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Griffin PT, Kane AE, Trapp A, Li J, Arnold M, Poganik JR, Conway RJ, McNamara MS, Meer MV, Hoffman N, Amorim JA, Tian X, MacArthur MR, Mitchell SJ, Mueller AL, Carmody C, Vera DL, Kerepesi C, Ying K, Noren Hooten N, Mitchell JR, Evans MK, Gladyshev VN, Sinclair DA. TIME-seq reduces time and cost of DNA methylation measurement for epigenetic clock construction. NATURE AGING 2024; 4:261-274. [PMID: 38200273 PMCID: PMC11332592 DOI: 10.1038/s43587-023-00555-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/06/2021] [Accepted: 12/05/2023] [Indexed: 01/12/2024]
Abstract
Epigenetic 'clocks' based on DNA methylation have emerged as the most robust and widely used aging biomarkers, but conventional methods for applying them are expensive and laborious. Here we develop tagmentation-based indexing for methylation sequencing (TIME-seq), a highly multiplexed and scalable method for low-cost epigenetic clocks. Using TIME-seq, we applied multi-tissue and tissue-specific epigenetic clocks in over 1,800 mouse DNA samples from eight tissue and cell types. We show that TIME-seq clocks are accurate and robust, enriched for polycomb repressive complex 2-regulated loci, and benchmark favorably against conventional methods despite being up to 100-fold less expensive. Using dietary treatments and gene therapy, we find that TIME-seq clocks reflect diverse interventions in multiple tissues. Finally, we develop an economical human blood clock (R > 0.96, median error = 3.39 years) in 1,056 demographically representative individuals. These methods will enable more efficient epigenetic clock measurement in larger-scale human and animal studies.
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Affiliation(s)
- Patrick T Griffin
- Blavatnik Institute, Department of Genetics, Paul F. Glenn Center for Biology of Aging Research at Harvard Medical School, Boston, MA, USA
| | - Alice E Kane
- Blavatnik Institute, Department of Genetics, Paul F. Glenn Center for Biology of Aging Research at Harvard Medical School, Boston, MA, USA
- Institute for Systems Biology, Seattle, WA, USA
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, WA, USA
| | - Alexandre Trapp
- Brigham and Women's Hospital, Division of Genetics, Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Jien Li
- Blavatnik Institute, Department of Genetics, Paul F. Glenn Center for Biology of Aging Research at Harvard Medical School, Boston, MA, USA
| | - Matthew Arnold
- Blavatnik Institute, Department of Genetics, Paul F. Glenn Center for Biology of Aging Research at Harvard Medical School, Boston, MA, USA
| | - Jesse R Poganik
- Brigham and Women's Hospital, Division of Genetics, Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Ryan J Conway
- Blavatnik Institute, Department of Genetics, Paul F. Glenn Center for Biology of Aging Research at Harvard Medical School, Boston, MA, USA
| | - Maeve S McNamara
- Blavatnik Institute, Department of Genetics, Paul F. Glenn Center for Biology of Aging Research at Harvard Medical School, Boston, MA, USA
| | - Margarita V Meer
- Brigham and Women's Hospital, Division of Genetics, Department of Medicine, Harvard Medical School, Boston, MA, USA
- Department of Pathology, Yale University School of Medicine, New Haven, CT, USA
- San Diego Institute of Science, Altos Labs, San Diego, CA, USA
| | - Noah Hoffman
- Blavatnik Institute, Department of Genetics, Paul F. Glenn Center for Biology of Aging Research at Harvard Medical School, Boston, MA, USA
| | - João A Amorim
- Blavatnik Institute, Department of Genetics, Paul F. Glenn Center for Biology of Aging Research at Harvard Medical School, Boston, MA, USA
| | - Xiao Tian
- Blavatnik Institute, Department of Genetics, Paul F. Glenn Center for Biology of Aging Research at Harvard Medical School, Boston, MA, USA
- Sanford Burnham Prebys Medical Discovery Institute, La Jolla, CA, USA
| | - Michael R MacArthur
- Department of Health Sciences and Technology, Eidgenössische Technische Hochschule Zürich, Zurich, Switzerland
- Lewis-Sigler Institute of Integrative Genomics, Princeton University, Princeton, NJ, USA
| | - Sarah J Mitchell
- Department of Health Sciences and Technology, Eidgenössische Technische Hochschule Zürich, Zurich, Switzerland
- Ludwig Princeton Branch, Princeton University, Princeton, NJ, USA
| | - Amber L Mueller
- Blavatnik Institute, Department of Genetics, Paul F. Glenn Center for Biology of Aging Research at Harvard Medical School, Boston, MA, USA
- Cell Metabolism, Cell Press, Cambridge, MA, USA
| | - Colleen Carmody
- Blavatnik Institute, Department of Genetics, Paul F. Glenn Center for Biology of Aging Research at Harvard Medical School, Boston, MA, USA
| | - Daniel L Vera
- Blavatnik Institute, Department of Genetics, Paul F. Glenn Center for Biology of Aging Research at Harvard Medical School, Boston, MA, USA
| | - Csaba Kerepesi
- Brigham and Women's Hospital, Division of Genetics, Department of Medicine, Harvard Medical School, Boston, MA, USA
- Institute for Computer Science and Control, Eötvös Loránd Research Network, Budapest, Hungary
| | - Kejun Ying
- Brigham and Women's Hospital, Division of Genetics, Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Nicole Noren Hooten
- Laboratory of Epidemiology and Population Science, National Institute on Aging, National Institutes of Health, Baltimore, MD, USA
| | - James R Mitchell
- Department of Health Sciences and Technology, Eidgenössische Technische Hochschule Zürich, Zurich, Switzerland
| | - Michele K Evans
- Laboratory of Epidemiology and Population Science, National Institute on Aging, National Institutes of Health, Baltimore, MD, USA
| | - Vadim N Gladyshev
- Brigham and Women's Hospital, Division of Genetics, Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - David A Sinclair
- Blavatnik Institute, Department of Genetics, Paul F. Glenn Center for Biology of Aging Research at Harvard Medical School, Boston, MA, USA.
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Mohanraj L, Wolf H, Silvey S, Liu J, Toor A, Swift-Scanlan T. DNA Methylation Changes in Autologous Hematopoietic Stem Cell Transplant Patients. Biol Res Nurs 2023; 25:310-325. [PMID: 36321693 PMCID: PMC10236442 DOI: 10.1177/10998004221135628] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
BACKGROUND Blood cancers may be potentially cured with hematopoietic stem cell transplantation (HCT); however, standard pre-assessments for transplant eligibility do not capture all contributing factors for transplant outcomes. Epigenetic biomarkers predict outcomes in various diseases. This pilot study aims to explore epigenetic changes (epigenetic age and differentially methylated genes) in patients before and after autologous HCT, that can serve as potential biomarkers to better predict HCT outcomes. METHODS This study used a prospective longitudinal study design to compare genome wide DNA methylation changes in 36 autologous HCT eligible patients recruited from the Cellular Immunotherapies and Transplant clinic at a designated National Cancer Center. RESULTS Genome-wide DNA methylation, measured by the Illumina Infinium Human Methylation 850K BeadChip, showed a significant difference in DNA methylation patterns post-HCT compared to pre-HCT. Compared to baseline levels of DNA methylation pre-HCT, 3358 CpG sites were hypo-methylated and 3687 were hyper-methylated. Identified differentially methylated positions overlapped with genes involved in hematopoiesis, blood cancers, inflammation and immune responses. Enrichment analyses showed significant alterations in biological processes such as immune response and cell structure organization, however no significant pathways were noted. Though participants had an advanced epigenetic age compared to chronologic age before and after HCT, both epigenetic age and accelerated age decreased post-HCT. CONCLUSION Epigenetic changes, both in epigenetic age and differentially methylated genes were observed in autologous HCT recipients, and should be explored as biomarkers to predict transplant outcomes after autologous HCT in larger, longitudinal studies.
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Affiliation(s)
- Lathika Mohanraj
- Department of Adult Health and Nursing
Systems, VCU School of Nursing, Richmond, VA, USA
| | - Hope Wolf
- Department of Human and Molecular Genetics, VCU School of Medicine, Richmond, VA, USA
| | - Scott Silvey
- Department of Biostatistics, VCU School of Medicine, Richmond, VA, USA
| | - Jinze Liu
- Department of Biostatistics, VCU School of Medicine, Richmond, VA, USA
| | - Amir Toor
- Department of Internal Medicine, VCU School of Medicine, Richmond, VA, USA
| | - Theresa Swift-Scanlan
- Endowed Professor and Director,
Biobehavioral Research Lab, VCU School of Nursing, Richmond, VA, USA
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Nwanaji-Enwerem JC, Colicino E, Gao X, Wang C, Vokonas P, Boyer EW, Baccarelli AA, Schwartz J. Associations of Plasma Folate and Vitamin B6 With Blood DNA Methylation Age: An Analysis of One-Carbon Metabolites in the VA Normative Aging Study. J Gerontol A Biol Sci Med Sci 2021; 76:760-769. [PMID: 33027507 DOI: 10.1093/gerona/glaa257] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2020] [Indexed: 02/01/2023] Open
Abstract
One-carbon metabolism is an important contributor to aging-related diseases; nevertheless, relationships of one-carbon metabolites with novel DNA methylation-based measures of biological aging remain poorly characterized. We examined relationships of one-carbon metabolites with 3 DNA methylation-based measures of biological aging: DNAmAge, GrimAge, and PhenoAge. We measured plasma levels of 4 common one-carbon metabolites (vitamin B6, vitamin B12, folate, and homocysteine) in 715 VA Normative Aging Study participants with at least 1 visit between 1999 and 2008 (observations = 1153). DNA methylation age metrics were calculated using the HumanMethylation450 BeadChip. We utilized Bayesian Kernel Machine Regression models adjusted for chronological age, lifestyle factors, age-related diseases, and study visits to determine metabolites important to the aging outcomes. Bayesian Kernel Machine Regression models allowed for the estimation of the relationships of single metabolites and the cumulative metabolite mixture with methylation age. Log vitamin B6 was selected as important to PhenoAge (β = -1.62 years, 95% CI: -2.28, -0.96). Log folate was selected as important to GrimAge (β = 0.75 years, 95% CI: 0.41, 1.09) and PhenoAge (β = 1.62 years, 95% CI: 0.95, 2.29). Compared to a model where each metabolite in the mixture is set to its 50th percentile, the log cumulative mixture with each metabolite at its 30th (β = -0.13 years, 95% CI: -0.26, -0.005) and 40th percentile (β = -0.06 years, 95% CI: -0.11, -0.005) was associated with decreased GrimAge. Our results provide novel characterizations of the relationships between one-carbon metabolites and DNA methylation age in a human population study. Further research is required to confirm these findings and establish their generalizability.
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Affiliation(s)
- Jamaji C Nwanaji-Enwerem
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, and MD/PhD Program, Harvard Medical School, Boston, Massachusetts
| | - Elena Colicino
- Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, New York
| | - Xu Gao
- Department of Environmental Health Sciences, Columbia Mailman School of Public Health, New York, New York
| | - Cuicui Wang
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, Massachusetts
| | - Pantel Vokonas
- VA Normative Aging Study, Veterans Affairs Boston Healthcare System and the Department of Medicine, Boston University School of Medicine, Massachusetts
| | - Edward W Boyer
- Division of Medical Toxicology, Department of Emergency Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts
| | - Andrea A Baccarelli
- Department of Environmental Health Sciences, Columbia Mailman School of Public Health, New York, New York
| | - Joel Schwartz
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, Massachusetts
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