1
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Heinze SS, Hodgins ML, Howlett SE. The impact of a selective androgen receptor modulator (RAD140) on frailty and underlying mechanisms in older male and female C57Bl/6 mice. Mech Ageing Dev 2025; 225:112054. [PMID: 40158703 DOI: 10.1016/j.mad.2025.112054] [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: 01/10/2025] [Revised: 03/18/2025] [Accepted: 03/25/2025] [Indexed: 04/02/2025]
Abstract
BACKGROUND Androgen receptors (AR) are promising therapeutic targets for mechanisms of aging, including chronic inflammation, lean mass loss, and worsening bone health. We investigated the impact of RAD140, a selective AR modulator that activates ARs, on frailty and underlying mechanisms in older C57BL/6 mice. METHODS Mice (23.7-25.5 months; N = 21 males; 15 females) received RAD140 (5 mg/kg/day) or placebo (DMSO) daily for 6-weeks. Frailty (clinical and lab-based), body composition, circulating inflammatory markers, grip strength, and genes relating to function/hypertrophy in quadriceps femoris muscles were assessed. RESULTS Despite no differences in frailty between treatment and control, there were positive effects in male, but not female mice. RAD140 treated male mice had preserved lean mass (p = 0.024) and bone mineral density (p = 0.004) and lower serum interleukin-6 (p = 0.043) versus controls. In contrast, benefits to body composition and inflammatory markers were not seen in females. In either sex, grip strength, fat mass, and skeletal muscle genes were unaffected. CONCLUSION Six-weeks of RAD140 treatment did not affect frailty in older male or female mice. The beneficial effects in lean mass, bone mineral density, and systemic inflammation warrant longer treatments to explore any positive impact on frailty in males. RAD140 may not be ideal for achieving these in females.
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Affiliation(s)
- Stefan S Heinze
- Department of Pharmacology, Dalhousie University, Halifax, NS, Canada.
| | - Maddison L Hodgins
- Department of Medicine (Geriatric Medicine), Dalhousie University, Halifax, NS, Canada
| | - Susan E Howlett
- Department of Pharmacology, Dalhousie University, Halifax, NS, Canada; Department of Medicine (Geriatric Medicine), Dalhousie University, Halifax, NS, Canada
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2
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Salimi S, Vehtari A, Salive M, Kaeberlein M, Raftery D, Ferrucci L. Health octo tool matches personalized health with rate of aging. Nat Commun 2025; 16:4007. [PMID: 40325006 PMCID: PMC12053696 DOI: 10.1038/s41467-025-58819-x] [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: 02/26/2021] [Accepted: 04/03/2025] [Indexed: 05/07/2025] Open
Abstract
Medical practice mainly addresses single diseases, neglecting multimorbidity as a heterogeneous health decline across organ systems. Aging is a multidimensional process and cannot be captured by a single metric. Therefore, we assessed global health in longitudinal studies, BLSA (n = 907), InCHIANTI (n = 986), and NHANES (n = 40,790), by examining disease severities in 13 bodily systems, generating the Body Organ Disease Number (BODN), reflecting progressive system morbidities. We used Bayesian ordinal models, regressing BODN over organ specific and all organs disease severities to obtain Body System-Specific Clocks and the Body Clock, respectively. The Body Clock is BODN weighted by the posterior coefficient of diseases for each individual. It supersedes the frailty index, predicting disability, geriatric syndrome, SPPB, and mortality with ≥90% accuracy. The Health Octo Tool, derived from Bodily System-Specific Clocks, the Body Clock and Clocks that incorporate walking speed and disability and their aging rates, captures multidimensional aging heterogeneity across organs and individuals.
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Affiliation(s)
- Sh Salimi
- Department of Anesthesiology and Pain Medicine, University of Washington, Seattle, WA, USA.
| | - A Vehtari
- Department of Computer Science, Aalto University, Aalto, Finland
| | - M Salive
- Division of Geriatrics and Clinical Gerontology, National Institute on Aging, Bethesda, MD, USA
| | | | - D Raftery
- Department of Anesthesiology and Pain Medicine, University of Washington, Northwest Metabolomics Research Center, Seattle, WA, USA
| | - L Ferrucci
- Intramural Research Program, National Institute on Aging, Baltimore, MD, USA
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3
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Lyu D, Wang M, Qiu L, Deng R, Hu S, Zhang Y. Deletion of Nrf1α exacerbates oxidative stress-induced cellular senescence by disrupting cell homeostasis. BIOCHIMICA ET BIOPHYSICA ACTA. MOLECULAR CELL RESEARCH 2025; 1872:119970. [PMID: 40280334 DOI: 10.1016/j.bbamcr.2025.119970] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/12/2024] [Revised: 04/07/2025] [Accepted: 04/22/2025] [Indexed: 04/29/2025]
Abstract
Cellular senescence is recognized as a fundamental hallmark contributing to ageing and various age-related diseases, with oxidative stress playing a critical initiating role in their pathological processes. However, the anti-senescence potential of the antioxidant nuclear factor erythroid-derived 2-like 1 (Nrf1, encoded by Nfe2l1) remains elusive, despite accumulating evidence demonstrating its role as an indispensable redox-determining transcription factor for maintaining cellular homeostasis and organ integrity. This study reveals that deletion of Nrf1α significantly elevates senescence characteristics in Nrf1α-/--deficient cells, as evidenced by two distinct experimental models. These cells exhibit heightened activity of senescence-associated β-galactosidase and progressive senescence-associated secretory phenotype (SASP), accompanied by decreased cell vitality and intensified cell cycle arrest. Further investigation uncovers that this acceleration of oxidative stress-induced senescence results from increased disturbance in cellular homeostasis. The Nrf1α-/- deficiency leads to STAG2- and SMC3-dependent chromosomal stability disruption and autophagy dysfunction, albeit being accompanied by excessive accumulation of Nrf2 (encoded by Nfe2l2). The aberrantly hyperactive Nrf2 cannot effectively counteract the escalating disturbance of cellular homeostasis caused by Nrf1α-/-. This study provides evidence supporting Nrf1α's essential cytoprotective function against stress-induced cellular senescence, highlighting its indispensable contribution to maintaining robust cell homeostasis during the senescence pathophysiological process.
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Affiliation(s)
- Da Lyu
- The Laboratory of Cell Biochemistry and Topogenetic Regulation, College of Bioengineering, Chongqing University, No. 174 Shazheng Street, Shapingba District, Chongqing 400044, China.
| | - Meng Wang
- The Laboratory of Cell Biochemistry and Topogenetic Regulation, College of Bioengineering, Chongqing University, No. 174 Shazheng Street, Shapingba District, Chongqing 400044, China.
| | - Lu Qiu
- The Laboratory of Cell Biochemistry and Topogenetic Regulation, College of Bioengineering, Chongqing University, No. 174 Shazheng Street, Shapingba District, Chongqing 400044, China; School of Life Sciences, Zhengzhou University, No. 100 Kexue Avenue, Zhongyuan District, Zhengzhou 450001, Henan, China
| | - Rongzhen Deng
- The Laboratory of Cell Biochemistry and Topogenetic Regulation, College of Bioengineering, Chongqing University, No. 174 Shazheng Street, Shapingba District, Chongqing 400044, China
| | - Shaofan Hu
- The Laboratory of Cell Biochemistry and Topogenetic Regulation, College of Bioengineering, Chongqing University, No. 174 Shazheng Street, Shapingba District, Chongqing 400044, China.
| | - Yiguo Zhang
- The Laboratory of Cell Biochemistry and Topogenetic Regulation, College of Bioengineering, Chongqing University, No. 174 Shazheng Street, Shapingba District, Chongqing 400044, China; School of Life and Health Sciences, Fuyao University of Science and Technology (FyUST), No. 104 Wisdom Avenue, Nanyu Town, Minhou High-Tech District, Fuzhou 350109, Fujian, China.
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4
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Collinge CW, Razzoli M, Bartolomucci A. The Mouse Social Frailty Index (mSFI): A Standardized Protocol. Bio Protoc 2025; 15:e5272. [PMID: 40291432 PMCID: PMC12021592 DOI: 10.21769/bioprotoc.5272] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2024] [Revised: 03/11/2025] [Accepted: 03/11/2025] [Indexed: 04/30/2025] Open
Abstract
The advent of geroscience engendered the development of approaches to quantify the aging process and estimate biological age on an individual level. Recognizing that declines observed in aging are not only physical but also social led us to develop a mouse Social Frailty Index (mSFI) designed to quantify age-related impairments of social functioning in mice. The mSFI consists of seven behavioral assays that measure essential facets of social behavioral functioning in mice: social communication, social interaction, and social functional ability. The assays that comprise the mSFI are all minimally disruptive, relatively simple to execute, and optimized for compatibility with longitudinal studies utilizing experimental interventions relevant to geroscience. The mSFI is conducted over AM and PM sessions spanning a maximum of 3.5 days, using materials common to most animal facilities. The data for all assays is obtained observationally, manually recorded, and entered into predefined template sheets that automate the computation of the mSFI. We have demonstrated the validity and applicability of the mSFI across multiple laboratory sites and experiments. This index has proven to discriminate between differential trajectories of biological aging driven by sex, progeria, or social stress-relevant contexts. The mSFI represents a novel index to quantify trajectories of biological aging in mice, and its application may help elucidate the social dimensions of the aging process. Key features • The mSFI is a comprehensive assessment for the evaluation of impairment in social behavioral functioning related to aging in mice. • Minimally disruptive, relatively simple, commonly used high-throughput assays of spontaneous social behavior that are optimized for compatibility with longitudinal studies of aging. • The protocol spans AM and PM sessions over 3.5 days maximum; the sequence of individual assays is flexible by design. • The mSFI requires materials common to most animal research facilities. • mSFI application is compatible with most experimental treatments, social behavioral paradigms, longitudinal within-subject designs, and genetically modified mouse models.
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Affiliation(s)
- Charles W. Collinge
- Department of Integrative Biology & Physiology, University of Minnesota, Minneapolis, MN, USA
| | - Maria Razzoli
- Department of Integrative Biology & Physiology, University of Minnesota, Minneapolis, MN, USA
| | - Alessandro Bartolomucci
- Department of Integrative Biology & Physiology, University of Minnesota, Minneapolis, MN, USA
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5
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Hernández-Arciga U, Stamenkovic C, Yadav S, Nicoletti C, Albalawy WN, Al hammood F, Gonzalez TF, Naikwadi MU, Graham A, Smarz C, Little GJ, Williams SPG, McMahon B, Sipula IJ, Vandevender AM, Chuan B, Cooke D, Pinto AFM, Flores LC, Hartman HL, Diedrich JK, Brooke RT, Alder JK, Frahm KA, Pascal LE, Stolt E, Troensegaard H, Øvrebø B, Elshorbagy A, Molina E, Vinknes KJ, Tan RJ, Weisz OA, Bueno M, Eickelberg O, Steinhauser ML, Finkel T, Ables GP, Ikeno Y, Olsen T, Sacco A, Jurczak MJ, Sukoff Rizzo SJ, Parkhitko AA. Dietary methionine restriction started late in life promotes healthy aging in a sex-specific manner. SCIENCE ADVANCES 2025; 11:eads1532. [PMID: 40238871 PMCID: PMC12002124 DOI: 10.1126/sciadv.ads1532] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/04/2024] [Accepted: 03/11/2025] [Indexed: 04/18/2025]
Abstract
Aging is associated with dysregulated methionine metabolism and increased levels of enzymes in the tyrosine degradation pathway (TDP). To investigate the efficacy of targeting either methionine metabolism or the TDP for healthspan improvement in advanced age, we initiated dietary MetR or TDP inhibition in 18-month-old C57BL/6J mice. MetR significantly improved neuromuscular function, metabolic health, lung function, and frailty. In addition, we confirmed improved neuromuscular function from dietary MetR in 5XFAD mice, whose weight was not affected by MetR. We did not observe benefits with TDP inhibition. Single-nucleus RNA and ATAC sequencing of muscle revealed cell type-specific responses to MetR, although MetR did not significantly affect mouse aging epigenetic clock markers. Similarly, an 8-week MetR intervention in a human trial (NCT04701346) showed no significant impact on epigenetic clocks. The observed benefits from late-life MetR provide translational rationale to develop MetR mimetics as an antiaging intervention.
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Affiliation(s)
| | - Ceda Stamenkovic
- Development, Aging, and Regeneration Program, Sanford Burnham Prebys Medical Discovery Institute, La Jolla, CA, USA
- Graduate School of Biomedical Sciences, Sanford Burnham Prebys Medical Discovery Institute, La Jolla, CA, USA
| | - Shweta Yadav
- Aging Institute of UPMC and the University of Pittsburgh, Pittsburgh, PA, USA
| | - Chiara Nicoletti
- Development, Aging, and Regeneration Program, Sanford Burnham Prebys Medical Discovery Institute, La Jolla, CA, USA
| | - Wafaa N. Albalawy
- Renal Electrolyte Division, Department of Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
- Department of Human Genetics, School of Public Health, University of Pittsburgh, PA, USA
| | - Farazdaq Al hammood
- Aging Institute of UPMC and the University of Pittsburgh, Pittsburgh, PA, USA
| | | | | | - Aidan Graham
- Aging Institute of UPMC and the University of Pittsburgh, Pittsburgh, PA, USA
| | - Christian Smarz
- Aging Institute of UPMC and the University of Pittsburgh, Pittsburgh, PA, USA
| | - Gabriela J. Little
- Aging Institute of UPMC and the University of Pittsburgh, Pittsburgh, PA, USA
| | | | - Brenda McMahon
- Vascular Medicine Institute, Department of Medicine, University of Pittsburgh, PA, USA
| | - Ian J. Sipula
- Center for Metabolism and Mitochondrial Medicine, Department of Medicine, University of Pittsburgh, Pittsburgh, PA, USA
- Division of Endocrinology and Metabolism, Department of Medicine, University of Pittsburgh, Pittsburgh, PA, USA
| | - Amber M. Vandevender
- Center for Metabolism and Mitochondrial Medicine, Department of Medicine, University of Pittsburgh, Pittsburgh, PA, USA
- Division of Endocrinology and Metabolism, Department of Medicine, University of Pittsburgh, Pittsburgh, PA, USA
| | - Byron Chuan
- Pulmonary, Allergy, Critical Care, and Sleep Medicine, University of Pittsburgh, Pittsburgh, PA, USA
| | - Diana Cooke
- Orentreich Foundation for the Advancement of Science Inc., Cold Spring, NY, USA
| | - Antonio F. M. Pinto
- Mass Spectrometry Core for Proteomics and Metabolomics, Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Lisa C. Flores
- Barshop Institute for Longevity and Aging Studies, San Antonio, TX, USA
| | - Hannah L. Hartman
- Renal Electrolyte Division, Department of Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Jolene K. Diedrich
- Mass Spectrometry Core for Proteomics and Metabolomics, Salk Institute for Biological Studies, La Jolla, CA, USA
| | | | - Jonathan K. Alder
- Pulmonary, Allergy, Critical Care, and Sleep Medicine, University of Pittsburgh, Pittsburgh, PA, USA
- Dorothy P. and Richard P. Simmons Center for Interstitial Lung Disease, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Krystle A. Frahm
- Department of Pharmacology and Chemical Biology, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Laura E. Pascal
- Department of Pharmacology and Chemical Biology, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Emma Stolt
- Department of Nutrition, Institute of Basic Medical Sciences, University of Oslo, Oslo, Norway
| | - Hannibal Troensegaard
- Department of Nutrition, Institute of Basic Medical Sciences, University of Oslo, Oslo, Norway
| | - Bente Øvrebø
- Department of Food Safety, Norwegian Institute of Public Health, Oslo, Norway
| | - Amany Elshorbagy
- Department of Physiology, Faculty of Medicine, University of Alexandria, Alexandria, Egypt
- Department of Pharmacology, University of Oxford, Oxford, UK
| | - Elsa Molina
- Next Generation Sequencing Core, Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Kathrine J. Vinknes
- Department of Nutrition, Institute of Basic Medical Sciences, University of Oslo, Oslo, Norway
| | - Roderick J. Tan
- Renal Electrolyte Division, Department of Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Ora A. Weisz
- Renal Electrolyte Division, Department of Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Marta Bueno
- Pulmonary, Allergy, Critical Care, and Sleep Medicine, University of Pittsburgh, Pittsburgh, PA, USA
- Dorothy P. and Richard P. Simmons Center for Interstitial Lung Disease, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Oliver Eickelberg
- Pulmonary, Allergy, Critical Care, and Sleep Medicine, University of Pittsburgh, Pittsburgh, PA, USA
- Dorothy P. and Richard P. Simmons Center for Interstitial Lung Disease, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Matthew L. Steinhauser
- Aging Institute of UPMC and the University of Pittsburgh, Pittsburgh, PA, USA
- Center for Human Integrative Physiology, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
- Division of Cardiology, Department of Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Toren Finkel
- Aging Institute of UPMC and the University of Pittsburgh, Pittsburgh, PA, USA
| | - Gene P. Ables
- Orentreich Foundation for the Advancement of Science Inc., Cold Spring, NY, USA
| | - Yuji Ikeno
- Barshop Institute for Longevity and Aging Studies, San Antonio, TX, USA
- Department of Pathology, The University of Texas Health Science Center at San Antonio, San Antonio, TX, USA
- Geriatric Research and Education Center, Audie L. Murphy VA Hospital South Texas Veterans Health Care System, San Antonio, TX, USA
| | - Thomas Olsen
- Department of Nutrition, Institute of Basic Medical Sciences, University of Oslo, Oslo, Norway
| | - Alessandra Sacco
- Development, Aging, and Regeneration Program, Sanford Burnham Prebys Medical Discovery Institute, La Jolla, CA, USA
| | - Michael J. Jurczak
- Center for Metabolism and Mitochondrial Medicine, Department of Medicine, University of Pittsburgh, Pittsburgh, PA, USA
- Division of Endocrinology and Metabolism, Department of Medicine, University of Pittsburgh, Pittsburgh, PA, USA
| | | | - Andrey A. Parkhitko
- Aging Institute of UPMC and the University of Pittsburgh, Pittsburgh, PA, USA
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6
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Kuchel GA, Hevener AL, Ruby JG, Sebastiani P, Kumar V. Workshop Report-Heterogeneity and Successful Aging Part I: Heterogeneity in Aging-Challenges and Opportunities. J Gerontol A Biol Sci Med Sci 2025; 80:glaf023. [PMID: 40052564 DOI: 10.1093/gerona/glaf023] [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: 11/24/2024] [Indexed: 05/13/2025] Open
Abstract
Historically, aging research has focused primarily on the study of differences in means of varied measures obtained at different ages. However, growing evidence has shown that for many parameters, variability in measurements obtained both between- and within-age groups increases with aging. Moreover, growing heterogeneity may become especially apparent when examined via longitudinal as opposed to cross-sectional aging data. Efforts to deconvolute and better understand such heterogeneity present remarkable translational opportunities for developing targeted and more effective interventions into aging. Here, we present Part I, a summary of the NIA Heterogeneity and Successful Aging workshop virtually held in May 2023.
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Affiliation(s)
- George A Kuchel
- UConn Center on Aging, University of Connecticut School of Medicine, Farmington, Connecticut, USA
| | - Andrea L Hevener
- Division of Endocrinology, Diabetes and Hypertension, Department of Medicine, University of California, Los Angeles, Los Angeles, California, USA
| | - J Graham Ruby
- Calico Life Sciences LLC, South San Francisco, California, USA
| | - Paola Sebastiani
- Institute for Clinical Research and Health Policy Studies, Tufts Medical Center, Boston, Massachusetts, USA
| | - Vivek Kumar
- The Jackson Laboratory, Bar Harbor, Maine, USA
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7
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Jayne L, Lavin-Peter A, Roessler J, Tyshkovskiy A, Antoszewski M, Ren E, Markovski A, Sun S, Yao H, Sankaran VG, Gladyshev VN, Brooke RT, Horvath S, Griffith EC, Hrvatin S. A torpor-like state in mice slows blood epigenetic aging and prolongs healthspan. NATURE AGING 2025; 5:437-449. [PMID: 40055478 PMCID: PMC11922754 DOI: 10.1038/s43587-025-00830-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/20/2024] [Accepted: 02/03/2025] [Indexed: 03/12/2025]
Abstract
Torpor and hibernation are extreme physiological adaptations of homeotherms associated with pro-longevity effects. Yet the underlying mechanisms of how torpor affects aging, and whether hypothermic and hypometabolic states can be induced to slow aging and increase healthspan, remain unknown. Here we demonstrate that the activity of a spatially defined neuronal population in the preoptic area, which has previously been identified as a torpor-regulating brain region, is sufficient to induce a torpor-like state (TLS) in mice. Prolonged induction of TLS slows epigenetic aging across multiple tissues and improves healthspan. We isolate the effects of decreased metabolic rate, long-term caloric restriction, and decreased core body temperature (Tb) on blood epigenetic aging and find that the decelerating effect of TLSs on aging is mediated by decreased Tb. Taken together, our findings provide novel mechanistic insight into the decelerating effects of torpor and hibernation on aging and support the growing body of evidence that Tb is an important mediator of the aging processes.
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Affiliation(s)
- Lorna Jayne
- Whitehead Institute for Biomedical Research and Department of Biology, Massachusetts Institute of Technology, Cambridge, MA, USA
- Department of Neurobiology, Harvard Medical School, Boston, MA, USA
- Department of Neurobiology, Stanford University Medical Center, Stanford, CA, USA
| | - Aurora Lavin-Peter
- Whitehead Institute for Biomedical Research and Department of Biology, Massachusetts Institute of Technology, Cambridge, MA, USA
- Department of Neurobiology, Harvard Medical School, Boston, MA, USA
| | - Julian Roessler
- Whitehead Institute for Biomedical Research and Department of Biology, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Alexander Tyshkovskiy
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Mateusz Antoszewski
- Division of Hematology/Oncology, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
- Department of Pediatric Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Erika Ren
- Department of Neurobiology, Harvard Medical School, Boston, MA, USA
| | - Aleksandar Markovski
- Whitehead Institute for Biomedical Research and Department of Biology, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Senmiao Sun
- Department of Neurobiology, Harvard Medical School, Boston, MA, USA
- Program in Neuroscience, Harvard Medical School, Boston, MA, USA
| | - Hanqi Yao
- Department of Neurobiology, Harvard Medical School, Boston, MA, USA
| | - Vijay G Sankaran
- Division of Hematology/Oncology, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
- Department of Pediatric Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Vadim N Gladyshev
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | | | - Steve Horvath
- Epigenetic Clock Development Foundation, Torrance, CA, USA
- Altos Labs, Cambridge, UK
| | - Eric C Griffith
- Department of Neurobiology, Harvard Medical School, Boston, MA, USA
| | - Sinisa Hrvatin
- Whitehead Institute for Biomedical Research and Department of Biology, Massachusetts Institute of Technology, Cambridge, MA, USA.
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8
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Collinge CW, Razzoli M, Mansk R, McGonigle S, Lamming DW, Pacak CA, van der Pluijm I, Niedernhofer L, Bartolomucci A. The mouse Social Frailty Index (mSFI): a novel behavioral assessment for impaired social functioning in aging mice. GeroScience 2025; 47:85-107. [PMID: 38987495 PMCID: PMC11872866 DOI: 10.1007/s11357-024-01263-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2024] [Accepted: 06/23/2024] [Indexed: 07/12/2024] Open
Abstract
Various approaches exist to quantify the aging process and estimate biological age on an individual level. Frailty indices based on an age-related accumulation of physical deficits have been developed for human use and translated into mouse models. However, declines observed in aging are not limited to physical functioning but also involve social capabilities. The concept of "social frailty" has been recently introduced into human literature, but no index of social frailty exists for laboratory mice yet. To fill this gap, we developed a mouse Social Frailty Index (mSFI) consisting of seven distinct assays designed to quantify social functioning which is relatively simple to execute and is minimally invasive. Application of the mSFI in group-housed male C57BL/6 mice demonstrated a progressively elevated levels of social frailty through the lifespan. Conversely, group-housed females C57BL/6 mice manifested social frailty only at a very old age. Female mice also showed significantly lower mSFI score from 10 months of age onward when compared to males. We also applied the mSFI in male C57BL/6 mice under chronic subordination stress and in chronic isolation, both of which induced larger increases in social frailty compared to age-matched group-housed males. Lastly, we show that the mSFI is enhanced in mouse models that show accelerated biological aging such as progeroid Ercc1-/Δ and Xpg-/- mice of both sexes compared to age matched littermate wild types. In summary, the mSFI represents a novel index to quantify trajectories of biological aging in mice and may help elucidate links between impaired social behavior and the aging process.
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Affiliation(s)
- Charles W Collinge
- Department of Integrative Biology and Physiology, University of Minnesota, Minneapolis, MN, USA
| | - Maria Razzoli
- Department of Integrative Biology and Physiology, University of Minnesota, Minneapolis, MN, USA
| | - Rachel Mansk
- Department of Integrative Biology and Physiology, University of Minnesota, Minneapolis, MN, USA
| | - Seth McGonigle
- Department of Integrative Biology and Physiology, University of Minnesota, Minneapolis, MN, USA
| | - Dudley W Lamming
- Department of Medicine, University of Wisconsin, Madison, WI, USA
- William S. Middleton Memorial Veterans Hospital, Madison, WI, USA
| | - Christina A Pacak
- Greg Marzolf Jr. Muscular Dystrophy Center & Department of Neurology, University of Minnesota, Minneapolis, MN, USA
| | - Ingrid van der Pluijm
- Department of Molecular Genetics, and Department of Vascular Surgery, Cardiovascular Institute, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Laura Niedernhofer
- Department of Biochemistry, Molecular Biology and Biophysics, University of Minnesota, Minneapolis, MN, USA
- Institute on the Biology of Aging and Metabolism, University of Minnesota, Minneapolis, MN, USA
| | - Alessandro Bartolomucci
- Department of Integrative Biology and Physiology, University of Minnesota, Minneapolis, MN, USA.
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9
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Lamming DW. Quantification of healthspan in aging mice: introducing FAMY and GRAIL. GeroScience 2024; 46:4203-4215. [PMID: 38755467 PMCID: PMC11336093 DOI: 10.1007/s11357-024-01200-5] [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: 04/24/2024] [Accepted: 05/08/2024] [Indexed: 05/18/2024] Open
Abstract
The population around the world is graying, and as many of these individuals will spend years suffering from the burdens of age associated diseases, understanding how to increase healthspan, defined as the period of life free from disease and disability, is an urgent priority of geroscience research. The lack of agreed-upon quantitative metrics for measuring healthspan in aging mice has slowed progress in identifying interventions that do not simply increase lifespan, but also healthspan. Here, we define FAMY (Frailty-Adjusted Mouse Years) and GRAIL (Gauging Robust Aging when Increasing Lifespan) as new summary statistics for quantifying healthspan in mice. FAMY integrates lifespan data with longitudinal measurements of a widely utilized clinical frailty index, while GRAIL incorporates these measures and also adds information from widely utilized healthspan assays and the hallmarks of aging. Both metrics are conceptually similar to quality-adjusted life years (QALY), a widely utilized measure of disease burden in humans, and can be readily calculated from data acquired during longitudinal and cross-sectional studies of mouse aging. We find that interventions generally thought to promote health, including calorie restriction, robustly improve healthspan as measured by FAMY and GRAIL. Finally, we show that the use of GRAIL provides new insights, and identify dietary restriction of protein or isoleucine as interventions that robustly promote healthspan but not longevity in female HET3 mice. We suggest that the routine integration of these measures into studies of aging in mice will allow the identification and development of interventions that promote healthy aging even in the absence of increased lifespan.
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Affiliation(s)
- Dudley W Lamming
- Department of Medicine, University of Wisconsin-Madison, 1685 Highland Ave, MFCB Rm 4147, Madison, WI, 53705, USA.
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10
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Luciano A, Robinson L, Garland G, Lyons B, Korstanje R, Di Francesco A, Churchill GA. Longitudinal fragility phenotyping contributes to the prediction of lifespan and age-associated morbidity in C57BL/6 and Diversity Outbred mice. GeroScience 2024; 46:4937-4954. [PMID: 38935230 PMCID: PMC11639350 DOI: 10.1007/s11357-024-01226-9] [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: 02/07/2024] [Accepted: 05/24/2024] [Indexed: 06/28/2024] Open
Abstract
Aging studies in mammalian models often depend on natural lifespan data as a primary outcome. Tools for lifespan prediction could accelerate these studies and reduce the need for veterinary intervention. Here, we leveraged large-scale longitudinal frailty and lifespan data on two genetically distinct mouse cohorts to evaluate noninvasive strategies to predict life expectancy in mice. We applied a modified frailty assessment, the Fragility Index, derived from existing frailty indices with additional deficits selected by veterinarians. We developed an ensemble machine learning classifier to predict imminent mortality (95% proportion of life lived [95PLL]). Our algorithm represented improvement over previous predictive criteria but fell short of the level of reliability that would be needed to make advanced prediction of lifespan and thus accelerate lifespan studies. Highly sensitive and specific frailty-based predictive endpoint criteria for aged mice remain elusive. While frailty-based prediction falls short as a surrogate for lifespan, it did demonstrate significant predictive power and as such must contain information that could be used to inform the conclusion of aging experiments. We propose a frailty-based measure of healthspan as an alternative target for aging research and demonstrate that lifespan and healthspan criteria reveal distinct aspects of aging in mice.
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11
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Weibel CJ, Dasari MR, Jansen DA, Gesquiere LR, Mututua RS, Warutere JK, Siodi LI, Alberts SC, Tung J, Archie EA. Using non-invasive behavioral and physiological data to measure biological age in wild baboons. GeroScience 2024; 46:4059-4074. [PMID: 38693466 PMCID: PMC11336142 DOI: 10.1007/s11357-024-01157-5] [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: 01/03/2024] [Accepted: 04/05/2024] [Indexed: 05/03/2024] Open
Abstract
Biological aging is near-ubiquitous in the animal kingdom, but its timing and pace vary between individuals and over lifespans. Prospective, individual-based studies of wild animals-especially non-human primates-help identify the social and environmental drivers of this variation by indicating the conditions and exposure windows that affect aging processes. However, measuring individual biological age in wild primates is challenging because several of the most promising methods require invasive sampling. Here, we leverage observational data on behavior and physiology, collected non-invasively from 319 wild female baboons across 2402 female-years of study, to develop a composite predictor of age: the non-invasive physiology and behavior (NPB) clock. We found that age predictions from the NPB clock explained 51% of the variation in females' known ages. Further, deviations from the clock's age predictions predicted female survival: females predicted to be older than their known ages had higher adult mortality. Finally, females who experienced harsh early-life conditions were predicted to be about 6 months older than those who grew up in more benign conditions. While the relationship between early adversity and NPB age is noisy, this estimate translates to a predicted 2-3 year reduction in mean adult lifespan in our model. A constraint of our clock is that it is tailored to data collection approaches implemented in our study population. However, many of the clock's components have analogs in other populations, suggesting that non-invasive data can provide broadly applicable insight into heterogeneity in biological age in natural populations.
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Affiliation(s)
- Chelsea J Weibel
- Department of Biological Sciences, University of Notre Dame, Notre Dame, IN, USA
| | - Mauna R Dasari
- Department of Biological Sciences, University of Notre Dame, Notre Dame, IN, USA
| | - David A Jansen
- Department of Biological Sciences, University of Notre Dame, Notre Dame, IN, USA
| | | | - Raphael S Mututua
- Amboseli Baboon Research Project, Amboseli National Park, Kajiado, Kenya
| | - J Kinyua Warutere
- Amboseli Baboon Research Project, Amboseli National Park, Kajiado, Kenya
| | - Long'ida I Siodi
- Amboseli Baboon Research Project, Amboseli National Park, Kajiado, Kenya
| | - Susan C Alberts
- Department of Biology, Duke University, Durham, NC, USA
- Department of Evolutionary Anthropology, Duke University, Durham, NC, USA
- Duke University Population Research Institute, Duke University, Durham, NC, USA
| | - Jenny Tung
- Department of Biology, Duke University, Durham, NC, USA
- Department of Evolutionary Anthropology, Duke University, Durham, NC, USA
- Duke University Population Research Institute, Duke University, Durham, NC, USA
- Department of Primate Behavior and Evolution, Max Planck Institute for Evolutionary Anthropology, 04103, Leipzig, Germany
- Canadian Institute for Advanced Research, Toronto, M5G 1M1, Canada
- Faculty of Life Sciences, Institute of Biology, Leipzig University, Leipzig, Germany
| | - Elizabeth A Archie
- Department of Biological Sciences, University of Notre Dame, Notre Dame, IN, USA.
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12
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Niu K, Chang L, Zhang R, Jiang Y, Shen X, Lu X, Zhang S, Ma K, Zhao Z, Li M, Hou Y, Wu Y. Bazi Bushen mitigates age-related muscular atrophy by alleviating cellular senescence of skeletal muscle. J Tradit Complement Med 2024; 14:510-521. [PMID: 39262657 PMCID: PMC11385411 DOI: 10.1016/j.jtcme.2024.01.009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2023] [Revised: 01/06/2024] [Accepted: 01/21/2024] [Indexed: 09/13/2024] Open
Abstract
BACKGROUND AND AIM Muscular atrophy is one of the most common age-related conditions characterized by the deterioration of skeletal muscle structures and impaired functions. It is associated with cellular senescence and chronic inflammation, which impair the function of muscle stem cells. Bazi Bushen (BZBS) is a patent compound Chinese medicine that has been shown to have anti-aging effects in various animal models. In this study, we investigated the effects and mechanisms of BZBS on muscular atrophy in naturally aged mice. EXPERIMENTAL PROCEDURE A muscular atrophy model of naturally aged mice (18 months) was employed with administration of BZBS (2 g/kg/d, 1 g/kg/d) and nicotinamide mononucleotide (NMN, 200 mg/kg/d). After six months of drug administration, muscle weight loss, muscle function and muscle histopathology were measured to evaluate the therapeutic effect of BZBS. The expression of cellular senescence, inflammatory and satellite cell-related factors were used to assess the effects of BZBS in inhibiting cellular senescence, reducing inflammation and improving muscle atrophy. RESULTS AND CONCLUSION Compared with age matched natural aging mice, we found that BZBS improved muscle strength, mass, and morphology by reducing senescent cells, inflammatory cytokines, and intermyofiber fibrosis in aged muscle tissues. We also found that BZBS prevented the reduction of Pax7 positive stem cells and stimulated the activation and differentiation into myocytes. Our results suggest that BZBS might be a promising intervention in senile muscular atrophy.
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Affiliation(s)
- Kunxu Niu
- Hebei Medical University, Shijiazhuang, 050017, China
| | - Liping Chang
- National Key Laboratory for Innovation and Transformation of Luobing Theory, Shijiazhuang, 050035, China
- High-level TCM Key Disciplines of National Administration of Traditional Chinese Medicine—Luobing Theory, Shijiazhuang, 050035, China
| | - Runtao Zhang
- Hebei Medical University, Shijiazhuang, 050017, China
| | - Yuning Jiang
- College of Traditional Chinese Medicine·College of Integrated Traditional Chinese and Western Medicine, Nanjing University of Chinese Medicine, Nanjing, 210023, China
| | - Xiaogang Shen
- Hebei Medical University, Shijiazhuang, 050017, China
| | - Xuan Lu
- Hebei Medical University, Shijiazhuang, 050017, China
| | - Shixiong Zhang
- College of Traditional Chinese Medicine·College of Integrated Traditional Chinese and Western Medicine, Nanjing University of Chinese Medicine, Nanjing, 210023, China
| | - Kun Ma
- National Key Laboratory for Innovation and Transformation of Luobing Theory, Shijiazhuang, 050035, China
- High-level TCM Key Disciplines of National Administration of Traditional Chinese Medicine—Luobing Theory, Shijiazhuang, 050035, China
| | - Zhiqin Zhao
- Hebei Medical University, Shijiazhuang, 050017, China
| | - Mengnan Li
- National Key Laboratory for Innovation and Transformation of Luobing Theory, Shijiazhuang, 050035, China
- Key Laboratory of State Administration of TCM (Cardio-Cerebral Vessel Collateral Disease), Shijiazhuang, 050035, China
| | - Yunlong Hou
- Hebei Medical University, Shijiazhuang, 050017, China
- National Key Laboratory for Innovation and Transformation of Luobing Theory, Shijiazhuang, 050035, China
| | - Yiling Wu
- Hebei Medical University, Shijiazhuang, 050017, China
- National Key Laboratory for Innovation and Transformation of Luobing Theory, Shijiazhuang, 050035, China
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13
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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.
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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.
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14
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Rose RA, Howlett SE. Preclinical Studies on the Effects of Frailty in the Aging Heart. Can J Cardiol 2024; 40:1379-1393. [PMID: 38460611 DOI: 10.1016/j.cjca.2024.03.003] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2023] [Revised: 02/20/2024] [Accepted: 03/04/2024] [Indexed: 03/11/2024] Open
Abstract
Age is a major risk factor for the development of cardiovascular diseases in men and in women. However, not all people age at the same rate and those who are aging rapidly are considered frail, compared with their fit counterparts. Frailty is an important clinical challenge because those who are frail are more likely to develop and die from illnesses, including cardiovascular diseases, than fit people of the same age. This increase in susceptibility to cardiovascular diseases in older individuals might occur as the cellular and molecular mechanisms involved in the aging process facilitate structural and functional damage in the heart. Consistent with this, recent studies in murine frailty models have provided strong evidence that maladaptive cardiac remodelling in older mice is the most pronounced in mice with a high level of frailty. For example, there is evidence that ventricular hypertrophy and contractile dysfunction increase as frailty increases in aging mice. Additionally, fibrosis and slowing of conduction in the sinoatrial node and atria are proportional to the level of frailty. These modifications could predispose frail older adults to diseases like heart failure and atrial fibrillation. This preclinical work also raises the possibility that emerging interventions designed to "treat frailty" might also treat or prevent cardiovascular diseases. These findings might help to explain why frail older people are most likely to develop these disorders as they age.
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Affiliation(s)
- Robert A Rose
- Department of Cardiac Sciences, Libin Cardiovascular Institute, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada; Department of Physiology and Pharmacology, Libin Cardiovascular Institute, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada.
| | - Susan E Howlett
- Department of Pharmacology, Faculty of Medicine, Dalhousie University, Halifax, Nova Scotia, Canada; Department of Medicine (Geriatric Medicine), Faculty of Medicine, Dalhousie University, Halifax, Nova Scotia, Canada.
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15
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Sun ED, Zhou OY, Hauptschein M, Rappoport N, Xu L, Navarro Negredo P, Liu L, Rando TA, Zou J, Brunet A. Spatiotemporal transcriptomic profiling and modeling of mouse brain at single-cell resolution reveals cell proximity effects of aging and rejuvenation. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.07.16.603809. [PMID: 39071282 PMCID: PMC11275735 DOI: 10.1101/2024.07.16.603809] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/30/2024]
Abstract
Old age is associated with a decline in cognitive function and an increase in neurodegenerative disease risk1. Brain aging is complex and accompanied by many cellular changes2-20. However, the influence that aged cells have on neighboring cells and how this contributes to tissue decline is unknown. More generally, the tools to systematically address this question in aging tissues have not yet been developed. Here, we generate spatiotemporal data at single-cell resolution for the mouse brain across lifespan, and we develop the first machine learning models based on spatial transcriptomics ('spatial aging clocks') to reveal cell proximity effects during brain aging and rejuvenation. We collect a single-cell spatial transcriptomics brain atlas of 4.2 million cells from 20 distinct ages and across two rejuvenating interventions-exercise and partial reprogramming. We identify spatial and cell type-specific transcriptomic fingerprints of aging, rejuvenation, and disease, including for rare cell types. Using spatial aging clocks and deep learning models, we find that T cells, which infiltrate the brain with age, have a striking pro-aging proximity effect on neighboring cells. Surprisingly, neural stem cells have a strong pro-rejuvenating effect on neighboring cells. By developing computational tools to identify mediators of these proximity effects, we find that pro-aging T cells trigger a local inflammatory response likely via interferon-γ whereas pro-rejuvenating neural stem cells impact the metabolism of neighboring cells possibly via growth factors (e.g. vascular endothelial growth factor) and extracellular vesicles, and we experimentally validate some of these predictions. These results suggest that rare cells can have a drastic influence on their neighbors and could be targeted to counter tissue aging. We anticipate that these spatial aging clocks will not only allow scalable assessment of the efficacy of interventions for aging and disease but also represent a new tool for studying cell-cell interactions in many spatial contexts.
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Affiliation(s)
- Eric D. Sun
- Department of Biomedical Data Science, Stanford University, CA, USA
- Department of Genetics, Stanford University, CA, USA
| | - Olivia Y. Zhou
- Department of Genetics, Stanford University, CA, USA
- Stanford Biophysics Program, Stanford University, CA, USA
- Stanford Medical Scientist Training Program, Stanford University, CA, USA
| | | | | | - Lucy Xu
- Department of Genetics, Stanford University, CA, USA
- Department of Biology, Stanford University, CA, USA
| | | | - Ling Liu
- Department of Neurology, Stanford University, CA, USA
- Department of Neurology, UCLA, Los Angeles, CA, USA
- Eli and Edythe Broad Center for Regenerative Medicine and Stem Cell Biology, UCLA, Los Angeles, CA, USA
| | - Thomas A. Rando
- Department of Neurology, Stanford University, CA, USA
- Department of Neurology, UCLA, Los Angeles, CA, USA
- Eli and Edythe Broad Center for Regenerative Medicine and Stem Cell Biology, UCLA, Los Angeles, CA, USA
| | - James Zou
- Department of Biomedical Data Science, Stanford University, CA, USA
- These authors contributed equally: James Zou, Anne Brunet
| | - Anne Brunet
- Department of Genetics, Stanford University, CA, USA
- Glenn Center for the Biology of Aging, Stanford University, CA, USA
- Wu Tsai Neurosciences Institute, Stanford University, CA, USA
- These authors contributed equally: James Zou, Anne Brunet
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16
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Kane AE, Chellappa K, Schultz MB, Arnold M, Li J, Amorim J, Diener C, Zhu D, Mitchell SJ, Griffin P, Tian X, Petty C, Conway R, Walsh K, Shelerud L, Duesing C, Mueller A, Li K, McNamara M, Shima RT, Mitchell J, Bonkowski MS, de Cabo R, Gibbons SM, Wu LE, Ikeno Y, Baur JA, Rajman L, Sinclair DA. Long-term NMN treatment increases lifespan and healthspan in mice in a sex dependent manner. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.06.21.599604. [PMID: 38979132 PMCID: PMC11230277 DOI: 10.1101/2024.06.21.599604] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/10/2024]
Abstract
Nicotinamide adenine dinucleotide (NAD) is essential for many enzymatic reactions, including those involved in energy metabolism, DNA repair and the activity of sirtuins, a family of defensive deacylases. During aging, levels of NAD + can decrease by up to 50% in some tissues, the repletion of which provides a range of health benefits in both mice and humans. Whether or not the NAD + precursor nicotinamide mononucleotide (NMN) extends lifespan in mammals is not known. Here we investigate the effect of long-term administration of NMN on the health, cancer burden, frailty and lifespan of male and female mice. Without increasing tumor counts or severity in any tissue, NMN treatment of males and females increased activity, maintained more youthful gene expression patterns, and reduced overall frailty. Reduced frailty with NMN treatment was associated with increases in levels of Anerotruncus colihominis, a gut bacterium associated with lower inflammation in mice and increased longevity in humans. NMN slowed the accumulation of adipose tissue later in life and improved metabolic health in male but not female mice, while in females but not males, NMN increased median lifespan by 8.5%, possible due to sex-specific effects of NMN on NAD + metabolism. Together, these data show that chronic NMN treatment delays frailty, alters the microbiome, improves male metabolic health, and increases female mouse lifespan, without increasing cancer burden. These results highlight the potential of NAD + boosters for treating age-related conditions and the importance of using both sexes for interventional lifespan studies.
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17
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Cho HM, Choe SH, Lee JR, Park HR, Ko MG, Lee YJ, Lee HY, Park SH, Park SJ, Kim YH, Huh JW. Transcriptome analysis of cynomolgus macaques throughout their lifespan reveals age-related immune patterns. NPJ AGING 2024; 10:30. [PMID: 38902280 PMCID: PMC11189941 DOI: 10.1038/s41514-024-00158-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/07/2024] [Accepted: 06/11/2024] [Indexed: 06/22/2024]
Abstract
Despite the different perspectives by diverse research sectors spanning several decades, aging research remains uncharted territory for human beings. Therefore, we investigated the transcriptomic characteristics of eight male healthy cynomolgus macaques, and the annual sampling was designed with two individuals in four age groups. As a laboratory animal, the macaques were meticulously shielded from all environmental factors except aging. The results showed recent findings of certain immune response and the age-associated network of primate immunity. Three important aging patterns were identified and each gene clusters represented a different immune response. The increased expression pattern was predominantly associated with innate immune cells, such as Neutrophils and NK cells, causing chronic inflammation with aging whereas the other two decreased patterns were associated with adaptive immunity, especially "B cell activation" affecting antibody diversity of aging. Furthermore, the hub gene network of the patterns reflected transcriptomic age and correlated with human illness status, aiding in future human disease prediction. Our macaque transcriptome profiling results offer systematic insights into the age-related immunological features of primates.
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Affiliation(s)
- Hyeon-Mu Cho
- National Primate Research Center, Korea Research Institute of Bioscience and Biotechnology (KRIBB), Cheongju, 28116, Republic of Korea
- Department of Functional Genomics, KRIBB School of Bioscience, University of Science & Technology (UST), Cheongju, 28116, Republic of Korea
| | - Se-Hee Choe
- National Primate Research Center, Korea Research Institute of Bioscience and Biotechnology (KRIBB), Cheongju, 28116, Republic of Korea
| | - Ja-Rang Lee
- Primate Resources Center, Korea Research Institute of Bioscience and Biotechnology (KRIBB), Jeongeup, 56216, Republic of Korea
| | - Hye-Ri Park
- National Primate Research Center, Korea Research Institute of Bioscience and Biotechnology (KRIBB), Cheongju, 28116, Republic of Korea
- Department of Functional Genomics, KRIBB School of Bioscience, University of Science & Technology (UST), Cheongju, 28116, Republic of Korea
| | - Min-Gyeong Ko
- National Primate Research Center, Korea Research Institute of Bioscience and Biotechnology (KRIBB), Cheongju, 28116, Republic of Korea
- Department of Functional Genomics, KRIBB School of Bioscience, University of Science & Technology (UST), Cheongju, 28116, Republic of Korea
| | - Yun-Jung Lee
- National Primate Research Center, Korea Research Institute of Bioscience and Biotechnology (KRIBB), Cheongju, 28116, Republic of Korea
- Department of Functional Genomics, KRIBB School of Bioscience, University of Science & Technology (UST), Cheongju, 28116, Republic of Korea
| | - Hwal-Yong Lee
- National Primate Research Center, Korea Research Institute of Bioscience and Biotechnology (KRIBB), Cheongju, 28116, Republic of Korea
| | - Sung Hyun Park
- National Primate Research Center, Korea Research Institute of Bioscience and Biotechnology (KRIBB), Cheongju, 28116, Republic of Korea
| | - Sang-Je Park
- National Primate Research Center, Korea Research Institute of Bioscience and Biotechnology (KRIBB), Cheongju, 28116, Republic of Korea.
| | - Young-Hyun Kim
- National Primate Research Center, Korea Research Institute of Bioscience and Biotechnology (KRIBB), Cheongju, 28116, Republic of Korea.
| | - Jae-Won Huh
- National Primate Research Center, Korea Research Institute of Bioscience and Biotechnology (KRIBB), Cheongju, 28116, Republic of Korea.
- Department of Functional Genomics, KRIBB School of Bioscience, University of Science & Technology (UST), Cheongju, 28116, Republic of Korea.
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18
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Jayne L, Lavin-Peter A, Roessler J, Tyshkovskiy A, Antoszewski M, Ren E, Markovski A, Sun S, Yao H, Sankaran VG, Gladyshev VN, Brooke RT, Horvath S, Griffith EC, Hrvatin S. A torpor-like state (TLS) in mice slows blood epigenetic aging and prolongs healthspan. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.03.20.585828. [PMID: 38585858 PMCID: PMC10996477 DOI: 10.1101/2024.03.20.585828] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/09/2024]
Abstract
Torpor and hibernation are extreme physiological adaptations of homeotherms associated with pro-longevity effects. Yet the underlying mechanisms of how torpor affects aging, and whether hypothermic and hypometabolic states can be induced to slow aging and increase health span, remain unknown. We demonstrate that the activity of a spatially defined neuronal population in the avMLPA, which has previously been identified as a torpor-regulating brain region, is sufficient to induce a torpor like state (TLS) in mice. Prolonged induction of TLS slows epigenetic aging across multiple tissues and improves health span. We isolate the effects of decreased metabolic rate, long-term caloric restriction, and decreased core body temperature (Tb) on blood epigenetic aging and find that the pro-longevity effect of torpor-like states is mediated by decreased Tb. Taken together, our findings provide novel mechanistic insight into the pro-longevity effects of torpor and hibernation and support the growing body of evidence that Tb is an important mediator of aging processes.
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Affiliation(s)
- Lorna Jayne
- Whitehead Institute for Biomedical Research and Department of Biology, Massachusetts Institute of Technology, 455 Main Street, Cambridge, MA 02142, USA
- Department of Neurobiology, Harvard Medical School, Boston, MA 02115
- Present address: Department of Neurobiology, Stanford University Medical Center, Stanford, CA, USA
| | - Aurora Lavin-Peter
- Whitehead Institute for Biomedical Research and Department of Biology, Massachusetts Institute of Technology, 455 Main Street, Cambridge, MA 02142, USA
- Department of Neurobiology, Harvard Medical School, Boston, MA 02115
| | - Julian Roessler
- Whitehead Institute for Biomedical Research and Department of Biology, Massachusetts Institute of Technology, 455 Main Street, Cambridge, MA 02142, USA
| | - Alexander Tyshkovskiy
- Division of Genetics, Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, 02115, USA
| | - Mateusz Antoszewski
- Division of Hematology/Oncology, Boston Children’s Hospital, Harvard Medical School, Boston, MA, USA
- Department of Pediatric Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Erika Ren
- Department of Neurobiology, Harvard Medical School, Boston, MA 02115
| | - Aleksandar Markovski
- Whitehead Institute for Biomedical Research and Department of Biology, Massachusetts Institute of Technology, 455 Main Street, Cambridge, MA 02142, USA
| | - Senmiao Sun
- Department of Neurobiology, Harvard Medical School, Boston, MA 02115
- Program in Neuroscience, Harvard Medical School, Boston, MA, USA
| | - Hanqi Yao
- Department of Neurobiology, Harvard Medical School, Boston, MA 02115
| | - Vijay G. Sankaran
- Division of Hematology/Oncology, Boston Children’s Hospital, Harvard Medical School, Boston, MA, USA
- Department of Pediatric Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Vadim N. Gladyshev
- Division of Genetics, Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, 02115, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | | | - Steve Horvath
- Epigenetic Clock Development Foundation, Torrance, CA, USA
- Altos Labs, Cambridge, UK
| | - Eric C. Griffith
- Department of Neurobiology, Harvard Medical School, Boston, MA 02115
| | - Sinisa Hrvatin
- Whitehead Institute for Biomedical Research and Department of Biology, Massachusetts Institute of Technology, 455 Main Street, Cambridge, MA 02142, USA
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19
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Gu Y, Gao L, He J, Luo M, Hu M, Lin Y, Li J, Hou T, Si J, Yu Y. β-Nicotinamide mononucleotide supplementation prolongs the lifespan of prematurely aged mice and protects colon function in ageing mice. Food Funct 2024; 15:3199-3213. [PMID: 38445897 DOI: 10.1039/d3fo05221d] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/07/2024]
Abstract
Ageing is defined as the degeneration of physiological functions in numerous tissues and organs of an organism, which occurs with age. As we age, the gut undergoes a series of changes and weaknesses that may contribute to overall ageing. Emerging evidence suggests that β-nicotinamide mononucleotide (NMN) plays a role in regulating intestinal function, but there is still a lack of literature on its role in maintaining the colon health of ageing mice. In our research, Zmpste24-/- mice proved that NMN prolonged their life span and delayed senescence. This study was designed to investigate the effects of long-term intervention on regulating colon function in ageing mice. Our results indicated that NMN improved the pathology of intestinal epithelial cells and intestinal permeability by upregulating the expression of intestinal tight junction proteins and the number of goblet cells, increasing the release of anti-inflammatory factors, and increasing beneficial intestinal bacteria. NMN increased the expression of the proteins SIRT1, NMNAT2, and NMNAT3 and decreased the expression of the protein P53. It also regulated the activity of ISCs by increasing Wnt/β-catenin and Lgr5. Our findings also revealed that NMN caused a significant increase in the relative abundance of Akkermansia muciniphila and Bifidobacterium pseudolongum and notable differences in metabolic pathways related to choline metabolism in cancer. In summary, NMN supplementation can delay frailty in old age, aid healthy ageing, and delay gut ageing.
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Affiliation(s)
- Yanrou Gu
- Department of Gastroenterology, The Third Clinical Institute Affiliated to Wenzhou Medical University, Wenzhou People's Hospital, Wenzhou325035, China.
| | - Lidan Gao
- Department of Scientific Research Center, The Third Clinical Institute Affiliated to Wenzhou Medical University, Wenzhou People's Hospital, Wenzhou Maternal and Child Health Care Hospital, Wenzhou325035, China
| | - Jiamin He
- Department of Gastroenterology, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou310058, China.
- Institution of Gastroenterology, Zhejiang University, Hangzhou310058, China
- Prevention and Treatment Research Center for Senescent Disease, Zhejiang University School of Medicine, Hangzhou310058, China
| | - Man Luo
- Department of Clinical Nutrition, Sir Run Run Shaw Hospital, Zhejiang University, Hangzhou310058, China
| | - Mei Hu
- Department of Gastroenterology, The Third Clinical Institute Affiliated to Wenzhou Medical University, Wenzhou People's Hospital, Wenzhou325035, China.
| | - Yuxian Lin
- Department of Gastroenterology, The Third Clinical Institute Affiliated to Wenzhou Medical University, Wenzhou People's Hospital, Wenzhou325035, China.
| | - Jianxin Li
- Department of Gastroenterology, The Third Clinical Institute Affiliated to Wenzhou Medical University, Wenzhou People's Hospital, Wenzhou325035, China.
| | - Tongyao Hou
- Department of Gastroenterology, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou310058, China.
- Institution of Gastroenterology, Zhejiang University, Hangzhou310058, China
| | - Jianmin Si
- Department of Gastroenterology, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou310058, China.
- Institution of Gastroenterology, Zhejiang University, Hangzhou310058, China
- Prevention and Treatment Research Center for Senescent Disease, Zhejiang University School of Medicine, Hangzhou310058, China
| | - Yingcong Yu
- Department of Gastroenterology, The Third Clinical Institute Affiliated to Wenzhou Medical University, Wenzhou People's Hospital, Wenzhou325035, China.
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20
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Lamming DW. Quantification of healthspan in aging mice: Introducing FAMY and GRAIL. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.11.07.566044. [PMID: 37986745 PMCID: PMC10659332 DOI: 10.1101/2023.11.07.566044] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/22/2023]
Abstract
The population around the world is graying, and as many of these individuals will spend years suffering from the burdens of age associated diseases, understanding how to increase healthspan, defined as the period of life free from disease and disability, is an urgent priority of geroscience research. The lack of agreed-upon quantitative metrics for measuring healthspan in aging mice has slowed progress in identifying interventions that do not simply increase lifespan, but also healthspan. Here, we define FAMY (Frailty-Adjusted Mouse Years) and GRAIL (Gauging Robust Aging when Increasing Lifespan) as new summary statistics for quantifying healthspan in mice. FAMY integrates lifespan data with longitudinal measurements of a widely utilized clinical frailty index, while GRAIL incorporates these measures and also adds information from widely utilized healthspan assays and the hallmarks of aging. Both metrics are conceptually similar to quality-adjusted life years (QALY), a widely-utilized measure of disease burden in humans, and can be readily calculated from data acquired during longitudinal and cross-sectional studies of mouse aging. We find that interventions generally thought to promote health, including calorie restriction, robustly improve healthspan as measured by FAMY and GRAIL. Finally, we show that the use of GRAIL provides new insights, and identify dietary restriction of protein or isoleucine as interventions that robustly promote healthspan but not longevity in female HET3 mice. We suggest that the routine integration of these measures into studies of aging in mice will allow the identification and development of interventions that promote healthy aging even in the absence of increased lifespan.
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Affiliation(s)
- Dudley W. Lamming
- Department of Medicine, University of Wisconsin-Madison, Madison, WI 53705, USA
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21
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Spiridonova O, Kriukov D, Nemirovich-Danchenko N, Peshkin L. On standardization of controls in lifespan studies. Aging (Albany NY) 2024; 16:3047-3055. [PMID: 38421245 PMCID: PMC10929834 DOI: 10.18632/aging.205604] [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: 01/03/2024] [Accepted: 01/29/2024] [Indexed: 03/02/2024]
Abstract
The search for interventions to slow down and even reverse aging is a burgeoning field. The literature cites hundreds of supposedly beneficial pharmacological and genetic interventions in model organisms: mice, rats, flies and worms, where research into physiology is routinely accompanied by lifespan data. However, when experimental animals from one article live as long as controls from another article, comparing the results of interventions across studies can yield misleading outcomes. Theoretically, all lifespan data are ripe for re-analysis: we could contrast the molecular targets and pathways across studies and help focus the further search for interventions. Alas, the results of most longevity studies are difficult to compare. This is in part because there are no clear, universally accepted standards for conducting such experiments or even for reporting such data. The situation is worsened by the fact that the authors often do not describe experimental conditions completely. As a result, works on longevity make up a set of precedents, each of which might be interesting in its own right, yet incoherent and incomparable at least for the reason that in a general context, it may indicate, for example, not prolonging the life of an average organism, but compensating for any genetic abnormalities of a particular sample or inappropriate living conditions. Here we point out specific issues and propose solutions for quality control by checking both inter- and intra-study consistency of lifespan data.
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Affiliation(s)
- Olga Spiridonova
- Department of Systems Biology, Harvard Medical School, Boston, MA 02115, USA
| | - Dmitrii Kriukov
- Department of Systems Biology, Harvard Medical School, Boston, MA 02115, USA
| | | | - Leonid Peshkin
- Department of Systems Biology, Harvard Medical School, Boston, MA 02115, USA
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22
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Luciano A, Robinson L, Garland G, Lyons B, Korstanje R, Di Francesco A, Churchill GA. Longitudinal Fragility Phenotyping Predicts Lifespan and Age-Associated Morbidity in C57BL/6 and Diversity Outbred Mice. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.02.06.579096. [PMID: 38370707 PMCID: PMC10871234 DOI: 10.1101/2024.02.06.579096] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/20/2024]
Abstract
Aging studies in mammalian models often depend on natural lifespan data as a primary outcome. Tools for lifespan prediction could accelerate these studies and reduce the need for veterinary intervention. Here, we leveraged large-scale longitudinal frailty and lifespan data on two genetically distinct mouse cohorts to evaluate noninvasive strategies to predict life expectancy in mice. We applied a modified frailty assessment, the Fragility Index, derived from existing frailty indices with additional deficits selected by veterinarians. We developed an ensemble machine learning classifier to predict imminent mortality (95% proportion of life lived [95PLL]). Our algorithm represented improvement over previous predictive criteria but fell short of the level of reliability that would be needed to make advanced prediction of lifespan and thus accelerate lifespan studies. Highly sensitive and specific frailty-based predictive endpoint criteria for aged mice remain elusive. While frailty-based prediction falls short as a surrogate for lifespan, it did demonstrate significant predictive power and as such must contain information that could be used to inform the conclusion of aging experiments. We propose a frailty-based measure of healthspan as an alternative target for aging research and demonstrate that lifespan and healthspan criteria reveal distinct aspects of aging in mice.
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23
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Griffin PT, Kane AE, Trapp A, Li J, Arnold M, Poganik JR, Conway RJ, McNamara MS, Meer MV, Hoffman N, Amorim JA, Tian X, MacArthur MR, Mitchell SJ, Mueller AL, Carmody C, Vera DL, Kerepesi C, Ying K, Noren Hooten N, Mitchell JR, Evans MK, Gladyshev VN, Sinclair DA. TIME-seq reduces time and cost of DNA methylation measurement for epigenetic clock construction. NATURE AGING 2024; 4:261-274. [PMID: 38200273 PMCID: PMC11332592 DOI: 10.1038/s43587-023-00555-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/06/2021] [Accepted: 12/05/2023] [Indexed: 01/12/2024]
Abstract
Epigenetic 'clocks' based on DNA methylation have emerged as the most robust and widely used aging biomarkers, but conventional methods for applying them are expensive and laborious. Here we develop tagmentation-based indexing for methylation sequencing (TIME-seq), a highly multiplexed and scalable method for low-cost epigenetic clocks. Using TIME-seq, we applied multi-tissue and tissue-specific epigenetic clocks in over 1,800 mouse DNA samples from eight tissue and cell types. We show that TIME-seq clocks are accurate and robust, enriched for polycomb repressive complex 2-regulated loci, and benchmark favorably against conventional methods despite being up to 100-fold less expensive. Using dietary treatments and gene therapy, we find that TIME-seq clocks reflect diverse interventions in multiple tissues. Finally, we develop an economical human blood clock (R > 0.96, median error = 3.39 years) in 1,056 demographically representative individuals. These methods will enable more efficient epigenetic clock measurement in larger-scale human and animal studies.
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Affiliation(s)
- Patrick T Griffin
- Blavatnik Institute, Department of Genetics, Paul F. Glenn Center for Biology of Aging Research at Harvard Medical School, Boston, MA, USA
| | - Alice E Kane
- Blavatnik Institute, Department of Genetics, Paul F. Glenn Center for Biology of Aging Research at Harvard Medical School, Boston, MA, USA
- Institute for Systems Biology, Seattle, WA, USA
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, WA, USA
| | - Alexandre Trapp
- Brigham and Women's Hospital, Division of Genetics, Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Jien Li
- Blavatnik Institute, Department of Genetics, Paul F. Glenn Center for Biology of Aging Research at Harvard Medical School, Boston, MA, USA
| | - Matthew Arnold
- Blavatnik Institute, Department of Genetics, Paul F. Glenn Center for Biology of Aging Research at Harvard Medical School, Boston, MA, USA
| | - Jesse R Poganik
- Brigham and Women's Hospital, Division of Genetics, Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Ryan J Conway
- Blavatnik Institute, Department of Genetics, Paul F. Glenn Center for Biology of Aging Research at Harvard Medical School, Boston, MA, USA
| | - Maeve S McNamara
- Blavatnik Institute, Department of Genetics, Paul F. Glenn Center for Biology of Aging Research at Harvard Medical School, Boston, MA, USA
| | - Margarita V Meer
- Brigham and Women's Hospital, Division of Genetics, Department of Medicine, Harvard Medical School, Boston, MA, USA
- Department of Pathology, Yale University School of Medicine, New Haven, CT, USA
- San Diego Institute of Science, Altos Labs, San Diego, CA, USA
| | - Noah Hoffman
- Blavatnik Institute, Department of Genetics, Paul F. Glenn Center for Biology of Aging Research at Harvard Medical School, Boston, MA, USA
| | - João A Amorim
- Blavatnik Institute, Department of Genetics, Paul F. Glenn Center for Biology of Aging Research at Harvard Medical School, Boston, MA, USA
| | - Xiao Tian
- Blavatnik Institute, Department of Genetics, Paul F. Glenn Center for Biology of Aging Research at Harvard Medical School, Boston, MA, USA
- Sanford Burnham Prebys Medical Discovery Institute, La Jolla, CA, USA
| | - Michael R MacArthur
- Department of Health Sciences and Technology, Eidgenössische Technische Hochschule Zürich, Zurich, Switzerland
- Lewis-Sigler Institute of Integrative Genomics, Princeton University, Princeton, NJ, USA
| | - Sarah J Mitchell
- Department of Health Sciences and Technology, Eidgenössische Technische Hochschule Zürich, Zurich, Switzerland
- Ludwig Princeton Branch, Princeton University, Princeton, NJ, USA
| | - Amber L Mueller
- Blavatnik Institute, Department of Genetics, Paul F. Glenn Center for Biology of Aging Research at Harvard Medical School, Boston, MA, USA
- Cell Metabolism, Cell Press, Cambridge, MA, USA
| | - Colleen Carmody
- Blavatnik Institute, Department of Genetics, Paul F. Glenn Center for Biology of Aging Research at Harvard Medical School, Boston, MA, USA
| | - Daniel L Vera
- Blavatnik Institute, Department of Genetics, Paul F. Glenn Center for Biology of Aging Research at Harvard Medical School, Boston, MA, USA
| | - Csaba Kerepesi
- Brigham and Women's Hospital, Division of Genetics, Department of Medicine, Harvard Medical School, Boston, MA, USA
- Institute for Computer Science and Control, Eötvös Loránd Research Network, Budapest, Hungary
| | - Kejun Ying
- Brigham and Women's Hospital, Division of Genetics, Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Nicole Noren Hooten
- Laboratory of Epidemiology and Population Science, National Institute on Aging, National Institutes of Health, Baltimore, MD, USA
| | - James R Mitchell
- Department of Health Sciences and Technology, Eidgenössische Technische Hochschule Zürich, Zurich, Switzerland
| | - Michele K Evans
- Laboratory of Epidemiology and Population Science, National Institute on Aging, National Institutes of Health, Baltimore, MD, USA
| | - Vadim N Gladyshev
- Brigham and Women's Hospital, Division of Genetics, Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - David A Sinclair
- Blavatnik Institute, Department of Genetics, Paul F. Glenn Center for Biology of Aging Research at Harvard Medical School, Boston, MA, USA.
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24
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Kastberger B, Winter S, Brandstätter H, Biller J, Wagner W, Plesnila N. Treatment with Cerebrolysin Prolongs Lifespan in a Mouse Model of Cerebral Autosomal Dominant Arteriopathy with Subcortical Infarcts and Leukoencephalopathy. Adv Biol (Weinh) 2024; 8:e2300439. [PMID: 38062874 DOI: 10.1002/adbi.202300439] [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: 08/22/2023] [Indexed: 02/15/2024]
Abstract
Cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL) is a rare familial neurological disorder caused by mutations in the NOTCH3 gene and characterized by migraine attacks, depressive episodes, lacunar strokes, dementia, and premature death. Since there is no therapy for CADASIL the authors investigate whether the multi-modal neuropeptide drug Cerebrolysin may improve outcome in a murine CADASIL model. Twelve-month-old NOTCH3R169C mutant mice (n=176) are treated for nine weeks with Cerebrolysin or Vehicle and histopathological and functional outcomes are evaluated within the subsequent ten months. Cerebrolysin treatment improves spatial memory and overall health, reduces epigenetic aging, and prolongs lifespan, however, CADASIL-specific white matter vacuolization is not affected. On the molecular level Cerebrolysin treatment increases expression of Calcitonin Gene-Related Peptide (CGRP) and Silent Information Regulator Two (Sir2)-like protein 6 (SIRT6), decreases expression of Insulin-like Growth Factor 1 (IGF-1), and normalizes the expression of neurovascular laminin. In summary, Cerebrolysin fosters longevity and healthy aging without specifically affecting CADASIL pathology. Hence, Cerebrolysin may serve a therapeutic option for CADASIL and other disorders characterized by accelerated aging.
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Affiliation(s)
| | - Stefan Winter
- Ever Pharma, Oberburgau 3, Unterach am Attersee, 4866, Austria
| | | | - Janina Biller
- Institute for Stroke and Dementia Research (ISD), University Hospital, LMU Munich, 81377, Munich, Germany
| | - Wolfgang Wagner
- Institute for Stem Cell Biology, RWTH Aachen University Medical School, 52074, Aachen, Germany
- Helmholtz Institute for Biomedical Engineering, RWTH Aachen University, 52074, Aachen, Germany
- Cygenia GmbH, 52078, Aachen, Germany
| | - Nikolaus Plesnila
- Cluster of Systems Neurology (Synergy), 81377, Munich, Germany
- Institute for Stroke and Dementia Research (ISD), University Hospital, LMU Munich, 81377, Munich, Germany
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25
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He Y, Li Z, Niu Y, Duan Y, Wang Q, Liu X, Dong Z, Zheng Y, Chen Y, Wang Y, Zhao D, Sun X, Cai G, Feng Z, Zhang W, Chen X. Progress in the study of aging marker criteria in human populations. Front Public Health 2024; 12:1305303. [PMID: 38327568 PMCID: PMC10847233 DOI: 10.3389/fpubh.2024.1305303] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2023] [Accepted: 01/08/2024] [Indexed: 02/09/2024] Open
Abstract
The use of human aging markers, which are physiological, biochemical and molecular indicators of structural or functional degeneration associated with aging, is the fundamental basis of individualized aging assessments. Identifying methods for selecting markers has become a primary and vital aspect of aging research. However, there is no clear consensus or uniform principle on the criteria for screening aging markers. Therefore, we combine previous research from our center and summarize the criteria for screening aging markers in previous population studies, which are discussed in three aspects: functional perspective, operational implementation perspective and methodological perspective. Finally, an evaluation framework has been established, and the criteria are categorized into three levels based on their importance, which can help assess the extent to which a candidate biomarker may be feasible, valid, and useful for a specific use context.
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Affiliation(s)
- Yan He
- Chengdu University of Traditional Chinese Medicine, Chengdu, China
- Department of Nephrology, First Medical Center of Chinese PLA General Hospital, National Key Laboratory of Kidney Diseases, National Clinical Research Center for Kidney Diseases, Beijing Key Laboratory of Kidney Diseases Research, Beijing, China
| | - Zhe Li
- The First Affiliated Hospital, College of Clinical Medicine of Henan University of Science and Technology, Luoyang, China
| | - Yue Niu
- Department of Nephrology, First Medical Center of Chinese PLA General Hospital, National Key Laboratory of Kidney Diseases, National Clinical Research Center for Kidney Diseases, Beijing Key Laboratory of Kidney Diseases Research, Beijing, China
| | - Yuting Duan
- Department of Nephrology, First Medical Center of Chinese PLA General Hospital, National Key Laboratory of Kidney Diseases, National Clinical Research Center for Kidney Diseases, Beijing Key Laboratory of Kidney Diseases Research, Beijing, China
| | - Qian Wang
- Department of Nephrology, First Medical Center of Chinese PLA General Hospital, National Key Laboratory of Kidney Diseases, National Clinical Research Center for Kidney Diseases, Beijing Key Laboratory of Kidney Diseases Research, Beijing, China
| | - Xiaomin Liu
- Department of Nephrology, First Medical Center of Chinese PLA General Hospital, National Key Laboratory of Kidney Diseases, National Clinical Research Center for Kidney Diseases, Beijing Key Laboratory of Kidney Diseases Research, Beijing, China
| | - Zheyi Dong
- Department of Nephrology, First Medical Center of Chinese PLA General Hospital, National Key Laboratory of Kidney Diseases, National Clinical Research Center for Kidney Diseases, Beijing Key Laboratory of Kidney Diseases Research, Beijing, China
| | - Ying Zheng
- Department of Nephrology, First Medical Center of Chinese PLA General Hospital, National Key Laboratory of Kidney Diseases, National Clinical Research Center for Kidney Diseases, Beijing Key Laboratory of Kidney Diseases Research, Beijing, China
| | - Yizhi Chen
- Department of Nephrology, First Medical Center of Chinese PLA General Hospital, National Key Laboratory of Kidney Diseases, National Clinical Research Center for Kidney Diseases, Beijing Key Laboratory of Kidney Diseases Research, Beijing, China
- Department of Nephrology, Hainan Hospital of Chinese PLA General Hospital, Hainan Province Academician Team Innovation Center, Sanya, China
| | - Yong Wang
- Department of Nephrology, First Medical Center of Chinese PLA General Hospital, National Key Laboratory of Kidney Diseases, National Clinical Research Center for Kidney Diseases, Beijing Key Laboratory of Kidney Diseases Research, Beijing, China
| | - Delong Zhao
- Department of Nephrology, First Medical Center of Chinese PLA General Hospital, National Key Laboratory of Kidney Diseases, National Clinical Research Center for Kidney Diseases, Beijing Key Laboratory of Kidney Diseases Research, Beijing, China
| | - Xuefeng Sun
- Department of Nephrology, First Medical Center of Chinese PLA General Hospital, National Key Laboratory of Kidney Diseases, National Clinical Research Center for Kidney Diseases, Beijing Key Laboratory of Kidney Diseases Research, Beijing, China
| | - Guangyan Cai
- Department of Nephrology, First Medical Center of Chinese PLA General Hospital, National Key Laboratory of Kidney Diseases, National Clinical Research Center for Kidney Diseases, Beijing Key Laboratory of Kidney Diseases Research, Beijing, China
| | - Zhe Feng
- Department of Nephrology, First Medical Center of Chinese PLA General Hospital, National Key Laboratory of Kidney Diseases, National Clinical Research Center for Kidney Diseases, Beijing Key Laboratory of Kidney Diseases Research, Beijing, China
| | - Weiguang Zhang
- Department of Nephrology, First Medical Center of Chinese PLA General Hospital, National Key Laboratory of Kidney Diseases, National Clinical Research Center for Kidney Diseases, Beijing Key Laboratory of Kidney Diseases Research, Beijing, China
| | - Xiangmei Chen
- Chengdu University of Traditional Chinese Medicine, Chengdu, China
- Department of Nephrology, First Medical Center of Chinese PLA General Hospital, National Key Laboratory of Kidney Diseases, National Clinical Research Center for Kidney Diseases, Beijing Key Laboratory of Kidney Diseases Research, Beijing, China
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26
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Yu D, Li M, Linghu G, Hu Y, Hajdarovic KH, Wang A, Singh R, Webb AE. CellBiAge: Improved single-cell age classification using data binarization. Cell Rep 2023; 42:113500. [PMID: 38032797 PMCID: PMC10791072 DOI: 10.1016/j.celrep.2023.113500] [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: 05/04/2023] [Revised: 10/20/2023] [Accepted: 11/13/2023] [Indexed: 12/02/2023] Open
Abstract
Aging is a major risk factor for many diseases. Accurate methods for predicting age in specific cell types are essential to understand the heterogeneity of aging and to assess rejuvenation strategies. However, classifying organismal age at single-cell resolution using transcriptomics is challenging due to sparsity and noise. Here, we developed CellBiAge, a robust and easy-to-implement machine learning pipeline, to classify the age of single cells in the mouse brain using single-cell transcriptomics. We show that binarization of gene expression values for the top highly variable genes significantly improved test performance across different models, techniques, sexes, and brain regions, with potential age-related genes identified for model prediction. Additionally, we demonstrate CellBiAge's ability to capture exercise-induced rejuvenation in neural stem cells. This study provides a broadly applicable approach for robust classification of organismal age of single cells in the mouse brain, which may aid in understanding the aging process and evaluating rejuvenation methods.
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Affiliation(s)
- Doudou Yu
- Molecular Biology, Cell Biology, and Biochemistry Graduate Program, Brown University, Providence, RI 02912, USA; Data Science Institute, Brown University, Providence, RI 02912, USA
| | - Manlin Li
- Data Science Institute, Brown University, Providence, RI 02912, USA
| | - Guanjie Linghu
- Data Science Institute, Brown University, Providence, RI 02912, USA
| | - Yihuan Hu
- Data Science Institute, Brown University, Providence, RI 02912, USA
| | | | - An Wang
- Department of Applied Mathematics & Statistics, Johns Hopkins University, Baltimore, MD 21218, USA
| | - Ritambhara Singh
- Department of Computer Science, Brown University, Providence, RI 02912, USA; Center for Computational Molecular Biology, Brown University, Providence, RI 02912, USA.
| | - Ashley E Webb
- Department of Molecular Biology, Cell Biology, and Biochemistry, Brown University, Providence, RI 02912, USA; Center on the Biology of Aging, Brown University, Providence, RI 02912, USA; Carney Institute for Brain Science, Brown University, Providence, RI 02912, USA; Center for Translational Neuroscience, Brown University, Providence, RI 02912, USA.
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27
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Thomas C, Erni R, Wu JY, Fischer F, Lamers G, Grigolon G, Mitchell SJ, Zarse K, Carreira EM, Ristow M. A naturally occurring polyacetylene isolated from carrots promotes health and delays signatures of aging. Nat Commun 2023; 14:8142. [PMID: 38065964 PMCID: PMC10709416 DOI: 10.1038/s41467-023-43672-7] [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: 05/10/2023] [Accepted: 11/16/2023] [Indexed: 12/18/2023] Open
Abstract
To ameliorate or even prevent signatures of aging in ultimately humans, we here report the identification of a previously undescribed polyacetylene contained in the root of carrots (Daucus carota), hereafter named isofalcarintriol, which we reveal as potent promoter of longevity in the nematode C. elegans. We assign the absolute configuration of the compound as (3 S,8 R,9 R,E)-heptadeca-10-en-4,6-diyne-3,8,9-triol, and develop a modular asymmetric synthesis route for all E-isofalcarintriol stereoisomers. At the molecular level, isofalcarintriol affects cellular respiration in mammalian cells, C. elegans, and mice, and interacts with the α-subunit of the mitochondrial ATP synthase to promote mitochondrial biogenesis. Phenotypically, this also results in decreased mammalian cancer cell growth, as well as improved motility and stress resistance in C. elegans, paralleled by reduced protein accumulation in nematodal models of neurodegeneration. In addition, isofalcarintriol supplementation to both wild-type C57BL/6NRj mice on high-fat diet, and aged mice on chow diet results in improved glucose metabolism, increased exercise endurance, and attenuated parameters of frailty at an advanced age. Given these diverse effects on health parameters in both nematodes and mice, isofalcarintriol might become a promising mitohormesis-inducing compound to delay, ameliorate, or prevent aging-associated diseases in humans.
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Affiliation(s)
- Carolin Thomas
- Laboratory of Energy Metabolism, Institute of Translational Medicine, Department of Health Sciences and Technology, Swiss Federal Institute (ETH) Zurich, Schorenstrasse 16, 8603, Schwerzenbach, Switzerland
| | - Reto Erni
- Laboratory of Chemistry and Applied Biosciences, Department of Organic Chemistry, Swiss Federal Institute (ETH) Zurich, Vladimir-Prelog-Weg 1-5/10, Zurich, 8093, Switzerland
- Biozentrum, University of Basel, Basel, 4056, Switzerland
| | - Jia Yee Wu
- Laboratory of Energy Metabolism, Institute of Translational Medicine, Department of Health Sciences and Technology, Swiss Federal Institute (ETH) Zurich, Schorenstrasse 16, 8603, Schwerzenbach, Switzerland
| | - Fabian Fischer
- Laboratory of Energy Metabolism, Institute of Translational Medicine, Department of Health Sciences and Technology, Swiss Federal Institute (ETH) Zurich, Schorenstrasse 16, 8603, Schwerzenbach, Switzerland
- CureVac SE, Tübingen, 72076, Germany
| | - Greta Lamers
- Laboratory of Energy Metabolism, Institute of Translational Medicine, Department of Health Sciences and Technology, Swiss Federal Institute (ETH) Zurich, Schorenstrasse 16, 8603, Schwerzenbach, Switzerland
| | - Giovanna Grigolon
- Laboratory of Energy Metabolism, Institute of Translational Medicine, Department of Health Sciences and Technology, Swiss Federal Institute (ETH) Zurich, Schorenstrasse 16, 8603, Schwerzenbach, Switzerland
| | - Sarah J Mitchell
- Ludwig Princeton Branch, Princeton University, Princeton, NJ, 08540, USA
| | - Kim Zarse
- Laboratory of Energy Metabolism, Institute of Translational Medicine, Department of Health Sciences and Technology, Swiss Federal Institute (ETH) Zurich, Schorenstrasse 16, 8603, Schwerzenbach, Switzerland
- Institute of Experimental Endocrinology, Charité Universitätsmedizin Berlin, Berlin, 10117, Germany
| | - Erick M Carreira
- Laboratory of Chemistry and Applied Biosciences, Department of Organic Chemistry, Swiss Federal Institute (ETH) Zurich, Vladimir-Prelog-Weg 1-5/10, Zurich, 8093, Switzerland.
| | - Michael Ristow
- Laboratory of Energy Metabolism, Institute of Translational Medicine, Department of Health Sciences and Technology, Swiss Federal Institute (ETH) Zurich, Schorenstrasse 16, 8603, Schwerzenbach, Switzerland.
- Institute of Experimental Endocrinology, Charité Universitätsmedizin Berlin, Berlin, 10117, Germany.
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Fernandez ME, Martinez-Romero J, Aon MA, Bernier M, Price NL, de Cabo R. How is Big Data reshaping preclinical aging research? Lab Anim (NY) 2023; 52:289-314. [PMID: 38017182 DOI: 10.1038/s41684-023-01286-y] [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: 05/24/2023] [Accepted: 10/10/2023] [Indexed: 11/30/2023]
Abstract
The exponential scientific and technological progress during the past 30 years has favored the comprehensive characterization of aging processes with their multivariate nature, leading to the advent of Big Data in preclinical aging research. Spanning from molecular omics to organism-level deep phenotyping, Big Data demands large computational resources for storage and analysis, as well as new analytical tools and conceptual frameworks to gain novel insights leading to discovery. Systems biology has emerged as a paradigm that utilizes Big Data to gain insightful information enabling a better understanding of living organisms, visualized as multilayered networks of interacting molecules, cells, tissues and organs at different spatiotemporal scales. In this framework, where aging, health and disease represent emergent states from an evolving dynamic complex system, context given by, for example, strain, sex and feeding times, becomes paramount for defining the biological trajectory of an organism. Using bioinformatics and artificial intelligence, the systems biology approach is leading to remarkable advances in our understanding of the underlying mechanism of aging biology and assisting in creative experimental study designs in animal models. Future in-depth knowledge acquisition will depend on the ability to fully integrate information from different spatiotemporal scales in organisms, which will probably require the adoption of theories and methods from the field of complex systems. Here we review state-of-the-art approaches in preclinical research, with a focus on rodent models, that are leading to conceptual and/or technical advances in leveraging Big Data to understand basic aging biology and its full translational potential.
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Affiliation(s)
- Maria Emilia Fernandez
- Experimental Gerontology Section, Translational Gerontology Branch, National Institute on Aging, National Institutes of Health, Baltimore, MD, USA
| | - Jorge Martinez-Romero
- Experimental Gerontology Section, Translational Gerontology Branch, National Institute on Aging, National Institutes of Health, Baltimore, MD, USA
- Laboratory of Epidemiology and Population Science, National Institute on Aging, National Institutes of Health, Baltimore, MD, USA
| | - Miguel A Aon
- Experimental Gerontology Section, Translational Gerontology Branch, National Institute on Aging, National Institutes of Health, Baltimore, MD, USA
- Laboratory of Cardiovascular Science, National Institute on Aging, National Institutes of Health, Baltimore, MD, USA
| | - Michel Bernier
- Experimental Gerontology Section, Translational Gerontology Branch, National Institute on Aging, National Institutes of Health, Baltimore, MD, USA
| | - Nathan L Price
- Experimental Gerontology Section, Translational Gerontology Branch, National Institute on Aging, National Institutes of Health, Baltimore, MD, USA
| | - Rafael de Cabo
- Experimental Gerontology Section, Translational Gerontology Branch, National Institute on Aging, National Institutes of Health, Baltimore, MD, USA.
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29
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Alvarez-Kuglen M, Rodriguez D, Qin H, Ninomiya K, Fiengo L, Farhy C, Hsu WM, Havas A, Feng GS, Roberts AJ, Anderson RM, Serrano M, Adams PD, Sharpee TO, Terskikh AV. Imaging-based chromatin and epigenetic age, ImAge, quantitates aging and rejuvenation. RESEARCH SQUARE 2023:rs.3.rs-3479973. [PMID: 37986947 PMCID: PMC10659560 DOI: 10.21203/rs.3.rs-3479973/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/22/2023]
Abstract
Biomarkers of biological age that predict the risk of disease and expected lifespan better than chronological age are key to efficient and cost-effective healthcare1-3. To advance a personalized approach to healthcare, such biomarkers must reliably and accurately capture individual biology, predict biological age, and provide scalable and cost-effective measurements. We developed a novel approach - image-based chromatin and epigenetic age (ImAge) that captures intrinsic progressions of biological age, which readily emerge as principal changes in the spatial organization of chromatin and epigenetic marks in single nuclei without regression on chronological age. ImAge captured the expected acceleration or deceleration of biological age in mice treated with chemotherapy or following a caloric restriction regimen, respectively. ImAge from chronologically identical mice inversely correlated with their locomotor activity (greater activity for younger ImAge), consistent with the widely accepted role of locomotion as an aging biomarker across species. Finally, we demonstrated that ImAge is reduced following transient expression of OSKM cassette in the liver and skeletal muscles and reveals heterogeneity of in vivo reprogramming. We propose that ImAge represents the first-in-class imaging-based biomarker of aging with single-cell resolution.
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Affiliation(s)
| | | | - Haodong Qin
- UCSD, Department of Physics, La Jolla, CA 92093, USA
| | | | | | - Chen Farhy
- Sanford Burnham Prebys, La Jolla CA 92037, USA
| | - Wei-Mien Hsu
- Salk Institute for Biological Studies, La Jolla, CA 92037, USA
| | - Aaron Havas
- Sanford Burnham Prebys, La Jolla CA 92037, USA
| | - Gen-Sheng Feng
- UCSD School of Medicine, 9500 Gilman Drive, La Jolla, CA 92093, USA
| | | | | | - Manuel Serrano
- Institute for Research in Biomedicine (IRB Barcelona), Barcelona 08028, Spain
- Barcelona Institute of Science and Technology (BIST), Barcelona 08028, Spain
- Altos Labs, Cambridge Institute of Science, Granta Park CB21 6GP, UK
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30
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Thyne KM, Salmon AB. Sexually dimorphic effects of methionine sulfoxide reductase A (MsrA) on murine longevity and health span during methionine restriction. GeroScience 2023; 45:3003-3017. [PMID: 37391679 PMCID: PMC10643651 DOI: 10.1007/s11357-023-00857-8] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2023] [Accepted: 06/17/2023] [Indexed: 07/02/2023] Open
Abstract
Methionine restriction (MR) extends lifespan in various model organisms, and understanding the molecular effectors of MR could expand the repertoire of tools targeting the aging process. Here, we address to what extent the biochemical pathway responsible for redox metabolism of methionine plays in regulating the effects of MR on lifespan and health span. Aerobic organisms have evolved methionine sulfoxide reductases to counter the oxidation of the thioether group contained in the essential amino acid methionine. Of these enzymes, methionine sulfoxide reductase A (MsrA) is ubiquitously expressed in mammalian tissues and has subcellular localization in both the cytosol and mitochondria. Loss of MsrA increases sensitivity to oxidative stress and has been associated with increased susceptibility to age-associated pathologies including metabolic dysfunction. We rationalized that limiting the available methionine with MR may place increased importance on methionine redox pathways, and that MsrA may be required to maintain available methionine for its critical uses in cellular homeostasis including protein synthesis, metabolism, and methylation. Using a genetic mutant mouse lacking MsrA, we tested the requirement for this enzyme in the effects of MR on longevity and markers of healthy aging late in life. When initiated in adulthood, we found that MR had minimal effects in males and females regardless of MsrA status. MR had minimal effect on lifespan with the exception of wild-type males where loss of MsrA slightly increased lifespan on MR. We also observed that MR drove an increase in body weight in wild-type mice only, but mice lacking MsrA tended to maintain more stable body weight throughout their lives. We also found that MR had greater benefit to males than females in terms of glucose metabolism and some functional health span assessments, but MsrA generally had minimal impact on these metrics. Frailty was also found to be unaffected by MR or MsrA in aged animals. We found that in general, MsrA was not required for the beneficial effects of MR on longevity and health span.
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Affiliation(s)
- Kevin M Thyne
- Sam and Ann Barshop Institute for Longevity and Aging Studies, University of Texas Health San Antonio, San Antonio, TX, 78229, USA
| | - Adam B Salmon
- Sam and Ann Barshop Institute for Longevity and Aging Studies, University of Texas Health San Antonio, San Antonio, TX, 78229, USA.
- Department of Molecular Medicine, University of Texas Health San Antonio, San Antonio, TX, 78229, USA.
- Geriatric Research Education and Clinical Center, Audie L. Murphy Hospital, South Texas Veterans Health Care System, San Antonio, TX, 78229, USA.
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31
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Moqri M, Herzog C, Poganik JR, Justice J, Belsky DW, Higgins-Chen A, Moskalev A, Fuellen G, Cohen AA, Bautmans I, Widschwendter M, Ding J, Fleming A, Mannick J, Han JDJ, Zhavoronkov A, Barzilai N, Kaeberlein M, Cummings S, Kennedy BK, Ferrucci L, Horvath S, Verdin E, Maier AB, Snyder MP, Sebastiano V, Gladyshev VN. Biomarkers of aging for the identification and evaluation of longevity interventions. Cell 2023; 186:3758-3775. [PMID: 37657418 PMCID: PMC11088934 DOI: 10.1016/j.cell.2023.08.003] [Citation(s) in RCA: 211] [Impact Index Per Article: 105.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2023] [Revised: 08/01/2023] [Accepted: 08/02/2023] [Indexed: 09/03/2023]
Abstract
With the rapid expansion of aging biology research, the identification and evaluation of longevity interventions in humans have become key goals of this field. Biomarkers of aging are critically important tools in achieving these objectives over realistic time frames. However, the current lack of standards and consensus on the properties of a reliable aging biomarker hinders their further development and validation for clinical applications. Here, we advance a framework for the terminology and characterization of biomarkers of aging, including classification and potential clinical use cases. We discuss validation steps and highlight ongoing challenges as potential areas in need of future research. This framework sets the stage for the development of valid biomarkers of aging and their ultimate utilization in clinical trials and practice.
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Affiliation(s)
- Mahdi Moqri
- Division of Genetics, 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; Department of Obstetrics and Gynecology, School of Medicine, Stanford University, Stanford, CA, USA
| | - Chiara Herzog
- European Translational Oncology Prevention and Screening Institute, Universität Innsbruck, Innsbruck, Austria
| | - Jesse R Poganik
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Jamie Justice
- Department of Internal Medicine, Section on Gerontology and Geriatric Medicine, Wake Forest University School of Medicine, Winston-Salem, NC, USA
| | - Daniel W Belsky
- Department of Epidemiology, Butler Columbia Aging Center, Mailman School of Public Health, Columbia University, New York, NY, USA
| | | | - Alexey Moskalev
- Institute of Biogerontology, Lobachevsky University, Nizhny Novgorod, Russia
| | - Georg Fuellen
- Institute for Biostatistics and Informatics in Medicine and Ageing Research, Rostock University Medical Center, Rostock, Germany; School of Medicine, University College Dublin, Dublin, Ireland
| | - Alan A Cohen
- Department of Environmental Health Sciences, Butler Columbia Aging Center, Mailman School of Public Health, Columbia University, New York, NY, USA
| | - Ivan Bautmans
- Gerontology Department, Vrije Universiteit Brussel, Brussels, Belgium; Frailty in Ageing Research Department, Vrije Universiteit Brussel, Brussels, Belgium
| | - Martin Widschwendter
- European Translational Oncology Prevention and Screening Institute, Universität Innsbruck, Innsbruck, Austria; Department of Women's Cancer, EGA Institute for Women's Health, University College London, London, UK; Department of Women's and Children's Health, Division of Obstetrics and Gynaecology, Karolinska Institutet, Stockholm, Sweden
| | - Jingzhong Ding
- Gerontology and Geriatric Medicine, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | | | | | - Jing-Dong Jackie Han
- Peking-Tsinghua Center for Life Sciences, Academy for Advanced Interdisciplinary Studies, Center for Quantitative Biology, Peking University, Beijing, China
| | - Alex Zhavoronkov
- Insilico Medicine Hong Kong, Pak Shek Kok, New Territories, Hong Kong SAR, China
| | - Nir Barzilai
- Institute for Aging Research, Albert Einstein College of Medicine, Bronx, NY, USA
| | - Matt Kaeberlein
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, WA, USA
| | - Steven Cummings
- San Francisco Coordinating Center, California Pacific Medical Center Research Institute, San Francisco, CA, USA; Department of Epidemiology and Biostatistics, University of California, San Francisco, San Francisco, CA, USA
| | - Brian K Kennedy
- Healthy Longevity Translational Research Programme, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | | | | | - Eric Verdin
- Buck Institute for Research on Aging, Novato, CA, USA
| | - Andrea B Maier
- Department of Human Movement Sciences, @AgeAmsterdam, Amsterdam Movement Sciences, Faculty of Behavioural and Movement Sciences, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands; Healthy Longevity Translational Research Program, Yong Loo Lin School of Medicine, National University of Singapore, Centre for Healthy Longevity, @AgeSingapore, National University Health System, Singapore, Singapore
| | - Michael P Snyder
- Department of Genetics, School of Medicine, Stanford University, Stanford, CA, USA.
| | - Vittorio Sebastiano
- Department of Obstetrics and Gynecology, School of Medicine, Stanford University, Stanford, CA, USA.
| | - Vadim N Gladyshev
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
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32
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Spiridonova O, Kriukov D, Nemirovich-Danchenko N, Peshkin L. On standardization of controls in lifespan studies. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.08.17.552381. [PMID: 37645987 PMCID: PMC10462125 DOI: 10.1101/2023.08.17.552381] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 09/01/2023]
Abstract
The search for interventions to slow down and even reverse aging is a burgeoning field. The literature cites hundreds of supposedly beneficial pharmacological and genetic interventions in model organisms: mice, rats, flies and worms, where research into physiology is routinely accompanied by lifespan data. Naturally the negative results are more frequent, yet scientifically quite valuable if analyzed systematically. Yet, there is a strong "discovery bias", i.e. results of interventions which turn out not to be beneficial remain unpublished. Theoretically, all lifespan data is ripe for re-analysis: we could contrast the molecular targets and pathways across studies and help focus the further search for interventions. Alas, the results of most longevity studies are difficult to compare. This is in part because there are no clear, universally accepted standards for conducting such experiments or even for reporting such data. The situation is worsened by the fact that the authors often do not describe experimental conditions completely. As a result, works on longevity make up a set of precedents, each of which might be interesting in its own right, yet incoherent and incomparable. Here we point out specific issues and propose solutions for quality control by checking both inter- and intra-study consistency of lifespan data.
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Affiliation(s)
| | | | | | - Leonid Peshkin
- Department of Systems Biology, Harvard Medical School, Boston, MA 02115, USA
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33
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Sun J, Chong J, Zhang J, Ge L. Preterm pigs for preterm birth research: reasonably feasible. Front Physiol 2023; 14:1189422. [PMID: 37520824 PMCID: PMC10374951 DOI: 10.3389/fphys.2023.1189422] [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: 03/19/2023] [Accepted: 07/07/2023] [Indexed: 08/01/2023] Open
Abstract
Preterm birth will disrupt the pattern and course of organ development, which may result in morbidity and mortality of newborn infants. Large animal models are crucial resources for developing novel, credible, and effective treatments for preterm infants. This review summarizes the classification, definition, and prevalence of preterm birth, and analyzes the relationship between the predicted animal days and one human year in the most widely used animal models (mice, rats, rabbits, sheep, and pigs) for preterm birth studies. After that, the physiological characteristics of preterm pig models at different gestational ages are described in more detail, including birth weight, body temperature, brain development, cardiovascular system development, respiratory, digestive, and immune system development, kidney development, and blood constituents. Studies on postnatal development and adaptation of preterm pig models of different gestational ages will help to determine the physiological basis for survival and development of very preterm, middle preterm, and late preterm newborns, and will also aid in the study and accurate optimization of feeding conditions, diet- or drug-related interventions for preterm neonates. Finally, this review summarizes several accepted pediatric applications of preterm pig models in nutritional fortification, necrotizing enterocolitis, neonatal encephalopathy and hypothermia intervention, mechanical ventilation, and oxygen therapy for preterm infants.
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Affiliation(s)
- Jing Sun
- Chongqing Academy of Animal Sciences, Chongqing, China
- National Center of Technology Innovation for Pigs, Chongqing, China
- Key Laboratory of Pig Industry Sciences, Ministry of Agriculture, Chongqing, China
| | - Jie Chong
- Chongqing Academy of Animal Sciences, Chongqing, China
- National Center of Technology Innovation for Pigs, Chongqing, China
| | - Jinwei Zhang
- Chongqing Academy of Animal Sciences, Chongqing, China
- National Center of Technology Innovation for Pigs, Chongqing, China
- Key Laboratory of Pig Industry Sciences, Ministry of Agriculture, Chongqing, China
| | - Liangpeng Ge
- Chongqing Academy of Animal Sciences, Chongqing, China
- National Center of Technology Innovation for Pigs, Chongqing, China
- Key Laboratory of Pig Industry Sciences, Ministry of Agriculture, Chongqing, China
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34
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Park JYC, King A, Björk V, English BW, Fedintsev A, Ewald CY. Strategic outline of interventions targeting extracellular matrix for promoting healthy longevity. Am J Physiol Cell Physiol 2023; 325:C90-C128. [PMID: 37154490 DOI: 10.1152/ajpcell.00060.2023] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2023] [Revised: 04/28/2023] [Accepted: 04/28/2023] [Indexed: 05/10/2023]
Abstract
The extracellular matrix (ECM), composed of interlinked proteins outside of cells, is an important component of the human body that helps maintain tissue architecture and cellular homeostasis. As people age, the ECM undergoes changes that can lead to age-related morbidity and mortality. Despite its importance, ECM aging remains understudied in the field of geroscience. In this review, we discuss the core concepts of ECM integrity, outline the age-related challenges and subsequent pathologies and diseases, summarize diagnostic methods detecting a faulty ECM, and provide strategies targeting ECM homeostasis. To conceptualize this, we built a technology research tree to hierarchically visualize possible research sequences for studying ECM aging. This strategic framework will hopefully facilitate the development of future research on interventions to restore ECM integrity, which could potentially lead to the development of new drugs or therapeutic interventions promoting health during aging.
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Affiliation(s)
- Ji Young Cecilia Park
- Laboratory of Extracellular Matrix Regeneration, Institute of Translational Medicine, Department of Health Sciences and Technology, ETH Zürich, Schwerzenbach, Switzerland
| | - Aaron King
- Foresight Institute, San Francisco, California, United States
| | | | - Bradley W English
- Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, United States
| | | | - Collin Y Ewald
- Laboratory of Extracellular Matrix Regeneration, Institute of Translational Medicine, Department of Health Sciences and Technology, ETH Zürich, Schwerzenbach, Switzerland
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35
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Tyshkovskiy A, Ma S, Shindyapina AV, Tikhonov S, Lee SG, Bozaykut P, Castro JP, Seluanov A, Schork NJ, Gorbunova V, Dmitriev SE, Miller RA, Gladyshev VN. Distinct longevity mechanisms across and within species and their association with aging. Cell 2023; 186:2929-2949.e20. [PMID: 37269831 PMCID: PMC11192172 DOI: 10.1016/j.cell.2023.05.002] [Citation(s) in RCA: 51] [Impact Index Per Article: 25.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2021] [Revised: 12/29/2022] [Accepted: 05/02/2023] [Indexed: 06/05/2023]
Abstract
Lifespan varies within and across species, but the general principles of its control remain unclear. Here, we conducted multi-tissue RNA-seq analyses across 41 mammalian species, identifying longevity signatures and examining their relationship with transcriptomic biomarkers of aging and established lifespan-extending interventions. An integrative analysis uncovered shared longevity mechanisms within and across species, including downregulated Igf1 and upregulated mitochondrial translation genes, and unique features, such as distinct regulation of the innate immune response and cellular respiration. Signatures of long-lived species were positively correlated with age-related changes and enriched for evolutionarily ancient essential genes, involved in proteolysis and PI3K-Akt signaling. Conversely, lifespan-extending interventions counteracted aging patterns and affected younger, mutable genes enriched for energy metabolism. The identified biomarkers revealed longevity interventions, including KU0063794, which extended mouse lifespan and healthspan. Overall, this study uncovers universal and distinct strategies of lifespan regulation within and across species and provides tools for discovering longevity interventions.
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Affiliation(s)
- Alexander Tyshkovskiy
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115, USA; Belozersky Institute of Physico-Chemical Biology, Moscow State University, Moscow 119234, Russia
| | - Siming Ma
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115, USA
| | - Anastasia V Shindyapina
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115, USA
| | - Stanislav Tikhonov
- Belozersky Institute of Physico-Chemical Biology, Moscow State University, Moscow 119234, Russia
| | - Sang-Goo Lee
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115, USA
| | - Perinur Bozaykut
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115, USA; Department of Molecular Biology and Genetics, Faculty of Engineering and Natural Sciences, Acibadem Mehmet Ali Aydinlar University, Istanbul 34752, Turkey
| | - José P Castro
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115, USA; i3S, Instituto de Investigação e Inovação em Saúde, Universidade do Porto, 4200-135 Porto, Portugal; Aging and Aneuploidy Laboratory, IBMC, Instituto de Biologia Molecular e Celular, Universidade do Porto, 4200-135 Porto, Portugal
| | - Andrei Seluanov
- Departments of Biology and Medicine, University of Rochester, Rochester, NY, USA
| | - Nicholas J Schork
- Quantitative Medicine and Systems Biology Division, Translational Genomics Research Institute, Phoenix, AZ, USA
| | - Vera Gorbunova
- Departments of Biology and Medicine, University of Rochester, Rochester, NY, USA
| | - Sergey E Dmitriev
- Belozersky Institute of Physico-Chemical Biology, Moscow State University, Moscow 119234, Russia
| | - Richard A Miller
- Department of Pathology and Geriatrics Center, University of Michigan, Ann Arbor, MI 48109, USA
| | - Vadim N Gladyshev
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115, USA; Broad Institute, Cambridge, MA, USA.
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36
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Bao H, Cao J, Chen M, Chen M, Chen W, Chen X, Chen Y, Chen Y, Chen Y, Chen Z, Chhetri JK, Ding Y, Feng J, Guo J, Guo M, He C, Jia Y, Jiang H, Jing Y, Li D, Li J, Li J, Liang Q, Liang R, Liu F, Liu X, Liu Z, Luo OJ, Lv J, Ma J, Mao K, Nie J, Qiao X, Sun X, Tang X, Wang J, Wang Q, Wang S, Wang X, Wang Y, Wang Y, Wu R, Xia K, Xiao FH, Xu L, Xu Y, Yan H, Yang L, Yang R, Yang Y, Ying Y, Zhang L, Zhang W, Zhang W, Zhang X, Zhang Z, Zhou M, Zhou R, Zhu Q, Zhu Z, Cao F, Cao Z, Chan P, Chen C, Chen G, Chen HZ, Chen J, Ci W, Ding BS, Ding Q, Gao F, Han JDJ, Huang K, Ju Z, Kong QP, Li J, Li J, Li X, Liu B, Liu F, Liu L, Liu Q, Liu Q, Liu X, Liu Y, Luo X, Ma S, Ma X, Mao Z, Nie J, Peng Y, Qu J, Ren J, Ren R, Song M, Songyang Z, Sun YE, Sun Y, Tian M, Wang S, et alBao H, Cao J, Chen M, Chen M, Chen W, Chen X, Chen Y, Chen Y, Chen Y, Chen Z, Chhetri JK, Ding Y, Feng J, Guo J, Guo M, He C, Jia Y, Jiang H, Jing Y, Li D, Li J, Li J, Liang Q, Liang R, Liu F, Liu X, Liu Z, Luo OJ, Lv J, Ma J, Mao K, Nie J, Qiao X, Sun X, Tang X, Wang J, Wang Q, Wang S, Wang X, Wang Y, Wang Y, Wu R, Xia K, Xiao FH, Xu L, Xu Y, Yan H, Yang L, Yang R, Yang Y, Ying Y, Zhang L, Zhang W, Zhang W, Zhang X, Zhang Z, Zhou M, Zhou R, Zhu Q, Zhu Z, Cao F, Cao Z, Chan P, Chen C, Chen G, Chen HZ, Chen J, Ci W, Ding BS, Ding Q, Gao F, Han JDJ, Huang K, Ju Z, Kong QP, Li J, Li J, Li X, Liu B, Liu F, Liu L, Liu Q, Liu Q, Liu X, Liu Y, Luo X, Ma S, Ma X, Mao Z, Nie J, Peng Y, Qu J, Ren J, Ren R, Song M, Songyang Z, Sun YE, Sun Y, Tian M, Wang S, Wang S, Wang X, Wang X, Wang YJ, Wang Y, Wong CCL, Xiang AP, Xiao Y, Xie Z, Xu D, Ye J, Yue R, Zhang C, Zhang H, Zhang L, Zhang W, Zhang Y, Zhang YW, Zhang Z, Zhao T, Zhao Y, Zhu D, Zou W, Pei G, Liu GH. Biomarkers of aging. SCIENCE CHINA. LIFE SCIENCES 2023; 66:893-1066. [PMID: 37076725 PMCID: PMC10115486 DOI: 10.1007/s11427-023-2305-0] [Show More Authors] [Citation(s) in RCA: 163] [Impact Index Per Article: 81.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Received: 01/19/2023] [Accepted: 02/27/2023] [Indexed: 04/21/2023]
Abstract
Aging biomarkers are a combination of biological parameters to (i) assess age-related changes, (ii) track the physiological aging process, and (iii) predict the transition into a pathological status. Although a broad spectrum of aging biomarkers has been developed, their potential uses and limitations remain poorly characterized. An immediate goal of biomarkers is to help us answer the following three fundamental questions in aging research: How old are we? Why do we get old? And how can we age slower? This review aims to address this need. Here, we summarize our current knowledge of biomarkers developed for cellular, organ, and organismal levels of aging, comprising six pillars: physiological characteristics, medical imaging, histological features, cellular alterations, molecular changes, and secretory factors. To fulfill all these requisites, we propose that aging biomarkers should qualify for being specific, systemic, and clinically relevant.
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Affiliation(s)
- Hainan Bao
- 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
| | - Jiani Cao
- State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China
| | - Mengting Chen
- Department of Dermatology, Xiangya Hospital, Central South University, Changsha, 410008, China
- Hunan Key Laboratory of Aging Biology, Xiangya Hospital, Central South University, Changsha, 410008, China
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, 410008, China
| | - Min Chen
- Clinic Center of Human Gene Research, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China
- Hubei Clinical Research Center of Metabolic and Cardiovascular Disease, Huazhong University of Science and Technology, Wuhan, 430022, China
- Hubei Key Laboratory of Metabolic Abnormalities and Vascular Aging, Huazhong University of Science and Technology, Wuhan, 430022, China
| | - Wei Chen
- Stem Cell Translational Research Center, Tongji Hospital, Tongji University School of Medicine, Shanghai, 200065, China
| | - Xiao Chen
- Department of Nuclear Medicine, Daping Hospital, Third Military Medical University, Chongqing, 400042, China
| | - Yanhao Chen
- CAS Key Laboratory of Nutrition, Metabolism and Food Safety, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, 200031, China
| | - Yu Chen
- Shanghai Key Laboratory of Maternal Fetal Medicine, Clinical and Translational Research Center of Shanghai First Maternity and Infant Hospital, Frontier Science Center for Stem Cell Research, Shanghai Key Laboratory of Signaling and Disease Research, School of Life Sciences and Technology, Tongji University, Shanghai, 200092, China
| | - Yutian Chen
- The Department of Endovascular Surgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, China
| | - Zhiyang Chen
- Key Laboratory of Regenerative Medicine of Ministry of Education, Institute of Ageing and Regenerative Medicine, Jinan University, Guangzhou, 510632, China
| | - Jagadish K Chhetri
- National Clinical Research Center for Geriatric Diseases, Xuanwu Hospital, Capital Medical University, Beijing, 100053, China
| | - Yingjie Ding
- 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
| | - Junlin Feng
- CAS Key Laboratory of Tissue Microenvironment and Tumor, Shanghai Institute of Nutrition and Health, Chinese Academy of Sciences, Shanghai, 200031, China
| | - Jun Guo
- The Key Laboratory of Geriatrics, Beijing Institute of Geriatrics, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing Hospital/National Center of Gerontology of National Health Commission, Beijing, 100730, China
| | - Mengmeng Guo
- School of Pharmaceutical Sciences, Tsinghua University, Beijing, 100084, China
| | - Chuting He
- University of Chinese Academy of Sciences, Beijing, 100049, China
- State Key Laboratory of Membrane Biology, 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
| | - Yujuan Jia
- Department of Neurology, First Affiliated Hospital, Shanxi Medical University, Taiyuan, 030001, China
| | - Haiping Jiang
- 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
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing, 100101, China
| | - Ying Jing
- Beijing Municipal Geriatric Medical Research Center, 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
- Advanced Innovation Center for Human Brain Protection, and National Clinical Research Center for Geriatric Disorders, Xuanwu Hospital Capital Medical University, Beijing, 100053, China
| | - Dingfeng Li
- Department of Neurology, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, 230036, 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
| | - Jingyi Li
- University of Chinese Academy of Sciences, Beijing, 100049, China
- State Key Laboratory of Membrane Biology, 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
| | - Qinhao Liang
- College of Life Sciences, TaiKang Center for Life and Medical Sciences, Wuhan University, Wuhan, 430072, China
| | - Rui Liang
- Research Institute of Transplant Medicine, Organ Transplant Center, NHC Key Laboratory for Critical Care Medicine, Tianjin First Central Hospital, Nankai University, Tianjin, 300384, China
| | - Feng Liu
- MOE Key Laboratory of Gene Function and Regulation, Guangzhou Key Laboratory of Healthy Aging Research, School of Life Sciences, Institute of Healthy Aging Research, Sun Yat-sen University, Guangzhou, 510275, China
| | - Xiaoqian Liu
- 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
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing, 100101, China
| | - Zuojun Liu
- School of Life Sciences, Hainan University, Haikou, 570228, China
| | - Oscar Junhong Luo
- Department of Systems Biomedical Sciences, School of Medicine, Jinan University, Guangzhou, 510632, China
| | - Jianwei Lv
- School of Life Sciences, Xiamen University, Xiamen, 361102, China
| | - Jingyi Ma
- The State Key Laboratory of Organ Failure Research, National Clinical Research Center of Kidney Disease, Division of Nephrology, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, China
| | - Kehang Mao
- Peking-Tsinghua Center for Life Sciences, Academy for Advanced Interdisciplinary Studies, Center for Quantitative Biology (CQB), Peking University, Beijing, 100871, China
| | - Jiawei Nie
- Shanghai Institute of Hematology, State Key Laboratory for Medical Genomics, National Research Center for Translational Medicine (Shanghai), International Center for Aging and Cancer, Collaborative Innovation Center of Hematology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
| | - Xinhua Qiao
- National Laboratory of Biomacromolecules, CAS Center for Excellence in Biomacromolecules, Institute of Biophysics, Chinese Academy of Sciences, Beijing, 100101, China
| | - Xinpei Sun
- Peking University International Cancer Institute, Health Science Center, Peking University, Beijing, 100101, China
| | - Xiaoqiang Tang
- Key Laboratory of Birth Defects and Related Diseases of Women and Children of MOE, State Key Laboratory of Biotherapy, West China Second University Hospital, Sichuan University, Chengdu, 610041, China
| | - Jianfang Wang
- Institute for Regenerative Medicine, Shanghai East Hospital, Frontier Science Center for Stem Cell Research, Shanghai Key Laboratory of Signaling and Disease Research, School of Life Sciences and Technology, Tongji University, Shanghai, 200092, China
| | - Qiaoran 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
| | - Siyuan Wang
- Clinical Research Institute, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Science & Peking Union Medical College, Beijing, 100730, China
| | - Xuan Wang
- Hepatobiliary and Pancreatic Center, Medical Research Center, Beijing Tsinghua Changgung Hospital, Beijing, 102218, China
| | - Yaning Wang
- Key Laboratory for Stem Cells and Tissue Engineering, Ministry of Education, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, 510080, China
- Advanced Medical Technology Center, The First Affiliated Hospital, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, 510080, China
| | - Yuhan Wang
- University of Chinese Academy of Sciences, Beijing, 100049, China
- State Key Laboratory of Membrane Biology, 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
| | - Rimo Wu
- Bioland Laboratory (Guangzhou Regenerative Medicine and Health Guangdong Laboratory), Guangzhou, 510005, China
| | - Kai Xia
- Center for Stem Cell Biologyand Tissue Engineering, Key Laboratory for Stem Cells and Tissue Engineering, Ministry of Education, Sun Yat-sen University, Guangzhou, 510080, China
- National-Local Joint Engineering Research Center for Stem Cells and Regenerative Medicine, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, 510080, China
| | - Fu-Hui Xiao
- CAS Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming, 650223, China
- State Key Laboratory of Genetic Resources and Evolution, Key Laboratory of Healthy Aging Research of Yunnan Province, Kunming Key Laboratory of Healthy Aging Study, KIZ/CUHK Joint Laboratory of Bioresources and Molecular Research in Common Diseases, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650223, China
| | - Lingyan Xu
- Shanghai Key Laboratory of Regulatory Biology, Institute of Biomedical Sciences and School of Life Sciences, East China Normal University, Shanghai, 200241, China
| | - Yingying Xu
- 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
| | - Haoteng Yan
- Beijing Municipal Geriatric Medical Research Center, 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
- Advanced Innovation Center for Human Brain Protection, and National Clinical Research Center for Geriatric Disorders, Xuanwu Hospital Capital Medical University, Beijing, 100053, China
| | - Liang Yang
- CAS Key Laboratory of Regenerative Biology, Joint School of Life Sciences, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou Medical University, Guangzhou, 510530, China
| | - Ruici Yang
- State Key Laboratory of Cell Biology, Shanghai Institute of Biochemistry and Cell Biology, Center for Excellence in Molecular Cell Science, Chinese Academy of Sciences, University of Chinese Academy of Sciences, Shanghai, 200031, China
| | - Yuanxin Yang
- Interdisciplinary Research Center on Biology and Chemistry, Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences, Shanghai, 201210, China
| | - Yilin Ying
- Department of Geriatrics, Medical Center on Aging of Shanghai Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
- International Laboratory in Hematology and Cancer, Shanghai Jiao Tong University School of Medicine/Ruijin Hospital, Shanghai, 200025, China
| | - Le Zhang
- Gerontology Center of Hubei Province, Wuhan, 430000, China
- Institute of Gerontology, Department of Geriatrics, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China
| | - Weiwei Zhang
- Department of Cardiology, The Second Medical Centre, Chinese PLA General Hospital, National Clinical Research Center for Geriatric Diseases, Beijing, 100853, China
| | - Wenwan Zhang
- CAS Key Laboratory of Tissue Microenvironment and Tumor, Shanghai Institute of Nutrition and Health, Chinese Academy of Sciences, Shanghai, 200031, China
| | - Xing Zhang
- Key Laboratory of Ministry of Education, School of Aerospace Medicine, Fourth Military Medical University, Xi'an, 710032, China
| | - Zhuo Zhang
- Optogenetics & Synthetic Biology Interdisciplinary Research Center, State Key Laboratory of Bioreactor Engineering, Shanghai Frontiers Science Center of Optogenetic Techniques for Cell Metabolism, School of Pharmacy, East China University of Science and Technology, Shanghai, 200237, China
- Research Unit of New Techniques for Live-cell Metabolic Imaging, Chinese Academy of Medical Sciences, Beijing, 100730, China
| | - Min Zhou
- Department of Endocrinology, Endocrinology Research Center, Xiangya Hospital of Central South University, Changsha, 410008, China
| | - Rui Zhou
- Department of Nuclear Medicine and PET Center, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, 310009, China
| | - Qingchen Zhu
- CAS Key Laboratory of Tissue Microenvironment and Tumor, Shanghai Institute of Nutrition and Health, Chinese Academy of Sciences, Shanghai, 200031, China
| | - Zhengmao Zhu
- Department of Genetics and Cell Biology, College of Life Science, Nankai University, Tianjin, 300071, China
- Haihe Laboratory of Cell Ecosystem, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin, 300020, China
| | - Feng Cao
- Department of Cardiology, The Second Medical Centre, Chinese PLA General Hospital, National Clinical Research Center for Geriatric Diseases, Beijing, 100853, China.
| | - Zhongwei Cao
- State Key Laboratory of Biotherapy, West China Second University Hospital, Sichuan University, Chengdu, 610041, China.
| | - Piu Chan
- National Clinical Research Center for Geriatric Diseases, Xuanwu Hospital, Capital Medical University, Beijing, 100053, China.
| | - Chang Chen
- National Laboratory of Biomacromolecules, CAS Center for Excellence in Biomacromolecules, Institute of Biophysics, Chinese Academy of Sciences, Beijing, 100101, China.
| | - Guobing Chen
- Department of Microbiology and Immunology, School of Medicine, Jinan University, Guangzhou, 510632, China.
- Guangdong-Hong Kong-Macau Great Bay Area Geroscience Joint Laboratory, Guangzhou, 510000, China.
| | - Hou-Zao Chen
- Department of Biochemistryand Molecular Biology, State Key Laboratory of Medical Molecular Biology, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100005, China.
| | - Jun Chen
- Peking University Research Center on Aging, Beijing Key Laboratory of Protein Posttranslational Modifications and Cell Function, Department of Biochemistry and Molecular Biology, Department of Integration of Chinese and Western Medicine, School of Basic Medical Science, Peking University, Beijing, 100191, China.
| | - Weimin Ci
- 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.
| | - Bi-Sen Ding
- State Key Laboratory of Biotherapy, West China Second University Hospital, Sichuan University, Chengdu, 610041, China.
| | - Qiurong Ding
- CAS Key Laboratory of Nutrition, Metabolism and Food Safety, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, 200031, China.
| | - Feng Gao
- Key Laboratory of Ministry of Education, School of Aerospace Medicine, Fourth Military Medical University, Xi'an, 710032, China.
| | - Jing-Dong J Han
- Peking-Tsinghua Center for Life Sciences, Academy for Advanced Interdisciplinary Studies, Center for Quantitative Biology (CQB), Peking University, Beijing, 100871, China.
| | - Kai Huang
- Clinic Center of Human Gene Research, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China.
- Hubei Clinical Research Center of Metabolic and Cardiovascular Disease, Huazhong University of Science and Technology, Wuhan, 430022, China.
- Hubei Key Laboratory of Metabolic Abnormalities and Vascular Aging, Huazhong University of Science and Technology, Wuhan, 430022, China.
- Department of Cardiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China.
| | - Zhenyu Ju
- Key Laboratory of Regenerative Medicine of Ministry of Education, Institute of Ageing and Regenerative Medicine, Jinan University, Guangzhou, 510632, China.
| | - Qing-Peng Kong
- CAS Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming, 650223, China.
- State Key Laboratory of Genetic Resources and Evolution, Key Laboratory of Healthy Aging Research of Yunnan Province, Kunming Key Laboratory of Healthy Aging Study, KIZ/CUHK Joint Laboratory of Bioresources and Molecular Research in Common Diseases, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650223, China.
| | - Ji Li
- Department of Dermatology, Xiangya Hospital, Central South University, Changsha, 410008, China.
- Hunan Key Laboratory of Aging Biology, Xiangya Hospital, Central South University, Changsha, 410008, China.
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, 410008, China.
| | - Jian Li
- The Key Laboratory of Geriatrics, Beijing Institute of Geriatrics, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing Hospital/National Center of Gerontology of National Health Commission, Beijing, 100730, China.
| | - Xin Li
- 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.
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China.
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing, 100101, China.
| | - Baohua Liu
- School of Basic Medical Sciences, Shenzhen University Medical School, Shenzhen, 518060, China.
| | - Feng Liu
- Metabolic Syndrome Research Center, The Second Xiangya Hospital, Central South Unversity, Changsha, 410011, China.
| | - Lin Liu
- Department of Genetics and Cell Biology, College of Life Science, Nankai University, Tianjin, 300071, China.
- Haihe Laboratory of Cell Ecosystem, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin, 300020, China.
- Institute of Translational Medicine, Tianjin Union Medical Center, Nankai University, Tianjin, 300000, China.
- State Key Laboratory of Medicinal Chemical Biology, Nankai University, Tianjin, 300350, China.
| | - Qiang Liu
- Department of Neurology, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, 230036, China.
| | - Qiang Liu
- Department of Neurology, Tianjin Neurological Institute, Tianjin Medical University General Hospital, Tianjin, 300052, China.
- Tianjin Institute of Immunology, Tianjin Medical University, Tianjin, 300070, China.
| | - Xingguo Liu
- CAS Key Laboratory of Regenerative Biology, Joint School of Life Sciences, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou Medical University, Guangzhou, 510530, China.
| | - Yong Liu
- College of Life Sciences, TaiKang Center for Life and Medical Sciences, Wuhan University, Wuhan, 430072, China.
| | - Xianghang Luo
- Department of Endocrinology, Endocrinology Research Center, Xiangya Hospital of Central South University, Changsha, 410008, China.
| | - Shuai Ma
- University of Chinese Academy of Sciences, Beijing, 100049, China.
- State Key Laboratory of Membrane Biology, 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.
| | - Xinran Ma
- Shanghai Key Laboratory of Regulatory Biology, Institute of Biomedical Sciences and School of Life Sciences, East China Normal University, Shanghai, 200241, China.
| | - Zhiyong Mao
- Shanghai Key Laboratory of Maternal Fetal Medicine, Clinical and Translational Research Center of Shanghai First Maternity and Infant Hospital, Frontier Science Center for Stem Cell Research, Shanghai Key Laboratory of Signaling and Disease Research, School of Life Sciences and Technology, Tongji University, Shanghai, 200092, China.
| | - Jing Nie
- The State Key Laboratory of Organ Failure Research, National Clinical Research Center of Kidney Disease, Division of Nephrology, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, China.
| | - Yaojin Peng
- 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 for Stem Cell and Regenerative Medicine, Beijing, 100101, China.
| | - Jing Qu
- 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.
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China.
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing, 100101, China.
| | - Jie Ren
- 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.
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China.
| | - Ruibao Ren
- Shanghai Institute of Hematology, State Key Laboratory for Medical Genomics, National Research Center for Translational Medicine (Shanghai), International Center for Aging and Cancer, Collaborative Innovation Center of Hematology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China.
- International Center for Aging and Cancer, Hainan Medical University, Haikou, 571199, China.
| | - Moshi Song
- University of Chinese Academy of Sciences, Beijing, 100049, China.
- State Key Laboratory of Membrane Biology, 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.
| | - Zhou Songyang
- MOE Key Laboratory of Gene Function and Regulation, Guangzhou Key Laboratory of Healthy Aging Research, School of Life Sciences, Institute of Healthy Aging Research, Sun Yat-sen University, Guangzhou, 510275, China.
- Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, 510120, China.
| | - Yi Eve Sun
- Stem Cell Translational Research Center, Tongji Hospital, Tongji University School of Medicine, Shanghai, 200065, China.
| | - Yu Sun
- CAS Key Laboratory of Tissue Microenvironment and Tumor, Shanghai Institute of Nutrition and Health, Chinese Academy of Sciences, Shanghai, 200031, China.
- Department of Medicine and VAPSHCS, University of Washington, Seattle, WA, 98195, USA.
| | - Mei Tian
- Human Phenome Institute, Fudan University, Shanghai, 201203, China.
| | - Shusen Wang
- Research Institute of Transplant Medicine, Organ Transplant Center, NHC Key Laboratory for Critical Care Medicine, Tianjin First Central Hospital, Nankai University, Tianjin, 300384, China.
| | - Si Wang
- Beijing Municipal Geriatric Medical Research Center, 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.
- Advanced Innovation Center for Human Brain Protection, and National Clinical Research Center for Geriatric Disorders, Xuanwu Hospital Capital Medical University, Beijing, 100053, China.
| | - Xia Wang
- School of Pharmaceutical Sciences, Tsinghua University, Beijing, 100084, China.
| | - Xiaoning Wang
- Institute of Geriatrics, The second Medical Center, Beijing Key Laboratory of Aging and Geriatrics, National Clinical Research Center for Geriatric Diseases, Chinese PLA General Hospital, Beijing, 100853, China.
| | - Yan-Jiang Wang
- Department of Neurology and Center for Clinical Neuroscience, Daping Hospital, Third Military Medical University, Chongqing, 400042, China.
| | - Yunfang Wang
- Hepatobiliary and Pancreatic Center, Medical Research Center, Beijing Tsinghua Changgung Hospital, Beijing, 102218, China.
| | - Catherine C L Wong
- Clinical Research Institute, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Science & Peking Union Medical College, Beijing, 100730, China.
| | - Andy Peng Xiang
- Center for Stem Cell Biologyand Tissue Engineering, Key Laboratory for Stem Cells and Tissue Engineering, Ministry of Education, Sun Yat-sen University, Guangzhou, 510080, China.
- National-Local Joint Engineering Research Center for Stem Cells and Regenerative Medicine, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, 510080, China.
| | - Yichuan Xiao
- CAS Key Laboratory of Tissue Microenvironment and Tumor, Shanghai Institute of Nutrition and Health, Chinese Academy of Sciences, Shanghai, 200031, China.
| | - Zhengwei Xie
- Peking University International Cancer Institute, Health Science Center, Peking University, Beijing, 100101, China.
- Beijing & Qingdao Langu Pharmaceutical R&D Platform, Beijing Gigaceuticals Tech. Co. Ltd., Beijing, 100101, China.
| | - Daichao Xu
- Interdisciplinary Research Center on Biology and Chemistry, Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences, Shanghai, 201210, China.
| | - Jing Ye
- Department of Geriatrics, Medical Center on Aging of Shanghai Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China.
- International Laboratory in Hematology and Cancer, Shanghai Jiao Tong University School of Medicine/Ruijin Hospital, Shanghai, 200025, China.
| | - Rui Yue
- Institute for Regenerative Medicine, Shanghai East Hospital, Frontier Science Center for Stem Cell Research, Shanghai Key Laboratory of Signaling and Disease Research, School of Life Sciences and Technology, Tongji University, Shanghai, 200092, China.
| | - Cuntai Zhang
- Gerontology Center of Hubei Province, Wuhan, 430000, China.
- Institute of Gerontology, Department of Geriatrics, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China.
| | - Hongbo Zhang
- Key Laboratory for Stem Cells and Tissue Engineering, Ministry of Education, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, 510080, China.
- Advanced Medical Technology Center, The First Affiliated Hospital, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, 510080, China.
| | - Liang Zhang
- CAS Key Laboratory of Tissue Microenvironment and Tumor, Shanghai Institute of Nutrition and Health, Chinese Academy of Sciences, Shanghai, 200031, China.
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, 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.
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China.
| | - Yong Zhang
- Bioland Laboratory (Guangzhou Regenerative Medicine and Health Guangdong Laboratory), Guangzhou, 510005, China.
- The State Key Laboratory of Medical Molecular Biology, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences and School of Basic Medicine, Peking Union Medical College, Beijing, 100005, China.
| | - Yun-Wu Zhang
- Fujian Provincial Key Laboratory of Neurodegenerative Disease and Aging Research, Institute of Neuroscience, School of Medicine, Xiamen University, Xiamen, 361102, China.
| | - Zhuohua Zhang
- Key Laboratory of Molecular Precision Medicine of Hunan Province and Center for Medical Genetics, Institute of Molecular Precision Medicine, Xiangya Hospital, Central South University, Changsha, 410078, China.
- Department of Neurosciences, Hengyang Medical School, University of South China, Hengyang, 421001, China.
| | - Tongbiao Zhao
- 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.
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China.
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing, 100101, China.
| | - Yuzheng Zhao
- Optogenetics & Synthetic Biology Interdisciplinary Research Center, State Key Laboratory of Bioreactor Engineering, Shanghai Frontiers Science Center of Optogenetic Techniques for Cell Metabolism, School of Pharmacy, East China University of Science and Technology, Shanghai, 200237, China.
- Research Unit of New Techniques for Live-cell Metabolic Imaging, Chinese Academy of Medical Sciences, Beijing, 100730, China.
| | - Dahai Zhu
- Bioland Laboratory (Guangzhou Regenerative Medicine and Health Guangdong Laboratory), Guangzhou, 510005, China.
- The State Key Laboratory of Medical Molecular Biology, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences and School of Basic Medicine, Peking Union Medical College, Beijing, 100005, China.
| | - Weiguo Zou
- State Key Laboratory of Cell Biology, Shanghai Institute of Biochemistry and Cell Biology, Center for Excellence in Molecular Cell Science, Chinese Academy of Sciences, University of Chinese Academy of Sciences, Shanghai, 200031, China.
| | - Gang Pei
- Shanghai Key Laboratory of Signaling and Disease Research, Laboratory of Receptor-Based Biomedicine, The Collaborative Innovation Center for Brain Science, School of Life Sciences and Technology, Tongji University, Shanghai, 200070, China.
| | - Guang-Hui Liu
- University of Chinese Academy of Sciences, Beijing, 100049, China.
- State Key Laboratory of Membrane Biology, 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.
- Advanced Innovation Center for Human Brain Protection, and National Clinical Research Center for Geriatric Disorders, Xuanwu Hospital Capital Medical University, Beijing, 100053, China.
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Johnson AA, Cuellar TL. Glycine and aging: Evidence and mechanisms. Ageing Res Rev 2023; 87:101922. [PMID: 37004845 DOI: 10.1016/j.arr.2023.101922] [Citation(s) in RCA: 18] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2023] [Accepted: 03/30/2023] [Indexed: 04/03/2023]
Abstract
The restriction of calories, branched-chain amino acids, and methionine have all been shown to extend lifespan in model organisms. Recently, glycine was shown to significantly boost longevity in genetically heterogenous mice. This simple amino acid similarly extends lifespan in rats and improves health in mammalian models of age-related disease. While compelling data indicate that glycine is a pro-longevity molecule, divergent mechanisms may underlie its effects on aging. Glycine is abundant in collagen, a building block for glutathione, a precursor to creatine, and an acceptor for the enzyme Glycine N-methyltransferase (GNMT). A review of the literature strongly implicates GNMT, which clears methionine from the body by taking a methyl group from S-adenosyl-L-methionine and methylating glycine to form sarcosine. In flies, Gnmt is required for reduced insulin/insulin-like growth factor 1 signaling and caloric restriction to fully extend lifespan. The geroprotector spermidine requires Gnmt to upregulate autophagy genes and boost longevity. Moreover, the overexpression of Gnmt is sufficient to extend lifespan and reduce methionine levels. Sarcosine, or methylglycine, declines with age in multiple species and is capable of inducing autophagy both in vitro and in vivo. Taken all together, existing evidence suggests that glycine prolongs life by mimicking methionine restriction and activating autophagy.
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Reeve EH, Kronquist EK, Wolf JR, Lee B, Khurana A, Pham H, Cullen AE, Peterson JA, Meza A, Colton Bramwell R, Villasana L, Machin DR, Henson GD, Walker AE. Pyridoxamine treatment ameliorates large artery stiffening and cerebral artery endothelial dysfunction in old mice. J Cereb Blood Flow Metab 2023; 43:281-295. [PMID: 36189840 PMCID: PMC9903220 DOI: 10.1177/0271678x221130124] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/21/2023]
Abstract
Age-related increases in large artery stiffness are associated with cerebrovascular dysfunction and cognitive impairment. Pyridoxamine treatment prevents large artery stiffening with advancing age, but the effects of pyridoxamine treatment on the cerebral vasculature or cognition is unknown. The purpose of this study was to investigate the effects of pyridoxamine on blood pressure, large artery stiffness, cerebral artery function, and cognitive function in old mice. Old male C57BL/6 mice consumed either pyridoxamine (2 g/L) or vehicle control in drinking water for ∼7.5 months and were compared with young male C57BL/6 mice. From pre- to post-treatment, systolic blood pressure increased in old control mice, but was maintained in pyridoxamine treated mice. Large artery stiffness decreased in pyridoxamine-treated mice but was unaffected in control mice. Pyridoxamine-treated mice had greater cerebral artery endothelium-dependent dilation compared with old control mice, and not different from young mice. Old control mice had impaired cognitive function; however, pyridoxamine only partially preserved cognitive function in old mice. In summary, pyridoxamine treatment in old mice prevented age-related increases in blood pressure, reduced large artery stiffness, preserved cerebral artery endothelial function, and partially preserved cognitive function. Taken together, these results suggest that pyridoxamine treatment may limit vascular aging.
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Affiliation(s)
- Emily H Reeve
- Department of Human Physiology, 3265, University of Oregon, Eugene, OR, USA
| | - Elise K Kronquist
- Department of Human Physiology, 3265, University of Oregon, Eugene, OR, USA
| | - Julia R Wolf
- Department of Human Physiology, 3265, University of Oregon, Eugene, OR, USA
| | - Byron Lee
- Department of Human Physiology, 3265, University of Oregon, Eugene, OR, USA
| | - Aleena Khurana
- Department of Human Physiology, 3265, University of Oregon, Eugene, OR, USA
| | - Hanson Pham
- Department of Human Physiology, 3265, University of Oregon, Eugene, OR, USA
| | - Abigail E Cullen
- Department of Human Physiology, 3265, University of Oregon, Eugene, OR, USA
| | - Jessica A Peterson
- Department of Human Physiology, 3265, University of Oregon, Eugene, OR, USA
| | - Antonio Meza
- Department of Internal Medicine, University of Utah, Salt Lake City, UT, USA
| | - R Colton Bramwell
- Department of Internal Medicine, University of Utah, Salt Lake City, UT, USA
| | | | - Daniel R Machin
- Department of Internal Medicine, University of Utah, Salt Lake City, UT, USA
- Department of Nutrition and Integrative Physiology, 7823, Florida State University, Tallahassee, FL, USA
| | - Grant D Henson
- Department of Human Physiology, 3265, University of Oregon, Eugene, OR, USA
| | - Ashley E Walker
- Department of Human Physiology, 3265, University of Oregon, Eugene, OR, USA
- Department of Internal Medicine, University of Utah, Salt Lake City, UT, USA
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39
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Shu DY, Chaudhary S, Cho KS, Lennikov A, Miller WP, Thorn DC, Yang M, McKay TB. Role of Oxidative Stress in Ocular Diseases: A Balancing Act. Metabolites 2023; 13:187. [PMID: 36837806 PMCID: PMC9960073 DOI: 10.3390/metabo13020187] [Citation(s) in RCA: 45] [Impact Index Per Article: 22.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2022] [Revised: 01/22/2023] [Accepted: 01/24/2023] [Indexed: 01/31/2023] Open
Abstract
Redox homeostasis is a delicate balancing act of maintaining appropriate levels of antioxidant defense mechanisms and reactive oxidizing oxygen and nitrogen species. Any disruption of this balance leads to oxidative stress, which is a key pathogenic factor in several ocular diseases. In this review, we present the current evidence for oxidative stress and mitochondrial dysfunction in conditions affecting both the anterior segment (e.g., dry eye disease, keratoconus, cataract) and posterior segment (age-related macular degeneration, proliferative vitreoretinopathy, diabetic retinopathy, glaucoma) of the human eye. We posit that further development of therapeutic interventions to promote pro-regenerative responses and maintenance of the redox balance may delay or prevent the progression of these major ocular pathologies. Continued efforts in this field will not only yield a better understanding of the molecular mechanisms underlying the pathogenesis of ocular diseases but also enable the identification of novel druggable redox targets and antioxidant therapies.
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Affiliation(s)
- Daisy Y. Shu
- Department of Ophthalmology, Schepens Eye Research Institute of Mass Eye and Ear, Harvard Medical School, Boston, MA 02114, USA
| | - Suman Chaudhary
- Department of Ophthalmology, Schepens Eye Research Institute of Mass Eye and Ear, Harvard Medical School, Boston, MA 02114, USA
| | - Kin-Sang Cho
- Department of Ophthalmology, Schepens Eye Research Institute of Mass Eye and Ear, Harvard Medical School, Boston, MA 02114, USA
| | - Anton Lennikov
- Department of Ophthalmology, Schepens Eye Research Institute of Mass Eye and Ear, Harvard Medical School, Boston, MA 02114, USA
| | - William P. Miller
- Department of Ophthalmology, Schepens Eye Research Institute of Mass Eye and Ear, Harvard Medical School, Boston, MA 02114, USA
| | - David C. Thorn
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA 02138, USA
| | - Menglu Yang
- Department of Ophthalmology, Schepens Eye Research Institute of Mass Eye and Ear, Harvard Medical School, Boston, MA 02114, USA
| | - Tina B. McKay
- Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114, USA
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40
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Buckley MT, Sun ED, George BM, Liu L, Schaum N, Xu L, Reyes JM, Goodell MA, Weissman IL, Wyss-Coray T, Rando TA, Brunet A. Cell-type-specific aging clocks to quantify aging and rejuvenation in neurogenic regions of the brain. NATURE AGING 2023; 3:121-137. [PMID: 37118510 PMCID: PMC10154228 DOI: 10.1038/s43587-022-00335-4] [Citation(s) in RCA: 79] [Impact Index Per Article: 39.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/25/2022] [Accepted: 11/14/2022] [Indexed: 12/24/2022]
Abstract
The diversity of cell types is a challenge for quantifying aging and its reversal. Here we develop 'aging clocks' based on single-cell transcriptomics to characterize cell-type-specific aging and rejuvenation. We generated single-cell transcriptomes from the subventricular zone neurogenic region of 28 mice, tiling ages from young to old. We trained single-cell-based regression models to predict chronological age and biological age (neural stem cell proliferation capacity). These aging clocks are generalizable to independent cohorts of mice, other regions of the brains, and other species. To determine if these aging clocks could quantify transcriptomic rejuvenation, we generated single-cell transcriptomic datasets of neurogenic regions for two interventions-heterochronic parabiosis and exercise. Aging clocks revealed that heterochronic parabiosis and exercise reverse transcriptomic aging in neurogenic regions, but in different ways. This study represents the first development of high-resolution aging clocks from single-cell transcriptomic data and demonstrates their application to quantify transcriptomic rejuvenation.
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Affiliation(s)
- Matthew T Buckley
- Department of Genetics, Stanford University, Stanford, CA, USA
- Genetics Graduate Program, Stanford University, Stanford, CA, USA
| | - Eric D Sun
- Department of Genetics, Stanford University, Stanford, CA, USA
- Biomedical Informatics Graduate Program, Stanford University, Stanford, CA, USA
| | - Benson M George
- Stanford Medical Scientist Training Program, Stanford University, Stanford, CA, USA
- Institute for Stem Cell Biology and Regenerative Medicine, Stanford University, Stanford, CA, USA
| | - Ling Liu
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA, USA
- Department of Neurology, UCLA, Los Angeles, CA, USA
| | - Nicholas Schaum
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA, USA
| | - Lucy Xu
- Department of Genetics, Stanford University, Stanford, CA, USA
- Department of Biology, Stanford University, Stanford, CA, USA
| | - Jaime M Reyes
- Stem Cells and Regenerative Medicine Center, Baylor College of Medicine, Houston, TX, USA
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA
- Department of Molecular and Cellular Biology, Baylor College of Medicine, Houston, TX, USA
| | - Margaret A Goodell
- Stem Cells and Regenerative Medicine Center, Baylor College of Medicine, Houston, TX, USA
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA
- Department of Molecular and Cellular Biology, Baylor College of Medicine, Houston, TX, USA
| | - Irving L Weissman
- Institute for Stem Cell Biology and Regenerative Medicine, Stanford University, Stanford, CA, USA
- Ludwig Center for Cancer Stem Cell Research and Medicine, Stanford University School of Medicine, Stanford, CA, USA
- Stanford Cancer Institute, Stanford University School of Medicine, Stanford, CA, USA
- Department of Pathology, Stanford University School of Medicine, Stanford, CA, USA
| | - Tony Wyss-Coray
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA, USA
- Wu Tsai Neurosciences Institute, Stanford University, Stanford, CA, USA
- Glenn Center for the Biology of Aging, Stanford University, Stanford, CA, USA
| | - Thomas A Rando
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA, USA
- Glenn Center for the Biology of Aging, Stanford University, Stanford, CA, USA
- Neurology Service, Veterans Affairs Palo Alto Health Care System, Palo Alto, CA, USA
- Department of Neurology, UCLA, Los Angeles, CA, USA
- Broad Stem Cell Research Center, UCLA, Los Angeles, CA, USA
| | - Anne Brunet
- Department of Genetics, Stanford University, Stanford, CA, USA.
- Wu Tsai Neurosciences Institute, Stanford University, Stanford, CA, USA.
- Glenn Center for the Biology of Aging, Stanford University, Stanford, CA, USA.
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41
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Liu X, Li XJ, Lin L. Dynamic 5-Hydroxymethylcytosine Change: Implication for Aging of Non-Human Primate Brain. EPIGENOMES 2022; 6:epigenomes6040041. [PMID: 36547250 PMCID: PMC9777599 DOI: 10.3390/epigenomes6040041] [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: 10/31/2022] [Revised: 11/18/2022] [Accepted: 11/26/2022] [Indexed: 11/29/2022] Open
Abstract
Profiling of 5-hydroxymethylcytosine (5hmC) in the brain regions of rhesus monkey at different ages reveals accumulation and tissue-specific patterns of 5hmC with aging. Region-specific differentially hydroxymethylated regions (DhMRs) are involved in neuronal functions and signal transduction. These data suggest that 5hmC may be a key regulator of gene transcription in neurodevelopment and thus a potential candidate for the epigenetic clock. Importantly, non-human primates are the ideal animal models for investigation of human aging and diseases not only because they are more genetically similar to humans but also epigenetically.
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42
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Farrell S, Kane AE, Bisset E, Howlett SE, Rutenberg AD. Measurements of damage and repair of binary health attributes in aging mice and humans reveal that robustness and resilience decrease with age, operate over broad timescales, and are affected differently by interventions. eLife 2022; 11:e77632. [PMID: 36409200 PMCID: PMC9725749 DOI: 10.7554/elife.77632] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2022] [Accepted: 11/20/2022] [Indexed: 11/23/2022] Open
Abstract
As an organism ages, its health-state is determined by a balance between the processes of damage and repair. Measuring these processes requires longitudinal data. We extract damage and repair transition rates from repeated observations of binary health attributes in mice and humans to explore robustness and resilience, which respectively represent resisting or recovering from damage. We assess differences in robustness and resilience using changes in damage rates and repair rates of binary health attributes. We find a conserved decline with age in robustness and resilience in mice and humans, implying that both contribute to worsening aging health - as assessed by the frailty index (FI). A decline in robustness, however, has a greater effect than a decline in resilience on the accelerated increase of the FI with age, and a greater association with reduced survival. We also find that deficits are damaged and repaired over a wide range of timescales ranging from the shortest measurement scales toward organismal lifetime timescales. We explore the effect of systemic interventions that have been shown to improve health, including the angiotensin-converting enzyme inhibitor enalapril and voluntary exercise for mice. We have also explored the correlations with household wealth for humans. We find that these interventions and factors affect both damage and repair rates, and hence robustness and resilience, in age and sex-dependent manners.
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Affiliation(s)
| | - Alice E Kane
- Blavatnik Institute, Department of Genetics, Paul F. Glenn Center for Biology of Aging Research at Harvard Medical SchoolBostonUnited States
| | - Elise Bisset
- Department of Pharmacology, Dalhousie UniversityHalifaxCanada
| | - Susan E Howlett
- Department of Pharmacology, Dalhousie UniversityHalifaxCanada
- Department of Medicine (GeriatricMedicine), Dalhousie UniversityHalifaxCanada
| | - Andrew D Rutenberg
- Department of Physics and Atmospheric Science, Dalhousie UniversityHalifaxCanada
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43
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Avchaciov K, Antoch MP, Andrianova EL, Tarkhov AE, Menshikov LI, Burmistrova O, Gudkov AV, Fedichev PO. Unsupervised learning of aging principles from longitudinal data. Nat Commun 2022; 13:6529. [PMID: 36319638 PMCID: PMC9626636 DOI: 10.1038/s41467-022-34051-9] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2020] [Accepted: 10/06/2022] [Indexed: 11/07/2022] Open
Abstract
Age is the leading risk factor for prevalent diseases and death. However, the relation between age-related physiological changes and lifespan is poorly understood. We combined analytical and machine learning tools to describe the aging process in large sets of longitudinal measurements. Assuming that aging results from a dynamic instability of the organism state, we designed a deep artificial neural network, including auto-encoder and auto-regression (AR) components. The AR model tied the dynamics of physiological state with the stochastic evolution of a single variable, the "dynamic frailty indicator" (dFI). In a subset of blood tests from the Mouse Phenome Database, dFI increased exponentially and predicted the remaining lifespan. The observation of the limiting dFI was consistent with the late-life mortality deceleration. dFI changed along with hallmarks of aging, including frailty index, molecular markers of inflammation, senescent cell accumulation, and responded to life-shortening (high-fat diet) and life-extending (rapamycin) treatments.
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Affiliation(s)
| | - Marina P Antoch
- Department of Pharmacology and Therapeutics, Roswell Park Comprehensive Cancer Center, Buffalo, NY, USA
| | | | | | | | | | - Andrei V Gudkov
- Genome Protection, Inc., Buffalo, NY, USA
- Department of Cell Stress Biology, Roswell Park Comprehensive Cancer Center, Buffalo, NY, USA
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44
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Shindyapina AV, Cho Y, Kaya A, Tyshkovskiy A, Castro JP, Deik A, Gordevicius J, Poganik JR, Clish CB, Horvath S, Peshkin L, Gladyshev VN. Rapamycin treatment during development extends life span and health span of male mice and Daphnia magna. SCIENCE ADVANCES 2022; 8:eabo5482. [PMID: 36112674 PMCID: PMC9481125 DOI: 10.1126/sciadv.abo5482] [Citation(s) in RCA: 44] [Impact Index Per Article: 14.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/10/2022] [Accepted: 07/26/2022] [Indexed: 05/22/2023]
Abstract
Development is tightly connected to aging, but whether pharmacologically targeting development can extend life remains unknown. Here, we subjected genetically diverse UMHET3 mice to rapamycin for the first 45 days of life. The mice grew slower and remained smaller than controls for their entire lives. Their reproductive age was delayed without affecting offspring numbers. The treatment was sufficient to extend the median life span by 10%, with the strongest effect in males, and helped to preserve health as measured by frailty index scores, gait speed, and glucose and insulin tolerance tests. Mechanistically, the liver transcriptome and epigenome of treated mice were younger at the completion of treatment. Analogous to mice, rapamycin exposure during development robustly extended the life span of Daphnia magna and reduced its body size. Overall, the results demonstrate that short-term rapamycin treatment during development is a novel longevity intervention that acts by slowing down development and aging, suggesting that aging may be targeted already early in life.
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Affiliation(s)
| | - Yongmin Cho
- Department of Systems Biology, Harvard Medical School, Boston, MA 02115, USA
| | - Alaattin Kaya
- Department of Biology, Virginia Commonwealth University, Richmond, VA 23284, USA
| | - Alexander Tyshkovskiy
- Brigham and Women’s Hospital, Harvard Medical School, Boston, MA 02115, USA
- Belozersky Institute of Physico-Chemical Biology, Moscow State University, Moscow 119234, Russia
| | - José P. Castro
- Brigham and Women’s Hospital, Harvard Medical School, Boston, MA 02115, USA
| | - Amy Deik
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | | | - Jesse R. Poganik
- Brigham and Women’s Hospital, Harvard Medical School, Boston, MA 02115, USA
| | - Clary B. Clish
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Steve Horvath
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - Leonid Peshkin
- Department of Systems Biology, Harvard Medical School, Boston, MA 02115, USA
- Eugene Bell Center for Regenerative Biology and Tissue Engineering and National Xenopus Resource, Marine Biological Laboratory, Woods Hole, MA 02543, USA
| | - Vadim N. Gladyshev
- Brigham and Women’s Hospital, Harvard Medical School, Boston, MA 02115, USA
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
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45
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Aiello G, Sabino C, Pernici D, Audano M, Antonica F, Gianesello M, Ballabio C, Quattrone A, Mitro N, Romanel A, Soldano A, Tiberi L. Transient rapamycin treatment during developmental stage extends lifespan in Mus musculus and Drosophila melanogaster. EMBO Rep 2022; 23:e55299. [PMID: 35796299 PMCID: PMC9442325 DOI: 10.15252/embr.202255299] [Citation(s) in RCA: 24] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2022] [Revised: 06/20/2022] [Accepted: 06/23/2022] [Indexed: 12/13/2022] Open
Abstract
Lifespan is determined by complex and tangled mechanisms that are largely unknown. The early postnatal stage has been proposed to play a role in lifespan, but its contribution is still controversial. Here, we show that a short rapamycin treatment during early life can prolong lifespan in Mus musculus and Drosophila melanogaster. Notably, the same treatment at later time points has no effect on lifespan, suggesting that a specific time window is involved in lifespan regulation. We also find that sulfotransferases are upregulated during early rapamycin treatment both in newborn mice and in Drosophila larvae, and transient dST1 overexpression in Drosophila larvae extends lifespan. Our findings unveil a novel link between early-life treatments and long-term effects on lifespan.
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Affiliation(s)
- Giuseppe Aiello
- Armenise‐Harvard Laboratory of Brain Disorders and Cancer, Department CIBIOUniversity of TrentoTrentoItaly
| | - Cosimo Sabino
- Armenise‐Harvard Laboratory of Brain Disorders and Cancer, Department CIBIOUniversity of TrentoTrentoItaly
| | - Davide Pernici
- Armenise‐Harvard Laboratory of Brain Disorders and Cancer, Department CIBIOUniversity of TrentoTrentoItaly
| | - Matteo Audano
- DiSFeB, Dipartimento di Scienze Farmacologiche e BiomolecolariUniversità degli Studi di MilanoMilanItaly
| | - Francesco Antonica
- Armenise‐Harvard Laboratory of Brain Disorders and Cancer, Department CIBIOUniversity of TrentoTrentoItaly
| | - Matteo Gianesello
- Armenise‐Harvard Laboratory of Brain Disorders and Cancer, Department CIBIOUniversity of TrentoTrentoItaly
| | - Claudio Ballabio
- Armenise‐Harvard Laboratory of Brain Disorders and Cancer, Department CIBIOUniversity of TrentoTrentoItaly
| | - Alessandro Quattrone
- Laboratory of Translational Genomics, Department CIBIOUniversity of TrentoTrentoItaly
| | - Nico Mitro
- DiSFeB, Dipartimento di Scienze Farmacologiche e BiomolecolariUniversità degli Studi di MilanoMilanItaly
| | - Alessandro Romanel
- Laboratory of Bioinformatics and Computational Genomics, Department CIBIOUniversity of TrentoTrentoItaly
| | - Alessia Soldano
- Laboratory of Translational Genomics, Department CIBIOUniversity of TrentoTrentoItaly
| | - Luca Tiberi
- Armenise‐Harvard Laboratory of Brain Disorders and Cancer, Department CIBIOUniversity of TrentoTrentoItaly
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46
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Harnett MM, Doonan J, Lumb FE, Crowe J, Damink RO, Buitrago G, Duncombe-Moore J, Wilkinson DI, Suckling CJ, Selman C, Harnett W. The parasitic worm product ES-62 protects the osteoimmunology axis in a mouse model of obesity-accelerated ageing. Front Immunol 2022; 13:953053. [PMID: 36105811 PMCID: PMC9465317 DOI: 10.3389/fimmu.2022.953053] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2022] [Accepted: 08/11/2022] [Indexed: 11/13/2022] Open
Abstract
Despite significant increases in human lifespan over the last century, adoption of high calorie diets (HCD) has driven global increases in type-2 diabetes, obesity and cardiovascular disease, disorders precluding corresponding improvements in healthspan. Reflecting that such conditions are associated with chronic systemic inflammation, evidence is emerging that infection with parasitic helminths might protect against obesity-accelerated ageing, by virtue of their evolution of survival-promoting anti-inflammatory molecules. Indeed, ES-62, an anti-inflammatory secreted product of the filarial nematode Acanthocheilonema viteae, improves the healthspan of both male and female C57BL/6J mice undergoing obesity-accelerated ageing and also extends median lifespan in male animals, by positively impacting on inflammatory, adipose metabolic and gut microbiome parameters of ageing. We therefore explored whether ES-62 affects the osteoimmunology axis that integrates environmental signals, such as diet and the gut microbiome to homeostatically regulate haematopoiesis and training of immune responses, which become dysregulated during (obesity-accelerated) ageing. Of note, we find sexual dimorphisms in the decline in bone health, and associated dysregulation of haematopoiesis and consequent peripheral immune responses, during obesity-accelerated ageing, highlighting the importance of developing sex-specific anti-ageing strategies. Related to this, ES-62 protects trabecular bone structure, maintaining bone marrow (BM) niches that counter the ageing-associated decline in haematopoietic stem cell (HSC) functionality highlighted by a bias towards myeloid lineages, in male but not female, HCD-fed mice. This is evidenced by the ability of ES-62 to suppress the adipocyte and megakaryocyte bias and correspondingly promote increases in B lymphocytes in the BM. Furthermore, the consequent prevention of ageing-associated myeloid/lymphoid skewing is associated with reduced accumulation of inflammatory CD11c+ macrophages and IL-1β in adipose tissue, disrupting the perpetuation of inflammation-driven dysregulation of haematopoiesis during obesity-accelerated ageing in male HCD-fed mice. Finally, we report the ability of small drug-like molecule analogues of ES-62 to mimic some of its key actions, particularly in strongly protecting trabecular bone structure, highlighting the translational potential of these studies.
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Affiliation(s)
- Margaret M. Harnett
- Institute of Infection, Immunity and Inflammation, University of Glasgow, Glasgow, United Kingdom
| | - James Doonan
- Strathclyde Institute of Pharmacy and Biomedical Sciences, University of Strathclyde, Glasgow, United Kingdom
| | - Felicity E. Lumb
- Strathclyde Institute of Pharmacy and Biomedical Sciences, University of Strathclyde, Glasgow, United Kingdom
| | - Jenny Crowe
- Institute of Infection, Immunity and Inflammation, University of Glasgow, Glasgow, United Kingdom
| | - Roel Olde Damink
- Strathclyde Institute of Pharmacy and Biomedical Sciences, University of Strathclyde, Glasgow, United Kingdom
| | - Geraldine Buitrago
- Strathclyde Institute of Pharmacy and Biomedical Sciences, University of Strathclyde, Glasgow, United Kingdom
| | - Josephine Duncombe-Moore
- Institute of Infection, Immunity and Inflammation, University of Glasgow, Glasgow, United Kingdom
| | - Debbie I. Wilkinson
- Institute of Medical Sciences, University of Aberdeen, Aberdeen, United Kingdom
| | - Colin J. Suckling
- Department of Pure and Applied Chemistry, University of Strathclyde, Glasgow, United Kingdom
| | - Colin Selman
- Glasgow Ageing Research Network (GARNER), Institute of Biodiversity, Animal Health and Comparative Medicine, University of Glasgow, Glasgow, United Kingdom
| | - William Harnett
- Strathclyde Institute of Pharmacy and Biomedical Sciences, University of Strathclyde, Glasgow, United Kingdom
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47
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Ceolini E, Brunner I, Bunschoten J, Majoie MH, Thijs RD, Ghosh A. A model of healthy aging based on smartphone interactions reveals advanced behavioral age in neurological disease. iScience 2022; 25:104792. [PMID: 36039359 PMCID: PMC9418593 DOI: 10.1016/j.isci.2022.104792] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2022] [Revised: 05/19/2022] [Accepted: 07/14/2022] [Indexed: 12/02/2022] Open
Abstract
Smartphones offer unique opportunities to trace the convoluted behavioral patterns accompanying healthy aging. Here we captured smartphone touchscreen interactions from a healthy population (N = 684, ∼309 million interactions) spanning 16 to 86 years of age and trained a decision tree regression model to estimate chronological age based on the interactions. The interactions were clustered according to their next interval dynamics to quantify diverse smartphone behaviors. The regression model well-estimated the chronological age in health (mean absolute error = 6 years, R2 = 0.8). We next deployed this model on a population of stroke survivors (N = 41) to find larger prediction errors such that the estimated age was advanced by 6 years. A similar pattern was observed in people with epilepsy (N = 51), with prediction errors advanced by 10 years. The smartphone behavioral model trained in health can be used to study altered aging in neurological diseases.
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Affiliation(s)
- Enea Ceolini
- Cognitive Psychology Unit, Institute of Psychology, Leiden University, Wassenaarseweg 52, Leiden 2333, the Netherlands
| | - Iris Brunner
- IRIS Brunner, Hammel Neurocenter and University Research Clinic, Aarhus University, Aarhus, Denmark
| | - Johanna Bunschoten
- Department of Neurology, Leiden University Medical Centre, Leiden, the Netherlands
- Stichting Epilepsie Instellingen Nederland (SEIN), Heemstede, the Netherlands
| | - Marian H.J.M. Majoie
- Department of Neurology, Academic Centre for Epileptology, Epilepsy Centre Kempenhaeghe & Maastricht University Medical Centre, Maastricht, the Netherlands
- MHeNS, School for Mental Health and Neuroscience, Department of Psychiatry and Neuropsychology, Maastricht University Medical Centre, Maastricht, the Netherlands
- School of Health Professions Education, Faculty of Health, Medicine and Life Sciences, Maastricht University, Maastricht, the Netherlands
| | - Roland D. Thijs
- Department of Neurology, Leiden University Medical Centre, Leiden, the Netherlands
- Stichting Epilepsie Instellingen Nederland (SEIN), Heemstede, the Netherlands
- UCL Queen Square Institute of Neurology, London, UK
| | - Arko Ghosh
- Cognitive Psychology Unit, Institute of Psychology, Leiden University, Wassenaarseweg 52, Leiden 2333, the Netherlands
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48
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McIntyre RL, Rahman M, Vanapalli SA, Houtkooper RH, Janssens GE. Biological Age Prediction From Wearable Device Movement Data Identifies Nutritional and Pharmacological Interventions for Healthy Aging. FRONTIERS IN AGING 2022; 2:708680. [PMID: 35822021 PMCID: PMC9261299 DOI: 10.3389/fragi.2021.708680] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/12/2021] [Accepted: 07/01/2021] [Indexed: 12/14/2022]
Abstract
Intervening in aging processes is hypothesized to extend healthy years of life and treat age-related disease, thereby providing great benefit to society. However, the ability to measure the biological aging process in individuals, which is necessary to test for efficacy of these interventions, remains largely inaccessible to the general public. Here we used NHANES physical activity accelerometer data from a wearable device and machine-learning algorithms to derive biological age predictions for individuals based on their movement patterns. We found that accelerated biological aging from our “MoveAge” predictor is associated with higher all-cause mortality. We further searched for nutritional or pharmacological compounds that associate with decelerated aging according to our model. A number of nutritional components peak in their association to decelerated aging later in life, including fiber, magnesium, and vitamin E. We additionally identified one FDA-approved drug associated with decelerated biological aging: the alpha-blocker doxazosin. We show that doxazosin extends healthspan and lifespan in C. elegans. Our work demonstrates how a biological aging score based on relative mobility can be accessible to the wider public and can potentially be used to identify and determine efficacy of geroprotective interventions.
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Affiliation(s)
- Rebecca L McIntyre
- Laboratory Genetic Metabolic Diseases, Amsterdam Gastroenterology, Endocrinology, and Metabolism, Amsterdam Cardiovascular Sciences, Amsterdam UMC, University of Amsterdam, Amsterdam, Netherlands
| | - Mizanur Rahman
- Department of Chemical Engineering, Texas Tech University, Lubbock, TX, United States
| | - Siva A Vanapalli
- Department of Chemical Engineering, Texas Tech University, Lubbock, TX, United States.,NemaLife Inc., Lubbock, TX, United States
| | - Riekelt H Houtkooper
- Laboratory Genetic Metabolic Diseases, Amsterdam Gastroenterology, Endocrinology, and Metabolism, Amsterdam Cardiovascular Sciences, Amsterdam UMC, University of Amsterdam, Amsterdam, Netherlands
| | - Georges E Janssens
- Laboratory Genetic Metabolic Diseases, Amsterdam Gastroenterology, Endocrinology, and Metabolism, Amsterdam Cardiovascular Sciences, Amsterdam UMC, University of Amsterdam, Amsterdam, Netherlands
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Bisset ES, Howlett SE. The Use of Dietary Supplements and Amino Acid Restriction Interventions to Reduce Frailty in Pre-Clinical Models. Nutrients 2022; 14:2806. [PMID: 35889763 PMCID: PMC9316446 DOI: 10.3390/nu14142806] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2022] [Revised: 06/06/2022] [Accepted: 07/05/2022] [Indexed: 02/04/2023] Open
Abstract
Frailty is a state of accelerated aging that increases susceptibility to adverse health outcomes. Due to its high societal and personal costs, there is growing interest in discovering beneficial interventions to attenuate frailty. Many of these interventions involve the use of lifestyle modifications such as dietary supplements. Testing these interventions in pre-clinical models can facilitate our understanding of their impact on underlying mechanisms of frailty. We conducted a narrative review of studies that investigated the impact of dietary modifications on measures of frailty or overall health in rodent models. These interventions include vitamin supplements, dietary supplements, or amino acid restriction diets. We found that vitamins, amino acid restriction diets, and dietary supplements can have beneficial effects on frailty and other measures of overall health in rodent models. Mechanistic studies show that these effects are mediated by modifying one or more mechanisms underlying frailty, in particular effects on chronic inflammation. However, many interventions do not measure frailty directly and most do not investigate effects in both sexes, which limits their applicability. Examining dietary interventions in animal models allows for detailed investigation of underlying mechanisms involved in their beneficial effects. This may lead to more successful, translatable interventions to attenuate frailty.
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Affiliation(s)
- Elise S. Bisset
- Department of Pharmacology, Dalhousie University, P.O. Box 15000, Halifax, NS B3H 4R2, Canada;
| | - Susan E. Howlett
- Department of Pharmacology, Dalhousie University, P.O. Box 15000, Halifax, NS B3H 4R2, Canada;
- Department of Medicine (Geriatric Medicine), Dalhousie University, P.O. Box 15000, Halifax, NS B3H 4R2, Canada
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50
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Bernier M, Enamorado IN, Gómez-Cabrera MC, Calvo-Rubio M, González-Reyes JA, Price NL, Cortés-Rodríguez AB, Rodríguez-Aguilera JC, Rodríguez-López S, Mitchell SJ, Murt KN, Kalafut K, Williams KM, Ward CW, Stains JP, Brea-Calvo G, Villalba JM, Cortassa S, Aon MA, de Cabo R. Age-dependent impact of two exercise training regimens on genomic and metabolic remodeling in skeletal muscle and liver of male mice. NPJ AGING 2022; 8:8. [PMID: 35927269 PMCID: PMC9237062 DOI: 10.1038/s41514-022-00089-8] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/26/2021] [Accepted: 05/11/2022] [Indexed: 11/09/2022]
Abstract
Skeletal muscle adapts to different exercise training modalities with age; however, the impact of both variables at the systemic and tissue levels is not fully understood. Here, adult and old C57BL/6 male mice were assigned to one of three groups: sedentary, daily high-intensity intermittent training (HIIT), or moderate intensity continuous training (MICT) for 4 weeks, compatible with the older group's exercise capacity. Improvements in body composition, fasting blood glucose, and muscle strength were mostly observed in the MICT old group, while effects of HIIT training in adult and old animals was less clear. Skeletal muscle exhibited structural and functional adaptations to exercise training, as revealed by electron microscopy, OXPHOS assays, respirometry, and muscle protein biomarkers. Transcriptomics analysis of gastrocnemius muscle combined with liver and serum metabolomics unveiled an age-dependent metabolic remodeling in response to exercise training. These results support a tailored exercise prescription approach aimed at improving health and ameliorating age-associated loss of muscle strength and function in the elderly.
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Affiliation(s)
- Michel Bernier
- Translational Gerontology Branch, National Institute on Aging, NIH, Baltimore, MD, 21224, USA
| | - Ignacio Navas Enamorado
- Translational Gerontology Branch, National Institute on Aging, NIH, Baltimore, MD, 21224, USA
- Translational Medicine Section, Akouos, Inc., 645 Summer St, Boston, MA, 02210, USA
| | - Mari Carmen Gómez-Cabrera
- Freshage Research Group, Department of Physiology, Faculty of Medicine, University of Valencia, and CIBERFES, Fundación Investigación Hospital Clínico Universitario/INCLIVA, Valencia, Spain
| | - Miguel Calvo-Rubio
- Translational Gerontology Branch, National Institute on Aging, NIH, Baltimore, MD, 21224, USA
- Departamento de Biología Celular, Fisiología e Inmunología, Campus de Excelencia Internacional Agroalimentario, ceiA3, Universidad de Córdoba, Campus de Rabanales, Edificio Severo Ochoa, 3ª planta, 14014, Córdoba, Spain
| | - Jose Antonio González-Reyes
- Departamento de Biología Celular, Fisiología e Inmunología, Campus de Excelencia Internacional Agroalimentario, ceiA3, Universidad de Córdoba, Campus de Rabanales, Edificio Severo Ochoa, 3ª planta, 14014, Córdoba, Spain
| | - Nathan L Price
- Translational Gerontology Branch, National Institute on Aging, NIH, Baltimore, MD, 21224, USA
| | | | | | - Sandra Rodríguez-López
- Departamento de Biología Celular, Fisiología e Inmunología, Campus de Excelencia Internacional Agroalimentario, ceiA3, Universidad de Córdoba, Campus de Rabanales, Edificio Severo Ochoa, 3ª planta, 14014, Córdoba, Spain
| | - Sarah J Mitchell
- Translational Gerontology Branch, National Institute on Aging, NIH, Baltimore, MD, 21224, USA
| | - Kelsey N Murt
- Translational Gerontology Branch, National Institute on Aging, NIH, Baltimore, MD, 21224, USA
| | - Krystle Kalafut
- Translational Gerontology Branch, National Institute on Aging, NIH, Baltimore, MD, 21224, USA
| | - Katrina M Williams
- Department of Orthopaedics, University of Maryland School of Medicine, Baltimore, MD, 21201, USA
| | - Christopher W Ward
- Department of Orthopaedics, University of Maryland School of Medicine, Baltimore, MD, 21201, USA
| | - Joseph P Stains
- Department of Orthopaedics, University of Maryland School of Medicine, Baltimore, MD, 21201, USA
| | - Gloria Brea-Calvo
- Centro Andaluz de Biología del Desarrollo and CIBERER, Instituto de Salud Carlos III, Universidad Pablo de Olavide - CSIC - JA, Sevilla, 41013, Spain
| | - Jose M Villalba
- Departamento de Biología Celular, Fisiología e Inmunología, Campus de Excelencia Internacional Agroalimentario, ceiA3, Universidad de Córdoba, Campus de Rabanales, Edificio Severo Ochoa, 3ª planta, 14014, Córdoba, Spain
| | - Sonia Cortassa
- Laboratory of Cardiovascular Science, National Institute on Aging, NIH, Baltimore, MD, 21224, USA
| | - Miguel A Aon
- Translational Gerontology Branch, National Institute on Aging, NIH, Baltimore, MD, 21224, USA
- Laboratory of Cardiovascular Science, National Institute on Aging, NIH, Baltimore, MD, 21224, USA
| | - Rafael de Cabo
- Translational Gerontology Branch, National Institute on Aging, NIH, Baltimore, MD, 21224, USA.
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