1
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Bell CG. Epigenomic insights into common human disease pathology. Cell Mol Life Sci 2024; 81:178. [PMID: 38602535 PMCID: PMC11008083 DOI: 10.1007/s00018-024-05206-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2024] [Revised: 03/11/2024] [Accepted: 03/13/2024] [Indexed: 04/12/2024]
Abstract
The epigenome-the chemical modifications and chromatin-related packaging of the genome-enables the same genetic template to be activated or repressed in different cellular settings. This multi-layered mechanism facilitates cell-type specific function by setting the local sequence and 3D interactive activity level. Gene transcription is further modulated through the interplay with transcription factors and co-regulators. The human body requires this epigenomic apparatus to be precisely installed throughout development and then adequately maintained during the lifespan. The causal role of the epigenome in human pathology, beyond imprinting disorders and specific tumour suppressor genes, was further brought into the spotlight by large-scale sequencing projects identifying that mutations in epigenomic machinery genes could be critical drivers in both cancer and developmental disorders. Abrogation of this cellular mechanism is providing new molecular insights into pathogenesis. However, deciphering the full breadth and implications of these epigenomic changes remains challenging. Knowledge is accruing regarding disease mechanisms and clinical biomarkers, through pathogenically relevant and surrogate tissue analyses, respectively. Advances include consortia generated cell-type specific reference epigenomes, high-throughput DNA methylome association studies, as well as insights into ageing-related diseases from biological 'clocks' constructed by machine learning algorithms. Also, 3rd-generation sequencing is beginning to disentangle the complexity of genetic and DNA modification haplotypes. Cell-free DNA methylation as a cancer biomarker has clear clinical utility and further potential to assess organ damage across many disorders. Finally, molecular understanding of disease aetiology brings with it the opportunity for exact therapeutic alteration of the epigenome through CRISPR-activation or inhibition.
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Affiliation(s)
- Christopher G Bell
- William Harvey Research Institute, Barts & The London Faculty of Medicine, Queen Mary University of London, Charterhouse Square, London, EC1M 6BQ, UK.
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2
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Schmidt S. Speeding Up Time: New Urinary Peptide Clock Associates Greater Air Pollution Exposures with Faster Biological Aging. Environ Health Perspect 2024; 132:44001. [PMID: 38568857 PMCID: PMC10990112 DOI: 10.1289/ehp14528] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [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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3
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Halabicky OM, Téllez-Rojo MM, Goodrich JM, Dolinoy DC, Mercado-García A, Hu H, Peterson KE. Prenatal and childhood lead exposure is prospectively associated with biological markers of aging in adolescence. Sci Total Environ 2024; 913:169757. [PMID: 38176546 PMCID: PMC10823594 DOI: 10.1016/j.scitotenv.2023.169757] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/03/2023] [Revised: 12/22/2023] [Accepted: 12/27/2023] [Indexed: 01/06/2024]
Abstract
Few studies have related early life lead exposure to adolescent biological aging, a period characterized by marked increases in maturational tempo. We examined associations between prenatal and childhood lead exposure and adolescent biological age (mean 14.5 years) utilizing multiple epigenetic clocks including: intrinsic (IEAA), extrinsic (EEAA), Horvath, Hannum, PhenoAge, GrimAge, Skin-Blood, Wu, PedBE, as well as DNA methylation derived telomere length (DNAmTL). Epigenetic clocks and DNAmTL were calculated via adolescent blood DNA methylation measured by Infinium MethylationEPIC BeadChips. We constructed general linear models (GLMs) with individual lead measures predicting biological age. We additionally examined sex-stratified models and lead by sex interactions, adjusting for adolescent age and lead levels, maternal smoking and education, and proportion of cell types. We also estimated effects of lead exposure on biological age using generalized estimating equations (GEE). First trimester blood lead was positively associated with a 0.14 increase in EEAA age in the GLMs though not the GEE models (95%CI 0.03, 0.25). First and 2nd trimester blood lead levels were associated with a 0.02 year increase in PedBE age in GLM and GEE models (1st trimester, 95%CI 0.004, 0.03; 2nd trimester, 95%CI 0.01, 0.03). Third trimester and 24 month blood lead levels were associated with a -0.06 and -0.05 decrease in Skin-Blood age, respectively, in GLM models. Additionally, 3rd trimester blood lead levels were associated with a 0.08 year decrease in Hannum age in GLM and GEE models (95%CI -0.15, -0.01). There were multiple significant results in sex-stratified models and significant lead by sex interactions, where males experienced accelerated biological age, compared to females who saw a decelerated biological age, with respect to IEAA, EEAA, Horvath, Hannum, and PedBE clocks. Further research is needed to understand sex-specific relationships between lead exposure and measures of biological aging in adolescence and the trajectory of biological aging into young adulthood.
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Affiliation(s)
- O M Halabicky
- Department of Nutritional Sciences, School of Public Health, University of Michigan, Ann Arbor, MI, USA.
| | - M M Téllez-Rojo
- Center for Nutrition and Health Research, National Institute of Public Health, Cuernavaca, Morelos, Mexico
| | - J M Goodrich
- Department of Environmental Health Sciences, School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | - D C Dolinoy
- Department of Nutritional Sciences, School of Public Health, University of Michigan, Ann Arbor, MI, USA; Department of Environmental Health Sciences, School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | - A Mercado-García
- Center for Nutrition and Health Research, National Institute of Public Health, Cuernavaca, Morelos, Mexico
| | - H Hu
- Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - K E Peterson
- Department of Nutritional Sciences, School of Public Health, University of Michigan, Ann Arbor, MI, USA
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4
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Casella C, Kiles F, Urquhart C, Michaud DS, Kirwa K, Corlin L. Methylomic, Proteomic, and Metabolomic Correlates of Traffic-Related Air Pollution in the Context of Cardiorespiratory Health: A Systematic Review, Pathway Analysis, and Network Analysis. Toxics 2023; 11:1014. [PMID: 38133415 PMCID: PMC10748071 DOI: 10.3390/toxics11121014] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/03/2023] [Revised: 11/18/2023] [Accepted: 12/06/2023] [Indexed: 12/23/2023]
Abstract
A growing body of literature has attempted to characterize how traffic-related air pollution (TRAP) affects molecular and subclinical biological processes in ways that could lead to cardiorespiratory disease. To provide a streamlined synthesis of what is known about the multiple mechanisms through which TRAP could lead to cardiorespiratory pathology, we conducted a systematic review of the epidemiological literature relating TRAP exposure to methylomic, proteomic, and metabolomic biomarkers in adult populations. Using the 139 papers that met our inclusion criteria, we identified the omic biomarkers significantly associated with short- or long-term TRAP and used these biomarkers to conduct pathway and network analyses. We considered the evidence for TRAP-related associations with biological pathways involving lipid metabolism, cellular energy production, amino acid metabolism, inflammation and immunity, coagulation, endothelial function, and oxidative stress. Our analysis suggests that an integrated multi-omics approach may provide critical new insights into the ways TRAP could lead to adverse clinical outcomes. We advocate for efforts to build a more unified approach for characterizing the dynamic and complex biological processes linking TRAP exposure and subclinical and clinical disease and highlight contemporary challenges and opportunities associated with such efforts.
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Affiliation(s)
- Cameron Casella
- Department of Public Health and Community Medicine, Tufts University School of Medicine, Boston, MA 02111, USA; (C.C.); (F.K.); (C.U.); (D.S.M.); (K.K.)
| | - Frances Kiles
- Department of Public Health and Community Medicine, Tufts University School of Medicine, Boston, MA 02111, USA; (C.C.); (F.K.); (C.U.); (D.S.M.); (K.K.)
| | - Catherine Urquhart
- Department of Public Health and Community Medicine, Tufts University School of Medicine, Boston, MA 02111, USA; (C.C.); (F.K.); (C.U.); (D.S.M.); (K.K.)
| | - Dominique S. Michaud
- Department of Public Health and Community Medicine, Tufts University School of Medicine, Boston, MA 02111, USA; (C.C.); (F.K.); (C.U.); (D.S.M.); (K.K.)
| | - Kipruto Kirwa
- Department of Public Health and Community Medicine, Tufts University School of Medicine, Boston, MA 02111, USA; (C.C.); (F.K.); (C.U.); (D.S.M.); (K.K.)
- Department of Environmental Health, Boston University School of Public Health, Boston, MA 02118, USA
| | - Laura Corlin
- Department of Public Health and Community Medicine, Tufts University School of Medicine, Boston, MA 02111, USA; (C.C.); (F.K.); (C.U.); (D.S.M.); (K.K.)
- Department of Civil and Environmental Engineering, Tufts University School of Engineering, Medford, MA 02155, USA
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Martens DS, An DW, Yu YL, Chori BS, Wang C, Silva AI, Wei FF, Liu C, Stolarz-Skrzypek K, Rajzer M, Latosinska A, Mischak H, Staessen JA, Nawrot TS. Association of Air Pollution with a Urinary Biomarker of Biological Aging and Effect Modification by Vitamin K in the FLEMENGHO Prospective Population Study. Environ Health Perspect 2023; 131:127011. [PMID: 38078706 PMCID: PMC10712426 DOI: 10.1289/ehp13414] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 05/31/2023] [Revised: 09/28/2023] [Accepted: 11/15/2023] [Indexed: 12/18/2023]
Abstract
BACKGROUND A recently developed urinary peptidomics biological aging clock can be used to study accelerated human aging. From 1990 to 2019, exposure to airborne particulate matter (PM) became the leading environmental risk factor worldwide. OBJECTIVES This study investigated whether air pollution exposure is associated with accelerated urinary peptidomic aging, independent of calendar age, and whether this association is modified by other risk factors. METHODS In a Flemish population, the urinary peptidomic profile (UPP) age (UPP-age) was derived from the urinary peptidomic profile measured by capillary electrophoresis coupled with mass spectrometry. UPP-age-R was calculated as the residual of the regression of UPP-age on chronological age, which reflects accelerated aging predicted by UPP-age, independent of chronological age. A high-resolution spatial-temporal interpolation method was used to assess each individual's exposure to PM 10 , PM 2.5 , black carbon (BC), and nitrogen dioxide (NO 2 ). Associations of UPP-age-R with these pollutants were investigated by mixed models, accounting for clustering by residential address and confounders. Effect modifiers of the associations between UPP-age-R and air pollutants that included 18 factors reflecting vascular function, renal function, insulin resistance, lipid metabolism, or inflammation were evaluated. Direct and indirect (via UPP-age-R) effects of air pollution on mortality were evaluated by multivariable-adjusted Cox models. RESULTS Among 660 participants (50.2% women; mean age: 50.7 y), higher exposure to PM 10 , PM 2.5 , BC, and NO 2 was associated with a higher UPP-age-R. Studying effect modifiers showed that higher plasma levels of desphospho-uncarboxylated matrix Gla protein (dpucMGP), signifying poorer vitamin K status, steepened the slopes of UPP-age-R on the air pollutants. In further analyses among participants with dpucMGP ≥ 4.26 μ g / L (median), an interquartile range (IQR) higher level in PM 10 , PM 2.5 , BC, and NO 2 was associated with a higher UPP-age-R of 2.03 [95% confidence interval (CI): 0.60, 3.46], 2.22 (95% CI: 0.71, 3.74), 2.00 (95% CI: 0.56, 3.43), and 2.09 (95% CI: 0.77, 3.41) y, respectively. UPP-age-R was an indirect mediator of the associations of mortality with the air pollutants [multivariable-adjusted hazard ratios from 1.094 (95% CI: 1.000, 1.196) to 1.110 (95% CI: 1.007, 1.224)] in participants with a high dpucMGP, whereas no direct associations were observed. DISCUSSION Ambient air pollution was associated with accelerated urinary peptidomics aging, and high vitamin K status showed a potential protective effect in this population. Current guidelines are insufficient to decrease the adverse health effects of airborne pollutants, including healthy aging trajectories. https://doi.org/10.1289/EHP13414.
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Affiliation(s)
- Dries S. Martens
- Centre for Environmental Sciences, Hasselt University, Hasselt, Belgium
| | - De-Wei An
- Shanghai Institute of Hypertension, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China
- Non-Profit Research Association Alliance for the Promotion of Preventive Medicine, Mechelen, Belgium
- Research Unit Environment and Health, KU Leuven Department of Public Health and Primary Care, University of Leuven, Leuven, Belgium
| | - Yu-Ling Yu
- Non-Profit Research Association Alliance for the Promotion of Preventive Medicine, Mechelen, Belgium
- Research Unit Environment and Health, KU Leuven Department of Public Health and Primary Care, University of Leuven, Leuven, Belgium
| | - Babangida S. Chori
- Centre for Environmental Sciences, Hasselt University, Hasselt, Belgium
- Non-Profit Research Association Alliance for the Promotion of Preventive Medicine, Mechelen, Belgium
| | - Congrong Wang
- Centre for Environmental Sciences, Hasselt University, Hasselt, Belgium
| | - Ana Inês Silva
- Centre for Environmental Sciences, Hasselt University, Hasselt, Belgium
| | - Fang-Fei Wei
- Department of Cardiology, The First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, Guangdong, China
| | - Chen Liu
- Department of Cardiology, The First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, Guangdong, China
| | - Katarzyna Stolarz-Skrzypek
- First Department of Cardiology, Interventional Electrocardiology and Hypertension, Jagiellonian University, Kraków, Poland
| | - Marek Rajzer
- First Department of Cardiology, Interventional Electrocardiology and Hypertension, Jagiellonian University, Kraków, Poland
| | | | | | - Jan A. Staessen
- Shanghai Institute of Hypertension, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China
- Non-Profit Research Association Alliance for the Promotion of Preventive Medicine, Mechelen, Belgium
- Biomedical Sciences Group, Faculty of Medicine, University of Leuven, Leuven, Belgium
| | - Tim S. Nawrot
- Centre for Environmental Sciences, Hasselt University, Hasselt, Belgium
- Research Unit Environment and Health, KU Leuven Department of Public Health and Primary Care, University of Leuven, Leuven, Belgium
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Huang H, Xie B, Liu Y, Dong GH, Liu R, Gui Z, Chen L, Li S, Guo Y, Yang L, Chen G. Long-term exposure to PM 2.5 compositions and O 3 and their interactive effects on DNA methylation of peripheral brain-derived neurotrophic factor promoter. Int J Environ Health Res 2023:1-12. [PMID: 37939783 DOI: 10.1080/09603123.2023.2280157] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/11/2023] [Accepted: 11/01/2023] [Indexed: 11/10/2023]
Abstract
This study examined the associations of long-term exposure to ambient fine particulate matter (PM2.5) compositions/ozone with methylation of peripheral brain-derived neurotrophic factor (BDNF) promoters. A total of 101 participants were recruited from a cohort in Shijiazhuang, Hebei province, China. They underwent baseline and follow-up surveys in 2011 and 2015. DNA methylation levels were detected by bisulfite-PCR amplification and pyrosequencing. Participants' three-year average levels of PM2.5 compositions and ozone were estimated. Bayesian kernel machine regression (BKMR) models were used to examine the joint effects of pollutants on methylation levels. Exposure to PM2.5 compositions and ozone mixtures at the 75th percentile was associated with increased methylation levels at CpG2 of BDNF promoter (203%, 95% CI: 89, 316) than the lowest level of exposure, and sulfate dominated the effect in the BKMR models.Our findings provide clues to the epigenetic mechanisms for the associations of PM2.5 compositions and ozone with BDNF.
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Affiliation(s)
- Haoyu Huang
- Department of Occupational and Environmental Health, School of Public Health, Sun Yat-sen University, Guangzhou, China
| | - Bing Xie
- College of Forensic Medicine, Hebei Medical University, Shijiazhuang, China
- Hebei Key Laboratory of Forensic Medicine, Collaborative Innovation Center of Forensic Medical Molecular Identification, Research Unit of Digestive Tract Microecosystem Pharmacology and Toxicology, Chinese Academy of Medical Sciences, Shijiazhuang, China
| | - Yuewei Liu
- Department of Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou, China
| | - Guang-Hui Dong
- Department of Occupational and Environmental Health, School of Public Health, Sun Yat-sen University, Guangzhou, China
| | - Ruqing Liu
- Department of Occupational and Environmental Health, School of Public Health, Sun Yat-sen University, Guangzhou, China
| | - Zhaohuan Gui
- Department of Occupational and Environmental Health, School of Public Health, Sun Yat-sen University, Guangzhou, China
| | - Lijun Chen
- College of Information Engineering, Hubei University of Chinese Medicine, Wuhan, China
| | - Shanshan Li
- Climate, Air Quality Research Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia
| | - Yuming Guo
- Climate, Air Quality Research Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia
| | - Lei Yang
- Department of Epidemiology and Biostatistics, School of Public Health, Hebei Key Laboratory of Environment and Human Health, Hebei Medical University, Shijiazhuang, China
| | - Gongbo Chen
- Climate, Air Quality Research Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia
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7
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Cheng X, Wei Y, Wang R, Jia C, Zhang Z, An J, Li W, Zhang J, He M. Associations of essential trace elements with epigenetic aging indicators and the potential mediating role of inflammation. Redox Biol 2023; 67:102910. [PMID: 37793240 PMCID: PMC10562911 DOI: 10.1016/j.redox.2023.102910] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2023] [Revised: 09/27/2023] [Accepted: 09/27/2023] [Indexed: 10/06/2023] Open
Abstract
BACKGROUND Essential trace elements (ETEs) play essential roles in vital functions, but their effects on epigenetic aging remain poorly understood. OBJECTIVES This study aimed to investigate the associations of ETEs with four epigenetic aging indicators and assess the potential mediating role of inflammation. METHODS We recruited 93 individuals from hospitals between October 2018 and August 2019. Plasma levels of cobalt, copper, iron, manganese, molybdenum, selenium, and zinc were measured by ICP-MS, and leukocyte DNA methylation levels were measured using Illumina MethylationEPIC beadchip. Linear regression was used to estimate the association between seven plasma ETEs and epigenetic aging indicators. Weighted quantile sum (WQS) regression and Bayesian kernel machine regression (BKMR) models were used to evaluate the effect of ETEs mixtures. Inflammatory status was assessed using four systemic inflammation indices (neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), monocyte-to-lymphocyte ratio (MLR), and systemic immune-inflammation index (SII)) and three cytokines (IL-4, IL-6, and IL-13). Mediation analysis was performed to explore the role of inflammation in the above associations. RESULTS Plasma Se levels were significantly negatively associated with DunedinPACE, whereas Cu levels were significantly positively associated with it. Both WQS regression and BKMR models suggested that Se and Cu dominate the effect of the ETEs mixture. MLR and interleukin 6 were significantly and positively associated with DunedinPACE. Further mediation analysis indicated that inflammation partially mediated the association between ETEs and DunedinPACE. DISCUSSION Plasma Se and Cu levels are closely associated to epigenetic aging, and inflammation might be a potential mechanism underlying this relationship. These findings contribute to the prevention of health hazards associated with population aging.
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Affiliation(s)
- Xu Cheng
- Department of Occupational and Environmental Health and State Key Laboratory of Environmental Health for Incubating, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China
| | - Yue Wei
- Department of Occupational and Environmental Health and State Key Laboratory of Environmental Health for Incubating, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China
| | - Ruixin Wang
- Department of Occupational and Environmental Health and State Key Laboratory of Environmental Health for Incubating, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China
| | - Chengyong Jia
- Department of Occupational and Environmental Health and State Key Laboratory of Environmental Health for Incubating, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China
| | - Zefang Zhang
- Department of Occupational and Environmental Health and State Key Laboratory of Environmental Health for Incubating, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China
| | - Jun An
- Department of Occupational and Environmental Health and State Key Laboratory of Environmental Health for Incubating, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China
| | - Weiya Li
- Department of Occupational and Environmental Health and State Key Laboratory of Environmental Health for Incubating, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China
| | - Jiazhen Zhang
- Department of Occupational and Environmental Health and State Key Laboratory of Environmental Health for Incubating, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China
| | - Meian He
- Department of Occupational and Environmental Health and State Key Laboratory of Environmental Health for Incubating, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China.
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Koenigsberg SH, Chang CJ, Ish J, Xu Z, Kresovich JK, Lawrence KG, Kaufman JD, Sandler DP, Taylor JA, White AJ. Air pollution and epigenetic aging among Black and White women in the US. Environ Int 2023; 181:108270. [PMID: 37890265 PMCID: PMC10872847 DOI: 10.1016/j.envint.2023.108270] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/17/2023] [Revised: 10/12/2023] [Accepted: 10/16/2023] [Indexed: 10/29/2023]
Abstract
BACKGROUND DNA methylation-based measures of biological aging have been associated with air pollution and may link pollutant exposures to aging-related health outcomes. However, evidence is inconsistent and there is little information for Black women. OBJECTIVE We examined associations of ambient particulate matter <2.5 μm and <10 μm in diameter (PM2.5 and PM10) and nitrogen dioxide (NO2) with DNA methylation, including epigenetic aging and individual CpG sites, and evaluated whether associations differ between Black and non-Hispanic White (NHW) women. METHODS Validated models were used to estimate annual average outdoor residential exposure to PM2.5, PM10, and NO2 in a sample of self-identified Black (n=633) and NHW (n=3493) women residing in the contiguous US. We used sampling-weighted generalized linear regression to examine the effects of pollutants on six epigenetic aging measures (primary: DunedinPACE, GrimAgeAccel, and PhenoAgeAccel; secondary: Horvath intrinsic epigenetic age acceleration [EAA], Hannum extrinsic EAA, and skin & blood EAA) and epigenome-wide associations for individual CpG sites. Wald tests of nested models with and without interaction terms were used to examine effect measure modification by race/ethnicity. RESULTS Black participants had higher median air pollution exposure than NHW participants. GrimAgeAccel was associated with both PM10 and NO2 among Black participants, (Q4 versus Q1, PM10: β=1.09, 95% CI: 0.16-2.03; NO2: β=1.01, 95% CI 0.08-1.94) but not NHW participants (p-for-heterogeneity: PM10=0.10, NO2=0.20). In Black participants, we also observed a monotonic exposure-response relationship between NO2 and DunedinPACE (Q4 versus Q1, NO2: β=0.029, 95% CI: 0.004-0.055; p-for-trend=0.03), which was not observed in NHW participants (p-for-heterogeneity=0.09). In the EWAS, pollutants were significantly associated with differential methylation at 19 CpG sites in Black women and one in NHW women. CONCLUSIONS In a US-wide cohort study, our findings suggest that air pollution is associated with DNA methylation alterations consistent with higher epigenetic aging among Black, but not NHW, women.
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Affiliation(s)
- Sarah H Koenigsberg
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, 123 W. Franklin St., Chapel Hill, NC 27517, USA; Epidemiology Branch, National Institute of Environmental Health Sciences, 111 TW Alexander Dr, Research Triangle Park, NC 27709, USA.
| | - Che-Jung Chang
- Epidemiology Branch, National Institute of Environmental Health Sciences, 111 TW Alexander Dr, Research Triangle Park, NC 27709, USA
| | - Jennifer Ish
- Epidemiology Branch, National Institute of Environmental Health Sciences, 111 TW Alexander Dr, Research Triangle Park, NC 27709, USA
| | - Zongli Xu
- Epidemiology Branch, National Institute of Environmental Health Sciences, 111 TW Alexander Dr, Research Triangle Park, NC 27709, USA
| | - Jacob K Kresovich
- Epidemiology Branch, National Institute of Environmental Health Sciences, 111 TW Alexander Dr, Research Triangle Park, NC 27709, USA; Departments of Cancer Epidemiology and Breast Oncology, H. Lee Moffitt Cancer Center and Research Institute, 12902 Magnolia Drive, Tampa, FL 33612, USA
| | - Kaitlyn G Lawrence
- Epidemiology Branch, National Institute of Environmental Health Sciences, 111 TW Alexander Dr, Research Triangle Park, NC 27709, USA
| | - Joel D Kaufman
- Departments of Environmental & Occupational Health Sciences, Medicine, and Epidemiology University of Washington, 4225 Roosevelt Way NE, Seattle, WA 98105, USA
| | - Dale P Sandler
- Epidemiology Branch, National Institute of Environmental Health Sciences, 111 TW Alexander Dr, Research Triangle Park, NC 27709, USA
| | - Jack A Taylor
- Epidemiology Branch, National Institute of Environmental Health Sciences, 111 TW Alexander Dr, Research Triangle Park, NC 27709, USA
| | - Alexandra J White
- Epidemiology Branch, National Institute of Environmental Health Sciences, 111 TW Alexander Dr, Research Triangle Park, NC 27709, USA.
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9
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Casella C, Kiles F, Urquhart C, Michaud DS, Kirwa K, Corlin L. Methylomic, proteomic, and metabolomic correlates of traffic-related air pollution: A systematic review, pathway analysis, and network analysis relating traffic-related air pollution to subclinical and clinical cardiorespiratory outcomes. medRxiv 2023:2023.09.30.23296386. [PMID: 37873294 PMCID: PMC10592990 DOI: 10.1101/2023.09.30.23296386] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/25/2023]
Abstract
A growing body of literature has attempted to characterize how traffic-related air pollution (TRAP) affects molecular and subclinical biological processes in ways that could lead to cardiorespiratory disease. To provide a streamlined synthesis of what is known about the multiple mechanisms through which TRAP could lead cardiorespiratory pathology, we conducted a systematic review of the epidemiological literature relating TRAP exposure to methylomic, proteomic, and metabolomic biomarkers in adult populations. Using the 139 papers that met our inclusion criteria, we identified the omic biomarkers significantly associated with short- or long-term TRAP and used these biomarkers to conduct pathway and network analyses. We considered the evidence for TRAP-related associations with biological pathways involving lipid metabolism, cellular energy production, amino acid metabolism, inflammation and immunity, coagulation, endothelial function, and oxidative stress. Our analysis suggests that an integrated multi-omics approach may provide critical new insights into the ways TRAP could lead to adverse clinical outcomes. We advocate for efforts to build a more unified approach for characterizing the dynamic and complex biological processes linking TRAP exposure and subclinical and clinical disease, and highlight contemporary challenges and opportunities associated with such efforts.
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Affiliation(s)
- Cameron Casella
- Department of Public Health and Community Medicine, Tufts University School of Medicine, Boston, MA 02111, USA
| | - Frances Kiles
- Department of Public Health and Community Medicine, Tufts University School of Medicine, Boston, MA 02111, USA
| | - Catherine Urquhart
- Department of Public Health and Community Medicine, Tufts University School of Medicine, Boston, MA 02111, USA
| | - Dominique S. Michaud
- Department of Public Health and Community Medicine, Tufts University School of Medicine, Boston, MA 02111, USA
| | - Kipruto Kirwa
- Department of Public Health and Community Medicine, Tufts University School of Medicine, Boston, MA 02111, USA
- Department of Environmental Health, Boston University School of Public Health, Boston, MA, 02118, USA
| | - Laura Corlin
- Department of Public Health and Community Medicine, Tufts University School of Medicine, Boston, MA 02111, USA
- Department of Civil and Environmental Engineering, Tufts University School of Engineering, Medford, MA 02155, USA
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10
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Wang C, Amini H, Xu Z, Peralta AA, Yazdi MD, Qiu X, Wei Y, Just A, Heiss J, Hou L, Zheng Y, Coull BA, Kosheleva A, Baccarelli AA, Schwartz JD. Long-term exposure to ambient fine particulate components and leukocyte epigenome-wide DNA Methylation in older men: the Normative Aging Study. Environ Health 2023; 22:54. [PMID: 37550674 PMCID: PMC10405403 DOI: 10.1186/s12940-023-01007-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2023] [Accepted: 07/26/2023] [Indexed: 08/09/2023]
Abstract
BACKGROUND Epigenome-wide association studies of ambient fine particulate matter (PM2.5) have been reported. However, few have examined PM2.5 components (PMCs) and sources or included repeated measures. The lack of high-resolution exposure measurements is the key limitation. We hypothesized that significant changes in DNA methylation might vary by PMCs and the sources. METHODS We predicted the annual average of 14 PMCs using novel high-resolution exposure models across the contiguous U.S., between 2000-2018. The resolution was 50 m × 50 m in the Greater Boston Area. We also identified PM2.5 sources using positive matrix factorization. We repeatedly collected blood samples and measured leukocyte DNAm with the Illumina HumanMethylation450K BeadChip in the Normative Aging Study. We then used median regression with subject-specific intercepts to estimate the associations between long-term (one-year) exposure to PMCs / PM2.5 sources and DNA methylation at individual cytosine-phosphate-guanine CpG sites. Significant probes were identified by the number of independent degrees of freedom approach, using the number of principal components explaining > 95% of the variation of the DNA methylation data. We also performed regional and pathway analyses to identify significant regions and pathways. RESULTS We included 669 men with 1,178 visits between 2000-2013. The subjects had a mean age of 75 years. The identified probes, regions, and pathways varied by PMCs and their sources. For example, iron was associated with 6 probes and 6 regions, whereas nitrate was associated with 15 probes and 3 regions. The identified pathways from biomass burning, coal burning, and heavy fuel oil combustion sources were associated with cancer, inflammation, and cardiovascular diseases, whereas there were no pathways associated with all traffic. CONCLUSIONS Our findings showed that the effects of PM2.5 on DNAm varied by its PMCs and sources.
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Affiliation(s)
- Cuicui Wang
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA, 02115, USA.
| | - Heresh Amini
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA, 02115, USA
- Department of Public Health, Faculty of Health and Medical Sciences, Section of Environmental Health, University of Copenhagen, Copenhagen, Denmark
| | - Zongli Xu
- Biostatistics & Computational Biology Branch, National Institute of Environmental Health Sciences, NIH, Research Triangle Park, Durham, NC, USA
| | - Adjani A Peralta
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA, 02115, USA
| | - Mahdieh Danesh Yazdi
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA, 02115, USA
- Program in Public Health, Department of Family, Population, and Preventive Medicine, Renaissance School of Medicine at Stony Brook University, Stony Brook, NY, USA
| | - Xinye Qiu
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA, 02115, USA
| | - Yaguang Wei
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA, 02115, USA
| | - Allan Just
- Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Jonathan Heiss
- Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Lifang Hou
- Department of Preventive Medicine, Feinberg School of Medicine, Northwestern University, Chicago, IL, 60611, USA
| | - Yinan Zheng
- Department of Preventive Medicine, Feinberg School of Medicine, Northwestern University, Chicago, IL, 60611, USA
| | - Brent A Coull
- Department of Biostatistics, Harvard T. H. Chan School of Public Health, Boston, MA, 02115, USA
| | - Anna Kosheleva
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA, 02115, USA
| | - Andrea A Baccarelli
- Department of Environmental Health Sciences, Columbia Mailman School of Public Health, New York, NY, 10032, USA
| | - Joel D Schwartz
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA, 02115, USA
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, 02115, USA
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11
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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. Transl Med 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] [What about the content of this article? (0)] [Affiliation(s)] [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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12
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Shen Y, Kioumourtzoglou MA, Wu H, Vokonas P, Spiro A, Navas-Acien A, Baccarelli AA, Gao F. Cohort Network: A Knowledge Graph toward Data Dissemination and Knowledge-Driven Discovery for Cohort Studies. Environ Sci Technol 2023; 57:8236-8244. [PMID: 37224396 PMCID: PMC10597774 DOI: 10.1021/acs.est.2c08174] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/26/2023]
Abstract
Contemporary environmental health sciences draw on large-scale longitudinal studies to understand the impact of environmental exposures and behavior factors on the risk of disease and identify potential underlying mechanisms. In such studies, cohorts of individuals are assembled and followed up over time. Each cohort generates hundreds of publications, which are typically neither coherently organized nor summarized, hence limiting knowledge-driven dissemination. Hence, we propose a Cohort Network, a multilayer knowledge graph approach to extract exposures, outcomes, and their connections. We applied the Cohort Network on 121 peer-reviewed papers published over the past 10 years from the Veterans Affairs (VA) Normative Aging Study (NAS). The Cohort Network visualized connections between exposures and outcomes across different publications and identified key exposures and outcomes, such as air pollution, DNA methylation, and lung function. We demonstrated the utility of the Cohort Network for new hypothesis generation, e.g., identification of potential mediators of exposure-outcome associations. The Cohort Network can be used by investigators to summarize the cohort's research and facilitate knowledge-driven discovery and dissemination.
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Affiliation(s)
- Yike Shen
- Department of Environmental Health Sciences, Mailman School of Public Health, Columbia University, New York, New York 10032, United States
| | - Marianthi-Anna Kioumourtzoglou
- Department of Environmental Health Sciences, Mailman School of Public Health, Columbia University, New York, New York 10032, United States
| | - Haotian Wu
- Department of Environmental Health Sciences, Mailman School of Public Health, Columbia University, New York, New York 10032, United States
| | - Pantel Vokonas
- VA Normative Aging Study, VA Boston Healthcare System, Boston, Massachusetts 02130, United States
- Department of Medicine, Boston University Chobanian & Avedisian School of Medicine, Boston, Massachusetts 02118, United States
| | - Avron Spiro
- VA Normative Aging Study, VA Boston Healthcare System, Boston, Massachusetts 02130, United States
- Department of Epidemiology, Boston University School of Public Health, Boston, Massachusetts 02118, United States
- Department of Psychiatry, Boston University Chobanian & Avedisian School of Medicine, Boston, Massachusetts 02118, United States
| | - Ana Navas-Acien
- Department of Environmental Health Sciences, Mailman School of Public Health, Columbia University, New York, New York 10032, United States
| | - Andrea A Baccarelli
- Department of Environmental Health Sciences, Mailman School of Public Health, Columbia University, New York, New York 10032, United States
| | - Feng Gao
- Department of Environmental Health Sciences, Mailman School of Public Health, Columbia University, New York, New York 10032, United States
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13
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Krieger N, Chen JT, Testa C, Diez Roux A, Tilling K, Watkins S, Simpkin AJ, Suderman M, Davey Smith G, De Vivo I, Waterman PD, Relton C. Use of Correct and Incorrect Methods of Accounting for Age in Studies of Epigenetic Accelerated Aging: Implications and Recommendations for Best Practices. Am J Epidemiol 2023; 192:800-811. [PMID: 36721372 PMCID: PMC10160768 DOI: 10.1093/aje/kwad025] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2022] [Revised: 11/28/2022] [Accepted: 01/27/2023] [Indexed: 02/02/2023] Open
Abstract
Motivated by our conduct of a literature review on social exposures and accelerated aging as measured by a growing number of epigenetic "clocks" (which estimate age via DNA methylation (DNAm) patterns), we report on 3 different approaches in the epidemiologic literature-1 incorrect and 2 correct-on the treatment of age in these and other studies using other common exposures (i.e., body mass index and alcohol consumption). Among the 50 empirical articles reviewed, the majority (n = 29; 58%) used the incorrect method of analyzing accelerated aging detrended for age as the outcome and did not control for age as a covariate. By contrast, only 42% used correct methods, which are either to analyze accelerated aging detrended for age as the outcome and control for age as a covariate (n = 16; 32%) or to analyze raw DNAm age as the outcome and control for age as a covariate (n = 5; 10%). In accord with prior demonstrations of bias introduced by use of the incorrect approach, we provide simulation analyses and additional empirical analyses to illustrate how the incorrect method can lead to bias towards the null, and we discuss implications for extant research and recommendations for best practices.
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Affiliation(s)
- Nancy Krieger
- Correspondence to Dr. Nancy Krieger, Department of Social and Behavioral Sciences, Harvard T.H. Chan School of Public Health, 677 Huntington Avenue, Kresge 717, Boston, MA 02115 (e-mail: )
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14
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Wang C, DeMeo DL, Kim ES, Cardenas A, Fong KC, Lee LO, Spiro A, Whitsel EA, Horvath S, Hou L, Baccarelli AA, Li Y, Stewart JD, Manson JE, Grodstein F, Kubzansky LD, Schwartz JD. Epigenome-Wide Analysis of DNA Methylation and Optimism in Women and Men. Psychosom Med 2023; 85:89-97. [PMID: 36201768 PMCID: PMC9771983 DOI: 10.1097/psy.0000000000001147] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/02/2023]
Abstract
OBJECTIVE Higher optimism is associated with reduced mortality and a lower risk of age-related chronic diseases. DNA methylation (DNAm) may provide insight into mechanisms underlying these relationships. We hypothesized that DNAm would differ among older individuals who are more versus less optimistic. METHODS Using cross-sectional data from two population-based cohorts of women with diverse races/ethnicities ( n = 3816) and men (only White, n = 667), we investigated the associations of optimism with epigenome-wide leukocyte DNAm. Random-effects meta-analyses were subsequently used to pool the individual results. Significantly differentially methylated cytosine-phosphate-guanines (CpGs) were identified by the "number of independent degrees of freedom" approach: effective degrees of freedom correction using the number of principal components (PCs), explaining >95% of the variation of the DNAm data (PC-correction). We performed regional analyses using comb-p and pathway analyses using the Ingenuity Pathway Analysis software. RESULTS We found that essentially all CpGs (total probe N = 359,862) were homogeneous across sex and race/ethnicity in the DNAm-optimism association. In the single CpG site analyses based on homogeneous CpGs, we identified 13 significantly differentially methylated probes using PC-correction. We found four significantly differentially methylated regions and two significantly differentially methylated pathways. The annotated genes from the single CpG site and regional analyses are involved in psychiatric disorders, cardiovascular disease, cognitive impairment, and cancer. Identified pathways were related to cancer, and neurodevelopmental and neurodegenerative disorders. CONCLUSION Our findings provide new insights into possible mechanisms underlying optimism and health.
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Affiliation(s)
- Cuicui Wang
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA
| | - Dawn L. DeMeo
- Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA 02115, USA
- Channing Division of Network Medicine, Brigham and Women’s Hospital, Boston, MA 02115, USA
| | - Eric S. Kim
- Department of Social and Behavioral Sciences, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA
- Lee Kum Sheung Center for Health and Happiness, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA
- Department of Psychology, University of British Columbia, BC V6T 1Z4, Canada
| | - Andres Cardenas
- Division of Environmental Health Sciences, School of Public Health, University of California, Berkeley, Berkeley, CA 94720, USA
- Department of Population Medicine, Division of Chronic Disease Research Across the Lifecourse, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, MA 02215, USA
| | - Kelvin C. Fong
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA
- School of the Environment, Yale University, New Haven, CT 06511, USA
| | - Lewina O. Lee
- National Center for Posttraumatic Stress Disorder, VA Boston Healthcare System, Boston, MA 02130, USA
- Department Psychiatry, Boston University School of Medicine, Boston, MA 02118, USA
| | - Avron Spiro
- Department Psychiatry, Boston University School of Medicine, Boston, MA 02118, USA
- Massachusetts Veterans Epidemiology Research and Information Center, Veterans Affairs Boston Healthcare System, Boston, MA 02130, USA
- Department of Epidemiology, Boston University School of Public Health, Boston, MA 02118, USA
| | - Eric A. Whitsel
- Department of Epidemiology, Gillings School of Global Public Health, Chapel Hill, NC 27599, USA
- Department of Medicine, School of Medicine, University of North Carolina, Chapel Hill, NC 27599, USA
| | - Steve Horvath
- Department of Human Genetics, University of California, Los Angeles, CA 90095, USA
- Department of Biostatistics, David Geffen School of Medicine, University of California, Los Angeles, CA 90095, USA
| | - Lifang Hou
- Department of Preventive Medicine, Northwestern Feinberg School of Medicine, Northwestern University, Chicago, IL, 60611, USA
| | - Andrea A. Baccarelli
- Department of Environmental Health Sciences, Columbia Mailman School of Public Health, New York, NY 10032, USA
| | - Yun Li
- Department of Genetics, University of North Carolina, Chapel Hill, NC 27599, USA
- Department of Biostatistics, University of North Carolina, Chapel Hill, NC 27599, USA
- Department of Computer Science, University of North Carolina, Chapel Hill, NC, 27599 USA
| | - James D. Stewart
- Cardiovascular Program, Department of Epidemiology, University of North Carolina Gillings School of Global Public Health, Chapel Hill, NC, 27599, USA
| | - JoAnn E. Manson
- Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA 02115, USA
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA
| | - Francine Grodstein
- Channing Division of Network Medicine, Brigham and Women’s Hospital, Boston, MA 02115, USA
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA
| | - Laura D. Kubzansky
- Department of Social and Behavioral Sciences, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA
- Lee Kum Sheung Center for Health and Happiness, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA
| | - Joel D. Schwartz
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA
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15
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Feng S, Huang F, Zhang Y, Feng Y, Zhang Y, Cao Y, Wang X. The pathophysiological and molecular mechanisms of atmospheric PM 2.5 affecting cardiovascular health: A review. Ecotoxicol Environ Saf 2023; 249:114444. [PMID: 38321663 DOI: 10.1016/j.ecoenv.2022.114444] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/18/2022] [Revised: 12/13/2022] [Accepted: 12/15/2022] [Indexed: 02/08/2024]
Abstract
BACKGROUND Exposure to ambient fine particulate matter (PM2.5, with aerodynamic diameter less than 2.5 µm) is a leading environmental risk factor for global cardiovascular health concern. OBJECTIVE To provide a roadmap for those new to this field, we reviewed the new insights into the pathophysiological and cellular/molecular mechanisms of PM2.5 responsible for cardiovascular health. MAIN FINDINGS PM2.5 is able to disrupt multiple physiological barriers integrity and translocate into the systemic circulation and get access to a range of secondary target organs. An ever-growing body of epidemiological and controlled exposure studies has evidenced a causal relationship between PM2.5 exposure and cardiovascular morbidity and mortality. A variety of cellular and molecular biology mechanisms responsible for the detrimental cardiovascular outcomes attributable to PM2.5 exposure have been described, including metabolic activation, oxidative stress, genotoxicity, inflammation, dysregulation of Ca2+ signaling, disturbance of autophagy, and induction of apoptosis, by which PM2.5 exposure impacts the functions and fates of multiple target cells in cardiovascular system or related organs and further alters a series of pathophysiological processes, such as cardiac autonomic nervous system imbalance, increasing blood pressure, metabolic disorder, accelerated atherosclerosis and plaque vulnerability, platelet aggregation and thrombosis, and disruption in cardiac structure and function, ultimately leading to cardiovascular events and death. Therein, oxidative stress and inflammation were suggested to play pivotal roles in those pathophysiological processes. CONCLUSION Those biology mechanisms have deepen insights into the etiology, course, prevention and treatment of this public health concern, although the underlying mechanisms have not yet been entirely clarified.
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Affiliation(s)
- Shaolong Feng
- The Guangxi Key Laboratory of Environmental Exposomics and Entire Lifecycle Heath, School of Public Health, Guilin Medical University, Guilin 541199, China; Guangdong Provincial Key Laboratory of Environmental Protection and Resources Utilization, Guangzhou 510640, China; The State Key Laboratory of Organic Geochemistry, Guangzhou Institute of Geochemistry, Chinese Academy of Sciences, Guangzhou 510640, China.
| | - Fangfang Huang
- The Guangxi Key Laboratory of Environmental Exposomics and Entire Lifecycle Heath, School of Public Health, Guilin Medical University, Guilin 541199, China
| | - Yuqi Zhang
- The Guangxi Key Laboratory of Environmental Exposomics and Entire Lifecycle Heath, School of Public Health, Guilin Medical University, Guilin 541199, China
| | - Yashi Feng
- The Guangxi Key Laboratory of Environmental Exposomics and Entire Lifecycle Heath, School of Public Health, Guilin Medical University, Guilin 541199, China
| | - Ying Zhang
- The Guangxi Key Laboratory of Environmental Exposomics and Entire Lifecycle Heath, School of Public Health, Guilin Medical University, Guilin 541199, China
| | - Yunchang Cao
- The Department of Molecular Biology, School of Intelligent Medicine and Biotechnology, Guilin Medical University, Guilin 541199, China
| | - Xinming Wang
- Guangdong Provincial Key Laboratory of Environmental Protection and Resources Utilization, Guangzhou 510640, China; The State Key Laboratory of Organic Geochemistry, Guangzhou Institute of Geochemistry, Chinese Academy of Sciences, Guangzhou 510640, China
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16
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Shi W, Gao X, Cao Y, Chen Y, Cui Q, Deng F, Yang B, Lin EZ, Fang J, Li T, Tang S, Godri Pollitt KJ, Shi X. Personal airborne chemical exposure and epigenetic ageing biomarkers in healthy Chinese elderly individuals: Evidence from mixture approaches. Environ Int 2022; 170:107614. [PMID: 36375280 DOI: 10.1016/j.envint.2022.107614] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/14/2022] [Revised: 10/24/2022] [Accepted: 11/02/2022] [Indexed: 06/16/2023]
Abstract
BACKGROUND Air pollution is associated with accelerated biological ages determined by DNA methylation (DNAm) patterns, imposing further risks of age-related adverse effects. However, little is known about the independent and joint effects of exposure to gaseous organic chemicals that may share a common source. METHODS We conducted a panel study with the 3-day exposure assessment monthly among 73 Chinese healthy elderly people aged 60 to 69 years in Jinan, Shandong province during September 2018 to January 2019.Exposure to 26 ambient organic chemical contaminants were measured by wearable passive samplers, including volatile organic compounds, polycyclic aromatic hydrocarbons (PAHs), phthalates (PAEs), nitroaromatics (NIs), polybrominated diphenyl ethers, chlorinated hydrocarbons, and organophosphate esters. The Illumina MethylationEPIC BeadChip was used to measure DNA methylation levels in blood samples, and based on which, epigenetic ageing biomarkers, including Hannum clock, Horvath clock, DNAm PhenoAge, DNAm GrimAge, and DNAm estimator of telomere length (DNAmTL) were calculated. Linear mixed effect models were used to estimate the linear associations between 3-day personal chemical exposure and the epigenetic biomarkers, Weighted quantile sum (WQS) regression and the Bayesian kernel machine regression (BKMR) model were further used to evaluate the effect of chemical mixtures. RESULTS Multiple linear mixed effects regression models showed that DNAmPhenoAge acceleration was significantly and positively associated with exposure to PAEs, NIs, and PAHs in healthy elderly individuals. Both WQS regression and BKMR models showed a significant positive association with DNAmPhenoAge acceleration with chemical exposures, in which the effect of di-n-butyl phthalate exposure showed the greatest importance. CONCLUSION These findings suggest that exposure to a mixture of airborne chemicals significantly increase the acceleration of the epigenetic biomarker of phenotypic age. These findings serve to identify toxic chemicals in the air and facilitate the evaluation of their potentially severe health effects.
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Affiliation(s)
- Wanying Shi
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China; Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, and Beijing Municipal Key Laboratory of Clinical Epidemiology, Beijing, China
| | - Xu Gao
- Department of Occupational and Environmental Health Sciences, School of Public Health, Peking University, Beijing, China
| | - Yaqiang Cao
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China; Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu, China
| | - Yuanyuan Chen
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Qian Cui
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China; School of Ecology and Environment, Inner Mongolia University, Hohhot, China
| | - Fuchang Deng
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Bo Yang
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China; School of Public Health, Baotou Medical College, Inner Mongolia University of Science and Technology, Baotou, China
| | - Elizabeth Z Lin
- Department of Environmental Health Sciences, Yale School of Public Health, New Haven, CT, USA
| | - Jianlong Fang
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, 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, China; Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu, China
| | - Song Tang
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China; Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu, China
| | - Krystal J Godri Pollitt
- Department of Environmental Health Sciences, Yale School of Public Health, New Haven, CT, USA.
| | - Xiaoming Shi
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China; Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu, China.
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17
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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. Environ Int 2022; 169:107501. [PMID: 36126422 DOI: 10.1016/j.envint.2022.107501] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [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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18
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Gao X, Huang J, Cardenas A, Zhao Y, Sun Y, Wang J, Xue L, Baccarelli AA, Guo X, Zhang L, Wu S. Short-Term Exposure of PM 2.5 and Epigenetic Aging: A Quasi-Experimental Study. Environ Sci Technol 2022; 56:14690-14700. [PMID: 36197060 DOI: 10.1021/acs.est.2c05534] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/20/2023]
Abstract
Epigenetic age (EA) is an emerging DNA methylation-based biomarker of biological aging, but whether EA is causally associated with short-term PM2.5 exposure remains unknown. We conducted a quasi-experimental study of 26 healthy adults to test whether short-term PM2.5 exposure accelerates seven EAs with three health examinations performed before, during, and after multiple PM2.5 pollution waves. Seven EAs were derived from the DNA methylation profiles of the Illumina HumanMethylationEPIC BeadChip from CD4+ T-helper cells. We found that an increase of 10 μg/m3 in the 0-24 h personal PM2.5 exposure prior to health examinations was associated with a 0.035, 0.035, 0.050, 0.055, 0.052, and 0.037-unit increase in the changes of z-scored DNA methylation age acceleration (AA,Horvath), AA (Hannum), AA (GrimAge), DunedinPoAm, mortality risk score (MS), and epiTOC, respectively (p-values < 0.05). The same increase in the 24-48 h average personal PM2.5 exposure yielded smaller effects but was still robustly associated with the changes in AA (GrimAge), DunedinPoAm, and MS. Such acute aging effects of PM2.5 were mediated by the changes in several circulating biomarkers, including EC-SOD and sCD40L, with up to ∼28% mediated proportions. Our findings demonstrated that short-term PM2.5 exposure could accelerate aging reflected by DNA methylation profiles via blood coagulation, oxidative stress, and systematic inflammation.
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Affiliation(s)
- Xu Gao
- Department of Occupational and Environmental Health Sciences, School of Public Health, Peking University, Beijing100191, China
| | - Jing Huang
- Department of Occupational and Environmental Health Sciences, School of Public Health, Peking University, Beijing100191, China
| | - Andres Cardenas
- Division of Environmental Health Sciences, School of Public Health and Center for Computational Biology, University of California, Berkeley, California94720, United States
| | - Yan Zhao
- Department of Occupational and Environmental Health Sciences, School of Public Health, Peking University, Beijing100191, China
| | - Yanyan Sun
- Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, and Beijing Municipal Key Laboratory of Clinical Epidemiology, Beijing100069, China
| | - Jiawei Wang
- Department of Occupational and Environmental Health Sciences, School of Public Health, Peking University, Beijing100191, China
| | - Lijun Xue
- Department of Occupational and Environmental Health Sciences, School of Public Health, Peking University, Beijing100191, China
| | - Andrea A Baccarelli
- Laboratory of Environmental Precision Health, Mailman School of Public Health, Columbia University, New York, New York10032, United States
| | - Xinbiao Guo
- Department of Occupational and Environmental Health Sciences, School of Public Health, Peking University, Beijing100191, China
| | - Ling Zhang
- Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, and Beijing Municipal Key Laboratory of Clinical Epidemiology, Beijing100069, China
| | - Shaowei Wu
- Department of Occupational and Environmental Health, School of Public Health, Xi'an Jiaotong University Health Science Center, Xi'an710061, China
- Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, Xi'an, Shaanxi710061, China
- Key Laboratory of Trace Elements and Endemic Diseases in Ministry of Health, Xi'an, Shaanxi710061, China
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19
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Bozack AK, Boileau P, Hubbard AE, Sillé FCM, Ferreccio C, Steinmaus CM, Smith MT, Cardenas A. The impact of prenatal and early-life arsenic exposure on epigenetic age acceleration among adults in Northern Chile. Environ Epigenet 2022; 8:dvac014. [PMID: 35769198 PMCID: PMC9235373 DOI: 10.1093/eep/dvac014] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/21/2022] [Revised: 05/02/2022] [Accepted: 05/31/2022] [Indexed: 06/15/2023]
Abstract
Exposure to arsenic affects millions of people globally. Changes in the epigenome may be involved in pathways linking arsenic to health or serve as biomarkers of exposure. This study investigated associations between prenatal and early-life arsenic exposure and epigenetic age acceleration (EAA) in adults, a biomarker of morbidity and mortality. DNA methylation was measured in peripheral blood mononuclear cells (PBMCs) and buccal cells from 40 adults (median age = 49 years) in Chile with and without high prenatal and early-life arsenic exposure. EAA was calculated using the Horvath, Hannum, PhenoAge, skin and blood, GrimAge, and DNA methylation telomere length clocks. We evaluated associations between arsenic exposure and EAA using robust linear models. Participants classified as with and without arsenic exposure had a median drinking water arsenic concentration at birth of 555 and 2 μg/l, respectively. In PBMCs, adjusting for sex and smoking, exposure was associated with a 6-year PhenoAge acceleration [B (95% CI) = 6.01 (2.60, 9.42)]. After adjusting for cell-type composition, we found positive associations with Hannum EAA [B (95% CI) = 3.11 (0.13, 6.10)], skin and blood EAA [B (95% CI) = 1.77 (0.51, 3.03)], and extrinsic EAA [B (95% CI) = 4.90 (1.22, 8.57)]. The association with PhenoAge acceleration in buccal cells was positive but not statistically significant [B (95% CI) = 4.88 (-1.60, 11.36)]. Arsenic exposure limited to early-life stages may be associated with biological aging in adulthood. Future research may provide information on how EAA programmed in early life is related to health.
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Affiliation(s)
- Anne K Bozack
- Division of Environmental Health Sciences, School of Public Health, University of California, 2121 Berkeley Way, Room 5302, Berkeley, CA 94720, USA
| | - Philippe Boileau
- Graduate Group in Biostatistics, University of California, 2121 Berkeley Way, Room 5302, Berkeley, CA 94720, USA
| | - Alan E Hubbard
- Graduate Group in Biostatistics, University of California, 2121 Berkeley Way, Room 5302, Berkeley, CA 94720, USA
| | - Fenna C M Sillé
- Department of Environmental Health and Engineering, The Johns Hopkins University Bloomberg School of Public Health, 615 N. Wolfe Street, Room E7527, Baltimore, MD 21205, USA
| | - Catterina Ferreccio
- Advanced Center for Chronic Diseases (ACCDiS), School of Medicine, Pontificia Universidad Católica de Chile, Sergio Livingstone 1007, Independencia, Santiago, Chile
| | - Craig M Steinmaus
- Division of Environmental Health Sciences, School of Public Health, University of California, 2121 Berkeley Way, Room 5302, Berkeley, CA 94720, USA
| | - Martyn T Smith
- Division of Environmental Health Sciences, School of Public Health, University of California, 2121 Berkeley Way, Room 5302, Berkeley, CA 94720, USA
| | - Andres Cardenas
- *Correspondence address. Division of Environmental Health Sciences, School of Public Health, University of California, 2121 Berkeley Way, Room 5302, Berkeley, CA 94720, USA. Tel: +510-643-0965; E-mail:
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20
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Wang C, Cardenas A, Hutchinson JN, Just A, Heiss J, Hou L, Zheng Y, Coull BA, Kosheleva A, Koutrakis P, Baccarelli AA, Schwartz JD. Short- and intermediate-term exposure to ambient fine particulate elements and leukocyte epigenome-wide DNA methylation in older men: the Normative Aging Study. Environ Int 2022; 158:106955. [PMID: 34717175 PMCID: PMC8710082 DOI: 10.1016/j.envint.2021.106955] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/18/2021] [Revised: 10/18/2021] [Accepted: 10/22/2021] [Indexed: 05/08/2023]
Abstract
BACKGROUND Several epigenome-wide association studies (EWAS) of ambient particulate matter with aerodynamic diameter ≤ 2.5 µm (PM2.5) have been reported. However, EWAS of PM2.5 elements (PEs), reflecting different emission sources, are very limited. OBJECTIVES We performed EWAS of short- and intermediate-term exposure to PM2.5 and 13 PEs. We hypothesized that significant changes in DNAm may vary by PM2.5 mass and its elements. METHODS We repeatedly collected blood samples in the Normative Aging Study and measured leukocyte DNA methylation (DNAm) with the Illumina HumanMethylation450K BeadChip. We collected daily PM2.5 and 13 PEs at a fixed central site. To estimate the associations between each PE and DNAm at individual cytosine-phosphate-guanine (CpG) sites, we incorporated a distributed-lag (0-27 d) term in the setting of median regression with subject-specific intercept and examined cumulative lag associations. We also accounted for selection bias due to loss to follow-up and mortality prior to enrollment. Significantly differentially methylated probes (DMPs) were identified using Bonferroni correction for multiple testing. We further conducted regional and pathway analyses to identify significantly differentially methylated regions (DMRs) and pathways. RESULTS We included 695 men with 1,266 visits between 1999 and 2013. The subjects had a mean age of 75 years. The significant DMPs, DMRs, and pathways varied by to PM2.5 total mass and PEs. For example, PM2.5 total mass was associated with 2,717 DMPs and 10,470 DMRs whereas Pb was associated with 3,173 DMPs and 637 DMRs. The identified pathways by PM2.5 mass were mostly involved in mood disorders, neuroplasticity, immunity, and inflammation, whereas the pathways associated with motor vehicles (BC, Cu, Pb, and Zn) were related with cardiovascular disease and cancer (e.g., "PPARs signaling"). CONCLUSIONS PM2.5 and PE were associated with methylation changes at multiple probes and along multiple pathways, in ways that varied by particle components.
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Affiliation(s)
- Cuicui Wang
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA.
| | - Andres Cardenas
- Division of Environmental Health Sciences, School of Public Health and Center for Computational Biology, University of California, Berkeley, Berkeley, CA 94720, USA
| | - John N Hutchinson
- Department of Biostatistics, Harvard T. H. Chan School of Public Health, Boston, MA 02115, USA
| | - Allan Just
- Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Jonathan Heiss
- Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Lifang Hou
- Department of Preventive Medicine, Feinberg School of Medicine, Northwestern University, Chicago, IL 60611, USA
| | - Yinan Zheng
- Department of Preventive Medicine, Feinberg School of Medicine, Northwestern University, Chicago, IL 60611, USA
| | - Brent A Coull
- Department of Biostatistics, Harvard T. H. Chan School of Public Health, Boston, MA 02115, USA
| | - Anna Kosheleva
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA
| | - Petros Koutrakis
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA
| | - Andrea A Baccarelli
- Department of Environmental Health Sciences, Columbia Mailman School of Public Health, New York, NY 10032, USA
| | - Joel D Schwartz
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA; Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA
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21
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Oblak L, van der Zaag J, Higgins-Chen AT, Levine ME, Boks MP. A systematic review of biological, social and environmental factors associated with epigenetic clock acceleration. Ageing Res Rev 2021; 69:101348. [PMID: 33930583 DOI: 10.1016/j.arr.2021.101348] [Citation(s) in RCA: 169] [Impact Index Per Article: 56.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2020] [Revised: 04/01/2021] [Accepted: 04/21/2021] [Indexed: 02/06/2023]
Abstract
Aging involves a diverse set of biological changes accumulating over time that leads to increased risk of morbidity and mortality. Epigenetic clocks are now widely used to quantify biological aging, in order to investigate determinants that modify the rate of aging and to predict age-related outcomes. Numerous biological, social and environmental factors have been investigated for their relationship to epigenetic clock acceleration and deceleration. The aim of this review was to synthesize general trends concerning the associations between human epigenetic clocks and these investigated factors. We conducted a systematic review of all available literature and included 156 publications across 4 resource databases. We compiled a list of all presently existing blood-based epigenetic clocks. Subsequently, we created an extensive dataset of over 1300 study findings in which epigenetic clocks were utilized in blood tissue of human subjects to assess the relationship between these clocks and numeral environmental exposures and human traits. Statistical analysis was possible on 57 such relationships, measured across 4 different epigenetic clocks (Hannum, Horvath, Levine and GrimAge). We found that the Horvath, Hannum, Levine and GrimAge epigenetic clocks tend to agree in direction of effects, but vary in size. Body mass index, HIV infection, and male sex were significantly associated with acceleration of one or more epigenetic clocks. Acceleration of epigenetic clocks was also significantly related to mortality, cardiovascular disease, cancer and diabetes. Our findings provide a graphical and numerical synopsis of the past decade of epigenetic age estimation research and indicate areas where further attention could be focused in the coming years.
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22
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Nassan FL, Wang C, Kelly RS, Lasky-Su JA, Vokonas PS, Koutrakis P, Schwartz JD. Ambient PM 2.5 species and ultrafine particle exposure and their differential metabolomic signatures. Environ Int 2021; 151:106447. [PMID: 33639346 PMCID: PMC7994935 DOI: 10.1016/j.envint.2021.106447] [Citation(s) in RCA: 39] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/10/2020] [Accepted: 02/03/2021] [Indexed: 05/09/2023]
Abstract
BACKGROUND The metabolomic signatures of short- and long-term exposure to PM2.5 have been reported and linked to inflammation and oxidative stress. However, little is known about the relative contribution of the specific PM2.5 species (hence sources) that drive these metabolomic signatures. OBJECTIVES We aimed to determine the relative contribution of the different species of PM2.5 exposure to the perturbed metabolic pathways related to changes in the plasma metabolome. METHODS We performed mass-spectrometry based metabolomic profiling of plasma samples among men from the Normative Aging Study to identify metabolic pathways associated with PM2.5 species. The exposure windows included short-term (one, seven-, and thirty-day moving average) and long-term (one year moving average). We used linear mixed-effect regression with subject-specific intercepts while simultaneously adjusting for PM2.5, NO2, O3, temperature, relative humidity, and covariates and correcting for multiple testing. We also used independent component analysis (ICA) to examine the relative contribution of patterns of PM2.5 species. RESULTS Between 2000 and 2016, 456 men provided 648 blood samples, in which 1158 metabolites were quantified. We chose 305 metabolites for the short-term and 288 metabolites for the long-term exposure in this analysis that were significantly associated (p-value < 0.01) with PM2.5 to include in our PM2.5 species analysis. On average, men were 75.0 years old and their body mass index was 27.7 kg/m2. Only 3% were current smokers. In the adjusted models, ultrafine particles (UFPs) were the most significant species of short-term PM2.5 exposure followed by nickel, vanadium, potassium, silicon, and aluminum. Black carbon, vanadium, zinc, nickel, iron, copper, and selenium were the significant species of long-term PM2.5 exposure. We identified several metabolic pathways perturbed with PM2.5 species including glycerophospholipid, sphingolipid, and glutathione. These pathways are involved in inflammation, oxidative stress, immunity, and nucleic acid damage and repair. Results were overlapped with the ICA. CONCLUSIONS We identified several significant perturbed plasma metabolites and metabolic pathways associated with exposure to PM2.5 species. These species are associated with traffic, fuel oil, and wood smoke. This is the largest study to report a metabolomic signature of PM2.5 species' exposure and the first to use ICA.
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Affiliation(s)
- Feiby L Nassan
- Department of Environmental Health, Harvard T. H. Chan School of Public Health, Boston, MA 02115, USA.
| | - Cuicui Wang
- Department of Environmental Health, Harvard T. H. Chan School of Public Health, Boston, MA 02115, USA
| | - Rachel S Kelly
- Channing Division of Network Medicine; Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02129, USA
| | - Jessica A Lasky-Su
- Channing Division of Network Medicine; Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02129, USA
| | - Pantel S Vokonas
- VA Normative Aging Study, VA Boston Healthcare System, School of Medicine and School of Public Health, Boston University, Boston, MA 02215, USA
| | - Petros Koutrakis
- Department of Environmental Health, Harvard T. H. Chan School of Public Health, Boston, MA 02115, USA
| | - Joel D Schwartz
- Department of Environmental Health, Harvard T. H. Chan School of Public Health, Boston, MA 02115, USA; Channing Division of Network Medicine; Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02129, USA; Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, MA 02115, USA
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23
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Xiao L, Zan G, Feng X, Bao Y, Huang S, Luo X, Xu X, Zhang Z, Yang X. The associations of multiple metals mixture with accelerated DNA methylation aging. Environ Pollut 2021; 269:116230. [PMID: 33316491 DOI: 10.1016/j.envpol.2020.116230] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/09/2020] [Revised: 10/29/2020] [Accepted: 12/03/2020] [Indexed: 06/12/2023]
Abstract
Aging is a leading cause of mortality for the elderly and DNA methylation age is reported to be predictive of biological aging. However, few studies have investigated the associations between multiple metals exposure and accelerated aging in the elderly. We performed a pilot study of 288 elderly participants aged 50-115 years and measured genome-wide DNA methylation and 22 blood metals concentrations. Measures of DNA methylation age were estimated using CpGs from Illumina HumanMethylation EPIC BeadChip. Linear mixed regression and Bayesian kernel machine regression (BKMR) models were used to estimate the individual and overall associations between multiple metals and accelerated methylation aging. Single metal models revealed that each 1-standard deviance (SD) increase in log-transformed vanadium, cobalt, nickel, zinc, arsenic, and barium was associated with a -2.256, -1.318, 1.004, -1.926, 1.910 and -1.356 changes in ΔAge, respectively; meanwhile, for aging rate, the change was -0.019, -0.013, 0.010, -0.018, 0.023, and -0.012, respectively (all P < 0.05). The BKMR models showed reverse U-shaped associations of the overall metals mixture with ΔAge and aging rate. Downward trends of ΔAge and aging rate were observed for increasing quantiles of essential metals mixture, but upward trends were observed for non-essential metals mixture. Further individual analysis of the BKMR revealed that the 95% confidence interval of ΔAge and aging rate associated with vanadium, zinc, and arsenic did not cross 0, when other metals concentrations set at 25th, 50th, and 75th percentile. Our findings suggest reverse U-shaped associations of the overall metals mixture with accelerated methylation aging for the first time, and vanadium, zinc, and arsenic may be major contributors driving the associations.
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Affiliation(s)
- Lili Xiao
- Department of Occupational Health and Environmental Health, School of Public Health, Guangxi Medical University, Nanning, Guangxi, China
| | - Gaohui Zan
- Department of Occupational Health and Environmental Health, School of Public Health, Guangxi Medical University, Nanning, Guangxi, China
| | - Xiuming Feng
- Department of Occupational Health and Environmental Health, School of Public Health, Guangxi Medical University, Nanning, Guangxi, China
| | - Yu Bao
- Department of Occupational Health and Environmental Health, School of Public Health, Guangxi Medical University, Nanning, Guangxi, China
| | - Sifang Huang
- Department of Occupational Health and Environmental Health, School of Public Health, Guangxi Medical University, Nanning, Guangxi, China
| | - Xiaoyu Luo
- Department of Occupational Health and Environmental Health, School of Public Health, Guangxi Medical University, Nanning, Guangxi, China
| | - Xia Xu
- Department of Occupational Health and Environmental Health, School of Public Health, Guangxi Medical University, Nanning, Guangxi, China
| | - Zhiyong Zhang
- School of Public Health, Guilin Medical University, Guilin, Guangxi, China
| | - Xiaobo Yang
- Department of Occupational Health and Environmental Health, School of Public Health, Guangxi Medical University, Nanning, Guangxi, China; Department of Public Health, School of Medicine, Guangxi University of Science and Technology, Liuzhou, Guangxi, China.
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24
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Abstract
Aging is an inevitable biological phenomenon displayed by single cells and organs to entire organismal systems. Aging as a biological process is characterized as a progressive decline in intrinsic biological function. Understanding the causative mechanisms of aging has always captured the imagination of researchers since time immemorial. Although both biological and chronological aging are well defined and studied in terms of genetic, epigenetic, and lifestyle predispositions, the hallmarks of aging in terms of small molecules (i.e., endogenous metabolites to chemical exposures) are limited to obscure. On top of the endogenous metabolites leading to the onset and progression of healthy aging, human beings are constantly exposed to a natural and anthropogenic "chemical" environment round the clock, from conception till death, affecting one's physiology, health and well-being, and disease predisposition. The research community has started gaining sizeable insights into deciphering the aging factors such as immunosenescence, nutrition, frailty, inflamm-aging, and diseases till date, without much input from their interaction with exogenous chemical exposures. The "exposome" around us, mostly, accelerates the process of aging by affecting the internal biological pathways and signaling mechanisms that result in the deterioration of human health. However, the entirety of exposome on human aging is far from established. This review intends to catalog the known and established associations of the exposome from past studies focusing on aging in humans and other model organisms. Further discussed are the current technologies and informatics tools that enable the study of aging exposotypes, and thus, provide a window of opportunities and challenges to study the "aging exposome" in granular details.
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25
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Nwanaji-Enwerem JC, Colicino E, Specht AJ, Gao X, Wang C, Vokonas P, Weisskopf MG, Boyer EW, Baccarelli AA, Schwartz J. Individual species and cumulative mixture relationships of 24-hour urine metal concentrations with DNA methylation age variables in older men. Environ Res 2020; 186:109573. [PMID: 32361261 PMCID: PMC7363532 DOI: 10.1016/j.envres.2020.109573] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/07/2020] [Revised: 04/19/2020] [Accepted: 04/21/2020] [Indexed: 05/16/2023]
Abstract
BACKGROUND Globally, toxic metal exposures are a well-recognized risk factor for many adverse health outcomes. DNA methylation-based measures of biological aging are predictive of disease, but have poorly understood relationships with metal exposures. OBJECTIVE We performed a pilot study examining the relationships of 24-h urine metal concentrations with three novel DNA methylation-based measures of biological aging: DNAmAge, GrimAge, and PhenoAge. METHODS We utilized a previously established urine panel of five common metals [arsenic (As), cadmium (Cd), lead (Pb), manganese (Mn), and mercury (Hg)] found in a subset of the elderly US Veterans Affairs Normative Aging Study cohort (N = 48). The measures of DNA methylation-based biological age were calculated using CpG sites on the Illumina HumanMethylation450 BeadChip. Bayesian Kernel Machine Regression (BKMR) was used to determine metals most important to the aging outcomes and the relationship of the cumulative metal mixture with the outcomes. Individual relationships of important metals with the biological aging outcomes were modeled using fully-adjusted linear models controlling for chronological age, renal function, and lifestyle/environmental factors. RESULTS Mn was selected as important to PhenoAge. A 1 ng/mL increase in urine Mn was associated with a 9.93-year increase in PhenoAge (95%CI: 1.24, 18.61, p = 0.03). The cumulative urine metal mixture was associated with increases in PhenoAge. Compared to a model where each metal in the mixture is set to its 50th percentile value, every one-unit increase of the cumulative mixture with each metal at its 70th percentile was associated with a 2.53-year increase in PhenoAge (95%CI: 0.10, 4.96, P<0.05). CONCLUSION Our results add novel evidence that metals detected in urine are associated with increases in biological aging and suggest that these DNA methylation-based measures may be useful for identifying individuals at-risk for diseases related to toxic metal exposures. Further research is necessary to confirm these findings more broadly.
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Affiliation(s)
- Jamaji C Nwanaji-Enwerem
- Belfer Center for Science and International Affairs, Harvard Kennedy School of Government, Department of Environmental Health, Harvard T.H. Chan School of Public Health, and MD/PhD Program, Harvard Medical School, Boston, MA, USA.
| | - Elena Colicino
- Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Aaron J Specht
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Xu Gao
- Department of Environmental Health Sciences, Columbia Mailman School of Public Health, New York, NY, USA
| | - Cuicui Wang
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, 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
| | - Marc G Weisskopf
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Edward W Boyer
- Division of Medical Toxicology, Department of Emergency Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - 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, Boston, MA, USA
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Wang C, Just A, Heiss J, Coull BA, Hou L, Zheng Y, Sparrow D, Vokonas PS, Baccarelli A, Schwartz J. Biomarkers of aging and lung function in the normative aging study. Aging (Albany NY) 2020; 12:11942-11966. [PMID: 32561690 PMCID: PMC7343502 DOI: 10.18632/aging.103363] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2019] [Accepted: 05/20/2020] [Indexed: 12/17/2022]
Abstract
Elderly individuals who are never smokers but have the same height and chronological age can have substantial differences in lung function. The underlying biological mechanisms are unclear. To evaluate the associations of different biomarkers of aging (BoA) and lung function, we performed a repeated-measures analysis in the Normative Aging Study using linear mixed-effect models. We generated GrimAgeAccel, PhenoAgeAccel, extrinsic and intrinsic epigenetic age acceleration using a publically available online calculator. We calculated Zhang's DNAmRiskScore based on 10 CpGs. We measured telomere length (TL) and mitochondrial DNA copy number (mtDNA-CN) using quantitative real-time polymerase chain reaction. A pulmonary function test was performed measuring forced expiratory volume in 1 second / forced vital capacity (FEV1/FVC), FEV1, and maximum mid-expiratory flow (MMEF). Epigenetic-based BoA were associated with lower lung function. For example, a one-year increase in GrimAgeAccel was associated with a 13.64 mL [95% confidence interval (CI), 5.11 to 22.16] decline in FEV1; a 0.2 increase in Zhang's DNAmRiskScore was associated with a 0.009 L/s (0.005 to 0.013) reduction in MMEF. No association was found between TL/mtDNA-CN and lung function. Overall, this paper shows that epigenetics might be a potential mechanism underlying pulmonary dysfunction in the elderly.
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Affiliation(s)
- Cuicui Wang
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA
| | - Allan Just
- Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Jonathan Heiss
- Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Brent A Coull
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA.,Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA
| | - Lifang Hou
- Department of Preventive Medicine, Feinberg School of Medicine, Northwestern University, Chicago, IL 60611, USA
| | - Yinan Zheng
- Department of Preventive Medicine, Feinberg School of Medicine, Northwestern University, Chicago, IL 60611, USA
| | - David Sparrow
- VA Normative Aging Study, VA Boston Healthcare System, Boston, MA 02130, USA.,Department of Medicine, Boston University School of Medicine, Boston, MA 02118, USA
| | - Pantel S Vokonas
- VA Normative Aging Study, VA Boston Healthcare System, Boston, MA 02130, USA.,Department of Medicine, Boston University School of Medicine, Boston, MA 02118, USA
| | - Andrea Baccarelli
- Department of Epidemiology and Environmental Health Sciences, Columbia University, New York, NY 10027, USA
| | - Joel Schwartz
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA
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