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Bizzarri D, Reinders MJT, Kuiper L, Beekman M, Deelen J, van Meurs JBJ, van Dongen J, Pool R, Boomsma DI, Ghanbari M, Franke L, Slagboom PE, van den Akker EB. NMR metabolomics-guided DNA methylation mortality predictors. EBioMedicine 2024; 107:105279. [PMID: 39154540 DOI: 10.1016/j.ebiom.2024.105279] [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: 03/14/2024] [Revised: 07/25/2024] [Accepted: 07/29/2024] [Indexed: 08/20/2024] Open
Abstract
BACKGROUND 1H-NMR metabolomics and DNA methylation in blood are widely known biomarkers predicting age-related physiological decline and mortality yet exert mutually independent mortality and frailty signals. METHODS Leveraging multi-omics data in four Dutch population studies (N = 5238, ∼40% of which male) we investigated whether the mortality signal captured by 1H-NMR metabolomics could guide the construction of DNA methylation-based mortality predictors. FINDINGS We trained DNA methylation-based surrogates for 64 metabolomic analytes and found that analytes marking inflammation, fluid balance, or HDL/VLDL metabolism could be accurately reconstructed using DNA-methylation assays. Interestingly, a previously reported multi-analyte score indicating mortality risk (MetaboHealth) could also be accurately reconstructed. Sixteen of our derived surrogates, including the MetaboHealth surrogate, showed significant associations with mortality, independent of relevant covariates. INTERPRETATION The addition of our metabolic analyte-derived surrogates to the well-established epigenetic clock GrimAge demonstrates that our surrogates potentially represent valuable mortality signal. FUNDING BBMRI-NL, X-omics, VOILA, Medical Delta, NWO, ERC.
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Affiliation(s)
- Daniele Bizzarri
- Molecular Epidemiology, Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, the Netherlands; Leiden Computational Biology Center, Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, the Netherlands; Delft Bioinformatics Lab, TU Delft, Delft, the Netherlands
| | - Marcel J T Reinders
- Leiden Computational Biology Center, Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, the Netherlands; Delft Bioinformatics Lab, TU Delft, Delft, the Netherlands
| | - Lieke Kuiper
- Department of Internal Medicine, Erasmus MC, Rotterdam, the Netherlands; Center for Nutrition, Prevention and Health Services, National Institute for Public Health and Environment (RIVM), Bilthoven, the Netherlands
| | - Marian Beekman
- Molecular Epidemiology, Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, the Netherlands
| | - Joris Deelen
- Molecular Epidemiology, Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, the Netherlands; Max Planck Institute for the Biology of Ageing, Cologne, Germany; Cologne Excellence Cluster on Cellular Stress Responses in Aging Associated Diseases, University of Cologne, Cologne, Germany
| | - Joyce B J van Meurs
- Department of Internal Medicine, Erasmus MC, Rotterdam, the Netherlands; Department of Orthopaedics & Sports, Erasmus Medical Center, Rotterdam, the Netherlands
| | - Jenny van Dongen
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands; Amsterdam Reproduction and Development (AR&D) Research Institute, Amsterdam, the Netherlands; Amsterdam Public Health Research Institute, Amsterdam, the Netherlands
| | - René Pool
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands; Amsterdam Public Health Research Institute, Amsterdam, the Netherlands
| | - Dorret I Boomsma
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands; Amsterdam Reproduction and Development (AR&D) Research Institute, Amsterdam, the Netherlands; Amsterdam Public Health Research Institute, Amsterdam, the Netherlands
| | - Mohsen Ghanbari
- Department of Epidemiology, Erasmus MC, Rotterdam, the Netherlands
| | - Lude Franke
- Department of Genetics, University Medical Center Groningen, Groningen, the Netherlands
| | - Pieternella E Slagboom
- Molecular Epidemiology, Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, the Netherlands; Max Planck Institute for the Biology of Ageing, Cologne, Germany
| | - Erik B van den Akker
- Molecular Epidemiology, Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, the Netherlands; Leiden Computational Biology Center, Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, the Netherlands; Delft Bioinformatics Lab, TU Delft, Delft, the Netherlands.
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2
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Gigliotti G, Joshi R, Khalid A, Widmer D, Boccellino M, Viggiano D. Epigenetics, Microbiome and Personalized Medicine: Focus on Kidney Disease. Int J Mol Sci 2024; 25:8592. [PMID: 39201279 DOI: 10.3390/ijms25168592] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2024] [Revised: 07/25/2024] [Accepted: 07/31/2024] [Indexed: 09/02/2024] Open
Abstract
Personalized medicine, which involves modifying treatment strategies/drug dosages based on massive laboratory/imaging data, faces large statistical and study design problems. The authors believe that the use of continuous multidimensional data, such as those regarding gut microbiota, or binary multidimensional systems properly transformed into a continuous variable, such as the epigenetic clock, offer an advantageous scenario for the design of trials of personalized medicine. We will discuss examples focusing on kidney diseases, specifically on IgA nephropathy. While gut dysbiosis can provide a treatment strategy to restore the standard gut microbiota using probiotics, transforming epigenetic omics data into epigenetic clocks offers a promising tool for personalized acute and chronic kidney disease care. Epigenetic clocks involve a complex transformation of DNA methylome data into estimated biological age. These clocks can identify people at high risk of developing kidney problems even before symptoms appear. Some of the effects of both the epigenetic clock and microbiota on kidney diseases seem to be mediated by endothelial dysfunction. These "big data" (epigenetic clocks and microbiota) can help tailor treatment plans by pinpointing patients likely to experience rapid declines or those who might not need overly aggressive therapies.
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Affiliation(s)
| | - Rashmi Joshi
- Department Translational Medical Sciences, University of Campania, 81100 Naples, Italy
| | - Anam Khalid
- Department Translational Medical Sciences, University of Campania, 81100 Naples, Italy
| | | | - Mariarosaria Boccellino
- Department Experimental Medicine, University of Campania, 81100 Naples, Italy
- Department Life Sciences, Health and Health Professions, Link University, 00165 Rome, Italy
| | - Davide Viggiano
- Department Translational Medical Sciences, University of Campania, 81100 Naples, Italy
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3
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Félix J, Martínez de Toda I, Díaz-Del Cerro E, González-Sánchez M, De la Fuente M. Frailty and biological age. Which best describes our aging and longevity? Mol Aspects Med 2024; 98:101291. [PMID: 38954948 DOI: 10.1016/j.mam.2024.101291] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2023] [Revised: 05/01/2024] [Accepted: 06/26/2024] [Indexed: 07/04/2024]
Abstract
Frailty and Biological Age are two closely related concepts; however, frailty is a multisystem geriatric syndrome that applies to elderly subjects, whereas biological age is a gerontologic way to describe the rate of aging of each individual, which can be used from the beginning of the aging process, in adulthood. If frailty reaches less consensus on the definition, it is a term much more widely used than this of biological age, which shows a clearer definition but is scarcely employed in social and medical fields. In this review, we suggest that this Biological Age is the best to describe how we are aging and determine our longevity, and several examples support our proposal.
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Affiliation(s)
- Judith Félix
- Department of Genetics, Physiology, and Microbiology (Unit of Animal Physiology), Faculty of Biological Sciences, Complutense University of Madrid, 28040 Madrid, Spain; Institute of Investigation Hospital 12 Octubre (imas12), 28041 Madrid, Spain.
| | - Irene Martínez de Toda
- Department of Genetics, Physiology, and Microbiology (Unit of Animal Physiology), Faculty of Biological Sciences, Complutense University of Madrid, 28040 Madrid, Spain; Institute of Investigation Hospital 12 Octubre (imas12), 28041 Madrid, Spain.
| | - Estefanía Díaz-Del Cerro
- Department of Genetics, Physiology, and Microbiology (Unit of Animal Physiology), Faculty of Biological Sciences, Complutense University of Madrid, 28040 Madrid, Spain; Institute of Investigation Hospital 12 Octubre (imas12), 28041 Madrid, Spain.
| | - Mónica González-Sánchez
- Department of Genetics, Physiology, and Microbiology (Unit of Genetics), Faculty of Biological Sciences, Complutense University of Madrid, 28040 Madrid, Spain; Institute of Investigation Hospital 12 Octubre (imas12), 28041 Madrid, Spain.
| | - Mónica De la Fuente
- Department of Genetics, Physiology, and Microbiology (Unit of Animal Physiology), Faculty of Biological Sciences, Complutense University of Madrid, 28040 Madrid, Spain; Institute of Investigation Hospital 12 Octubre (imas12), 28041 Madrid, Spain.
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4
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Lee CAA, Wu S, Chow YT, Kofman E, Williams V, Riddle M, Eide C, Ebens CL, Frank MH, Tolar J, Hook KP, AlDubayan SH, Frank NY. Accelerated Aging and Microsatellite Instability in Recessive Dystrophic Epidermolysis Bullosa-Associated Cutaneous Squamous Cell Carcinoma. J Invest Dermatol 2024; 144:1534-1543.e2. [PMID: 38272206 PMCID: PMC11267985 DOI: 10.1016/j.jid.2023.11.025] [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: 08/25/2023] [Revised: 10/22/2023] [Accepted: 11/06/2023] [Indexed: 01/27/2024]
Abstract
Recessive dystrophic epidermolysis bullosa (RDEB) is a severely debilitating disorder caused by pathogenic variants in COL7A1 and is characterized by extreme skin fragility, chronic inflammation, and fibrosis. A majority of patients with RDEB develop squamous cell carcinoma, a highly aggressive skin cancer with limited treatment options currently available. In this study, we utilized an approach leveraging whole-genome sequencing and RNA sequencing across 3 different tissues in a single patient with RDEB to gain insight into possible mechanisms of RDEB-associated squamous cell carcinoma progression and to identify potential therapeutic options. As a result, we identified PLK-1 as a possible candidate for targeted therapy and discovered microsatellite instability and accelerated aging as factors potentially contributing to the aggressive nature and early onset of RDEB squamous cell carcinoma. By integrating multitissue genomic and transcriptomic analyses in a single patient, we demonstrate the promise of bridging the gap between genomic research and clinical applications for developing tailored therapies for patients with rare genetic disorders such as RDEB.
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Affiliation(s)
- Catherine A A Lee
- Division of Genetics, Department of Medicine, Brigham & Women's Hospital, Boston, Massachusetts, USA; Harvard Medical School, Boston, Massachusetts, USA; Transplant Research Program, Division of Nephrology, Boston Children's Hospital, Boston, Massachusetts, USA
| | - Siyuan Wu
- Division of Genetics, Department of Medicine, Brigham & Women's Hospital, Boston, Massachusetts, USA; Harvard Medical School, Boston, Massachusetts, USA; Transplant Research Program, Division of Nephrology, Boston Children's Hospital, Boston, Massachusetts, USA
| | - Yuen Ting Chow
- Division of Genetics, Department of Medicine, Brigham & Women's Hospital, Boston, Massachusetts, USA
| | - Eric Kofman
- Division of Genetics, Department of Medicine, Brigham & Women's Hospital, Boston, Massachusetts, USA; Broad Institute, Cambridge, Massachusetts, USA
| | - Valencia Williams
- Division of Pediatric Blood and Marrow Transplantation & Cellular Therapy, Department of Pediatrics, University of Minnesota Twin Cities, Minneapolis, Minnesota, USA
| | - Megan Riddle
- Division of Pediatric Blood and Marrow Transplantation & Cellular Therapy, Department of Pediatrics, University of Minnesota Twin Cities, Minneapolis, Minnesota, USA
| | - Cindy Eide
- Division of Pediatric Blood and Marrow Transplantation & Cellular Therapy, Department of Pediatrics, University of Minnesota Twin Cities, Minneapolis, Minnesota, USA
| | - Christen L Ebens
- Division of Pediatric Blood and Marrow Transplantation & Cellular Therapy, Department of Pediatrics, University of Minnesota Twin Cities, Minneapolis, Minnesota, USA
| | - Markus H Frank
- Harvard Medical School, Boston, Massachusetts, USA; Transplant Research Program, Division of Nephrology, Boston Children's Hospital, Boston, Massachusetts, USA; Harvard Stem Cell Institute, Harvard University, Cambridge, Massachusetts, USA; Department of Dermatology, Brigham & Women's Hospital, Boston, Massachusetts, USA
| | - Jakub Tolar
- Division of Pediatric Blood and Marrow Transplantation & Cellular Therapy, Department of Pediatrics, University of Minnesota Twin Cities, Minneapolis, Minnesota, USA; Medical School, University of Minnesota Twin Cities, Minneapolis, Minnesota, USA; Stem Cell Institute, Medical School, University of Minnesota Twin Cities, Minneapolis, Minnesota, USA
| | - Kristen P Hook
- Department of Dermatology, Medical School, University of Minnesota Twin Cities, Minneapolis, Minnesota, USA
| | - Saud H AlDubayan
- Division of Genetics, Department of Medicine, Brigham & Women's Hospital, Boston, Massachusetts, USA; Broad Institute, Cambridge, Massachusetts, USA; Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts, USA; Department of Medicine, King Saud bin Abdulaziz University for Health Sciences, Riyadh, Saudi Arabia
| | - Natasha Y Frank
- Division of Genetics, Department of Medicine, Brigham & Women's Hospital, Boston, Massachusetts, USA; Harvard Medical School, Boston, Massachusetts, USA; Transplant Research Program, Division of Nephrology, Boston Children's Hospital, Boston, Massachusetts, USA; Department of Medicine, VA Boston Healthcare System, West Roxbury, Massachusetts, USA.
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5
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Martínez-Magaña JJ, Hurtado-Soriano J, Rivero-Segura NA, Montalvo-Ortiz JL, Garcia-delaTorre P, Becerril-Rojas K, Gomez-Verjan JC. Towards a Novel Frontier in the Use of Epigenetic Clocks in Epidemiology. Arch Med Res 2024; 55:103033. [PMID: 38955096 DOI: 10.1016/j.arcmed.2024.103033] [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: 01/10/2024] [Revised: 05/10/2024] [Accepted: 06/17/2024] [Indexed: 07/04/2024]
Abstract
Health problems associated with aging are a major public health concern for the future. Aging is a complex process with wide intervariability among individuals. Therefore, there is a need for innovative public health strategies that target factors associated with aging and the development of tools to assess the effectiveness of these strategies accurately. Novel approaches to measure biological age, such as epigenetic clocks, have become relevant. These clocks use non-sequential variable information from the genome and employ mathematical algorithms to estimate biological age based on DNA methylation levels. Therefore, in the present study, we comprehensively review the current status of the epigenetic clocks and their associations across the human phenome. We emphasize the potential utility of these tools in an epidemiological context, particularly in evaluating the impact of public health interventions focused on promoting healthy aging. Our review describes associations between epigenetic clocks and multiple traits across the life and health span. Additionally, we highlighted the evolution of studies beyond mere associations to establish causal mechanisms between epigenetic age and disease. We explored the application of epigenetic clocks to measure the efficacy of interventions focusing on rejuvenation.
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Affiliation(s)
- José Jaime Martínez-Magaña
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA; U.S. Department of Veterans Affairs National Center for Post-Traumatic Stress Disorder, Clinical Neuroscience Division, West Haven, CT, USA; VA Connecticut Healthcare System, West Haven, CT, USA
| | | | | | - Janitza L Montalvo-Ortiz
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA; U.S. Department of Veterans Affairs National Center for Post-Traumatic Stress Disorder, Clinical Neuroscience Division, West Haven, CT, USA; VA Connecticut Healthcare System, West Haven, CT, USA
| | - Paola Garcia-delaTorre
- Unidad de Investigación Epidemiológica y en Servicios de Salud, Área de Envejecimiento, Centro Médico Nacional, Siglo XXI, Instituto Mexicano del Seguro Social, Mexico City, Mexico
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6
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Koncevičius K, Nair A, Šveikauskaitė A, Šeštokaitė A, Kazlauskaitė A, Dulskas A, Petronis A. Epigenetic age oscillates during the day. Aging Cell 2024; 23:e14170. [PMID: 38638005 PMCID: PMC11258449 DOI: 10.1111/acel.14170] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2023] [Revised: 03/18/2024] [Accepted: 03/20/2024] [Indexed: 04/20/2024] Open
Abstract
Since their introduction, epigenetic clocks have been extensively used in aging, human disease, and rejuvenation studies. In this article, we report an intriguing pattern: epigenetic age predictions display a 24-h periodicity. We tested a circadian blood sample collection using 17 epigenetic clocks addressing different aspects of aging. Thirteen clocks exhibited significant oscillations with the youngest and oldest age estimates around midnight and noon, respectively. In addition, daily oscillations were consistent with the changes of epigenetic age across different times of day observed in an independant populational dataset. While these oscillations can in part be attributed to variations in white blood cell type composition, cell count correction methods might not fully resolve the issue. Furthermore, some epigenetic clocks exhibited 24-h periodicity even in the purified fraction of neutrophils pointing at plausible contributions of intracellular epigenomic oscillations. Evidence for circadian variation in epigenetic clocks emphasizes the importance of the time-of-day for obtaining accurate estimates of epigenetic age.
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Affiliation(s)
- Karolis Koncevičius
- Institute of Biotechnology, Life Sciences Center, Vilnius UniversityVilniusLithuania
| | - Akhil Nair
- Institute of Biotechnology, Life Sciences Center, Vilnius UniversityVilniusLithuania
- The Krembil Family Epigenetics Laboratory, The Campbell Family Mental Health Research Institute, Centre for Addiction and Mental HealthTorontoOntarioCanada
| | - Aušrinė Šveikauskaitė
- Institute of Biotechnology, Life Sciences Center, Vilnius UniversityVilniusLithuania
| | - Agnė Šeštokaitė
- Laboratory for Genetic DiagnosticsNational Cancer InstituteVilniusLithuania
| | - Auksė Kazlauskaitė
- Institute of Biotechnology, Life Sciences Center, Vilnius UniversityVilniusLithuania
| | - Audrius Dulskas
- Department of Abdominal and General Surgery and OncologyNational Cancer InstituteVilniusLithuania
- Faculty of MedicineVilnius UniversityVilniusLithuania
| | - Artūras Petronis
- Institute of Biotechnology, Life Sciences Center, Vilnius UniversityVilniusLithuania
- The Krembil Family Epigenetics Laboratory, The Campbell Family Mental Health Research Institute, Centre for Addiction and Mental HealthTorontoOntarioCanada
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7
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Cheng M, Conley D, Kuipers T, Li C, Ryan CP, Taeubert MJ, Wang S, Wang T, Zhou J, Schmitz LL, Tobi EW, Heijmans B, Lumey LH, Belsky DW. Accelerated biological aging six decades after prenatal famine exposure. Proc Natl Acad Sci U S A 2024; 121:e2319179121. [PMID: 38833467 PMCID: PMC11181019 DOI: 10.1073/pnas.2319179121] [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: 11/09/2023] [Accepted: 04/06/2024] [Indexed: 06/06/2024] Open
Abstract
To test the hypothesis that early-life adversity accelerates the pace of biological aging, we analyzed data from the Dutch Hunger Winter Families Study (DHWFS, N = 951). DHWFS is a natural-experiment birth-cohort study of survivors of in-utero exposure to famine conditions caused by the German occupation of the Western Netherlands in Winter 1944 to 1945, matched controls, and their siblings. We conducted DNA methylation analysis of blood samples collected when the survivors were aged 58 to quantify biological aging using the DunedinPACE, GrimAge, and PhenoAge epigenetic clocks. Famine survivors had faster DunedinPACE, as compared with controls. This effect was strongest among women. Results were similar for GrimAge, although effect-sizes were smaller. We observed no differences in PhenoAge between survivors and controls. Famine effects were not accounted for by blood-cell composition and were similar for individuals exposed early and later in gestation. Findings suggest in-utero undernutrition may accelerate biological aging in later life.
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Affiliation(s)
- Mengling Cheng
- Swiss Centre of Expertise in Life Course Research, Faculty of Social and Political Sciences, University of Lausanne, LausanneCH 1015, Switzerland
- Robert N. Butler Columbia Aging Center, Mailman School of Public Health, Columbia University, New York, NY10032
| | - Dalton Conley
- Department of Sociology, Princeton University, Mercer, NJ08544
| | - Tom Kuipers
- Department of Biomedical Data Sciences, Leiden University Medical Center, LeidenZC 2333, Netherlands
| | - Chihua Li
- Institute for Social Research, University of Michigan at Ann Arbor, Ann Arbor, MI48106
- Department of Epidemiology, Columbia University Mailman School of Public Health, New York, NY10032
| | - Calen P. Ryan
- Robert N. Butler Columbia Aging Center, Mailman School of Public Health, Columbia University, New York, NY10032
| | - M. Jazmin Taeubert
- Department of Biomedical Data Sciences, Leiden University Medical Center, LeidenZC 2333, Netherlands
| | - Shuang Wang
- Department of Biostatistics, Columbia University Mailman School of Public Health, New York, NY10032
| | - Tian Wang
- Department of Biostatistics, Columbia University Mailman School of Public Health, New York, NY10032
| | - Jiayi Zhou
- Robert N. Butler Columbia Aging Center, Mailman School of Public Health, Columbia University, New York, NY10032
| | - Lauren L. Schmitz
- Center for Demography and Ecology, Robert M. La Follette School of Public Affairs, University of Wisconsin-Madison, Madison, WI53706
| | - Elmar W. Tobi
- Department of Biomedical Data Sciences, Leiden University Medical Center, LeidenZC 2333, Netherlands
| | - Bas Heijmans
- Department of Biomedical Data Sciences, Leiden University Medical Center, LeidenZC 2333, Netherlands
| | - L. H. Lumey
- Department of Biomedical Data Sciences, Leiden University Medical Center, LeidenZC 2333, Netherlands
- Department of Epidemiology, Columbia University Mailman School of Public Health, New York, NY10032
| | - Daniel W. Belsky
- Robert N. Butler Columbia Aging Center, Mailman School of Public Health, Columbia University, New York, NY10032
- Department of Epidemiology, Columbia University Mailman School of Public Health, New York, NY10032
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Shokhirev MN, Torosin NS, Kramer DJ, Johnson AA, Cuellar TL. CheekAge: a next-generation buccal epigenetic aging clock associated with lifestyle and health. GeroScience 2024; 46:3429-3443. [PMID: 38441802 PMCID: PMC11009193 DOI: 10.1007/s11357-024-01094-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2023] [Accepted: 02/05/2024] [Indexed: 04/13/2024] Open
Abstract
Epigenetic aging clocks are computational models that predict age using DNA methylation information. Initially, first-generation clocks were developed to make predictions using CpGs that change with age. Over time, next-generation clocks were created using CpGs that relate to both age and health. Since existing next-generation clocks were constructed in blood, we sought to develop a next-generation clock optimized for prediction in cheek swabs, which are non-invasive and easy to collect. To do this, we collected MethylationEPIC data as well as lifestyle and health information from 8045 diverse adults. Using a novel simulated annealing approach that allowed us to incorporate lifestyle and health factors into training as well as a combination of CpG filtering, CpG clustering, and clock ensembling, we constructed CheekAge, an epigenetic aging clock that has a strong correlation with age, displays high test-retest reproducibility across replicates, and significantly associates with a plethora of lifestyle and health factors, such as BMI, smoking status, and alcohol intake. We validated CheekAge in an internal dataset and multiple publicly available datasets, including samples from patients with progeria or meningioma. In addition to exploring the underlying biology of the data and clock, we provide a free online tool that allows users to mine our methylomic data and predict epigenetic age.
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9
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Harinath G, Zalzala S, Nyquist A, Wouters M, Isman A, Moel M, Verdin E, Kaeberlein M, Kennedy B, Bischof E. The role of quality of life data as an endpoint for collecting real-world evidence within geroscience clinical trials. Ageing Res Rev 2024; 97:102293. [PMID: 38574864 DOI: 10.1016/j.arr.2024.102293] [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: 02/02/2024] [Revised: 03/21/2024] [Accepted: 04/01/2024] [Indexed: 04/06/2024]
Abstract
With geroscience research evolving at a fast pace, the need arises for human randomized controlled trials to assess the efficacy of geroprotective interventions to prevent age-related adverse outcomes, disease, and mortality in normative aging cohorts. However, to confirm efficacy requires a long-term and costly approach as time to the event of morbidity and mortality can be decades. While this could be circumvented using sensitive biomarkers of aging, current molecular, physiological, and digital endpoints require further validation. In this review, we discuss how collecting real-world evidence (RWE) by obtaining health data that is amenable for collection from large heterogeneous populations in a real-world setting can help speed up validation of geroprotective interventions. Further, we propose inclusion of quality of life (QoL) data as a biomarker of aging and candidate endpoint for geroscience clinical trials to aid in distinguishing healthy from unhealthy aging. We highlight how QoL assays can aid in accelerating data collection in studies gathering RWE on the geroprotective effects of repurposed drugs to support utilization within healthy longevity medicine. Finally, we summarize key metrics to consider when implementing QoL assays in studies, and present the short-form 36 (SF-36) as the most well-suited candidate endpoint.
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Affiliation(s)
| | | | | | | | | | | | - Eric Verdin
- Buck Institute for Research on Aging, Novato, CA, USA
| | | | - Brian Kennedy
- Healthy Longevity Translational Research Programme, Yong Loo Lin School of Medicine, National University of Singapore, Singapore; Centre for Healthy Longevity, National University Health System, Singapore
| | - Evelyne Bischof
- Department of Medical Oncology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China; Shanghai University of Medicine and Health Sciences, Shanghai, China; Sheba Longevity Center, Sheba Medical Center, Tel Aviv, Israel.
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10
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Xu Z, Niu L, Kresovich JK, Taylor JA. methscore: a comprehensive R function for DNA methylation-based health predictors. Bioinformatics 2024; 40:btae302. [PMID: 38702768 PMCID: PMC11105949 DOI: 10.1093/bioinformatics/btae302] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2023] [Revised: 04/10/2024] [Accepted: 05/01/2024] [Indexed: 05/06/2024] Open
Abstract
MOTIVATION DNA methylation-based predictors of various biological metrics have been widely published and are becoming valuable tools in epidemiologic studies of epigenetics and personalized medicine. However, generating these predictors from original source software and web servers is complex and time consuming. Furthermore, different predictors were often derived based on data from different types of arrays, where array differences and batch effects can make predictors difficult to compare across studies. RESULTS We integrate these published methods into a single R function to produce 158 previously published predictors for chronological age, biological age, exposures, lifestyle traits and serum protein levels using both classical and principal component-based methods. To mitigate batch and array differences, we also provide a modified RCP method (ref-RCP) that normalize input DNA methylation data to reference data prior to estimation. Evaluations in real datasets show that this approach improves estimate precision and comparability across studies. AVAILABILITY AND IMPLEMENTATION The function was included in software package ENmix, and is freely available from Bioconductor website (https://www.bioconductor.org/packages/release/bioc/html/ENmix.html).
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Affiliation(s)
- Zongli Xu
- Biostatistics & Computational Biology Branch, National Institute of Environmental Health Sciences, Research Triangle Park, NC, 27709, United States
| | - Liang Niu
- Division of Biostatistics and Bioinformatics, Department of Environmental and Public Health Sciences, College of Medicine, University of Cincinnati, Cincinnati, OH, 45267, United States
| | - Jacob K Kresovich
- Departments of Cancer Epidemiology & Breast Oncology, H. Lee Moffitt Cancer Center & Research Institute, Tampa, FL, 33612, United States
| | - Jack A Taylor
- Epidemiology Branch, National Institute of Environmental Health Sciences, Research Triangle Park, NC, 27709, United States
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11
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Bell CG. Epigenomic insights into common human disease pathology. Cell Mol Life Sci 2024; 81:178. [PMID: 38602535 PMCID: PMC11008083 DOI: 10.1007/s00018-024-05206-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2024] [Revised: 03/11/2024] [Accepted: 03/13/2024] [Indexed: 04/12/2024]
Abstract
The epigenome-the chemical modifications and chromatin-related packaging of the genome-enables the same genetic template to be activated or repressed in different cellular settings. This multi-layered mechanism facilitates cell-type specific function by setting the local sequence and 3D interactive activity level. Gene transcription is further modulated through the interplay with transcription factors and co-regulators. The human body requires this epigenomic apparatus to be precisely installed throughout development and then adequately maintained during the lifespan. The causal role of the epigenome in human pathology, beyond imprinting disorders and specific tumour suppressor genes, was further brought into the spotlight by large-scale sequencing projects identifying that mutations in epigenomic machinery genes could be critical drivers in both cancer and developmental disorders. Abrogation of this cellular mechanism is providing new molecular insights into pathogenesis. However, deciphering the full breadth and implications of these epigenomic changes remains challenging. Knowledge is accruing regarding disease mechanisms and clinical biomarkers, through pathogenically relevant and surrogate tissue analyses, respectively. Advances include consortia generated cell-type specific reference epigenomes, high-throughput DNA methylome association studies, as well as insights into ageing-related diseases from biological 'clocks' constructed by machine learning algorithms. Also, 3rd-generation sequencing is beginning to disentangle the complexity of genetic and DNA modification haplotypes. Cell-free DNA methylation as a cancer biomarker has clear clinical utility and further potential to assess organ damage across many disorders. Finally, molecular understanding of disease aetiology brings with it the opportunity for exact therapeutic alteration of the epigenome through CRISPR-activation or inhibition.
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Affiliation(s)
- Christopher G Bell
- William Harvey Research Institute, Barts & The London Faculty of Medicine, Queen Mary University of London, Charterhouse Square, London, EC1M 6BQ, UK.
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12
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Whitman ET, Ryan CP, Abraham WC, Addae A, Corcoran DL, Elliott ML, Hogan S, Ireland D, Keenan R, Knodt AR, Melzer TR, Poulton R, Ramrakha S, Sugden K, Williams BS, Zhou J, Hariri AR, Belsky DW, Moffitt TE, Caspi A. A blood biomarker of the pace of aging is associated with brain structure: replication across three cohorts. Neurobiol Aging 2024; 136:23-33. [PMID: 38301452 PMCID: PMC11017787 DOI: 10.1016/j.neurobiolaging.2024.01.008] [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: 09/06/2023] [Revised: 01/16/2024] [Accepted: 01/19/2024] [Indexed: 02/03/2024]
Abstract
Biological aging is the correlated decline of multi-organ system integrity central to the etiology of many age-related diseases. A novel epigenetic measure of biological aging, DunedinPACE, is associated with cognitive dysfunction, incident dementia, and mortality. Here, we tested for associations between DunedinPACE and structural MRI phenotypes in three datasets spanning midlife to advanced age: the Dunedin Study (age=45 years), the Framingham Heart Study Offspring Cohort (mean age=63 years), and the Alzheimer's Disease Neuroimaging Initiative (mean age=75 years). We also tested four additional epigenetic measures of aging: the Horvath clock, the Hannum clock, PhenoAge, and GrimAge. Across all datasets (total N observations=3380; total N individuals=2322), faster DunedinPACE was associated with lower total brain volume, lower hippocampal volume, greater burden of white matter microlesions, and thinner cortex. Across all measures, DunedinPACE and GrimAge had the strongest and most consistent associations with brain phenotypes. Our findings suggest that single timepoint measures of multi-organ decline such as DunedinPACE could be useful for gauging nervous system health.
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Affiliation(s)
- Ethan T Whitman
- Department of Psychology and Neuroscience, Duke University, Durham, NC, USA.
| | - Calen P Ryan
- Butler Columbia Aging Center, Columbia University Mailman School of Public Health, New York, USA
| | | | - Angela Addae
- Department of Psychology and Neuroscience, Duke University, Durham, NC, USA
| | - David L Corcoran
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Maxwell L Elliott
- Department of Psychology, Center for Brain Science, Harvard University, Cambridge, MA, USA
| | - Sean Hogan
- Dunedin Multidisciplinary Health and Development Research Unit, Department of Psychology, University of Otago, Dunedin, New Zealand
| | - David Ireland
- Dunedin Multidisciplinary Health and Development Research Unit, Department of Psychology, University of Otago, Dunedin, New Zealand
| | - Ross Keenan
- Brain Research New Zealand-Rangahau Roro Aotearoa, Centre of Research Excellence, Universities of Auckland and Otago, New Zealand; Christchurch Radiology Group, Christchurch, New Zealand
| | - Annchen R Knodt
- Department of Psychology and Neuroscience, Duke University, Durham, NC, USA
| | - Tracy R Melzer
- Brain Research New Zealand-Rangahau Roro Aotearoa, Centre of Research Excellence, Universities of Auckland and Otago, New Zealand; Department of Medicine, University of Otago, Christchurch, New Zealand
| | - Richie Poulton
- Dunedin Multidisciplinary Health and Development Research Unit, Department of Psychology, University of Otago, Dunedin, New Zealand
| | - Sandhya Ramrakha
- Dunedin Multidisciplinary Health and Development Research Unit, Department of Psychology, University of Otago, Dunedin, New Zealand
| | - Karen Sugden
- Department of Psychology and Neuroscience, Duke University, Durham, NC, USA
| | | | - Jiayi Zhou
- Butler Columbia Aging Center, Columbia University Mailman School of Public Health, New York, USA
| | - Ahmad R Hariri
- Department of Psychology and Neuroscience, Duke University, Durham, NC, USA
| | - Daniel W Belsky
- Butler Columbia Aging Center, Columbia University Mailman School of Public Health, New York, USA; Department of Epidemiology, Columbia University Mailman School of Public Health, New York, USA
| | - Terrie E Moffitt
- Department of Psychology and Neuroscience, Duke University, Durham, NC, USA; Center for Genomic and Computational Biology, Duke University, Durham, NC, USA; King's College London, Social, Genetic, and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology, & Neuroscience, London, UK; PROMENTA, Department of Psychology, University of Oslo, Norway; Department of Psychiatry and Behavioral Sciences, Duke University, Durham, NC, USA
| | - Avshalom Caspi
- Department of Psychology and Neuroscience, Duke University, Durham, NC, USA; Center for Genomic and Computational Biology, Duke University, Durham, NC, USA; King's College London, Social, Genetic, and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology, & Neuroscience, London, UK; PROMENTA, Department of Psychology, University of Oslo, Norway; Department of Psychiatry and Behavioral Sciences, Duke University, Durham, NC, USA
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13
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Aroke EN, Srinivasasainagendra V, Kottae P, Quinn TL, Wiggins AM, Hobson J, Kinnie K, Stoudmire T, Tiwari HK, Goodin BR. The Pace of Biological Aging Predicts Nonspecific Chronic Low Back Pain Severity. THE JOURNAL OF PAIN 2024; 25:974-983. [PMID: 37907115 PMCID: PMC10960701 DOI: 10.1016/j.jpain.2023.10.018] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/24/2023] [Revised: 10/15/2023] [Accepted: 10/21/2023] [Indexed: 11/02/2023]
Abstract
This study aimed to determine if and how the pace of biological aging was associated with nonspecific chronic low back pain (cLBP) and compare what measure of epigenetic age acceleration most strongly predicts cLBP outcomes. We used the Dunedin Pace of Aging from the Epigenome (DunedinPACE), Horvath's, Hannum's, and PhenoAge clocks to determine the pace of biological aging in 69 cLBP, and 49 pain-free controls (PFCs) adults, ages 18 to 85 years. On average, participants with cLBP had higher DunedinPACE (P < .001) but lower Horvath (P = .04) and Hannum (P = .02) accelerated epigenetic age than PFCs. There was no significant difference in PhenoAge acceleration between the cLBP and PFC groups (P = .97). DunedinPACE had the largest effect size (Cohen's d = .78) on group differences. In univariate regressions, a unit increase in DunedinPACE score was associated with 265.98 times higher odds of cLBP than the PFC group (P < .001). After controlling for sex, race, and body mass index (BMI), the odds ratio of cLBP to PFC group was 149.62 (P < .001). Furthermore, among participants with cLBP, DunedinPACE scores positively correlated with pain severity (rs = .385, P = .001) and interference (rs = .338, P = .005). Epigenetic age acceleration from Horvath, Hannum, and PhenoAge clocks were not significant predictors of cLBP. The odds of a faster pace of biological aging are higher among adults with cLBP, and this was associated with greater pain severity and disability. Future interventions to slow the pace of biological aging may improve cLBP outcomes. PERSPECTIVE: Accelerated epigenetic aging is common among adults with nonspecific cLBP. Higher DunedinPACE scores positively correlate with pain severity and interference, and better predict cLBP than other DNA methylation clocks. Interventions to slow the pace of biological aging may be viable targets for improving pain outcomes.
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Affiliation(s)
- Edwin N. Aroke
- School of Nursing, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Vinodh Srinivasasainagendra
- Department of Biostatistics, School of Public Health, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Pooja Kottae
- Department of Computer Science, College of Arts and Sciences, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Tammie L. Quinn
- Department of Psychology, College of Arts and Sciences, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Asia M. Wiggins
- Department of Psychology, College of Arts and Sciences, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Joanna Hobson
- Department of Psychology, College of Arts and Sciences, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Kiari Kinnie
- School of Nursing, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Tonya Stoudmire
- School of Nursing, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Hemant K. Tiwari
- Department of Biostatistics, School of Public Health, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Burel R. Goodin
- Department of Anesthesiology, School of Medicine, Washington University, St Louis, USA
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14
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Ungvari Z, Tabák AG, Adany R, Purebl G, Kaposvári C, Fazekas-Pongor V, Csípő T, Szarvas Z, Horváth K, Mukli P, Balog P, Bodizs R, Ujma P, Stauder A, Belsky DW, Kovács I, Yabluchanskiy A, Maier AB, Moizs M, Östlin P, Yon Y, Varga P, Vokó Z, Papp M, Takács I, Vásárhelyi B, Torzsa P, Ferdinandy P, Csiszar A, Benyó Z, Szabó AJ, Dörnyei G, Kivimäki M, Kellermayer M, Merkely B. The Semmelweis Study: a longitudinal occupational cohort study within the framework of the Semmelweis Caring University Model Program for supporting healthy aging. GeroScience 2024; 46:191-218. [PMID: 38060158 PMCID: PMC10828351 DOI: 10.1007/s11357-023-01018-7] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2023] [Accepted: 11/11/2023] [Indexed: 12/08/2023] Open
Abstract
The Semmelweis Study is a prospective occupational cohort study that seeks to enroll all employees of Semmelweis University (Budapest, Hungary) aged 25 years and older, with a population of 8866 people, 70.5% of whom are women. The study builds on the successful experiences of the Whitehall II study and aims to investigate the complex relationships between lifestyle, environmental, and occupational risk factors, and the development and progression of chronic age-associated diseases. An important goal of the Semmelweis Study is to identify groups of people who are aging unsuccessfully and therefore have an increased risk of developing age-associated diseases. To achieve this, the study takes a multidisciplinary approach, collecting economic, social, psychological, cognitive, health, and biological data. The Semmelweis Study comprises a baseline data collection with open healthcare data linkage, followed by repeated data collection waves every 5 years. Data are collected through computer-assisted self-completed questionnaires, followed by a physical health examination, physiological measurements, and the assessment of biomarkers. This article provides a comprehensive overview of the Semmelweis Study, including its origin, context, objectives, design, relevance, and expected contributions.
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Affiliation(s)
- Zoltan Ungvari
- International Training Program in Geroscience/Healthy Aging Program, Doctoral School of Basic and Translational Medicine/Department of Public Health, Semmelweis University, Budapest, Hungary.
- Vascular Cognitive Impairment, Neurodegeneration and Healthy Brain Aging Program, Department of Neurosurgery, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA.
- Department of Health Promotion Sciences, The Hudson College of Public Health, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA.
| | - Adam G Tabák
- International Training Program in Geroscience/Healthy Aging Program, Doctoral School of Basic and Translational Medicine/Department of Public Health, Semmelweis University, Budapest, Hungary
- Department of Public Health, Faculty of Medicine, Semmelweis University, Budapest, Hungary
- UCL Brain Sciences, University College London, London, UK
- Department of Internal Medicine and Oncology, Semmelweis University, Faculty of Medicine, Budapest, Hungary
| | - Roza Adany
- International Training Program in Geroscience/Healthy Aging Program, Doctoral School of Basic and Translational Medicine/Department of Public Health, Semmelweis University, Budapest, Hungary
- Department of Public Health, Faculty of Medicine, Semmelweis University, Budapest, Hungary
- HUN-REN-UD Public Health Research Group, Department of Public Health and Epidemiology, Faculty of Medicine, University of Debrecen, Debrecen, Hungary
| | - György Purebl
- Institute of Behavioral Sciences, Faculty of Medicine, Semmelweis University, Budapest, Hungary
| | - Csilla Kaposvári
- Department of Public Health, Faculty of Medicine, Semmelweis University, Budapest, Hungary
| | - Vince Fazekas-Pongor
- Department of Public Health, Faculty of Medicine, Semmelweis University, Budapest, Hungary
| | - Tamás Csípő
- International Training Program in Geroscience/Healthy Aging Program, Doctoral School of Basic and Translational Medicine/Department of Public Health, Semmelweis University, Budapest, Hungary
- Department of Public Health, Faculty of Medicine, Semmelweis University, Budapest, Hungary
| | - Zsófia Szarvas
- International Training Program in Geroscience/Healthy Aging Program, Doctoral School of Basic and Translational Medicine/Department of Public Health, Semmelweis University, Budapest, Hungary
- Vascular Cognitive Impairment, Neurodegeneration and Healthy Brain Aging Program, Department of Neurosurgery, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
- Department of Health Promotion Sciences, The Hudson College of Public Health, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
- Department of Public Health, Faculty of Medicine, Semmelweis University, Budapest, Hungary
| | - Krisztián Horváth
- Department of Public Health, Faculty of Medicine, Semmelweis University, Budapest, Hungary
| | - Peter Mukli
- International Training Program in Geroscience/Healthy Aging Program, Doctoral School of Basic and Translational Medicine/Department of Public Health, Semmelweis University, Budapest, Hungary
- Vascular Cognitive Impairment, Neurodegeneration and Healthy Brain Aging Program, Department of Neurosurgery, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
- Department of Public Health, Faculty of Medicine, Semmelweis University, Budapest, Hungary
| | - Piroska Balog
- Institute of Behavioral Sciences, Faculty of Medicine, Semmelweis University, Budapest, Hungary
| | - Robert Bodizs
- Institute of Behavioral Sciences, Faculty of Medicine, Semmelweis University, Budapest, Hungary
| | - Peter Ujma
- Institute of Behavioral Sciences, Faculty of Medicine, Semmelweis University, Budapest, Hungary
| | - Adrienne Stauder
- Institute of Behavioral Sciences, Faculty of Medicine, Semmelweis University, Budapest, Hungary
| | - Daniel W Belsky
- Robert N. Butler Columbia Aging Center, Columbia University, New York, NY, USA
- Department of Epidemiology, Columbia University Mailman School of Public Health, New York, NY, USA
| | - Illés Kovács
- Department of Ophthalmology, Faculty of Medicine, Semmelweis University, Budapest, Hungary
- Department of Ophthalmology, Weill Cornell Medical College, New York City, NY, USA
- Department of Clinical Ophthalmology, Faculty of Health Sciences, Semmelweis University, Budapest, Hungary
| | - Andriy Yabluchanskiy
- Vascular Cognitive Impairment, Neurodegeneration and Healthy Brain Aging Program, Department of Neurosurgery, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
- Department of Health Promotion Sciences, The Hudson College of Public Health, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
| | - Andrea B Maier
- Healthy Longevity Translational Research Program, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
- Centre for Healthy Longevity, National University Health System, Singapore, Singapore
- Department of Human Movement Sciences, @AgeAmsterdam, Vrije Universiteit, Amsterdam Movement Sciences, Amsterdam, The Netherlands
| | - Mariann Moizs
- Department of Public Health, Faculty of Medicine, Semmelweis University, Budapest, Hungary
- Ministry of Interior of Hungary, Budapest, Hungary
| | | | - Yongjie Yon
- WHO Regional Office for Europe, Copenhagen, Denmark
| | - Péter Varga
- Department of Public Health, Faculty of Medicine, Semmelweis University, Budapest, Hungary
- Clinical Center, Semmelweis University, Budapest, Hungary
| | - Zoltán Vokó
- Center for Health Technology Assessment, Semmelweis University, Budapest, Hungary
| | - Magor Papp
- Department of Public Health, Faculty of Medicine, Semmelweis University, Budapest, Hungary
| | - István Takács
- UCL Brain Sciences, University College London, London, UK
| | - Barna Vásárhelyi
- Department of Laboratory Medicine, Faculty of Medicine, Semmelweis University, Budapest, Hungary
| | - Péter Torzsa
- Department of Family Medicine, Faculty of Medicine, Semmelweis University, Budapest, Hungary
| | - Péter Ferdinandy
- Department of Pharmacology and Pharmacotherapy, Faculty of Medicine, Semmelweis University, Budapest, Hungary
| | - Anna Csiszar
- Vascular Cognitive Impairment, Neurodegeneration and Healthy Brain Aging Program, Department of Neurosurgery, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
- Department of Health Promotion Sciences, The Hudson College of Public Health, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
| | - Zoltán Benyó
- Department of Translational Medicine, Faculty of Medicine, Semmelweis University, Budapest, Hungary
- HUN-REN-SU Cerebrovascular and Neurocognitive Diseases Research Group, Budapest, Hungary
| | - Attila J Szabó
- First Department of Pediatrics, Faculty of Medicine, Semmelweis University, Budapest, Hungary
- HUN-REN-SU Pediatrics and Nephrology Research Group, Semmelweis University, Budapest, Hungary
| | - Gabriella Dörnyei
- Department of Morphology and Physiology, Faculty of Health Sciences, Semmelweis University, Budapest, Hungary
| | - Mika Kivimäki
- UCL Brain Sciences, University College London, London, UK
| | - Miklos Kellermayer
- Department of Biophysics and Radiation Biology, Faculty of Medicine, Semmelweis University, Budapest, Hungary
| | - Bela Merkely
- Heart and Vascular Center, Semmelweis University, Budapest, Hungary
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15
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Moqri M, Herzog C, Poganik JR, Ying K, Justice JN, Belsky DW, Higgins-Chen AT, Chen BH, Cohen AA, Fuellen G, Hägg S, Marioni RE, Widschwendter M, Fortney K, Fedichev PO, Zhavoronkov A, Barzilai N, Lasky-Su J, Kiel DP, Kennedy BK, Cummings S, Slagboom PE, Verdin E, Maier AB, Sebastiano V, Snyder MP, Gladyshev VN, Horvath S, Ferrucci L. Validation of biomarkers of aging. Nat Med 2024; 30:360-372. [PMID: 38355974 PMCID: PMC11090477 DOI: 10.1038/s41591-023-02784-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2023] [Accepted: 12/19/2023] [Indexed: 02/16/2024]
Abstract
The search for biomarkers that quantify biological aging (particularly 'omic'-based biomarkers) has intensified in recent years. Such biomarkers could predict aging-related outcomes and could serve as surrogate endpoints for the evaluation of interventions promoting healthy aging and longevity. However, no consensus exists on how biomarkers of aging should be validated before their translation to the clinic. Here, we review current efforts to evaluate the predictive validity of omic biomarkers of aging in population studies, discuss challenges in comparability and generalizability and provide recommendations to facilitate future validation of biomarkers of aging. Finally, we discuss how systematic validation can accelerate clinical translation of biomarkers of aging and their use in gerotherapeutic clinical trials.
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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
| | - Kejun Ying
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- T.H. Chan School of Public Health, Harvard University, Boston, MA, USA
| | - Jamie N 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
| | | | - Brian H Chen
- Herbert Wertheim School of Public Health and Human Longevity Science, University of California San Diego, San Diego, CA, USA
| | - Alan A Cohen
- Department of Environmental Health Sciences, Butler Columbia Aging Center, Mailman School of Public Health, Columbia University, New York, NY, USA
| | - 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
| | - Sara Hägg
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Riccardo E Marioni
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
| | - 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
| | | | | | | | - Nir Barzilai
- Institute for Aging Research, Albert Einstein College of Medicine, Bronx, NY, USA
| | - Jessica Lasky-Su
- Department of Network Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Douglas P Kiel
- Musculoskeletal Research Center, Hinda and Arthur Marcus Institute for Aging Research and Department of Medicine, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA, USA
| | - Brian K Kennedy
- Healthy Longevity Translational Research Programme, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
- 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
| | - 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
| | - P Eline Slagboom
- Section of Molecular Epidemiology, Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, the Netherlands
| | - Eric Verdin
- Buck Institute for Research on Aging, Novato, CA, USA
| | - Andrea B Maier
- 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
- Department of Human Movement Sciences, @AgeAmsterdam, Amsterdam Movement Sciences, Faculty of Behavioural and Movement Sciences, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
| | - Vittorio Sebastiano
- Department of Obstetrics and Gynecology, School of Medicine, Stanford University, Stanford, CA, USA
| | - Michael P Snyder
- Department of Genetics, 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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16
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Lozupone M, Solfrizzi V, Sardone R, Dibello V, Castellana F, Zupo R, Lampignano L, Bortone I, Daniele A, Panza F. The epigenetics of frailty. Epigenomics 2024; 16:189-202. [PMID: 38112012 DOI: 10.2217/epi-2023-0279] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2023] Open
Abstract
The conceptual change of frailty, from a physical to a biopsychosocial phenotype, expanded the field of frailty, including social and behavioral domains with critical interaction between different frailty models. Environmental exposures - including physical exercise, psychosocial factors and diet - may play a role in the frailty pathophysiology. Complex underlying mechanisms involve the progressive interactions of genetics with epigenetics and of multimorbidity with environmental factors. Here we review the literature on possible mechanisms explaining the association between epigenetic hallmarks (i.e., global DNA methylation, DNA methylation age acceleration and microRNAs) and frailty, considered as biomarkers of aging. Frailty could be considered the result of environmental epigenetic factors on biological aging, caused by conflicting DNA methylation age and chronological age.
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Affiliation(s)
- Madia Lozupone
- Department of Translational Biomedicine & Neuroscience 'DiBraiN', University of Bari Aldo Moro, Bari, Italy
| | - Vincenzo Solfrizzi
- Cesare Frugoni Internal & Geriatric Medicine & Memory Unit, University of Bari Aldo Moro, Bari, Italy
| | | | - Vittorio Dibello
- Cesare Frugoni Internal & Geriatric Medicine & Memory Unit, University of Bari Aldo Moro, Bari, Italy
- Department of Orofacial Pain & Dysfunction, Academic Centre for Dentistry Amsterdam (ACTA), University of Amsterdam & Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Fabio Castellana
- Cesare Frugoni Internal & Geriatric Medicine & Memory Unit, University of Bari Aldo Moro, Bari, Italy
| | - Roberta Zupo
- Cesare Frugoni Internal & Geriatric Medicine & Memory Unit, University of Bari Aldo Moro, Bari, Italy
| | | | - Ilaria Bortone
- Department of Translational Biomedicine & Neuroscience 'DiBraiN', University of Bari Aldo Moro, Bari, Italy
| | - Antonio Daniele
- Department of Neuroscience, Catholic University of Sacred Heart, Rome, Italy
- Neurology Unit, IRCCS Fondazione Policlinico Universitario A. Gemelli, Rome, Italy
| | - Francesco Panza
- Cesare Frugoni Internal & Geriatric Medicine & Memory Unit, University of Bari Aldo Moro, Bari, Italy
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17
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Lau CHE, Manou M, Markozannes G, Ala-Korpela M, Ben-Shlomo Y, Chaturvedi N, Engmann J, Gentry-Maharaj A, Herzig KH, Hingorani A, Järvelin MR, Kähönen M, Kivimäki M, Lehtimäki T, Marttila S, Menon U, Munroe PB, Palaniswamy S, Providencia R, Raitakari O, Schmidt F, Sebert S, Wong A, Vineis P, Tzoulaki I, Robinson O. NMR metabolomic modelling of age and lifespan: a multi-cohort analysis. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.11.07.23298200. [PMID: 37986811 PMCID: PMC10659522 DOI: 10.1101/2023.11.07.23298200] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/22/2023]
Abstract
Metabolomic age models have been proposed for the study of biological aging, however they have not been widely validated. We aimed to assess the performance of newly developed and existing nuclear magnetic resonance spectroscopy (NMR) metabolomic age models for prediction of chronological age (CA), mortality, and age-related disease. 98 metabolic variables were measured in blood from nine UK and Finnish cohort studies (N ≈ 31,000 individuals, age range 24-86 years). We used non-linear and penalised regression to model CA and time to all-cause mortality. We examined associations of four new and two previously published metabolomic age models, with ageing risk factors and phenotypes. Within the UK Biobank (N≈ 102,000), we tested prediction of CA, incident disease (cardiovascular disease (CVD), type-2 diabetes mellitus, cancer, dementia, chronic obstructive pulmonary disease) and all-cause mortality. Cross-validated Pearson's r between metabolomic age models and CA ranged between 0.47-0.65 in the training set (mean absolute error: 8-9 years). Metabolomic age models, adjusted for CA, were associated with C-reactive protein, and inversely associated with glomerular filtration rate. Positively associated risk factors included obesity, diabetes, smoking, and physical inactivity. In UK Biobank, correlations of metabolomic age with chronological age were modest (r = 0.29-0.33), yet all metabolomic model scores predicted mortality (hazard ratios of 1.01 to 1.06 / metabolomic age year) and CVD, after adjustment for CA. While metabolomic age models were only moderately associated with CA in an independent population, they provided additional prediction of morbidity and mortality over CA itself, suggesting their wider applicability.
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Affiliation(s)
- Chung-Ho E. Lau
- MRC Centre for Environment and Health, Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
| | - Maria Manou
- Department of Hygiene and Epidemiology, University of Ioannina Medical School, Ioannina, Greece
| | - Georgios Markozannes
- MRC Centre for Environment and Health, Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
- Department of Hygiene and Epidemiology, University of Ioannina Medical School, Ioannina, Greece
| | - Mika Ala-Korpela
- Systems Epidemiology, Faculty of Medicine, University of Oulu, Oulu, Finland
- Research Unit of Population Health, Faculty of Medicine, University of Oulu, Oulu, Finland
- Biocenter Oulu, University of Oulu, Oulu, Finland
- NMR Metabolomics Laboratory, School of Pharmacy, Faculty of Health Sciences, University of Eastern Finland, Kuopio, Finland
| | - Yoav Ben-Shlomo
- Population Health Sciences, University of Bristol, Bristol, UK
| | - Nish Chaturvedi
- MRC Unit for Lifelong Health and Ageing at UCL, University College London, UK
| | - Jorgen Engmann
- UCL Institute of Cardiovascular Science, Population Science and Experimental Medicine, Centre for Translational Genomics
| | - Aleksandra Gentry-Maharaj
- MRC Clinical Trials Unit, Institute of Clinical Trials and Methodology, UCL, London, UK
- Department of Women’s Cancer, Elizabeth Garrett Anderson Institute for Women’s Health, UCL, London, UK
| | - Karl-Heinz Herzig
- Institute of Biomedicine and Internal Medicine, Medical Research Center Oulu, Oulu University Hospital, Faculty of Medicine, Oulu University; Finland
- Department of Pediatric Gastroenterology and Metabolic Diseases, Poznan University of Medical Sciences, Poland
| | - Aroon Hingorani
- UCL Institute of Cardiovascular Science, Population Science and Experimental Medicine, Centre for Translational Genomics
| | - Marjo-Riitta Järvelin
- MRC Centre for Environment and Health, Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
- Research Unit of Population Health, Faculty of Medicine, University of Oulu, Oulu, Finland
- Department of Life Sciences, College of Health and Life Sciences, Brunel University London, London, UK
| | - Mika Kähönen
- Department of Clinical Physiology, Tampere University Hospital, Finland
- Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - Mika Kivimäki
- Brain Sciences, University College London, London, UK
| | - Terho Lehtimäki
- Faculty of Medicine and Health Technology and Finnish Cardiovascular Research Center Tampere, Tampere University, Tampere, Finland
- Department of Clinical Chemistry Fimlab Laboratories, Tampere, Finland
| | - Saara Marttila
- Molecular Epidemiology, Faculty of Medicine and Health Technology, Tampere University, Finland
- Gerontology Research Center (GEREC), Tampere University, Finland
| | - Usha Menon
- MRC Clinical Trials Unit, Institute of Clinical Trials and Methodology, UCL, London, UK
| | - Patricia B. Munroe
- William Harvey Research Institute, Barts and the London Faculty of Medicine and Dentistry, Queen Mary University of London, UK
- National Institute of Health and Care Research, Barts Cardiovascular Biomedical Research Centre, Queen Mary University of London, UK
| | - Saranya Palaniswamy
- Research Unit of Population Health, Faculty of Medicine, University of Oulu, Oulu, Finland
| | - Rui Providencia
- Institute of Health Informatics Research, University College London, London, UK
- Barts Heart Centre, Barts Health NHS Trust, London, UK
| | - Olli Raitakari
- Centre for Population Health Research, University of Turku and Turku University Hospital, Turku, Finland
- Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland
- Department of Clinical Physiology and Nuclear Medicine, Turku University Hospital, Turku, Finland
| | - Floriaan Schmidt
- Institute of Cardiovascular Science, Faculty of Population Health Sciences, University College London, London, UK
- Department of Cardiology, Amsterdam Cardiovascular Science, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, The Netherlands
- UCL BHF Research Accelerator Centre, London, UK
| | - Sylvain Sebert
- Research Unit of Population Health, Faculty of Medicine, University of Oulu, Oulu, Finland
| | - Andrew Wong
- MRC Unit for Lifelong Health and Ageing at UCL, University College London, UK
| | - Paolo Vineis
- MRC Centre for Environment and Health, Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
| | - Ioanna Tzoulaki
- MRC Centre for Environment and Health, Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
| | - Oliver Robinson
- MRC Centre for Environment and Health, Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
- Ageing Epidemiology (AGE) Research Unit, School of Public Health, Imperial College London, London, UK
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18
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Cheng M, Conley D, Kuipers T, Li C, Ryan C, Taubert J, Wang S, Wang T, Zhou J, Schmitz LL, Tobi EW, Heijmans B, Lumey L, Belsky DW. Accelerated biological aging six decades after prenatal famine exposure. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.11.03.23298046. [PMID: 37961696 PMCID: PMC10635274 DOI: 10.1101/2023.11.03.23298046] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/15/2023]
Abstract
To test the hypothesis that early-life adversity accelerates the pace of biological aging, we analyzed data from the Dutch Hunger Winter Families Study (DHWFS, N=951). DHWFS is a natural-experiment birth-cohort study of survivors of in-utero exposure to famine conditions caused by the German occupation of the Western Netherlands in Winter 1944-5, matched controls, and their siblings. We conducted DNA methylation analysis of blood samples collected when the survivors were aged 58 to quantify biological aging using the DunedinPACE, GrimAge, and PhenoAge epigenetic clocks. Famine survivors had faster DunedinPACE, as compared with controls. This effect was strongest among women. Results were similar for GrimAge, although effect-sizes were smaller. We observed no differences in PhenoAge between survivors and controls. Famine effects were not accounted for by blood-cell composition and were similar for individuals exposed early and later in gestation. Findings suggest in-utero undernutrition may accelerate biological aging in later life.
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Affiliation(s)
- Mengling Cheng
- Swiss Centre of Expertise in Life Course Research, University of Lausanne, Lausanne, Switzerland
- Robert N. Butler Columbia Aging Center, Columbia University, New York, NY, USA
| | - Dalton Conley
- Department of Sociology, Princeton University, Princeton, NJ, USA
| | - Tom Kuipers
- Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, Netherlands
| | - Chihua Li
- Institute for Social Research, University of Michigan at Ann Arbor, Ann Arbor, MI, USA
- Department of Epidemiology, Columbia University Mailman School of Public Health, New York, NY, USA
| | - Calen Ryan
- Robert N. Butler Columbia Aging Center, Columbia University, New York, NY, USA
| | - Jazmin Taubert
- Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, Netherlands
| | - Shuang Wang
- Department of Biostatistics, Columbia University Mailman School of Public Health, New York, NY, USA
| | - Tian Wang
- Department of Biostatistics, Columbia University Mailman School of Public Health, New York, NY, USA
| | - Jiayi Zhou
- Robert N. Butler Columbia Aging Center, Columbia University, New York, NY, USA
| | - Lauren L. Schmitz
- Robert M. La Follette School of Public Affairs, University of Wisconsin-Madison, Madison, WI, USA
| | - Elmar W. Tobi
- Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, Netherlands
| | - Bas Heijmans
- Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, Netherlands
| | - L.H. Lumey
- Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, Netherlands
- Department of Epidemiology, Columbia University Mailman School of Public Health, New York, NY, USA
| | - Daniel W. Belsky
- Robert N. Butler Columbia Aging Center, Columbia University, New York, NY, USA
- Department of Epidemiology, Columbia University Mailman School of Public Health, New York, NY, USA
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19
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Hubens WHG, Maié T, Schnitker M, Bocova L, Puri D, Wessiepe M, Kramer J, Rink L, Koschmieder S, Costa IG, Wagner W. Targeted DNA Methylation Analysis Facilitates Leukocyte Counts in Dried Blood Samples. Clin Chem 2023; 69:1283-1294. [PMID: 37708296 DOI: 10.1093/clinchem/hvad143] [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: 05/31/2023] [Accepted: 08/10/2023] [Indexed: 09/16/2023]
Abstract
BACKGROUND Cell-type specific DNA methylation (DNAm) can be employed to determine the numbers of leukocyte subsets in blood. In contrast to conventional methods for leukocyte counts, which are based on cellular morphology or surface marker protein expression, the cellular deconvolution based on DNAm levels is applicable for frozen or dried blood. Here, we further enhanced targeted DNAm assays for leukocyte counts in clinical application. METHODS DNAm profiles of 40 different studies were compiled to identify CG dinucleotides (CpGs) with cell-type specific DNAm using a computational framework, CimpleG. DNAm levels at these CpGs were then measured with digital droplet PCR in venous blood from 160 healthy donors and 150 patients with various hematological disorders. Deconvolution was further validated with venous blood (n = 75) and capillary blood (n = 31) that was dried on Whatman paper or on Mitra microsampling devices. RESULTS In venous blood, automated cell counting or flow cytometry correlated well with epigenetic estimates of relative leukocyte counts for granulocytes (r = 0.95), lymphocytes (r = 0.97), monocytes (r = 0.82), CD4 T cells (r = 0.84), CD8 T cells (r = 0.94), B cells (r = 0.96), and NK cells (r = 0.72). Similar correlations and precisions were achieved for dried blood samples. Spike-in with a reference plasmid enabled accurate epigenetic estimation of absolute leukocyte counts from dried blood samples, correlating with conventional venous (r = 0.86) and capillary (r = 0.80) blood measurements. CONCLUSIONS The advanced selection of cell-type specific CpGs and utilization of digital droplet PCR analysis provided accurate epigenetic blood counts. Analysis of dried blood facilitates self-sampling with a finger prick, thereby enabling easier accessibility to testing.
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Affiliation(s)
- Wouter H G Hubens
- Institute for Stem Cell Biology, Faculty of Medicine, RWTH Aachen University, Aachen, Germany
- Helmholtz-Institute for Biomedical Engineering, RWTH Aachen University, Aachen, Germany
| | - Tiago Maié
- Institute for Computational Genomics, Faculty of Medicine, RWTH Aachen University, Aachen, Germany
| | - Matthis Schnitker
- Institute for Stem Cell Biology, Faculty of Medicine, RWTH Aachen University, Aachen, Germany
- Helmholtz-Institute for Biomedical Engineering, RWTH Aachen University, Aachen, Germany
| | - Ledio Bocova
- Institute for Stem Cell Biology, Faculty of Medicine, RWTH Aachen University, Aachen, Germany
- Helmholtz-Institute for Biomedical Engineering, RWTH Aachen University, Aachen, Germany
| | - Deepika Puri
- Institute for Stem Cell Biology, Faculty of Medicine, RWTH Aachen University, Aachen, Germany
- Helmholtz-Institute for Biomedical Engineering, RWTH Aachen University, Aachen, Germany
| | - Martina Wessiepe
- Institute for Transfusion Medicine, Faculty of Medicine, RWTH Aachen University, Aachen, Germany
| | - Jan Kramer
- Division of Nephrology and Transplantation Unit, Department of Internal Medicine I, University of Lübeck, Lübeck, Germany
- LADR Laboratory Group Dr. Kramer & Colleagues, Geesthacht, Germany
| | - Lothar Rink
- Institute of Immunology, Faculty of Medicine, RWTH Aachen University, Aachen, Germany
| | - Steffen Koschmieder
- Department of Hematology, Oncology, Hemostaseology and Stem Cell Transplantation, Faculty of Medicine, RWTH Aachen University, Aachen, Germany
- Center for Integrated Oncology Aachen Bonn Cologne Düsseldorf (CIO ABCD), Aachen, Germany
| | - Ivan G Costa
- Institute for Computational Genomics, Faculty of Medicine, RWTH Aachen University, Aachen, Germany
| | - Wolfgang Wagner
- Institute for Stem Cell Biology, Faculty of Medicine, RWTH Aachen University, Aachen, Germany
- Helmholtz-Institute for Biomedical Engineering, RWTH Aachen University, Aachen, Germany
- Center for Integrated Oncology Aachen Bonn Cologne Düsseldorf (CIO ABCD), Aachen, Germany
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20
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Gaare JJ, Brügger K, Nido GS, Tzoulis C. DNA Methylation Age Acceleration Is Not Associated with Age of Onset in Parkinson's Disease. Mov Disord 2023; 38:2064-2071. [PMID: 37551021 DOI: 10.1002/mds.29574] [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: 04/20/2023] [Revised: 07/04/2023] [Accepted: 07/24/2023] [Indexed: 08/09/2023] Open
Abstract
BACKGROUND Epigenetic clocks using DNA methylation (DNAm) to estimate biological age have become popular tools in the study of neurodegenerative diseases. Notably, several recent reports have shown a strikingly similar inverse relationship between accelerated biological aging, as measured by DNAm, and the age of onset of several neurodegenerative disorders, including Parkinson's disease (PD). Common to all of these studies is that they were performed without control subjects and using the exact same measure of accelerated aging: DNAm age minus chronological age. OBJECTIVE We aimed to assess the validity of these findings in PD, using the same dataset as in the original study, blood DNAm data from the Parkinson's Progression Markers Initiative cohort, but also including control samples in the analyses. METHODS We replicated the analyses and findings of the previous study and then reanalyzed the dataset incorporating control samples to account for underlying age-related biases. RESULTS Our reanalysis shows that there is no correlation between age of onset and DNAm age acceleration. Conversely, there is a pattern of overestimating DNAm age in younger and underestimating DNAm age in older individuals in the dataset that entirely explains the previously reported association. CONCLUSIONS Our findings refute the previously reported inverse relationship between DNAm age acceleration and age of onset in PD. We show that these findings are fully accounted for by an expected over/underestimation of DNAm age in younger/older individuals. Furthermore, this effect is likely to be responsible for nearly identical findings reported in other neurodegenerative diseases. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.
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Affiliation(s)
- Johannes J Gaare
- Neuro-SysMed Center, Department of Neurology, Haukeland University Hospital, Bergen, Norway
- K.G. Jebsen Center for Translational Research in Parkinson's Disease, University of Bergen, Bergen, Norway
- Department of Clinical Medicine, University of Bergen, Bergen, Norway
| | - Kim Brügger
- Neuro-SysMed Center, Department of Neurology, Haukeland University Hospital, Bergen, Norway
- Department of Clinical Medicine, University of Bergen, Bergen, Norway
| | - Gonzalo S Nido
- Neuro-SysMed Center, Department of Neurology, Haukeland University Hospital, Bergen, Norway
- K.G. Jebsen Center for Translational Research in Parkinson's Disease, University of Bergen, Bergen, Norway
- Department of Clinical Medicine, University of Bergen, Bergen, Norway
| | - Charalampos Tzoulis
- Neuro-SysMed Center, Department of Neurology, Haukeland University Hospital, Bergen, Norway
- K.G. Jebsen Center for Translational Research in Parkinson's Disease, University of Bergen, Bergen, Norway
- Department of Clinical Medicine, University of Bergen, Bergen, Norway
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21
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Demongeot J, Magal P. Population dynamics model for aging. MATHEMATICAL BIOSCIENCES AND ENGINEERING : MBE 2023; 20:19636-19660. [PMID: 38052618 DOI: 10.3934/mbe.2023870] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/07/2023]
Abstract
The chronological age used in demography describes the linear evolution of the life of a living being. The chronological age cannot give precise information about the exact developmental stage or aging processes an organism has reached. On the contrary, the biological age (or epigenetic age) represents the true evolution of the tissues and organs of the living being. Biological age is not always linear and sometimes proceeds by discontinuous jumps. These jumps can be negative (we then speak of rejuvenation) or positive (in the event of premature aging), and they can be dependent on endogenous events such as pregnancy (negative jump) or stroke (positive jump) or exogenous ones such as surgical treatment (negative jump) or infectious disease (positive jump). The article proposes a mathematical model of the biological age by defining a valid model for the two types of jumps (positive and negative). The existence and uniqueness of the solution are solved, and its temporal dynamic is analyzed using a moments equation. We also provide some individual-based stochastic simulations.
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Affiliation(s)
| | - Pierre Magal
- University of Bordeaux, IMB, UMR 5251, F-33400 Talence, France. CNRS, IMB, UMR 5251, F-33400 Talence, France
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22
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Whitman ET, Ryan CP, Abraham WC, Addae A, Corcoran DL, Elliott ML, Hogan S, Ireland D, Keenan R, Knodt AR, Melzer TR, Poulton R, Ramrakha S, Sugden K, Williams BS, Zhou J, Hariri AR, Belsky DW, Moffitt TE, Caspi A. A blood biomarker of accelerated aging in the body associates with worse structural integrity in the brain: replication across three cohorts. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.09.06.23295140. [PMID: 37732266 PMCID: PMC10508789 DOI: 10.1101/2023.09.06.23295140] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/22/2023]
Abstract
Biological aging is the correlated decline of multi-organ system integrity central to the etiology of many age-related diseases. A novel epigenetic measure of biological aging, DunedinPACE, is associated with cognitive dysfunction, incident dementia, and mortality. Here, we tested for associations between DunedinPACE and structural MRI phenotypes in three datasets spanning midlife to advanced age: the Dunedin Study (age=45 years), the Framingham Heart Study Offspring Cohort (mean age=63 years), and the Alzheimer's Disease Neuroimaging Initiative (mean age=75 years). We also tested four additional epigenetic measures of aging: the Horvath clock, the Hannum clock, PhenoAge, and GrimAge. Across all datasets (total N observations=3,380; total N individuals=2,322), faster DunedinPACE was associated with lower total brain volume, lower hippocampal volume, and thinner cortex. In two datasets, faster DunedinPACE was associated with greater burden of white matter hyperintensities. Across all measures, DunedinPACE and GrimAge had the strongest and most consistent associations with brain phenotypes. Our findings suggest that single timepoint measures of multi-organ decline such as DunedinPACE could be useful for gauging nervous system health.
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Affiliation(s)
- Ethan T Whitman
- Department of Psychology and Neuroscience, Duke University, Durham, NC, USA
| | - Calen P Ryan
- Butler Columbia Aging Center, Columbia University Mailman School of Public Health, New York, USA
| | | | - Angela Addae
- Department of Psychology and Neuroscience, Duke University, Durham, NC, USA
| | - David L Corcoran
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Maxwell L Elliott
- Department of Psychology, Center for Brain Science, Harvard University, Cambridge, MA, USA
| | - Sean Hogan
- Dunedin Multidisciplinary Health and Development Research Unit, Department of Psychology, University of Otago, Dunedin, New Zealand
| | - David Ireland
- Dunedin Multidisciplinary Health and Development Research Unit, Department of Psychology, University of Otago, Dunedin, New Zealand
| | - Ross Keenan
- Brain Research New Zealand-Rangahau Roro Aotearoa, Centre of Research Excellence, Universities of Auckland and Otago, New Zealand
- Christchurch Radiology Group, Christchurch, New Zealand
| | - Annchen R Knodt
- Department of Psychology and Neuroscience, Duke University, Durham, NC, USA
| | - Tracy R Melzer
- Brain Research New Zealand-Rangahau Roro Aotearoa, Centre of Research Excellence, Universities of Auckland and Otago, New Zealand
- Department of Medicine, University of Otago, Christchurch, New Zealand
| | - Richie Poulton
- Dunedin Multidisciplinary Health and Development Research Unit, Department of Psychology, University of Otago, Dunedin, New Zealand
| | - Sandhya Ramrakha
- Dunedin Multidisciplinary Health and Development Research Unit, Department of Psychology, University of Otago, Dunedin, New Zealand
| | - Karen Sugden
- Department of Psychology and Neuroscience, Duke University, Durham, NC, USA
| | | | - Jiayi Zhou
- Butler Columbia Aging Center, Columbia University Mailman School of Public Health, New York, USA
| | - Ahmad R Hariri
- Department of Psychology and Neuroscience, Duke University, Durham, NC, USA
| | - Daniel W Belsky
- Butler Columbia Aging Center, Columbia University Mailman School of Public Health, New York, USA
- Department of Epidemiology, Columbia University Mailman School of Public Health, New York, USA
| | - Terrie E Moffitt
- Department of Psychology and Neuroscience, Duke University, Durham, NC, USA
- Center for Genomic and Computational Biology, Duke University, Durham, NC, USA
- King's College London, Social, Genetic, and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology, & Neuroscience, London, UK
- PROMENTA, Department of Psychology, University of Oslo, Norway
- Department of Psychiatry and Behavioral Sciences, Duke University, Durham, NC, USA
| | - Avshalom Caspi
- Department of Psychology and Neuroscience, Duke University, Durham, NC, USA
- Center for Genomic and Computational Biology, Duke University, Durham, NC, USA
- King's College London, Social, Genetic, and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology, & Neuroscience, London, UK
- PROMENTA, Department of Psychology, University of Oslo, Norway
- Department of Psychiatry and Behavioral Sciences, Duke University, Durham, NC, USA
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23
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Pośpiech E, Pisarek A, Rudnicka J, Noroozi R, Boroń M, Masny A, Wysocka B, Migacz-Gruszka K, Lisman D, Pruszkowska-Przybylska P, Kobus M, Szargut M, Dowejko J, Stanisz K, Zacharczuk J, Zieliński P, Sitek A, Ossowski A, Spólnicka M, Branicki W. Introduction of a multiplex amplicon sequencing assay to quantify DNA methylation in target cytosine markers underlying four selected epigenetic clocks. Clin Epigenetics 2023; 15:128. [PMID: 37563670 PMCID: PMC10416531 DOI: 10.1186/s13148-023-01545-2] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2023] [Accepted: 08/02/2023] [Indexed: 08/12/2023] Open
Abstract
BACKGROUND DNA methylation analysis has proven to be a powerful tool for age assessment. However, the implementation of epigenetic age prediction in diagnostics or routine forensic casework requires appropriate laboratory methods. In this study, we aimed to compare the performance of large-scale DNA methylation analysis protocols that show promise in terms of accuracy, throughput, multiplexing capacity, and high sensitivity. RESULTS The protocols were designed to target a predefined panel of 161 genomic CG/CA sites from four known estimators of epigenetic age-related parameters, optimized and validated using artificially methylated controls or blood samples. We successfully targeted 96% of these loci using two enrichment protocols: Ion AmpliSeq™, an amplicon-based method integrated with Ion Torrent S5, and SureSelectXT Methyl-Seq, a hybridization-based method followed by MiSeq FGx sequencing. Both protocols demonstrated high accuracy and robustness. Although hybridization assays have greater multiplexing capabilities, the best overall performance was observed for the amplicon-based protocol with the lowest variability in DNA methylation at 25 ng of starting DNA, mean observed marker coverage of ~ 6.7 k reads, and accuracy of methylation quantification with a mean absolute difference between observed and expected methylation beta value of 0.054. The Ion AmpliSeq method correlated strongly with genome-scale EPIC microarray data (R = 0.91) and showed superiority in terms of methylation measurement accuracy. Method-to-method bias was accounted for by the use of linear transformation, which provided a highly accurate prediction of calendar age with a mean absolute error of less than 5 years for the VISAGE and Hannum age clocks used. The pace of aging (PoAm) and the mortality risk score (MRS) estimators included in our panel represent next-generation clocks, were found to have low to moderate correlations with the VISAGE and Hannum models (R < 0.75), and thus may capture different aspects of epigenetic aging. CONCLUSIONS We propose a laboratory tool that allows the quantification of DNA methylation in cytosines underlying four different clocks, thus providing broad information on epigenetic aging while maintaining a reasonable number of CpG markers, opening the way to a wide range of applications in forensics, medicine, and healthcare.
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Affiliation(s)
- Ewelina Pośpiech
- Malopolska Centre of Biotechnology, Jagiellonian University, Krakow, Poland.
- Department of Forensic Genetics, Pomeranian Medical University in Szczecin, Szczecin, Poland.
| | - Aleksandra Pisarek
- Institute of Zoology and Biomedical Research, Faculty of Biology, Jagiellonian University, Krakow, Poland
| | - Joanna Rudnicka
- Malopolska Centre of Biotechnology, Jagiellonian University, Krakow, Poland
- Doctoral School of Exact and Natural Sciences, Jagiellonian University, Krakow, Poland
| | - Rezvan Noroozi
- Malopolska Centre of Biotechnology, Jagiellonian University, Krakow, Poland
- Doctoral School of Exact and Natural Sciences, Jagiellonian University, Krakow, Poland
| | - Michał Boroń
- Central Forensic Laboratory of the Police, Warsaw, Poland
| | | | - Bożena Wysocka
- Central Forensic Laboratory of the Police, Warsaw, Poland
| | - Kamila Migacz-Gruszka
- Department of Dermatology, Collegium Medicum of the Jagiellonian University, Krakow, Poland
| | - Dagmara Lisman
- Department of Forensic Genetics, Pomeranian Medical University in Szczecin, Szczecin, Poland
| | | | - Magdalena Kobus
- Institute of Biological Sciences, Faculty of Biology and Environmental Sciences, Cardinal Stefan Wyszynski University in Warsaw, Warsaw, Poland
| | - Maria Szargut
- Department of Forensic Genetics, Pomeranian Medical University in Szczecin, Szczecin, Poland
| | - Joanna Dowejko
- Department of Forensic Genetics, Pomeranian Medical University in Szczecin, Szczecin, Poland
| | - Kamila Stanisz
- Department of Forensic Genetics, Pomeranian Medical University in Szczecin, Szczecin, Poland
| | - Julia Zacharczuk
- Department of Forensic Genetics, Pomeranian Medical University in Szczecin, Szczecin, Poland
| | - Piotr Zieliński
- Institute of Environmental Sciences, Faculty of Biology, Jagiellonian University, Krakow, Poland
| | - Aneta Sitek
- Department of Anthropology, Faculty of Biology and Environmental Protection, University of Łódź, Łódź, Poland
| | - Andrzej Ossowski
- Department of Forensic Genetics, Pomeranian Medical University in Szczecin, Szczecin, Poland
| | | | - Wojciech Branicki
- Institute of Zoology and Biomedical Research, Faculty of Biology, Jagiellonian University, Krakow, Poland
- Institute of Forensic Research, Krakow, Poland
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24
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Bapteste E, Huneman P, Keller L, Teulière J, Lopez P, Teeling EC, Lindner AB, Baudisch A, Ludington WB, Franceschi C. Expanding evolutionary theories of ageing to better account for symbioses and interactions throughout the Web of Life. Ageing Res Rev 2023; 89:101982. [PMID: 37321383 PMCID: PMC10771319 DOI: 10.1016/j.arr.2023.101982] [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: 04/14/2023] [Revised: 05/26/2023] [Accepted: 06/11/2023] [Indexed: 06/17/2023]
Abstract
How, when, and why organisms age are fascinating issues that can only be fully addressed by adopting an evolutionary perspective. Consistently, the main evolutionary theories of ageing, namely the Mutation Accumulation theory, the Antagonistic Pleiotropy theory, and the Disposable Soma theory, have formulated stimulating hypotheses that structure current debates on both the proximal and ultimate causes of organismal ageing. However, all these theories leave a common area of biology relatively under-explored. The Mutation Accumulation theory and the Antagonistic Pleiotropy theory were developed under the traditional framework of population genetics, and therefore are logically centred on the ageing of individuals within a population. The Disposable Soma theory, based on principles of optimising physiology, mainly explains ageing within a species. Consequently, current leading evolutionary theories of ageing do not explicitly model the countless interspecific and ecological interactions, such as symbioses and host-microbiomes associations, increasingly recognized to shape organismal evolution across the Web of Life. Moreover, the development of network modelling supporting a deeper understanding on the molecular interactions associated with ageing within and between organisms is also bringing forward new questions regarding how and why molecular pathways associated with ageing evolved. Here, we take an evolutionary perspective to examine the effects of organismal interactions on ageing across different levels of biological organisation, and consider the impact of surrounding and nested systems on organismal ageing. We also apply this perspective to suggest open issues with potential to expand the standard evolutionary theories of ageing.
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Affiliation(s)
- Eric Bapteste
- Institut de Systématique, Evolution, Biodiversité (ISYEB), Sorbonne Université, CNRS, Museum National d'Histoire Naturelle, EPHE, Université des Antilles, Paris, France.
| | - Philippe Huneman
- Institut d'Histoire et de Philosophie des Sciences et des Techniques (CNRS/ Université Paris I Sorbonne), Paris, France
| | - Laurent Keller
- Department of Ecology and Evolution, University of Lausanne, 1015 Lausanne, Switzerland
| | - Jérôme Teulière
- Institut de Systématique, Evolution, Biodiversité (ISYEB), Sorbonne Université, CNRS, Museum National d'Histoire Naturelle, EPHE, Université des Antilles, Paris, France
| | - Philippe Lopez
- Institut de Systématique, Evolution, Biodiversité (ISYEB), Sorbonne Université, CNRS, Museum National d'Histoire Naturelle, EPHE, Université des Antilles, Paris, France
| | - Emma C Teeling
- School of Biology and Environmental Science, University College Dublin, Ireland
| | - Ariel B Lindner
- Université de Paris, INSERM U1284, Center for Research and Interdisciplinarity (CRI), Paris, France
| | - Annette Baudisch
- Interdisciplinary Centre on Population Dynamics, University of Southern Denmark, 5230 Odense M, Denmark
| | - William B Ludington
- Department of Embryology, Carnegie Institution for Science, Baltimore, MD 21218, USA; Department of Biology, Johns Hopkins University, Baltimore, MD 21218, USA
| | - Claudio Franceschi
- Department of Medical and Surgical Sciences, Alma Mater Studiorum University of Bologna, 40138 Bologna, Italy; Department of Applied Mathematics and Laboratory of Systems Medicine of Aging, Lobachevsky University, Nizhny Novgorod 603950, Russia
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25
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Gaylord A, Cohen A, Kupsco A. Biomarkers of aging through the life course: A Recent Literature Update. CURRENT OPINION IN EPIDEMIOLOGY AND PUBLIC HEALTH 2023; 2:7-17. [PMID: 38130910 PMCID: PMC10732539 DOI: 10.1097/pxh.0000000000000018] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/23/2023]
Abstract
Purpose of review The development of biomarkers of aging has greatly advanced epidemiological studies of aging processes. However, much debate remains on the timing of aging onset and the causal relevance of these biomarkers. In this review, we discuss the most recent biomarkers of aging that have been applied across the life course. Recent findings The most recently developed aging biomarkers that have been applied across the life course can be designated into three categories: epigenetic clocks, epigenetic markers of chronic inflammation, and mitochondrial DNA copy number. While these have been applied at different life stages, the development, validation, and application of these markers has been largely centered on populations of older adults. Few studies have examined trajectories of aging biomarkers across the life course. As the wealth of molecular and biochemical data increases, emerging biomarkers may be able to capture complex and system-specific aging processes. Recently developed biomarkers include novel epigenetic clocks; clocks based on ribosomal DNA, transcriptomic profiles, proteomics, metabolomics, and inflammatory markers; clonal hematopoiesis of indeterminate potential gene mutations; and multi-omics approaches. Summary Attention should be placed on aging at early and middle life stages to better understand trajectories of aging biomarkers across the life course. Additionally, novel biomarkers will provide greater insight into aging processes. The specific mechanisms of aging reflected by these biomarkers should be considered when interpreting results.
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Affiliation(s)
- Abigail Gaylord
- Department of Environmental Health Sciences, Mailman School of Public Health, Columbia University, New York, NY, United States
| | - Alan Cohen
- Department of Environmental Health Sciences, Mailman School of Public Health, Columbia University, New York, NY, United States
- PRIMUS Research Group, Department of Family Medicine, University of Sherbrooke, Sherbrooke, Quebec, Canada
- Research Center on Aging and Research Center of Centre Hospitalier Universitaire de Sherbrooke, Sherbrooke, Quebec, Canada
- Butler Columbia Aging Center, Mailman School of Public Health, Columbia University, New York, NY, United States
| | - Allison Kupsco
- Department of Environmental Health Sciences, Mailman School of Public Health, Columbia University, New York, NY, United States
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26
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Giuliani ME, Barbi V, Bigossi G, Marcozzi S, Giacconi R, Cardelli M, Piacenza F, Orlando F, Ciaglia E, Cattaneo M, Mongelli A, Gaetano C, Provinciali M, Puca AA, Malavolta M. Effects of Human LAV-BPIFB4 Gene Therapy on the Epigenetic Clock and Health of Aged Mice. Int J Mol Sci 2023; 24:ijms24076464. [PMID: 37047437 PMCID: PMC10095240 DOI: 10.3390/ijms24076464] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2023] [Revised: 03/21/2023] [Accepted: 03/28/2023] [Indexed: 04/14/2023] Open
Abstract
The homozygous genotype of the Longevity-Associated Variant (LAV) in Bactericidal/Permeability-Increasing Fold-Containing Family B member 4 (BPIFB4) is enriched in long-living individuals of three independent populations and its genetic transfer in C57BL/6J mice showed a delay in frailty progression and improvement of several biomarkers of aging and multiple aspects of health. The C57BL/6J strain is a suitable model for studying therapies aimed at extending healthy aging and longevity due to its relatively short lifespan and the availability of aging biomarkers. Epigenetic clocks based on DNA methylation profiles are reliable molecular biomarkers of aging, while frailty measurement tools are used to evaluate overall health during aging. In this study, we show that the systemic gene transfer of LAV-BPIFB4 in aged C57BL/6J mice was associated with a significant reduction in the epigenetic clock-based biological age, as measured by a three CpG clock method. Furthermore, LAV-BPIFB4 gene transfer resulted in an improvement of the Vitality Score with a reduction in the Frailty Index. These findings further support the use of LAV-BPIFB4 gene therapy to induce beneficial effects on epigenetic mechanisms associated with aging and frailty in aged mice, with potential implications for future therapies to prevent frailty in humans.
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Affiliation(s)
| | - Veronica Barbi
- Laboratory of Epigenetics, Istituti Clinici Scientifici Maugeri IRCCS, Via Maugeri 10, 27100 Pavia, Italy
| | - Giorgia Bigossi
- Advanced Technology Center for Aging Research, IRCCS INRCA, 60121 Ancona, Italy
| | - Serena Marcozzi
- Advanced Technology Center for Aging Research, IRCCS INRCA, 60121 Ancona, Italy
| | - Robertina Giacconi
- Advanced Technology Center for Aging Research, IRCCS INRCA, 60121 Ancona, Italy
| | - Maurizio Cardelli
- Advanced Technology Center for Aging Research, IRCCS INRCA, 60121 Ancona, Italy
| | - Francesco Piacenza
- Advanced Technology Center for Aging Research, IRCCS INRCA, 60121 Ancona, Italy
| | - Fiorenza Orlando
- Experimental Animal Models for Aging Unit, Scientific Technological Area, IRCCS INRCA, 60015 Falconara Marittima, Italy
| | - Elena Ciaglia
- Department of Medicine, Surgery and Dentistry "Scuola Medica Salernitana", University of Salerno, Via Salvatore Allende, 84081 Baronissi, Italy
| | - Monica Cattaneo
- Cardiovascular Research Unit, IRCCS MultiMedica, 20138 Milan, Italy
| | - Alessia Mongelli
- Laboratory of Epigenetics, Istituti Clinici Scientifici Maugeri IRCCS, Via Maugeri 10, 27100 Pavia, Italy
| | - Carlo Gaetano
- Laboratory of Epigenetics, Istituti Clinici Scientifici Maugeri IRCCS, Via Maugeri 10, 27100 Pavia, Italy
| | - Mauro Provinciali
- Advanced Technology Center for Aging Research, IRCCS INRCA, 60121 Ancona, Italy
| | - Annibale Alessandro Puca
- Department of Medicine, Surgery and Dentistry "Scuola Medica Salernitana", University of Salerno, Via Salvatore Allende, 84081 Baronissi, Italy
- Cardiovascular Research Unit, IRCCS MultiMedica, 20138 Milan, Italy
| | - Marco Malavolta
- Advanced Technology Center for Aging Research, IRCCS INRCA, 60121 Ancona, Italy
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