have epigenetic markers associated with a premature aging phenotype, which could be suggestive of negative outcomes associated with the disease. In our future studies, we hope to elucidate this finding further by elucidating the precise link between epigenetic age, symptomatology and disease progression.
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Affiliation(s)
| | | | - Zanib Chaudhary
- Centre for Addiction and Mental Health (CAMH), Toronto, Canada
| | | | - Jessica Qian
- Centre for Addiction and Mental Health (CAMH), Toronto, Canada
| | - Clement Zai
- Centre for Addiction and Mental Health (CAMH), Toronto, Canada
| | | | | | | | - James L Kennedy
- Centre for Addiction and Mental Health (CAMH), Toronto, Canada
| | - Carol Borlido
- Centre for Addiction and Mental Health (CAMH), Toronto, Canada
| | | | - Ariel Graff
- Centre for Addiction and Mental Health (CAMH), Toronto, Canada
| | - Gary Remington
- Centre for Addiction and Mental Health (CAMH), Toronto, Canada
| | - John B Vincent
- Centre for Addiction and Mental Health (CAMH), Toronto, Canada
| | - John S Strauss
- Nanaimo Regional General Hospital, Vancouver Island Health Authority, British Columbia
| | - Vincenzo De Luca
- Centre for Addiction and Mental Health (CAMH), Toronto, Canada; St Michael's Hospital, Toronto, Canada.
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24
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Nwanaji-Enwerem JC, Mair WB. Redefining Age-Based Screening and Diagnostic Guidelines: An Opportunity for Biological Aging Clocks in Clinical Medicine? THE LANCET. HEALTHY LONGEVITY 2022; 3:e376-e377. [PMID: 36034882 PMCID: PMC9415968 DOI: 10.1016/s2666-7568(22)00114-3] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/14/2023] Open
Affiliation(s)
- Jamaji C. Nwanaji-Enwerem
- Gangarosa Department of Environmental Health, Emory Rollins School of Public Health and Department of Emergency Medicine, Emory University School of Medicine, Atlanta, GA, USA.,Correspondence to: Jamaji C. Nwanaji-Enwerem, Emory Rollins School of Public Health, Emory School of Medicine, Steiner Building, 68 Armstrong Street, Room 318, Atlanta, GA 30303, , Phone: 404.778.5975
| | - William B. Mair
- Department of Molecular Metabolism, Harvard TH Chan School of Public Health. MA. USA
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25
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Pavanello S, Campisi M, Rigotti P, Bello MD, Nuzzolese E, Neri F, Furian L. DNA Methylation - and Telomere - Based Biological Age Estimation as Markers of Biological Aging in Donors Kidneys. Front Med (Lausanne) 2022; 9:832411. [PMID: 35402460 PMCID: PMC8984253 DOI: 10.3389/fmed.2022.832411] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2021] [Accepted: 02/15/2022] [Indexed: 11/13/2022] Open
Abstract
The biological age of an organ may represent a valuable tool for assessing its quality, especially in the elder. We examined the biological age of the kidneys [right (RK) and left kidney (LK)] and blood leukocytes in the same subject and compared these to assess whether blood mirrors kidney biological aging. Biological age was studied in n = 36 donors (median age: 72 years, range: 19-92; male: 42%) by exploring mitotic and non-mitotic pathways, using telomere length (TL) and age-methylation changes (DNAmAge) and its acceleration (AgeAcc). RK and LK DNAmAge are older than blood DNAmAge (RK vs. Blood, p = 0.0271 and LK vs. Blood, p = 0.0245) and RK and LK AgeAcc present higher score (this mean the AgeAcc is faster) than that of blood leukocytes (p = 0.0271 and p = 0.0245) in the same donor. TL of RK and LK are instead longer than that of blood (p = 0.0011 and p = 0.0098) and the increase in Remuzzi-Karpinski score is strongly correlated with kidney TL attrition (p = 0.0046). Finally, blood and kidney TL (p < 0.01) and DNAmAge (p < 0.001) were correlated. These markers can be evaluated in further studies as indicators of biological age of donor organ quality and increase the usage of organs from donors of advanced age therefore offering a potential translational research inkidney transplantation.
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Affiliation(s)
- Sofia Pavanello
- Occupational Medicine, Department of Cardiac, Thoracic, and Vascular Sciences and Public Health, University Hospital of Padova, Padova, Italy
| | - Manuela Campisi
- Occupational Medicine, Department of Cardiac, Thoracic, and Vascular Sciences and Public Health, University Hospital of Padova, Padova, Italy
| | - Paolo Rigotti
- Kidney and Pancreas Transplantation Unit, Department of Surgery, Oncology and Gastroenterology, University Hospital of Padova, Padova, Italy
| | - Marianna Di Bello
- Kidney and Pancreas Transplantation Unit, Department of Surgery, Oncology and Gastroenterology, University Hospital of Padova, Padova, Italy
| | - Erica Nuzzolese
- Kidney and Pancreas Transplantation Unit, Department of Surgery, Oncology and Gastroenterology, University Hospital of Padova, Padova, Italy
| | - Flavia Neri
- Kidney and Pancreas Transplantation Unit, Department of Surgery, Oncology and Gastroenterology, University Hospital of Padova, Padova, Italy
| | - Lucrezia Furian
- Kidney and Pancreas Transplantation Unit, Department of Surgery, Oncology and Gastroenterology, University Hospital of Padova, Padova, Italy
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Martin CL, Ghastine L, Lodge EK, Dhingra R, Ward-Caviness CK. Understanding Health Inequalities Through the Lens of Social Epigenetics. Annu Rev Public Health 2022; 43:235-254. [PMID: 35380065 PMCID: PMC9584166 DOI: 10.1146/annurev-publhealth-052020-105613] [Citation(s) in RCA: 19] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022]
Abstract
Longstanding racial/ethnic inequalities in morbidity and mortality persist in the United States. Although the determinants of health inequalities are complex, social and structural factors produced by inequitable and racialized systems are recognized as contributing sources. Social epigenetics is an emerging area of research that aims to uncover biological pathways through which social experiences affect health outcomes. A growing body of literature links adverse social exposures to epigenetic mechanisms, namely DNA methylation, offering a plausible pathway through which health inequalities may arise. This review provides an overview of social epigenetics and highlights existing literature linking social exposures—i.e., psychosocial stressors, racism, discrimination, socioeconomic position, and neighborhood social environment—to DNA methylation in humans.We conclude with a discussion of social epigenetics as a mechanistic link to health inequalities and provide suggestions for future social epigenetics research on health inequalities.
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Affiliation(s)
- Chantel L Martin
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA; .,Carolina Population Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Lea Ghastine
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA;
| | - Evans K Lodge
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA; .,Carolina Population Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA.,School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Radhika Dhingra
- Department of Environmental Sciences and Engineering, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA.,Institute of Environmental Health Solutions, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Cavin K Ward-Caviness
- Center for Public Health and Environmental Assessment, US Environmental Protection Agency, Chapel Hill, North Carolina, USA
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Nwanaji‐Enwerem JC, Boileau P, Galazka JM, Cardenas A. In vitro relationships of galactic cosmic radiation and epigenetic clocks in human bronchial epithelial cells. ENVIRONMENTAL AND MOLECULAR MUTAGENESIS 2022; 63:184-189. [PMID: 35470505 PMCID: PMC9233067 DOI: 10.1002/em.22483] [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] [Subscribe] [Scholar Register] [Received: 03/19/2022] [Accepted: 04/22/2022] [Indexed: 06/14/2023]
Abstract
Ionizing radiation is a well-appreciated health risk, precipitant of DNA damage, and contributor to DNA methylation variability. Nevertheless, relationships of ionizing radiation with DNA methylation-based markers of biological age (i.e. epigenetic clocks) remain poorly understood. Using existing data from human bronchial epithelial cells, we examined in vitro relationships of three epigenetic clock measures (Horvath DNAmAge, MiAge, and epiTOC2) with galactic cosmic radiation (GCR), which is particularly hazardous due to its high linear energy transfer (LET) heavy-ion components. High-LET 56Fe was significantly associated with accelerations in epiTOC2 (β = 192 cell divisions, 95% CI: 71, 313, p-value = .003). We also observed a significant, positive interaction of 56Fe ions and time-in-culture with epiTOC2 (95% CI: 42, 441, p-value = .019). However, only the direct 56Fe ion association remained statistically significant after adjusting for multiple hypothesis testing. Epigenetic clocks were not significantly associated with high-LET 28Si and low-LET X-rays. Our results demonstrate sensitivities of specific epigenetic clock measures to certain forms of GCR. These findings suggest that epigenetic clocks may have some utility for monitoring and better understanding the health impacts of GCR.
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Affiliation(s)
- Jamaji C. Nwanaji‐Enwerem
- Gangarosa Department of Environmental Health, Emory Rollins School of Public Health, and Department of Emergency MedicineEmory University School of MedicineAtlantaGeorgiaUSA
- Division of Environmental Health Sciences, School of Public Health and Center for Computational BiologyUniversity of CaliforniaBerkeleyCaliforniaUSA
| | - Philippe Boileau
- Graduate Group in Biostatistics and Center for Computational BiologyUniversity of CaliforniaBerkeleyCaliforniaUSA
| | | | - Andres Cardenas
- Division of Environmental Health Sciences, School of Public Health and Center for Computational BiologyUniversity of CaliforniaBerkeleyCaliforniaUSA
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Malecki KMC, Andersen JK, Geller AM, Harry GJ, Jackson CL, James KA, Miller GW, Ottinger MA. Integrating Environment and Aging Research: Opportunities for Synergy and Acceleration. Front Aging Neurosci 2022; 14:824921. [PMID: 35264945 PMCID: PMC8901047 DOI: 10.3389/fnagi.2022.824921] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2021] [Accepted: 01/12/2022] [Indexed: 12/25/2022] Open
Abstract
Despite significant overlaps in mission, the fields of environmental health sciences and aging biology are just beginning to intersect. It is increasingly clear that genetics alone does not predict an individual’s neurological aging and sensitivity to disease. Accordingly, aging neuroscience is a growing area of mutual interest within environmental health sciences. The impetus for this review came from a workshop hosted by the National Academies of Sciences, Engineering, and Medicine in June of 2020, which focused on integrating the science of aging and environmental health research. It is critical to bridge disciplines with multidisciplinary collaborations across toxicology, comparative biology, epidemiology to understand the impacts of environmental toxicant exposures and age-related outcomes. This scoping review aims to highlight overlaps and gaps in existing knowledge and identify essential research initiatives. It begins with an overview of aging biology and biomarkers, followed by examples of synergy with environmental health sciences. New areas for synergistic research and policy development are also discussed. Technological advances including next-generation sequencing and other-omics tools now offer new opportunities, including exposomic research, to integrate aging biomarkers into environmental health assessments and bridge disciplinary gaps. This is necessary to advance a more complete mechanistic understanding of how life-time exposures to toxicants and other physical and social stressors alter biological aging. New cumulative risk frameworks in environmental health sciences acknowledge that exposures and other external stressors can accumulate across the life course and the advancement of new biomarkers of exposure and response grounded in aging biology can support increased understanding of population vulnerability. Identifying the role of environmental stressors, broadly defined, on aging biology and neuroscience can similarly advance opportunities for intervention and translational research. Several areas of growing research interest include expanding exposomics and use of multi-omics, the microbiome as a mediator of environmental stressors, toxicant mixtures and neurobiology, and the role of structural and historical marginalization and racism in shaping persistent disparities in population aging and outcomes. Integrated foundational and translational aging biology research in environmental health sciences is needed to improve policy, reduce disparities, and enhance the quality of life for older individuals.
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Affiliation(s)
- Kristen M. C. Malecki
- Department of Population Health Sciences, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, United States
- *Correspondence: Kristen M. C. Malecki,
| | | | - Andrew M. Geller
- United States Environmental Protection Agency, Office of Research and Development, Durham, NC, United States
| | - G. Jean Harry
- Division of National Toxicology Program, National Institute of Environmental Health Sciences, Durham, NC, United States
| | - Chandra L. Jackson
- Division of Intramural Research, Department of Health and Human Services, Epidemiology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Durham, NC, United States
- Department of Health and Human Services, National Institute on Minority Health and Health Disparities, National Institutes of Health, Bethesda, MD, United States
| | - Katherine A. James
- Department of Environmental and Occupational Health, Colorado School of Public Health, University of Colorado Denver, Denver, CO, United States
| | - Gary W. Miller
- Department of Environmental Health Sciences, Columbia University Mailman School of Public Health, New York, NY, United States
| | - Mary Ann Ottinger
- Department of Biology and Biochemistry, University of Houston, Houston, TX, United States
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Abstract
PURPOSE OF REVIEW With cardiovascular disease (CVD) being the top cause of deaths worldwide, it is important to ensure healthy cardiovascular aging through enhanced understanding and prevention of adverse health effects exerted by external factors. This review aims to provide an updated understanding of environmental influences on cardiovascular aging, by summarizing epidemiological and mechanistic evidence for the cardiovascular health impact of major environmental stressors, including air pollution, endocrine-disrupting chemicals (EDCs), metals, and climate change. RECENT FINDINGS Recent studies generally support positive associations of exposure to multiple chemical environmental stressors (air pollution, EDCs, toxic metals) and extreme temperatures with increased risks of cardiovascular mortality and morbidity in the population. Environmental stressors have also been associated with a number of cardiovascular aging-related subclinical changes including biomarkers in the population, which are supported by evidence from relevant experimental studies. The elderly and patients are the most vulnerable demographic groups to majority environmental stressors. Future studies should account for the totality of individuals' exposome in addition to single chemical pollutants or environmental factors. Specific factors most responsible for the observed health effects related to cardiovascular aging remain to be elucidated.
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Affiliation(s)
- Yang Lan
- Department of Occupational and Environmental Health, School of Public Health, Xi'an Jiaotong University Health Science Center, 76 Yanta West Road, Yanta District, Xi'an City, Shaanxi Province, 710061, People's Republic of China
- Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, Xi'an, Shaanxi, China
- Key Laboratory of Trace Elements and Endemic Diseases in Ministry of Health, Xi'an, Shaanxi, China
| | - Shaowei Wu
- Department of Occupational and Environmental Health, School of Public Health, Xi'an Jiaotong University Health Science Center, 76 Yanta West Road, Yanta District, Xi'an City, Shaanxi Province, 710061, People's Republic of China.
- Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, Xi'an, Shaanxi, China.
- Key Laboratory of Trace Elements and Endemic Diseases in Ministry of Health, Xi'an, Shaanxi, China.
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30
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Sleep Health among Racial/Ethnic groups and Strategies to achieve Sleep Health Equity. Respir Med 2022. [DOI: 10.1007/978-3-030-93739-3_3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
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31
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van der Laan L, Cardenas A, Vermeulen R, Fadadu RP, Hubbard AE, Phillips RV, Zhang L, Breeze C, Hu W, Wen C, Huang Y, Tang X, Smith MT, Rothman N, Lan Q. Epigenetic aging biomarkers and occupational exposure to benzene, trichloroethylene and formaldehyde. ENVIRONMENT INTERNATIONAL 2022; 158:106871. [PMID: 34560324 PMCID: PMC9084243 DOI: 10.1016/j.envint.2021.106871] [Citation(s) in RCA: 18] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/10/2021] [Revised: 09/02/2021] [Accepted: 09/07/2021] [Indexed: 05/23/2023]
Abstract
Epigenetic aging biomarkers are associated with increased morbidity and mortality. We evaluated if occupational exposure to three established chemical carcinogens is associated with acceleration of epigenetic aging. We studied workers in China occupationally exposed to benzene, trichloroethylene (TCE) or formaldehyde by measuring personal air exposures prior to blood collection. Unexposed controls matched by age and sex were selected from nearby factories. We measured leukocyte DNA methylation (DNAm) in peripheral white blood cells using the Infinium HumanMethylation450 BeadChip to calculate five epigenetic aging clocks and DNAmTL, a biomarker associated with leukocyte telomere length and cell replication. We tested associations between exposure intensity and epigenetic age acceleration (EAA), defined as the residuals of regressing the DNAm aging biomarker on chronological age, matching factors and potential confounders. Median differences in EAA between exposure groups were tested using a permutation test with exact p-values. Epigenetic clocks were strongly correlated with age (Spearman r > 0.8) in all three occupational studies. There was a positive exposure-response relationship between benzene and the Skin-Blood Clock EAA biomarker: median EAA was -0.91 years in controls (n = 44), 0.78 years in workers exposed to <10 ppm (n = 41; mean benzene = 1.35 ppm; p = 0.034 vs. controls), and 2.10 years in workers exposed to ≥10 ppm (n = 9; mean benzene = 27.3 ppm; p = 0.019 vs. controls; ptrend = 0.0021). In the TCE study, control workers had a median Skin-Blood Clock EAA of -0.54 years (n = 71) compared to 1.63 years among workers exposed to <10 ppm of TCE (n = 27; mean TCE = 4.22 ppm; p = 0.035). We observed no evidence of EAA associations with formaldehyde exposure (39 controls, 31 exposed). Occupational benzene and TCE exposure were associated with increased epigenetic age acceleration measured by the Skin-Blood Clock. For TCE, there was some evidence of epigenetic age acceleration for lower exposures compared to controls. Our results suggest that some chemical carcinogens may accelerate epigenetic aging.
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Affiliation(s)
- Lars van der Laan
- Divisions of Environmental Health Sciences and Biostatistics, School of Public Health, University of California, Berkeley, 2121 Berkeley Way #5302, Berkeley, CA 94704, USA
| | - Andres Cardenas
- Divisions of Environmental Health Sciences and Biostatistics, School of Public Health, University of California, Berkeley, 2121 Berkeley Way #5302, Berkeley, CA 94704, USA; Center for Computational Biology, University of California, Berkeley, 108 Stanley Hall, Berkeley, CA 94720, USA.
| | - Roel Vermeulen
- Institute for Risk Assessment Sciences (IRAS), Utrecht University, Yalelaan 2, Utrecht, 3584CM, Netherlands
| | - Raj P Fadadu
- Divisions of Environmental Health Sciences and Biostatistics, School of Public Health, University of California, Berkeley, 2121 Berkeley Way #5302, Berkeley, CA 94704, USA
| | - Alan E Hubbard
- Divisions of Environmental Health Sciences and Biostatistics, School of Public Health, University of California, Berkeley, 2121 Berkeley Way #5302, Berkeley, CA 94704, USA; Center for Computational Biology, University of California, Berkeley, 108 Stanley Hall, Berkeley, CA 94720, USA
| | - Rachael V Phillips
- Divisions of Environmental Health Sciences and Biostatistics, School of Public Health, University of California, Berkeley, 2121 Berkeley Way #5302, Berkeley, CA 94704, USA; Center for Computational Biology, University of California, Berkeley, 108 Stanley Hall, Berkeley, CA 94720, USA
| | - Luoping Zhang
- Divisions of Environmental Health Sciences and Biostatistics, School of Public Health, University of California, Berkeley, 2121 Berkeley Way #5302, Berkeley, CA 94704, USA
| | - Charles Breeze
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, 9609 Medical Center Drive, Rockville, MD 20850, USA
| | - Wei Hu
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, 9609 Medical Center Drive, Rockville, MD 20850, USA
| | - Cuiju Wen
- Guangdong Poison Control Center, Guangzhou, China
| | | | - Xiaojiang Tang
- Guangdong Medical Laboratory Animal Center, Foshan 528248, Guangdong, China
| | - Martyn T Smith
- Divisions of Environmental Health Sciences and Biostatistics, School of Public Health, University of California, Berkeley, 2121 Berkeley Way #5302, Berkeley, CA 94704, USA
| | - Nathaniel Rothman
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, 9609 Medical Center Drive, Rockville, MD 20850, USA
| | - Qing Lan
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, 9609 Medical Center Drive, Rockville, MD 20850, USA
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32
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Ward-Caviness CK. Accelerated Epigenetic Aging and Incident Atrial Fibrillation: New Outlook on an Immutable Risk Factor? Circulation 2021; 144:1912-1914. [PMID: 34898242 PMCID: PMC9070310 DOI: 10.1161/circulationaha.121.057533] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Affiliation(s)
- Cavin K Ward-Caviness
- Center for Public Health and Environmental Assessment, US Environmental Protection Agency, Chapel Hill, NC
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33
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Becker J, Böhme P, Reckert A, Eickhoff SB, Koop BE, Blum J, Gündüz T, Takayama M, Wagner W, Ritz-Timme S. Evidence for differences in DNA methylation between Germans and Japanese. Int J Legal Med 2021; 136:405-413. [PMID: 34739581 PMCID: PMC8847189 DOI: 10.1007/s00414-021-02736-3] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2021] [Accepted: 10/22/2021] [Indexed: 12/16/2022]
Abstract
As a contribution to the discussion about the possible effects of ethnicity/ancestry on age estimation based on DNA methylation (DNAm) patterns, we directly compared age-associated DNAm in German and Japanese donors in one laboratory under identical conditions. DNAm was analyzed by pyrosequencing for 22 CpG sites (CpGs) in the genes PDE4C, RPA2, ELOVL2, DDO, and EDARADD in buccal mucosa samples from German and Japanese donors (N = 368 and N = 89, respectively). Twenty of these CpGs revealed a very high correlation with age and were subsequently tested for differences between German and Japanese donors aged between 10 and 65 years (N = 287 and N = 83, respectively). ANCOVA was performed by testing the Japanese samples against age- and sex-matched German subsamples (N = 83 each; extracted 500 times from the German total sample). The median p values suggest a strong evidence for significant differences (p < 0.05) at least for two CpGs (EDARADD, CpG 2, and PDE4C, CpG 2) and no differences for 11 CpGs (p > 0.3). Age prediction models based on DNAm data from all 20 CpGs from German training data did not reveal relevant differences between the Japanese test samples and German subsamples. Obviously, the high number of included “robust CpGs” prevented relevant effects of differences in DNAm at two CpGs. Nevertheless, the presented data demonstrates the need for further research regarding the impact of confounding factors on DNAm in the context of ethnicity/ancestry to ensure a high quality of age estimation. One approach may be the search for “robust” CpG markers—which requires the targeted investigation of different populations, at best by collaborative research with coordinated research strategies.
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Affiliation(s)
- J Becker
- Institute of Legal Medicine, University Hospital Düsseldorf, 40225, Düsseldorf, Germany.
| | - P Böhme
- Institute of Legal Medicine, University Hospital Düsseldorf, 40225, Düsseldorf, Germany
| | - A Reckert
- Institute of Legal Medicine, University Hospital Düsseldorf, 40225, Düsseldorf, Germany
| | - S B Eickhoff
- Institute for Systems Neuroscience, University Hospital Düsseldorf, 40225, Düsseldorf, Germany.,Institute of Neuroscience and Medicine, Brain and Behaviour, (INM-7), Research Centre Jülich, 52428, Jülich, Germany
| | - B E Koop
- Institute of Legal Medicine, University Hospital Düsseldorf, 40225, Düsseldorf, Germany
| | - J Blum
- Institute of Legal Medicine, University Hospital Düsseldorf, 40225, Düsseldorf, Germany
| | - T Gündüz
- Institute of Legal Medicine, University Hospital Düsseldorf, 40225, Düsseldorf, Germany
| | - M Takayama
- Department of Forensic Medicine, Faculty of Medicine, Fukuoka University, Fukuoka, Japan.,Tokyo Medical Examiner's Office, Tokyo, Japan
| | - W Wagner
- Helmholtz Institute for Biomedical Engineering, Stem Cell Biology and Cellular Engineering, RWTH Aachen University Medical School, 52074, Aachen, Germany
| | - S Ritz-Timme
- Institute of Legal Medicine, University Hospital Düsseldorf, 40225, Düsseldorf, Germany
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Abstract
PURPOSE OF REVIEW Both social and genetic factors are associated with health outcomes in systemic lupus erythematosus (SLE), thus playing a role in its health disparities. Despite the growing list of social and genetic factors associated with SLE outcomes, studies integrating sociocultural and individual determinants of health to understand health disparities in SLE are lacking. We review the contributions of different social and genetic factors to the disparities in SLE, and propose a socioecological model to integrate and examine the complex interactions between individual and social factors in SLE outcomes. RECENT FINDINGS Multiple studies collecting comprehensive social data and biospecimens from diverse populations are underway, which will contribute to the elucidation of the interplay and underlying mechanisms by which positive and negative social determinants of health influence epigenomic variation, and how the resulting biological changes may contribute to the lupus health disparities. SUMMARY There is growing awareness of the need to integrate genomic and health disparities research to understand how social exposures affect disease outcomes. Understanding the contributions of these factors to the SLE health disparity will inform the development of interventions to eliminate risk exposures and close the health disparity gap.
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Qi H, Kinoshita K, Mori T, Matsumoto K, Matsui Y, Inoue-Murayama M. Age estimation using methylation-sensitive high-resolution melting (MS-HRM) in both healthy felines and those with chronic kidney disease. Sci Rep 2021; 11:19963. [PMID: 34620957 PMCID: PMC8497492 DOI: 10.1038/s41598-021-99424-4] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2021] [Accepted: 09/22/2021] [Indexed: 11/12/2022] Open
Abstract
Age is an important ecological tool in wildlife conservation. However, it is difficult to estimate in most animals, including felines-most of whom are endangered. Here, we developed the first DNA methylation-based age-estimation technique-as an alternative to current age-estimation methods-for two feline species that share a relatively long genetic distance with each other: domestic cat (Felis catus; 79 blood samples) and an endangered Panthera, the snow leopard (Panthera uncia; 11 blood samples). We measured the methylation rates of two gene regions using methylation-sensitive high-resolution melting (MS-HRM). Domestic cat age was estimated with a mean absolute deviation (MAD) of 3.83 years. Health conditions influenced accuracy of the model. Specifically, the models built on cats with chronic kidney disease (CKD) had lower accuracy than those built on healthy cats. The snow leopard-specific model (i.e. the model that resets the model settings for snow leopards) had a better accuracy (MAD = 2.10 years) than that obtained on using the domestic cat model directly. This implies that our markers could be utilised across species, although changing the model settings when targeting different species could lead to better estimation accuracy. The snow leopard-specific model also successfully distinguished between sexually immature and mature individuals.
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Affiliation(s)
- Huiyuan Qi
- Wildlife Research Center, Kyoto University, Kyoto, 606-8203, Japan
| | - Kodzue Kinoshita
- Wildlife Research Center, Kyoto University, Kyoto, 606-8203, Japan
| | - Takashi Mori
- Kyoto Medical Center, Daktari Animal Hospital, Kyoto, 615-8234, Japan
| | - Kaori Matsumoto
- Kyoto Medical Center, Daktari Animal Hospital, Kyoto, 615-8234, Japan
- Miyazaki Prefectural Miyakonojo Livestock Hygiene Service Center, Miyazaki, 889-4505, Japan
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36
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Campisi M, Liviero F, Maestrelli P, Guarnieri G, Pavanello S. DNA Methylation-Based Age Prediction and Telomere Length Reveal an Accelerated Aging in Induced Sputum Cells Compared to Blood Leukocytes: A Pilot Study in COPD Patients. Front Med (Lausanne) 2021; 8:690312. [PMID: 34368190 PMCID: PMC8342924 DOI: 10.3389/fmed.2021.690312] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2021] [Accepted: 06/08/2021] [Indexed: 11/13/2022] Open
Abstract
Aging is the predominant risk factor for most degenerative diseases, including chronic obstructive pulmonary disease (COPD). This process is however very heterogeneous. Defining the biological aging of individual tissues may contribute to better assess this risky process. In this study, we examined the biological age of induced sputum (IS) cells, and peripheral blood leukocytes in the same subject, and compared these to assess whether biological aging of blood leukocytes mirrors that of IS cells. Biological aging was assessed in 18 COPD patients (72.4 ± 7.7 years; 50% males). We explored mitotic and non-mitotic aging pathways, using telomere length (TL) and DNA methylation-based age prediction (DNAmAge) and age acceleration (AgeAcc) (i.e., difference between DNAmAge and chronological age). Data on demographics, life style and occupational exposure, lung function, and clinical and blood parameters were collected. DNAmAge (67.4 ± 5.80 vs. 61.6 ± 5.40 years; p = 0.0003), AgeAcc (-4.5 ± 5.02 vs. -10.8 ± 3.50 years; p = 0.0003), and TL attrition (1.05 ± 0.35 vs. 1.48 ± 0.21 T/S; p = 0.0341) are higher in IS cells than in blood leukocytes in the same patients. Blood leukocytes DNAmAge (r = 0.927245; p = 0.0026) and AgeAcc (r = 0.916445; p = 0.0037), but not TL, highly correlate with that of IS cells. Multiple regression analysis shows that both blood leukocytes DNAmAge and AgeAcc decrease (i.e., younger) in patients with FEV1% enhancement (p = 0.0254 and p = 0.0296) and combined inhaled corticosteroid (ICS) therapy (p = 0.0494 and p = 0.0553). In conclusion, new findings from our work reveal a differential aging in the context of COPD, by a direct quantitative comparison of cell aging in the airway with that in the more accessible peripheral blood leukocytes, providing additional knowledge which could offer a potential translation into the disease management.
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Affiliation(s)
- Manuela Campisi
- Occupational Medicine, Department of Cardiac, Thoracic, and Vascular Sciences and Public Health, University Hospital of Padua, Padua, Italy
| | - Filippo Liviero
- Occupational Medicine, Department of Cardiac, Thoracic, and Vascular Sciences and Public Health, University Hospital of Padua, Padua, Italy
| | - Piero Maestrelli
- Occupational Medicine, Department of Cardiac, Thoracic, and Vascular Sciences and Public Health, University Hospital of Padua, Padua, Italy
| | - Gabriella Guarnieri
- Respiratory Pathophysiology Unit, Department of Cardiac, Thoracic, and Vascular Sciences and Public Health, University Hospital of Padua, Padua, Italy
| | - Sofia Pavanello
- Occupational Medicine, Department of Cardiac, Thoracic, and Vascular Sciences and Public Health, University Hospital of Padua, Padua, Italy
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37
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Kim Y, Huan T, Joehanes R, McKeown NM, Horvath S, Levy D, Ma J. Higher diet quality relates to decelerated epigenetic aging. Am J Clin Nutr 2021; 115:163-170. [PMID: 34134146 PMCID: PMC8755029 DOI: 10.1093/ajcn/nqab201] [Citation(s) in RCA: 35] [Impact Index Per Article: 11.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2021] [Accepted: 05/26/2021] [Indexed: 12/11/2022] Open
Abstract
BACKGROUND DNA methylation-based epigenetic age measures have been used as biological aging markers and are associated with a healthy lifespan. Few population-based studies have examined the relation between diet and epigenetic age acceleration. OBJECTIVES We aimed to investigate the relation between diet quality and epigenetic age acceleration. METHODS We analyzed data from 1995 participants (mean age, 67 years; 55% women) of the Framingham Heart Study Offspring Cohort. Cross-sectional associations between the Dietary Approaches to Stop Hypertension (DASH) score and 3 whole-blood DNA methylation-derived epigenetic age acceleration measures-Dunedin Pace of Aging Methylation (DunedinPoAm), GrimAge acceleration (GrimAA), and PhenoAge acceleration (PhenoAA)-were examined. A mediation analysis was conducted to assess the mediating role of epigenetic age acceleration in relation to DASH and all-cause mortality. RESULTS A higher DASH score was associated with lower levels of DunedinPoAm (β = -0.05; SE = 0.02; P = 0.007), GrimAA (β = -0.09; SE = 0.02; P < 0.001), and PhenoAA (β = -0.07; SE = 0.02; P = 0.001). All 3 epigenetic measures mediated the association between the DASH score and all-cause mortality, with mean proportions of 22.1% for DunedinPoAm (Pmediation = 0.04), 45.1% for GrimAA (Pmediation = 0.001), and 22.9% for PhenoAA (Pmediation = 0.03). An interaction was observed between the DASH score and smoking status in relation to the epigenetic aging markers. The association between the DASH score and epigenetic aging markers tended to be stronger in "ever-smokers" (former and current smokers) compared to "never-smokers." The proportions of mediation were 31.3% for DunedinPoAm, 46.8% for GrimAA, and 10.3% for PhenoAA in ever-smokers, whereas no significant mediation was observed in never-smokers. CONCLUSIONS Higher diet quality is associated with slower epigenetic age acceleration, which partially explains the beneficial effect of diet quality on the lifespan. Our findings emphasize that adopting a healthy diet is crucial for maintaining healthy aging.
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Affiliation(s)
- Youjin Kim
- Nutrition Epidemiology and Data Science, Friedman School of Nutrition Science and Policy, Tufts University, Boston, MA, USA
| | - Tianxiao Huan
- Department of Ophthalmology and Visual Sciences, University of Massachusetts Medical School, Worcester, MA, USA
| | - Roby Joehanes
- Population Sciences Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD & Framingham Heart Study, Framingham, MA, USA
| | - Nicola M McKeown
- Nutrition Epidemiology and Data Science, Friedman School of Nutrition Science and Policy, Tufts University, Boston, MA, USA,Nutritional Epidemiology Laboratory, Jean Mayer USDA Human Nutrition Research Center on Aging, Tufts University, Boston, MA, USA
| | - Steve Horvath
- Department of Human Genetics, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA,Department of Biostatistics, Fielding School of Public Health, University of California Los Angeles, Los Angeles, CA, USA
| | - Daniel Levy
- Population Sciences Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD & Framingham Heart Study, Framingham, MA, USA
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Matías-García PR, Ward-Caviness CK, Raffield LM, Gao X, Zhang Y, Wilson R, Gào X, Nano J, Bostom A, Colicino E, Correa A, Coull B, Eaton C, Hou L, Just AC, Kunze S, Lange L, Lange E, Lin X, Liu S, Nwanaji-Enwerem JC, Reiner A, Shen J, Schöttker B, Vokonas P, Zheng Y, Young B, Schwartz J, Horvath S, Lu A, Whitsel EA, Koenig W, Adamski J, Winkelmann J, Brenner H, Baccarelli AA, Gieger C, Peters A, Franceschini N, Waldenberger M. DNAm-based signatures of accelerated aging and mortality in blood are associated with low renal function. Clin Epigenetics 2021; 13:121. [PMID: 34078457 PMCID: PMC8170969 DOI: 10.1186/s13148-021-01082-w] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2020] [Accepted: 04/18/2021] [Indexed: 01/30/2023] Open
Abstract
BACKGROUND The difference between an individual's chronological and DNA methylation predicted age (DNAmAge), termed DNAmAge acceleration (DNAmAA), can capture life-long environmental exposures and age-related physiological changes reflected in methylation status. Several studies have linked DNAmAA to morbidity and mortality, yet its relationship with kidney function has not been assessed. We evaluated the associations between seven DNAm aging and lifespan predictors (as well as GrimAge components) and five kidney traits (estimated glomerular filtration rate [eGFR], urine albumin-to-creatinine ratio [uACR], serum urate, microalbuminuria and chronic kidney disease [CKD]) in up to 9688 European, African American and Hispanic/Latino individuals from seven population-based studies. RESULTS We identified 23 significant associations in our large trans-ethnic meta-analysis (p < 1.43E-03 and consistent direction of effect across studies). Age acceleration measured by the Extrinsic and PhenoAge estimators, as well as Zhang's 10-CpG epigenetic mortality risk score (MRS), were associated with all parameters of poor kidney health (lower eGFR, prevalent CKD, higher uACR, microalbuminuria and higher serum urate). Six of these associations were independently observed in European and African American populations. MRS in particular was consistently associated with eGFR (β = - 0.12, 95% CI = [- 0.16, - 0.08] change in log-transformed eGFR per unit increase in MRS, p = 4.39E-08), prevalent CKD (odds ratio (OR) = 1.78 [1.47, 2.16], p = 2.71E-09) and higher serum urate levels (β = 0.12 [0.07, 0.16], p = 2.08E-06). The "first-generation" clocks (Hannum, Horvath) and GrimAge showed different patterns of association with the kidney traits. Three of the DNAm-estimated components of GrimAge, namely adrenomedullin, plasminogen-activation inhibition 1 and pack years, were positively associated with higher uACR, serum urate and microalbuminuria. CONCLUSION DNAmAge acceleration and DNAm mortality predictors estimated in whole blood were associated with multiple kidney traits, including eGFR and CKD, in this multi-ethnic study. Epigenetic biomarkers which reflect the systemic effects of age-related mechanisms such as immunosenescence, inflammaging and oxidative stress may have important mechanistic or prognostic roles in kidney disease. Our study highlights new findings linking kidney disease to biological aging, and opportunities warranting future investigation into DNA methylation biomarkers for prognostic or risk stratification in kidney disease.
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Affiliation(s)
- Pamela R Matías-García
- TUM School of Medicine, Technical University of Munich, Munich, Germany.
- Research Unit Molecular Epidemiology, Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Munich/Neuherberg, Germany.
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Munich/Neuherberg, Germany.
- German Center for Cardiovascular Research (DZHK), Partner Site Munich Heart Alliance, Munich, Germany.
| | - Cavin K Ward-Caviness
- Center for Public Health and Environmental Assessment, US Environmental Protection Agency, Chapel Hill, NC, USA
| | - Laura M Raffield
- Department of Genetics, University of North Carolina, Chapel Hill, NC, USA
| | - Xu Gao
- Laboratory of Precision Environmental Health, Mailman School of Public Health, Columbia University, New York, NY, USA
| | - Yan Zhang
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Heidelberg, Germany
- German Cancer Consortium (DKTK), German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Rory Wilson
- Research Unit Molecular Epidemiology, Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Munich/Neuherberg, Germany
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Munich/Neuherberg, Germany
| | - Xīn Gào
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Jana Nano
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Munich/Neuherberg, Germany
- German Center for Diabetes Research (DZD), Neuherberg, Germany
| | - Andrew Bostom
- Center For Primary Care and Prevention, Memorial Hospital of Rhode Island, Pawtucket, RI, USA
| | - Elena Colicino
- Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Adolfo Correa
- Departments of Medicine and Pediatrics, University of Mississippi Medical Center, Jackson, MS, USA
| | - Brent Coull
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Charles Eaton
- Center For Primary Care and Prevention, Memorial Hospital of Rhode Island, Pawtucket, RI, USA
- Department of Family Medicine, Warren Alpert Medical School, Brown University, Providence, RI, USA
| | - Lifang Hou
- Department of Preventive Medicine, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
| | - Allan C Just
- Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Sonja Kunze
- Research Unit Molecular Epidemiology, Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Munich/Neuherberg, Germany
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Munich/Neuherberg, Germany
| | - Leslie Lange
- Department of Medicine, University of Colorado Denver, Anschutz Medical Campus, Aurora, CO, USA
| | - Ethan Lange
- Department of Medicine, University of Colorado Denver, Anschutz Medical Campus, Aurora, CO, USA
| | - Xihong Lin
- Veterans Affairs Normative Aging Study, Veterans Affairs Boston Healthcare System, Department of Medicine, Boston University School of Medicine, Boston, MA, USA
| | - Simin Liu
- Department of Epidemiology, School of Public Health, Brown University, Providence, RI, USA
| | | | - Alex Reiner
- Department of Epidemiology, University of Washington, Seattle, WA, USA
| | - Jincheng Shen
- Department of Population Health Sciences, School of Medicine, University of Utah, Salt Lake City, UT, USA
| | - Ben Schöttker
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Heidelberg, Germany
- Network Aging Research, University of Heidelberg, Heidelberg, Germany
| | - Pantel Vokonas
- Veterans Affairs Normative Aging Study, Veterans Affairs Boston Healthcare System, Department of Medicine, Boston University School of Medicine, Boston, MA, USA
| | - Yinan Zheng
- Department of Preventive Medicine, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
| | - Bessie Young
- Nephrology, Hospital and Specialty Medicine and Center for Innovation for Veteran-Centered and Value Driven Care, Veterans Affairs Puget Sound Health Care System, Seattle, WA, USA
- Division of Nephrology, Kidney Research Institute, University of Washington, Seattle, WA, USA
| | - Joel Schwartz
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Steve Horvath
- Department of Human Genetics, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Ake Lu
- Department of Human Genetics, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Eric A Whitsel
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC, USA
- Department of Medicine, School of Medicine, University of North Carolina, Chapel Hill, NC, USA
| | - Wolfgang Koenig
- German Center for Cardiovascular Research (DZHK), Partner Site Munich Heart Alliance, Munich, Germany
- Deutsches Herzzentrum München, Technische Universität München, Munich, Germany
- Institute of Epidemiology and Medical Biometry, University of Ulm, Ulm, Germany
| | - Jerzy Adamski
- Research Unit Molecular Endocrinology and Metabolism, Genome Analysis Center, Helmholtz Zentrum München, German Research Center for Environmental Health, Munich/Neuherberg, Germany
- Chair for Experimental Genetics, Technical University of Munich, Freising-Weihenstephan, Germany
- Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Juliane Winkelmann
- Institute of Neurogenomics, Helmholtz Zentrum München, German Research Center for Environmental Health, Munich/Neuherberg, Germany
- Chair Neurogenetics, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
- Institute of Human Genetics, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
- Munich Cluster for Systems Neurology (SyNergy), Munich, Germany
| | - Hermann Brenner
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Heidelberg, Germany
- Network Aging Research, University of Heidelberg, Heidelberg, Germany
| | - Andrea A Baccarelli
- Laboratory of Precision Environmental Health, Mailman School of Public Health, Columbia University, New York, NY, USA
| | - Christian Gieger
- Research Unit Molecular Epidemiology, Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Munich/Neuherberg, Germany
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Munich/Neuherberg, Germany
| | - Annette Peters
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Munich/Neuherberg, Germany
- German Center for Cardiovascular Research (DZHK), Partner Site Munich Heart Alliance, Munich, Germany
- German Center for Diabetes Research (DZD), Neuherberg, Germany
| | - Nora Franceschini
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC, USA
| | - Melanie Waldenberger
- Research Unit Molecular Epidemiology, Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Munich/Neuherberg, Germany.
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Munich/Neuherberg, Germany.
- German Center for Cardiovascular Research (DZHK), Partner Site Munich Heart Alliance, Munich, Germany.
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Rytel MR, Butler R, Eliot M, Braun JM, Houseman EA, Kelsey KT. DNA methylation in the adipose tissue and whole blood of Agent Orange-exposed Operation Ranch Hand veterans: a pilot study. Environ Health 2021; 20:43. [PMID: 33849548 PMCID: PMC8045317 DOI: 10.1186/s12940-021-00717-y] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2020] [Accepted: 03/08/2021] [Indexed: 05/26/2023]
Abstract
BACKGROUND Between 1962 and 1971, the US Air Force sprayed Agent Orange across Vietnam, exposing many soldiers to this dioxin-containing herbicide. Several negative health outcomes have been linked to Agent Orange exposure, but data is lacking on the effects this chemical has on the genome. Therefore, we sought to characterize the impact of Agent Orange exposure on DNA methylation in the whole blood and adipose tissue of veterans enrolled in the Air Force Health Study (AFHS). METHODS We received adipose tissue (n = 37) and whole blood (n = 42) from veterans in the AFHS. Study participants were grouped as having low, moderate, or high TCDD body burden based on their previously measured serum levels of dioxin. DNA methylation was assessed using the Illumina 450 K platform. RESULTS Epigenome-wide analysis indicated that there were no FDR-significantly methylated CpGs in either tissue with TCDD burden. However, 3 CpGs in the adipose tissue (contained within SLC9A3, LYNX1, and TNRC18) were marginally significantly (q < 0.1) hypomethylated, and 1 CpG in whole blood (contained within PTPRN2) was marginally significantly (q < 0.1) hypermethylated with high TCDD burden. Analysis for differentially methylated DNA regions yielded SLC9A3, among other regions in adipose tissue, to be significantly differentially methylated with higher TCDD burden. Comparing whole blood data to a study of dioxin exposed adults from Alabama identified a CpG within the gene SMO that was hypomethylated with dioxin exposure in both studies. CONCLUSION We found limited evidence of dioxin associated DNA methylation in adipose tissue and whole blood in this pilot study of Vietnam War veterans. Nevertheless, loci in the genes of SLC9A3 in adipose tissue, and PTPRN2 and SMO in whole blood, should be included in future exposure analyses.
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Affiliation(s)
- Matthew R. Rytel
- Department of Epidemiology, Brown University School of Public Health, Providence, RI 02912 USA
| | - Rondi Butler
- Department of Epidemiology, Brown University School of Public Health, Providence, RI 02912 USA
- Department of Pathology and Laboratory Medicine, Brown University School of Public Health, Providence, RI 02912 USA
| | - Melissa Eliot
- Department of Epidemiology, Brown University School of Public Health, Providence, RI 02912 USA
| | - Joseph M. Braun
- Department of Epidemiology, Brown University School of Public Health, Providence, RI 02912 USA
| | - E. Andres Houseman
- Statistical Bioinformatics, GlaxoSmithKline, 1250 S Collegeville Rd, Collegeville, PA 19426 USA
| | - Karl T. Kelsey
- Department of Epidemiology, Brown University School of Public Health, Providence, RI 02912 USA
- Department of Pathology and Laboratory Medicine, Brown University School of Public Health, Providence, RI 02912 USA
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Cerveira de Baumont A, Hoffmann MS, Bortoluzzi A, Fries GR, Lavandoski P, Grun LK, Guimarães LSP, Guma FTCR, Salum GA, Barbé-Tuana FM, Manfro GG. Telomere length and epigenetic age acceleration in adolescents with anxiety disorders. Sci Rep 2021; 11:7716. [PMID: 33833304 PMCID: PMC8032711 DOI: 10.1038/s41598-021-87045-w] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2020] [Accepted: 03/16/2021] [Indexed: 02/01/2023] Open
Abstract
Evidence on the relationship between genetics and mental health are flourishing. However, few studies are evaluating early biomarkers that might link genes, environment, and psychopathology. We aimed to study telomere length (TL) and epigenetic age acceleration (AA) in a cohort of adolescents with and without anxiety disorders (N = 234). We evaluated a representative subsample of participants at baseline and after 5 years (n = 76) and categorized them according to their anxiety disorder diagnosis at both time points: (1) control group (no anxiety disorder, n = 18), (2) variable group (anxiety disorder in one evaluation, n = 38), and (3) persistent group (anxiety disorder at both time points, n = 20). We assessed relative mean TL by real-time quantitative PCR and DNA methylation by Infinium HumanMethylation450 BeadChip. We calculated AA using the Horvath age estimation algorithm and analyzed differences among groups using generalized linear mixed models. The persistent group of anxiety disorder did not change TL over time (p = 0.495). The variable group had higher baseline TL (p = 0.003) but no accelerated TL erosion in comparison to the non-anxiety control group (p = 0.053). Furthermore, there were no differences in AA among groups over time. Our findings suggest that adolescents with chronic anxiety did not change telomere length over time, which could be related to a delay in neuronal development in this period of life.
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Affiliation(s)
- Angelica Cerveira de Baumont
- Anxiety Disorders Outpatient Program for Children and Adolescents, Protaia, Federal University of Rio Grande do Sul, UFRGS/Hospital de Clínicas de Porto Alegre, HCPA, Porto Alegre, Brazil.
- Graduate Program in Psychiatry and Behavioral Sciences, Federal University of Rio Grande do Sul, UFRGS, Porto Alegre, Brazil.
- Basic Research and Advanced Investigations in Neurosciences, BRAIN Laboratory, Hospital de Clínicas de Porto Alegre, HCPA, Porto Alegre, Brazil.
- Serviço de Psiquiatria, Hospital de Clínicas de Porto Alegre, HCPA, Rua Ramiro Barcelos, 2350-sala 400N, Rio Branco, Porto Alegre, RS, 90035-903, Brazil.
| | - Mauricio Scopel Hoffmann
- Graduate Program in Psychiatry and Behavioral Sciences, Federal University of Rio Grande do Sul, UFRGS, Porto Alegre, Brazil
- Departamento de Neuropsiquiatria, Universidade Federal de Santa Maria, Avenida Roraima 1000, Santa Maria, 97105-900, Brazil
- Care Policy and Evaluation Centre, London School of Economics and Political Science, London, UK
- Instituto Nacional de Psiquiatria do Desenvolvimento para Crianças e Adolescentes (INPD), Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq), Porto Alegre, RS, Brazil
| | - Andressa Bortoluzzi
- Anxiety Disorders Outpatient Program for Children and Adolescents, Protaia, Federal University of Rio Grande do Sul, UFRGS/Hospital de Clínicas de Porto Alegre, HCPA, Porto Alegre, Brazil
- Graduate Program in Neuroscience, Institute of Basic Sciences/Health, Federal University of Rio Grande do Sul, UFRGS, Porto Alegre, Brazil
- Basic Research and Advanced Investigations in Neurosciences, BRAIN Laboratory, Hospital de Clínicas de Porto Alegre, HCPA, Porto Alegre, Brazil
| | - Gabriel R Fries
- Translational Psychiatry Program, Department of Psychiatry and Behavioral Sciences, McGovern Medical School, University of Texas Health Science Center at Houston, (UTHealth), Houston, TX, USA
| | - Patrícia Lavandoski
- Graduate Program in Biochemistry, Laboratoy of Molecular Biology and Bioinformatics, Federal University of Rio Grande do Sul, UFRGS, Porto Alegre, Brazil
| | - Lucas K Grun
- Group of Inflammation and Cellular Senescence, Graduate Program in Cellular and Molecular Biology, School of Sciences, Pontifícia Universidade Católica do Rio Grande do Sul (PUCRS), Porto Alegre, RS, Brazil
- Postgraduate Program in Pediatrics and Child Health, School of Medicine, Pontifical Catholic University of Rio Grande do Sul (PUCRS), Porto Alegre, Brazil
| | - Luciano S P Guimarães
- Unit of Epidemiology and Biostatistics, Hospital de Clínicas de Porto Alegre, HCPA, Porto Alegre, Brazil
| | - Fátima T C R Guma
- Graduate Program in Biochemistry, Laboratoy of Molecular Biology and Bioinformatics, Federal University of Rio Grande do Sul, UFRGS, Porto Alegre, Brazil
| | - Giovanni Abrahão Salum
- Anxiety Disorders Outpatient Program for Children and Adolescents, Protaia, Federal University of Rio Grande do Sul, UFRGS/Hospital de Clínicas de Porto Alegre, HCPA, Porto Alegre, Brazil
- Graduate Program in Psychiatry and Behavioral Sciences, Federal University of Rio Grande do Sul, UFRGS, Porto Alegre, Brazil
- Instituto Nacional de Psiquiatria do Desenvolvimento para Crianças e Adolescentes (INPD), Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq), Porto Alegre, RS, Brazil
| | - Florencia M Barbé-Tuana
- Graduate Program in Biochemistry, Laboratoy of Molecular Biology and Bioinformatics, Federal University of Rio Grande do Sul, UFRGS, Porto Alegre, Brazil
- Group of Inflammation and Cellular Senescence, Graduate Program in Cellular and Molecular Biology, School of Sciences, Pontifícia Universidade Católica do Rio Grande do Sul (PUCRS), Porto Alegre, RS, Brazil
| | - Gisele G Manfro
- Anxiety Disorders Outpatient Program for Children and Adolescents, Protaia, Federal University of Rio Grande do Sul, UFRGS/Hospital de Clínicas de Porto Alegre, HCPA, Porto Alegre, Brazil
- Graduate Program in Psychiatry and Behavioral Sciences, Federal University of Rio Grande do Sul, UFRGS, Porto Alegre, Brazil
- Graduate Program in Neuroscience, Institute of Basic Sciences/Health, Federal University of Rio Grande do Sul, UFRGS, Porto Alegre, Brazil
- Basic Research and Advanced Investigations in Neurosciences, BRAIN Laboratory, Hospital de Clínicas de Porto Alegre, HCPA, Porto Alegre, Brazil
- Instituto Nacional de Psiquiatria do Desenvolvimento para Crianças e Adolescentes (INPD), Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq), Porto Alegre, RS, Brazil
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Nwanaji-Enwerem JC, Jackson CL, Ottinger MA, Cardenas A, James KA, Malecki KM, Chen JC, Geller AM, Mitchell UA. Adopting a "Compound" Exposome Approach in Environmental Aging Biomarker Research: A Call to Action for Advancing Racial Health Equity. ENVIRONMENTAL HEALTH PERSPECTIVES 2021; 129:45001. [PMID: 33822649 PMCID: PMC8043128 DOI: 10.1289/ehp8392] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/02/2020] [Revised: 02/24/2021] [Accepted: 03/15/2021] [Indexed: 05/02/2023]
Abstract
BACKGROUND In June 2020, the National Academies of Sciences, Engineering, and Medicine hosted a virtual workshop focused on integrating the science of aging and environmental health research. The concurrent COVID-19 pandemic and national attention on racism exposed shortcomings in the environmental research field's conceptualization and methodological use of race, which have subsequently hindered the ability of research to address racial health disparities. By the workshop's conclusion, the authors deduced that the utility of environmental aging biomarkers-aging biomarkers shown to be specifically influenced by environmental exposures-would be greatly diminished if these biomarkers are developed absent of considerations of broader societal factors-like structural racism-that impinge on racial health equity. OBJECTIVES The authors reached a post-workshop consensus recommendation: To advance racial health equity, a "compound" exposome approach should be widely adopted in environmental aging biomarker research. We present this recommendation here. DISCUSSION The authors believe that without explicit considerations of racial health equity, people in most need of the benefits afforded by a better understanding of the relationships between exposures and aging will be the least likely to receive them because biomarkers may not encompass cumulative impacts from their unique social and environmental stressors. Employing an exposome approach that allows for more comprehensive exposure-disease pathway characterization across broad domains, including the social exposome and neighborhood factors, is the first step. Exposome-centered study designs must then be supported with efforts aimed at increasing the recruitment and retention of racially diverse study populations and researchers and further "compounded" with strategies directed at improving the use and interpretation of race throughout the publication and dissemination process. This compound exposome approach maximizes the ability of our science to identify environmental aging biomarkers that explicate racial disparities in health and best positions the environmental research community to contribute to the elimination of racial health disparities. https://doi.org/10.1289/EHP8392.
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Affiliation(s)
- Jamaji C. Nwanaji-Enwerem
- Department of Environmental Health, Harvard T.H. Chan School of Public Health and MD/PhD Program, Harvard Medical School, Boston, Massachusetts, USA
- Division of Environmental Health Sciences, School of Public Health and Center for Computational Biology, University of California, Berkeley, Berkeley, California, USA
| | - Chandra L. Jackson
- Epidemiology Branch, National Institute of Environmental Health Sciences, National Institutes of Health (NIH), U.S. Department of Health and Human Services (U.S. HHS), Research Triangle Park, North Carolina, USA
- Intramural Program, National Institute on Minority Health and Health Disparities, NIH, U.S. HHS, Bethesda, Maryland, USA
| | - Mary Ann Ottinger
- Department of Biology and Biochemistry, University of Houston, Houston, Texas USA
| | - Andres Cardenas
- Division of Environmental Health Sciences, School of Public Health and Center for Computational Biology, University of California, Berkeley, Berkeley, California, USA
| | - Katherine A. James
- Department of Environmental and Occupational Health, Colorado School of Public Health, University of Colorado Anschutz Medical Campus, Aurora, Colorado, USA
| | - Kristen M.C. Malecki
- Department of Population Health Sciences, University of Wisconsin Madison School of Medicine and Public Health, Madison, Wisconsin, USA
| | - Jiu-Chiuan Chen
- Departments of Preventive Medicine and Neurology, Keck School of Medicine, University of Southern California, Los Angeles, California, USA
| | - Andrew M. Geller
- Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, North Carolina, USA
| | - Uchechi A. Mitchell
- Division of Community Health Sciences, School of Public Health, University of Illinois at Chicago, Chicago, Illinois, USA
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Hallmarks of environmental insults. Cell 2021; 184:1455-1468. [PMID: 33657411 DOI: 10.1016/j.cell.2021.01.043] [Citation(s) in RCA: 169] [Impact Index Per Article: 56.3] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2020] [Revised: 01/15/2021] [Accepted: 01/25/2021] [Indexed: 02/07/2023]
Abstract
Environmental insults impair human health around the world. Contaminated air, water, soil, food, and occupational and household settings expose humans of all ages to a plethora of chemicals and environmental stressors. We propose eight hallmarks of environmental insults that jointly underpin the damaging impact of environmental exposures during the lifespan. Specifically, they include oxidative stress and inflammation, genomic alterations and mutations, epigenetic alterations, mitochondrial dysfunction, endocrine disruption, altered intercellular communication, altered microbiome communities, and impaired nervous system function. They provide a framework to understand why complex mixtures of environmental exposures induce severe health effects even at relatively modest concentrations.
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Genetic Knowledge and Communication Among Mexican Farmworkers and Non-farmworkers in North Carolina. J Immigr Minor Health 2021; 23:1026-1034. [PMID: 33469784 DOI: 10.1007/s10903-020-01136-w] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 12/17/2020] [Indexed: 10/22/2022]
Abstract
It is important to understand genetics within the context of health. This paper assesses (a) genetic knowledge among Mexican-born farmworker and non-farmworker adults; (b) their interpersonal and device sources of genetic knowledge; and (c) the association between their genetic knowledge and the sources of this genetic knowledge.Interviews were conducted with Mexican-born farmworkers (100) and non-farmworkers (100) in North Carolina. Participants answered 15 questions to assess genetic knowledge, and sources from which they had seen or heard about genes and genetics.Results show limited knowledge of genetics, with farmworkers and non-farmworkers providing a similar level of correct responses (6.6 versus 7.3), but with farmworkers providing more incorrect responses (4.0 versus 2.7). Important sources of genetic information for farmworkers were promotoras (47%), compared to teachers (49%) for non-farmworkers.This study demonstrates a need for increased dissemination of genetic information to Mexican-origin farmworkers and non-farmworkers.
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Clark DF, Schmelz R, Rogers N, Smith NE, Shorter KR. Acute high folic acid treatment in SH-SY5Y cells with and without MTHFR function leads to gene expression changes in epigenetic modifying enzymes, changes in epigenetic marks, and changes in dendritic spine densities. PLoS One 2021; 16:e0245005. [PMID: 33411826 PMCID: PMC7790414 DOI: 10.1371/journal.pone.0245005] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2020] [Accepted: 12/19/2020] [Indexed: 12/12/2022] Open
Abstract
Epigenetics are known to be involved in various disorders, including neurobiological disorders like autism. Dietary factors such as folic acid can affect epigenetic marks using methylenetetrahydrofolate reductase (MTHFR) to metabolize folic acid to a one-carbon methyl group. As MTHFR mutations are frequent, it is curious as to whether excess folic acid, with or without functioning MTHFR, could affect gene expression, epigenetics, and neuromorphology. Here, we investigated gene expression and activity of epigenetic modifying enzymes, genome-wide DNA methylation, histone 3 modifications, and dendritic spine densities in SH-SY5Y cells with or without a knockdown of MTHFR and with or without an excess of folic acid. We found alterations to gene expression of epigenetic modifying enzymes, including those associated with disorders like autism. Grouping the epigenetic modifying enzymes by function indicated that gene expression was widely affected for genes that code for enzymes affecting DNA methylation, histone acetylation, histone methylation, histone phosphorylation, and histone ubiquitination when excess folic acid treatment occurred with or without the knockdown of MTHFR. MTHFR was significantly reduced upon excess folic acid treatment whether MTHFR was knocked-down or not. Further, methyl-CpG binding protein 2 expression was significantly decreased with excess folic acid treatment with and without proper MTHFR expression. Global DNA methylation decreased due to the knockdown alone while global hydroxymethylated DNA increased due to the knockdown alone. TET2 expression significantly increased with the MTHFR knockdown alone. Excess folic acid alone induced a decrease in TET3 expression. Excess folic acid induced an increase in dendritic spines without the MTHFR knockdown, but folic acid induced a decrease in dendritic spines when MTHFR was knocked-down. The knockdown alone also increased the dendritic spines significantly. Histone 3 acetylation at lysine 18 was significantly increased when excess folic acid was applied to cells with the MTHFR knockdown, as was histone 3 phosphorylation at serine 10. Broadly, our results indicate that excess folic acid, even with functioning MTHFR, could have detrimental effects on cells.
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Affiliation(s)
- Daniel F. Clark
- Division of Natural Sciences and Engineering, University of South Carolina Upstate, Spartanburg, South Carolina, United States of America
| | - Rachael Schmelz
- Division of Natural Sciences and Engineering, University of South Carolina Upstate, Spartanburg, South Carolina, United States of America
| | - Nicole Rogers
- Division of Natural Sciences and Engineering, University of South Carolina Upstate, Spartanburg, South Carolina, United States of America
| | - Nuri E. Smith
- Division of Natural Sciences and Engineering, University of South Carolina Upstate, Spartanburg, South Carolina, United States of America
| | - Kimberly R. Shorter
- Division of Natural Sciences and Engineering, University of South Carolina Upstate, Spartanburg, South Carolina, United States of America
- * E-mail:
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Chung M, Ruan M, Zhao N, Koestler DC, De Vivo I, Kelsey KT, Michaud DS. DNA methylation ageing clocks and pancreatic cancer risk: pooled analysis of three prospective nested case-control studies. Epigenetics 2021; 16:1306-1316. [PMID: 33315530 DOI: 10.1080/15592294.2020.1861401] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/22/2022] Open
Abstract
DNA methylation (DNAm) age may reflect age-related variations in biological changes and abnormalities related to ageing. DNAm age acceleration measures have been associated with a number of cancers, but to our knowledge, have not been examined in relation to pancreatic cancer risk or survival. DNAm levels in leukocytes of prediagnostic blood samples of 393 pancreatic cancer cases and 431 matched controls, pooled from three large prospective cohort studies, were used to estimate DNAm age, epigenetic age acceleration (AA), and intrinsic epigenetic age acceleration (IEAA) metrics. Logistic regression and Cox proportional hazard regression models were used to examine the relationship between the various AA and IEAA metrics and pancreatic cancer risk and survival, respectively. The results showed that pancreatic cancer risk was significantly increased across all IEAA metrics, ranging from 83% to 95% increased risk when comparing the third and highest quartiles to the lowest quartile of IEAA. Consistent with these findings, the results from multivariate spline regression analyses showed non-linear relationships between all three IEAA metrics and pancreatic cancer risk with apparent threshold effect including two turning points at minimal and at maximal risks, respectively. There is no evidence of a significant association between pancreatic cancer survival and any of the epigenetic AA or IEAA metrics. Our results indicate DNAm age acceleration, measured in blood prior to cancer diagnosis, is associated with an increased risk of pancreatic cancer in a complex nonlinear, dose-response manner. Epigenetic IEAA metrics may be a useful addition to current methods for pancreatic cancer risk prediction.
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Affiliation(s)
- Mei Chung
- Department of Public Health & Community Medicine, Tufts University School of Medicine, Tufts University, Boston, MA, USA
| | - Mengyuan Ruan
- Department of Public Health & Community Medicine, Tufts University School of Medicine, Tufts University, Boston, MA, USA
| | - Naisi Zhao
- Department of Public Health & Community Medicine, Tufts University School of Medicine, Tufts University, Boston, MA, USA
| | - Devin C Koestler
- Department of Biostatistics & Data Science, University of Kansas Medical Center, Kansas City, KS, USA.,University of Kansas Cancer Center, University of Kansas Medical Center, Kansas City, KS, USA
| | - Immaculata De Vivo
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Karl T Kelsey
- Department of Epidemiology, Brown University, Providence, RI, USA.,Department of Pathology and Laboratory Medicine, Brown University, Providence, RI, USA
| | - Dominique S Michaud
- Department of Public Health & Community Medicine, Tufts University School of Medicine, Tufts University, Boston, MA, USA
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Accelerated epigenetic age as a biomarker of cardiovascular sensitivity to traffic-related air pollution. Aging (Albany NY) 2020; 12:24141-24155. [PMID: 33289704 PMCID: PMC7762491 DOI: 10.18632/aging.202341] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2020] [Accepted: 10/27/2020] [Indexed: 11/25/2022]
Abstract
BACKGROUND Accelerated epigenetic age has been proposed as a biomarker of increased aging, which may indicate disruptions in cellular and organ system homeostasis and thus contribute to sensitivity to environmental exposures. METHODS Using 497 participants from the CATHGEN cohort, we evaluated whether accelerated epigenetic aging increases cardiovascular sensitivity to traffic-related air pollution (TRAP) exposure. We used residential proximity to major roadways and source apportioned air pollution models as measures of TRAP exposure, and chose peripheral arterial disease (PAD) and blood pressure as outcomes based on previous associations with TRAP. We used Horvath epigenetic age acceleration (AAD) and phenotypic age acceleration (PhenoAAD) as measures of age acceleration, and adjusted all models for chronological age, race, sex, smoking, and socioeconomic status. RESULTS We observed significant interactions between TRAP and both AAD and PhenoAAD. Interactions indicated that increased epigenetic age acceleration elevated associations between proximity to roadways and PAD. Interactions were also observed between AAD and gasoline and diesel source apportioned PM2.5. CONCLUSION Epigenetic age acceleration may be a biomarker of sensitivity to air pollution, particularly for TRAP in urban cohorts. This presents a novel means by which to understand sensitivity to air pollution and provides a molecular measure of environmental sensitivity.
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Sobhani I, Rotkopf H, Khazaie K. Bacteria-related changes in host DNA methylation and the risk for CRC. Gut Microbes 2020; 12:1800898. [PMID: 32931352 PMCID: PMC7575230 DOI: 10.1080/19490976.2020.1800898] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/06/2020] [Accepted: 07/17/2020] [Indexed: 02/03/2023] Open
Abstract
Colorectal cancer (CRC) is the second most common cause of cancer deaths in men and women combined. Colon-tumor growth is multistage and the result of the accumulation of spontaneous mutations and epigenetic events that silence tumor-suppressor genes and activate oncogenes. Environmental factors are primary contributors to these somatic gene alterations, which account for the increase in incidence of CRC in western countries. In recent decades, gut microbiota and their metabolites have been recognized as essential contributing factors to CRC, and now serve as biomarkers for the diagnosis and prognosis of CRC. In the present review, we highlight holistic approaches to understanding how gut microbiota contributes to CRC. We particularly focus herein on bacteria-related changes in host DNA methylation and the risk for CRC.
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Affiliation(s)
- Iradj Sobhani
- Head of the Department of Gastroenterology, Consultant in GI Oncology, Hopital Henri Mondor, APHP. Créteil-France; Head of the Research Team EC2M3, Université Paris-Est Créteil (UPEC), Créteil, France
| | - Hugo Rotkopf
- Department of Gastroenterology Hospital Henri Mondor, APHP. Créteil-France; Member of Research Team EC2M3, Université Paris-Est Créteil (UPEC). Créteil, France
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de Oliveira NFP, de Souza BF, de Castro Coêlho M. UV Radiation and Its Relation to DNA Methylation in Epidermal Cells: A Review. EPIGENOMES 2020; 4:23. [PMID: 34968303 PMCID: PMC8594722 DOI: 10.3390/epigenomes4040023] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2020] [Revised: 09/25/2020] [Accepted: 09/28/2020] [Indexed: 12/22/2022] Open
Abstract
DNA methylation is the most studied epigenetic mark, and it can be altered by environmental factors. Among these factors, ultraviolet radiation (UV) is little explored within this context. While the relationship between UV radiation and DNA mutations is clear, little is known about the relationship between UV radiation and epimutations. The present study aimed to perform a literature review to determine the influence of artificial or natural (solar) UV radiation on the global and site-specific methylation profile of epidermal cells. A systematic review of the literature was carried out using the databases PubMed, Scopus, Cochrane, and Web of Science. Observational and intervention studies in cultured cells and animal or human models were included. Most studies showed a relationship between UV radiation and changes in the methylation profile, both global and site-specific. Hypermethylation and hypomethylation changes were detected, which varied according to the studied CpG site. In conclusion, UV radiation can alter the DNA methylation profile in epidermal cells derived from the skin. These data can be used as potential biomarkers for environmental exposure and skin diseases, in addition to being targets for treatments. On the other hand, UV radiation (phototherapy) can also be used as a tool to treat skin diseases. Thus, the data suggest that epigenetic homeostasis can be disrupted or restored by exposure to UV radiation according to the applied wavelength.
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Affiliation(s)
- Naila Francis Paulo de Oliveira
- Departamento de Biologia Molecular, Centro de Ciências Exatas e da Natureza, Universidade Federal da Paraíba—UFPB, João Pessoa 58051-900, Brazil;
- Programa de Pós Graduação em Odontologia, Centro de Ciências da Saúde, Universidade Federal da Paraíba—UFPB, João Pessoa 58051-900, Brazil;
| | - Beatriz Fernandes de Souza
- Departamento de Biologia Molecular, Centro de Ciências Exatas e da Natureza, Universidade Federal da Paraíba—UFPB, João Pessoa 58051-900, Brazil;
| | - Marina de Castro Coêlho
- Programa de Pós Graduação em Odontologia, Centro de Ciências da Saúde, Universidade Federal da Paraíba—UFPB, João Pessoa 58051-900, Brazil;
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50
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Lodge EK, Engel LS, Ferrando-Martínez S, Wildman D, Uddin M, Galea S, Aiello AE. The association between residential proximity to brownfield sites and high-traffic areas and measures of immunity. JOURNAL OF EXPOSURE SCIENCE & ENVIRONMENTAL EPIDEMIOLOGY 2020; 30:824-834. [PMID: 32398779 PMCID: PMC7483819 DOI: 10.1038/s41370-020-0226-2] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/05/2019] [Revised: 04/22/2020] [Accepted: 04/27/2020] [Indexed: 06/11/2023]
Abstract
The mechanisms by which neighborhood environmental exposures influence health are poorly understood, although immune system dysregulation represents a potential biological pathway. While many neighborhood exposures have been investigated, there is little research on residential proximity to brownfield waste. Using biomarker data from 262 participants in the Detroit Neighborhood Health Study, we estimated the association between proximity to brownfields and heavy traffic and signal joint T-cell receptor excision circles (sjTRECs, a measure of naive T-cell production), C-reactive protein (CRP, a measure of systemic inflammation), and interleukin-6 (IL-6, a pro-inflammatory cytokine). We assessed residential proximity ≤200 m from brownfields and highways on all three biomarkers using multivariate regression. We demonstrated that living ≤200 m from a brownfield site was associated with a 0.30 (95% CI = 0.59, 0.02, p = 0.04) loge-unit decrease in sjTRECs per million whole blood cells, as well as non-significantly elevated levels of CRP and IL-6. Heavy traffic was not associated with any biomarker. Persons living in close proximity to brownfield sites had significantly lower naive T-cell production, suggesting accelerated immune aging. Decreased T-cell production associated with brownfield proximity may be caused by toxicant exposure in brownfield sites, or may serve as a marker of other neighborhood stressors.
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Affiliation(s)
- Evans K Lodge
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Lawrence S Engel
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | | | - Derek Wildman
- College of Public Health, University of South Florida, Tampa, FL, USA
| | - Monica Uddin
- College of Public Health, University of South Florida, Tampa, FL, USA
| | - Sandro Galea
- School of Public Health, Boston University, Boston, MA, USA
| | - Allison E Aiello
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
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