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Li Piani L, Reschini M, Somigliana E, Ferrari S, Busnelli A, Viganò P, Favero C, Albetti B, Hoxha M, Bollati V. Peripheral mitochondrial DNA, telomere length and DNA methylation as predictors of live birth in in vitro fertilization cycles. PLoS One 2022; 17:e0261591. [PMID: 35073322 PMCID: PMC8786209 DOI: 10.1371/journal.pone.0261591] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2021] [Accepted: 12/03/2021] [Indexed: 12/21/2022] Open
Abstract
OBJECTIVE To evaluate whether telomere length (TL), mitochondrial-DNA (mt-DNA) or epigenetic age estimators based on DNA methylation (DNAm) pattern could be considered reliable predictors of in-vitro-fertilization (IVF) success in terms of live birth rate. DESIGN Prospective cohort study. SETTING Infertility Unit of the Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico. PATIENTS 181 women aged 37-39 years who underwent IVF at a single-centre between January 2017 and December 2018. INTERVENTIONS On the day of recruitment, blood samples were collected, and genomic DNA was isolated from white blood cells. TL, mt-DNA and DNAm assessment was performed using quantitative real-time polymerase chain reaction (qPCR). Biological age (DNAm age) was computed as the algorithm based on methylation pattern of five genes. Epigenetic age acceleration was estimated from the residuals of the linear model of epigenetic age regressed on chronological age. Long Interspersed Nuclear Elements (LINE)-1 methylation pattern was used as a surrogate for global DNA methylation. MAIN OUTCOME MEASURES This study investigated whether peripheral TL, mt-DNA and DNAm could predict live birth in IVF cycles. RESULTS TL, mt-DNA and LINE-1 methylation were not associated with IVF success. Conversely, DNAm age resulted significantly lower in women who had a live birth compared to women who did not (36.1 ± 4.2 and 37.3 ± 3.3 years, respectively, p = 0.04). For DNAm age, odds ratio (OR) for live birth per year of age was 0.90 (95%CI: 0.82-0.99, p = 0.036) after adjusting for FSH and antral follicle count (AFC) and 0.90 (95%CI: 0.82-0.99, p = 0.028) after adjusting also for number of oocytes retrieved. A significant association also emerged for epigenetic age acceleration after adjustments (OR = 0.91, 95%CI: 0.83-1.00, p = 0.048). CONCLUSION DNAm age is associated with IVF success but the magnitude of this association is insufficient to claim a clinical use. However, our findings are promising and warrant further investigation. Assessment of biological age using different epigenetic clocks or focusing on different tissues may reveal new predictors of IVF success.
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Affiliation(s)
- Letizia Li Piani
- Dept of Clinical Sciences and Community Health, Università degli Studi di Milano, Milan, Italy
- Infertility Unit, Fondazione IRCCS Ca’ Granda Ospedale Maggiore Policlinico, Milan, Italy
| | - Marco Reschini
- Infertility Unit, Fondazione IRCCS Ca’ Granda Ospedale Maggiore Policlinico, Milan, Italy
| | - Edgardo Somigliana
- Dept of Clinical Sciences and Community Health, Università degli Studi di Milano, Milan, Italy
- Infertility Unit, Fondazione IRCCS Ca’ Granda Ospedale Maggiore Policlinico, Milan, Italy
| | - Stefania Ferrari
- Infertility Unit, Fondazione IRCCS Ca’ Granda Ospedale Maggiore Policlinico, Milan, Italy
| | - Andrea Busnelli
- Department of Biomedical Sciences, Humanitas University, Pieve Emanuele, Milan, Italy
- Division of Gynecology and Reproductive Medicine, Department of Gynecology, IRCCS Humanitas Research Hospital, Fertility Center, Rozzano, Milan, Italy
| | - Paola Viganò
- Infertility Unit, Fondazione IRCCS Ca’ Granda Ospedale Maggiore Policlinico, Milan, Italy
| | - Chiara Favero
- Dept of Clinical Sciences and Community Health, Università degli Studi di Milano, Milan, Italy
| | - Benedetta Albetti
- Dept of Clinical Sciences and Community Health, Università degli Studi di Milano, Milan, Italy
| | - Mirjam Hoxha
- Dept of Clinical Sciences and Community Health, Università degli Studi di Milano, Milan, Italy
| | - Valentina Bollati
- Dept of Clinical Sciences and Community Health, Università degli Studi di Milano, Milan, Italy
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202
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Macdonald-Dunlop E, Taba N, Klarić L, Frkatović A, Walker R, Hayward C, Esko T, Haley C, Fischer K, Wilson JF, Joshi PK. A catalogue of omics biological ageing clocks reveals substantial commonality and associations with disease risk. Aging (Albany NY) 2022; 14:623-659. [PMID: 35073279 PMCID: PMC8833109 DOI: 10.18632/aging.203847] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2021] [Accepted: 12/20/2021] [Indexed: 11/25/2022]
Abstract
Biological age (BA), a measure of functional capacity and prognostic of health outcomes that discriminates between individuals of the same chronological age (chronAge), has been estimated using a variety of biomarkers. Previous comparative studies have mainly used epigenetic models (clocks), we use ~1000 participants to compare fifteen omics ageing clocks, with correlations of 0.21-0.97 with chronAge, even with substantial sub-setting of biomarkers. These clocks track common aspects of ageing with 95% of the variance in chronAge being shared among clocks. The difference between BA and chronAge - omics clock age acceleration (OCAA) - often associates with health measures. One year’s OCAA typically has the same effect on risk factors/10-year disease incidence as 0.09/0.25 years of chronAge. Epigenetic and IgG glycomics clocks appeared to track generalised ageing while others capture specific risks. We conclude BA is measurable and prognostic and that future work should prioritise health outcomes over chronAge.
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Affiliation(s)
- Erin Macdonald-Dunlop
- Centre for Global Health Research, Usher Institute, University of Edinburgh, Edinburgh EH8 9AG, UK
| | - Nele Taba
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu 51010, Estonia.,Institute of Molecular and Cell Biology, University of Tartu, Tartu 51010, Estonia
| | - Lucija Klarić
- MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Western General Hospital, Edinburgh EH4 2XU, UK
| | - Azra Frkatović
- Genos Glycoscience Research Laboratory, Zagreb 10000, Croatia
| | - Rosie Walker
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh EH4 2XU, UK
| | - Caroline Hayward
- MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Western General Hospital, Edinburgh EH4 2XU, UK
| | - Tõnu Esko
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu 51010, Estonia.,Program in Medical and Population Genetics, Broad Institute, Cambridge, MA 02142, USA
| | - Chris Haley
- MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Western General Hospital, Edinburgh EH4 2XU, UK
| | - Krista Fischer
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu 51010, Estonia.,Institute of Mathematics and Statistics, University of Tartu, Tartu 51009, Estonia
| | - James F Wilson
- Centre for Global Health Research, Usher Institute, University of Edinburgh, Edinburgh EH8 9AG, UK.,MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Western General Hospital, Edinburgh EH4 2XU, UK
| | - Peter K Joshi
- Centre for Global Health Research, Usher Institute, University of Edinburgh, Edinburgh EH8 9AG, UK
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203
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McCartney DL, Hillary RF, Conole ELS, Banos DT, Gadd DA, Walker RM, Nangle C, Flaig R, Campbell A, Murray AD, Maniega SM, Valdés-Hernández MDC, Harris MA, Bastin ME, Wardlaw JM, Harris SE, Porteous DJ, Tucker-Drob EM, McIntosh AM, Evans KL, Deary IJ, Cox SR, Robinson MR, Marioni RE. Blood-based epigenome-wide analyses of cognitive abilities. Genome Biol 2022; 23:26. [PMID: 35039062 PMCID: PMC8762878 DOI: 10.1186/s13059-021-02596-5] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2021] [Accepted: 12/29/2021] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Blood-based markers of cognitive functioning might provide an accessible way to track neurodegeneration years prior to clinical manifestation of cognitive impairment and dementia. RESULTS Using blood-based epigenome-wide analyses of general cognitive function, we show that individual differences in DNA methylation (DNAm) explain 35.0% of the variance in general cognitive function (g). A DNAm predictor explains ~4% of the variance, independently of a polygenic score, in two external cohorts. It also associates with circulating levels of neurology- and inflammation-related proteins, global brain imaging metrics, and regional cortical volumes. CONCLUSIONS As sample sizes increase, the ability to assess cognitive function from DNAm data may be informative in settings where cognitive testing is unreliable or unavailable.
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Affiliation(s)
- Daniel L. McCartney
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, EH4 2XU UK
| | - Robert F. Hillary
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, EH4 2XU UK
| | - Eleanor L. S. Conole
- Lothian Birth Cohorts, Department of Psychology, University of Edinburgh, Edinburgh, EH8 9JZ UK
- Centre for Clinical Brain Sciences, UK Dementia Research Institute at the University of Edinburgh, Chancellor’s Building, 49 Little France Crescent, Edinburgh BioQuarter, Edinburgh, EH16 4SB UK
| | - Daniel Trejo Banos
- Department of Quantitative Biomedicine, University of Zurich, Zurich, Switzerland
- Biomedical Informatics, University Hospital of Zurich, Zurich, Switzerland
| | - Danni A. Gadd
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, EH4 2XU UK
| | - Rosie M. Walker
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, EH4 2XU UK
- Centre for Clinical Brain Sciences, UK Dementia Research Institute at the University of Edinburgh, Chancellor’s Building, 49 Little France Crescent, Edinburgh BioQuarter, Edinburgh, EH16 4SB UK
| | - Cliff Nangle
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, EH4 2XU UK
| | - Robin Flaig
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, EH4 2XU UK
| | - Archie Campbell
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, EH4 2XU UK
| | - Alison D. Murray
- Aberdeen Biomedical Imaging Centre, University of Aberdeen, Aberdeen, Scotland, UK
| | - Susana Muñoz Maniega
- Lothian Birth Cohorts, Department of Psychology, University of Edinburgh, Edinburgh, EH8 9JZ UK
- Centre for Clinical Brain Sciences, UK Dementia Research Institute at the University of Edinburgh, Chancellor’s Building, 49 Little France Crescent, Edinburgh BioQuarter, Edinburgh, EH16 4SB UK
| | - María del C. Valdés-Hernández
- Lothian Birth Cohorts, Department of Psychology, University of Edinburgh, Edinburgh, EH8 9JZ UK
- Centre for Clinical Brain Sciences, UK Dementia Research Institute at the University of Edinburgh, Chancellor’s Building, 49 Little France Crescent, Edinburgh BioQuarter, Edinburgh, EH16 4SB UK
| | - Mathew A. Harris
- Lothian Birth Cohorts, Department of Psychology, University of Edinburgh, Edinburgh, EH8 9JZ UK
| | - Mark E. Bastin
- Lothian Birth Cohorts, Department of Psychology, University of Edinburgh, Edinburgh, EH8 9JZ UK
- Centre for Clinical Brain Sciences, UK Dementia Research Institute at the University of Edinburgh, Chancellor’s Building, 49 Little France Crescent, Edinburgh BioQuarter, Edinburgh, EH16 4SB UK
| | - Joanna M. Wardlaw
- Lothian Birth Cohorts, Department of Psychology, University of Edinburgh, Edinburgh, EH8 9JZ UK
- Centre for Clinical Brain Sciences, UK Dementia Research Institute at the University of Edinburgh, Chancellor’s Building, 49 Little France Crescent, Edinburgh BioQuarter, Edinburgh, EH16 4SB UK
| | - Sarah E. Harris
- Lothian Birth Cohorts, Department of Psychology, University of Edinburgh, Edinburgh, EH8 9JZ UK
| | - David J. Porteous
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, EH4 2XU UK
| | - Elliot M. Tucker-Drob
- Department of Psychology, University of Texas, Austin, TX USA
- Population Research Center and Center on Aging and Population Sciences, University of Texas, Austin, TX USA
| | - Andrew M. McIntosh
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, EH4 2XU UK
- Division of Psychiatry, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - Kathryn L. Evans
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, EH4 2XU UK
| | - Ian J. Deary
- Lothian Birth Cohorts, Department of Psychology, University of Edinburgh, Edinburgh, EH8 9JZ UK
| | - Simon R. Cox
- Lothian Birth Cohorts, Department of Psychology, University of Edinburgh, Edinburgh, EH8 9JZ UK
| | | | - Riccardo E. Marioni
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, EH4 2XU UK
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204
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Malyutina S, Chervova O, Tillmann T, Maximov V, Ryabikov A, Gafarov V, Hubacek JA, Pikhart H, Beck S, Bobak M. The Relationship between Epigenetic Age and Myocardial Infarction/Acute Coronary Syndrome in a Population-Based Nested Case-Control Study. J Pers Med 2022; 12:jpm12010110. [PMID: 35055425 PMCID: PMC8781885 DOI: 10.3390/jpm12010110] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2021] [Revised: 12/24/2021] [Accepted: 01/10/2022] [Indexed: 02/05/2023] Open
Abstract
We investigated the relationship between ‘epigenetic age’ (EA) derived from DNA methylation (DNAm) and myocardial infarction (MI)/acute coronary syndrome (ACS). A random population sample was examined in 2003/2005 (n = 9360, 45–69, the HAPIEE project) and followed up for 15 years. From this cohort, incident MI/ACS (cases, n = 129) and age- and sex-stratified controls (n = 177) were selected for a nested case-control study. Baseline EA (Horvath’s, Hannum’s, PhenoAge, Skin and Blood) and the differences between EA and chronological age (CA) were calculated (ΔAHr, ΔAHn, ΔAPh, ΔASB). EAs by Horvath’s, Hannum’s and Skin and Blood were close to CA (median absolute difference, MAD, of 1.08, –1.91 and –2.03 years); PhenoAge had MAD of −9.29 years vs. CA. The adjusted odds ratios (ORs) of MI/ACS per 1–year increments of ΔAHr, ΔAHn, ΔASB and ΔAPh were 1.01 (95% CI 0.95–1.07), 1.01 (95% CI 0.95–1.08), 1.02 (95% CI 0.97–1.06) and 1.01 (0.93–1.09), respectively. When classified into tertiles, only the highest tertile of ΔAPh showed a suggestion of increased risk of MI/ACS with OR 2.09 (1.11–3.94) independent of age and 1.84 (0.99–3.52) in the age- and sex-adjusted model. Metabolic modulation may be the likely mechanism of this association. In conclusion, this case-control study nested in a prospective population-based cohort did not find strong associations between accelerated epigenetic age markers and risk of MI/ACS. Larger cohort studies are needed to re-examine this important research question.
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Affiliation(s)
- Sofia Malyutina
- Research Institute of Internal and Preventive Medicine-Branch of Institute of Cytology and Genetics SB RAS, 630089 Novosibirsk, Russia; (V.M.); (A.R.); (V.G.)
- Correspondence: ; Tel.: +7-913-929-33-63
| | - Olga Chervova
- UCL Cancer Institute, University College London, London WC1E 6BT, UK; (O.C.); (S.B.)
| | - Taavi Tillmann
- Institute for Global Health, University College London, London WC1E 6BT, UK;
| | - Vladimir Maximov
- Research Institute of Internal and Preventive Medicine-Branch of Institute of Cytology and Genetics SB RAS, 630089 Novosibirsk, Russia; (V.M.); (A.R.); (V.G.)
| | - Andrew Ryabikov
- Research Institute of Internal and Preventive Medicine-Branch of Institute of Cytology and Genetics SB RAS, 630089 Novosibirsk, Russia; (V.M.); (A.R.); (V.G.)
| | - Valery Gafarov
- Research Institute of Internal and Preventive Medicine-Branch of Institute of Cytology and Genetics SB RAS, 630089 Novosibirsk, Russia; (V.M.); (A.R.); (V.G.)
| | - Jaroslav A. Hubacek
- Experimental Medicine Centre, Institute for Clinical and Experimental Medicine, 14021 Prague, Czech Republic;
| | - Hynek Pikhart
- Institute of Epidemiology and Health Care, University College London, London WC1E 6BT, UK; (H.P.); (M.B.)
| | - Stephan Beck
- UCL Cancer Institute, University College London, London WC1E 6BT, UK; (O.C.); (S.B.)
| | - Martin Bobak
- Institute of Epidemiology and Health Care, University College London, London WC1E 6BT, UK; (H.P.); (M.B.)
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205
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Association between Phenotypic Age and Mortality in Patients with Multivessel Coronary Artery Disease. DISEASE MARKERS 2022; 2022:4524032. [PMID: 35069932 PMCID: PMC8776473 DOI: 10.1155/2022/4524032] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/18/2021] [Revised: 12/14/2021] [Accepted: 12/23/2021] [Indexed: 11/18/2022]
Abstract
Background Chronological age (CA) is not a perfect proxy for the true biological aging status of the body. A new biological aging measure, phenotypic age (PhenoAge), has been shown to capture morbidity and mortality risk in the general US population and diverse subpopulations. This study was aimed at evaluating the association between PhenoAge and long-term outcome of patients with multivessel coronary artery disease (CAD). Methods A total of 609 multivessel CAD patients who received PCI attempt and with follow-up were enrolled. The clinical outcome was all-cause mortality on follow-up. PhenoAge was calculated using an equation constructed from CA and 9 clinical biomarkers. Cox proportional hazards regression models and receiver operating characteristic (ROC) curves were performed to evaluate the association between PhenoAge and mortality. Results Overall, patients with more diseases had older PhenoAge and phenotypic age acceleration (PhenoAgeAccel). After a median follow-up of 33.5 months, those with positive PhenoAgeAccel had a significantly higher incidence of all-cause mortality (P = 0.001). After adjusting for CA, Cox proportional hazards models showed that both PhenoAge and PhenoAgeAccel were significantly associated with all-cause mortality. Even after further adjusting for confounding factors, each 10-year increase in PhenoAge was also associated with a 51% increased mortality risk. ROC curves revealed that PhenoAge, with an area under the curve of 0.705, significantly outperformed CA, the individual clinical chemistry measure, and other risk factors. When reexamining the ROC curves using various combinations of variables, we found that PhenoAge provides additional predictive power to all models. Conclusions In conclusion, PhenoAge was strongly associated with all-cause mortality even after adjusting for CA. Our findings suggest that PhenoAge measure may be complementary in predicting mortality risk for patients with multivessel CAD.
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206
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Xiao L, Zan G, Liu C, Xu X, Li L, Chen X, Zhang Z, Yang X. Associations Between Blood Pressure and Accelerated DNA Methylation Aging. J Am Heart Assoc 2022; 11:e022257. [PMID: 35001659 PMCID: PMC9238504 DOI: 10.1161/jaha.121.022257] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
Background Individuals of the same chronological age may exhibit diverse susceptibilities to death. However, few studies have investigated the associations between blood pressure and the accelerated aging. Methods and Results A cross‐sectional study was conducted in 288 adults aged ≥50 years. We assessed the DNA methylation‐based measures of biological age using CpG sites on the Illumina HumanMethylationEPIC BeadChip. Epigenetic age acceleration metrics were derived by regressing residuals (ΔAge) and ratios (aging rate) of DNA methylation age on chronological age. Dose‐response relationships between blood pressure and epigenetic age acceleration were quantified using multiple linear regression and restricted cubic regression models. We found that each 10–mm Hg increase in systolic blood pressure was associated with 0.608 (95% CI, 0.231–0.984) years increase in ΔAge and 0.007 (95% CI, 0.002–0.012) increase in aging rate; meanwhile, for pulse pressure, the increase was 1.12 (95% CI, 0.625–1.61) years for ΔAge and 0.013 (95% CI, 0.007–0.020) for aging rate. Subgroup analysis showed that the significant associations of systolic blood pressure and pulse pressure with epigenetic age acceleration appeared to be limited to women, although interactions between blood pressure and sex were not significant (P values for interaction >0.05). The combination of women and hypertension was associated with a much higher increase in ΔAge (β [95% CI], 4.05 [1.07–7.02]) and aging rate (β [95% CI], 0.047 [0.008–0.087]), compared with male participants without hypertension. Conclusions Our findings suggested that high systolic blood pressure and pulse pressure were associated with the epigenetic age acceleration, providing important clues for relationships between blood pressure and epigenetic aging.
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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
| | - Chaoqun Liu
- 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
| | - Longman Li
- Department of Occupational Health and Environmental Health School of Public Health Guangxi Medical University Nanning Guangxi China
| | - Xing Chen
- Department of Occupational Health and Environmental Health School of Public Health Guangxi Medical University Nanning Guangxi China
| | - Zhiyong Zhang
- Department of Environmental Health and Occupational Medicine; Guangxi Key Laboratory of Environmental Exposomics and Entire Lifecycle Heath Research 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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207
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Horvath S, Haghani A, Peng S, Hales EN, Zoller JA, Raj K, Larison B, Robeck TR, Petersen JL, Bellone RR, Finno CJ. DNA methylation aging and transcriptomic studies in horses. Nat Commun 2022; 13:40. [PMID: 35013267 PMCID: PMC8748428 DOI: 10.1038/s41467-021-27754-y] [Citation(s) in RCA: 23] [Impact Index Per Article: 11.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2021] [Accepted: 12/07/2021] [Indexed: 12/28/2022] Open
Abstract
Cytosine methylation patterns have not yet been thoroughly studied in horses. Here, we profile n = 333 samples from 42 horse tissue types at loci that are highly conserved between mammalian species using a custom array (HorvathMammalMethylChip40). Using the blood and liver tissues from horses, we develop five epigenetic aging clocks: a multi-tissue clock, a blood clock, a liver clock and two dual-species clocks that apply to both horses and humans. In addition, using blood methylation data from three additional equid species (plains zebra, Grevy's zebras and Somali asses), we develop another clock that applies across all equid species. Castration does not significantly impact the epigenetic aging rate of blood or liver samples from horses. Methylation and RNA data from the same tissues define the relationship between methylation and RNA expression across horse tissues. We expect that the multi-tissue atlas will become a valuable resource.
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Affiliation(s)
- Steve Horvath
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA.
- Department of Biostatistics, Fielding School of Public Health, University of California, Los Angeles, Los Angeles, CA, USA.
| | - Amin Haghani
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - Sichong Peng
- Department of Population Health and Reproduction, University of California, Davis School of Veterinary Medicine, Davis, CA, USA
| | - Erin N Hales
- Department of Population Health and Reproduction, University of California, Davis School of Veterinary Medicine, Davis, CA, USA
| | - Joseph A Zoller
- Department of Biostatistics, Fielding School of Public Health, University of California, Los Angeles, Los Angeles, CA, USA
| | - Ken Raj
- Radiation Effects Department, Centre for Radiation, Chemical and Environmental Hazards, Public Health England, Chilton, Didcot, UK
| | - Brenda Larison
- Department of Ecology and Evolutionary Biology, University of California, Los Angeles, CA, USA
- Center for Tropical Research, Institute of the Environment and Sustainability, University of California, Los Angeles, CA, USA
| | - Todd R Robeck
- Zoological Operations, SeaWorld Parks and Entertainment, 7007 SeaWorld Drive, Orlando, FL, USA
| | | | - Rebecca R Bellone
- Department of Population Health and Reproduction, University of California, Davis School of Veterinary Medicine, Davis, CA, USA
- Veterinary Genetics Laboratory, University of California, Davis School of Veterinary Medicine, Davis, CA, USA
| | - Carrie J Finno
- Department of Population Health and Reproduction, University of California, Davis School of Veterinary Medicine, Davis, CA, USA.
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208
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Soda K. Overview of Polyamines as Nutrients for Human Healthy Long Life and Effect of Increased Polyamine Intake on DNA Methylation. Cells 2022; 11:cells11010164. [PMID: 35011727 PMCID: PMC8750749 DOI: 10.3390/cells11010164] [Citation(s) in RCA: 22] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2021] [Revised: 12/24/2021] [Accepted: 12/28/2021] [Indexed: 02/04/2023] Open
Abstract
Polyamines, spermidine and spermine, are synthesized in every living cell and are therefore contained in foods, especially in those that are thought to contribute to health and longevity. They have many physiological activities similar to those of antioxidant and anti-inflammatory substances such as polyphenols. These include antioxidant and anti-inflammatory properties, cell and gene protection, and autophagy activation. We have first reported that increased polyamine intake (spermidine much more so than spermine) over a long period increased blood spermine levels and inhibited aging-associated pathologies and pro-inflammatory status in humans and mice and extended life span of mice. However, it is unlikely that the life-extending effect of polyamines is exerted by the same bioactivity as polyphenols because most studies using polyphenols and antioxidants have failed to demonstrate their life-extending effects. Recent investigations revealed that aging-associated pathologies and lifespan are closely associated with DNA methylation, a regulatory mechanism of gene expression. There is a close relationship between polyamine metabolism and DNA methylation. We have shown that the changes in polyamine metabolism affect the concentrations of substances and enzyme activities involved in DNA methylation. I consider that the increased capability of regulation of DNA methylation by spermine is a key of healthy long life of humans.
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Affiliation(s)
- Kuniyasu Soda
- Department Cardiovascular Institute for Medical Research, Saitama Medical Center, Jichi Medical University, 1-847, Amanuma, Saitama-City 330-0834, Saitama, Japan
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209
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Lee YC, Christensen JJ, Parnell LD, Smith CE, Shao J, McKeown NM, Ordovás JM, Lai CQ. Using Machine Learning to Predict Obesity Based on Genome-Wide and Epigenome-Wide Gene-Gene and Gene-Diet Interactions. Front Genet 2022; 12:783845. [PMID: 35047011 PMCID: PMC8763388 DOI: 10.3389/fgene.2021.783845] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2021] [Accepted: 11/29/2021] [Indexed: 12/15/2022] Open
Abstract
Obesity is associated with many chronic diseases that impair healthy aging and is governed by genetic, epigenetic, and environmental factors and their complex interactions. This study aimed to develop a model that predicts an individual's risk of obesity by better characterizing these complex relations and interactions focusing on dietary factors. For this purpose, we conducted a combined genome-wide and epigenome-wide scan for body mass index (BMI) and up to three-way interactions among 402,793 single nucleotide polymorphisms (SNPs), 415,202 DNA methylation sites (DMSs), and 397 dietary and lifestyle factors using the generalized multifactor dimensionality reduction (GMDR) method. The training set consisted of 1,573 participants in exam 8 of the Framingham Offspring Study (FOS) cohort. After identifying genetic, epigenetic, and dietary factors that passed statistical significance, we applied machine learning (ML) algorithms to predict participants' obesity status in the test set, taken as a subset of independent samples (n = 394) from the same cohort. The quality and accuracy of prediction models were evaluated using the area under the receiver operating characteristic curve (ROC-AUC). GMDR identified 213 SNPs, 530 DMSs, and 49 dietary and lifestyle factors as significant predictors of obesity. Comparing several ML algorithms, we found that the stochastic gradient boosting model provided the best prediction accuracy for obesity with an overall accuracy of 70%, with ROC-AUC of 0.72 in test set samples. Top predictors of the best-fit model were 21 SNPs, 230 DMSs in genes such as CPT1A, ABCG1, SLC7A11, RNF145, and SREBF1, and 26 dietary factors, including processed meat, diet soda, French fries, high-fat dairy, artificial sweeteners, alcohol intake, and specific nutrients and food components, such as calcium and flavonols. In conclusion, we developed an integrated approach with ML to predict obesity using omics and dietary data. This extends our knowledge of the drivers of obesity, which can inform precision nutrition strategies for the prevention and treatment of obesity. Clinical Trial Registration: [www.ClinicalTrials.gov], the Framingham Heart Study (FHS), [NCT00005121].
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Affiliation(s)
- Yu-Chi Lee
- USDA ARS, Nutrition and Genomics Laboratory, JM-USDA Human Nutrition Research Center on Aging at Tufts University, Boston, MA, United States
| | - Jacob J. Christensen
- Department of Nutrition, Norwegian National Advisory Unit on FH, Oslo University Hospital, University of Oslo, Oslo, Norway
| | - Laurence D. Parnell
- USDA ARS, Nutrition and Genomics Laboratory, JM-USDA Human Nutrition Research Center on Aging at Tufts University, Boston, MA, United States
| | - Caren E. Smith
- Nutrition and Genomics Laboratory, JM-USDA Human Nutrition Research Center on Aging at Tufts University, Boston, MA, United States
| | - Jonathan Shao
- Statistical and Bioinformatics Group, Northeast Area, USDA ARS, Beltsville, MD, United States
| | - Nicola M. McKeown
- Nutritional Epidemiology Laboratory, JM-USDA Human Nutrition Research Center on Aging at Tufts University, Boston, MA, United States
- Friedman School of Nutrition Science and Policy, Tufts University, Boston, MA, United States
| | - José M. Ordovás
- Nutrition and Genomics Laboratory, JM-USDA Human Nutrition Research Center on Aging at Tufts University, Boston, MA, United States
- CEI UAM + CSIC, IMDEA Food Institute, Madrid, Spain
- Centro Nacional de Investigaciones Cardiovasculares (CNIC), Madrid, Spain
| | - Chao-Qiang Lai
- USDA ARS, Nutrition and Genomics Laboratory, JM-USDA Human Nutrition Research Center on Aging at Tufts University, Boston, MA, United States
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Beynon RA, Ingle SM, Langdon R, May M, Ness A, Martin RM, Suderman M, Ingarfield K, Marioni RE, McCartney DL, Waterboer T, Pawlita M, Relton C, Smith GD, Richmond RC. Epigenetic biomarkers of ageing are predictive of mortality risk in a longitudinal clinical cohort of individuals diagnosed with oropharyngeal cancer. Clin Epigenetics 2022; 14:1. [PMID: 34980250 PMCID: PMC8725548 DOI: 10.1186/s13148-021-01220-4] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/25/2021] [Accepted: 12/14/2021] [Indexed: 12/14/2022] Open
Abstract
BACKGROUND Epigenetic clocks are biomarkers of ageing derived from DNA methylation levels at a subset of CpG sites. The difference between age predicted by these clocks and chronological age, termed "epigenetic age acceleration", has been shown to predict age-related disease and mortality. We aimed to assess the prognostic value of epigenetic age acceleration and a DNA methylation-based mortality risk score with all-cause mortality in a prospective clinical cohort of individuals with head and neck cancer: Head and Neck 5000. We investigated two markers of intrinsic epigenetic age acceleration (IEAAHorvath and IEAAHannum), one marker of extrinsic epigenetic age acceleration (EEAA), one optimised to predict physiological dysregulation (AgeAccelPheno), one optimised to predict lifespan (AgeAccelGrim) and a DNA methylation-based predictor of mortality (ZhangScore). Cox regression models were first used to estimate adjusted hazard ratios (HR) and 95% confidence intervals (CI) for associations of epigenetic age acceleration with all-cause mortality in people with oropharyngeal cancer (n = 408; 105 deaths). The added prognostic value of epigenetic markers compared to a clinical model including age, sex, TNM stage and HPV status was then evaluated. RESULTS IEAAHannum and AgeAccelGrim were associated with mortality risk after adjustment for clinical and lifestyle factors (HRs per standard deviation [SD] increase in age acceleration = 1.30 [95% CI 1.07, 1.57; p = 0.007] and 1.40 [95% CI 1.06, 1.83; p = 0.016], respectively). There was weak evidence that the addition of AgeAccelGrim to the clinical model improved 3-year mortality prediction (area under the receiver operating characteristic curve: 0.80 vs. 0.77; p value for difference = 0.069). CONCLUSION In the setting of a large, clinical cohort of individuals with head and neck cancer, our study demonstrates the potential of epigenetic markers of ageing to enhance survival prediction in people with oropharyngeal cancer, beyond established prognostic factors. Our findings have potential uses in both clinical and non-clinical contexts: to aid treatment planning and improve patient stratification.
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Affiliation(s)
- Rhona A Beynon
- MRC Integrative Epidemiology Unit, University of Bristol, Oakfield House, Bristol, BS8 2BN, UK.
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK.
| | - Suzanne M Ingle
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Ryan Langdon
- MRC Integrative Epidemiology Unit, University of Bristol, Oakfield House, Bristol, BS8 2BN, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Margaret May
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Andy Ness
- NIHR Bristol Biomedical Research Centre, University Hospitals Bristol and University of Bristol, Bristol, UK
| | - Richard M Martin
- MRC Integrative Epidemiology Unit, University of Bristol, Oakfield House, Bristol, BS8 2BN, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Matthew Suderman
- MRC Integrative Epidemiology Unit, University of Bristol, Oakfield House, Bristol, BS8 2BN, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Kate Ingarfield
- NIHR Bristol Biomedical Research Centre, University Hospitals Bristol and University of Bristol, Bristol, UK
- Centre for Trials Research, Neuadd Meirionnydd, Heath Park Way, Cardiff, UK
- Community Oral Health, University of Glasgow Dental School, Sauchiehall Street, Glasgow, UK
| | - Riccardo E Marioni
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU, UK
| | - Daniel L McCartney
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU, UK
| | - Tim Waterboer
- Infections and Cancer Epidemiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Michael Pawlita
- Infections and Cancer Epidemiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Caroline Relton
- MRC Integrative Epidemiology Unit, University of Bristol, Oakfield House, Bristol, BS8 2BN, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - George Davey Smith
- MRC Integrative Epidemiology Unit, University of Bristol, Oakfield House, Bristol, BS8 2BN, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Rebecca C Richmond
- MRC Integrative Epidemiology Unit, University of Bristol, Oakfield House, Bristol, BS8 2BN, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
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Zhang B, Trapp A, Kerepesi C, Gladyshev VN. Emerging rejuvenation strategies-Reducing the biological age. Aging Cell 2022; 21:e13538. [PMID: 34972247 PMCID: PMC8761015 DOI: 10.1111/acel.13538] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/25/2021] [Revised: 11/02/2021] [Accepted: 11/29/2021] [Indexed: 12/11/2022] Open
Abstract
Several interventions have recently emerged that were proposed to reverse rather than just attenuate aging, but the criteria for what it takes to achieve rejuvenation remain controversial. Distinguishing potential rejuvenation therapies from other longevity interventions, such as those that slow down aging, is challenging, and these anti-aging strategies are often referred to interchangeably. We suggest that the prerequisite for a rejuvenation intervention is a robust, sustained, and systemic reduction in biological age, which can be assessed by biomarkers of aging, such as epigenetic clocks. We discuss known and putative rejuvenation interventions and comparatively analyze them to explore underlying mechanisms.
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Affiliation(s)
- Bohan Zhang
- Division of GeneticsDepartment of MedicineHarvard Medical SchoolBrigham and Women’s HospitalBostonMassachusettsUSA
| | - Alexandre Trapp
- Division of GeneticsDepartment of MedicineHarvard Medical SchoolBrigham and Women’s HospitalBostonMassachusettsUSA
| | - Csaba Kerepesi
- Division of GeneticsDepartment of MedicineHarvard Medical SchoolBrigham and Women’s HospitalBostonMassachusettsUSA
| | - Vadim N. Gladyshev
- Division of GeneticsDepartment of MedicineHarvard Medical SchoolBrigham and Women’s HospitalBostonMassachusettsUSA
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212
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Bøstrand SM, Vaher K, de Nooij L, Harris MA, Cole JH, Cox SR, Marioni RE, McCartney DL, Walker RM, McIntosh AM, Evans KL, Whalley HC, Wootton RE, Clarke TK. Associations between alcohol use and accelerated biological ageing. Addict Biol 2022; 27:e13100. [PMID: 34636470 PMCID: PMC7614236 DOI: 10.1111/adb.13100] [Citation(s) in RCA: 18] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2021] [Revised: 08/31/2021] [Accepted: 09/13/2021] [Indexed: 12/12/2022]
Abstract
Harmful alcohol use is a leading cause of premature death and is associated with age-related disease. Biological ageing is highly variable between individuals and may deviate from chronological ageing, suggesting that biomarkers of biological ageing (derived from DNA methylation or brain structural measures) may be clinically relevant. Here, we investigated the relationships between alcohol phenotypes and both brain and DNA methylation age estimates. First, using data from UK Biobank and Generation Scotland, we tested the association between alcohol consumption (units/week) or hazardous use (Alcohol Use Disorders Identification Test [AUDIT] scores) and accelerated brain and epigenetic ageing in 20,258 and 8051 individuals, respectively. Second, we used Mendelian randomisation (MR) to test for a causal effect of alcohol consumption levels and alcohol use disorder (AUD) on biological ageing. Alcohol use showed a consistent positive association with higher predicted brain age (AUDIT-C: β = 0.053, p = 3.16 × 10-13 ; AUDIT-P: β = 0.052, p = 1.6 × 10-13 ; total AUDIT score: β = 0.062, p = 5.52 × 10-16 ; units/week: β = 0.078, p = 2.20 × 10-16 ), and two DNA methylation-based estimates of ageing, GrimAge (units/week: β = 0.053, p = 1.48 × 10-7 ) and PhenoAge (units/week: β = 0.077, p = 2.18x10-10 ). MR analyses revealed limited evidence for a causal effect of AUD on accelerated brain ageing (β = 0.118, p = 0.044). However, this result should be interpreted cautiously as the significant effect was driven by a single genetic variant. We found no evidence for a causal effect of alcohol consumption levels on accelerated biological ageing. Future studies investigating the mechanisms associating alcohol use with accelerated biological ageing are warranted.
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Affiliation(s)
- Sunniva M.K. Bøstrand
- Division of Psychiatry, Royal Edinburgh Hospital, The University of Edinburgh, Edinburgh, UK
- Centre for Regenerative Medicine, Institute for Regeneration and Repair, The University of Edinburgh, Edinburgh, UK
| | - Kadi Vaher
- Division of Psychiatry, Royal Edinburgh Hospital, The University of Edinburgh, Edinburgh, UK
- MRC Centre for Reproductive Health, The Queen’s Medical Research Institute, The University of Edinburgh, Edinburgh, UK
| | - Laura de Nooij
- Division of Psychiatry, Royal Edinburgh Hospital, The University of Edinburgh, Edinburgh, UK
| | - Matthew A. Harris
- Division of Psychiatry, Royal Edinburgh Hospital, The University of Edinburgh, Edinburgh, UK
| | - James H. Cole
- Centre for Medical Image Computing, Department of Computer Science, University College London, London, UK
- Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, UK
- Dementia Research Centre, Institute of Neurology, University College London, London, UK
| | - Simon R. Cox
- Department of Psychology, The University of Edinburgh, Edinburgh, UK
| | - Riccardo E. Marioni
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, The University of Edinburgh, Edinburgh, UK
| | - Daniel L. McCartney
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, The University of Edinburgh, Edinburgh, UK
| | - Rosie M. Walker
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, The University of Edinburgh, Edinburgh, UK
- Centre for Clinical Brain Sciences, The University of Edinburgh, Edinburgh, UK
| | - Andrew M. McIntosh
- Division of Psychiatry, Royal Edinburgh Hospital, The University of Edinburgh, Edinburgh, UK
| | - Kathryn L. Evans
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, The University of Edinburgh, Edinburgh, UK
| | - Heather C. Whalley
- Division of Psychiatry, Royal Edinburgh Hospital, The University of Edinburgh, Edinburgh, UK
| | - Robyn E. Wootton
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- School of Psychological Science, University of Bristol, Bristol, UK
| | - Toni-Kim Clarke
- Division of Psychiatry, Royal Edinburgh Hospital, The University of Edinburgh, Edinburgh, UK
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213
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Hawe JS, Wilson R, Schmid KT, Zhou L, Lakshmanan LN, Lehne BC, Kühnel B, Scott WR, Wielscher M, Yew YW, Baumbach C, Lee DP, Marouli E, Bernard M, Pfeiffer L, Matías-García PR, Autio MI, Bourgeois S, Herder C, Karhunen V, Meitinger T, Prokisch H, Rathmann W, Roden M, Sebert S, Shin J, Strauch K, Zhang W, Tan WLW, Hauck SM, Merl-Pham J, Grallert H, Barbosa EGV, Illig T, Peters A, Paus T, Pausova Z, Deloukas P, Foo RSY, Jarvelin MR, Kooner JS, Loh M, Heinig M, Gieger C, Waldenberger M, Chambers JC. Genetic variation influencing DNA methylation provides insights into molecular mechanisms regulating genomic function. Nat Genet 2022; 54:18-29. [PMID: 34980917 DOI: 10.1038/s41588-021-00969-x] [Citation(s) in RCA: 54] [Impact Index Per Article: 27.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2019] [Accepted: 10/18/2021] [Indexed: 02/07/2023]
Abstract
We determined the relationships between DNA sequence variation and DNA methylation using blood samples from 3,799 Europeans and 3,195 South Asians. We identify 11,165,559 SNP-CpG associations (methylation quantitative trait loci (meQTL), P < 10-14), including 467,915 meQTL that operate in trans. The meQTL are enriched for functionally relevant characteristics, including shared chromatin state, High-throuhgput chromosome conformation interaction, and association with gene expression, metabolic variation and clinical traits. We use molecular interaction and colocalization analyses to identify multiple nuclear regulatory pathways linking meQTL loci to phenotypic variation, including UBASH3B (body mass index), NFKBIE (rheumatoid arthritis), MGA (blood pressure) and COMMD7 (white cell counts). For rs6511961 , chromatin immunoprecipitation followed by sequencing (ChIP-seq) validates zinc finger protein (ZNF)333 as the likely trans acting effector protein. Finally, we used interaction analyses to identify population- and lineage-specific meQTL, including rs174548 in FADS1, with the strongest effect in CD8+ T cells, thus linking fatty acid metabolism with immune dysregulation and asthma. Our study advances understanding of the potential pathways linking genetic variation to human phenotype.
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Affiliation(s)
- Johann S Hawe
- Institute of Computational Biology, Deutsches Forschungszentrum für Gesundheit und Umwelt, Helmholtz Zentrum München, Neuherberg, Germany
- Department of Informatics, Technical University of Munich, Garching bei München, Germany
| | - Rory Wilson
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- Research Unit Molecular Epidemiology, Helmholtz Zentrum München, German Research Centre for Environmental Health, Neuherberg, Germany
| | - Katharina T Schmid
- Institute of Computational Biology, Deutsches Forschungszentrum für Gesundheit und Umwelt, Helmholtz Zentrum München, Neuherberg, Germany
- Department of Informatics, Technical University of Munich, Garching bei München, Germany
| | - Li Zhou
- Lee Kong Chian School of Medicine, Singapore, Singapore
| | | | - Benjamin C Lehne
- Department of Epidemiology and Biostatistics, Imperial College London, London, UK
| | - Brigitte Kühnel
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- Research Unit Molecular Epidemiology, Helmholtz Zentrum München, German Research Centre for Environmental Health, Neuherberg, Germany
| | - William R Scott
- Department of Epidemiology and Biostatistics, Imperial College London, London, UK
| | - Matthias Wielscher
- Department of Epidemiology and Biostatistics, Imperial College London, London, UK
| | - Yik Weng Yew
- Lee Kong Chian School of Medicine, Singapore, Singapore
| | - Clemens Baumbach
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- Research Unit Molecular Epidemiology, Helmholtz Zentrum München, German Research Centre for Environmental Health, Neuherberg, Germany
| | | | - Eirini Marouli
- Centre for Genomic Health, Queen Mary University of London, London, UK
- William Harvey Research Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UK
| | - Manon Bernard
- Departments of Physiology and Nutritional Sciences, University of Toronto, Toronto, Ontario, Canada
- The Hospital for Sick Children, University of Toronto, Toronto, Ontario, Canada
| | - Liliane Pfeiffer
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- Research Unit Molecular Epidemiology, Helmholtz Zentrum München, German Research Centre for Environmental Health, Neuherberg, Germany
| | - Pamela R Matías-García
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- Research Unit Molecular Epidemiology, Helmholtz Zentrum München, German Research Centre for Environmental Health, Neuherberg, Germany
| | - Matias I Autio
- Genome Institute of Singapore, Singapore, Singapore
- Cardiovascular Research Institute, National University Health Systems, National University of Singapore, Singapore, Singapore
| | - Stephane Bourgeois
- William Harvey Research Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UK
| | - Christian Herder
- German Center for Diabetes Research (DZD), partner site Düsseldorf, Düsseldorf, Germany
- Institute for Clinical Diabetology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University, Düsseldorf, Germany
- Division of Endocrinology and Diabetology, Medical Faculty, Heinrich Heine University, Düsseldorf, Germany
| | - Ville Karhunen
- Department of Epidemiology and Biostatistics, Imperial College London, London, UK
- Center for Life Course Health Research, Faculty of Medicine, University of Oulu, Oulu, Finland
| | - Thomas Meitinger
- Institute of Human Genetics, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- Institute of Human Genetics, Technical University Munich, Munich, Germany
| | - Holger Prokisch
- Institute of Human Genetics, Technical University Munich, Munich, Germany
- Institute of Neurogenomics, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Wolfgang Rathmann
- German Center for Diabetes Research (DZD), partner site Düsseldorf, Düsseldorf, Germany
- Institute for Biometrics and Epidemiology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Michael Roden
- German Center for Diabetes Research (DZD), partner site Düsseldorf, Düsseldorf, Germany
- Institute for Clinical Diabetology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University, Düsseldorf, Germany
- Division of Endocrinology and Diabetology, Medical Faculty, Heinrich Heine University, Düsseldorf, Germany
| | - Sylvain Sebert
- Center for Life Course Health Research, Faculty of Medicine, University of Oulu, Oulu, Finland
- Biocenter Oulu, University of Oulu, Oulu, Finland
- Department for Genomics of Common Diseases, School of Public Health, Imperial College London, London, UK
| | - Jean Shin
- Departments of Physiology and Nutritional Sciences, University of Toronto, Toronto, Ontario, Canada
- The Hospital for Sick Children, University of Toronto, Toronto, Ontario, Canada
| | - Konstantin Strauch
- Chair of Genetic Epidemiology, IBE, Faculty of Medicine, LMU Munich, Munich, Germany
- Institute of Genetic Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- Institute of Medical Biostatistics, Epidemiology and Informatics (IMBEI), University Medical Center, Johannes Gutenberg University, Mainz, Germany
| | - Weihua Zhang
- Department of Epidemiology and Biostatistics, Imperial College London, London, UK
- Department of Cardiology, Ealing Hospital, London North West Healthcare NHS Trust, Southall, UK
| | | | - Stefanie M Hauck
- Research Unit Protein Science, Helmholtz Zentrum München, German Research Centre for Environmental Health, Munich, Germany
| | - Juliane Merl-Pham
- Research Unit Protein Science, Helmholtz Zentrum München, German Research Centre for Environmental Health, Munich, Germany
| | - Harald Grallert
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- Research Unit Molecular Epidemiology, Helmholtz Zentrum München, German Research Centre for Environmental Health, Neuherberg, Germany
- German Center for Diabetes Research (DZD), Munich-Neuherberg, Germany
| | - Eudes G V Barbosa
- Institute of Computational Biology, Deutsches Forschungszentrum für Gesundheit und Umwelt, Helmholtz Zentrum München, Neuherberg, Germany
| | - Thomas Illig
- Hannover Unified Biobank, Hannover Medical School, Hannover, Germany
- Institute for Human Genetics, Hannover Medical School, Hannover, Germany
| | - Annette Peters
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- Research Unit Molecular Epidemiology, Helmholtz Zentrum München, German Research Centre for Environmental Health, Neuherberg, Germany
- German Research Center for Cardiovascular Disease (DZHK), partner site Munich Heart Alliance, Hannover, Germany
| | - Tomas Paus
- Centre Hospitalier Universitaire Sainte-Justine, University of Montreal, Montreal, Canada
| | - Zdenka Pausova
- Departments of Physiology and Nutritional Sciences, University of Toronto, Toronto, Ontario, Canada
- The Hospital for Sick Children, University of Toronto, Toronto, Ontario, Canada
| | - Panos Deloukas
- Centre for Genomic Health, Queen Mary University of London, London, UK
- William Harvey Research Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UK
| | - Roger S Y Foo
- Genome Institute of Singapore, Singapore, Singapore
- Cardiovascular Research Institute, National University Health Systems, National University of Singapore, Singapore, Singapore
| | - Marjo-Riitta Jarvelin
- Department of Epidemiology and Biostatistics, Imperial College London, London, UK
- Center for Life Course Health Research, Faculty of Medicine, University of Oulu, Oulu, Finland
- Biocenter Oulu, University of Oulu, Oulu, Finland
- Unit of Primary Care, Oulu University Hospital, Oulu, Finland
| | - Jaspal S Kooner
- National Heart and Lung Institute, Imperial College London, London, UK.
| | - Marie Loh
- Lee Kong Chian School of Medicine, Singapore, Singapore.
- Department of Epidemiology and Biostatistics, Imperial College London, London, UK.
| | - Matthias Heinig
- Institute of Computational Biology, Deutsches Forschungszentrum für Gesundheit und Umwelt, Helmholtz Zentrum München, Neuherberg, Germany.
- Department of Informatics, Technical University of Munich, Garching bei München, Germany.
| | - Christian Gieger
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany.
- Research Unit Molecular Epidemiology, Helmholtz Zentrum München, German Research Centre for Environmental Health, Neuherberg, Germany.
| | - Melanie Waldenberger
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany.
- Research Unit Molecular Epidemiology, Helmholtz Zentrum München, German Research Centre for Environmental Health, Neuherberg, Germany.
- German Research Center for Cardiovascular Disease (DZHK), partner site Munich Heart Alliance, Hannover, Germany.
| | - John C Chambers
- Lee Kong Chian School of Medicine, Singapore, Singapore.
- Department of Epidemiology and Biostatistics, Imperial College London, London, UK.
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van der Laan L, Cardenas A, Vermeulen R, Fadadu RP, Hubbard AE, Phillips RV, Zhang L, Breeze C, Hu W, Wen C, Huang Y, Tang X, Smith MT, Rothman N, Lan Q. Epigenetic aging biomarkers and occupational exposure to benzene, trichloroethylene and formaldehyde. ENVIRONMENT INTERNATIONAL 2022; 158:106871. [PMID: 34560324 PMCID: PMC9084243 DOI: 10.1016/j.envint.2021.106871] [Citation(s) in RCA: 21] [Impact Index Per Article: 10.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/10/2021] [Revised: 09/02/2021] [Accepted: 09/07/2021] [Indexed: 05/23/2023]
Abstract
Epigenetic aging biomarkers are associated with increased morbidity and mortality. We evaluated if occupational exposure to three established chemical carcinogens is associated with acceleration of epigenetic aging. We studied workers in China occupationally exposed to benzene, trichloroethylene (TCE) or formaldehyde by measuring personal air exposures prior to blood collection. Unexposed controls matched by age and sex were selected from nearby factories. We measured leukocyte DNA methylation (DNAm) in peripheral white blood cells using the Infinium HumanMethylation450 BeadChip to calculate five epigenetic aging clocks and DNAmTL, a biomarker associated with leukocyte telomere length and cell replication. We tested associations between exposure intensity and epigenetic age acceleration (EAA), defined as the residuals of regressing the DNAm aging biomarker on chronological age, matching factors and potential confounders. Median differences in EAA between exposure groups were tested using a permutation test with exact p-values. Epigenetic clocks were strongly correlated with age (Spearman r > 0.8) in all three occupational studies. There was a positive exposure-response relationship between benzene and the Skin-Blood Clock EAA biomarker: median EAA was -0.91 years in controls (n = 44), 0.78 years in workers exposed to <10 ppm (n = 41; mean benzene = 1.35 ppm; p = 0.034 vs. controls), and 2.10 years in workers exposed to ≥10 ppm (n = 9; mean benzene = 27.3 ppm; p = 0.019 vs. controls; ptrend = 0.0021). In the TCE study, control workers had a median Skin-Blood Clock EAA of -0.54 years (n = 71) compared to 1.63 years among workers exposed to <10 ppm of TCE (n = 27; mean TCE = 4.22 ppm; p = 0.035). We observed no evidence of EAA associations with formaldehyde exposure (39 controls, 31 exposed). Occupational benzene and TCE exposure were associated with increased epigenetic age acceleration measured by the Skin-Blood Clock. For TCE, there was some evidence of epigenetic age acceleration for lower exposures compared to controls. Our results suggest that some chemical carcinogens may accelerate epigenetic aging.
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Affiliation(s)
- Lars van der Laan
- Divisions of Environmental Health Sciences and Biostatistics, School of Public Health, University of California, Berkeley, 2121 Berkeley Way #5302, Berkeley, CA 94704, USA
| | - Andres Cardenas
- Divisions of Environmental Health Sciences and Biostatistics, School of Public Health, University of California, Berkeley, 2121 Berkeley Way #5302, Berkeley, CA 94704, USA; Center for Computational Biology, University of California, Berkeley, 108 Stanley Hall, Berkeley, CA 94720, USA.
| | - Roel Vermeulen
- Institute for Risk Assessment Sciences (IRAS), Utrecht University, Yalelaan 2, Utrecht, 3584CM, Netherlands
| | - Raj P Fadadu
- Divisions of Environmental Health Sciences and Biostatistics, School of Public Health, University of California, Berkeley, 2121 Berkeley Way #5302, Berkeley, CA 94704, USA
| | - Alan E Hubbard
- Divisions of Environmental Health Sciences and Biostatistics, School of Public Health, University of California, Berkeley, 2121 Berkeley Way #5302, Berkeley, CA 94704, USA; Center for Computational Biology, University of California, Berkeley, 108 Stanley Hall, Berkeley, CA 94720, USA
| | - Rachael V Phillips
- Divisions of Environmental Health Sciences and Biostatistics, School of Public Health, University of California, Berkeley, 2121 Berkeley Way #5302, Berkeley, CA 94704, USA; Center for Computational Biology, University of California, Berkeley, 108 Stanley Hall, Berkeley, CA 94720, USA
| | - Luoping Zhang
- Divisions of Environmental Health Sciences and Biostatistics, School of Public Health, University of California, Berkeley, 2121 Berkeley Way #5302, Berkeley, CA 94704, USA
| | - Charles Breeze
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, 9609 Medical Center Drive, Rockville, MD 20850, USA
| | - Wei Hu
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, 9609 Medical Center Drive, Rockville, MD 20850, USA
| | - Cuiju Wen
- Guangdong Poison Control Center, Guangzhou, China
| | | | - Xiaojiang Tang
- Guangdong Medical Laboratory Animal Center, Foshan 528248, Guangdong, China
| | - Martyn T Smith
- Divisions of Environmental Health Sciences and Biostatistics, School of Public Health, University of California, Berkeley, 2121 Berkeley Way #5302, Berkeley, CA 94704, USA
| | - Nathaniel Rothman
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, 9609 Medical Center Drive, Rockville, MD 20850, USA
| | - Qing Lan
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, 9609 Medical Center Drive, Rockville, MD 20850, USA
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Ong ML, Lei MK, Klopack E, Berg M, Zhang Y, Philibert R, Beach SS, Simons RL. Unstable Childhood, Adult Adversity, and Smoking Accelerate Biological Aging Among Middle-Age African Americans: Similar Findings for GrimAge and PoAm. J Aging Health 2022; 34:487-498. [PMID: 34525884 PMCID: PMC9851128 DOI: 10.1177/08982643211043668] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/21/2023]
Abstract
Objectives: The recent biological clocks GrimAge and PoAm are robust predictors of morbidity and mortality. Little research, however, has investigated the factors that influence their ticking speed. No study has used multivariate analyses to examine whether childhood adversity, adult hardship, lifestyle practices, or some combination of these factors best explains acceleration of these indices. Methods: Using a sample of 506 middle-age African Americans, the present study investigated the extent to which childhood instability, adult adversity, and lifestyle predict accelerated GrimAge and PoAm. Results: The two clocks were highly correlated and the pattern of findings was very similar for the two measures. Childhood instability, adult financial hardship, and smoking were significant predictors of both clocks. Discussion: The findings support a life course perspective where both the long arm of childhood as well as later life conditions influence speed of aging. Similar results across the two clocks enhance confidence in the findings.
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Affiliation(s)
- Mei Ling Ong
- Center for Family Research, University of Georgia
| | - Man-Kit Lei
- Department of Sociology, University of Georgia
| | - Eric Klopack
- Leonard-Davis School of Gerontology, University of Southern California
| | - Mark Berg
- Department of Sociology, University of Iowa
| | - Yue Zhang
- Department of Sociology, University of Georgia
| | | | | | - Ronald L. Simons
- Department of Sociology, University of Georgia, Athens, GA 30602
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Larison B, Pinho GM, Haghani A, Zoller JA, Li CZ, Finno CJ, Farrell C, Kaelin CB, Barsh GS, Wooding B, Robeck TR, Maddox D, Pellegrini M, Horvath S. Epigenetic models developed for plains zebras predict age in domestic horses and endangered equids. Commun Biol 2021; 4:1412. [PMID: 34921240 PMCID: PMC8683477 DOI: 10.1038/s42003-021-02935-z] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2021] [Accepted: 12/02/2021] [Indexed: 01/09/2023] Open
Abstract
Effective conservation and management of threatened wildlife populations require an accurate assessment of age structure to estimate demographic trends and population viability. Epigenetic aging models are promising developments because they estimate individual age with high accuracy, accurately predict age in related species, and do not require invasive sampling or intensive long-term studies. Using blood and biopsy samples from known age plains zebras (Equus quagga), we model epigenetic aging using two approaches: the epigenetic clock (EC) and the epigenetic pacemaker (EPM). The plains zebra EC has the potential for broad application within the genus Equus given that five of the seven extant wild species of the genus are threatened. We test the EC's ability to predict age in sister taxa, including two endangered species and the more distantly related domestic horse, demonstrating high accuracy in all cases. By comparing chronological and estimated age in plains zebras, we investigate age acceleration as a proxy of health status. An interaction between chronological age and inbreeding is associated with age acceleration estimated by the EPM, suggesting a cumulative effect of inbreeding on biological aging throughout life.
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Affiliation(s)
- Brenda Larison
- Department of Ecology and Evolutionary Biology, University of California, Los Angeles, CA, 90095, USA.
- Center for Tropical Research, Institute of the Environment and Sustainability, University of California, Los Angeles, CA, 90095, USA.
| | - Gabriela M Pinho
- Department of Ecology and Evolutionary Biology, University of California, Los Angeles, CA, 90095, USA
| | - Amin Haghani
- Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, CA, 90095, USA
| | - Joseph A Zoller
- Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, CA, 90095, USA
| | - Caesar Z Li
- Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, CA, 90095, USA
| | - Carrie J Finno
- Department of Population Health and Reproduction, School of Veterinary Medicine, University of California, Davis, CA, 95616, USA
| | - Colin Farrell
- Department of Molecular, Cell and Developmental Biology, University of California, Los Angeles, CA, USA
| | - Christopher B Kaelin
- HudsonAlpha Institute for Biotechnology, Huntsville, AL, 35806, USA
- Department of Genetics, Stanford University, Stanford, CA, 94305, USA
| | - Gregory S Barsh
- HudsonAlpha Institute for Biotechnology, Huntsville, AL, 35806, USA
- Department of Genetics, Stanford University, Stanford, CA, 94305, USA
| | - Bernard Wooding
- Quagga Project, Elandsberg Farms, Hermon, 7308, South Africa
| | - Todd R Robeck
- Zoological Operations, SeaWorld Parks and Entertainment, 7007 SeaWorld Drive, Orlando, FL, USA
| | - Dewey Maddox
- White Oak Conservation, 581705 White Oak Road, Yulee, FL, 32097, USA
| | - Matteo Pellegrini
- Department of Molecular, Cell and Developmental Biology, University of California, Los Angeles, CA, USA
| | - Steve Horvath
- Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, CA, 90095, USA.
- Department of Biostatistics, Fielding School of Public Health, University of California, Los Angeles, Los Angeles, CA, USA.
- Altos Labs, San Diego, CA, USA.
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217
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Coto-Vílchez C, Martínez-Magaña JJ, Mora-Villalobos L, Valerio D, Genis-Mendoza AD, Silverman JM, Nicolini H, Raventós H, Chavarria-Soley G. Genome-wide DNA methylation profiling in nonagenarians suggests an effect of PM20D1 in late onset Alzheimer's disease. CNS Spectr 2021; 28:1-27. [PMID: 34911598 DOI: 10.1017/s109285292100105x] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
AbstractBackgroundThe aim of this study is to identify differentially methylated regions (DMRs) in the genomes of a sample of cognitively healthy individuals and a sample of individuals with LOAD, all of them nonagenarians from Costa Rica.MethodsIn this study, we compared whole blood DNA methylation profiles of 32 individuals: 21 cognitively healthy and 11 with LOAD, using the Infinium MethylationEPIC BeadChip. First, we calculated the epigenetic age of the participants based on Horvath’s epigenetic clock. DMRcate and Bumphunter were used to identify DMRs. After in silico and knowledge-based filtering of the DMRs, we performed a methylation quantitative loci (mQTL) analysis (rs708727 and rs960603).ResultsOn average, the epigenetic age was 73 years in both groups, which represents a difference of over 20 years between epigenetic and chronological age in both affected and unaffected individuals. Methylation analysis revealed 11 DMRs between groups, which contain six genes and two pseudogenes. These genes are involved in cell cycle regulation, embryogenesis, synthesis of ceramides, and migration of interneurons to the cerebral cortex. One of the six genes is PM20D1, for which altered expression has been reported in LOAD. After genotyping previously reported mQTL SNPs for the gene, we found that average methylation in the PM20D1 DMR differs between genotypes for rs708727, but not for rs960603.ConclusionsThis work supports the possible role of PM20D1 in protection against AD, by showing differential methylation in blood of affected and unaffected nonagenarians. Our results also support the influence of genetic factors on PM20D1 methylation levels.
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218
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Mc Auley MT. DNA methylation in genes associated with the evolution of ageing and disease: A critical review. Ageing Res Rev 2021; 72:101488. [PMID: 34662746 DOI: 10.1016/j.arr.2021.101488] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2021] [Revised: 09/30/2021] [Accepted: 10/12/2021] [Indexed: 12/28/2022]
Abstract
Ageing is characterised by a physical decline in biological functioning which results in a progressive risk of mortality with time. As a biological phenomenon, it is underpinned by the dysregulation of a myriad of complex processes. Recently, however, ever-increasing evidence has associated epigenetic mechanisms, such as DNA methylation (DNAm) with age-onset pathologies, including cancer, cardiovascular disease, and Alzheimer's disease. These diseases compromise healthspan. Consequently, there is a medical imperative to understand the link between epigenetic ageing, and healthspan. Evolutionary theory provides a unique way to gain new insights into epigenetic ageing and health. This review will: (1) provide a brief overview of the main evolutionary theories of ageing; (2) discuss recent genetic evidence which has revealed alleles that have pleiotropic effects on fitness at different ages in humans; (3) consider the effects of DNAm on pleiotropic alleles, which are associated with age related disease; (4) discuss how age related DNAm changes resonate with the mutation accumulation, disposable soma and programmed theories of ageing; (5) discuss how DNAm changes associated with caloric restriction intersect with the evolution of ageing; and (6) conclude by discussing how evolutionary theory can be used to inform investigations which quantify age-related DNAm changes which are linked to age onset pathology.
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Affiliation(s)
- Mark Tomás Mc Auley
- Faculty of Science and Engineering, University of Chester, Exton Park, Chester CH1 4BJ, UK.
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219
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Gialluisi A, Santoro A, Tirozzi A, Cerletti C, Donati MB, de Gaetano G, Franceschi C, Iacoviello L. Epidemiological and genetic overlap among biological aging clocks: New challenges in biogerontology. Ageing Res Rev 2021; 72:101502. [PMID: 34700008 DOI: 10.1016/j.arr.2021.101502] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/07/2021] [Revised: 10/18/2021] [Accepted: 10/20/2021] [Indexed: 01/09/2023]
Abstract
Estimators of biological age (BA) - defined as the hypothetical underlying age of an organism - have attracted more and more attention in the last years, especially after the advent of new algorithms based on machine learning and genetic markers. While different aging clocks reportedly predict mortality in the general population, very little is known on their overlap. Here we review the evidence reported so far to support the existence of a partial overlap among different BA acceleration estimators, both from an epidemiological and a genetic perspective. On the epidemiological side, we review evidence supporting shared and independent influence on mortality risk of different aging clocks - including telomere length, brain, blood and epigenetic aging - and provide an overview of how an important exposure like diet may affect the different aging systems. On the genetic side, we apply linkage disequilibrium score regression analyses to support the existence of partly shared genomic overlap among these aging clocks. Through multivariate analysis of published genetic associations with these clocks, we also identified the most associated variants, genes, and pathways, which may affect common mechanisms underlying biological aging of different systems within the body. Based on our analyses, the most implicated pathways were involved in inflammation, lipid and carbohydrate metabolism, suggesting them as potential molecular targets for future anti-aging interventions. Overall, this review is meant as a contribution to the knowledge on the overlap of aging clocks, trying to clarify their shared biological basis and epidemiological implications.
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Affiliation(s)
| | - Aurelia Santoro
- Department of Experimental, Diagnostic and Specialty Medicine, University of Bologna, Bologna, Italy; Alma Mater Research Institute on Global Challenges and Climate Change (Alma Climate), University of Bologna, Bologna 40126, Italy
| | - Alfonsina Tirozzi
- Department of Epidemiology and Prevention, IRCCS NEUROMED, Pozzilli, Italy
| | - Chiara Cerletti
- Department of Epidemiology and Prevention, IRCCS NEUROMED, Pozzilli, Italy
| | | | | | - Claudio Franceschi
- Department of Experimental, Diagnostic and Specialty Medicine, University of Bologna, Bologna, Italy; Laboratory of Systems Medicine of Healthy Aging and Department of Applied Mathematics, Lobachevsky University, Nizhny Novgorod, Russia
| | - Licia Iacoviello
- Department of Epidemiology and Prevention, IRCCS NEUROMED, Pozzilli, Italy; Department of Medicine and Surgery, University of Insubria, Varese, Italy
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220
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Heinsberg LW, Liu D, Shaffer JR, Weeks DE, Conley YP. Characterization of cerebrospinal fluid DNA methylation age during the acute recovery period following aneurysmal subarachnoid hemorrhage. EPIGENETICS COMMUNICATIONS 2021; 1. [PMID: 35083469 PMCID: PMC8787331 DOI: 10.1186/s43682-021-00002-6] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
Abstract
Abstract
Background
Biological aging may occur at different rates than chronological aging due to genetic, social, and environmental factors. DNA methylation (DNAm) age is thought to be a reliable measure of accelerated biological aging which has been linked to an array of poor health outcomes. Given the importance of chronological age in recovery following aneurysmal subarachnoid hemorrhage (aSAH), a type of stroke, DNAm age may also be an important biomarker of outcomes, further improving predictive models. Cerebrospinal fluid (CSF) is a unique tissue representing the local central nervous system environment post-aSAH. However, the validity of CSF DNAm age is unknown, and it is unclear which epigenetic clock is ideal to compute CSF DNAm age, particularly given changes in cell type heterogeneity (CTH) during the acute recovery period. Further, the stability of DNAm age post-aSAH, specifically, has not been examined and may improve our understanding of patient recovery post-aSAH. Therefore, the purpose of this study was to characterize CSF DNAm age over 14 days post-aSAH using four epigenetic clocks.
Results
Genome-wide DNAm data were available for two tissues: (1) CSF for N = 273 participants with serial sampling over 14 days post-aSAH (N = 850 samples) and (2) blood for a subset of n = 72 participants at one time point post-aSAH. DNAm age was calculated using the Horvath, Hannum, Levine, and “Improved Precision” (Zhang) epigenetic clocks. “Age acceleration” was computed as the residuals of DNAm age regressed on chronological age both with and without correcting for CTH. Using scatterplots, Pearson correlations, and group-based trajectory analysis, we examined the relationships between CSF DNAm age and chronological age, the concordance between DNAm ages calculated from CSF versus blood, and the stability (i.e., trajectories) of CSF DNAm age acceleration over time during recovery from aSAH. We observed moderate to strong correlations between CSF DNAm age and chronological age (R = 0.66 [Levine] to R = 0.97 [Zhang]), moderate to strong correlations between DNAm age in CSF versus blood (R = 0.69 [Levine] to R = 0.98 [Zhang]), and stable CSF age acceleration trajectories over 14 days post-aSAH in the Horvath and Zhang clocks (unadjusted for CTH), as well as the Hannum clock (adjusted for CTH).
Conclusions
CSF DNAm age was generally stable post-aSAH. Although correlated, CSF DNAm age differs from blood DNAm age in the Horvath, Hannum, and Levine clocks, but not in the Zhang clock. Taken together, our results suggest that, of the clocks examined here, the Zhang clock is the most robust to CTH and is recommended for use in complex tissues such as CSF.
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221
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Boyle PA, Wang T, Yu L, Wilson RS, Dawe R, Arfanakis K, Schneider JA, Beck T, Rajan KB, Evans D, Bennett DA. The "cognitive clock": A novel indicator of brain health. Alzheimers Dement 2021; 17:1923-1937. [PMID: 34060702 PMCID: PMC9014826 DOI: 10.1002/alz.12351] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2020] [Revised: 03/06/2021] [Accepted: 03/11/2021] [Indexed: 12/11/2022]
Abstract
INTRODUCTION We identified a "cognitive clock," a novel indicator of brain health that provides person-specific estimates of cognitive age, and tested the hypothesis that cognitive age is a better predictor of brain health than chronological age in two independent datasets. METHODS The initial analyses were based on 1057 participants from the Rush Memory and Aging Project and the Religious Orders Study who began without impairment and underwent cognitive assessments up to 24 years. A shape invariant model characterized the latent pattern of cognitive decline, conceptualized here as the "cognitive clock," and yielded person-specific estimates of cognitive age. Survival analyses examined cognitive versus chronological age for predicting Alzheimer's disease dementia, mild cognitive impairment and mortality, and regression analyses examined associations of cognitive versus chronological age with neuropathology and brain atrophy. Finally, we applied the cognitive clock to an independent validation sample of 2592 participants from the Chicago Health and Aging Project, a biracial population-based study, to confirm the predictive utility of cognitive age. RESULTS The "cognitive clock" showed that cognition remained stable until a cognitive age of about 80, then declined moderately until 90, then declined precipitously. In the initial dataset, cognitive age was a better predictor of dementia, mild cognitive impairment and mortality than chronological age, and was more strongly associated with neuropathology and brain atrophy. Application of the cognitive clock to the independent validation sample provided further support for the utility of cognitive age as a strong prognostic indicator of adverse outcomes. DISCUSSION Cognitive age is a robust prognostic indicator of adverse health outcomes and may serve as a useful biomarker in aging research.
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Affiliation(s)
- Patricia A Boyle
- Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, Illinois, USA
- Department of Psychiatry and Behavioral Sciences, Rush University Medical Center, Chicago, Illinois, USA
| | - Tianhao Wang
- Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, Illinois, USA
- Department of Neurological Sciences, Rush University Medical Center, Chicago, Illinois, USA
| | - Lei Yu
- Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, Illinois, USA
- Department of Neurological Sciences, Rush University Medical Center, Chicago, Illinois, USA
| | - Robert S Wilson
- Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, Illinois, USA
- Department of Psychiatry and Behavioral Sciences, Rush University Medical Center, Chicago, Illinois, USA
- Department of Neurological Sciences, Rush University Medical Center, Chicago, Illinois, USA
| | - Robert Dawe
- Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, Illinois, USA
- Department of Diagnostic Radiology and Nuclear Medicine, Chicago, Illinois, USA
| | - Konstantinos Arfanakis
- Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, Illinois, USA
- Department of Diagnostic Radiology and Nuclear Medicine, Chicago, Illinois, USA
- Department of Biomedical Engineering, Illinois Institute of Technology, Chicago, Illinois, USA
| | - Julie A Schneider
- Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, Illinois, USA
- Department of Neurological Sciences, Rush University Medical Center, Chicago, Illinois, USA
- Department of Pathology, Rush University Medical Center, Chicago, Illinois, USA
| | - Todd Beck
- Rush Institute for Healthy Aging, Rush University Medical Center, Chicago, Illinois, USA
| | - Kumar B Rajan
- Rush Institute for Healthy Aging, Rush University Medical Center, Chicago, Illinois, USA
| | - Denis Evans
- Rush Institute for Healthy Aging, Rush University Medical Center, Chicago, Illinois, USA
| | - David A Bennett
- Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, Illinois, USA
- Department of Neurological Sciences, Rush University Medical Center, Chicago, Illinois, USA
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Bima A, Eldakhakhny B, Nuwaylati D, Alnami A, Ajabnoor M, Elsamanoudy A. The Interplay of Vitamin D Deficiency and Cellular Senescence in The Pathogenesis of Obesity-Related Co-Morbidities. Nutrients 2021; 13:nu13114127. [PMID: 34836382 PMCID: PMC8618094 DOI: 10.3390/nu13114127] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2021] [Revised: 11/09/2021] [Accepted: 11/15/2021] [Indexed: 01/10/2023] Open
Abstract
This scoping review aims to clarify the interplay between obesity, vitamin D deficiency, cellular senescence, and obesity-related metabolic consequences, mainly subclinical atherosclerosis, and non-alcoholic fatty liver disease (NAFLD). Obesity is a significant global health problem that involves cellular, environmental, behavioral, and genetic elements. The fundamental cause of obesity throughout all life stages is an energy imbalance, and its consequences are countless and, foremost, very common. Obesity has been comprehensively studied in the literature given its association with low serum vitamin D, with many proposed mechanisms linking the two conditions. Moreover, markers of exaggerated cellular senescence have been proven to accumulate in obese individuals. Subclinical atherosclerosis initiates an early stage that ends in serious cardiac events, and obesity, low vitamin D, and senescent cells largely contribute to its associated chronic low-grade inflammation. Furthermore, NAFLD signifies the hepatic manifestation of metabolic syndrome, and studies have highlighted the important role of obesity, vitamin D deficiency, and cellular senescence in its development. Therefore, we outlined the most important mechanisms tying these conditions to one another.
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Affiliation(s)
- Abdulhadi Bima
- Department of Clinical Biochemistry, Faculty of Medicine, King AbdulAziz University, Jeddah 21465, Saudi Arabia; (A.B.); (B.E.); (A.A.); (M.A.)
| | - Basmah Eldakhakhny
- Department of Clinical Biochemistry, Faculty of Medicine, King AbdulAziz University, Jeddah 21465, Saudi Arabia; (A.B.); (B.E.); (A.A.); (M.A.)
| | - Dina Nuwaylati
- Department of Clinical Biochemistry, Faculty of Medicine, University of Jeddah, Jeddah 21959, Saudi Arabia;
| | - Abrar Alnami
- Department of Clinical Biochemistry, Faculty of Medicine, King AbdulAziz University, Jeddah 21465, Saudi Arabia; (A.B.); (B.E.); (A.A.); (M.A.)
| | - Mohammed Ajabnoor
- Department of Clinical Biochemistry, Faculty of Medicine, King AbdulAziz University, Jeddah 21465, Saudi Arabia; (A.B.); (B.E.); (A.A.); (M.A.)
| | - Ayman Elsamanoudy
- Department of Clinical Biochemistry, Faculty of Medicine, King AbdulAziz University, Jeddah 21465, Saudi Arabia; (A.B.); (B.E.); (A.A.); (M.A.)
- Medical Biochemistry and Molecular Biology, Faculty of Medicine, Mansoura University, Mansoura 35516, Egypt
- Correspondence: ; Tel.: +966-59-506-2375
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223
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Zimmer-Bensch G, Zempel H. DNA Methylation in Genetic and Sporadic Forms of Neurodegeneration: Lessons from Alzheimer's, Related Tauopathies and Genetic Tauopathies. Cells 2021; 10:3064. [PMID: 34831288 PMCID: PMC8624300 DOI: 10.3390/cells10113064] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2021] [Revised: 11/03/2021] [Accepted: 11/04/2021] [Indexed: 12/14/2022] Open
Abstract
Genetic and sporadic forms of tauopathies, the most prevalent of which is Alzheimer's Disease, are a scourge of the aging society, and in the case of genetic forms, can also affect children and young adults. All tauopathies share ectopic expression, mislocalization, or aggregation of the microtubule associated protein TAU, encoded by the MAPT gene. As TAU is a neuronal protein widely expressed in the CNS, the overwhelming majority of tauopathies are neurological disorders. They are characterized by cognitive dysfunction often leading to dementia, and are frequently accompanied by movement abnormalities such as parkinsonism. Tauopathies can lead to severe neurological deficits and premature death. For some tauopathies there is a clear genetic cause and/or an epigenetic contribution. However, for several others the disease etiology is unclear, with few tauopathies being environmentally triggered. Here, we review current knowledge of tauopathies listing known genetic and important sporadic forms of these disease. Further, we discuss how DNA methylation as a major epigenetic mechanism emerges to be involved in the disease pathophysiology of Alzheimer's, and related genetic and non-genetic tauopathies. Finally, we debate the application of epigenetic signatures in peripheral blood samples as diagnostic tools and usages of epigenetic therapy strategies for these diseases.
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Affiliation(s)
- Geraldine Zimmer-Bensch
- Functional Epigenetics in the Animal Model, Institute for Biology II, RWTH Aachen University, 52074 Aachen, Germany
- Research Training Group 2416 MultiSenses-MultiScales, Institute for Biology II, RWTH Aachen University, 52074 Aachen, Germany
| | - Hans Zempel
- Institute of Human Genetics, Faculty of Medicine and University Hospital Cologne, University of Cologne, 50931 Cologne, Germany
- Center for Molecular Medicine Cologne (CMMC), Faculty of Medicine and University Hospital Cologne, University of Cologne, 50931 Cologne, Germany
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224
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Predicting physiological aging rates from a range of quantitative traits using machine learning. Aging (Albany NY) 2021; 13:23471-23516. [PMID: 34718232 PMCID: PMC8580337 DOI: 10.18632/aging.203660] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2021] [Accepted: 09/29/2021] [Indexed: 11/25/2022]
Abstract
It is widely thought that individuals age at different rates. A method that measures “physiological age” or physiological aging rate independent of chronological age could therefore help elucidate mechanisms of aging and inform an individual’s risk of morbidity and mortality. Here we present machine learning frameworks for inferring individual physiological age from a broad range of biochemical and physiological traits including blood phenotypes (e.g., high-density lipoprotein), cardiovascular functions (e.g., pulse wave velocity) and psychological traits (e.g., neuroticism) as main groups in two population cohorts SardiNIA (~6,100 participants) and InCHIANTI (~1,400 participants). The inferred physiological age was highly correlated with chronological age (R2 > 0.8). We further defined an individual’s physiological aging rate (PAR) as the ratio of the predicted physiological age to the chronological age. Notably, PAR was a significant predictor of survival, indicating an effect of aging rate on mortality. Our trait-based PAR was correlated with DNA methylation-based epigenetic aging score (r = 0.6), suggesting that both scores capture a common aging process. PAR was also substantially heritable (h2~0.3), and a subsequent genome-wide association study of PAR identified significant associations with two genetic loci, one of which is implicated in telomerase activity. Our findings support PAR as a proxy for an underlying whole-body aging mechanism. PAR may thus be useful to evaluate the efficacy of treatments that target aging-related deficits and controllable epidemiological factors.
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225
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Lemaître JF, Rey B, Gaillard JM, Régis C, Gilot-Fromont E, Débias F, Duhayer J, Pardonnet S, Pellerin M, Haghani A, Zoller JA, Li CZ, Horvath S. DNA methylation as a tool to explore ageing in wild roe deer populations. Mol Ecol Resour 2021; 22:1002-1015. [PMID: 34665921 PMCID: PMC9297961 DOI: 10.1111/1755-0998.13533] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2021] [Revised: 09/24/2021] [Accepted: 10/11/2021] [Indexed: 12/12/2022]
Abstract
DNA methylation‐based biomarkers of ageing (epigenetic clocks) promise to lead to new insights into evolutionary biology of ageing. Relatively little is known about how the natural environment affects epigenetic ageing effects in wild species. In this study, we took advantage of a unique long‐term (>40 years) longitudinal monitoring of individual roe deer (Capreolus capreolus) living in two wild populations (Chizé and Trois‐Fontaines, France) facing different ecological contexts, to investigate the relationship between chronological age and levels of DNA methylation (DNAm). We generated novel DNA methylation data from n = 94 blood samples, from which we extracted leucocyte DNA, using a custom methylation array (HorvathMammalMethylChip40). We present three DNA methylation‐based estimators of age (DNAm or epigenetic age), which were trained in males, females, and both sexes combined. We investigated how sex differences influenced the relationship between DNAm age and chronological age using sex‐specific epigenetic clocks. Our results highlight that old females may display a lower degree of biological ageing than males. Further, we identify the main sites of epigenetic alteration that have distinct ageing patterns between the two sexes. These findings open the door to promising avenues of research at the crossroads of evolutionary biology and biogerontology.
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Affiliation(s)
- Jean-François Lemaître
- Laboratoire de Biométrie et Biologie Evolutive, UMR5558, Université de Lyon, Université Lyon 1, CNRS, Villeurbanne, France
| | - Benjamin Rey
- Laboratoire de Biométrie et Biologie Evolutive, UMR5558, Université de Lyon, Université Lyon 1, CNRS, Villeurbanne, France
| | - Jean-Michel Gaillard
- Laboratoire de Biométrie et Biologie Evolutive, UMR5558, Université de Lyon, Université Lyon 1, CNRS, Villeurbanne, France
| | - Corinne Régis
- Laboratoire de Biométrie et Biologie Evolutive, UMR5558, Université de Lyon, Université Lyon 1, CNRS, Villeurbanne, France
| | - Emmanuelle Gilot-Fromont
- Laboratoire de Biométrie et Biologie Evolutive, UMR5558, Université de Lyon, Université Lyon 1, CNRS, Villeurbanne, France.,Université de Lyon, VetAgro Sup, Marcy-l'Etoile, France
| | - François Débias
- Laboratoire de Biométrie et Biologie Evolutive, UMR5558, Université de Lyon, Université Lyon 1, CNRS, Villeurbanne, France
| | - Jeanne Duhayer
- Laboratoire de Biométrie et Biologie Evolutive, UMR5558, Université de Lyon, Université Lyon 1, CNRS, Villeurbanne, France
| | - Sylvia Pardonnet
- Laboratoire de Biométrie et Biologie Evolutive, UMR5558, Université de Lyon, Université Lyon 1, CNRS, Villeurbanne, France
| | - Maryline Pellerin
- Direction de la Recherche et de l'Appui Scientifique, Office Français de la Biodiversité, Unité Ongulés Sauvages, Gap, France
| | - Amin Haghani
- Human Genetics, David Geffen School of Medicine, University of California, Los Angeles California, USA
| | - Joseph A Zoller
- Department of Biostatistics, Fielding School of Public Health, University of California, Los Angeles, California, USA
| | - Caesar Z Li
- Department of Biostatistics, Fielding School of Public Health, University of California, Los Angeles, California, USA
| | - Steve Horvath
- Human Genetics, David Geffen School of Medicine, University of California, Los Angeles California, USA.,Department of Biostatistics, Fielding School of Public Health, University of California, Los Angeles, California, USA
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226
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Bertucci EM, Mason MW, Rhodes OE, Parrott BB. Exposure to ionizing radiation disrupts normal epigenetic aging in Japanese medaka. Aging (Albany NY) 2021; 13:22752-22771. [PMID: 34644261 PMCID: PMC8544305 DOI: 10.18632/aging.203624] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2021] [Accepted: 09/03/2021] [Indexed: 02/06/2023]
Abstract
Alterations to the epigenome are a hallmark of biological aging and age-dependent patterning of the DNA methylome ("epigenetic aging") can be modeled to produce epigenetic age predictors. Rates of epigenetic aging vary amongst individuals and correlate to the onset of age-related disease and all-cause mortality. Yet, the origins of epigenetic-to-chronological age discordance are not empirically resolved. Here, we investigate the relationship between aging, DNA methylation, and environmental exposures in Japanese medaka (Oryzias latipes). We find age-associated DNA methylation patterning enriched in genomic regions of low CpG density and that, similar to mammals, most age-related changes occur during early life. We construct an epigenetic clock capable of predicting chronological age with a mean error of 61.1 days (~8.4% of average lifespan). To test the role of environmental factors in driving epigenetic age variation, we exposed medaka to chronic, environmentally relevant doses of ionizing radiation. Because most organisms share an evolutionary history with ionizing radiation, we hypothesized that exposure would reveal fundamental insights into environment-by-epigenetic aging interactions. Radiation exposure disrupted epigenetic aging by accelerating and decelerating normal age-associated patterning and was most pronounced in cytosines that were moderately associated with age. These findings empirically demonstrate the role of DNA methylation in integrating environmental factors into aging trajectories.
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Affiliation(s)
- Emily M. Bertucci
- Odum School of Ecology, University of Georgia, Athens, GA 30602, USA
- Savannah River Ecology Laboratory, University of Georgia, Aiken, SC 29802, USA
| | - Marilyn W. Mason
- Savannah River Ecology Laboratory, University of Georgia, Aiken, SC 29802, USA
| | - Olin E. Rhodes
- Odum School of Ecology, University of Georgia, Athens, GA 30602, USA
- Savannah River Ecology Laboratory, University of Georgia, Aiken, SC 29802, USA
| | - Benjamin B. Parrott
- Odum School of Ecology, University of Georgia, Athens, GA 30602, USA
- Savannah River Ecology Laboratory, University of Georgia, Aiken, SC 29802, USA
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227
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Kresovich JK, Park YMM, Keller JA, Sandler DP, Taylor JA. Healthy eating patterns and epigenetic measures of biological age. Am J Clin Nutr 2021; 115:171-179. [PMID: 34637497 PMCID: PMC8754996 DOI: 10.1093/ajcn/nqab307] [Citation(s) in RCA: 27] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2021] [Accepted: 09/02/2021] [Indexed: 12/16/2022] Open
Abstract
BACKGROUND Healthy eating is associated with lower risks of disease and mortality, but the mechanisms underlying these associations are unclear. Age is strongly related to health outcomes, and biological age can be estimated using the blood methylome. OBJECTIVES To determine whether healthy eating patterns are associated with methylation-based measures of biological age. METHODS Among women in the Sister Study, we calculated scores on 4 recommendation-based healthy eating indexes [Dietary Approaches to Stop Hypertension diet, Healthy Eating Index-2015, Alternative Healthy Eating Index (aHEI-2010), and the Alternative Mediterranean diet] using a validated 110-item Block FFQ completed at enrollment. Genome-wide DNA methylation data were generated using the HumanMethylation450 BeadChip on whole blood samples collected at enrollment from a case-cohort sample of 2694 women and were used to calculate 4 measures of epigenetic age acceleration (Hannum AgeAccel, Horvath AgeAccel, PhenoAgeAccel, and GrimAgeAccel). Linear regression models, adjusted for covariates and cohort sampling weights, were used to examine cross-sectional associations between eating patterns and measures of biological age. RESULTS All 4 healthy eating indexes had inverse associations with epigenetic age acceleration, most notably with PhenoAgeAccel and GrimAgeAccel. Of these, the strongest associations were for aHEI-2010 [per 1-SD increase in diet quality, PhenoAgeAccel β = -0.5 y (95% CI: -0.8 to -0.2 y) and GrimAgeAccel β = -0.4 y (95% CI: -0.6 to -0.3 y)]. Although effect modification was not observed for most lifestyle factors, in analyses stratified by physical activity, the benefits of a healthy diet on epigenetic age acceleration were more pronounced among women who did not meet physical activity guidelines (reporting <2.5 h/wk of exercise). CONCLUSIONS Higher diet quality is inversely associated with methylation-based measures of biological age. Improving diet could have the most benefits in lowering biological age among women with lower levels of physical activity. This trial was registered at clinicaltrials.gov as NCT00047970.
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Affiliation(s)
- Jacob K Kresovich
- Epidemiology Branch, National Institute of Environmental Health Sciences, NIH, Research Triangle Park, NC, USA
| | - Yong-Moon Mark Park
- Epidemiology Branch, National Institute of Environmental Health Sciences, NIH, Research Triangle Park, NC, USA,Department of Epidemiology, Fay W. Boozman College of Public Health, University of Arkansas for Medical Sciences, Little Rock, AR, USA
| | | | - Dale P Sandler
- Epidemiology Branch, National Institute of Environmental Health Sciences, NIH, Research Triangle Park, NC, USA
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228
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Idiopathic early ovarian aging: is there a relation with premenopausal accelerated biological aging in young women with diminished response to ART? J Assist Reprod Genet 2021; 38:3027-3038. [PMID: 34599460 DOI: 10.1007/s10815-021-02326-7] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2021] [Accepted: 09/20/2021] [Indexed: 12/15/2022] Open
Abstract
PURPOSE To evaluate whether young women with idiopathic early ovarian aging, as defined by producing fewer oocytes than expected for a given age over multiple in vitro fertilization (IVF) cycles, have changes in telomere length and epigenetic age indicating accelerated biological aging (i.e., increased risk of morbidity and mortality). METHODS A prospective cohort study was conducted at two Danish public fertility clinics. A total of 55 young women (≤ 37 years) with at least two IVF cycles with ≤ 5 harvested oocytes despite sufficient stimulation with follicle-stimulating hormone (FSH) were included in the early ovarian aging group. As controls, 52 young women (≤ 37 years) with normal ovarian function, defined by at least eight harvested oocytes, were included. Relative telomere length (rTL) and epigenetic age acceleration (AgeAccel) were measured in white blood cells as markers of premenopausal accelerated biological aging. RESULTS rTL was comparable with a mean of 0.46 (± SD 0.12) in the early ovarian aging group and 0.47 (0.14) in the normal ovarian aging group. The AgeAccel of the early ovarian aging group was, insignificantly, 0.5 years older, but this difference disappeared when adjusting for chronological age. Sub-analysis using Anti-Müllerian hormone (AMH) as selection criterion for the two groups did not change the results. CONCLUSION We did not find any indications of accelerated aging in whole blood from young women with idiopathic early ovarian aging. Further investigations in a similar cohort of premenopausal women or other tissues are needed to fully elucidate the potential relationship between premenopausal accelerated biological aging and early ovarian aging.
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229
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Horvath S, Zoller JA, Haghani A, Jasinska AJ, Raj K, Breeze CE, Ernst J, Vaughan KL, Mattison JA. Epigenetic clock and methylation studies in the rhesus macaque. GeroScience 2021; 43:2441-2453. [PMID: 34487267 PMCID: PMC8599607 DOI: 10.1007/s11357-021-00429-8] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2021] [Accepted: 08/01/2021] [Indexed: 11/28/2022] Open
Abstract
Methylation levels at specific CpG positions in the genome have been used to develop accurate estimators of chronological age in humans, mice, and other species. Although epigenetic clocks are generally species-specific, the principles underpinning them appear to be conserved at least across the mammalian class. This is exemplified by the successful development of epigenetic clocks for mice and several other mammalian species. Here, we describe epigenetic clocks for the rhesus macaque (Macaca mulatta), the most widely used nonhuman primate in biological research. Using a custom methylation array (HorvathMammalMethylChip40), we profiled n = 281 tissue samples (blood, skin, adipose, kidney, liver, lung, muscle, and cerebral cortex). From these data, we generated five epigenetic clocks for macaques. These clocks differ with regard to applicability to different tissue types (pan-tissue, blood, skin), species (macaque only or both humans and macaques), and measure of age (chronological age versus relative age). Additionally, the age-based human-macaque clock exhibits a high age correlation (R = 0.89) with the vervet monkey (Chlorocebus sabaeus), another Old World species. Four CpGs within the KLF14 promoter were consistently altered with age in four tissues (adipose, blood, cerebral cortex, skin). Future studies will be needed to evaluate whether these epigenetic clocks predict age-related conditions in the rhesus macaque.
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Affiliation(s)
- Steve Horvath
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA USA
- Department of Biostatistics, Fielding School of Public Health, University of California, Los Angeles, Los Angeles, CA USA
| | - Joseph A. Zoller
- Department of Biostatistics, Fielding School of Public Health, University of California, Los Angeles, Los Angeles, CA USA
| | - Amin Haghani
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA USA
| | - Anna J. Jasinska
- Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine, University of California, Los Angeles, CA Los Angeles, USA
| | - Ken Raj
- Radiation Effects Department, Centre for Radiation, Chemical and Environmental Hazards, Public Health England, Chilton, , Didcot, UK
| | | | - Jason Ernst
- Department of Biological Chemistry, University of California, Los Angeles, Los Angeles, CA 90095 USA
| | - Kelli L. Vaughan
- Translational Gerontology Branch, National Institute on Aging Intramural Research Program, National Institutes of Health, 16701 Elmer School Rd., MD 20842 Dickerson, USA
| | - Julie A. Mattison
- Translational Gerontology Branch, National Institute on Aging Intramural Research Program, National Institutes of Health, 16701 Elmer School Rd., MD 20842 Dickerson, USA
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230
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Horvath S, Zoller JA, Haghani A, Lu AT, Raj K, Jasinska AJ, Mattison JA, Salmon AB. DNA methylation age analysis of rapamycin in common marmosets. GeroScience 2021; 43:2413-2425. [PMID: 34482522 PMCID: PMC8599537 DOI: 10.1007/s11357-021-00438-7] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2021] [Accepted: 08/09/2021] [Indexed: 01/10/2023] Open
Abstract
Human DNA methylation data have previously been used to develop highly accurate biomarkers of aging ("epigenetic clocks"). Subsequent studies demonstrate that similar epigenetic clocks can also be developed for mice and many other mammals. Here, we describe epigenetic clocks for common marmosets (Callithrix jacchus) based on novel DNA methylation data generated from highly conserved mammalian CpGs that were profiled using a custom Infinium array (HorvathMammalMethylChip40). From these, we developed and present here two epigenetic clocks for marmosets that are applicable to whole blood samples. We find that the human-marmoset clock for relative age exhibits moderately high age correlations in two other non-human primate species: vervet monkeys and rhesus macaques. In a separate cohort of marmosets, we tested whether intervention with rapamycin, a drug shown to extend lifespan in mice, would alter the epigenetic age of marmosets, as measured by the marmoset epigenetic clocks. These clocks did not detect significant effects of rapamycin on the epigenetic age of marmoset blood. The common marmoset stands out from other mammals in that it is not possible to build accurate estimators of sex based on DNA methylation data: the accuracy of a random forest predictor of sex (66%) was substantially lower than that observed for other mammals (which is close to 100%). Overall, the epigenetic clocks developed here for the common marmoset are expected to be useful for age estimation of wild-born animals and for anti-aging studies in this species.
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Affiliation(s)
- Steve Horvath
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Gonda Building, 695 Charles Young Drive South, Los Angeles, CA USA
- Department of Biostatistics, Fielding School of Public Health, University of California, Los Angeles, Los Angeles, CA 90095 USA
| | - Joseph A. Zoller
- Department of Biostatistics, Fielding School of Public Health, University of California, Los Angeles, Los Angeles, CA 90095 USA
| | - Amin Haghani
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Gonda Building, 695 Charles Young Drive South, Los Angeles, CA USA
| | - Ake T. Lu
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Gonda Building, 695 Charles Young Drive South, Los Angeles, CA USA
| | - Ken Raj
- Radiation Effects Department, Centre for Radiation, Chemical and Environmental Hazards, Public Health England, Chilton, Didcot, UK
| | - Anna J. Jasinska
- Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA USA
| | - Julie A. Mattison
- Translational Gerontology Branch, National Institute on Aging Intramural Research Program, National Institutes of Health, Dickerson, MD USA
| | - Adam B. Salmon
- The Sam and Ann Barshop Institute for Longevity and Aging Studies, and Department of Molecular Medicine, UT Health San Antonio, and the Geriatric Research Education and Clinical Center, South Texas Veterans Healthcare System, San Antonio, TX USA
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231
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Schachtschneider KM, Schook LB, Meudt JJ, Shanmuganayagam D, Zoller JA, Haghani A, Li CZ, Zhang J, Yang A, Raj K, Horvath S. Epigenetic clock and DNA methylation analysis of porcine models of aging and obesity. GeroScience 2021; 43:2467-2483. [PMID: 34523051 PMCID: PMC8599541 DOI: 10.1007/s11357-021-00439-6] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2021] [Accepted: 08/09/2021] [Indexed: 12/29/2022] Open
Abstract
DNA-methylation profiles have been used successfully to develop highly accurate biomarkers of age, epigenetic clocks, for many species. Using a custom methylation array, we generated DNA methylation data from n = 238 porcine tissues including blood, bladder, frontal cortex, kidney, liver, and lung, from domestic pigs (Sus scrofa domesticus) and minipigs (Wisconsin Miniature Swine™). Samples used in this study originated from Large White X Landrace crossbred pigs, Large White X Minnesota minipig crossbred pigs, and Wisconsin Miniature Swine™. We present 4 epigenetic clocks for pigs that are distinguished by their compatibility with tissue type (pan-tissue and blood clock) and species (pig and human). Two dual-species human-pig pan-tissue clocks accurately measure chronological age and relative age, respectively. We also characterized CpGs that differ between minipigs and domestic pigs. Strikingly, several genes implicated by our epigenetic studies of minipig status overlap with genes (ADCY3, TFAP2B, SKOR1, and GPR61) implicated by genetic studies of body mass index in humans. In addition, CpGs with different levels of methylation between the two pig breeds were identified proximal to genes involved in blood LDL levels and cholesterol synthesis, of particular interest given the minipig's increased susceptibility to cardiovascular disease compared to domestic pigs. Thus, breed-specific differences of domestic and minipigs may potentially help to identify biological mechanisms underlying weight gain and aging-associated diseases. Our porcine clocks are expected to be useful for elucidating the role of epigenetics in aging and obesity, and the testing of anti-aging interventions.
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Affiliation(s)
- Kyle M. Schachtschneider
- Department of Radiology, University of Illinois At Chicago, Chicago, IL USA
- Department of Biochemistry and Molecular Genetics, University of Illinois At Chicago, Chicago, IL USA
- National Center for Supercomputing Applications, University of Illinois At Urbana-Champaign, Urban, IL USA
| | - Lawrence B. Schook
- Department of Radiology, University of Illinois At Chicago, Chicago, IL USA
- Department of Animal Sciences, University of Illinois At Urbana-Champaign, Urbana, IL USA
| | - Jennifer J. Meudt
- Biomedical & Genomic Research Group, Department of Animal and Dairy Sciences, University of Wisconsin – Madison, Madison, WI USA
| | - Dhanansayan Shanmuganayagam
- Biomedical & Genomic Research Group, Department of Animal and Dairy Sciences, University of Wisconsin – Madison, Madison, WI USA
- Department of Surgery, University of Wisconsin School of Medicine and Public Health, Madison, WI USA
| | - Joseph A. Zoller
- Department of Biostatistics, Fielding School of Public Health, University of California, Los Angeles, Los Angeles, CA USA
| | - Amin Haghani
- Department of Biostatistics, Fielding School of Public Health, University of California, Los Angeles, Los Angeles, CA USA
| | - Caesar Z. Li
- Department of Biostatistics, Fielding School of Public Health, University of California, Los Angeles, Los Angeles, CA USA
| | - Joshua Zhang
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Gonda Building, 695 Charles Young Drive South, Los Angeles, CA 90095 USA
| | - Andrew Yang
- Department of Biostatistics, Fielding School of Public Health, University of California, Los Angeles, Los Angeles, CA USA
| | - Ken Raj
- Radiation Effects Department, Centre for Radiation, Chemical and Environmental Hazards, Public Health England, Chilton, Didcot, UK
| | - Steve Horvath
- Department of Biostatistics, Fielding School of Public Health, University of California, Los Angeles, Los Angeles, CA USA
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Gonda Building, 695 Charles Young Drive South, Los Angeles, CA 90095 USA
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Raj K, Szladovits B, Haghani A, Zoller JA, Li CZ, Black P, Maddox D, Robeck TR, Horvath S. Epigenetic clock and methylation studies in cats. GeroScience 2021; 43:2363-2378. [PMID: 34463900 PMCID: PMC8599556 DOI: 10.1007/s11357-021-00445-8] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2021] [Accepted: 08/17/2021] [Indexed: 12/21/2022] Open
Abstract
Human DNA methylation profiles have been used successfully to develop highly accurate biomarkers of aging ("epigenetic clocks"). Although these human epigenetic clocks are not immediately applicable to all species of the animal kingdom, the principles underpinning them appear to be conserved even in animals that are evolutionarily far removed from humans. This is exemplified by recent development of epigenetic clocks for mice and other mammalian species. Here, we describe epigenetic clocks for the domestic cat (Felis catus), based on methylation profiles of CpGs with flanking DNA sequences that are highly conserved between multiple mammalian species. Methylation levels of these CpGs are measured using a custom-designed Infinium array (HorvathMammalMethylChip40). From these, we present 3 epigenetic clocks for cats; of which, one applies only to blood samples from cats, while the remaining two dual-species human-cat clocks apply both to cats and humans. We demonstrate that these domestic cat clocks also lead to high age correlations in cheetahs, tigers, and lions. It is expected that these epigenetic clocks for cats possess the potential to be further developed for monitoring feline health as well as being used for identifying and validating anti-aging interventions.
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Affiliation(s)
- Ken Raj
- Radiation Effects Department, Centre for Radiation, Chemical and Environmental Hazards, Public Health England, Chilton, Didcot, UK
| | - Balazs Szladovits
- Department of Pathobiology and Population Sciences, Royal Veterinary College, Hatfield, UK
| | - Amin Haghani
- Department of Human Genetics, David Geffen School of Medicine, University of California, 695 Charles E. Young Drive South, Los Angeles, CA 90095 USA
| | - Joseph A. Zoller
- Department of Biostatistics, Fielding School of Public Health, University of California, Gonda Building, Los Angeles, CA 90095 USA
| | - Caesar Z. Li
- Department of Biostatistics, Fielding School of Public Health, University of California, Gonda Building, Los Angeles, CA 90095 USA
| | | | | | - Todd R. Robeck
- Corporate Zoological Operations, SeaWorld Parks and Entertainment, Orlando, FL USA
| | - Steve Horvath
- Department of Human Genetics, David Geffen School of Medicine, University of California, 695 Charles E. Young Drive South, Los Angeles, CA 90095 USA
- Department of Biostatistics, Fielding School of Public Health, University of California, Gonda Building, Los Angeles, CA 90095 USA
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Martínez-Magaña JJ, Genis-Mendoza AD, Santana D, Tóvilla-Zárate CA, Lanzagorta N, Nicolini H. [The presence of a psychiatric diagnosis could alter the epigenetic clock in monozygotic twins]. Rev Esp Geriatr Gerontol 2021; 56:361-363. [PMID: 34583863 DOI: 10.1016/j.regg.2021.07.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2021] [Revised: 07/02/2021] [Accepted: 07/05/2021] [Indexed: 10/20/2022]
Abstract
BACKGROUND The acceleration of the epigenetic clock has been associated with a reduction in life expectancy. Individuals diagnosed with a psychiatric disorder have a reduction in life expectancy, and some studies have correlated it with accelerated aging. OBJECTIVE The present study aims to explore whether the presence of any psychiatric disorder could accelerate the epigenetic clock in monozygotic twins. METHODS A total of 15 pairs of monozygotic twins were included. Epigenetic age in peripheral blood cells was estimated by previously published algorithms, using the 450K Beadchip microarray. RESULTS We found that in twins with a diagnosis of a psychiatric disorder, the epigenetic clock could increase compared to their twin without a psychiatric disorder. DISCUSSION AND CONCLUSION The presence of some psychiatric disorder could accelerate the epigenetic clock in homozygous twins, but studies with larger samples are required to clarify this relationship.
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Affiliation(s)
- José Jaime Martínez-Magaña
- Laboratorio de Genómica de Enfermedades Psiquiátricas y Neurodegenerativas, Instituto Nacional de Medicina Genómica, Ciudad de México, México
| | - Alma Delia Genis-Mendoza
- Laboratorio de Genómica de Enfermedades Psiquiátricas y Neurodegenerativas, Instituto Nacional de Medicina Genómica, Ciudad de México, México; Servicios de Atención Psiquiátrica, Hospital Psiquiátrico Infantil Juan N. Navarro, Ciudad de México, México
| | - Daniel Santana
- Clínica de Trastornos del Sueño, Universidad Nacional Autonóma de México, Ciudad de México, México
| | - Carlos Alfonso Tóvilla-Zárate
- División Académica Multidisciplinaria de Comalcalco, Universidad Juárez Autónoma de Tabasco, Comalcalco, Tabasco, México
| | - Nuria Lanzagorta
- División de Investigación, Departamento de Psiquiatría, Grupo de Estudios Médicos y Familiares Carracci, Ciudad de México, México
| | - Humberto Nicolini
- Laboratorio de Genómica de Enfermedades Psiquiátricas y Neurodegenerativas, Instituto Nacional de Medicina Genómica, Ciudad de México, México; División de Investigación, Departamento de Psiquiatría, Grupo de Estudios Médicos y Familiares Carracci, Ciudad de México, México.
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234
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Richmond RC, Sillero-Rejon C, Khouja JN, Prince C, Board A, Sharp G, Suderman M, Relton CL, Munafò M, Gage SH. Investigating the DNA methylation profile of e-cigarette use. Clin Epigenetics 2021; 13:183. [PMID: 34583751 PMCID: PMC8479883 DOI: 10.1186/s13148-021-01174-7] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2021] [Accepted: 09/18/2021] [Indexed: 12/15/2022] Open
Abstract
BACKGROUND Little evidence exists on the health effects of e-cigarette use. DNA methylation may serve as a biomarker for exposure and could be predictive of future health risk. We aimed to investigate the DNA methylation profile of e-cigarette use. RESULTS Among 117 smokers, 117 non-smokers and 116 non-smoking vapers, we evaluated associations between e-cigarette use and epigenome-wide methylation from saliva. DNA methylation at 7 cytosine-phosphate-guanine sites (CpGs) was associated with e-cigarette use at p < 1 × 10-5 and none at p < 5.91 × 10-8. 13 CpGs were associated with smoking at p < 1 × 10-5 and one at p < 5.91 × 10-8. CpGs associated with e-cigarette use were largely distinct from those associated with smoking. There was strong enrichment of known smoking-related CpGs in the smokers but not the vapers. We also tested associations between e-cigarette use and methylation scores known to predict smoking and biological ageing. Methylation scores for smoking and biological ageing were similar between vapers and non-smokers. Higher levels of all smoking scores and a biological ageing score (GrimAge) were observed in smokers. A methylation score for e-cigarette use showed poor prediction internally (AUC 0.55, 0.41-0.69) and externally (AUC 0.57, 0.36-0.74) compared with a smoking score (AUCs 0.80) and was less able to discriminate lung squamous cell carcinoma from adjacent normal tissue (AUC 0.64, 0.52-0.76 versus AUC 0.73, 0.61-0.85). CONCLUSIONS The DNA methylation profile for e-cigarette use is largely distinct from that of cigarette smoking, did not replicate in independent samples, and was unable to discriminate lung cancer from normal tissue. The extent to which methylation related to long-term e-cigarette use translates into chronic effects requires further investigation.
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Affiliation(s)
- Rebecca C Richmond
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK.
- Population Health Sciences, Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS8 2BN, UK.
| | - Carlos Sillero-Rejon
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK
- National Institute for Health Research Applied Research Collaboration West (NIHR ARC West), University Hospitals Bristol NHS Foundation Trust, Bristol, UK
| | - Jasmine N Khouja
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK
- School of Psychological Science, University of Bristol, Bristol, UK
| | - Claire Prince
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS8 2BN, UK
| | - Alexander Board
- Department of Experimental Psychology, Medical Sciences Division, University of Oxford, Oxford, UK
| | - Gemma Sharp
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS8 2BN, UK
| | - Matthew Suderman
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS8 2BN, UK
| | - Caroline L Relton
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS8 2BN, UK
| | - Marcus Munafò
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK
- School of Psychological Science, University of Bristol, Bristol, UK
| | - Suzanne H Gage
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK
- Department of Psychological Sciences, University of Liverpool, Liverpool, UK
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235
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Liu T, Wang J, Xiu Y, Wu Y, Xu D. DNA Methylation Age Drift Is Associated with Poor Outcomes and De-Differentiation in Papillary and Follicular Thyroid Carcinomas. Cancers (Basel) 2021; 13:cancers13194827. [PMID: 34638311 PMCID: PMC8508076 DOI: 10.3390/cancers13194827] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2021] [Revised: 09/19/2021] [Accepted: 09/23/2021] [Indexed: 12/17/2022] Open
Abstract
Simple Summary Normal human tissues contain an epigenetic clock resulting from the age-dependent DNA methylation signature, which is the so-called DNA methylation (DNAm) age and can be used to precisely predict chronological age of healthy individuals. Abnormal DNAm age drift has been implicated in cancer risk and pathogenesis. Here, we observed that highly drifted DNAm age (HDDA) occurred in approximately 1/3 tumors derived from patients with papillary and follicular thyroid carcinomas. HDDA is significantly associated with dedifferentiation of tumor cells and poor patient outcomes. Thus, HDDA may serve as a new prognostic factor for thyroid carcinoma. Abstract Alterations in global DNA methylation play a critical role in both aging and cancer, and DNA methylation (DNAm) age drift has been implicated in cancer risk and pathogenesis. In the present study, we analyzed the TCGA cohort of papillary and follicular thyroid carcinoma (PTC and FTC) for their DNAm age and association with clinic-pathological features. In 54 noncancerous thyroid (NT) samples, DNAm age was highly correlated with patient chronological age (R2 = 0.928, p = 2.6 × 10−31), but drifted to younger than chronological age in most specimens, especially those from patients >50 years old. DNAm age in 502 tumors was also correlated with patient chronological age, but to a much lesser extent (R2 = 0.403). Highly drifted DNAm age (HDDA) was identified in 161 tumors, among which were 101 with DNAm age acceleration while 60 with DNAm age deceleration. Tumors with HDDA were characterized by the robust aberrations in metabolic activities, extracellular microenvironment components and inflammation/immunology responses, and dedifferentiation. Importantly, HDDA in tumors independently predicted shorter disease-free survival of patients. Collectively, NT thyroids from TC patients have younger DNAm age, while HDDA frequently occurs in TCs, and contributes to the TC progression and poor patient outcomes. HDDA may serve as a new prognostic factor for TCs.
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Affiliation(s)
- Tiantian Liu
- Pathology Department, School of Basic Medical Science, Shandong University, Jinan 250012, China; (J.W.); (Y.X.)
- Correspondence:
| | - Jiansheng Wang
- Pathology Department, School of Basic Medical Science, Shandong University, Jinan 250012, China; (J.W.); (Y.X.)
| | - Yuchen Xiu
- Pathology Department, School of Basic Medical Science, Shandong University, Jinan 250012, China; (J.W.); (Y.X.)
| | - Yujiao Wu
- Department of Medicine, Division of Hematology, Bioclinicum and Center for Molecular Medicine (CMM), Karolinska University Hospital Solna, Karolinsk Institutet, SE-171 76 Stockholm, Sweden; (Y.W.); (D.X.)
| | - Dawei Xu
- Department of Medicine, Division of Hematology, Bioclinicum and Center for Molecular Medicine (CMM), Karolinska University Hospital Solna, Karolinsk Institutet, SE-171 76 Stockholm, Sweden; (Y.W.); (D.X.)
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Abstract
ABSTRACT Recent research efforts have provided compelling evidence of genome-wide DNA methylation alterations in pediatrics. It is currently well established that epigenetic clocks, composed of DNA methylation sites, can estimate the gestational and chronological age of cells and tissues from different ages. Also, extensive research is aimed at their correlation with early life exposure and pediatric diseases. This review aimed to systematically summarize the epigenetic clocks in the pediatric population. Publications were collected from PubMed and Web of Science databases up to Apr 2021. Epigenetic clocks, DNA methylation clocks, epigenetic age acceleration or deceleration, pediatric and the pediatric population were used as search criteria. Here, we first review the currently applicative pediatric epigenetic clocks. We then highlight the interpretation for epigenetic age deviations in the pediatric population and their association with external factors, developmental trajectories, and pediatric diseases. Considering the remaining unknown of pediatric clocks, research strategies into them are also discussed. In all, pediatric epigenetic clocks may act as potent tools to understand development, growth and diseases in early life.
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237
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Gharipour M, Mani A, Amini Baghbahadorani M, de Souza Cardoso CK, Jahanfar S, Sarrafzadegan N, de Oliveira C, Silveira EA. How Are Epigenetic Modifications Related to Cardiovascular Disease in Older Adults? Int J Mol Sci 2021; 22:9949. [PMID: 34576113 PMCID: PMC8470616 DOI: 10.3390/ijms22189949] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2021] [Revised: 09/08/2021] [Accepted: 09/09/2021] [Indexed: 12/16/2022] Open
Abstract
The rate of aging has increased globally during recent decades and has led to a rising burden of age-related diseases such as cardiovascular disease (CVD). At the molecular level, epigenetic modifications have been shown recently to alter gene expression during the life course and impair cellular function. In this regard, several CVD risk factors, such as lifestyle and environmental factors, have emerged as key factors in epigenetic modifications within the cardiovascular system. In this study, we attempted to summarized recent evidence related to epigenetic modification, inflammation response, and CVD in older adults as well as the effect of lifestyle modification as a preventive strategy in this age group. Recent evidence showed that lifestyle and environmental factors may affect epigenetic mechanisms, such as DNA methylation, histone acetylation, and miRNA expression. Several substances or nutrients such as selenium, magnesium, curcumin, and caffeine (present in coffee and some teas) could regulate epigenetics. Similarly, physical inactivity, alcohol consumption, air pollutants, psychological stress, and shift working are well-known modifiers of epigenetic patterns. Understanding the exact ways that lifestyle and environmental factors could affect the expression of genes could help to influence the time of incidence and severity of aging-associated diseases. This review highlighted that a healthy lifestyle throughout the life course, such as a healthy diet rich in fibers, vitamins, and essential elements, and specific fatty acids, adequate physical activity and sleep, smoking cessation, and stress control, could be useful tools in preventing epigenetic changes that lead to impaired cardiovascular function.
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Affiliation(s)
- Mojgan Gharipour
- Isfahan Cardiovascular Research Center, Cardiovascular Research Institute, Isfahan University of Medical Sciences, Isfahan 8158388994, Iran;
| | - Arya Mani
- Cardiovascular Research Center, Department of Internal Medicine, and Department of Genetics, Yale University School of Medicine, New Haven, CT 06520, USA;
| | - Mona Amini Baghbahadorani
- Interventional Cardiology Research Center, Cardiovascular Research Institute, Isfahan University of Medical Sciences, Isfahan 8158388994, Iran;
| | - Camila Kellen de Souza Cardoso
- School of Social Sciences and Health, Nutrition Course, Pontifical Catholic University of Goias, Goiânia 74605-010, Brazil;
| | - Shayesteh Jahanfar
- Department of Public Health and Community Medicine, Tufts University School of Medicine, Boston, MI 02111, USA;
| | - Nizal Sarrafzadegan
- Isfahan Cardiovascular Research Center, Cardiovascular Research Institute, Isfahan University of Medical Sciences, Isfahan 8158388994, Iran;
- Faculty of Medicine, School of Population and Public Health, The University of British Columbia, Vancouver, BC V6T 1Z3, Canada
| | - Cesar de Oliveira
- Department of Epidemiology & Public Health, Institute of Epidemiology & Health Care, University College London, London WC1E 6BT, UK;
| | - Erika Aparecida Silveira
- Department of Epidemiology & Public Health, Institute of Epidemiology & Health Care, University College London, London WC1E 6BT, UK;
- Graduate Program in Health Sciences, Faculty of Medicine, Federal University of Goiás, Goiânia 74690-900, Brazil
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238
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Simpson DJ, Olova NN, Chandra T. Cellular reprogramming and epigenetic rejuvenation. Clin Epigenetics 2021; 13:170. [PMID: 34488874 PMCID: PMC8419998 DOI: 10.1186/s13148-021-01158-7] [Citation(s) in RCA: 46] [Impact Index Per Article: 15.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2021] [Accepted: 08/02/2021] [Indexed: 11/10/2022] Open
Abstract
Ageing is an inevitable condition that afflicts all humans. Recent achievements, such as the generation of induced pluripotent stem cells, have delivered preliminary evidence that slowing down and reversing the ageing process might be possible. However, these techniques usually involve complete dedifferentiation, i.e. somatic cell identity is lost as cells are converted to a pluripotent state. Separating the rejuvenative properties of reprogramming from dedifferentiation is a promising prospect, termed epigenetic rejuvenation. Reprogramming-induced rejuvenation strategies currently involve using Yamanaka factors (typically transiently expressed to prevent full dedifferentiation) and are promising candidates to safely reduce biological age. Here, we review the development and potential of reprogramming-induced rejuvenation as an anti-ageing strategy.
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Affiliation(s)
- Daniel J Simpson
- MRC Human Genetics Unit, MRC Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, EH4 2XU, UK.
| | - Nelly N Olova
- MRC Human Genetics Unit, MRC Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, EH4 2XU, UK.
| | - Tamir Chandra
- MRC Human Genetics Unit, MRC Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, EH4 2XU, UK.
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239
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Simpson DJ, Chandra T. Epigenetic age prediction. Aging Cell 2021; 20:e13452. [PMID: 34415665 PMCID: PMC8441394 DOI: 10.1111/acel.13452] [Citation(s) in RCA: 59] [Impact Index Per Article: 19.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2021] [Revised: 07/21/2021] [Accepted: 07/27/2021] [Indexed: 12/14/2022] Open
Abstract
Advanced age is the main common risk factor for cancer, cardiovascular disease and neurodegeneration. Yet, more is known about the molecular basis of any of these groups of diseases than the changes that accompany ageing itself. Progress in molecular ageing research was slow because the tools predicting whether someone aged slowly or fast (biological age) were unreliable. To understand ageing as a risk factor for disease and to develop interventions, the molecular ageing field needed a quantitative measure; a clock for biological age. Over the past decade, a number of age predictors utilising DNA methylation have been developed, referred to as epigenetic clocks. While they appear to estimate biological age, it remains unclear whether the methylation changes used to train the clocks are a reflection of other underlying cellular or molecular processes, or whether methylation itself is involved in the ageing process. The precise aspects of ageing that the epigenetic clocks capture remain hidden and seem to vary between predictors. Nonetheless, the use of epigenetic clocks has opened the door towards studying biological ageing quantitatively, and new clocks and applications, such as forensics, appear frequently. In this review, we will discuss the range of epigenetic clocks available, their strengths and weaknesses, and their applicability to various scientific queries.
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Affiliation(s)
- Daniel J. Simpson
- MRC Human Genetics UnitMRC Institute of Genetics and Molecular MedicineUniversity of EdinburghEdinburghUK
| | - Tamir Chandra
- MRC Human Genetics UnitMRC Institute of Genetics and Molecular MedicineUniversity of EdinburghEdinburghUK
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240
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Yang R, Wu GWY, Verhoeven JE, Gautam A, Reus VI, Kang JI, Flory JD, Abu-Amara D, Hood L, Doyle FJ, Yehuda R, Marmar CR, Jett M, Hammamieh R, Mellon SH, Wolkowitz OM. A DNA methylation clock associated with age-related illnesses and mortality is accelerated in men with combat PTSD. Mol Psychiatry 2021; 26:4999-5009. [PMID: 32382136 DOI: 10.1038/s41380-020-0755-z] [Citation(s) in RCA: 40] [Impact Index Per Article: 13.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/29/2020] [Revised: 03/20/2020] [Accepted: 04/23/2020] [Indexed: 02/02/2023]
Abstract
DNA methylation patterns at specific cytosine-phosphate-guanine (CpG) sites predictably change with age and can be used to derive "epigenetic age", an indicator of biological age, as opposed to merely chronological age. A relatively new estimator, called "DNAm GrimAge", is notable for its superior predictive ability in older populations regarding numerous age-related metrics like time-to-death, time-to-coronary heart disease, and time-to-cancer. PTSD is associated with premature mortality and frequently has comorbid physical illnesses suggestive of accelerated biological aging. This is the first study to assess DNAm GrimAge in PTSD patients. We investigated the acceleration of GrimAge relative to chronological age, denoted "AgeAccelGrim" in combat trauma-exposed male veterans with and without PTSD using cross-sectional and longitudinal data from two independent well-characterized veteran cohorts. In both cohorts, AgeAccelGrim was significantly higher in the PTSD group compared to the control group (N = 162, 1.26 vs -0.57, p = 0.001 and N = 53, 0.93 vs -1.60 Years, p = 0.008), suggesting accelerated biological aging in both cohorts with PTSD. In 3-year follow-up study of individuals initially diagnosed with PTSD (N = 26), changes in PTSD symptom severity were correlated with AgeAccelGrim changes (r = 0.39, p = 0.049). In addition, the loss of CD28 cell surface markers on CD8 + T cells, an indicator of T-cell senescence/exhaustion that is associated with biological aging, was positively correlated with AgeAccelGrim, suggesting an immunological contribution to the accelerated biological aging. Overall, our findings delineate cellular correlates of biological aging in combat-related PTSD, which may help explain the increased medical morbidity and mortality seen in this disease.
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Affiliation(s)
- Ruoting Yang
- Medical Readiness Systems Biology, Walter Reed Army Institute of Research, Silver Spring, MD, USA.
| | - Gwyneth W Y Wu
- Weill Institute for Neurosciences and Department of Psychiatry, University of California San Francisco (UCSF) School of Medicine, San Francisco, CA, USA
| | - Josine E Verhoeven
- Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Psychiatry, Amsterdam Public Health Research Institute, Amsterdam, The Netherlands
| | - Aarti Gautam
- Medical Readiness Systems Biology, Walter Reed Army Institute of Research, Silver Spring, MD, USA
| | - Victor I Reus
- Weill Institute for Neurosciences and Department of Psychiatry, University of California San Francisco (UCSF) School of Medicine, San Francisco, CA, USA
| | - Jee In Kang
- Institute of Behavioral Science in Medicine & Department of Psychiatry, Yonsei University College of Medicine, Seoul, South Korea
| | - Janine D Flory
- James J Peters VA Medical Center, Bronx, NY, USA.,Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Duna Abu-Amara
- Department of Psychiatry, New York University School of Medicine, New York, NY, USA
| | | | - Leroy Hood
- Institute for Systems Biology, Seattle, WA, USA
| | - Francis J Doyle
- John A. Paulson School of Engineering & Applied Sciences, Harvard University, Cambridge, MA, USA
| | - Rachel Yehuda
- James J Peters VA Medical Center, Bronx, NY, USA.,Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Charles R Marmar
- Department of Psychiatry, New York University School of Medicine, New York, NY, USA
| | - Marti Jett
- Medical Readiness Systems Biology, Walter Reed Army Institute of Research, Silver Spring, MD, USA
| | - Rasha Hammamieh
- Medical Readiness Systems Biology, Walter Reed Army Institute of Research, Silver Spring, MD, USA
| | - Synthia H Mellon
- Department of OB-GYN and Reproductive Sciences, UCSF School of Medicine, San Francisco, CA, USA
| | - Owen M Wolkowitz
- Weill Institute for Neurosciences and Department of Psychiatry, University of California San Francisco (UCSF) School of Medicine, San Francisco, CA, USA
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241
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Simons RL, Lei MK, Klopach E, Berg M, Zhang Y, Beach SSR. Re(Setting) Epigenetic Clocks: An Important Avenue Whereby Social Conditions Become Biologically Embedded across the Life Course. JOURNAL OF HEALTH AND SOCIAL BEHAVIOR 2021; 62:436-453. [PMID: 34528488 DOI: 10.1177/00221465211009309] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/13/2023]
Abstract
Research on biological embedding of the social environment has been expedited by increased availability of biomarkers. Recently, this arsenal of measures has been expanded to include epigenetic clocks that indicate in years the extent to which an individual is older or younger than their chronological age. These measures of biological aging, especially GrimAge, are robust predictors of both illness and time to death. Importantly for sociologists, several studies have linked social conditions to these indices of aging. The present study extends this research using longitudinal data from a sample of 223 black women participating in the Family and Community Health Study. We find that changes in income and living arrangements over an 11-year period predict changes in speed of biological aging. These results provide further support for the idea that epigenetic aging is a mechanism whereby social conditions become biologically embedded. The utility of epigenetic clocks for sociological studies of health are discussed.
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Affiliation(s)
| | | | | | - Mark Berg
- University of Iowa, Iowa City, IA, USA
| | - Yue Zhang
- University of Georgia, Athens, GA, USA
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242
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Gialluisi A, Di Castelnuovo A, Costanzo S, Bonaccio M, Persichillo M, Magnacca S, De Curtis A, Cerletti C, Donati MB, de Gaetano G, Capobianco E, Iacoviello L. Exploring domains, clinical implications and environmental associations of a deep learning marker of biological ageing. Eur J Epidemiol 2021; 37:35-48. [PMID: 34453631 DOI: 10.1007/s10654-021-00797-7] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2020] [Accepted: 08/07/2021] [Indexed: 01/05/2023]
Abstract
Deep Neural Networks (DNN) have been recently developed for the estimation of Biological Age (BA), the hypothetical underlying age of an organism, which can differ from its chronological age (CA). Although promising, these population-specific algorithms warrant further characterization and validation, since their biological, clinical and environmental correlates remain largely unexplored. Here, an accurate DNN was trained to compute BA based on 36 circulating biomarkers in an Italian population (N = 23,858; age ≥ 35 years; 51.7% women). This estimate was heavily influenced by markers of metabolic, heart, kidney and liver function. The resulting Δage (BA-CA) significantly predicted mortality and hospitalization risk for all and specific causes. Slowed biological aging (Δage < 0) was associated with higher physical and mental wellbeing, healthy lifestyles (e.g. adherence to Mediterranean diet) and higher socioeconomic status (educational attainment, household income and occupational status), while accelerated aging (Δage > 0) was associated with smoking and obesity. Together, lifestyles and socioeconomic variables explained ~48% of the total variance in Δage, potentially suggesting the existence of a genetic basis. These findings validate blood-based biological aging as a marker of public health in adult Italians and provide a robust body of knowledge on its biological architecture, clinical implications and potential environmental influences.
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Affiliation(s)
- Alessandro Gialluisi
- Department of Epidemiology and Prevention, IRCCS Neuromed, Via dell´Elettronica, 86077, Pozzilli, Italy.
| | | | - Simona Costanzo
- Department of Epidemiology and Prevention, IRCCS Neuromed, Via dell´Elettronica, 86077, Pozzilli, Italy
| | - Marialaura Bonaccio
- Department of Epidemiology and Prevention, IRCCS Neuromed, Via dell´Elettronica, 86077, Pozzilli, Italy
| | - Mariarosaria Persichillo
- Department of Epidemiology and Prevention, IRCCS Neuromed, Via dell´Elettronica, 86077, Pozzilli, Italy
| | | | - Amalia De Curtis
- Department of Epidemiology and Prevention, IRCCS Neuromed, Via dell´Elettronica, 86077, Pozzilli, Italy
| | - Chiara Cerletti
- Department of Epidemiology and Prevention, IRCCS Neuromed, Via dell´Elettronica, 86077, Pozzilli, Italy
| | - Maria Benedetta Donati
- Department of Epidemiology and Prevention, IRCCS Neuromed, Via dell´Elettronica, 86077, Pozzilli, Italy
| | - Giovanni de Gaetano
- Department of Epidemiology and Prevention, IRCCS Neuromed, Via dell´Elettronica, 86077, Pozzilli, Italy
| | - Enrico Capobianco
- Institute of Data Science and Computing, University of Miami, Miami, FL, USA
| | - Licia Iacoviello
- Department of Epidemiology and Prevention, IRCCS Neuromed, Via dell´Elettronica, 86077, Pozzilli, Italy
- Department of Medicine and Surgery, Research Center in Epidemiology and Preventive Medicine (EPIMED), University of Insubria, Varese, Italy
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243
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Franzen J, Nüchtern S, Tharmapalan V, Vieri M, Nikolić M, Han Y, Balfanz P, Marx N, Dreher M, Brümmendorf TH, Dahl E, Beier F, Wagner W. Epigenetic Clocks Are Not Accelerated in COVID-19 Patients. Int J Mol Sci 2021; 22:ijms22179306. [PMID: 34502212 PMCID: PMC8431654 DOI: 10.3390/ijms22179306] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2021] [Revised: 08/23/2021] [Accepted: 08/25/2021] [Indexed: 02/06/2023] Open
Abstract
Age is a major risk factor for severe outcome of the 2019 coronavirus disease (COVID-19). In this study, we followed the hypothesis that particularly patients with accelerated epigenetic age are affected by severe outcomes of COVID-19. We investigated various DNA methylation datasets of blood samples with epigenetic aging signatures and performed targeted bisulfite amplicon sequencing. Overall, epigenetic clocks closely correlated with the chronological age of patients, either with or without acute respiratory distress syndrome. Furthermore, lymphocytes did not reveal significantly accelerated telomere attrition. Thus, these biomarkers cannot reliably predict higher risk for severe COVID-19 infection in elderly patients.
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Affiliation(s)
- Julia Franzen
- Helmholtz-Institute for Biomedical Engineering, Stem Cell Biology and Cellular Engineering, Medical Faculty of RWTH Aachen University, 52074 Aachen, Germany; (J.F.); (S.N.); (V.T.); (M.N.); (Y.H.)
| | - Selina Nüchtern
- Helmholtz-Institute for Biomedical Engineering, Stem Cell Biology and Cellular Engineering, Medical Faculty of RWTH Aachen University, 52074 Aachen, Germany; (J.F.); (S.N.); (V.T.); (M.N.); (Y.H.)
| | - Vithurithra Tharmapalan
- Helmholtz-Institute for Biomedical Engineering, Stem Cell Biology and Cellular Engineering, Medical Faculty of RWTH Aachen University, 52074 Aachen, Germany; (J.F.); (S.N.); (V.T.); (M.N.); (Y.H.)
| | - Margherita Vieri
- Department of Hematology, Oncology, Hemostaseology and Stem Cell Transplantation, University Hospital Aachen, RWTH Aachen University, 52074 Aachen, Germany; (M.V.); (T.H.B.); (F.B.)
- Center for Integrated Oncology Aachen Bonn Cologne Düsseldorf (CIO ABCD), 52074 Aachen, Germany
| | - Miloš Nikolić
- Helmholtz-Institute for Biomedical Engineering, Stem Cell Biology and Cellular Engineering, Medical Faculty of RWTH Aachen University, 52074 Aachen, Germany; (J.F.); (S.N.); (V.T.); (M.N.); (Y.H.)
| | - Yang Han
- Helmholtz-Institute for Biomedical Engineering, Stem Cell Biology and Cellular Engineering, Medical Faculty of RWTH Aachen University, 52074 Aachen, Germany; (J.F.); (S.N.); (V.T.); (M.N.); (Y.H.)
| | - Paul Balfanz
- Department of Cardiology, Angiology and Intensive Care Medicine (Department of Internal Medicine I), University Hospital Aachen, RWTH Aachen University, 52074 Aachen, Germany; (P.B.); (N.M.)
| | - Nikolaus Marx
- Department of Cardiology, Angiology and Intensive Care Medicine (Department of Internal Medicine I), University Hospital Aachen, RWTH Aachen University, 52074 Aachen, Germany; (P.B.); (N.M.)
| | - Michael Dreher
- Department of Pneumology and Intensive Care Medicine, University Hospital Aachen, RWTH Aachen University, 52074 Aachen, Germany;
| | - Tim H. Brümmendorf
- Department of Hematology, Oncology, Hemostaseology and Stem Cell Transplantation, University Hospital Aachen, RWTH Aachen University, 52074 Aachen, Germany; (M.V.); (T.H.B.); (F.B.)
- Center for Integrated Oncology Aachen Bonn Cologne Düsseldorf (CIO ABCD), 52074 Aachen, Germany
| | - Edgar Dahl
- Institute of Pathology, University Hospital Aachen, RWTH Aachen University, 52074 Aachen, Germany;
- RWTH Centralized Biomaterial Bank (RWTH cBMB), Medical Faculty of RWTH Aachen University, 52074 Aachen, Germany
| | - Fabian Beier
- Department of Hematology, Oncology, Hemostaseology and Stem Cell Transplantation, University Hospital Aachen, RWTH Aachen University, 52074 Aachen, Germany; (M.V.); (T.H.B.); (F.B.)
- Center for Integrated Oncology Aachen Bonn Cologne Düsseldorf (CIO ABCD), 52074 Aachen, Germany
| | - Wolfgang Wagner
- Helmholtz-Institute for Biomedical Engineering, Stem Cell Biology and Cellular Engineering, Medical Faculty of RWTH Aachen University, 52074 Aachen, Germany; (J.F.); (S.N.); (V.T.); (M.N.); (Y.H.)
- Center for Integrated Oncology Aachen Bonn Cologne Düsseldorf (CIO ABCD), 52074 Aachen, Germany
- Correspondence:
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244
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Piniewska-Róg D, Heidegger A, Pośpiech E, Xavier C, Pisarek A, Jarosz A, Woźniak A, Wojtas M, Phillips C, Kayser M, Parson W, Branicki W. Impact of excessive alcohol abuse on age prediction using the VISAGE enhanced tool for epigenetic age estimation in blood. Int J Legal Med 2021; 135:2209-2219. [PMID: 34405265 PMCID: PMC8523459 DOI: 10.1007/s00414-021-02665-1] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2021] [Accepted: 07/06/2021] [Indexed: 12/13/2022]
Abstract
DNA methylation-based clocks provide the most accurate age estimates with practical implications for clinical and forensic genetics. However, the effects of external factors that may influence the estimates are poorly studied. Here, we evaluated the effect of alcohol consumption on epigenetic age prediction in a cohort of extreme alcohol abusers. Blood samples from deceased alcohol abusers and age- and sex-matched controls were analyzed using the VISAGE enhanced tool for age prediction from somatic tissues that enables examination of 44 CpGs within eight age markers. Significantly altered DNA methylation was recorded for alcohol abusers in MIR29B2CHG. This resulted in a mean predicted age of 1.4 years higher compared to the controls and this trend increased in older individuals. The association of alcohol abuse with epigenetic age acceleration, as determined by the prediction analysis performed based on MIR29B2CHG, was small but significant (β = 0.190; P-value = 0.007). However, the observed alteration in DNA methylation of MIR29B2CHG had a non-significant effect on age estimation with the VISAGE age prediction model. The mean absolute error in the alcohol-abusing cohort was 3.1 years, compared to 3.3 years in the control group. At the same time, upregulation of MIR29B2CHG expression may have a biological function, which merits further studies.
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Affiliation(s)
- Danuta Piniewska-Róg
- Jagiellonian University Medical College, Faculty of Medicine, Department of Forensic Medicine, Grzegórzecka 16, 31-531, Krakow, Poland
| | - Antonia Heidegger
- Institute of Legal Medicine, Medical University of Innsbruck, Muellerstrasse 44, 6020, Innsbruck, Austria
| | - Ewelina Pośpiech
- Malopolska Centre of Biotechnology, Jagiellonian University, Gronostajowa 7A, 30-348, Krakow, Poland
| | - Catarina Xavier
- Institute of Legal Medicine, Medical University of Innsbruck, Muellerstrasse 44, 6020, Innsbruck, Austria
| | - Aleksandra Pisarek
- Malopolska Centre of Biotechnology, Jagiellonian University, Gronostajowa 7A, 30-348, Krakow, Poland
| | - Agata Jarosz
- Malopolska Centre of Biotechnology, Jagiellonian University, Gronostajowa 7A, 30-348, Krakow, Poland
| | - Anna Woźniak
- Central Forensic Laboratory of the Police, Aleje Ujazdowskie 7, 00-583, Warsaw, Poland
| | - Marta Wojtas
- Jagiellonian University Medical College, Faculty of Medicine, Department of Forensic Medicine, Grzegórzecka 16, 31-531, Krakow, Poland
| | - Christopher Phillips
- Forensic Genetics Unit, Institute of Forensic Sciences, University of Santiago de Compostela, R/ San Francisco s/n, 15782, Santiago de Compostela, Spain
| | - Manfred Kayser
- Department of Genetic Identification, Erasmus MC University Medical Center Rotterdam, PO Box 2040, 3000 CA, Rotterdam, The Netherlands
| | - Walther Parson
- Institute of Legal Medicine, Medical University of Innsbruck, Muellerstrasse 44, 6020, Innsbruck, Austria
- Forensic Science Program, The Pennsylvania State University, 13 Thomas Building, University Park, PA, 16802, USA
| | - Wojciech Branicki
- Malopolska Centre of Biotechnology, Jagiellonian University, Gronostajowa 7A, 30-348, Krakow, Poland.
- Central Forensic Laboratory of the Police, Aleje Ujazdowskie 7, 00-583, Warsaw, Poland.
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245
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Spooner RK, Taylor BK, L'Heureux E, Schantell M, Arif Y, May PE, Morsey B, Wang T, Ideker T, Fox HS, Wilson TW. Stress-induced aberrations in sensory processing predict worse cognitive outcomes in healthy aging adults. Aging (Albany NY) 2021; 13:19996-20015. [PMID: 34410999 PMCID: PMC8436901 DOI: 10.18632/aging.203433] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2021] [Accepted: 08/03/2021] [Indexed: 01/06/2023]
Abstract
It is well recognized that not all individuals age equivalently, with functional dependence attributable, at least in part, to stress accumulated across the lifespan. Amongst these dependencies are age-related declines in cognitive function, which may be the result of impaired inhibitory processing (e.g., sensory gating). Herein, we examined the unique roles of life and biological stress on somatosensory gating dynamics in 74 adults (22-72 years old). Participants completed a sensory gating paired-pulse electrical stimulation paradigm of the right median nerve during magnetoencephalography (MEG) and data were subjected to advanced oscillatory and time-domain analysis methods. We observed separable mechanisms by which increasing levels of life and biological stress predicted higher oscillatory gating ratios, indicative of age-related impairments in inhibitory function. Specifically, elevations in life stress significantly modulated the neural response to the first stimulation in the pair, while elevations in biological stress significantly modulated the neural response to the second stimulation in the pair. In contrast, neither elevations in life nor biological stress significantly predicted the gating of time-domain neural activity in the somatosensory cortex. Finally, our study is the first to link stress-induced decline in sensory gating to cognitive dysfunction, suggesting that gating paradigms may hold promise for detecting discrepant functional trajectories in age-related pathologies in the future.
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Affiliation(s)
- Rachel K Spooner
- Institute for Human Neuroscience, Boys Town National Research Hospital, Omaha, NE 68010, USA.,College of Medicine, University of Nebraska Medical Center, Omaha, NE 68198, USA
| | - Brittany K Taylor
- Institute for Human Neuroscience, Boys Town National Research Hospital, Omaha, NE 68010, USA
| | - Emma L'Heureux
- College of Medicine, University of Nebraska Medical Center, Omaha, NE 68198, USA
| | - Mikki Schantell
- Institute for Human Neuroscience, Boys Town National Research Hospital, Omaha, NE 68010, USA.,College of Medicine, University of Nebraska Medical Center, Omaha, NE 68198, USA
| | - Yasra Arif
- Institute for Human Neuroscience, Boys Town National Research Hospital, Omaha, NE 68010, USA.,College of Medicine, University of Nebraska Medical Center, Omaha, NE 68198, USA
| | - Pamela E May
- Department of Neurological Sciences, University of Nebraska Medical Center, Omaha, NE 68198, USA
| | - Brenda Morsey
- Department of Neurological Sciences, University of Nebraska Medical Center, Omaha, NE 68198, USA
| | - Tina Wang
- Department of Medicine, University of California San Diego, La Jolla, CA 92161, USA
| | - Trey Ideker
- Department of Medicine, University of California San Diego, La Jolla, CA 92161, USA
| | - Howard S Fox
- Department of Neurological Sciences, University of Nebraska Medical Center, Omaha, NE 68198, USA
| | - Tony W Wilson
- Institute for Human Neuroscience, Boys Town National Research Hospital, Omaha, NE 68010, USA.,College of Medicine, University of Nebraska Medical Center, Omaha, NE 68198, USA
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246
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Ji L, Jazwinski SM, Kim S. Frailty and Biological Age. Ann Geriatr Med Res 2021; 25:141-149. [PMID: 34399574 PMCID: PMC8497950 DOI: 10.4235/agmr.21.0080] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2021] [Accepted: 08/10/2021] [Indexed: 12/15/2022] Open
Abstract
A reliable model of biological age is instrumental in the field of geriatrics and gerontology. This model should account for the heterogeneity and plasticity of aging and also accurately predict aging-related adverse outcomes. Epigenetic age models are based on DNA methylation levels at selected genomic sites and can be significant predictors of mortality and healthy/unhealthy aging. However, the biological function of DNA methylation at selected sites is yet to be determined. Frailty is a syndrome resulting from decreased physiological reserves and resilience. The frailty index is a probability-based extension of the concept of frailty. Defined as the proportion of health deficits, the frailty index quantifies the progression of unhealthy aging. The frailty index is currently the best predictor of mortality. It is associated with various biological factors and provides insight into the biological processes of aging. Investigation of the multi-omics factors associated with the frailty index will provide further insight.
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Affiliation(s)
- Lixin Ji
- Tulane University School of Medicine, New Orleans, LA, USA
| | - S Michal Jazwinski
- Tulane Center for Aging & Department of Medicine, Tulane University Health Sciences Center, New Orleans, LA, USA
| | - Sangkyu Kim
- Tulane Center for Aging & Department of Medicine, Tulane University Health Sciences Center, New Orleans, LA, USA
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247
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McCrory C, Fiorito G, Hernandez B, Polidoro S, O'Halloran AM, Hever A, Ni Cheallaigh C, Lu AT, Horvath S, Vineis P, Kenny RA. GrimAge Outperforms Other Epigenetic Clocks in the Prediction of Age-Related Clinical Phenotypes and All-Cause Mortality. J Gerontol A Biol Sci Med Sci 2021; 76:741-749. [PMID: 33211845 DOI: 10.1093/gerona/glaa286] [Citation(s) in RCA: 191] [Impact Index Per Article: 63.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2020] [Indexed: 12/18/2022] Open
Abstract
The aging process is characterized by the presence of high interindividual variation between individuals of the same chronical age prompting a search for biomarkers that capture this heterogeneity. Epigenetic clocks measure changes in DNA methylation levels at specific CpG sites that are highly correlated with calendar age. The discrepancy resulting from the regression of DNA methylation age on calendar age is hypothesized to represent a measure of biological aging with a positive/negative residual signifying age acceleration (AA)/deceleration, respectively. The present study examines the associations of 4 epigenetic clocks-Horvath, Hannum, PhenoAge, GrimAge-with a wide range of clinical phenotypes (walking speed, grip strength, Fried frailty, polypharmacy, Mini-Mental State Examination (MMSE), Montreal Cognitive Assessment (MOCA), Sustained Attention Reaction Time, 2-choice reaction time), and with all-cause mortality at up to 10-year follow-up, in a sample of 490 participants in the Irish Longitudinal Study on Ageing (TILDA). HorvathAA and HannumAA were not predictive of health; PhenoAgeAA was associated with 4/9 outcomes (walking speed, frailty MOCA, MMSE) in minimally adjusted models, but not when adjusted for other social and lifestyle factors. GrimAgeAA by contrast was associated with 8/9 outcomes (all except grip strength) in minimally adjusted models, and remained a significant predictor of walking speed, .polypharmacy, frailty, and mortality in fully adjusted models. Results indicate that the GrimAge clock represents a step-improvement in the predictive utility of the epigenetic clocks for identifying age-related decline in an array of clinical phenotypes promising to advance precision medicine.
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Affiliation(s)
- Cathal McCrory
- Department of Medical Gerontology, Trinity College Dublin, Ireland
| | - Giovanni Fiorito
- Department of Biomedical Sciences, University of Sassari, Italy.,MRC Centre for Environment and Health, School of Public Medicine, Imperial College London, UK
| | | | | | | | - Ann Hever
- Department of Medical Gerontology, Trinity College Dublin, Ireland
| | | | - Ake T Lu
- Department of Human Genetics, David Geffen School of Medicine, Department of Biostatistics Fielding School of Public Health, University of California Los Angeles
| | - Steve Horvath
- Department of Human Genetics, David Geffen School of Medicine, Department of Biostatistics Fielding School of Public Health, University of California Los Angeles
| | - Paolo Vineis
- MRC Centre for Environment and Health, School of Public Medicine, Imperial College London, UK
| | - Rose Anne Kenny
- Department of Medical Gerontology, Trinity College Dublin, Ireland
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248
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Hirota N, Suzuki S, Arita T, Yagi N, Otsuka T, Yamashita T. Prediction of biological age and all-cause mortality by 12-lead electrocardiogram in patients without structural heart disease. BMC Geriatr 2021; 21:460. [PMID: 34380426 PMCID: PMC8359578 DOI: 10.1186/s12877-021-02391-8] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2020] [Accepted: 07/13/2021] [Indexed: 12/12/2022] Open
Abstract
Background There is a well-established relationship between 12-lead electrocardiogram (ECG) and age and mortality. Furthermore, there is increasing evidence that ECG can be used to predict biological age. However, the utility of biological age from ECG for predicting mortality remains unclear. Methods This was a single-center cohort study from a cardiology specialized hospital. A total of 19,170 patients registered in this study from February 2010 to March 2018. ECG was analyzed in a final 12,837 patients after excluding those with structural heart disease or with pacing beats, atrial or ventricular tachyarrhythmia, or an indeterminate axis (R axis > 180°) on index ECG. The models for biological age were developed by principal component analysis (BA) and the Klemera and Doubal’s method (not adjusted for age [BAE] and adjusted for age [BAEC]) using 438 ECG parameters. The predictive capability for all-cause death and cardiovascular death by chronological age (CA) and biological age using the three algorithms were evaluated by receiver operating characteristic analysis. Results During the mean follow-up period of 320.4 days, there were 55 all-cause deaths and 23 cardiovascular deaths. The predictive capabilities for all-cause death by BA, BAE, and BAEC using area under the curves were 0.731, 0.657, and 0.685, respectively, which were comparable to 0.725 for CA (p = 0.760, 0.141, and 0.308, respectively). The predictive capabilities for cardiovascular death by BA, BAE, and BAEC were 0.682, 0.685, and 0.692, respectively, which were also comparable to 0.674 for CA (p = 0.775, 0.839, and 0.706, respectively). In patients aged 60–74 years old, the area under the curves for all-cause death by BA, BAE, and BAEC were 0.619, 0.702, and 0.697, respectively, which tended to be or were significantly higher than 0.482 for CA (p = 0.064, 0.006, and 0.005, respectively). Conclusion Biological age by 12-lead ECG showed a similar predictive capability for mortality compared to CA among total patients, but partially showed a significant increase in predictive capability among patients aged 60–74 years old. Supplementary Information The online version contains supplementary material available at 10.1186/s12877-021-02391-8.
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Affiliation(s)
- Naomi Hirota
- Department of Cardiovascular Medicine, The Cardiovascular Institute, 3-2-19 Nishiazabu, Minato-Ku, Tokyo, 106-0031, Japan.
| | - Shinya Suzuki
- Department of Cardiovascular Medicine, The Cardiovascular Institute, 3-2-19 Nishiazabu, Minato-Ku, Tokyo, 106-0031, Japan
| | - Takuto Arita
- Department of Cardiovascular Medicine, The Cardiovascular Institute, 3-2-19 Nishiazabu, Minato-Ku, Tokyo, 106-0031, Japan
| | - Naoharu Yagi
- Department of Cardiovascular Medicine, The Cardiovascular Institute, 3-2-19 Nishiazabu, Minato-Ku, Tokyo, 106-0031, Japan
| | - Takayuki Otsuka
- Department of Cardiovascular Medicine, The Cardiovascular Institute, 3-2-19 Nishiazabu, Minato-Ku, Tokyo, 106-0031, Japan
| | - Takeshi Yamashita
- Department of Cardiovascular Medicine, The Cardiovascular Institute, 3-2-19 Nishiazabu, Minato-Ku, Tokyo, 106-0031, Japan
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249
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Maddock J, Castillo-Fernandez J, Wong A, Ploubidis GB, Kuh D, Bell JT, Hardy R. Childhood growth and development and DNA methylation age in mid-life. Clin Epigenetics 2021; 13:155. [PMID: 34372922 PMCID: PMC8351141 DOI: 10.1186/s13148-021-01138-x] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2021] [Accepted: 07/20/2021] [Indexed: 01/03/2023] Open
Abstract
BACKGROUND In the first study of its kind, we examine the association between growth and development in early life and DNAm age biomarkers in mid-life. METHODS Participants were from the Medical Research Council National Survey of Health and Development (n = 1376). Four DNAm age acceleration (AgeAccel) biomarkers were measured when participants were aged 53 years: AgeAccelHannum; AgeAccelHorvath; AgeAccelLevine; and AgeAccelGrim. Exposure variables included: relative weight gain (standardised residuals from models of current weight z-score on current height, and previous weight and height z-scores); and linear growth (standardised residuals from models of current height z-score on previous height and weight z-scores) during infancy (0-2 years, weight gain only), early childhood (2-4 years), middle childhood (4-7 years) and late childhood to adolescence (7-15 years); age at menarche; and pubertal stage for men at 14-15 years. The relationship between relative weight gain and linear growth and AgeAccel was investigated using conditional growth models. We replicated analyses from the late childhood to adolescence period and pubertal timing among 240 participants from The National Child and Development Study (NCDS). RESULTS A 1SD increase in relative weight gain in late childhood to adolescence was associated with 0.50 years (95% CI 0.20, 0.79) higher AgeAccelGrim. Although the CI includes the null, the estimate was similar in NCDS [0.57 years (95% CI - 0.01, 1.16)] There was no strong evidence that relative weight gain and linear growth in childhood was associated with any other AgeAccel biomarker. There was no relationship between pubertal timing in men and AgeAccel biomarkers. Women who reached menarche ≥ 12 years had 1.20 years (95% CI 0.15, 2.24) higher AgeAccelGrim on average than women who reached menarche < 12 years; however, this was not replicated in NCDS and was not statistically significant after Bonferroni correction. CONCLUSIONS Our findings generally do not support an association between growth and AgeAccel biomarkers in mid-life. However, we found rapid weight gain during pubertal development, previously related to higher cardiovascular disease risk, to be associated with older AgeAccelGrim. Given this is an exploratory study, this finding requires replication.
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Affiliation(s)
- Jane Maddock
- MRC Unit for Lifelong Health and Ageing at UCL, Faculty of Population Health, University College London, 1-19 Torrington Place, London, WC1E 7HB, UK.
| | | | - Andrew Wong
- MRC Unit for Lifelong Health and Ageing at UCL, Faculty of Population Health, University College London, 1-19 Torrington Place, London, WC1E 7HB, UK
| | - George B Ploubidis
- Centre for Longitudinal Studies, UCL Social Research Institute, University College London, London, UK
| | - Diana Kuh
- MRC Unit for Lifelong Health and Ageing at UCL, Faculty of Population Health, University College London, 1-19 Torrington Place, London, WC1E 7HB, UK
| | - Jordana T Bell
- Department of Twin Research and Genetic Epidemiology, King's College London, London, UK
| | - Rebecca Hardy
- CLOSER, UCL Institute of Education, University College London, London, WC1H 0NU, UK
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250
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Hillary RF, Stevenson AJ, Cox SR, McCartney DL, Harris SE, Seeboth A, Higham J, Sproul D, Taylor AM, Redmond P, Corley J, Pattie A, Hernández MDCV, Muñoz-Maniega S, Bastin ME, Wardlaw JM, Horvath S, Ritchie CW, Spires-Jones TL, McIntosh AM, Evans KL, Deary IJ, Marioni RE. An epigenetic predictor of death captures multi-modal measures of brain health. Mol Psychiatry 2021; 26:3806-3816. [PMID: 31796892 PMCID: PMC8550950 DOI: 10.1038/s41380-019-0616-9] [Citation(s) in RCA: 66] [Impact Index Per Article: 22.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/30/2019] [Revised: 11/14/2019] [Accepted: 11/20/2019] [Indexed: 11/08/2022]
Abstract
Individuals of the same chronological age exhibit disparate rates of biological ageing. Consequently, a number of methodologies have been proposed to determine biological age and primarily exploit variation at the level of DNA methylation (DNAm). A novel epigenetic clock, termed 'DNAm GrimAge' has outperformed its predecessors in predicting the risk of mortality as well as many age-related morbidities. However, the association between DNAm GrimAge and cognitive or neuroimaging phenotypes remains unknown. We explore these associations in the Lothian Birth Cohort 1936 (n = 709, mean age 73 years). Higher DNAm GrimAge was strongly associated with all-cause mortality over the eighth decade (Hazard Ratio per standard deviation increase in GrimAge: 1.81, P < 2.0 × 10-16). Higher DNAm GrimAge was associated with lower age 11 IQ (β = -0.11), lower age 73 general cognitive ability (β = -0.18), decreased brain volume (β = -0.25) and increased brain white matter hyperintensities (β = 0.17). There was tentative evidence for a longitudinal association between DNAm GrimAge and cognitive decline from age 70 to 79. Sixty-nine of 137 health- and brain-related phenotypes tested were significantly associated with GrimAge. Adjusting all models for childhood intelligence attenuated to non-significance a small number of associations (12/69 associations; 6 of which were cognitive traits), but not the association with general cognitive ability (33.9% attenuation). Higher DNAm GrimAge associates with lower cognitive ability and brain vascular lesions in older age, independently of early-life cognitive ability. This epigenetic predictor of mortality associates with different measures of brain health and may aid in the prediction of age-related cognitive decline.
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Affiliation(s)
- Robert F Hillary
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK
| | - Anna J Stevenson
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK
| | - Simon R Cox
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
- Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - Daniel L McCartney
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK
| | - Sarah E Harris
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
- Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - Anne Seeboth
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK
| | - Jon Higham
- Medical Research Council Human Genetics Unit, Medical Research Council Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK
| | - Duncan Sproul
- Medical Research Council Human Genetics Unit, Medical Research Council Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK
- Edinburgh Cancer Research Centre, Medical Research Council Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK
| | - Adele M Taylor
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
- Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - Paul Redmond
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
- Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - Janie Corley
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
- Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - Alison Pattie
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
- Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - Maria Del C Valdés Hernández
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
- Department of Neuroimaging Sciences, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - Susana Muñoz-Maniega
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
- Department of Neuroimaging Sciences, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - Mark E Bastin
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
- Department of Neuroimaging Sciences, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - Joanna M Wardlaw
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
- Department of Neuroimaging Sciences, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
- UK Dementia Research Institute, Edinburgh Medical School, University of Edinburgh, Edinburgh, UK
| | - Steve Horvath
- Department of Human Genetics, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California, USA
- Department of Biostatistics, Fielding School of Public Health, University of California Los Angeles, Los Angeles, California, USA
| | - Craig W Ritchie
- Edinburgh Dementia Prevention, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - Tara L Spires-Jones
- UK Dementia Research Institute, Edinburgh Medical School, University of Edinburgh, Edinburgh, UK
- Centre for Discovery Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - Andrew M McIntosh
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
- Division of Psychiatry, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - Kathryn L Evans
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
| | - Ian J Deary
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
- Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - Riccardo E Marioni
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK.
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK.
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