1
|
Smith ZD, Hetzel S, Meissner A. DNA methylation in mammalian development and disease. Nat Rev Genet 2025; 26:7-30. [PMID: 39134824 DOI: 10.1038/s41576-024-00760-8] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 06/24/2024] [Indexed: 12/15/2024]
Abstract
The DNA methylation field has matured from a phase of discovery and genomic characterization to one seeking deeper functional understanding of how this modification contributes to development, ageing and disease. In particular, the past decade has seen many exciting mechanistic discoveries that have substantially expanded our appreciation for how this generic, evolutionarily ancient modification can be incorporated into robust epigenetic codes. Here, we summarize the current understanding of the distinct DNA methylation landscapes that emerge over the mammalian lifespan and discuss how they interact with other regulatory layers to support diverse genomic functions. We then review the rising interest in alternative patterns found during senescence and the somatic transition to cancer. Alongside advancements in single-cell and long-read sequencing technologies, the collective insights made across these fields offer new opportunities to connect the biochemical and genetic features of DNA methylation to cell physiology, developmental potential and phenotype.
Collapse
Affiliation(s)
- Zachary D Smith
- Department of Genetics, Yale Stem Cell Center, Yale School of Medicine, New Haven, CT, USA.
| | - Sara Hetzel
- Department of Genome Regulation, Max Planck Institute for Molecular Genetics, Berlin, Germany
| | - Alexander Meissner
- Department of Genome Regulation, Max Planck Institute for Molecular Genetics, Berlin, Germany.
| |
Collapse
|
2
|
Campos FA, Wikberg EC, Orkin JD, Park Y, Snyder-Mackler N, Cheves Hernandez S, Lopez Navarro R, Fedigan LM, Gurven M, Higham JP, Jack KM, Melin AD. Wild capuchin monkeys as a model system for investigating the social and ecological determinants of ageing. Philos Trans R Soc Lond B Biol Sci 2024; 379:20230482. [PMID: 39463253 PMCID: PMC11513648 DOI: 10.1098/rstb.2023.0482] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2023] [Revised: 03/29/2024] [Accepted: 05/10/2024] [Indexed: 10/29/2024] Open
Abstract
Studying biological ageing in animal models can circumvent some of the confounds exhibited by studies of human ageing. Ageing research in non-human primates has provided invaluable insights into human lifespan and healthspan. Yet data on patterns of ageing from wild primates remain relatively scarce, centred around a few populations of catarrhine species. Here, we introduce the white-faced capuchin, a long-lived platyrrhine primate, as a promising new model system for ageing research. Like humans, capuchins are highly social, omnivorous generalists, whose healthspan and lifespan relative to body size exceed that of other non-human primate model species. We review recent insights from capuchin ageing biology and outline our expanding, integrative research programme that combines metrics of the social and physical environments with physical, physiological and molecular hallmarks of ageing across the natural life courses of multiple longitudinally tracked individuals. By increasing the taxonomic breadth of well-studied primate ageing models, we generate new insights, increase the comparative value of existing datasets to geroscience and work towards the collective goal of developing accurate, non-invasive and reliable biomarkers with high potential for standardization across field sites and species, enhancing the translatability of primate studies.This article is part of the discussion meeting issue 'Understanding age and society using natural populations'.
Collapse
Affiliation(s)
- Fernando A. Campos
- Department of Anthropology, University of Texas at San Antonio, San Antonio, TX78249, USA
| | - Eva C. Wikberg
- Department of Anthropology, University of Texas at San Antonio, San Antonio, TX78249, USA
| | - Joseph D. Orkin
- Département d’anthropologie, Université de Montréal, Montréal, QuébecH3T 1N8, Canada
- Département de sciences biologiques, Université de Montréal, Montréal, QuébecH2V 0B3, Canada
| | - Yeonjoo Park
- Department of Management Science and Statistics, University of Texas at San Antonio, San Antonio, TX78249, USA
| | - Noah Snyder-Mackler
- Center for Evolution and Medicine, School of Life Sciences, School of Human Evolution and Social Change, Arizona State University, Tempe, AZ85287, USA
| | | | | | - Linda M. Fedigan
- Department of Anthropology and Archaeology, University of Calgary, Calgary, AlbertaT2N 1N4, Canada
| | - Michael Gurven
- Department of Anthropology, University of California, Santa Barbara, CA93106, USA
| | - James P. Higham
- Department of Anthropology, New York University, NY10003, USA
| | - Katharine M. Jack
- Department of Anthropology, Tulane University, New Orleans, LA70118, USA
| | - Amanda D. Melin
- Department of Anthropology and Archaeology, University of Calgary, Calgary, AlbertaT2N 1N4, Canada
- Department of Medical Genetics, University of Calgary, Calgary, AlbertaT2N 4N1, Canada
- Alberta Children’s Hospital Research Institute, University of Calgary, Calgary, AlbertaT2N 4N1, Canada
| |
Collapse
|
3
|
Blokhina Y, Buchwalter A. Modeling the consequences of age-linked rDNA hypermethylation with dCas9-directed DNA methylation in human cells. PLoS One 2024; 19:e0310626. [PMID: 39666677 PMCID: PMC11637357 DOI: 10.1371/journal.pone.0310626] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2024] [Accepted: 09/03/2024] [Indexed: 12/14/2024] Open
Abstract
Ribosomal DNA (rDNA) genes encode the structural RNAs of the ribosome and are present in hundreds of copies in mammalian genomes. Age-linked DNA hypermethylation throughout the rDNA constitutes a robust "methylation clock" that accurately reports age, yet the consequences of hypermethylation on rDNA function are unknown. We confirmed that pervasive hypermethylation of rDNA occurs during mammalian aging and senescence while rDNA copy number remains stable. We found that DNA methylation is exclusively found on the promoters and gene bodies of inactive rDNA. To model the effects of age-linked methylation on rDNA function, we directed de novo DNA methylation to the rDNA promoter or gene body with a nuclease-dead Cas9 (dCas9)-DNA methyltransferase fusion enzyme in human cells. Hypermethylation at each target site had no detectable effect on rRNA transcription, nucleolar morphology, or cellular growth rate. Instead, human UBF and Pol I remain bound to rDNA promoters in the presence of increased DNA methylation. These data suggest that promoter methylation is not sufficient to impair transcription of the human rDNA and imply that the human rDNA transcription machinery may be resilient to age-linked rDNA hypermethylation.
Collapse
Affiliation(s)
- Yana Blokhina
- Cardiovascular Research Institute and Department of Physiology, University of California, San Francisco, San Francisco, California, United States of America
| | - Abigail Buchwalter
- Cardiovascular Research Institute and Department of Physiology, University of California, San Francisco, San Francisco, California, United States of America
| |
Collapse
|
4
|
Huang H, Chen Y, Xu W, Cao L, Qian K, Bischof E, Kennedy BK, Pu J. Decoding aging clocks: New insights from metabolomics. Cell Metab 2024:S1550-4131(24)00453-4. [PMID: 39657675 DOI: 10.1016/j.cmet.2024.11.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/25/2024] [Revised: 09/23/2024] [Accepted: 11/10/2024] [Indexed: 12/12/2024]
Abstract
Chronological age is a crucial risk factor for diseases and disabilities among older adults. However, individuals of the same chronological age often exhibit divergent biological aging states, resulting in distinct individual risk profiles. Chronological age estimators based on omics data and machine learning techniques, known as aging clocks, provide a valuable framework for interpreting molecular-level biological aging. Metabolomics is an intriguing and rapidly growing field of study, involving the comprehensive profiling of small molecules within the body and providing the ultimate genome-environment interaction readout. Consequently, leveraging metabolomics to characterize biological aging holds immense potential. The aim of this review was to provide an overview of metabolomics approaches, highlighting the establishment and interpretation of metabolomic aging clocks while emphasizing their strengths, limitations, and applications, and to discuss their underlying biological significance, which has the potential to drive innovation in longevity research and development.
Collapse
Affiliation(s)
- Honghao Huang
- Division of Cardiology, State Key Laboratory for Systems Medicine for Cancer, Shanghai Cancer Institute, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Yifan Chen
- Division of Cardiology, State Key Laboratory for Systems Medicine for Cancer, Shanghai Cancer Institute, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Wei Xu
- Division of Cardiology, State Key Laboratory for Systems Medicine for Cancer, Shanghai Cancer Institute, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Linlin Cao
- Division of Cardiology, State Key Laboratory for Systems Medicine for Cancer, Shanghai Cancer Institute, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Kun Qian
- Division of Cardiology, State Key Laboratory for Systems Medicine for Cancer, Shanghai Cancer Institute, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China; School of Biomedical Engineering and Med-X Research Institute, Shanghai Jiao Tong University, Shanghai, China
| | - Evelyne Bischof
- University Hospital of Basel, Division of Internal Medicine, University of Basel, Basel, Switzerland; Shanghai University of Medicine and Health Sciences, College of Clinical Medicine, Shanghai, China
| | - Brian K Kennedy
- Health Longevity Translational Research Programme, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore; Centre for Healthy Longevity, National University Health System, Singapore, Singapore; Departments of Biochemistry and Physiology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore.
| | - Jun Pu
- Division of Cardiology, State Key Laboratory for Systems Medicine for Cancer, Shanghai Cancer Institute, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China; Aging Biomarker Consortium, China.
| |
Collapse
|
5
|
Hwang T, Sitko LK, Khoirunnisa R, Navarro-Aguad F, Samuel DM, Park H, Cheon B, Mutsnaini L, Lee J, Otlu B, Takeda S, Lee S, Ivanov D, Gartner A. Comprehensive whole-genome sequencing reveals origins of mutational signatures associated with aging, mismatch repair deficiency and temozolomide chemotherapy. Nucleic Acids Res 2024:gkae1122. [PMID: 39656916 DOI: 10.1093/nar/gkae1122] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2024] [Revised: 10/17/2024] [Accepted: 11/07/2024] [Indexed: 12/17/2024] Open
Abstract
In a comprehensive study to decipher the multi-layered response to the chemotherapeutic agent temozolomide (TMZ), we analyzed 427 genomes and determined mutational patterns in a collection of ∼40 isogenic DNA repair-deficient human TK6 lymphoblast cell lines. We first demonstrate that the spontaneous mutational background is very similar to the aging-associated mutational signature SBS40 and mainly caused by polymerase zeta-mediated translesion synthesis (TLS). MSH2-/- mismatch repair (MMR) knockout in conjunction with additional repair deficiencies uncovers cryptic mutational patterns. We next report how distinct mutational signatures are induced by TMZ upon sequential inactivation of DNA repair pathways, mirroring the acquisition of chemotherapy resistance by glioblastomas. The most toxic adduct induced by TMZ, O6-meG, is directly repaired by the O6-methylguanine-DNA methyltransferase (MGMT). In MGMT-/- cells, MMR leads to cell death and limits mutagenesis. MMR deficiency results in TMZ resistance, allowing the accumulation of ∼105 C > T substitutions corresponding to signature SBS11. Under these conditions, N3-methyladenine (3-meA), processed by base excision repair (BER), limits cell survival. Without BER, 3-meA is read through via error-prone TLS, causing T > A substitutions but not affecting survival. Blocking BER after abasic site formation results in large deletions and TMZ hypersensitization. Our findings reveal potential vulnerabilities of TMZ-resistant tumors.
Collapse
Affiliation(s)
- Taejoo Hwang
- Department of Biomedical Engineering, Ulsan National Institute of Science and Technology (UNIST), UNIST-gil 50, Ulsan, 44919, Republic of Korea
| | - Lukasz Karol Sitko
- Department of Biological Sciences, Ulsan National Institute of Science and Technology (UNIST), UNIST-gil 50, Ulsan 44919, Republic of Korea
- Center for Genomic Integrity, Institute for Basic Science, UNIST-gil 50, Ulsan 44919, Republic of Korea
| | - Ratih Khoirunnisa
- Center for Genomic Integrity, Institute for Basic Science, UNIST-gil 50, Ulsan 44919, Republic of Korea
| | - Fernanda Navarro-Aguad
- Department of Biological Sciences, Ulsan National Institute of Science and Technology (UNIST), UNIST-gil 50, Ulsan 44919, Republic of Korea
- Center for Genomic Integrity, Institute for Basic Science, UNIST-gil 50, Ulsan 44919, Republic of Korea
| | - David M Samuel
- Center for Genomic Integrity, Institute for Basic Science, UNIST-gil 50, Ulsan 44919, Republic of Korea
| | - Hajoong Park
- Department of Biological Sciences, Ulsan National Institute of Science and Technology (UNIST), UNIST-gil 50, Ulsan 44919, Republic of Korea
- Center for Genomic Integrity, Institute for Basic Science, UNIST-gil 50, Ulsan 44919, Republic of Korea
| | - Banyoon Cheon
- Center for Genomic Integrity, Institute for Basic Science, UNIST-gil 50, Ulsan 44919, Republic of Korea
| | - Luthfiyyah Mutsnaini
- Center for Genomic Integrity, Institute for Basic Science, UNIST-gil 50, Ulsan 44919, Republic of Korea
| | - Jaewoong Lee
- Department of Biomedical Engineering, Ulsan National Institute of Science and Technology (UNIST), UNIST-gil 50, Ulsan, 44919, Republic of Korea
| | - Burçak Otlu
- Department of Health Informatics, Graduate School of Informatics, Middle East Technical University, Ankara, Turkey
| | - Shunichi Takeda
- Guangdong Key Laboratory for Genome Stability & Disease Prevention, Shenzhen University Medical School, 1066 Xueyuan Avenue, Shenzhen, Guangdong 518060, China
| | - Semin Lee
- Department of Biomedical Engineering, Ulsan National Institute of Science and Technology (UNIST), UNIST-gil 50, Ulsan, 44919, Republic of Korea
| | - Dmitri Ivanov
- Center for Genomic Integrity, Institute for Basic Science, UNIST-gil 50, Ulsan 44919, Republic of Korea
| | - Anton Gartner
- Department of Biological Sciences, Ulsan National Institute of Science and Technology (UNIST), UNIST-gil 50, Ulsan 44919, Republic of Korea
- Center for Genomic Integrity, Institute for Basic Science, UNIST-gil 50, Ulsan 44919, Republic of Korea
- Graduate School for Health Sciences and Technology, Ulsan National Institute of Science and Technology (UNIST), UNIST-gil 50, Ulsan, 44919, Republic of Korea
| |
Collapse
|
6
|
Biga PR, Duan JE, Young TE, Marks JR, Bronikowski A, Decena LP, Randolph EC, Pavuluri AG, Li G, Fang Y, Wilkinson GS, Singh G, Nigrin NT, Larschan EN, Lonski AJ, Riddle NC. Hallmarks of aging: A user's guide for comparative biologists. Ageing Res Rev 2024; 104:102616. [PMID: 39643212 DOI: 10.1016/j.arr.2024.102616] [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: 05/30/2024] [Revised: 11/25/2024] [Accepted: 12/02/2024] [Indexed: 12/09/2024]
Abstract
Since the first description of a set of characteristics of aging as so-called hallmarks or pillars in 2013/2014, these characteristics have served as guideposts for the research in aging biology. They have been examined in a range of contexts, across tissues, in response to disease conditions or environmental factors, and served as a benchmark for various anti-aging interventions. While the hallmarks of aging were intended to capture generalizable characteristics of aging, they are derived mostly from studies of rodents and humans. Comparative studies of aging including species from across the animal tree of life have great promise to reveal new insights into the mechanistic foundations of aging, as there is a great diversity in lifespan and age-associated physiological changes. However, it is unclear how well the defined hallmarks of aging apply across diverse species. Here, we review each of the twelve hallmarks of aging defined by Lopez-Otin in 2023 with respect to the availability of data from diverse species. We evaluate the current methods used to assess these hallmarks for their potential to be adapted for comparative studies. Not unexpectedly, we find that the data supporting the described hallmarks of aging are restricted mostly to humans and a few model systems and that no data are available for many animal clades. Similarly, not all hallmarks can be easily assessed in diverse species. However, for at least half of the hallmarks, there are methods available today that can be employed to fill this gap in knowledge, suggesting that these studies can be prioritized while methods are developed for comparative study of the remaining hallmarks.
Collapse
Affiliation(s)
- Peggy R Biga
- Department of Biology, The University of Alabama at Birmingham, Birmingham, AL, USA
| | - Jingyue E Duan
- Department of Animal Science, Cornell University, Ithaca, NY, USA
| | - Tristan E Young
- Department of Biology, The University of Alabama at Birmingham, Birmingham, AL, USA
| | - Jamie R Marks
- Department of Integrative Biology, W. K. Kellogg Biological Station, Michigan State University, Hickory Corners, MI, USA
| | - Anne Bronikowski
- Department of Integrative Biology, W. K. Kellogg Biological Station, Michigan State University, Hickory Corners, MI, USA
| | - Louis P Decena
- Department of Integrative Biology, W. K. Kellogg Biological Station, Michigan State University, Hickory Corners, MI, USA
| | - Eric C Randolph
- Department of Biology, The University of Alabama at Birmingham, Birmingham, AL, USA
| | - Ananya G Pavuluri
- Center for Computational Molecular Biology, Brown University, Providence, RI, USA
| | - Guangsheng Li
- Department of Animal Science, Cornell University, Ithaca, NY, USA
| | - Yifei Fang
- Department of Animal Science, Cornell University, Ithaca, NY, USA
| | | | - Gunjan Singh
- Department of Molecular Biology, Cellular Biology and Biochemistry, Brown University, Providence, RI, USA
| | - Nathan T Nigrin
- Department of Molecular Biology, Cellular Biology and Biochemistry, Brown University, Providence, RI, USA
| | - Erica N Larschan
- Department of Molecular Biology, Cellular Biology and Biochemistry, Brown University, Providence, RI, USA
| | - Andrew J Lonski
- Department of Molecular Biology, Cellular Biology and Biochemistry, Brown University, Providence, RI, USA
| | - Nicole C Riddle
- Department of Biology, The University of Alabama at Birmingham, Birmingham, AL, USA.
| |
Collapse
|
7
|
Torres G, Salladay-Perez IA, Dhingra A, Covarrubias AJ. Genetic origins, regulators, and biomarkers of cellular senescence. Trends Genet 2024; 40:1018-1031. [PMID: 39341687 DOI: 10.1016/j.tig.2024.08.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2024] [Revised: 08/18/2024] [Accepted: 08/21/2024] [Indexed: 10/01/2024]
Abstract
This review comprehensively examines the molecular biology and genetic origins of cellular senescence. We focus on various cellular stressors and pathways leading to senescence, including recent advances in the understanding of the genetic influences driving senescence, such as telomere attrition, chemotherapy-induced DNA damage, pathogens, oncogene activation, and cellular and metabolic stress. This review also highlights the complex interplay of various signaling and metabolic pathways involved in cellular senescence and provides insights into potential therapeutic targets for aging-related diseases. Furthermore, this review outlines future research directions to deepen our understanding of senescence biology and develop effective interventions targeting senescent cells (SnCs).
Collapse
Affiliation(s)
- Grasiela Torres
- Department of Microbiology, Immunology, and Molecular Genetics, University of California, Los Angeles, Los Angeles, CA, USA; Molecular Biology Interdepartmental Doctoral Program, University of California, Los Angeles, Los Angeles, CA, USA; Molecular Biology Institute, University of California, Los Angeles, Los Angeles, CA, USA
| | - Ivan A Salladay-Perez
- Department of Microbiology, Immunology, and Molecular Genetics, University of California, Los Angeles, Los Angeles, CA, USA; Molecular Biology Interdepartmental Doctoral Program, University of California, Los Angeles, Los Angeles, CA, USA; Molecular Biology Institute, University of California, Los Angeles, Los Angeles, CA, USA
| | - Anika Dhingra
- Department of Microbiology, Immunology, and Molecular Genetics, University of California, Los Angeles, Los Angeles, CA, USA
| | - Anthony J Covarrubias
- Department of Microbiology, Immunology, and Molecular Genetics, University of California, Los Angeles, Los Angeles, CA, USA; Molecular Biology Institute, University of California, Los Angeles, Los Angeles, CA, USA.
| |
Collapse
|
8
|
Singh K, Khairnar SI, Sanghavi A, Yadav TT, Gupta N, Arora J, Katcher HL. E5 treatment showing improved health-span and lifespan in old Sprague Dawley rats. Aging Cell 2024; 23:e14335. [PMID: 39297361 PMCID: PMC11634717 DOI: 10.1111/acel.14335] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2024] [Revised: 08/21/2024] [Accepted: 08/24/2024] [Indexed: 12/13/2024] Open
Abstract
Aging and, in particular, the emergence of age-related disorders is associated with tissue dysfunction and macromolecular damage, some of which can be attributable to accumulated oxidative damage. In the current study, we determine the potential of 'plasma-derived fraction (E5)' for cellular rejuvenation and extending the lifespan of Sprague Dawley (SD) rats. This is a unique study wherein we have used 24-month-old rats and monitored them until the end of their lifespan with and without E5 treatment. In the present investigation, the SD rats were separated into two groups old control group and the treatment group (n = 8). The treatment group received four injections of E5 every alternate day for 8 days, and eight injections every alternate day for 16 days. Body weight, grip strength, cytokines, and biochemical markers were measured for more than 400 days of the study. Clinical observation, necropsy, and histology were performed. The E5 treatment exhibited great potential by showing significantly improved grip strength, remarkably decreased pro-inflammatory markers of chronic inflammation and oxidative stress, as well as biomarkers for vital organs (BUN, SGPT, SGOT, and triglycerides), and increased anti-oxidant levels. Clinical examinations, necropsies, and histopathology revealed that the animals treated with the E5 had normal cellular structure and architecture. In conclusion, this unique 'plasma-derived exosome' treatment (E5) alone is adequate to improve the health-span and extend the lifespan of the old SD rats significantly.
Collapse
Affiliation(s)
- Kavita Singh
- Shobhaben Pratapbhai Patel School of Pharmacy & Technology ManagementSVKM's NMIMSMumbaiIndia
| | - Shraddha I. Khairnar
- Shobhaben Pratapbhai Patel School of Pharmacy & Technology ManagementSVKM's NMIMSMumbaiIndia
| | | | | | - Neha Gupta
- Shobhaben Pratapbhai Patel School of Pharmacy & Technology ManagementSVKM's NMIMSMumbaiIndia
| | - Jay Arora
- Yuvan Research Pvt LtdMountain ViewCAUSA
| | | |
Collapse
|
9
|
Wang S, Ren J, Jing Y, Qu J, Liu GH. Perspectives on biomarkers of reproductive aging for fertility and beyond. NATURE AGING 2024; 4:1697-1710. [PMID: 39672897 DOI: 10.1038/s43587-024-00770-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/01/2024] [Accepted: 10/29/2024] [Indexed: 12/15/2024]
Abstract
Reproductive aging, spanning an age-related functional decline in the female and male reproductive systems, compromises fertility and leads to a range of health complications. In this Perspective, we first introduce a comprehensive framework for biomarkers applicable in clinical settings and discuss the existing repertoire of biomarkers used in practice. These encompass functional, imaging-based and biofluid-based biomarkers, all of which reflect the physiological characteristics of reproductive aging and help to determine the reproductive biological age. Next, we delve into the molecular alterations associated with aging in the reproductive system, highlighting the gap between these changes and their potential as biomarkers. Finally, to enhance the precision and practicality of assessing reproductive aging, we suggest adopting cutting-edge technologies for identifying new biomarkers and conducting thorough validations in population studies before clinical applications. These advancements will foster improved comprehension, prognosis and treatment of subfertility, thereby increasing chances of preserving reproductive health and resilience in populations of advanced age.
Collapse
Affiliation(s)
- Si Wang
- Advanced Innovation Center for Human Brain Protection, National Clinical Research Center for Geriatric Disorders, Xuanwu Hospital, Capital Medical University, Beijing, China.
- Aging Translational Medicine Center, Beijing Municipal Geriatric Medical Research Center, Xuanwu Hospital, Capital Medical University, Beijing, China.
- Aging Biomarker Consortium, Beijing, China.
| | - Jie Ren
- Aging Biomarker Consortium, Beijing, China
- Key Laboratory of RNA Science and Engineering, China National Center for Bioinformation, Beijing, China
- Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Ying Jing
- Advanced Innovation Center for Human Brain Protection, National Clinical Research Center for Geriatric Disorders, Xuanwu Hospital, Capital Medical University, Beijing, China
- Aging Translational Medicine Center, Beijing Municipal Geriatric Medical Research Center, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Jing Qu
- Aging Biomarker Consortium, Beijing, China.
- University of Chinese Academy of Sciences, Beijing, China.
- Key Laboratory of Organ Regeneration and Reconstruction, State Key Laboratory of Membrane Biology, State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, China.
- Institute for Stem Cell and Regeneration, CAS, Beijing, China.
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing, China.
| | - Guang-Hui Liu
- Advanced Innovation Center for Human Brain Protection, National Clinical Research Center for Geriatric Disorders, Xuanwu Hospital, Capital Medical University, Beijing, China.
- Aging Biomarker Consortium, Beijing, China.
- University of Chinese Academy of Sciences, Beijing, China.
- Key Laboratory of Organ Regeneration and Reconstruction, State Key Laboratory of Membrane Biology, State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, China.
- Institute for Stem Cell and Regeneration, CAS, Beijing, China.
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing, China.
| |
Collapse
|
10
|
Tharmapalan V, Wagner W. Biomarkers for aging of blood - how transferable are they between mice and humans? Exp Hematol 2024; 140:104600. [PMID: 39128692 DOI: 10.1016/j.exphem.2024.104600] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2024] [Revised: 07/18/2024] [Accepted: 07/30/2024] [Indexed: 08/13/2024]
Abstract
Aging significantly impacts the hematopoietic system, reducing its regenerative capacity and ability to restore homeostasis after stress. Mouse models have been invaluable in studying this process due to their shorter lifespan and the ability to explore genetic, treatment, and environmental influences on aging. However, not all aspects of aging are mirrored between species. This review compares three key aging biomarkers in the hematopoietic systems of mice and humans: myeloid bias, telomere attrition, and epigenetic clocks. Myeloid bias, marked by an increased fraction of myeloid cells and decreased lymphoid cells, is a significant aging marker in mice but is scarcely observed in humans after childhood. Conversely, telomere length is a robust aging biomarker in humans, whereas mice exhibit significantly different telomere dynamics, making telomere length less reliable in the murine system. Epigenetic clocks, based on DNA methylation changes at specific genomic regions, provide precise estimates of chronologic age in both mice and humans. Notably, age-associated regions in mice and humans occur at homologous genomic locations. Epigenetic clocks, depending on the epigenetic signatures used, also capture aspects of biological aging, offering powerful tools to assess genetic and environmental impacts on aging. Taken together, not all blood aging biomarkers are transferable between mice and humans. When using murine models to extrapolate human aging, it may be advantageous to focus on aging phenomena observed in both species. In conclusion, although mouse models offer significant insights, selecting appropriate biomarkers is crucial for translating findings to human aging.
Collapse
Affiliation(s)
- Vithurithra Tharmapalan
- Institute for Stem Cell Biology, RWTH Aachen University Medical School, Aachen, Germany; Helmholtz-Institute for Biomedical Engineering, RWTH Aachen University Medical Faculty, Aachen, Germany
| | - Wolfgang Wagner
- Institute for Stem Cell Biology, RWTH Aachen University Medical School, Aachen, Germany; Helmholtz-Institute for Biomedical Engineering, RWTH Aachen University Medical Faculty, Aachen, Germany; Center for Integrated Oncology Aachen Bonn Cologne Düsseldorf (CIO ABCD), Aachen, Germany.
| |
Collapse
|
11
|
Winkler TW, Wiegrebe S, Herold JM, Stark KJ, Küchenhoff H, Heid IM. Genetic-by-age interaction analyses on complex traits in UK Biobank and their potential to identify effects on longitudinal trait change. Genome Biol 2024; 25:300. [PMID: 39609904 PMCID: PMC11606088 DOI: 10.1186/s13059-024-03439-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2023] [Accepted: 11/18/2024] [Indexed: 11/30/2024] Open
Abstract
BACKGROUND Genome-wide association studies (GWAS) have identified thousands of loci for disease-related human traits in cross-sectional data. However, the impact of age on genetic effects is underacknowledged. Also, identifying genetic effects on longitudinal trait change has been hampered by small sample sizes for longitudinal data. Such effects on deteriorating trait levels over time or disease progression can be clinically relevant. RESULTS Under certain assumptions, we demonstrate analytically that genetic-by-age interaction observed in cross-sectional data can be indicative of genetic association on longitudinal trait change. We propose a 2-stage approach with genome-wide pre-screening for genetic-by-age interaction in cross-sectional data and testing identified variants for longitudinal change in independent longitudinal data. Within UK Biobank cross-sectional data, we analyze 8 complex traits (up to 370,000 individuals). We identify 44 genetic-by-age interactions (7 loci for obesity traits, 26 for pulse pressure, few to none for lipids). Our cross-trait view reveals trait-specificity regarding the proportion of loci with age-modulated effects, which is particularly high for pulse pressure. Testing the 44 variants in longitudinal data (up to 50,000 individuals), we observe significant effects on change for obesity traits (near APOE, TMEM18, TFAP2B) and pulse pressure (near FBN1, IGFBP3; known for implication in arterial stiffness processes). CONCLUSIONS We provide analytical and empirical evidence that cross-sectional genetic-by-age interaction can help pinpoint longitudinal-change effects, when cross-sectional data surpasses longitudinal sample size. Our findings shed light on the distinction between traits that are impacted by age-dependent genetic effects and those that are not.
Collapse
Affiliation(s)
- Thomas W Winkler
- Department of Genetic Epidemiology, University of Regensburg, Franz-Josef-Strauß-Allee 11, Regensburg, 93053, Germany.
| | - Simon Wiegrebe
- Department of Genetic Epidemiology, University of Regensburg, Franz-Josef-Strauß-Allee 11, Regensburg, 93053, Germany
- Statistical Consulting Unit StaBLab, Department of Statistics, LMU Munich, Geschwister-Scholl-Platz 1, Munich, 80539, Germany
| | - Janina M Herold
- Department of Genetic Epidemiology, University of Regensburg, Franz-Josef-Strauß-Allee 11, Regensburg, 93053, Germany
| | - Klaus J Stark
- Department of Genetic Epidemiology, University of Regensburg, Franz-Josef-Strauß-Allee 11, Regensburg, 93053, Germany
| | - Helmut Küchenhoff
- Statistical Consulting Unit StaBLab, Department of Statistics, LMU Munich, Geschwister-Scholl-Platz 1, Munich, 80539, Germany
| | - Iris M Heid
- Department of Genetic Epidemiology, University of Regensburg, Franz-Josef-Strauß-Allee 11, Regensburg, 93053, Germany.
| |
Collapse
|
12
|
Castro JP. Metformin and monkeys: what can we learn about delaying aging? Lab Anim (NY) 2024:10.1038/s41684-024-01492-2. [PMID: 39609627 DOI: 10.1038/s41684-024-01492-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2024]
Affiliation(s)
- José Pedro Castro
- i3S - Instituto de Investigação e Inovação em Saúde, Universidade do Porto, Porto, Portugal.
- Aging and Aneuploidy Laboratory, IBMC - Instituto de Biologia Molecular e Celular, Universidade do Porto, Porto, Portugal.
| |
Collapse
|
13
|
Hubert DL, Arnold KR, Greenspan ZG, Pupo A, Robinson RD, Chavarin VV, Barter TB, Djukovic D, Raftery D, Vue Z, Hinton A, McReynolds MR, Harrison BR, Phillips MA. Selection for early reproduction leads to accelerated aging and extensive metabolic remodeling in Drosophila melanogaster. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.06.28.601037. [PMID: 39005259 PMCID: PMC11244849 DOI: 10.1101/2024.06.28.601037] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/16/2024]
Abstract
Experimental evolution studies that feature selection on life-history characters are a proven approach for studying the evolution of aging and variation in rates of senescence. Recently, the incorporation of genomic and transcriptomic approaches into this framework has led to the identification of hundreds of genes associated with different aging patterns. However, our understanding of the specific molecular mechanisms underlying these aging patterns remains limited. Here, we incorporated extensive metabolomic profiling into this framework to generate mechanistic insights into aging patterns in Drosophila melanogaster. Specifically, we characterized metabolomic change over adult lifespan in populations of D. melanogaster where selection for early reproduction has led to an accelerated aging phenotype relative to their controls. Using these data we: i) evaluated evolutionary repeatability across the metabolome; ii) assessed the value of the metabolome as a predictor of "biological age" in this system; and iii) identified specific metabolites associated with accelerated aging. Generally, our findings suggest that selection for early reproduction resulted in highly repeatable alterations to the metabolome and the metabolome itself is a reliable predictor of "biological age". Specifically, we find clusters of metabolites that are associated with the different rates of senescence observed between our accelerated aging population and their controls, adding new insights into the metabolites that may be driving the accelerated aging phenotype.
Collapse
Affiliation(s)
| | - Kenneth R. Arnold
- Department of Ecology and Evolutionary Biology, University of California, Irvine
| | - Zachary G. Greenspan
- Department of Ecology and Evolutionary Biology, University of California, Irvine
| | - Anastasia Pupo
- Department of Ecology and Evolutionary Biology, University of California, Irvine
| | - Ryan D. Robinson
- Department of Ecology and Evolutionary Biology, University of California, Irvine
| | - Valeria V. Chavarin
- Department of Ecology and Evolutionary Biology, University of California, Irvine
| | | | - Danijel Djukovic
- Northwest Metabolomics Research Center, Department of Anesthesiology and Pain Medicine, University of Washington
| | - Daniel Raftery
- Northwest Metabolomics Research Center, Department of Anesthesiology and Pain Medicine, University of Washington
| | - Zer Vue
- Department of Molecular Physiology and Biophysics, Vanderbilt University, Nashville, TN, 37232, USA
| | - Antentor Hinton
- Department of Molecular Physiology and Biophysics, Vanderbilt University, Nashville, TN, 37232, USA
| | - Melanie R. McReynolds
- Department of Biochemistry and Molecular Biology, The Huck Institutes of the Life Sciences Pennsylvania State University, University Park, PA 16802
| | | | | |
Collapse
|
14
|
Levy JJ, Diallo AB, Saldias Montivero MK, Gabbita S, Salas LA, Christensen BC. Insights to aging prediction with AI based epigenetic clocks. Epigenomics 2024:1-9. [PMID: 39584810 DOI: 10.1080/17501911.2024.2432854] [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: 07/19/2024] [Accepted: 11/15/2024] [Indexed: 11/26/2024] Open
Abstract
Over the past century, human lifespan has increased remarkably, yet the inevitability of aging persists. The disparity between biological age, which reflects pathological deterioration and disease, and chronological age, indicative of normal aging, has driven prior research focused on identifying mechanisms that could inform interventions to reverse excessive age-related deterioration and reduce morbidity and mortality. DNA methylation has emerged as an important predictor of age, leading to the development of epigenetic clocks that quantify the extent of pathological deterioration beyond what is typically expected for a given age. Machine learning technologies offer promising avenues to enhance our understanding of the biological mechanisms governing aging by further elucidating the gap between biological and chronological ages. This perspective article examines current algorithmic approaches to epigenetic clocks, explores the use of machine learning for age estimation from DNA methylation, and discusses how refining the interpretation of ML methods and tailoring their inferences for specific patient populations and cell types can amplify the utility of these technologies in age prediction. By harnessing insights from machine learning, we are well-positioned to effectively adapt, customize and personalize interventions aimed at aging.
Collapse
Affiliation(s)
- Joshua J Levy
- Department of Pathology and Laboratory Medicine, Cedars Sinai Medical Center, Los Angeles, CA, USA
- Department of Computational Biomedicine, Cedars Sinai Medical Center, Los Angeles, CA, USA
- Emerging Diagnostic and Investigative Technologies, Department of Pathology and Laboratory Medicine, Dartmouth Health, Lebanon, NH, USA
- Department of Dermatology, Dartmouth Health, Lebanon, NH, USA
- Department of Epidemiology, Dartmouth College Geisel School of Medicine, Hanover, NH, USA
| | - Alos B Diallo
- Program in Quantitative Biomedical Sciences, Dartmouth College Geisel School of Medicine, Hanover, NH, USA
| | | | - Sameer Gabbita
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA
| | - Lucas A Salas
- Department of Epidemiology, Dartmouth College Geisel School of Medicine, Hanover, NH, USA
- Integrative Neuroscience at Dartmouth, Guarini School of Graduate and Advanced Studies at Dartmouth College, Hanover, NH, USA
| | - Brock C Christensen
- Department of Epidemiology, Dartmouth College Geisel School of Medicine, Hanover, NH, USA
- Molecular and Cellular Biology Program, Guarini School of Graduate and Advanced Studies, Hanover, NH, USA
| |
Collapse
|
15
|
Olova NN. Epigenetic rejuvenation: a journey backwards towards an epigenomic ground state. Epigenomics 2024:1-3. [PMID: 39584805 DOI: 10.1080/17501911.2024.2432851] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2024] [Accepted: 11/15/2024] [Indexed: 11/26/2024] Open
Affiliation(s)
- Nelly N Olova
- MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
- Institute of Ecology and Evolution, School of Biological Sciences, University of Edinburgh, Edinburgh, UK
- Institute of Biodiversity, Animal Health and Comparative Medicine, School of Biodiversity, One Health and Veterinary Medicine, University of Glasgow, Glasgow, UK
| |
Collapse
|
16
|
Mannucci A, Goel A. Stool and blood biomarkers for colorectal cancer management: an update on screening and disease monitoring. Mol Cancer 2024; 23:259. [PMID: 39558327 PMCID: PMC11575410 DOI: 10.1186/s12943-024-02174-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2024] [Accepted: 11/07/2024] [Indexed: 11/20/2024] Open
Abstract
BACKGROUND Biomarkers have revolutionized the management of colorectal cancer (CRC), facilitating early detection, prevention, personalized treatment, and minimal residual disease (MRD) monitoring. This review explores current CRC screening strategies and emerging biomarker applications. MAIN BODY We summarize the landscape of non-invasive CRC screening and MRD detection strategies, discuss the limitations of the current approaches, and highlight the promising potential of novel biomarker solutions. The fecal immunochemical test remained the cornerstone of CRC screening, but its sensitivity has been improved by assays that combined its performance with other stool analytes. However, their sensitivity for advanced adenomas and the patient compliance both remain suboptimal. Blood-based tests promise to increase compliance but require further refinement to compete with stool-based biomarker tests. The ideal scenario involves leveraging blood tests to increase screening participation, and simultaneously promote stool- and endoscopy-based screening among those who are compliant. Once solely reliant on upfront surgery followed by stage and pathology-driven adjuvant chemotherapy, the treatment of stage II and III colon cancer has undergone a revolutionary transformation with the advent of MRD testing after surgery. A decade ago, the concept of using a post-surgical test instead of stage and pathology to determine the need for adjuvant chemotherapy was disruptive. Today, a blood test may be more informative of the need for chemotherapy than the stage at diagnosis. CONCLUSION Biomarker research is not just improving, but bringing a transformative change to CRC clinical management. Early detection is not just getting better, but improving thanks to a multi-modality approach, and personalized treatment plans are not just becoming a reality, but a promising future with MRD testing.
Collapse
Affiliation(s)
- Alessandro Mannucci
- Department of Molecular Diagnostics and Experimental Therapeutics, Beckman Research Institute at City of Hope, Monrovia, CA, USA
- Gastroenterology and Gastrointestinal Endoscopy Unit, Vita-Salute San Raffaele University, IRCCS San Raffaele Hospital, Milan, Italy
| | - Ajay Goel
- Department of Molecular Diagnostics and Experimental Therapeutics, Beckman Research Institute at City of Hope, Monrovia, CA, USA.
- City of Hope Comprehensive Cancer Center, Duarte, CA, USA.
| |
Collapse
|
17
|
Frasca D, Romero M, Blomberg BB. Similarities in B Cell Defects between Aging and Obesity. JOURNAL OF IMMUNOLOGY (BALTIMORE, MD. : 1950) 2024; 213:1407-1413. [PMID: 39495900 DOI: 10.4049/jimmunol.2300670] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/11/2023] [Accepted: 09/16/2024] [Indexed: 11/06/2024]
Abstract
The aging population is increasing worldwide, and there is also an increase in the aging population living with overweight and obesity, due to changes in lifestyle and in dietary patterns that elderly individuals experience later in life. Both aging and obesity are conditions of accelerated metabolic dysfunction and dysregulated immune responses. In this review, we summarize published findings showing that obesity induces changes in humoral immunity similar to those induced by aging and that the age-associated B cell defects are mainly due to metabolic changes. We discuss the role of the obese adipose tissue in inducing dysfunctional humoral responses and autoimmune Ab secretion.
Collapse
Affiliation(s)
- Daniela Frasca
- Department of Microbiology and Immunology, University of Miami Miller School of Medicine, Miami, FL
- Sylvester Comprehensive Cancer Center, University of Miami Miller School of Medicine, Miami, FL
| | - Maria Romero
- Department of Microbiology and Immunology, University of Miami Miller School of Medicine, Miami, FL
| | - Bonnie B Blomberg
- Department of Microbiology and Immunology, University of Miami Miller School of Medicine, Miami, FL
- Sylvester Comprehensive Cancer Center, University of Miami Miller School of Medicine, Miami, FL
| |
Collapse
|
18
|
Hille M, Kühn S, Kempermann G, Bonhoeffer T, Lindenberger U. From animal models to human individuality: Integrative approaches to the study of brain plasticity. Neuron 2024; 112:3522-3541. [PMID: 39461332 DOI: 10.1016/j.neuron.2024.10.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2024] [Revised: 06/02/2024] [Accepted: 10/04/2024] [Indexed: 10/29/2024]
Abstract
Plasticity allows organisms to form lasting adaptive changes in neural structures in response to interactions with the environment. It serves both species-general functions and individualized skill acquisition. To better understand human plasticity, we need to strengthen the dialogue between human research and animal models. Therefore, we propose to (1) enhance the interpretability of macroscopic methods used in human research by complementing molecular and fine-structural measures used in animals with such macroscopic methods, preferably applied to the same animals, to create macroscopic metrics common to both examined species; (2) launch dedicated cross-species research programs, using either well-controlled experimental paradigms, such as motor skill acquisition, or more naturalistic environments, where individuals of either species are observed in their habitats; and (3) develop conceptual and computational models linking molecular and fine-structural events to phenomena accessible by macroscopic methods. In concert, these three component strategies can foster new insights into the nature of plastic change.
Collapse
Affiliation(s)
- Maike Hille
- Center for Lifespan Psychology, Max Planck Institute for Human Development, Berlin, Germany; Center for Environmental Neuroscience, Max Planck Institute for Human Development, Berlin, Germany.
| | - Simone Kühn
- Center for Environmental Neuroscience, Max Planck Institute for Human Development, Berlin, Germany; Clinic and Policlinic for Psychiatry and Psychotherapy, University Clinic Hamburg-Eppendorf, Hamburg, Germany; Max Planck UCL Centre for Computational Psychiatry and Ageing Research, Berlin, Germany, and London, UK
| | - Gerd Kempermann
- German Center for Neurodegenerative Diseases (DZNE), Dresden, Germany; CRTD - Center for Regenerative Therapies Dresden, TU Dresden, Dresden, Germany
| | - Tobias Bonhoeffer
- Synapses-Circuits-Plasticity, Max Planck Institute for Biological Intelligence, Martinsried, Germany
| | - Ulman Lindenberger
- Center for Lifespan Psychology, Max Planck Institute for Human Development, Berlin, Germany; Max Planck UCL Centre for Computational Psychiatry and Ageing Research, Berlin, Germany, and London, UK.
| |
Collapse
|
19
|
Hao Y, Han K, Wang T, Yu J, Ding H, Dao F. Exploring the potential of epigenetic clocks in aging research. Methods 2024; 231:37-44. [PMID: 39251102 DOI: 10.1016/j.ymeth.2024.09.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2024] [Revised: 07/26/2024] [Accepted: 09/01/2024] [Indexed: 09/11/2024] Open
Abstract
The process of aging is a notable risk factor for numerous age-related illnesses. Hence, a reliable technique for evaluating biological age or the pace of aging is crucial for understanding the aging process and its influence on the progression of disease. Epigenetic alterations are recognized as a prominent biomarker of aging, and epigenetic clocks formulated on this basis have been shown to provide precise estimations of chronological age. Extensive research has validated the effectiveness of epigenetic clocks in determining aging rates, identifying risk factors for aging, evaluating the impact of anti-aging interventions, and predicting the emergence of age-related diseases. This review provides a detailed overview of the theoretical principles underlying the development of epigenetic clocks and their utility in aging research. Furthermore, it explores the existing obstacles and possibilities linked to epigenetic clocks and proposes potential avenues for future studies in this field.
Collapse
Affiliation(s)
- Yuduo Hao
- Center for Informational Biology, University of Electronic Science and Technology of China, Chengdu 610054, China
| | - Kaiyuan Han
- Center for Informational Biology, University of Electronic Science and Technology of China, Chengdu 610054, China
| | - Ting Wang
- Center for Informational Biology, University of Electronic Science and Technology of China, Chengdu 610054, China
| | - Junwen Yu
- Center for Informational Biology, University of Electronic Science and Technology of China, Chengdu 610054, China
| | - Hui Ding
- Center for Informational Biology, University of Electronic Science and Technology of China, Chengdu 610054, China.
| | - Fuying Dao
- School of Biological Sciences, Nanyang Technological University, Singapore 639798, Singapore.
| |
Collapse
|
20
|
Yang Y, Lu X, Liu N, Ma S, Zhang H, Zhang Z, Yang K, Jiang M, Zheng Z, Qiao Y, Hu Q, Huang Y, Zhang Y, Xiong M, Liu L, Jiang X, Reddy P, Dong X, Xu F, Wang Q, Zhao Q, Lei J, Sun S, Jing Y, Li J, Cai Y, Fan Y, Yan K, Jing Y, Haghani A, Xing M, Zhang X, Zhu G, Song W, Horvath S, Rodriguez Esteban C, Song M, Wang S, Zhao G, Li W, Izpisua Belmonte JC, Qu J, Zhang W, Liu GH. Metformin decelerates aging clock in male monkeys. Cell 2024; 187:6358-6378.e29. [PMID: 39270656 DOI: 10.1016/j.cell.2024.08.021] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2024] [Revised: 07/10/2024] [Accepted: 08/12/2024] [Indexed: 09/15/2024]
Abstract
In a rigorous 40-month study, we evaluated the geroprotective effects of metformin on adult male cynomolgus monkeys, addressing a gap in primate aging research. The study encompassed a comprehensive suite of physiological, imaging, histological, and molecular evaluations, substantiating metformin's influence on delaying age-related phenotypes at the organismal level. Specifically, we leveraged pan-tissue transcriptomics, DNA methylomics, plasma proteomics, and metabolomics to develop innovative monkey aging clocks and applied these to gauge metformin's effects on aging. The results highlighted a significant slowing of aging indicators, notably a roughly 6-year regression in brain aging. Metformin exerts a substantial neuroprotective effect, preserving brain structure and enhancing cognitive ability. The geroprotective effects on primate neurons were partially mediated by the activation of Nrf2, a transcription factor with anti-oxidative capabilities. Our research pioneers the systemic reduction of multi-dimensional biological age in primates through metformin, paving the way for advancing pharmaceutical strategies against human aging.
Collapse
Affiliation(s)
- Yuanhan Yang
- Key Laboratory of Organ Regeneration and Reconstruction, State Key Laboratory of Membrane Biology, State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing 100101, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Xiaoyong Lu
- China National Center for Bioinformation, Beijing, China; Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Ning Liu
- State Key Laboratory of Brain and Cognitive Science, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China; College of Life Sciences, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Shuai Ma
- Key Laboratory of Organ Regeneration and Reconstruction, State Key Laboratory of Membrane Biology, State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing 100101, China; Institute for Stem Cell and Regeneration, CAS, Beijing 100101, China; Beijing Institute for Stem Cell and Regenerative Medicine, Beijing 100101, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Hui Zhang
- Key Laboratory of Organ Regeneration and Reconstruction, State Key Laboratory of Membrane Biology, State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing 100101, China; University of Chinese Academy of Sciences, Beijing 100049, China; Beijing Institute of Heart, Lung and Blood Vessel Diseases, Beijing Anzhen Hospital, Capital Medical University, Beijing 100029, China
| | - Zhiyi Zhang
- State Key Laboratory of Brain and Cognitive Science, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China
| | - Kuan Yang
- China National Center for Bioinformation, Beijing, China; Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Mengmeng Jiang
- Key Laboratory of Organ Regeneration and Reconstruction, State Key Laboratory of Membrane Biology, State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing 100101, China; Institute for Stem Cell and Regeneration, CAS, Beijing 100101, China; Beijing Institute for Stem Cell and Regenerative Medicine, Beijing 100101, China
| | - Zikai Zheng
- China National Center for Bioinformation, Beijing, China; Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Yicheng Qiao
- State Key Laboratory of Brain and Cognitive Science, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China; College of Life Sciences, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Qinchao Hu
- Key Laboratory of Organ Regeneration and Reconstruction, State Key Laboratory of Membrane Biology, State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing 100101, China; Hospital of Stomatology, Guanghua School of Stomatology, Guangdong Provincial Key Laboratory of Stomatology, Sun Yat-Sen University, Guangzhou 510060, China
| | - Ying Huang
- Chongqing Fifth People's Hospital, Chongqing 400060, China
| | - Yiyuan Zhang
- Key Laboratory of Organ Regeneration and Reconstruction, State Key Laboratory of Membrane Biology, State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing 100101, China; Institute for Stem Cell and Regeneration, CAS, Beijing 100101, China; Beijing Institute for Stem Cell and Regenerative Medicine, Beijing 100101, China
| | - Muzhao Xiong
- China National Center for Bioinformation, Beijing, China; Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Lixiao Liu
- China National Center for Bioinformation, Beijing, China; Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Xiaoyu Jiang
- Key Laboratory of Organ Regeneration and Reconstruction, State Key Laboratory of Membrane Biology, State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing 100101, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Pradeep Reddy
- Altos Labs San Diego Institute of Science, San Diego, CA, USA
| | - Xueda Dong
- State Key Laboratory of Brain and Cognitive Science, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China; Sino-Danish College, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Fanshu Xu
- State Key Laboratory of Brain and Cognitive Science, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China; College of Life Sciences, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Qiaoran Wang
- China National Center for Bioinformation, Beijing, China; Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Qian Zhao
- National Clinical Research Center for Geriatric Disorders, Aging Translational Medicine Center, International Center for Aging and Cancer, Xuanwu Hospital Capital Medical University, Beijing 100053, China
| | - Jinghui Lei
- National Clinical Research Center for Geriatric Disorders, Aging Translational Medicine Center, International Center for Aging and Cancer, Xuanwu Hospital Capital Medical University, Beijing 100053, China
| | - Shuhui Sun
- Beijing Institute of Heart, Lung and Blood Vessel Diseases, Beijing Anzhen Hospital, Capital Medical University, Beijing 100029, China
| | - Ying Jing
- National Clinical Research Center for Geriatric Disorders, Aging Translational Medicine Center, International Center for Aging and Cancer, Xuanwu Hospital Capital Medical University, Beijing 100053, China
| | - Jingyi Li
- Key Laboratory of Organ Regeneration and Reconstruction, State Key Laboratory of Membrane Biology, State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing 100101, China; Institute for Stem Cell and Regeneration, CAS, Beijing 100101, China; Beijing Institute for Stem Cell and Regenerative Medicine, Beijing 100101, China; Aging Biomarker Consortium (ABC), Beijing 100101, China
| | - Yusheng Cai
- Key Laboratory of Organ Regeneration and Reconstruction, State Key Laboratory of Membrane Biology, State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing 100101, China; Institute for Stem Cell and Regeneration, CAS, Beijing 100101, China; Beijing Institute for Stem Cell and Regenerative Medicine, Beijing 100101, China
| | - Yanling Fan
- China National Center for Bioinformation, Beijing, China; Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing, China
| | - Kaowen Yan
- Key Laboratory of Organ Regeneration and Reconstruction, State Key Laboratory of Membrane Biology, State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing 100101, China; Institute for Stem Cell and Regeneration, CAS, Beijing 100101, China; Beijing Institute for Stem Cell and Regenerative Medicine, Beijing 100101, China
| | - Yaobin Jing
- Key Laboratory of Organ Regeneration and Reconstruction, State Key Laboratory of Membrane Biology, State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing 100101, China; Institute for Stem Cell and Regeneration, CAS, Beijing 100101, China; Beijing Institute for Stem Cell and Regenerative Medicine, Beijing 100101, China; International Center for Aging and Cancer, Hainan Medical University, Haikou 571199, China
| | - Amin Haghani
- Altos Labs San Diego Institute of Science, San Diego, CA, USA
| | - Mengen Xing
- Oujiang Laboratory, Center for Geriatric Medicine and Institute of Aging, Key Laboratory of Alzheimer's Disease of Zhejiang Province, Zhejiang Provincial Clinical Research for Mental Disorders, The First-Affiliated Hospital, Wenzhou Medical University, Wenzhou, Zhejiang 325035, China
| | - Xuan Zhang
- Department of Rheumatology, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Clinical Immunology Center, Chinese Academy of Medical Sciences, Beijing 100730, China
| | - Guodong Zhu
- Institute of Gerontology, Guangzhou Geriatric Hospital, Guangzhou Medical University, Guangzhou, China
| | - Weihong Song
- Oujiang Laboratory, Center for Geriatric Medicine and Institute of Aging, Key Laboratory of Alzheimer's Disease of Zhejiang Province, Zhejiang Provincial Clinical Research for Mental Disorders, The First-Affiliated Hospital, Wenzhou Medical University, Wenzhou, Zhejiang 325035, China
| | - Steve Horvath
- Altos Labs San Diego Institute of Science, San Diego, CA, USA
| | | | - Moshi Song
- Key Laboratory of Organ Regeneration and Reconstruction, State Key Laboratory of Membrane Biology, State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing 100101, China; Beijing Institute for Stem Cell and Regenerative Medicine, Beijing 100101, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Si Wang
- National Clinical Research Center for Geriatric Disorders, Aging Translational Medicine Center, International Center for Aging and Cancer, Xuanwu Hospital Capital Medical University, Beijing 100053, China; Aging Biomarker Consortium (ABC), Beijing 100101, China
| | - Guoguang Zhao
- Department of Neurosurgery, Xuanwu Hospital Capital Medical University, Beijing 100053, China; National Medical Center for Neurological Diseases, Beijing 100053, China; Beijing Municipal Geriatric Medical Research Center, Beijing 100053, China
| | - Wei Li
- Key Laboratory of Organ Regeneration and Reconstruction, State Key Laboratory of Membrane Biology, State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing 100101, China; Institute for Stem Cell and Regeneration, CAS, Beijing 100101, China; Beijing Institute for Stem Cell and Regenerative Medicine, Beijing 100101, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | | | - Jing Qu
- Key Laboratory of Organ Regeneration and Reconstruction, State Key Laboratory of Membrane Biology, State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing 100101, China; Institute for Stem Cell and Regeneration, CAS, Beijing 100101, China; Beijing Institute for Stem Cell and Regenerative Medicine, Beijing 100101, China; University of Chinese Academy of Sciences, Beijing 100049, China; Beijing Institute of Heart, Lung and Blood Vessel Diseases, Beijing Anzhen Hospital, Capital Medical University, Beijing 100029, China; Aging Biomarker Consortium (ABC), Beijing 100101, China.
| | - Weiqi Zhang
- China National Center for Bioinformation, Beijing, China; Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing, China; Institute for Stem Cell and Regeneration, CAS, Beijing 100101, China; Beijing Institute for Stem Cell and Regenerative Medicine, Beijing 100101, China; University of Chinese Academy of Sciences, Beijing 100049, China; Aging Biomarker Consortium (ABC), Beijing 100101, China.
| | - Guang-Hui Liu
- Key Laboratory of Organ Regeneration and Reconstruction, State Key Laboratory of Membrane Biology, State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing 100101, China; Institute for Stem Cell and Regeneration, CAS, Beijing 100101, China; Beijing Institute for Stem Cell and Regenerative Medicine, Beijing 100101, China; National Clinical Research Center for Geriatric Disorders, Aging Translational Medicine Center, International Center for Aging and Cancer, Xuanwu Hospital Capital Medical University, Beijing 100053, China; University of Chinese Academy of Sciences, Beijing 100049, China; Aging Biomarker Consortium (ABC), Beijing 100101, China.
| |
Collapse
|
21
|
Mitchell W, Pharaoh G, Tyshkovskiy A, Campbell M, Marcinek DJ, Gladyshev VN. The mitochondrial-targeted peptide therapeutic elamipretide improves cardiac and skeletal muscle function during aging without detectable changes in tissue epigenetic or transcriptomic age. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.10.30.620676. [PMID: 39554099 PMCID: PMC11565897 DOI: 10.1101/2024.10.30.620676] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 11/19/2024]
Abstract
Aging-related decreases in cardiac and skeletal muscle function are strongly associated with various comorbidities. Elamipretide (ELAM), a novel mitochondrial-targeted peptide, has demonstrated broad therapeutic efficacy in ameliorating disease conditions associated with mitochondrial dysfunction across both clinical and pre-clinical models. ELAM is proposed to restore mitochondrial bioenergetic function by stabilizing inner membrane structure and increasing oxidative phosphorylation coupling and efficiency. Although ELAM treatment effectively attenuates physiological declines in multiple tissues in rodent aging models, it remains unclear whether these functional improvements correlate with favorable changes in molecular biomarkers of aging. Herein, we investigated the impact of 8-week ELAM treatment on pre- and post- measures of C57BL/6J mice frailty, skeletal muscle, and cardiac muscle function, coupled with post-treatment assessments of biological age and affected molecular pathways. We found that health status, as measured by frailty index, cardiac strain, diastolic function, and skeletal muscle force are significantly diminished with age, with skeletal muscle force changing in a sex-dependent manner. Conversely, ELAM mitigated frailty accumulation and was able to partially reverse these declines, as evidenced by treatment-induced increases in cardiac strain and muscle fatigue resistance. Despite these improvements, we did not detect statistically significant changes in gene expression or DNA methylation profiles indicative of molecular reorganization or reduced biological age in most ELAM-treated groups. However, pathway analyses revealed that ELAM treatment showed pro-longevity shifts in gene expression such as upregulation of genes involved in fatty acid metabolism, mitochondrial translation and oxidative phosphorylation, and downregulation of inflammation. Together, these results indicate that ELAM treatment is effective at mitigating signs of sarcopenia and heart failure in an aging mouse model, but that these functional improvements occur independently of detectable changes in epigenetic and transcriptomic age. Thus, some age-related changes in function may be uncoupled from changes in molecular biological age.
Collapse
Affiliation(s)
- Wayne Mitchell
- Division of Genetics, Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA 02115 United States
| | - Gavin Pharaoh
- Department of Radiology, University of Washington, Seattle, WA 98195 United States
| | - Alexander Tyshkovskiy
- Division of Genetics, Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA 02115 United States
| | - Matthew Campbell
- Department of Radiology, University of Washington, Seattle, WA 98195 United States
| | - David J. Marcinek
- Department of Radiology, University of Washington, Seattle, WA 98195 United States
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, WA 98195 United States
| | - Vadim N. Gladyshev
- Division of Genetics, Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA 02115 United States
| |
Collapse
|
22
|
Mariner BL, McCoy BM, Greenier A, Brassington L, Slikas E, Adjangba C, Marye A, Harrison BR, Bamberger T, Algavi Y, Muller E, Harris A, Rout E, Avery A, Borenstein E, Promislow D, Snyder-Mackler N. DNA methylation of transposons pattern aging differences across a diverse cohort of dogs from the Dog Aging Project. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.10.08.617286. [PMID: 39416178 PMCID: PMC11482827 DOI: 10.1101/2024.10.08.617286] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/19/2024]
Abstract
Within a species, larger individuals often have shorter lives and higher rates of age-related disease. Despite this well-known link, we still know little about underlying age-related epigenetic differences, which could help us better understand inter-individual variation in aging and the etiology, onset, and progression of age-associated disease. Dogs exhibit this negative correlation between size, health, and longevity and thus represent an excellent system in which to test the underlying mechanisms. Here, we quantified genome-wide DNA methylation in a cohort of 864 dogs in the Dog Aging Project. Age strongly patterned the dog epigenome, with the majority (66% of age-associated loci) of regions associating age-related loss of methylation. These age effects were non-randomly distributed in the genome and differed depending on genomic context. We found the LINE1 (long interspersed elements) class of TEs (transposable elements) were the most frequently hypomethylated with age (FDR < 0.05, 40% of all LINE1 regions). This LINE1 pattern differed in magnitude across breeds of different sizes- the largest dogs lost 0.26% more LINE1 methylation per year than the smallest dogs. This suggests that epigenetic regulation of TEs, particularly LINE1s, may contribute to accelerated age and disease phenotypes within a species. Since our study focused on the methylome of immune cells, we looked at LINE1 methylation changes in golden retrievers, a breed highly susceptible to hematopoietic cancers, and found they have accelerated age-related LINE1 hypomethylation compared to other breeds. We also found many of the LINE1s hypomethylated with age are located on the X chromosome and are, when considering X chromosome inactivation, counter-intuitively more methylated in males. These results have revealed the demethylation of LINE1 transposons as a potential driver of inter-species, demographic-dependent aging variation.
Collapse
|
23
|
Gorelov R, Hochedlinger K. A cellular identity crisis? Plasticity changes during aging and rejuvenation. Genes Dev 2024; 38:823-842. [PMID: 39293862 PMCID: PMC11535162 DOI: 10.1101/gad.351728.124] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/20/2024]
Abstract
Cellular plasticity in adult multicellular organisms is a protective mechanism that allows certain tissues to regenerate in response to injury. Considering that aging involves exposure to repeated injuries over a lifetime, it is conceivable that cell identity itself is more malleable-and potentially erroneous-with age. In this review, we summarize and critically discuss the available evidence that cells undergo age-related shifts in identity, with an emphasis on those that contribute to age-associated pathologies, including neurodegeneration and cancer. Specifically, we focus on reported instances of programs associated with dedifferentiation, biased differentiation, acquisition of features from alternative lineages, and entry into a preneoplastic state. As some of the most promising approaches to rejuvenate cells reportedly also elicit transient changes to cell identity, we further discuss whether cell state change and rejuvenation can be uncoupled to yield more tractable therapeutic strategies.
Collapse
Affiliation(s)
- Rebecca Gorelov
- Department of Molecular Biology, Massachusetts General Hospital, Boston, Massachusetts 02114, USA
- Cancer Center, Massachusetts General Hospital, Boston, Massachusetts 02114, USA
- Center for Regenerative Medicine, Massachusetts General Hospital, Boston, Massachusetts 02114, USA
- Harvard Stem Cell Institute, Harvard University, Cambridge, Massachusetts 02138, USA
- Department of Genetics, Harvard Medical School, Boston, Massachusetts 02115, USA
| | - Konrad Hochedlinger
- Department of Molecular Biology, Massachusetts General Hospital, Boston, Massachusetts 02114, USA;
- Cancer Center, Massachusetts General Hospital, Boston, Massachusetts 02114, USA
- Center for Regenerative Medicine, Massachusetts General Hospital, Boston, Massachusetts 02114, USA
- Harvard Stem Cell Institute, Harvard University, Cambridge, Massachusetts 02138, USA
- Department of Genetics, Harvard Medical School, Boston, Massachusetts 02115, USA
| |
Collapse
|
24
|
van Dongen J, Breeze CE. Examining the Utility of the Mammalian Methylation Array for Pan-Mammalian Analysis of Monozygotic Twinning. EPIGENOMES 2024; 8:37. [PMID: 39449361 PMCID: PMC11503326 DOI: 10.3390/epigenomes8040037] [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: 08/25/2024] [Revised: 09/26/2024] [Accepted: 09/30/2024] [Indexed: 10/26/2024] Open
Abstract
BACKGROUND/OBJECTIVES Human identical twins are born at a rate of 3-4 per 1000 live births. Many other mammals also occasionally produce monozygotic twins, referred to as sporadic polyembryony. The underlying mechanisms are unknown. Through epigenome-wide association studies (EWAS), we identified a robust DNA methylation signature in somatic tissues from human monozygotic (MZ) twins, comprising 834 differentially methylated positions (MZ-DMPs). The results point to a connection between monozygotic twinning and early genome programming and enable new angles to study monozygotic twinning. METHODS The mammalian methylation array (MMA) measures 38,608 CpGs focusing on regions that are well-conserved across many mammalian species, allowing for pan-mammalian comparative epigenomic studies. Here, we successfully map human MZ-DMPs to probes of the mammalian methylation array across 157 mammalian genomes. RESULTS As expected, based on the modest probe overlap between Illumina 450k/EPIC and mammalian methylation array probes, only a subset of MZ-DMPs reside in conserved regions covered by the mammalian methylation array. These include probes mapping to NPAS3, KLHL35, CASZ1, and ATP2B2. Re-analysis restricting the original EWAS in humans to conserved MMA regions yielded additional MZ-DMPs, suggesting that more loci may be detected by application of the mammalian array to monozygotic twins. CONCLUSIONS In conclusion, the mammalian methylation array may prove to be a promising platform to study whether a shared DNA methylation signature of sporadic polyembryony exists across diverse mammalian species. This may potentially point to shared underlying mechanisms.
Collapse
Affiliation(s)
- Jenny van Dongen
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Van der Boechorststraat 7, 1081 BT Amsterdam, The Netherlands
- Amsterdam Reproduction and Development Institute, 1081 HV Amsterdam, The Netherlands
| | - Charles E. Breeze
- UCL Cancer Institute, University College London, 72 Huntley Street, London WC1E 6BT, UK
| | | |
Collapse
|
25
|
Ndhlovu LC, Bendall ML, Dwaraka V, Pang APS, Dopkins N, Carreras N, Smith R, Nixon DF, Corley MJ. Retro-age: A unique epigenetic biomarker of aging captured by DNA methylation states of retroelements. Aging Cell 2024; 23:e14288. [PMID: 39092674 PMCID: PMC11464121 DOI: 10.1111/acel.14288] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2024] [Revised: 07/11/2024] [Accepted: 07/16/2024] [Indexed: 08/04/2024] Open
Abstract
Reactivation of retroelements in the human genome has been linked to aging. However, whether the epigenetic state of specific retroelements can predict chronological age remains unknown. We provide evidence that locus-specific retroelement DNA methylation can be used to create retroelement-based epigenetic clocks that accurately measure chronological age in the immune system, across human tissues, and pan-mammalian species. We also developed a highly accurate retroelement epigenetic clock compatible with EPICv.2.0 data that was constructed from CpGs that did not overlap with existing first- and second-generation epigenetic clocks, suggesting a unique signal for epigenetic clocks not previously captured. We found retroelement-based epigenetic clocks were reversed during transient epigenetic reprogramming, accelerated in people living with HIV-1, and responsive to antiretroviral therapy. Our findings highlight the utility of retroelement-based biomarkers of aging and support a renewed emphasis on the role of retroelements in geroscience.
Collapse
Affiliation(s)
- Lishomwa C. Ndhlovu
- Department of Medicine, Division of Infectious DiseasesWeill Cornell MedicineNew YorkNew York CityUSA
| | - Matthew L. Bendall
- Department of Medicine, Division of Infectious DiseasesWeill Cornell MedicineNew YorkNew York CityUSA
| | | | - Alina P. S. Pang
- Department of Medicine, Division of Infectious DiseasesWeill Cornell MedicineNew YorkNew York CityUSA
| | - Nicholas Dopkins
- Department of Medicine, Division of Infectious DiseasesWeill Cornell MedicineNew YorkNew York CityUSA
| | | | | | - Douglas F. Nixon
- Department of Medicine, Division of Infectious DiseasesWeill Cornell MedicineNew YorkNew York CityUSA
| | - Michael J. Corley
- Department of Medicine, Division of Infectious DiseasesWeill Cornell MedicineNew YorkNew York CityUSA
| |
Collapse
|
26
|
Fritz García JHG, Keller Valsecchi CI, Basilicata MF. Sex as a biological variable in ageing: insights and perspectives on the molecular and cellular hallmarks. Open Biol 2024; 14:240177. [PMID: 39471841 PMCID: PMC11521605 DOI: 10.1098/rsob.240177] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/25/2024] [Revised: 08/28/2024] [Accepted: 09/05/2024] [Indexed: 11/01/2024] Open
Abstract
Sex-specific differences in lifespan and ageing are observed in various species. In humans, women generally live longer but are frailer and suffer from different age-related diseases compared to men. The hallmarks of ageing, such as genomic instability, telomere attrition or loss of proteostasis, exhibit sex-specific patterns. Sex chromosomes and sex hormones, as well as the epigenetic regulation of the inactive X chromosome, have been shown to affect lifespan and age-related diseases. Here we review the current knowledge on the biological basis of sex-biased ageing. While our review is focused on humans, we also discuss examples of model organisms such as the mouse, fruit fly or the killifish. Understanding these molecular differences is crucial as the elderly population is expected to double worldwide by 2050, making sex-specific approaches in the diagnosis, treatment, therapeutic development and prevention of age-related diseases a pressing need.
Collapse
Affiliation(s)
| | | | - M. Felicia Basilicata
- Institute of Molecular Biology (IMB), Mainz, Germany
- University Medical Center (UMC), Mainz, Germany
| |
Collapse
|
27
|
Roman L, Mayne B, Anderson C, Kim Y, O'Dwyer T, Carlile N. A novel technique for estimating age and demography of long-lived seabirds (genus Pterodroma) using an epigenetic clock for Gould's petrel (Pterodroma leucoptera). Mol Ecol Resour 2024; 24:e14003. [PMID: 39075891 DOI: 10.1111/1755-0998.14003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2024] [Revised: 06/28/2024] [Accepted: 07/18/2024] [Indexed: 07/31/2024]
Abstract
Understanding the demography of wildlife populations is a key component for ecological research, and where necessary, supporting the conservation and management of long-lived animals. However, many animals lack phenological changes with which to determine individual age; therefore, gathering this fundamental information presents difficulties. More so for species that are rare, highly mobile, migratory and those that reside in inaccessible habitats. Until recently, the primary method to measure demography is through labour intensive mark-recapture approaches, necessitating decades of effort for long-lived species. Gadfly petrels (genus: Pterodroma) are one such taxa that are overrepresented with threatened and declining species, and for which numerous aspects of their ecology present challenges for research, monitoring and recovery efforts. To overcome some of these challenges, we developed the first DNA methylation (DNAm) demography technique to estimate the age of petrels, using the epigenetic clock of Gould's petrels (Pterodroma leucoptera). We collected reference blood samples from known-aged Gould's petrels at a long-term monitored population on Cabbage Tree Island, Australia. Epigenetic ages were successfully estimated for 121 individuals ranging in age from zero (fledgling) to 30 years of age, showing a mean error of 2.24 ± 0.17 years between the estimated and real age across the population. This is the first development of an epigenetic clock using multiplex PCR sequencing in a bird. This method enables demography to be measured with relative accuracy in a single sampling trip. This technique can provide information for emerging demographic risks that can mask declines in long-lived seabird populations and be applied to other Pterodroma populations.
Collapse
Affiliation(s)
- Lauren Roman
- Institute for Marine and Antarctic Studies, University of Tasmania, Battery Point, Hobart, Tasmania, Australia
- Commonwealth Scientific and Industrial Research Organisation (CSIRO) Environment, Battery Point, Hobart, Tasmania, Australia
| | - Benjamin Mayne
- Environomics Future Science Platform, Commonwealth Scientific and Industrial Research Organisation (CSIRO), Indian Ocean Marine Research Centre, Crawley, Western Australia, Australia
| | - Chloe Anderson
- Environomics Future Science Platform, Commonwealth Scientific and Industrial Research Organisation (CSIRO), Indian Ocean Marine Research Centre, Crawley, Western Australia, Australia
| | - Yuna Kim
- Dr Kim's Conservation Solutions, Sydney, New South Wales, Australia
| | | | - Nicholas Carlile
- Department of Climate Change, Energy, The Environment and Water, Parramatta, New South Wales, Australia
| |
Collapse
|
28
|
Ying K, Tyshkovskiy A, Chen Q, Latorre-Crespo E, Zhang B, Liu H, Matei-Dediu B, Poganik JR, Moqri M, Kirschne K, Lasky-Su J, Gladyshev VN. High-dimensional Ageome Representations of Biological Aging across Functional Modules. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.09.17.613599. [PMID: 39345525 PMCID: PMC11429788 DOI: 10.1101/2024.09.17.613599] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 10/01/2024]
Abstract
The aging process involves numerous molecular changes that lead to functional decline and increased disease and mortality risk. While epigenetic aging clocks have shown accuracy in predicting biological age, they typically provide single estimates for the samples and lack mechanistic insights. In this study, we challenge the paradigm that aging can be sufficiently described with a single biological age estimate. We describe Ageome, a computational framework for measuring the epigenetic age of thousands of molecular pathways simultaneously in mice and humans. Ageome is based on the premise that an organism's overall biological age can be approximated by the collective ages of its functional modules, which may age at different rates and have different biological ages. We show that, unlike conventional clocks, Ageome provides a high-dimensional representation of biological aging across cellular functions, enabling comprehensive assessment of aging dynamics within an individual, in a population, and across species. Application of Ageome to longevity intervention models revealed distinct patterns of pathway-specific age deceleration. Notably, cell reprogramming, while rejuvenating cells, also accelerated aging of some functional modules. When applied to human cohorts, Ageome demonstrated heterogeneity in predictive power for mortality risk, and some modules showed better performance in predicting the onset of age-related diseases, especially cancer, compared to existing clocks. Together, the Ageome framework offers a comprehensive and interpretable approach for assessing aging, providing insights into mechanisms and targets for intervention.
Collapse
Affiliation(s)
- Kejun Ying
- Division of Genetics, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
- T. H. Chan School of Public Health, Harvard University, Boston, MA, USA
| | - Alexander Tyshkovskiy
- Division of Genetics, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
| | - Qingwen Chen
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
| | | | - Bohan Zhang
- Division of Genetics, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
| | - Hanna Liu
- Division of Genetics, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
- Department of Pharmacy, Massachusetts General Hospital, Boston, MA, USA
| | - Benyamin Matei-Dediu
- Division of Genetics, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
| | - Jesse R. Poganik
- Division of Genetics, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
| | - Mahdi Moqri
- Division of Genetics, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
- Department of Genetics, Stanford University, Stanford, CA, USA
| | - Kristina Kirschne
- School of Cancer Sciences, University of Glasgow, Glasgow, UK
- Mayo Clinic, Rochester, MN, USA
| | - Jessica Lasky-Su
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
| | - Vadim N. Gladyshev
- Division of Genetics, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
| |
Collapse
|
29
|
Cao M, Zhang X. DNA Adductomics: A Narrative Review of Its Development, Applications, and Future. Biomolecules 2024; 14:1173. [PMID: 39334939 PMCID: PMC11430648 DOI: 10.3390/biom14091173] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2024] [Revised: 08/24/2024] [Accepted: 09/10/2024] [Indexed: 09/30/2024] Open
Abstract
DNA adductomics is the global study of all DNA adducts and was first proposed in 2006 by the Matsuda group. Its development has been greatly credited to the advances in mass spectrometric techniques, particularly tandem and multiple-stage mass spectrometry. In fact, liquid chromatography-mass spectrometry (LC-MS)-based methods are virtually the sole technique with practicality for DNA adductomic studies to date. At present, DNA adductomics is primarily used as a tool to search for DNA adducts, known and unknown, providing evidence for exposure to exogenous genotoxins and/or for the molecular mechanisms of their genotoxicity. Some DNA adducts discovered in this way have the potential to predict cancer risks and/or to be associated with adverse health outcomes. DNA adductomics has been successfully used to identify and determine exogenous carcinogens that may contribute to the etiology of certain cancers, including bacterial genotoxins and an N-nitrosamine. Also using the DNA adductomic approach, multiple DNA adducts have been observed to show age dependence and may serve as aging biomarkers. These achievements highlight the capability and power of DNA adductomics in the studies of medicine, biological science, and environmental science. Nonetheless, DNA adductomics is still in its infancy, and great advances are expected in the future.
Collapse
Affiliation(s)
- Mengqiu Cao
- School of Public Health, Hongqiao International Institute of Medicine, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
| | - Xinyu Zhang
- School of Public Health, Hongqiao International Institute of Medicine, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
| |
Collapse
|
30
|
Horvath S, Zhang J, Haghani A, Lu AT, Fei Z. Fundamental equations linking methylation dynamics to maximum lifespan in mammals. Nat Commun 2024; 15:8093. [PMID: 39285199 PMCID: PMC11405513 DOI: 10.1038/s41467-024-51855-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2023] [Accepted: 08/20/2024] [Indexed: 09/22/2024] Open
Abstract
We describe a framework that addresses concern that the rate of change in any aging biomarker displays a trivial inverse relation with maximum lifespan. We apply this framework to methylation data from the Mammalian Methylation Consortium. We study the relationship of lifespan with the average rate of change in methylation (AROCM) from two datasets: one with 90 dog breeds and the other with 125 mammalian species. After examining 54 chromatin states, we conclude three key findings: First, a reciprocal relationship exists between the AROCM in bivalent promoter regions and maximum mammalian lifespan: AROCM ∝ 1/MaxLifespan. Second, the correlation between average methylation and age bears no relation to maximum lifespan, Cor(Methyl,Age) ⊥ MaxLifespan. Third, the rate of methylation change in young animals is related to that in old animals: Young animals' AROCM ∝ Old AROCM. These findings critically hinge on the chromatin context, as different results emerge in other chromatin contexts.
Collapse
Affiliation(s)
- Steve Horvath
- Department of Human Genetics, University of California, Los Angeles, CA, USA.
- Department of Biostatistics, University of California, Los Angeles, CA, USA.
- Altos Labs, San Diego, CA, USA.
| | - Joshua Zhang
- Department of Human Genetics, University of California, Los Angeles, CA, USA
| | - Amin Haghani
- Department of Human Genetics, University of California, Los Angeles, CA, USA
- Altos Labs, San Diego, CA, USA
| | - Ake T Lu
- Department of Human Genetics, University of California, Los Angeles, CA, USA
- Altos Labs, San Diego, CA, USA
| | - Zhe Fei
- Department of Statistics, University of California, Riverside, CA, USA.
| |
Collapse
|
31
|
Belenguer Á, Naya-Català F, Calduch-Giner JÀ, Pérez-Sánchez J. Exploring Multifunctional Markers of Biological Age in Farmed Gilthead Sea Bream ( Sparus aurata): A Transcriptomic and Epigenetic Interplay for an Improved Fish Welfare Assessment Approach. Int J Mol Sci 2024; 25:9836. [PMID: 39337324 PMCID: PMC11432111 DOI: 10.3390/ijms25189836] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2024] [Revised: 09/05/2024] [Accepted: 09/10/2024] [Indexed: 09/30/2024] Open
Abstract
DNA methylation clocks provide information not only about chronological but also biological age, offering a high-resolution and precise understanding of age-related pathology and physiology. Attempts based on transcriptomic and epigenetic approaches arise as integrative biomarkers linking the quantification of stress responses with specific fitness traits and may help identify biological age markers, which are also considered welfare indicators. In gilthead sea bream, targeted gene expression and DNA methylation analyses in white skeletal muscle proved sirt1 as a reliable marker of age-mediated changes in energy metabolism. To complete the list of welfare auditing biomarkers, wide analyses of gene expression and DNA methylation in one- and three-year-old fish were combined. After discriminant analysis, 668 differentially expressed transcripts were matched with those containing differentially methylated (DM) regions (14,366), and 172 were overlapping. Through enrichment analyses and selection, two sets of genes were retained: 33 showing an opposite trend for DNA methylation and expression, and 57 down-regulated and hypo-methylated. The first set displayed an apparently more reproducible and reliable pattern and 10 multifunctional genes with DM CpG in regulatory regions (sirt1, smad1, ramp1, psmd2-up-regulated; col5a1, calcrl, bmp1, thrb, spred2, atp1a2-down-regulated) were deemed candidate biological age markers for improved welfare auditing in gilthead sea bream.
Collapse
Affiliation(s)
- Álvaro Belenguer
- Instituto de Acuicultura Torre de la Sal (IATS, CSIC), 12595 Ribera de Cabanes, Castellón, Spain
| | - Fernando Naya-Català
- Instituto de Acuicultura Torre de la Sal (IATS, CSIC), 12595 Ribera de Cabanes, Castellón, Spain
| | | | - Jaume Pérez-Sánchez
- Instituto de Acuicultura Torre de la Sal (IATS, CSIC), 12595 Ribera de Cabanes, Castellón, Spain
| |
Collapse
|
32
|
Gorelov R, Weiner A, Huebner A, Yagi M, Haghani A, Brooke R, Horvath S, Hochedlinger K. Dissecting the impact of differentiation stage, replicative history, and cell type composition on epigenetic clocks. Stem Cell Reports 2024; 19:1242-1254. [PMID: 39178844 PMCID: PMC11411293 DOI: 10.1016/j.stemcr.2024.07.009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2023] [Revised: 07/22/2024] [Accepted: 07/23/2024] [Indexed: 08/26/2024] Open
Abstract
Epigenetic clocks, built on DNA methylation patterns of bulk tissues, are powerful age predictors, but their biological basis remains incompletely understood. Here, we conducted a comparative analysis of epigenetic age in murine muscle, epithelial, and blood cell types across lifespan. Strikingly, our results show that cellular subpopulations within these tissues, including adult stem and progenitor cells as well as their differentiated progeny, exhibit different epigenetic ages. Accordingly, we experimentally demonstrate that clocks can be skewed by age-associated changes in tissue composition. Mechanistically, we provide evidence that the observed variation in epigenetic age among adult stem cells correlates with their proliferative state, and, fittingly, forced proliferation of stem cells leads to increases in epigenetic age. Collectively, our analyses elucidate the impact of cell type composition, differentiation state, and replicative potential on epigenetic age, which has implications for the interpretation of existing clocks and should inform the development of more sensitive clocks.
Collapse
Affiliation(s)
- Rebecca Gorelov
- Massachusetts General Hospital Department of Molecular Biology, Boston, MA 02114, USA; Massachusetts General Hospital Cancer Center and Center for Regenerative Medicine, Boston, MA 02114, USA; Harvard Stem Cell Institute, Harvard University, Cambridge, MA 02139, USA; Department of Genetics, Harvard Medical School, Boston, MA 02115, USA
| | - Aaron Weiner
- Massachusetts General Hospital Department of Molecular Biology, Boston, MA 02114, USA; Massachusetts General Hospital Cancer Center and Center for Regenerative Medicine, Boston, MA 02114, USA; Harvard Stem Cell Institute, Harvard University, Cambridge, MA 02139, USA; Department of Genetics, Harvard Medical School, Boston, MA 02115, USA
| | - Aaron Huebner
- Massachusetts General Hospital Department of Molecular Biology, Boston, MA 02114, USA; Massachusetts General Hospital Cancer Center and Center for Regenerative Medicine, Boston, MA 02114, USA; Harvard Stem Cell Institute, Harvard University, Cambridge, MA 02139, USA; Department of Genetics, Harvard Medical School, Boston, MA 02115, USA
| | - Masaki Yagi
- Massachusetts General Hospital Department of Molecular Biology, Boston, MA 02114, USA; Massachusetts General Hospital Cancer Center and Center for Regenerative Medicine, Boston, MA 02114, USA; Harvard Stem Cell Institute, Harvard University, Cambridge, MA 02139, USA; Department of Genetics, Harvard Medical School, Boston, MA 02115, USA
| | - Amin Haghani
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA; Altos Labs, San Diego, CA 92121, USA
| | - Robert Brooke
- Epigenetic Clock Development Foundation, Torrance, CA 90502, USA
| | - Steve Horvath
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA; Altos Labs, San Diego, CA 92121, USA; Epigenetic Clock Development Foundation, Torrance, CA 90502, USA; Department of Biostatistics, School of Public Health, University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - Konrad Hochedlinger
- Massachusetts General Hospital Department of Molecular Biology, Boston, MA 02114, USA; Massachusetts General Hospital Cancer Center and Center for Regenerative Medicine, Boston, MA 02114, USA; Harvard Stem Cell Institute, Harvard University, Cambridge, MA 02139, USA; Department of Genetics, Harvard Medical School, Boston, MA 02115, USA.
| |
Collapse
|
33
|
Seale K, Teschendorff A, Reiner AP, Voisin S, Eynon N. A comprehensive map of the aging blood methylome in humans. Genome Biol 2024; 25:240. [PMID: 39242518 PMCID: PMC11378482 DOI: 10.1186/s13059-024-03381-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2024] [Accepted: 08/28/2024] [Indexed: 09/09/2024] Open
Abstract
BACKGROUND During aging, the human methylome undergoes both differential and variable shifts, accompanied by increased entropy. The distinction between variably methylated positions (VMPs) and differentially methylated positions (DMPs), their contribution to epigenetic age, and the role of cell type heterogeneity remain unclear. RESULTS We conduct a comprehensive analysis of > 32,000 human blood methylomes from 56 datasets (age range = 6-101 years). We find a significant proportion of the blood methylome that is differentially methylated with age (48% DMPs; FDR < 0.005) and variably methylated with age (37% VMPs; FDR < 0.005), with considerable overlap between the two groups (59% of DMPs are VMPs). Bivalent and Polycomb regions become increasingly methylated and divergent between individuals, while quiescent regions lose methylation more uniformly. Both chronological and biological clocks, but not pace-of-aging clocks, show a strong enrichment for CpGs undergoing both mean and variance changes during aging. The accumulation of DMPs shifting towards a methylation fraction of 50% drives the increase in entropy, smoothening the epigenetic landscape. However, approximately a quarter of DMPs exhibit anti-entropic effects, opposing this direction of change. While changes in cell type composition minimally affect DMPs, VMPs and entropy measurements are moderately sensitive to such alterations. CONCLUSION This study represents the largest investigation to date of genome-wide DNA methylation changes and aging in a single tissue, providing valuable insights into primary molecular changes relevant to chronological and biological aging.
Collapse
Affiliation(s)
- Kirsten Seale
- Institute for Health and Sport (iHeS), Victoria University, Footscray, VIC, 3011, Australia
| | - Andrew Teschendorff
- CAS Key Lab of Computational Biology, Shanghai Institute of Nutrition and Health, Chinese Academy of Sciences, Shanghai, 200031, China
- UCL Cancer Institute, University College London, London, UK
| | | | - Sarah Voisin
- Institute for Health and Sport (iHeS), Victoria University, Footscray, VIC, 3011, Australia
- Australian Regenerative Medicine Institute, Monash University, Clayton, VIC, 3800, Australia
| | - Nir Eynon
- Australian Regenerative Medicine Institute, Monash University, Clayton, VIC, 3800, Australia.
| |
Collapse
|
34
|
Yi SV. Epigenetics Research in Evolutionary Biology: Perspectives on Timescales and Mechanisms. Mol Biol Evol 2024; 41:msae170. [PMID: 39235767 PMCID: PMC11376073 DOI: 10.1093/molbev/msae170] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2024] [Revised: 08/06/2024] [Accepted: 08/08/2024] [Indexed: 09/06/2024] Open
Abstract
Epigenetics research in evolutionary biology encompasses a variety of research areas, from regulation of gene expression to inheritance of environmentally mediated phenotypes. Such divergent research foci can occasionally render the umbrella term "epigenetics" ambiguous. Here I discuss several areas of contemporary epigenetics research in the context of evolutionary biology, aiming to provide balanced views across timescales and molecular mechanisms. The importance of epigenetics in development is now being assessed in many nonmodel species. These studies not only confirm the importance of epigenetic marks in developmental processes, but also highlight the significant diversity in epigenetic regulatory mechanisms across taxa. Further, these comparative epigenomic studies have begun to show promise toward enhancing our understanding of how regulatory programs evolve. A key property of epigenetic marks is that they can be inherited along mitotic cell lineages, and epigenetic differences that occur during early development can have lasting consequences on the organismal phenotypes. Thus, epigenetic marks may play roles in short-term (within an organism's lifetime or to the next generation) adaptation and phenotypic plasticity. However, the extent to which observed epigenetic variation occurs independently of genetic influences remains uncertain, due to the widespread impact of genetics on epigenetic variation and the limited availability of comprehensive (epi)genomic resources from most species. While epigenetic marks can be inherited independently of genetic sequences in some species, there is little evidence that such "transgenerational inheritance" is a general phenomenon. Rather, molecular mechanisms of epigenetic inheritance are highly variable between species.
Collapse
Affiliation(s)
- Soojin V Yi
- Department of Ecology, Evolution and Marine Biology, University of California, Santa Barbara, Santa Barbara, CA 93106, USA
- Department of Molecular, Cellular and Developmental Biology, University of California, Santa Barbara, Santa Barbara, CA 93106, USA
- Neuroscience Research Institute, University of California, Santa Barbara, Santa Barbara, CA 93106, USA
| |
Collapse
|
35
|
Bartolomucci A, Kane AE, Gaydosh L, Razzoli M, McCoy BM, Ehninger D, Chen BH, Howlett SE, Snyder-Mackler N. Animal Models Relevant for Geroscience: Current Trends and Future Perspectives in Biomarkers, and Measures of Biological Aging. J Gerontol A Biol Sci Med Sci 2024; 79:glae135. [PMID: 39126297 PMCID: PMC11316208 DOI: 10.1093/gerona/glae135] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2023] [Indexed: 08/12/2024] Open
Abstract
For centuries, aging was considered inevitable and immutable. Geroscience provides the conceptual framework to shift this focus toward a new view that regards aging as an active biological process, and the biological age of an individual as a modifiable entity. Significant steps forward have been made toward the identification of biomarkers for and measures of biological age, yet knowledge gaps in geroscience are still numerous. Animal models of aging are the focus of this perspective, which discusses how experimental design can be optimized to inform and refine the development of translationally relevant measures and biomarkers of biological age. We provide recommendations to the field, including: the design of longitudinal studies in which subjects are deeply phenotyped via repeated multilevel behavioral/social/molecular assays; the need to consider sociobehavioral variables relevant for the species studied; and finally, the importance of assessing age of onset, severity of pathologies, and age-at-death. We highlight approaches to integrate biomarkers and measures of functional impairment using machine learning approaches designed to estimate biological age as well as to predict future health declines and mortality. We expect that advances in animal models of aging will be crucial for the future of translational geroscience but also for the next chapter of medicine.
Collapse
Affiliation(s)
- Alessandro Bartolomucci
- Department of Integrative Biology and Physiology, University of Minnesota, Minneapolis, Minnesota, USA
- Department of Medicine and Surgery, University of Parma, Parma, Italy
| | - Alice E Kane
- Institute for Systems Biology, Seattle, Washington, USA
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, Washington, USA
| | - Lauren Gaydosh
- Department of Sociology, University of Texas at Austin, Austin, Texas, USA
| | - Maria Razzoli
- Department of Integrative Biology and Physiology, University of Minnesota, Minneapolis, Minnesota, USA
| | - Brianah M McCoy
- School of Life Sciences, Arizona State University, Tempe, Arizona, USA
- Center for Evolution and Medicine, Arizona State University, Tempe, Arizona, USA
| | - Dan Ehninger
- German Center for Neurodegenerative Diseases, Bonn, Germany
| | - Brian H Chen
- California Pacific Medical Center Research Institute, Sutter Health, San Francisco, CA, 94143, USA
| | - Susan E Howlett
- Departments of Pharmacology and Medicine (Geriatric Medicine), Dalhousie University, Halifax, Nova Scotia, Canada
| | - Noah Snyder-Mackler
- School of Life Sciences, Arizona State University, Tempe, Arizona, USA
- Center for Evolution and Medicine, Arizona State University, Tempe, Arizona, USA
| |
Collapse
|
36
|
Merriell BD, Manseau M, Wilson PJ. Assessing the suitability of a one-time sampling event for close-kin mark-recapture: A caribou case study. Ecol Evol 2024; 14:e70230. [PMID: 39234160 PMCID: PMC11371883 DOI: 10.1002/ece3.70230] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2024] [Revised: 08/03/2024] [Accepted: 08/12/2024] [Indexed: 09/06/2024] Open
Abstract
Abundance estimation is frequently an objective of conservation and monitoring initiatives for threatened and other managed populations. While abundance estimation via capture-mark-recapture or spatially explicit capture-recapture is now common, such approaches are logistically challenging and expensive for species such as boreal caribou (Rangifer tarandus), which inhabit remote regions, are widely dispersed, and exist at low densities. Fortunately, the recently developed 'close-kin mark-recapture' (CKMR) framework, which uses the number of kin pairs obtained within a sample to generate an abundance estimate, eliminates the need for multiple sampling events. As a result, some caribou managers are interested in using this method to generate an abundance estimate from a single, non-invasive sampling event for caribou populations. We conducted a simulation study using realistic boreal caribou demographic rates and population sizes to assess how population size and the proportion of the population surveyed impact the accuracy and precision of single-survey CKMR-based abundance estimates. Our results indicated that abundance estimates were biased and highly imprecise when very small proportions of the population were sampled, regardless of the population size. However, the larger the population size, the smaller the required proportion of the population surveyed to generate both accurate and reasonably precise estimates. Additionally, we also present a case study in which we used the CKMR framework to generate annual female abundance estimates for a small caribou population in Jasper National Park, Alberta, Canada, from 2006 to 2015 and compared them to existing published capture-mark-recapture-based estimates. Both the accuracy and precision of the annual CKMR-based abundance estimates varied across years and were sensitive to the proportion of pairwise kinship comparisons which yielded a mother-offspring pair. Taken together, our study demonstrates that it is possible to generate CKMR-based abundance estimates from a single sampling event for small caribou populations, so long as a sufficient sampling intensity can be achieved.
Collapse
Affiliation(s)
- Brandon D Merriell
- Environmental and Life Sciences Department Trent University Peterborough Ontario Canada
| | - Micheline Manseau
- Environmental and Life Sciences Department Trent University Peterborough Ontario Canada
- Landscape Science and Technology Division, Environment and Climate Change Canada Ottawa Ontario Canada
| | - Paul J Wilson
- Environmental and Life Sciences Department Trent University Peterborough Ontario Canada
| |
Collapse
|
37
|
Alvarez-Kuglen M, Ninomiya K, Qin H, Rodriguez D, Fiengo L, Farhy C, Hsu WM, Kirk B, Havas A, Feng GS, Roberts AJ, Anderson RM, Serrano M, Adams PD, Sharpee TO, Terskikh AV. ImAge quantitates aging and rejuvenation. NATURE AGING 2024; 4:1308-1327. [PMID: 39210148 DOI: 10.1038/s43587-024-00685-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/23/2023] [Accepted: 07/11/2024] [Indexed: 09/04/2024]
Abstract
For efficient, cost-effective and personalized healthcare, biomarkers that capture aspects of functional, biological aging, thus predicting disease risk and lifespan more accurately and reliably than chronological age, are essential. We developed an imaging-based chromatin and epigenetic age (ImAge) that captures intrinsic age-related trajectories of the spatial organization of chromatin and epigenetic marks in single nuclei, in mice. We show that such trajectories readily emerge as principal changes in each individual dataset without regression on chronological age, and that ImAge can be computed using several epigenetic marks and DNA labeling. We find that interventions known to affect biological aging induce corresponding effects on ImAge, including increased ImAge upon chemotherapy treatment and decreased ImAge upon caloric restriction and partial reprogramming by transient OSKM expression in liver and skeletal muscle. Further, ImAge readouts from chronologically identical mice inversely correlated with their locomotor activity, suggesting that ImAge may capture elements of biological and functional age. In sum, we developed ImAge, an imaging-based biomarker of aging with single-cell resolution rooted in the analysis of spatial organization of epigenetic marks.
Collapse
Affiliation(s)
| | - Kenta Ninomiya
- Harry Perkins Institute of Medical Research, The University of Western Australia, Perth, Western Australia, Australia
| | - Haodong Qin
- Department of Physics, University of California San Diego, La Jolla, CA, USA
| | | | | | - Chen Farhy
- Sanford Burnham Prebys, La Jolla, CA, USA
| | - Wei-Mien Hsu
- Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Brian Kirk
- Sanford Burnham Prebys, La Jolla, CA, USA
| | | | - Gen-Sheng Feng
- School of Medicine, Univerity of California San Diego, La Jolla, CA, USA
| | | | - Rozalyn M Anderson
- University of Wisconsin, Madison, WI, USA
- GRECC, William S Middleton Memorial Veterans Hospital, Madison, WI, USA
| | - Manuel Serrano
- Institute for Research in Biomedicine (IRB Barcelona), Barcelona, Spain
- Barcelona Institute of Science and Technology (BIST), Barcelona, Spain
- Altos Labs, Cambridge Institute of Science, Granta Park, UK
| | | | | | - Alexey V Terskikh
- The Scintillon Research Institute, San Diego, CA, USA.
- Harry Perkins Institute of Medical Research, The University of Western Australia, Perth, Western Australia, Australia.
| |
Collapse
|
38
|
Liu A, Cheong JZA, Hassan S, Wielgat MB, Meudt JJ, Townsend EC, Shanmuganayagam D, Kalan LR, Gibson A. The effect of anatomic location on porcine models of burn injury and wound healing. Wound Repair Regen 2024; 32:675-685. [PMID: 38775411 DOI: 10.1111/wrr.13190] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2023] [Revised: 04/04/2024] [Accepted: 05/07/2024] [Indexed: 08/22/2024]
Abstract
Porcine models are frequently used for burn healing studies; however, factors including anatomic location and lack of standardised wound methods can impact the interpretation of wound data. The objectives of this study are to examine the influence of anatomical locations on the uniformity of burn creation and healing in porcine burn models. To optimise burn parameters on dorsal and ventral surfaces, ex vivo and in situ euthanized animals were first used to examine the location-dependence of the burn depth and contact time relationship. The location-dependent healing in vivo was then examined using burn and excisional wounds at dorsal, ventral, caudal and cranial locations. Lactate dehydrogenase (LDH) and H&E were used to assess burn depth and wound re-epithelialization. We found that burn depth on the ventral skin was significantly deeper than that of the dorsal skin at identical thermal conditions. Compared with burns created ex vivo, burns created in situ immediately post-mortem were significantly deeper in the ventral location. In live animals, 2 out of 12 burn wounds were fully re-epithelialized after 14 days in contrast to complete re-epithelialization of all excisional wounds. Among the burn wounds, those at the cranial-dorsal site exhibited faster healing than at the caudal-dorsal site. This study showed that anatomical location is an important consideration for the consistency of burn depth creation and healing. These data support symmetric localization of treatment and control for comparative assessment of burn healing in porcine models to prevent misinterpretation of results and increase the translatability of findings to humans.
Collapse
Affiliation(s)
- Aiping Liu
- Department of Surgery, University of Wisconsin-Madison, Madison, Wisconsin, USA
| | - J Z Alex Cheong
- Department of Medical Microbiology & Immunology, University of Wisconsin-Madison, Madison, Wisconsin, USA
| | - Sameeha Hassan
- Department of Surgery, University of Wisconsin-Madison, Madison, Wisconsin, USA
| | - Matthew B Wielgat
- Department of Animal & Dairy Sciences, University of Wisconsin-Madison, Madison, Wisconsin, USA
| | - Jennifer J Meudt
- Department of Animal & Dairy Sciences, University of Wisconsin-Madison, Madison, Wisconsin, USA
| | - Elizabeth Catherine Townsend
- Department of Medical Microbiology & Immunology, University of Wisconsin-Madison, Madison, Wisconsin, USA
- Medical Scientist Training Program, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin, USA
| | - Dhanansayan Shanmuganayagam
- Department of Surgery, University of Wisconsin-Madison, Madison, Wisconsin, USA
- Department of Animal & Dairy Sciences, University of Wisconsin-Madison, Madison, Wisconsin, USA
- Center for Biomedical Swine Research & Innovation, University of Wisconsin-Madison, Madison, Wisconsin, USA
| | - Lindsay R Kalan
- Department of Medical Microbiology & Immunology, University of Wisconsin-Madison, Madison, Wisconsin, USA
- Department of Biochemistry and Biomedical Sciences, Faculty of Health Sciences, McMaster University, Hamilton, Ontario, Canada
| | - Angela Gibson
- Department of Surgery, University of Wisconsin-Madison, Madison, Wisconsin, USA
| |
Collapse
|
39
|
Bonder MJ, Clark SJ, Krueger F, Luo S, Agostinho de Sousa J, Hashtroud AM, Stubbs TM, Stark AK, Rulands S, Stegle O, Reik W, von Meyenn F. scEpiAge: an age predictor highlighting single-cell ageing heterogeneity in mouse blood. Nat Commun 2024; 15:7567. [PMID: 39217176 PMCID: PMC11366017 DOI: 10.1038/s41467-024-51833-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2023] [Accepted: 08/16/2024] [Indexed: 09/04/2024] Open
Abstract
Ageing is the accumulation of changes and decline of function of organisms over time. The concept and biomarkers of biological age have been established, notably DNA methylation-based clocks. The emergence of single-cell DNA methylation profiling methods opens the possibility of studying the biological age of individual cells. Here, we generate a large single-cell DNA methylation and transcriptome dataset from mouse peripheral blood samples, spanning a broad range of ages. The number of genes expressed increases with age, but gene-specific changes are small. We next develop scEpiAge, a single-cell DNA methylation age predictor, which can accurately predict age in (very sparse) publicly available datasets, and also in single cells. DNA methylation age distribution is wider than technically expected, indicating epigenetic age heterogeneity and functional differences. Our work provides a foundation for single-cell and sparse data epigenetic age predictors, validates their functionality and highlights epigenetic heterogeneity during ageing.
Collapse
Affiliation(s)
- Marc Jan Bonder
- Division of Computational Genomics and Systems Genetics, German Cancer Research Center, Heidelberg, Germany.
- Genome Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany.
- Department of Genetics, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands.
- Oncode Institute, Utrecht, The Netherlands.
| | - Stephen J Clark
- Altos Labs, Cambridge Institute of Science, Cambridge, UK.
- Epigenetics Programme, The Babraham Institute, Cambridge, UK.
| | - Felix Krueger
- Altos Labs, Cambridge Institute of Science, Cambridge, UK
- Bioinformatics Group, The Babraham Institute, Cambridge, UK
| | - Siyuan Luo
- Laboratory of Nutrition and Metabolic Epigenetics, Department of Health Sciences and Technology, ETH Zurich, Zurich, Switzerland
| | - João Agostinho de Sousa
- Laboratory of Nutrition and Metabolic Epigenetics, Department of Health Sciences and Technology, ETH Zurich, Zurich, Switzerland
| | - Aida M Hashtroud
- Max Planck Institute for the Physics of Complex Systems, Dresden, Germany
- Arnold Sommerfeld Center for Theoretical Physics and Center for NanoScience, Department of Physics, Ludwig-Maximilians-Universität, Munich, Germany
| | - Thomas M Stubbs
- Epigenetics Programme, The Babraham Institute, Cambridge, UK
- Chronomics Limited, London, UK
| | | | - Steffen Rulands
- Max Planck Institute for the Physics of Complex Systems, Dresden, Germany
- Arnold Sommerfeld Center for Theoretical Physics and Center for NanoScience, Department of Physics, Ludwig-Maximilians-Universität, Munich, Germany
| | - Oliver Stegle
- Division of Computational Genomics and Systems Genetics, German Cancer Research Center, Heidelberg, Germany
- Genome Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany
| | - Wolf Reik
- Altos Labs, Cambridge Institute of Science, Cambridge, UK.
- Epigenetics Programme, The Babraham Institute, Cambridge, UK.
- Wellcome Trust Sanger Institute, Hinxton, Cambridge, UK.
| | - Ferdinand von Meyenn
- Laboratory of Nutrition and Metabolic Epigenetics, Department of Health Sciences and Technology, ETH Zurich, Zurich, Switzerland.
- Department of Medical and Molecular Genetics, King's College London, London, UK.
| |
Collapse
|
40
|
Chien JF, Liu H, Wang BA, Luo C, Bartlett A, Castanon R, Johnson ND, Nery JR, Osteen J, Li J, Altshul J, Kenworthy M, Valadon C, Liem M, Claffey N, O'Connor C, Seeker LA, Ecker JR, Behrens MM, Mukamel EA. Cell-type-specific effects of age and sex on human cortical neurons. Neuron 2024; 112:2524-2539.e5. [PMID: 38838671 DOI: 10.1016/j.neuron.2024.05.013] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2023] [Revised: 03/29/2024] [Accepted: 05/09/2024] [Indexed: 06/07/2024]
Abstract
Altered transcriptional and epigenetic regulation of brain cell types may contribute to cognitive changes with advanced age. Using single-nucleus multi-omic DNA methylation and transcriptome sequencing (snmCT-seq) in frontal cortex from young adult and aged donors, we found widespread age- and sex-related variation in specific neuron types. The proportion of inhibitory SST- and VIP-expressing neurons was reduced in aged donors. Excitatory neurons had more profound age-related changes in their gene expression and DNA methylation than inhibitory cells. Hundreds of genes involved in synaptic activity, including EGR1, were less expressed in aged adults. Genes located in subtelomeric regions increased their expression with age and correlated with reduced telomere length. We further mapped cell-type-specific sex differences in gene expression and X-inactivation escape genes. Multi-omic single-nucleus epigenomes and transcriptomes provide new insight into the effects of age and sex on human neurons.
Collapse
Affiliation(s)
- Jo-Fan Chien
- Department of Physics, University of California, San Diego, La Jolla, CA 92037, USA
| | - Hanqing Liu
- Genomic Analysis Laboratory, Salk Institute, La Jolla, CA 92037, USA; Howard Hughes Medical Institute, Salk Institute, La Jolla, CA 92037, USA
| | - Bang-An Wang
- Genomic Analysis Laboratory, Salk Institute, La Jolla, CA 92037, USA; Howard Hughes Medical Institute, Salk Institute, La Jolla, CA 92037, USA
| | - Chongyuan Luo
- Department of Human Genetics, University of California, Los Angeles, Los Angeles, CA, USA
| | - Anna Bartlett
- Genomic Analysis Laboratory, Salk Institute, La Jolla, CA 92037, USA; Howard Hughes Medical Institute, Salk Institute, La Jolla, CA 92037, USA
| | - Rosa Castanon
- Genomic Analysis Laboratory, Salk Institute, La Jolla, CA 92037, USA; Howard Hughes Medical Institute, Salk Institute, La Jolla, CA 92037, USA
| | - Nicholas D Johnson
- Department of Psychiatry, University of California, San Diego, La Jolla, CA 92037, USA; Computational Neurobiology Laboratory, Salk Institute, La Jolla, CA 92037, USA
| | - Joseph R Nery
- Genomic Analysis Laboratory, Salk Institute, La Jolla, CA 92037, USA; Howard Hughes Medical Institute, Salk Institute, La Jolla, CA 92037, USA
| | - Julia Osteen
- Genomic Analysis Laboratory, Salk Institute, La Jolla, CA 92037, USA; Howard Hughes Medical Institute, Salk Institute, La Jolla, CA 92037, USA
| | - Junhao Li
- Department of Cognitive Science, University of California, San Diego, La Jolla, CA 92037, USA
| | - Jordan Altshul
- Genomic Analysis Laboratory, Salk Institute, La Jolla, CA 92037, USA; Howard Hughes Medical Institute, Salk Institute, La Jolla, CA 92037, USA
| | - Mia Kenworthy
- Genomic Analysis Laboratory, Salk Institute, La Jolla, CA 92037, USA; Howard Hughes Medical Institute, Salk Institute, La Jolla, CA 92037, USA
| | - Cynthia Valadon
- Genomic Analysis Laboratory, Salk Institute, La Jolla, CA 92037, USA; Howard Hughes Medical Institute, Salk Institute, La Jolla, CA 92037, USA
| | - Michelle Liem
- Flow Cytometry Core Facility, Salk Institute, La Jolla, CA 92037, USA
| | - Naomi Claffey
- Flow Cytometry Core Facility, Salk Institute, La Jolla, CA 92037, USA
| | - Carolyn O'Connor
- Flow Cytometry Core Facility, Salk Institute, La Jolla, CA 92037, USA
| | - Luise A Seeker
- Department of Bioengineering, Stanford University, Stanford, CA, USA
| | - Joseph R Ecker
- Genomic Analysis Laboratory, Salk Institute, La Jolla, CA 92037, USA; Howard Hughes Medical Institute, Salk Institute, La Jolla, CA 92037, USA.
| | - M Margarita Behrens
- Department of Psychiatry, University of California, San Diego, La Jolla, CA 92037, USA; Computational Neurobiology Laboratory, Salk Institute, La Jolla, CA 92037, USA.
| | - Eran A Mukamel
- Department of Cognitive Science, University of California, San Diego, La Jolla, CA 92037, USA.
| |
Collapse
|
41
|
Patrick R, Naval-Sanchez M, Deshpande N, Huang Y, Zhang J, Chen X, Yang Y, Tiwari K, Esmaeili M, Tran M, Mohamed AR, Wang B, Xia D, Ma J, Bayliss J, Wong K, Hun ML, Sun X, Cao B, Cottle DL, Catterall T, Barzilai-Tutsch H, Troskie RL, Chen Z, Wise AF, Saini S, Soe YM, Kumari S, Sweet MJ, Thomas HE, Smyth IM, Fletcher AL, Knoblich K, Watt MJ, Alhomrani M, Alsanie W, Quinn KM, Merson TD, Chidgey AP, Ricardo SD, Yu D, Jardé T, Cheetham SW, Marcelle C, Nilsson SK, Nguyen Q, White MD, Nefzger CM. The activity of early-life gene regulatory elements is hijacked in aging through pervasive AP-1-linked chromatin opening. Cell Metab 2024; 36:1858-1881.e23. [PMID: 38959897 DOI: 10.1016/j.cmet.2024.06.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/21/2023] [Revised: 03/28/2024] [Accepted: 06/06/2024] [Indexed: 07/05/2024]
Abstract
A mechanistic connection between aging and development is largely unexplored. Through profiling age-related chromatin and transcriptional changes across 22 murine cell types, analyzed alongside previous mouse and human organismal maturation datasets, we uncovered a transcription factor binding site (TFBS) signature common to both processes. Early-life candidate cis-regulatory elements (cCREs), progressively losing accessibility during maturation and aging, are enriched for cell-type identity TFBSs. Conversely, cCREs gaining accessibility throughout life have a lower abundance of cell identity TFBSs but elevated activator protein 1 (AP-1) levels. We implicate TF redistribution toward these AP-1 TFBS-rich cCREs, in synergy with mild downregulation of cell identity TFs, as driving early-life cCRE accessibility loss and altering developmental and metabolic gene expression. Such remodeling can be triggered by elevating AP-1 or depleting repressive H3K27me3. We propose that AP-1-linked chromatin opening drives organismal maturation by disrupting cell identity TFBS-rich cCREs, thereby reprogramming transcriptome and cell function, a mechanism hijacked in aging through ongoing chromatin opening.
Collapse
Affiliation(s)
- Ralph Patrick
- Institute for Molecular Bioscience, The University of Queensland, St. Lucia, Brisbane, QLD 4072, Australia
| | - Marina Naval-Sanchez
- Institute for Molecular Bioscience, The University of Queensland, St. Lucia, Brisbane, QLD 4072, Australia
| | - Nikita Deshpande
- Institute for Molecular Bioscience, The University of Queensland, St. Lucia, Brisbane, QLD 4072, Australia; WHO Collaborating Centre for Reference and Research on Influenza, The Peter Doherty Institute for Infection and Immunity, Melbourne, VIC 3000, Australia
| | - Yifei Huang
- Institute for Molecular Bioscience, The University of Queensland, St. Lucia, Brisbane, QLD 4072, Australia
| | - Jingyu Zhang
- Institute for Molecular Bioscience, The University of Queensland, St. Lucia, Brisbane, QLD 4072, Australia
| | - Xiaoli Chen
- Institute for Molecular Bioscience, The University of Queensland, St. Lucia, Brisbane, QLD 4072, Australia
| | - Ying Yang
- Institute for Molecular Bioscience, The University of Queensland, St. Lucia, Brisbane, QLD 4072, Australia
| | - Kanupriya Tiwari
- Institute for Molecular Bioscience, The University of Queensland, St. Lucia, Brisbane, QLD 4072, Australia
| | - Mohammadhossein Esmaeili
- Institute for Molecular Bioscience, The University of Queensland, St. Lucia, Brisbane, QLD 4072, Australia
| | - Minh Tran
- Institute for Molecular Bioscience, The University of Queensland, St. Lucia, Brisbane, QLD 4072, Australia
| | - Amin R Mohamed
- Institute for Molecular Bioscience, The University of Queensland, St. Lucia, Brisbane, QLD 4072, Australia
| | - Binxu Wang
- Institute for Molecular Bioscience, The University of Queensland, St. Lucia, Brisbane, QLD 4072, Australia
| | - Di Xia
- Genome Innovation Hub, The University of Queensland, St. Lucia, Brisbane, QLD 4072, Australia
| | - Jun Ma
- Genome Innovation Hub, The University of Queensland, St. Lucia, Brisbane, QLD 4072, Australia
| | - Jacqueline Bayliss
- Department of Anatomy and Physiology, Faculty of Medicine Dentistry and Health Sciences, The University of Melbourne, Parkville, VIC 3010, Australia
| | - Kahlia Wong
- Department of Anatomy and Developmental Biology, Monash Biomedicine Discovery Institute, Monash University, Clayton, VIC 3800, Australia
| | - Michael L Hun
- Department of Anatomy and Developmental Biology, Monash Biomedicine Discovery Institute, Monash University, Clayton, VIC 3800, Australia
| | - Xuan Sun
- Biomedical Manufacturing, Commonwealth Scientific and Industrial Research Organization, Melbourne, VIC, Australia; Australian Regenerative Medicine Institute, Monash University, Clayton, VIC 3800, Australia
| | - Benjamin Cao
- Biomedical Manufacturing, Commonwealth Scientific and Industrial Research Organization, Melbourne, VIC, Australia; Australian Regenerative Medicine Institute, Monash University, Clayton, VIC 3800, Australia
| | - Denny L Cottle
- Department of Anatomy and Developmental Biology, Monash Biomedicine Discovery Institute, Monash University, Clayton, VIC 3800, Australia
| | - Tara Catterall
- St. Vincent's Institute of Medical Research, Fitzroy, VIC 3065, Australia
| | - Hila Barzilai-Tutsch
- Australian Regenerative Medicine Institute, Monash University, Clayton, VIC 3800, Australia; Institut NeuroMyoGène, University Claude Bernard Lyon 1, 69008 Lyon, France
| | - Robin-Lee Troskie
- Australian Institute for Bioengineering and Nanotechnology, The University of Queensland, St. Lucia, Brisbane, QLD 4072, Australia
| | - Zhian Chen
- Frazer Institute, Faculty of Medicine, The University of Queensland, Brisbane, QLD 4102, Australia
| | - Andrea F Wise
- Department of Pharmacology, Monash Biomedicine Discovery Institute, Monash University, Clayton, VIC 3800, Australia
| | - Sheetal Saini
- Department of Pharmacology, Monash Biomedicine Discovery Institute, Monash University, Clayton, VIC 3800, Australia
| | - Ye Mon Soe
- Frazer Institute, Faculty of Medicine, The University of Queensland, Brisbane, QLD 4102, Australia
| | - Snehlata Kumari
- Frazer Institute, Faculty of Medicine, The University of Queensland, Brisbane, QLD 4102, Australia
| | - Matthew J Sweet
- Institute for Molecular Bioscience, The University of Queensland, St. Lucia, Brisbane, QLD 4072, Australia; Australian Infectious Diseases Research Centre, The University of Queensland, Brisbane, QLD, Australia
| | - Helen E Thomas
- St. Vincent's Institute of Medical Research, Fitzroy, VIC 3065, Australia
| | - Ian M Smyth
- Department of Anatomy and Developmental Biology, Monash Biomedicine Discovery Institute, Monash University, Clayton, VIC 3800, Australia
| | - Anne L Fletcher
- Department of Biochemistry and Molecular Biology, Monash Biomedicine Discovery Institute, Monash University, Clayton, VIC 3800, Australia
| | - Konstantin Knoblich
- Department of Biochemistry and Molecular Biology, Monash Biomedicine Discovery Institute, Monash University, Clayton, VIC 3800, Australia
| | - Matthew J Watt
- Department of Anatomy and Physiology, Faculty of Medicine Dentistry and Health Sciences, The University of Melbourne, Parkville, VIC 3010, Australia
| | - Majid Alhomrani
- Department of Clinical Laboratories Sciences, Faculty of Applied Medical Sciences, Taif University, Taif, Saudi Arabia; Research Centre for Health Sciences, Taif University, Taif, Saudi Arabia
| | - Walaa Alsanie
- Department of Clinical Laboratories Sciences, Faculty of Applied Medical Sciences, Taif University, Taif, Saudi Arabia; Research Centre for Health Sciences, Taif University, Taif, Saudi Arabia
| | - Kylie M Quinn
- Department of Biochemistry and Molecular Biology, Monash Biomedicine Discovery Institute, Monash University, Clayton, VIC 3800, Australia; School of Health and Biomedical Sciences, RMIT University, Bundoora, VIC 3083, Australia
| | - Tobias D Merson
- Australian Regenerative Medicine Institute, Monash University, Clayton, VIC 3800, Australia; National Institute of Mental Health, National Institutes of Health, Bethesda, MD 20892, USA
| | - Ann P Chidgey
- Department of Anatomy and Developmental Biology, Monash Biomedicine Discovery Institute, Monash University, Clayton, VIC 3800, Australia
| | - Sharon D Ricardo
- Department of Pharmacology, Monash Biomedicine Discovery Institute, Monash University, Clayton, VIC 3800, Australia
| | - Di Yu
- Frazer Institute, Faculty of Medicine, The University of Queensland, Brisbane, QLD 4102, Australia; Ian Frazer Centre for Children's Immunotherapy Research, Child Health Research Centre, Faculty of Medicine, The University of Queensland, Brisbane, QLD 4102, Australia
| | - Thierry Jardé
- Department of Anatomy and Developmental Biology, Monash Biomedicine Discovery Institute, Monash University, Clayton, VIC 3800, Australia; Development and Stem Cells Program, Monash Biomedicine Discovery Institute, Monash University, Clayton, VIC 3800, Australia; Cancer Program, Monash Biomedicine Discovery Institute, Monash University, Clayton, VIC 3800, Australia; Department of Surgery, Cabrini Monash University, Malvern, VIC 3144, Australia
| | - Seth W Cheetham
- Australian Institute for Bioengineering and Nanotechnology, The University of Queensland, St. Lucia, Brisbane, QLD 4072, Australia
| | - Christophe Marcelle
- Australian Regenerative Medicine Institute, Monash University, Clayton, VIC 3800, Australia; Institut NeuroMyoGène, University Claude Bernard Lyon 1, 69008 Lyon, France
| | - Susan K Nilsson
- Biomedical Manufacturing, Commonwealth Scientific and Industrial Research Organization, Melbourne, VIC, Australia; Australian Regenerative Medicine Institute, Monash University, Clayton, VIC 3800, Australia
| | - Quan Nguyen
- Institute for Molecular Bioscience, The University of Queensland, St. Lucia, Brisbane, QLD 4072, Australia; School of Biomedical Sciences, The University of Queensland, St. Lucia, Brisbane, QLD 4072, Australia
| | - Melanie D White
- Institute for Molecular Bioscience, The University of Queensland, St. Lucia, Brisbane, QLD 4072, Australia; School of Biomedical Sciences, The University of Queensland, St. Lucia, Brisbane, QLD 4072, Australia
| | - Christian M Nefzger
- Institute for Molecular Bioscience, The University of Queensland, St. Lucia, Brisbane, QLD 4072, Australia; Department of Anatomy and Developmental Biology, Monash Biomedicine Discovery Institute, Monash University, Clayton, VIC 3800, Australia; Development and Stem Cells Program, Monash Biomedicine Discovery Institute, Monash University, Clayton, VIC 3800, Australia; School of Chemistry and Molecular Biosciences, The University of Queensland, St. Lucia, Brisbane, QLD 4072, Australia.
| |
Collapse
|
42
|
Horvath S, Topol EJ. Digitising the ageing process with epigenetic clocks. Lancet 2024; 404:423. [PMID: 39097382 DOI: 10.1016/s0140-6736(24)01554-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 08/05/2024]
Affiliation(s)
- Steve Horvath
- Altos Labs, Cambridge Institute of Science, Cambridge, UK.
| | - Eric J Topol
- Scripps Research Translational Institute, La Jolla, CA, USA
| |
Collapse
|
43
|
Guynes K, Sarre LA, Carrillo-Baltodano AM, Davies BE, Xu L, Liang Y, Martín-Zamora FM, Hurd PJ, de Mendoza A, Martín-Durán JM. Annelid methylomes reveal ancestral developmental and aging-associated epigenetic erosion across Bilateria. Genome Biol 2024; 25:204. [PMID: 39090757 PMCID: PMC11292947 DOI: 10.1186/s13059-024-03346-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2024] [Accepted: 07/23/2024] [Indexed: 08/04/2024] Open
Abstract
BACKGROUND DNA methylation in the form of 5-methylcytosine (5mC) is the most abundant base modification in animals. However, 5mC levels vary widely across taxa. While vertebrate genomes are hypermethylated, in most invertebrates, 5mC concentrates on constantly and highly transcribed genes (gene body methylation; GbM) and, in some species, on transposable elements (TEs), a pattern known as "mosaic". Yet, the role and developmental dynamics of 5mC and how these explain interspecies differences in DNA methylation patterns remain poorly understood, especially in Spiralia, a large clade of invertebrates comprising nearly half of the animal phyla. RESULTS Here, we generate base-resolution methylomes for three species with distinct genomic features and phylogenetic positions in Annelida, a major spiralian phylum. All possible 5mC patterns occur in annelids, from typical invertebrate intermediate levels in a mosaic distribution to hypermethylation and methylation loss. GbM is common to annelids with 5mC, and methylation differences across species are explained by taxon-specific transcriptional dynamics or the presence of intronic TEs. Notably, the link between GbM and transcription decays during development, alongside a gradual and global, age-dependent demethylation in adult stages. Additionally, reducing 5mC levels with cytidine analogs during early development impairs normal embryogenesis and reactivates TEs in the annelid Owenia fusiformis. CONCLUSIONS Our study indicates that global epigenetic erosion during development and aging is an ancestral feature of bilateral animals. However, the tight link between transcription and gene body methylation is likely more important in early embryonic stages, and 5mC-mediated TE silencing probably emerged convergently across animal lineages.
Collapse
Affiliation(s)
- Kero Guynes
- School of Biological and Behavioural Sciences, Queen Mary University of London, Mile End Road, London, E1 4NS, UK
- Institute of Molecular Biotechnology of the Austrian Academy of Sciences (IMBA), Vienna BioCenter (VBC), Vienna, 1030, Austria
| | - Luke A Sarre
- School of Biological and Behavioural Sciences, Queen Mary University of London, Mile End Road, London, E1 4NS, UK
| | - Allan M Carrillo-Baltodano
- School of Biological and Behavioural Sciences, Queen Mary University of London, Mile End Road, London, E1 4NS, UK
| | - Billie E Davies
- School of Biological and Behavioural Sciences, Queen Mary University of London, Mile End Road, London, E1 4NS, UK
| | - Lan Xu
- School of Biological and Behavioural Sciences, Queen Mary University of London, Mile End Road, London, E1 4NS, UK
| | - Yan Liang
- School of Biological and Behavioural Sciences, Queen Mary University of London, Mile End Road, London, E1 4NS, UK
| | - Francisco M Martín-Zamora
- School of Biological and Behavioural Sciences, Queen Mary University of London, Mile End Road, London, E1 4NS, UK
- Altos Labs, Cambridge, UK
| | - Paul J Hurd
- School of Biological and Behavioural Sciences, Queen Mary University of London, Mile End Road, London, E1 4NS, UK
| | - Alex de Mendoza
- School of Biological and Behavioural Sciences, Queen Mary University of London, Mile End Road, London, E1 4NS, UK.
| | - José M Martín-Durán
- School of Biological and Behavioural Sciences, Queen Mary University of London, Mile End Road, London, E1 4NS, UK.
| |
Collapse
|
44
|
Betancourt AJ, Wei KHC, Huang Y, Lee YCG. Causes and Consequences of Varying Transposable Element Activity: An Evolutionary Perspective. Annu Rev Genomics Hum Genet 2024; 25:1-25. [PMID: 38603565 DOI: 10.1146/annurev-genom-120822-105708] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/13/2024]
Abstract
Transposable elements (TEs) are genomic parasites found in nearly all eukaryotes, including humans. This evolutionary success of TEs is due to their replicative activity, involving insertion into new genomic locations. TE activity varies at multiple levels, from between taxa to within individuals. The rapidly accumulating evidence of the influence of TE activity on human health, as well as the rapid growth of new tools to study it, motivated an evaluation of what we know about TE activity thus far. Here, we discuss why TE activity varies, and the consequences of this variation, from an evolutionary perspective. By studying TE activity in nonhuman organisms in the context of evolutionary theories, we can shed light on the factors that affect TE activity. While the consequences of TE activity are usually deleterious, some have lasting evolutionary impacts by conferring benefits on the host or affecting other evolutionary processes.
Collapse
Affiliation(s)
- Andrea J Betancourt
- Institute of Infection, Veterinary, and Ecological Sciences, University of Liverpool, Liverpool, United Kingdom
| | - Kevin H-C Wei
- Department of Zoology, University of British Columbia, Vancouver, British Columbia, Canada
| | - Yuheng Huang
- Department of Ecology and Evolutionary Biology, University of California, Irvine, California, USA
| | - Yuh Chwen G Lee
- Center for Complex Biological Systems, University of California, Irvine, California, USA;
- Department of Ecology and Evolutionary Biology, University of California, Irvine, California, USA
| |
Collapse
|
45
|
Mi T, Soerens AG, Alli S, Kang TG, Vasandan AB, Wang Z, Vezys V, Kimura S, Iacobucci I, Baylin SB, Jones PA, Hiner C, Mueller A, Goldstein H, Mullighan CG, Zebley CC, Masopust D, Youngblood B. Conserved epigenetic hallmarks of T cell aging during immunity and malignancy. NATURE AGING 2024; 4:1053-1063. [PMID: 38867059 PMCID: PMC11333289 DOI: 10.1038/s43587-024-00649-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/03/2024] [Accepted: 05/13/2024] [Indexed: 06/14/2024]
Abstract
Chronological aging correlates with epigenetic modifications at specific loci, calibrated to species lifespan. Such 'epigenetic clocks' appear conserved among mammals, but whether they are cell autonomous and restricted by maximal organismal lifespan remains unknown. We used a multilifetime murine model of repeat vaccination and memory T cell transplantation to test whether epigenetic aging tracks with cellular replication and if such clocks continue 'counting' beyond species lifespan. Here we found that memory T cell epigenetic clocks tick independently of host age and continue through four lifetimes. Instead of recording chronological time, T cells recorded proliferative experience through modification of cell cycle regulatory genes. Applying this epigenetic profile across a range of human T cell contexts, we found that naive T cells appeared 'young' regardless of organism age, while in pediatric patients, T cell acute lymphoblastic leukemia appeared to have epigenetically aged for up to 200 years. Thus, T cell epigenetic clocks measure replicative history and can continue to accumulate well-beyond organismal lifespan.
Collapse
Affiliation(s)
- Tian Mi
- Department of Immunology, St. Jude Children's Research Hospital, Memphis, TN, USA
| | - Andrew G Soerens
- Center for Immunology, Department of Microbiology and Immunology, University of Minnesota, Minneapolis, MN, USA
| | - Shanta Alli
- Department of Immunology, St. Jude Children's Research Hospital, Memphis, TN, USA
| | - Tae Gun Kang
- Department of Immunology, St. Jude Children's Research Hospital, Memphis, TN, USA
| | - Anoop Babu Vasandan
- Department of Immunology, St. Jude Children's Research Hospital, Memphis, TN, USA
| | - Zhaoming Wang
- Department of Computational Biology and Department of Epidemiology and Cancer Control, St. Jude Children's Research Hospital, Memphis, TN, USA
| | - Vaiva Vezys
- Center for Immunology, Department of Microbiology and Immunology, University of Minnesota, Minneapolis, MN, USA
| | - Shunsuke Kimura
- Department of Pathology, St. Jude Children's Research Hospital, Memphis, TN, USA
| | - Ilaria Iacobucci
- Department of Pathology, St. Jude Children's Research Hospital, Memphis, TN, USA
| | - Stephen B Baylin
- The Sidney Kimmel Comprehensive Cancer Institute, The Johns Hopkins Hospital, Baltimore, MD, USA
| | - Peter A Jones
- Department of Epigenetics, Van Andel Institute, Grand Rapids, MI, USA
| | - Christopher Hiner
- Department of Microbiology and Immunology, Albert Einstein College of Medicine, New York, NY, USA
| | - April Mueller
- Department of Microbiology and Immunology, Albert Einstein College of Medicine, New York, NY, USA
| | - Harris Goldstein
- Department of Microbiology and Immunology, Albert Einstein College of Medicine, New York, NY, USA
| | - Charles G Mullighan
- Department of Pathology, St. Jude Children's Research Hospital, Memphis, TN, USA
| | - Caitlin C Zebley
- Department of Immunology, St. Jude Children's Research Hospital, Memphis, TN, USA.
- Department of Bone Marrow Transplantation and Cellular Therapy, St. Jude Children's Research Hospital, Memphis, TN, USA.
| | - David Masopust
- Center for Immunology, Department of Microbiology and Immunology, University of Minnesota, Minneapolis, MN, USA.
| | - Ben Youngblood
- Department of Immunology, St. Jude Children's Research Hospital, Memphis, TN, USA.
| |
Collapse
|
46
|
Pośpiech E, Bar A, Pisarek-Pacek A, Karaś A, Branicki W, Chlopicki S. Epigenetic clock in the aorta and age-related endothelial dysfunction in mice. GeroScience 2024; 46:3993-4002. [PMID: 38381284 PMCID: PMC11226569 DOI: 10.1007/s11357-024-01086-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2023] [Accepted: 01/20/2024] [Indexed: 02/22/2024] Open
Abstract
While epigenetic age (EA) of mouse blood can be determined using DNA methylation analysis at three CpG sites in the Prima1, Hsf4 and Kcns1 genes it is not known whether this approach is useful for predicting vascular biological age. In this study we validated the 3-CpG estimator for age prediction in mouse blood, developed a new predictive model for EA in mouse aorta, and assessed whether epigenetic age acceleration (EAA) measured with blood and aorta samples correlates with age-dependent endothelial dysfunction. Endothelial function was characterized in vivo by MRI in 8-96-week-old C57BL/6 mice. Arterial stiffness was measured by USG-doppler. EA-related changes within 41 CpG sites in Prima1, Kcns1 and Hsf4 loci, were analyzed in the aorta and blood using bisulfite amplicon high-throughput sequencing. Progressive age-dependent endothelial dysfunction and changes in arterial stiffness were observed in 36-96-week-old C57BL/6 mice. Methylation levels of the investigated loci correlated with chronological age in blood and the aorta. The new model for EA estimation in aorta included three cytosines located in the Kcns1 and Hsf4, explained R2 = 87.8% of the variation in age, and predicted age with an mean absolute error of 9.6 weeks in the independent test set. EAA in the aorta was associated with endothelial dysfunction in the abdominal aorta and femoral artery what was consistent with the EAA direction estimated in blood samples. The rate of vascular biological ageing in mice, reflected by the age-dependent systemic endothelial dysfunction, could be estimated using DNA methylation measurements at three loci in aorta and blood samples.
Collapse
Affiliation(s)
- Ewelina Pośpiech
- Department of Forensic Genetics, Pomeranian Medical University in Szczecin, Al. Powstancow Wielkopolskich 72, 70-204, Szczecin, Poland
| | - Anna Bar
- Jagiellonian Centre for Experimental Therapeutics (JCET), Jagiellonian University, Bobrzynskiego 14, 30-348, Krakow, Poland
| | - Aleksandra Pisarek-Pacek
- Institute of Zoology and Biomedical Research, Faculty of Biology, Jagiellonian University, Gronostajowa 9, 30-387, Krakow, Poland
- Malopolska Centre of Biotechnology, Jagiellonian University, Gronostajowa 7a, 30-387, Krakow, Poland
| | - Agnieszka Karaś
- Jagiellonian Centre for Experimental Therapeutics (JCET), Jagiellonian University, Bobrzynskiego 14, 30-348, Krakow, Poland
| | - Wojciech Branicki
- Institute of Zoology and Biomedical Research, Faculty of Biology, Jagiellonian University, Gronostajowa 9, 30-387, Krakow, Poland.
- Institute of Forensic Research, Westerplatte 9, 31-033, Kraków, Poland.
| | - Stefan Chlopicki
- Jagiellonian Centre for Experimental Therapeutics (JCET), Jagiellonian University, Bobrzynskiego 14, 30-348, Krakow, Poland.
- Faculty of Medicine, Chair of Pharmacology, Jagiellonian University Medical College, Grzegorzecka 16, 31-531, Krakow, Poland.
| |
Collapse
|
47
|
Horvath S, Lacunza E, Mallat MC, Portiansky EL, Gallardo MD, Brooke RT, Chiavellini P, Pasquini DC, Girard M, Lehmann M, Yan Q, Lu AT, Haghani A, Gordevicius J, Abba M, Goya RG. Cognitive rejuvenation in old rats by hippocampal OSKM gene therapy. GeroScience 2024:10.1007/s11357-024-01269-y. [PMID: 39037528 DOI: 10.1007/s11357-024-01269-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2024] [Accepted: 06/27/2024] [Indexed: 07/23/2024] Open
Abstract
Several studies have indicated that interrupted epigenetic reprogramming using Yamanaka transcription factors (OSKM) can rejuvenate cells from old laboratory animals and humans. However, the potential of OSKM-induced rejuvenation in brain tissue has been less explored. Here, we aimed to restore cognitive performance in 25.3-month-old female Sprague-Dawley rats using OSKM gene therapy for 39 days. Their progress was then compared with the cognitive performance of untreated 3.5-month-old rats as well as old control rats treated with a placebo adenovector. The Barnes maze test, used to assess cognitive performance, demonstrated enhanced cognitive abilities in old rats treated with OSKM compared to old control animals. In the treated old rats, there was a noticeable trend towards improved spatial memory relative to the old controls. Further, OSKM gene expression did not lead to any pathological alterations within the 39 days. Analysis of DNA methylation following OSKM treatment yielded three insights. First, epigenetic clocks for rats suggested a marginally significant epigenetic rejuvenation. Second, chromatin state analysis revealed that OSKM treatment rejuvenated the methylome of the hippocampus. Third, an epigenome-wide association analysis indicated that OSKM expression in the hippocampus of old rats partially reversed the age-related increase in methylation. In summary, the administration of Yamanaka genes via viral vectors rejuvenates the functional capabilities and the epigenetic landscape of the rat hippocampus.
Collapse
Affiliation(s)
- Steve Horvath
- Altos Labs, San Diego, USA.
- Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA.
- Epigenetic Clock Development Foundation, Torrance, CA, USA.
| | | | - Martina Canatelli Mallat
- Institute for Biochemical Research (INIBIOLP) - Histology B & Pathology B, School of Medicine, National University of La Plata (UNLP), La Plata, Argentina
| | - Enrique L Portiansky
- Image Analysis Lab (LAI), School of Veterinary Sciences, National University of La Plata, La Plata, Argentina
| | - Maria D Gallardo
- Institute for Biochemical Research (INIBIOLP) - Histology B & Pathology B, School of Medicine, National University of La Plata (UNLP), La Plata, Argentina
| | | | - Priscila Chiavellini
- Institute for Biochemical Research (INIBIOLP) - Histology B & Pathology B, School of Medicine, National University of La Plata (UNLP), La Plata, Argentina
| | - Diana C Pasquini
- Institute for Biochemical Research (INIBIOLP) - Histology B & Pathology B, School of Medicine, National University of La Plata (UNLP), La Plata, Argentina
| | - Mauricio Girard
- Institute for Biochemical Research (INIBIOLP) - Histology B & Pathology B, School of Medicine, National University of La Plata (UNLP), La Plata, Argentina
| | - Marianne Lehmann
- Institute for Biochemical Research (INIBIOLP) - Histology B & Pathology B, School of Medicine, National University of La Plata (UNLP), La Plata, Argentina
| | - Qi Yan
- Altos Labs, San Diego, USA
| | | | | | | | - Martin Abba
- Institute for Biochemical Research (INIBIOLP) - Histology B & Pathology B, School of Medicine, National University of La Plata (UNLP), La Plata, Argentina
| | - Rodolfo G Goya
- Institute for Biochemical Research (INIBIOLP) - Histology B & Pathology B, School of Medicine, National University of La Plata (UNLP), La Plata, Argentina
- Vitality in Aging Research Group (VIA), Fort Lauderdale, FL, USA
| |
Collapse
|
48
|
Zheng Z, Li J, Liu T, Fan Y, Zhai QC, Xiong M, Wang QR, Sun X, Zheng QW, Che S, Jiang B, Zheng Q, Wang C, Liu L, Ping J, Wang S, Gao DD, Ye J, Yang K, Zuo Y, Ma S, Yang YG, Qu J, Zhang F, Jia P, Liu GH, Zhang W. DNA methylation clocks for estimating biological age in Chinese cohorts. Protein Cell 2024; 15:575-593. [PMID: 38482631 PMCID: PMC11259550 DOI: 10.1093/procel/pwae011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2023] [Accepted: 01/10/2024] [Indexed: 07/21/2024] Open
Abstract
Epigenetic clocks are accurate predictors of human chronological age based on the analysis of DNA methylation (DNAm) at specific CpG sites. However, a systematic comparison between DNA methylation data and other omics datasets has not yet been performed. Moreover, available DNAm age predictors are based on datasets with limited ethnic representation. To address these knowledge gaps, we generated and analyzed DNA methylation datasets from two independent Chinese cohorts, revealing age-related DNAm changes. Additionally, a DNA methylation aging clock (iCAS-DNAmAge) and a group of DNAm-based multi-modal clocks for Chinese individuals were developed, with most of them demonstrating strong predictive capabilities for chronological age. The clocks were further employed to predict factors influencing aging rates. The DNAm aging clock, derived from multi-modal aging features (compositeAge-DNAmAge), exhibited a close association with multi-omics changes, lifestyles, and disease status, underscoring its robust potential for precise biological age assessment. Our findings offer novel insights into the regulatory mechanism of age-related DNAm changes and extend the application of the DNAm clock for measuring biological age and aging pace, providing the basis for evaluating aging intervention strategies.
Collapse
Affiliation(s)
- Zikai Zheng
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing 100101, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Jiaming Li
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing 100101, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Tianzi Liu
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing 100101, China
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, Chinese Academy of Sciences, Shanghai 200031, China
| | - Yanling Fan
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing 100101, China
| | - Qiao-Cheng Zhai
- Division of Orthopaedics, Quzhou Affiliated Hospital of Wenzhou Medical University, Quzhou 324000, China
- The Joint Innovation Center for Engineering in Medicine, Quzhou Affiliated Hospital of Wenzhou Medical University, Quzhou 324000, China
| | - Muzhao Xiong
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing 100101, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Qiao-Ran Wang
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing 100101, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Xiaoyan Sun
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing 100101, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Qi-Wen Zheng
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing 100101, China
| | - Shanshan Che
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing 100101, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Beier Jiang
- The Joint Innovation Center for Engineering in Medicine, Quzhou Affiliated Hospital of Wenzhou Medical University, Quzhou 324000, China
| | - Quan Zheng
- The Joint Innovation Center for Engineering in Medicine, Quzhou Affiliated Hospital of Wenzhou Medical University, Quzhou 324000, China
| | - Cui Wang
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing 100101, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Lixiao Liu
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing 100101, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Jiale Ping
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing 100101, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Si Wang
- Advanced Innovation Center for Human Brain Protection, and National Clinical Research Center for Geriatric Disorders, Xuanwu Hospital Capital Medical University, Beijing 100053, China
- Aging Translational Medicine Center, International Center for Aging and Cancer, Xuanwu Hospital, Capital Medical University, Beijing 100053, China
- Aging Biomarker Consortium, Beijing 100101, China
| | - Dan-Dan Gao
- The Joint Innovation Center for Engineering in Medicine, Quzhou Affiliated Hospital of Wenzhou Medical University, Quzhou 324000, China
| | - Jinlin Ye
- The Joint Innovation Center for Engineering in Medicine, Quzhou Affiliated Hospital of Wenzhou Medical University, Quzhou 324000, China
| | - Kuan Yang
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing 100101, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Yuesheng Zuo
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing 100101, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Shuai Ma
- Aging Biomarker Consortium, Beijing 100101, China
- State Key Laboratory of Membrane Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing 100101, China
- Key Laboratory of Organ Regeneration and Reconstruction, Institute of Zoology, Chinese Academy of Sciences, Beijing 100101, China
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing 100101, China
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing 100101, China
| | - Yun-Gui Yang
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing 100101, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Jing Qu
- University of Chinese Academy of Sciences, Beijing 100049, China
- Aging Biomarker Consortium, Beijing 100101, China
- Key Laboratory of Organ Regeneration and Reconstruction, Institute of Zoology, Chinese Academy of Sciences, Beijing 100101, China
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing 100101, China
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing 100101, China
- State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing 100101, China
| | - Feng Zhang
- Division of Orthopaedics, Quzhou Affiliated Hospital of Wenzhou Medical University, Quzhou 324000, China
| | - Peilin Jia
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing 100101, China
- University of Chinese Academy of Sciences, Beijing 100049, China
- National Genomics Data Center, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing 100101, China
| | - Guang-Hui Liu
- University of Chinese Academy of Sciences, Beijing 100049, China
- Advanced Innovation Center for Human Brain Protection, and National Clinical Research Center for Geriatric Disorders, Xuanwu Hospital Capital Medical University, Beijing 100053, China
- Aging Translational Medicine Center, International Center for Aging and Cancer, Xuanwu Hospital, Capital Medical University, Beijing 100053, China
- Aging Biomarker Consortium, Beijing 100101, China
- State Key Laboratory of Membrane Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing 100101, China
- Key Laboratory of Organ Regeneration and Reconstruction, Institute of Zoology, Chinese Academy of Sciences, Beijing 100101, China
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing 100101, China
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing 100101, China
| | - Weiqi Zhang
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing 100101, China
- University of Chinese Academy of Sciences, Beijing 100049, China
- Aging Biomarker Consortium, Beijing 100101, China
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing 100101, China
| |
Collapse
|
49
|
Moqri M, Cipriano A, Simpson DJ, Rasouli S, Murty T, de Jong TA, Nachun D, de Sena Brandine G, Ying K, Tarkhov A, Aberg KA, van den Oord E, Zhou W, Smith A, Mackall C, Gladyshev VN, Horvath S, Snyder MP, Sebastiano V. PRC2-AgeIndex as a universal biomarker of aging and rejuvenation. Nat Commun 2024; 15:5956. [PMID: 39009581 PMCID: PMC11250797 DOI: 10.1038/s41467-024-50098-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2024] [Accepted: 07/01/2024] [Indexed: 07/17/2024] Open
Abstract
DNA methylation (DNAm) is one of the most reliable biomarkers of aging across mammalian tissues. While the age-dependent global loss of DNAm has been well characterized, DNAm gain is less characterized. Studies have demonstrated that CpGs which gain methylation with age are enriched in Polycomb Repressive Complex 2 (PRC2) targets. However, whole-genome examination of all PRC2 targets as well as determination of the pan-tissue or tissue-specific nature of these associations is lacking. Here, we show that low-methylated regions (LMRs) which are highly bound by PRC2 in embryonic stem cells (PRC2 LMRs) gain methylation with age in all examined somatic mitotic cells. We estimated that this epigenetic change represents around 90% of the age-dependent DNAm gain genome-wide. Therefore, we propose the "PRC2-AgeIndex," defined as the average DNAm in PRC2 LMRs, as a universal biomarker of cellular aging in somatic cells which can distinguish the effect of different anti-aging interventions.
Collapse
Affiliation(s)
- Mahdi Moqri
- Department of Biomedical Data Science, School of Medicine, Stanford University, Stanford, CA, USA
- Department of Obstetrics & Gynecology, School of Medicine, Stanford University, Stanford, CA, USA
- Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Department of Genetics, School of Medicine, Stanford University, Stanford, CA, USA
| | - Andrea Cipriano
- Department of Obstetrics & Gynecology, School of Medicine, Stanford University, Stanford, CA, USA
- Institute for Stem Cell Biology and Regenerative Medicine, School of Medicine, Stanford University, Stanford, CA, USA
| | - Daniel J Simpson
- Department of Obstetrics & Gynecology, School of Medicine, Stanford University, Stanford, CA, USA
- Institute for Stem Cell Biology and Regenerative Medicine, School of Medicine, Stanford University, Stanford, CA, USA
| | - Sajede Rasouli
- Department of Obstetrics & Gynecology, School of Medicine, Stanford University, Stanford, CA, USA
- Institute for Stem Cell Biology and Regenerative Medicine, School of Medicine, Stanford University, Stanford, CA, USA
| | - Tara Murty
- Center for Cancer Cell Therapy, Stanford Cancer Institute, School of Medicine, Stanford University, Stanford, CA, USA
| | - Tineke Anna de Jong
- Department of Obstetrics & Gynecology, School of Medicine, Stanford University, Stanford, CA, USA
- Institute for Stem Cell Biology and Regenerative Medicine, School of Medicine, Stanford University, Stanford, CA, USA
| | - Daniel Nachun
- Department of Pathology, School of Medicine, Stanford University, Stanford, CA, USA
| | | | - Kejun Ying
- Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Andrei Tarkhov
- Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Karolina A Aberg
- Center for Biomarker Research and Precision Medicine, Virginia Commonwealth University, Richmond, VA, 23298, USA
| | - Edwin van den Oord
- Center for Biomarker Research and Precision Medicine, Virginia Commonwealth University, Richmond, VA, 23298, USA
| | - Wanding Zhou
- Center for Computational and Genomic Medicine, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Andrew Smith
- Quantitative and Computational Biology, University of Southern California, Los Angeles, CA, USA
| | - Crystal Mackall
- Center for Cancer Cell Therapy, Stanford Cancer Institute, School of Medicine, Stanford University, Stanford, CA, USA
- Department of Pediatrics, Division of Hematology and Oncology, School of Medicine, Stanford University, Stanford, CA, USA
- Department of Medicine, Division of Stem Cell Transplantation and Cell Therapy, School of Medicine, Stanford University, Stanford, CA, USA
| | - Vadim N Gladyshev
- Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Steve Horvath
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, CA, USA
- Altos Labs, San Diego, CA, USA
| | - Michael P Snyder
- Department of Genetics, School of Medicine, Stanford University, Stanford, CA, USA.
- Center for Genomics and Personalized Medicine, Stanford University, Stanford, CA, USA.
| | - Vittorio Sebastiano
- Department of Obstetrics & Gynecology, School of Medicine, Stanford University, Stanford, CA, USA.
- Institute for Stem Cell Biology and Regenerative Medicine, School of Medicine, Stanford University, Stanford, CA, USA.
- Stanford Maternal & Child Health Research Institute, Stanford University, Stanford, CA, USA.
| |
Collapse
|
50
|
Armero AS, Buckley RM, Mboning L, Spatola GJ, Horvath S, Pellegrini M, Ostrander EA. Co-analysis of methylation platforms for signatures of biological aging in the domestic dog reveals previously unexplored confounding factors. Aging (Albany NY) 2024; 16:10724-10748. [PMID: 38985449 PMCID: PMC11272130 DOI: 10.18632/aging.206012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2023] [Accepted: 05/29/2024] [Indexed: 07/11/2024]
Abstract
Chronological age reveals the number of years an individual has lived since birth. By contrast, biological age varies between individuals of the same chronological age at a rate reflective of physiological decline. Differing rates of physiological decline are related to longevity and result from genetics, environment, behavior, and disease. The creation of methylation biological age predictors is a long-standing challenge in aging research due to the lack of individual pre-mortem longevity data. The consistent differences in longevity between domestic dog breeds enable the construction of biological age estimators which can, in turn, be contrasted with methylation measurements to elucidate mechanisms of biological aging. We draw on three flagship methylation studies using distinct measurement platforms and tissues to assess the feasibility of creating biological age methylation clocks in the dog. We expand epigenetic clock building strategies to accommodate phylogenetic relationships between individuals, thus controlling for the use of breed standard metrics. We observe that biological age methylation clocks are affected by population stratification and require heavy parameterization to achieve effective predictions. Finally, we observe that methylation-related markers reflecting biological age signals are rare and do not colocalize between datasets.
Collapse
Affiliation(s)
- Aitor Serres Armero
- Cancer Genetics and Comparative Genomics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | - Reuben M. Buckley
- Cancer Genetics and Comparative Genomics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | - Lajoyce Mboning
- Department of Chemistry and Biochemistry, University of California Los Angeles, Los Angeles, CA 90095, USA
| | - Gabriella J. Spatola
- Cancer Genetics and Comparative Genomics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | - Steve Horvath
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, CA 90095, USA
- Altos Labs Inc, Cambridge, United Kingdom
| | - Matteo Pellegrini
- Department of Molecular, Cell and Developmental Biology, University of Los Angeles, Los Angeles, CA 90095, USA
| | - Elaine A. Ostrander
- Cancer Genetics and Comparative Genomics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892, USA
| |
Collapse
|