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Zillich L, Cetin M, Hummel EM, Poisel E, Fries GR, Frank J, Streit F, Foo JC, Sirignano L, Friske MM, Lenz B, Hoffmann S, Adorjan K, Kiefer F, Bakalkin G, Hansson AC, Lohoff FW, Kärkkäinen O, Kok E, Karhunen PJ, Sutherland GT, Walss-Bass C, Spanagel R, Rietschel M, Moser DA, Witt SH. Biological aging markers in blood and brain tissue indicate age acceleration in alcohol use disorder. ALCOHOL, CLINICAL & EXPERIMENTAL RESEARCH 2024; 48:250-259. [PMID: 38276909 PMCID: PMC10922212 DOI: 10.1111/acer.15241] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/29/2023] [Revised: 11/30/2023] [Accepted: 12/05/2023] [Indexed: 01/27/2024]
Abstract
BACKGROUND Alcohol use disorder (AUD) is associated with increased mortality and morbidity risk. A reason for this could be accelerated biological aging, which is strongly influenced by disease processes such as inflammation. As recent studies of AUD show changes in DNA methylation and gene expression in neuroinflammation-related pathways in the brain, biological aging represents a potentially important construct for understanding the adverse effects of substance use disorders. Epigenetic clocks have shown accelerated aging in blood samples from individuals with AUD. However, no systematic evaluation of biological age measures in AUD across different tissues and brain regions has been undertaken. METHODS As markers of biological aging (BioAge markers), we assessed Levine's and Horvath's epigenetic clocks, DNA methylation telomere length (DNAmTL), telomere length (TL), and mitochondrial DNA copy number (mtDNAcn) in postmortem brain samples from Brodmann Area 9 (BA9), caudate nucleus, and ventral striatum (N = 63-94), and in whole blood samples (N = 179) of individuals with and without AUD. To evaluate the association between AUD status and BioAge markers, we performed linear regression analyses while adjusting for covariates. RESULTS The majority of BioAge markers were significantly associated with chronological age in all samples. Levine's epigenetic clock and DNAmTL were indicative of accelerated biological aging in AUD in BA9 and whole blood samples, while Horvath's showed the opposite effect in BA9. No significant association of AUD with TL and mtDNAcn was detected. Measured TL and DNAmTL showed only small correlations in blood and none in brain. CONCLUSIONS The present study is the first to simultaneously investigate epigenetic clocks, telomere length, and mtDNAcn in postmortem brain and whole blood samples in individuals with AUD. We found evidence for accelerated biological aging in AUD in blood and brain, as measured by Levine's epigenetic clock, and DNAmTL. Additional studies of different tissues from the same individuals are needed to draw valid conclusions about the congruence of biological aging in blood and brain.
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Affiliation(s)
- Lea Zillich
- Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
- Section on Clinical Genomics and Experimental Therapeutics, National Institute on Alcohol Abuse and Alcoholism, National Institutes of Health, Bethesda, Maryland, USA
| | - Metin Cetin
- Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Elisabeth M. Hummel
- Department of Genetic Psychology, Faculty of Psychology, Ruhr Universität Bochum, Bochum, Germany
| | - Eric Poisel
- Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Gabriel R. Fries
- Louis A. Faillace Department of Psychiatry and Behavioral Sciences, McGovern Medical School, University of Texas Health Science Center at Houston, Houston, Texas, USA
| | - Josef Frank
- Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Fabian Streit
- Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Jerome C. Foo
- Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Lea Sirignano
- Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Marion M. Friske
- Institute of Psychopharmacology, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Bernd Lenz
- Department of Addictive Behavior and Addiction Medicine, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Sabine Hoffmann
- Department of Addictive Behavior and Addiction Medicine, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Kristina Adorjan
- Department of Psychiatry and Psychotherapy, University Hospital, Ludwig Maximilian University of Munich, Munich, Germany
- Institute of Psychiatric Phenomics and Genomics, University Hospital, Ludwig Maximilian University of Munich, Munich, Germany
| | - Falk Kiefer
- Department of Addictive Behavior and Addiction Medicine, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Georgy Bakalkin
- Department of Pharmaceutical Biosciences, Uppsala University, Uppsala, Sweden
| | - Anita C. Hansson
- Institute of Psychopharmacology, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Falk W. Lohoff
- Section on Clinical Genomics and Experimental Therapeutics, National Institute on Alcohol Abuse and Alcoholism, National Institutes of Health, Bethesda, Maryland, USA
| | - Olli Kärkkäinen
- School of Pharmacy, University of Eastern Finland, Kuopio, Finland
| | - Eloise Kok
- Department of Pathology, University of Helsinki, Helsinki, Finland and HUS Diagnostic Center, Helsinki University Hospital, Helsinki, Finland
- Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - Pekka J. Karhunen
- Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
- Fimlab Laboratories Ltd., Pirkanmaa Hospital District, and Finnish Cardiovascular Research Centre Tampere, Tampere, Finland
| | - Greg T Sutherland
- Charles Perkins Centre and School of Medical Sciences, Faculty of Medicine and Health, The University of Sydney, Sydney, Australia
| | - Consuelo Walss-Bass
- Louis A. Faillace Department of Psychiatry and Behavioral Sciences, McGovern Medical School, University of Texas Health Science Center at Houston, Houston, Texas, USA
| | - Rainer Spanagel
- Institute of Psychopharmacology, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Marcella Rietschel
- Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Dirk A. Moser
- Department of Genetic Psychology, Faculty of Psychology, Ruhr Universität Bochum, Bochum, Germany
| | - Stephanie H. Witt
- Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
- Center for Innovative Psychiatric and Psychotherapeutic Research, Biobank, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
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Horvath S, Singh K, Raj K, Khairnar SI, Sanghavi A, Shrivastava A, Zoller JA, Li CZ, Herenu CB, Canatelli-Mallat M, Lehmann M, Habazin S, Novokmet M, Vučković F, Solberg Woods LC, Martinez AG, Wang T, Chiavellini P, Levine AJ, Chen H, Brooke RT, Gordevicius J, Lauc G, Goya RG, Katcher HL. Reversal of biological age in multiple rat organs by young porcine plasma fraction. GeroScience 2024; 46:367-394. [PMID: 37875652 PMCID: PMC10828479 DOI: 10.1007/s11357-023-00980-6] [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: 08/07/2023] [Accepted: 10/09/2023] [Indexed: 10/26/2023] Open
Abstract
Young blood plasma is known to confer beneficial effects on various organs in mice and rats. However, it was not known whether plasma from young adult pigs rejuvenates old rat tissues at the epigenetic level; whether it alters the epigenetic clock, which is a highly accurate molecular biomarker of aging. To address this question, we developed and validated six different epigenetic clocks for rat tissues that are based on DNA methylation values derived from n = 613 tissue samples. As indicated by their respective names, the rat pan-tissue clock can be applied to DNA methylation profiles from all rat tissues, while the rat brain, liver, and blood clocks apply to the corresponding tissue types. We also developed two epigenetic clocks that apply to both human and rat tissues by adding n = 1366 human tissue samples to the training data. We employed these six rat clocks to investigate the rejuvenation effects of a porcine plasma fraction treatment in different rat tissues. The treatment more than halved the epigenetic ages of blood, heart, and liver tissue. A less pronounced, but statistically significant, rejuvenation effect could be observed in the hypothalamus. The treatment was accompanied by progressive improvement in the function of these organs as ascertained through numerous biochemical/physiological biomarkers, behavioral responses encompassing cognitive functions. An immunoglobulin G (IgG) N-glycosylation pattern shift from pro- to anti-inflammatory also indicated reversal of glycan aging. Overall, this study demonstrates that a young porcine plasma-derived treatment markedly reverses aging in rats according to epigenetic clocks, IgG glycans, and other biomarkers of aging.
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Affiliation(s)
- Steve Horvath
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, CA, USA.
- Department of Biostatistics, Fielding School of Public Health, University of California, Los Angeles, CA, USA.
- Altos Labs, Cambridge, UK.
| | - Kavita Singh
- Shobhaben Pratapbhai Patel School of Pharmacy and Technology Management, SVKM's NMIMS University, Mumbai, India
| | | | - Shraddha I Khairnar
- Shobhaben Pratapbhai Patel School of Pharmacy and Technology Management, SVKM's NMIMS University, Mumbai, India
| | | | | | - Joseph A Zoller
- Department of Biostatistics, Fielding School of Public Health, University of California, Los Angeles, CA, USA
| | - Caesar Z Li
- Department of Biostatistics, Fielding School of Public Health, University of California, Los Angeles, CA, USA
| | - Claudia B Herenu
- Institute for Experimental Pharmacology of Cordoba (IFEC), School of Chemical Sciences, National University of Cordoba, Cordoba, Argentina
| | - Martina Canatelli-Mallat
- Biochemistry Research Institute of La Plata-Histology B, Pathology B, School of Medicine, University of La Plata, La Plata, Argentina
| | - Marianne Lehmann
- Biochemistry Research Institute of La Plata-Histology B, Pathology B, School of Medicine, University of La Plata, La Plata, Argentina
| | | | | | | | - Leah C Solberg Woods
- Wake Forest University School of Medicine, Medical Center Drive, Winston Salem, NC, USA
| | - Angel Garcia Martinez
- Department of Pharmacology, Addiction Science and Toxicology, The University of Tennessee Health Science Center, Memphis, TN, USA
| | - Tengfei Wang
- Department of Pharmacology, Addiction Science and Toxicology, The University of Tennessee Health Science Center, Memphis, TN, USA
| | - Priscila Chiavellini
- Biochemistry Research Institute of La Plata-Histology B, Pathology B, School of Medicine, University of La Plata, La Plata, Argentina
| | - Andrew J Levine
- Department of Neurology, David Geffen School of Medicine at the University of California, Los Angeles, CA, USA
| | - Hao Chen
- Department of Pharmacology, Addiction Science and Toxicology, The University of Tennessee Health Science Center, Memphis, TN, USA
| | | | | | - Gordan Lauc
- Genos Glycoscience Research Laboratory, Zagreb, Croatia
- Faculty of Pharmacy and Biochemistry, University of Zagreb, Zagreb, Croatia
| | - Rodolfo G Goya
- Biochemistry Research Institute of La Plata-Histology B, Pathology B, School of Medicine, University of La Plata, La Plata, Argentina
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Wang Y, Grant OA, Zhai X, Mcdonald-Maier KD, Schalkwyk LC. Insights into ageing rates comparison across tissues from recalibrating cerebellum DNA methylation clock. GeroScience 2024; 46:39-56. [PMID: 37597113 PMCID: PMC10828477 DOI: 10.1007/s11357-023-00871-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2023] [Accepted: 07/07/2023] [Indexed: 08/21/2023] Open
Abstract
DNA methylation (DNAm)-based age clocks have been studied extensively as a biomarker of human ageing and a risk factor for age-related diseases. Despite different tissues having vastly different rates of proliferation, it is still largely unknown whether they age at different rates. It was previously reported that the cerebellum ages slowly; however, this claim was drawn from a single clock using a relatively small sample size and so warrants further investigation. We collected the largest cerebellum DNAm dataset (N = 752) to date. We found the respective epigenetic ages are all severely underestimated by six representative DNAm age clocks, with the underestimation effects more pronounced in the four clocks whose training datasets do not include brain-related tissues. We identified 613 age-associated CpGs in the cerebellum, which accounts for only 14.5% of the number found in the middle temporal gyrus from the same population (N = 404). From the 613 cerebellum age-associated CpGs, we built a highly accurate age prediction model for the cerebellum named CerebellumClockspecific (Pearson correlation=0.941, MAD=3.18 years). Ageing rate comparisons based on the two tissue-specific clocks constructed on the 201 overlapping age-associated CpGs support the cerebellum has younger DNAm age. Nevertheless, we built BrainCortexClock to prove a single DNAm clock is able to unbiasedly estimate DNAm ages of both cerebellum and cerebral cortex, when they are adequately and equally represented in the training dataset. Comparing ageing rates across tissues using DNA methylation multi-tissue clocks is flawed. The large underestimation of age prediction for cerebellums by previous clocks mainly reflects the improper usage of these age clocks. There exist strong and consistent ageing effects on the cerebellar methylome, and we suggest the smaller number of age-associated CpG sites in cerebellum is largely attributed to its extremely low average cell replication rates.
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Affiliation(s)
- Yucheng Wang
- School of Computer Science and Electronic Engineering, University of Essex, Colchester, CO4 3SQ, UK
- School of Life Sciences, University of Essex, Colchester, CO4 3SQ, UK
| | - Olivia A Grant
- School of Life Sciences, University of Essex, Colchester, CO4 3SQ, UK
- Institute of Social and Economic Research, University of Essex, Colchester, CO4 3SQ, UK
- Blizard Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, E1 2AT, UK
| | - Xiaojun Zhai
- School of Computer Science and Electronic Engineering, University of Essex, Colchester, CO4 3SQ, UK.
| | - Klaus D Mcdonald-Maier
- School of Computer Science and Electronic Engineering, University of Essex, Colchester, CO4 3SQ, UK
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Kusters CDJ, Paul KC, Lu AT, Ferruci L, Ritz BR, Binder AM, Horvath S. Higher testosterone and testosterone/estradiol ratio in men are associated with decreased Pheno-/GrimAge and DNA-methylation based PAI1. GeroScience 2024; 46:1053-1069. [PMID: 37369886 PMCID: PMC10828310 DOI: 10.1007/s11357-023-00832-3] [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: 03/14/2023] [Accepted: 05/18/2023] [Indexed: 06/29/2023] Open
Abstract
Sex hormones are hypothesized to drive sex-specific health disparities. Here, we study the association between sex steroid hormones and DNA methylation-based (DNAm) biomarkers of age and mortality risk including Pheno Age Acceleration (AA), Grim AA, and DNAm-based estimators of Plasminogen Activator Inhibitor 1 (PAI1), and leptin concentrations. We pooled data from three population-based cohorts, the Framingham Heart Study Offspring Cohort, the Baltimore Longitudinal Study of Aging, and the InCHIANTI Study, including 1,062 postmenopausal women without hormone therapy and 1,612 men of European descent. Sex-stratified analyses using a linear mixed regression were performed, with a Benjamini-Hochberg (BH) adjustment for multiple testing. Sex Hormone Binding Globulin (SHBG) was associated with a decrease in DNAm PAI1 among men (per 1 standard deviation (SD): -478 pg/mL; 95%CI: -614 to -343; P:1e-11; BH-P: 1e-10), and women (-434 pg/mL; 95%CI: -589 to -279; P:1e-7; BH-P:2e-6). The testosterone/estradiol (TE) ratio was associated with a decrease in Pheno AA (-0.41 years; 95%CI: -0.70 to -0.12; P:0.01; BH-P: 0.04), and DNAm PAI1 (-351 pg/mL; 95%CI: -486 to -217; P:4e-7; BH-P:3e-6) among men. In men, testosterone was associated with a decrease in DNAm PAI1 (-481 pg/mL; 95%CI: -613 to -349; P:2e-12; BH-P:6e-11). SHBG was associated with lower DNAm PAI1 among men and women. Higher testosterone and testosterone/estradiol ratio were associated with lower DNAm PAI and a younger epigenetic age in men. A decrease in DNAm PAI1 is associated with lower mortality and morbidity risk indicating a potential protective effect of testosterone on lifespan and conceivably cardiovascular health via DNAm PAI1.
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Affiliation(s)
- Cynthia D J Kusters
- Department of Human Genetics, David Geffen School of Medicine, Los Angeles, CA, USA.
- Department of Epidemiology, UCLA Fielding School of Public Health, Los Angeles, CA, USA.
- Department of Epidemiology, Fielding School of Public Health at UCLA, Box 708822, 650 Charles E. Young Drive South, CA, 90095-7088, Los Angeles, USA.
| | - Kimberly C Paul
- Department of Neurology, David Geffen School of Medicine, Los Angeles, CA, USA
| | - Ake T Lu
- Department of Human Genetics, David Geffen School of Medicine, Los Angeles, CA, USA
- Altos Labs, San Diego, USA
| | - Luigi Ferruci
- Longitudinal Studies Section, Translational Gerontology Branch, National Institute On Aging, National Institutes of Health, Baltimore, USA
| | - Beate R Ritz
- Department of Epidemiology, UCLA Fielding School of Public Health, Los Angeles, CA, USA
- Department of Neurology, David Geffen School of Medicine, Los Angeles, CA, USA
- Department of Environmental Health, UCLA Fielding School of Public Health, Los Angeles, CA, USA
| | - Alexandra M Binder
- Department of Epidemiology, UCLA Fielding School of Public Health, Los Angeles, CA, USA
- Population Sciences in the Pacific Program, University of Hawaii Cancer Center, Honolulu, HI, USA
| | - Steve Horvath
- Department of Human Genetics, David Geffen School of Medicine, Los Angeles, CA, USA
- Altos Labs, San Diego, USA
- Department of Biostatistics, School of Public Health, University of California, Los Angeles, Los Angeles, CA, USA
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55
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Laubach ZM, Bozack A, Aris IM, Slopen N, Tiemeier H, Hivert MF, Cardenas A, Perng W. Maternal prenatal social experiences and offspring epigenetic age acceleration from birth to mid-childhood. Ann Epidemiol 2024; 90:28-34. [PMID: 37839726 PMCID: PMC10842218 DOI: 10.1016/j.annepidem.2023.10.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2023] [Revised: 09/27/2023] [Accepted: 10/10/2023] [Indexed: 10/17/2023]
Abstract
PURPOSE Investigate associations of maternal social experiences with offspring epigenetic age acceleration (EAA) from birth through mid-childhood among 205 mother-offspring dyads of minoritized racial and ethnic groups. METHODS We used linear regression to examine associations of maternal experiences of racial bias or discrimination (0 = none, 1-2 = intermediate, or 3+ = high), social support (tertile 1 = low, 2 = intermediate, 3 = high), and socioeconomic status index (tertile 1 = low, 2 = intermediate, 3 = high) during the prenatal period with offspring EAA according to Horvath's Pan-Tissue, Horvath's Skin and Blood, and Intrinsic EAA clocks at birth, 3 years, and 7 years. RESULTS In comparison to children of women who did not experience any racial bias or discrimination, those whose mothers reported highest levels of racial bias or discrimination had lower Pan-Tissue clock EAA in early (-0.50 years; 90% CI: -0.91, -0.09) and mid-childhood (-0.75 years; -1.41, -0.08). We observed similar associations for the Skin and Blood clock and Intrinsic EAA. Maternal experiences of discrimination were not associated with Pan-Tissue EAA at birth. Neither maternal social support nor socioeconomic status predicted offspring EAA. CONCLUSIONS Children whose mothers experienced higher racial bias or discrimination exhibited slower EAA. Future studies are warranted to confirm these findings and establish associations of early-life EAA with long-term health outcomes.
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Affiliation(s)
- Zachary M Laubach
- Department of Ecology and Evolutionary Biology (EBIO), University of Colorado Boulder
| | - Anne Bozack
- Department of Epidemiology and Population Health, Stanford University, Stanford, CA
| | - Izzuddin M Aris
- Division of Chronic Disease Research Across the Lifecourse (CORAL), Department of Population Medicine, Harvard Medical School, Boston, MA
| | - Natalie Slopen
- Department of Social and Behavioral Sciences, Harvard T.H. Chan School of Public Health, Boston, MA
| | - Henning Tiemeier
- Department of Social and Behavioral Sciences, Harvard T.H. Chan School of Public Health, Boston, MA
| | - Marie-France Hivert
- Division of Chronic Disease Research Across the Lifecourse (CORAL), Department of Population Medicine, Harvard Medical School, Boston, MA; Diabetes Unit, Massachusetts General Hospital, Boston, MA
| | - Andres Cardenas
- Department of Epidemiology and Population Health, Stanford University, Stanford, CA
| | - Wei Perng
- Lifecourse Epidemiology of Adiposity and Diabetes (LEAD Center), Department of Epidemiology, Colorado School of Public Health, Aurora, CO.
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Lasho T, Patnaik MM. Adaptive and Maladaptive Clonal Hematopoiesis in Telomere Biology Disorders. Curr Hematol Malig Rep 2024; 19:35-44. [PMID: 38095828 DOI: 10.1007/s11899-023-00719-2] [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] [Accepted: 11/24/2023] [Indexed: 01/30/2024]
Abstract
PURPOSE OF REVIEW Telomere biology disorders (TBDs) are germline-inherited conditions characterized by reduction in telomerase function, accelerated shortening of telomeres, predisposition to organ-failure syndromes, and increased risk of neoplasms, especially myeloid malignancies. In normal cells, critically short telomeres trigger apoptosis and/or cellular senescence. However, the evolutionary mechanism by which TBD-related telomerase-deficient cells can overcome this fitness constraint remains elusive. RECENT FINDINGS Preliminary data suggests the existence of adaptive somatic mosaic states characterized by variants in TBD-related genes and maladaptive somatic mosaic states that attempt to overcome hematopoietic fitness constraints by alternative methods leading to clonal hematopoiesis. TBDs are both rare and highly heterogeneous in presentation, and the association of TBD with malignant transformation is unclear. Understanding the clonal complexity and mechanisms behind TBD-associated molecular signatures that lead to somatic adaptation in the setting of defective hematopoiesis will help inform therapy and treatment for this set of diseases.
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Affiliation(s)
- Terra Lasho
- Division of Hematology, Mayo Clinic Rochester, 200 First Street SW, Rochester, MN, 55905, USA
| | - Mrinal M Patnaik
- Division of Hematology, Mayo Clinic Rochester, 200 First Street SW, Rochester, MN, 55905, USA.
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Knight AK, Spencer JB, Smith AK. DNA methylation as a window into female reproductive aging. Epigenomics 2024; 16:175-188. [PMID: 38131149 PMCID: PMC10841041 DOI: 10.2217/epi-2023-0298] [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: 08/24/2023] [Accepted: 12/05/2023] [Indexed: 12/23/2023] Open
Abstract
People with ovaries experience reproductive aging as their reproductive function and system declines. This has significant implications for both fertility and long-term health, with people experiencing an increased risk of cardiometabolic disorders after menopause. Reproductive aging can be assessed through markers of ovarian reserve, response to fertility treatment or molecular biomarkers, including DNA methylation. Changes in DNA methylation with age associate with poorer reproductive outcomes, and epigenome-wide studies can provide insight into genes and pathways involved. DNA methylation-based epigenetic clocks can quantify biological age in reproductive tissues and systemically. This review provides an overview of hallmarks and theories of aging in the context of the reproductive system, and then focuses on studies of DNA methylation in reproductive tissues.
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Affiliation(s)
- Anna K Knight
- Research Division, Department of Gynecology & Obstetrics, Emory University School of Medicine, Atlanta, GA 30322, USA
| | - Jessica B Spencer
- Reproductive Endocrinology & Infertility Division, Department of Gynecology & Obstetrics, Emory University School of Medicine, Atlanta, GA 30322, USA
| | - Alicia K Smith
- Research Division, Department of Gynecology & Obstetrics, Emory University School of Medicine, Atlanta, GA 30322, USA
- Reproductive Endocrinology & Infertility Division, Department of Gynecology & Obstetrics, Emory University School of Medicine, Atlanta, GA 30322, USA
- Department of Psychiatry & Behavioral Sciences, Emory University School of Medicine, Atlanta, GA 30322, USA
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58
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Farrell C, Hu C, Lapborisuth K, Pu K, Snir S, Pellegrini M. Identifying epigenetic aging moderators using the epigenetic pacemaker. FRONTIERS IN BIOINFORMATICS 2024; 3:1308680. [PMID: 38235295 PMCID: PMC10791860 DOI: 10.3389/fbinf.2023.1308680] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2023] [Accepted: 12/04/2023] [Indexed: 01/19/2024] Open
Abstract
Epigenetic clocks are DNA methylation-based chronological age prediction models that are commonly employed to study age-related biology. The difference between the predicted and observed age is often interpreted as a form of biological age acceleration, and many studies have measured the impact of environmental and disease-associated factors on epigenetic age. Most epigenetic clocks are fit using approaches that minimize the error between the predicted and observed chronological age, and as a result, they may not accurately model the impact of factors that moderate the relationship between the actual and epigenetic age. Here, we compare epigenetic clocks that are constructed using penalized regression methods to an evolutionary framework of epigenetic aging with the epigenetic pacemaker (EPM), which directly models DNA methylation as a function of a time-dependent epigenetic state. In simulations, we show that the value of the epigenetic state is impacted by factors such as age, sex, and cell-type composition. Next, in a dataset aggregated from previous studies, we show that the epigenetic state is also moderated by sex and the cell type. Finally, we demonstrate that the epigenetic state is also moderated by toxins in a study on polybrominated biphenyl exposure. Thus, we find that the pacemaker provides a robust framework for the study of factors that impact epigenetic age acceleration and that the effect of these factors may be obscured in traditional clocks based on linear regression models.
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Affiliation(s)
- Colin Farrell
- Department of Molecular, Cell and Developmental Biology, University of California, Los Angeles, Los Angeles, CA, United States
| | - Chanyue Hu
- Department of Molecular, Cell and Developmental Biology, University of California, Los Angeles, Los Angeles, CA, United States
| | - Kalsuda Lapborisuth
- Department of Molecular, Cell and Developmental Biology, University of California, Los Angeles, Los Angeles, CA, United States
| | - Kyle Pu
- Department of Molecular, Cell and Developmental Biology, University of California, Los Angeles, Los Angeles, CA, United States
| | - Sagi Snir
- Department of Evolutionary Biology, University of Haifa, Haifa, Israel
| | - Matteo Pellegrini
- Department of Molecular, Cell and Developmental Biology, University of California, Los Angeles, Los Angeles, CA, United States
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Gilmore N, Loh KP, Liposits G, Arora SP, Vertino P, Janelsins M. Epigenetic and inflammatory markers in older adults with cancer: A Young International Society of Geriatric Oncology narrative review. J Geriatr Oncol 2024; 15:101655. [PMID: 37931584 PMCID: PMC10841884 DOI: 10.1016/j.jgo.2023.101655] [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: 09/13/2023] [Revised: 10/17/2023] [Accepted: 10/26/2023] [Indexed: 11/08/2023]
Abstract
The number of adults aged ≥ 65 years with cancer is rapidly increasing. Older adults with cancer are susceptible to treatment-related acute and chronic adverse events, resulting in loss of independence, reduction in physical function, and decreased quality of life. Nevertheless, evidence-based interventions to prevent or treat acute and chronic adverse events in older adults with cancer are limited. Several promising blood-based biomarkers related to inflammation and epigenetic modifications are available to identify older adults with cancer who are at increased risk of accelerated aging and physical, functional, and cognitive impairments caused by the cancer and its treatment. Inflammatory changes and epigenetic modifications can be reversible and targeted by lifestyle changes and interventions. Here we discuss ways in which changes in inflammatory and epigenetic pathways influence the aging process and how these pathways can be targeted by interventions aimed at reducing inflammation and aging-associated biological markers. As the number of older adults with cancer entering survivorship continues to increase, it is becoming progressively more important to understand ways in which the benefit from treatment can be enhanced while reducing the effects of accelerated aging.
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Affiliation(s)
- Nikesha Gilmore
- Department of Surgery, Division of Supportive Care in Cancer, University of Rochester Medical Center, Rochester, NY, USA; James P Wilmot Cancer Institute, University of Rochester Medical Center, Rochester, NY, USA.
| | - Kah Poh Loh
- James P Wilmot Cancer Institute, University of Rochester Medical Center, Rochester, NY, USA; Division of Hematology/Oncology, Department of Medicine, University of Rochester Medical Center, Rochester, NY, USA.
| | - Gabor Liposits
- Department of Oncology, Odense University Hospital, Odense, Denmark; Department of Clinical Research, University of Southern Denmark, Odense, Denmark; Academy of Geriatric Cancer Research (AgeCare), Odense, Denmark; Department of Oncology, Regional Hospital Gødstrup, Herning, Denmark.
| | - Sukeshi Patel Arora
- Division of Hematology/Oncology, Department of Medicine, Mays Cancer Center, University of Texas Health San Antonio, San Antonio, Texas, USA.
| | - Paula Vertino
- James P Wilmot Cancer Institute, University of Rochester Medical Center, Rochester, NY, USA; Department of Biomedical Genetics, University of Rochester Medical Center, Rochester, NY, USA.
| | - Michelle Janelsins
- Department of Surgery, Division of Supportive Care in Cancer, University of Rochester Medical Center, Rochester, NY, USA; James P Wilmot Cancer Institute, University of Rochester Medical Center, Rochester, NY, USA.
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Han JDJ. The ticking of aging clocks. Trends Endocrinol Metab 2024; 35:11-22. [PMID: 37880054 DOI: 10.1016/j.tem.2023.09.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/18/2023] [Revised: 09/21/2023] [Accepted: 09/26/2023] [Indexed: 10/27/2023]
Abstract
Computational models that measure biological age and aging rate regardless of chronological age are called aging clocks. The underlying counting mechanisms of the intrinsic timers of these clocks are still unclear. Molecular mediators and determinants of aging rate point to the key roles of DNA damage, epigenetic drift, and inflammation. Persistent DNA damage leads to cellular senescence and the senescence-associated secretory phenotype (SASP), which induces cytotoxic immune cell infiltration; this further induces DNA damage through reactive oxygen and nitrogen species (RONS). I discuss the possibility that DNA damage (or the response to it, including epigenetic changes) is the fundamental counting unit of cell cycles and cellular senescence, that ultimately accounts for cell composition changes and functional decline in tissues, as well as the key intervention points.
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Affiliation(s)
- Jing-Dong J Han
- Peking-Tsinghua Center for Life Sciences, Academy for Advanced Interdisciplinary Studies, Center for Quantitative Biology (CQB), Peking University, Beijing, China; Peking University Chengdu Academy for Advanced Interdisciplinary Biotechnologies, Chengdu, China; International Center for Aging and Cancer (ICAC), The First Affiliated Hospital, Hainan Medical University, Haikou, China.
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Dutta S, Goodrich JM, Dolinoy DC, Ruden DM. Biological Aging Acceleration Due to Environmental Exposures: An Exciting New Direction in Toxicogenomics Research. Genes (Basel) 2023; 15:16. [PMID: 38275598 PMCID: PMC10815440 DOI: 10.3390/genes15010016] [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: 11/27/2023] [Revised: 12/14/2023] [Accepted: 12/20/2023] [Indexed: 01/27/2024] Open
Abstract
Biological clock technologies are designed to assess the acceleration of biological age (B-age) in diverse cell types, offering a distinctive opportunity in toxicogenomic research to explore the impact of environmental stressors, social challenges, and unhealthy lifestyles on health impairment. These clocks also play a role in identifying factors that can hinder aging and promote a healthy lifestyle. Over the past decade, researchers in epigenetics have developed testing methods that predict the chronological and biological age of organisms. These methods rely on assessing DNA methylation (DNAm) levels at specific CpG sites, RNA levels, and various biomolecules across multiple cell types, tissues, and entire organisms. Commonly known as 'biological clocks' (B-clocks), these estimators hold promise for gaining deeper insights into the pathways contributing to the development of age-related disorders. They also provide a foundation for devising biomedical or social interventions to prevent, reverse, or mitigate these disorders. This review article provides a concise overview of various epigenetic clocks and explores their susceptibility to environmental stressors.
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Affiliation(s)
- Sudipta Dutta
- Department of Veterinary Integrative Biosciences, College of Veterinary Medicine and Biomedical Sciences, Texas A&M University, College Station, TX 77843, USA;
| | - Jaclyn M. Goodrich
- Department of Environmental Health Sciences, School of Public Health, University of Michigan, Ann Arbor, MI 48109, USA; (J.M.G.); (D.C.D.)
| | - Dana C. Dolinoy
- Department of Environmental Health Sciences, School of Public Health, University of Michigan, Ann Arbor, MI 48109, USA; (J.M.G.); (D.C.D.)
- Department of Nutritional Sciences, School of Public Health, University of Michigan, Ann Arbor, MI 48109, USA
| | - Douglas M. Ruden
- C. S. Mott Center for Human Health and Development, Department of Obstetrics and Gynecology, Institute of Environmental Health Sciences, Wayne State University, Detroit, MI 48202, USA
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Lynch M, Em Arpawong T, Beam CR. Associations Between Longitudinal Loneliness, DNA Methylation Age Acceleration, and Cognitive Functioning. J Gerontol B Psychol Sci Soc Sci 2023; 78:2045-2059. [PMID: 37718577 PMCID: PMC10699733 DOI: 10.1093/geronb/gbad128] [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: 01/19/2023] [Indexed: 09/19/2023] Open
Abstract
OBJECTIVES Loneliness may influence aging biomarkers related to cognitive functioning, for example, through accelerated DNA methylation (DNAm) aging. METHODS In the present study, we tested whether six common DNAm age acceleration measures mediated the effects of baseline loneliness and five different longitudinal loneliness trajectories on general cognitive ability, immediate memory recall, delayed memory recall, and processing speed in 1,814 older adults in the Health and Retirement Study. RESULTS We found that baseline loneliness and individuals who belong to the highest loneliness trajectories had poorer general cognitive ability and memory scores. Only DNAm age acceleration measures that index physiological comorbidities, unhealthy lifestyle factors (e.g., smoking), and mortality risk-mediated effects of baseline loneliness on general cognitive ability and memory functioning but not processing speed. These same DNAm measures mediated effects of the moderate-but-declining loneliness trajectory on cognitive functioning. Additionally, immediate and delayed memory scores were mediated by GrimAge Accel in the lowest and two highest loneliness trajectory groups. Total and mediated effects of loneliness on cognitive functioning outcomes were mainly accounted for by demographic, social, psychological, and physiological covariates, most notably self-rated health, depressive symptomatology, objective social isolation, and body mass index. DISCUSSION Current findings suggest that DNAm biomarkers of aging, particularly GrimAge Accel, have promise for explaining the prospective association between loneliness and cognitive functioning outcomes.
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Affiliation(s)
- Morgan Lynch
- Department of Psychology, University of Southern California, Los Angeles, California, USA
| | - Thalida Em Arpawong
- Davis School of Gerontology, University of Southern California, Los Angeles, California, USA
| | - Christopher R Beam
- Department of Psychology, University of Southern California, Los Angeles, California, USA
- Davis School of Gerontology, University of Southern California, Los Angeles, California, USA
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Horvath S, Haghani A, Zoller JA, Lu AT, Ernst J, Pellegrini M, Jasinska AJ, Mattison JA, Salmon AB, Raj K, Horvath M, Paul KC, Ritz BR, Robeck TR, Spriggs M, Ehmke EE, Jenkins S, Li C, Nathanielsz PW. Pan-primate studies of age and sex. GeroScience 2023; 45:3187-3209. [PMID: 37493860 PMCID: PMC10643767 DOI: 10.1007/s11357-023-00878-3] [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: 06/08/2023] [Accepted: 07/16/2023] [Indexed: 07/27/2023] Open
Abstract
Age and sex have a profound effect on cytosine methylation levels in humans and many other species. Here we analyzed DNA methylation profiles of 2400 tissues derived from 37 primate species including 11 haplorhine species (baboons, marmosets, vervets, rhesus macaque, chimpanzees, gorillas, orangutan, humans) and 26 strepsirrhine species (suborders Lemuriformes and Lorisiformes). From these we present here, pan-primate epigenetic clocks which are highly accurate for all primates including humans (age correlation R = 0.98). We also carried out in-depth analysis of baboon DNA methylation profiles and generated five epigenetic clocks for baboons (Olive-yellow baboon hybrid), one of which, the pan-tissue epigenetic clock, was trained on seven tissue types (fetal cerebral cortex, adult cerebral cortex, cerebellum, adipose, heart, liver, and skeletal muscle) with ages ranging from late fetal life to 22.8 years of age. Using the primate data, we characterize the effect of age and sex on individual cytosines in highly conserved regions. We identify 11 sex-related CpGs on autosomes near genes (POU3F2, CDYL, MYCL, FBXL4, ZC3H10, ZXDC, RRAS, FAM217A, RBM39, GRIA2, UHRF2). Low overlap can be observed between age- and sex-related CpGs. Overall, this study advances our understanding of conserved age- and sex-related epigenetic changes in primates, and provides biomarkers of aging for all primates.
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Affiliation(s)
- Steve Horvath
- Altos Labs, San Diego, CA, USA.
- Department of Biostatistics, Fielding School of Public Health, University of California, Los Angeles, Los Angeles, CA, USA.
| | | | - Joseph A Zoller
- Department of Biostatistics, Fielding School of Public Health, University of California, Los Angeles, Los Angeles, CA, USA
| | | | - Jason Ernst
- Department of Biological Chemistry, University of California, Los Angeles, Los Angeles, CA, 90095, USA
| | - Matteo Pellegrini
- Department of Molecular, Cell and Developmental Biology, University of California Los Angeles, Los Angeles, CA, 90095, USA
| | - Anna J Jasinska
- Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, Department of Psychiatry and BiobehavioralSciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - Julie A Mattison
- Translational Gerontology Branch, National Institute On Aging Intramural Research Program, National Institutes of Health, Baltimore, MD, USA
| | - Adam B Salmon
- The Sam and Ann Barshop Institute for Longevity and Aging Studies, and Department of Molecular Medicine, UT Health San Antonio, and the Geriatric Research Education and Clinical Center, South Texas Veterans Healthcare System, San Antonio, TX, USA
| | | | | | - Kimberly C Paul
- Department of Neurology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, 90095, USA
| | - Beate R Ritz
- Department of Neurology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, 90095, USA
- Department of Epidemiology, UCLA Fielding School of Public Health, University of California Los Angeles, Los Angeles, CA, 90095, USA
| | - Todd R Robeck
- Corporate Zoological Operations, SeaWorld Parks, Orlando, FL, USA
| | - Maria Spriggs
- Busch Gardens Tampa, SeaWorld Parks, Tampa, FL, 33612, USA
| | | | - Susan Jenkins
- Texas Pregnancy & Life-Course Health Center, Southwest National Primate Research Center, San Antonio, TX, USA
- Department of Animal Science, College of Agriculture and Natural Resources Department, Laramie, WY, USA
| | - Cun Li
- Texas Pregnancy & Life-Course Health Center, Southwest National Primate Research Center, San Antonio, TX, USA
- Department of Animal Science, College of Agriculture and Natural Resources Department, Laramie, WY, USA
| | - Peter W Nathanielsz
- Texas Pregnancy & Life-Course Health Center, Southwest National Primate Research Center, San Antonio, TX, USA
- Department of Animal Science, College of Agriculture and Natural Resources Department, Laramie, WY, USA
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Christian LM, Wilson SJ, Madison AA, Prakash RS, Burd CE, Rosko AE, Kiecolt-Glaser JK. Understanding the health effects of caregiving stress: New directions in molecular aging. Ageing Res Rev 2023; 92:102096. [PMID: 37898293 PMCID: PMC10824392 DOI: 10.1016/j.arr.2023.102096] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2023] [Revised: 10/11/2023] [Accepted: 10/23/2023] [Indexed: 10/30/2023]
Abstract
Dementia caregiving has been linked to multiple health risks, including infectious illness, depression, anxiety, immune dysregulation, weakened vaccine responses, slow wound healing, hypertension, cardiovascular disease, metabolic syndrome, diabetes, frailty, cognitive decline, and reduced structural and functional integrity of the brain. The sustained overproduction of proinflammatory cytokines is a key pathway behind many of these risks. However, contrasting findings suggest that some forms of caregiving may have beneficial effects, such as maintaining caregivers' health and providing a sense of meaning and purpose which, in turn, may contribute to lower rates of functional decline and mortality. The current review synthesizes these disparate literatures, identifies methodological sources of discrepancy, and integrates caregiver research with work on aging biomarkers to propose a research agenda that traces the mechanistic pathways of caregivers' health trajectories with a focus on the unique stressors facing spousal caregivers as compared to other informal caregivers. Combined with a focus on psychosocial moderators and mechanisms, studies using state-of-the-art molecular aging biomarkers such as telomere length, p16INK4a, and epigenetic age could help to reconcile mixed literature on caregiving's sequelae by determining whether and under what conditions caregiving-related experiences contribute to faster aging, in part through inflammatory biology. The biomarkers predict morbidity and mortality, and each contributes non-redundant information about age-related molecular changes -together painting a more complete picture of biological aging. Indeed, assessing changes in these biopsychosocial mechanisms over time would help to clarify the dynamic relationships between caregiving experiences, psychological states, immune function, and aging.
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Affiliation(s)
- Lisa M Christian
- Department of Psychiatry & Behavioral Health, The Ohio State University Wexner Medical Center, Columbus, OH, USA; The Institute for Behavioral Medicine Research, The Ohio State University Wexner Medical Center, Columbus, OH, USA.
| | - Stephanie J Wilson
- Department of Psychology, Southern Methodist University, University Park, TX, USA
| | - Annelise A Madison
- The Institute for Behavioral Medicine Research, The Ohio State University Wexner Medical Center, Columbus, OH, USA; Department of Psychology, The Ohio State University, Columbus, OH, USA
| | - Ruchika S Prakash
- Department of Psychology, The Ohio State University, Columbus, OH, USA; Center for Cognitive and Behavioral Brain Imaging, Ohio State University, Columbus, OH, USA
| | - Christin E Burd
- Departments of Molecular Genetics, Cancer Biology and Genetics, The Ohio State University, Columbus, OH, USA
| | - Ashley E Rosko
- Division of Hematology, The Ohio State University, Columbus, OH, USA
| | - Janice K Kiecolt-Glaser
- Department of Psychiatry & Behavioral Health, The Ohio State University Wexner Medical Center, Columbus, OH, USA; The Institute for Behavioral Medicine Research, The Ohio State University Wexner Medical Center, Columbus, OH, USA
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Baranyi G, Williamson L, Feng Z, Tomlinson S, Vieno M, Dibben C. Early life PM 2.5 exposure, childhood cognitive ability and mortality between age 11 and 86: A record-linkage life-course study from Scotland. ENVIRONMENTAL RESEARCH 2023; 238:117021. [PMID: 37659643 DOI: 10.1016/j.envres.2023.117021] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/20/2023] [Revised: 08/18/2023] [Accepted: 08/29/2023] [Indexed: 09/04/2023]
Abstract
BACKGROUND Living in areas with high air pollution concentrations is associated with all-cause and cause-specific mortality. Exposure in sensitive developmental periods might be long-lasting but studies with very long follow-up are rare, and mediating pathways between early life exposure and life-course mortality are not fully understood. METHODS Data were drawn from the Scottish Longitudinal Study Birth Cohort of 1936, a representative record-linkage study comprising 5% of the Scottish population born in 1936. Participants had valid age 11 cognitive ability test scores along with linked mortality data until age 86. Fine particle (PM2.5) concentrations estimated with the EMEP4UK atmospheric chemistry transport model were linked to participants' residential address derived from the National Identity Register in 1939 (age 3). Confounder-adjusted Cox regression estimated associations between PM2.5 and mortality; regression-based causal mediation analysis explored mediation through childhood cognitive ability. RESULTS The final sample consisted of 2734 individuals with 1608 deaths registered during the 1,833,517 person-months at risk follow-up time. Higher early life PM2.5 exposure increased the risk of all-cause mortality (HR = 1.03, 95% CI: 1.01-1.04 per 10 μg m-3 increment), associations were stronger for mortality between age 65 and 86. PM2.5 increased the risk of cancer-related mortality (HR = 1.05, 95% CI: 1.02-1.08), especially for lung cancer among females (HR = 1.11, 95% CI: 1.02-1.21), but not for cardiovascular and respiratory diseases. Higher PM2.5 in early life (≥50 μg m-3) was associated with lower childhood cognitive ability, which, in turn, increased the risk of all-cause mortality and mediated 25% of the total associations. CONCLUSIONS In our life-course study with 75-year of continuous mortality records, we found that exposure to air pollution in early life was associated with higher mortality in late adulthood, and that childhood cognitive ability partly mediated this relationship. Findings suggest that past air pollution concentrations will likely impact health and longevity for decades to come.
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Affiliation(s)
- Gergő Baranyi
- Centre for Research on Environment, Society and Health, School of Geosciences, The University of Edinburgh, Edinburgh, UK.
| | - Lee Williamson
- Centre for Research on Environment, Society and Health, School of Geosciences, The University of Edinburgh, Edinburgh, UK; Longitudinal Studies Centre - Scotland, School of GeoSciences, The University of Edinburgh, Edinburgh, UK
| | - Zhiqiang Feng
- Centre for Research on Environment, Society and Health, School of Geosciences, The University of Edinburgh, Edinburgh, UK
| | - Sam Tomlinson
- UK Centre for Ecology & Hydrology, Library Ave, Bailrigg, Lancaster, UK
| | - Massimo Vieno
- UK Centre for Ecology & Hydrology, Bush Estate, Penicuik, UK
| | - Chris Dibben
- Centre for Research on Environment, Society and Health, School of Geosciences, The University of Edinburgh, Edinburgh, UK
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Jackson P, Kempf MC, Goodin BR, A. Hidalgo B, Aroke EN. Neighborhood Environment and Epigenetic Age: A Scoping Review. West J Nurs Res 2023; 45:1139-1149. [PMID: 37902222 PMCID: PMC10748459 DOI: 10.1177/01939459231208304] [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: 10/31/2023]
Abstract
BACKGROUND Interest in how the neighborhood environment impacts age-related health conditions has been increasing for decades. Epigenetic changes are environmentally derived modifications to the genome that alter the way genes function-thus altering health status. Epigenetic age, a biomarker for biological age, has been shown to be a useful predictor of several age-related health conditions. Consequently, its relation to the neighborhood environment has been the focus of a growing body of literature. OBJECTIVE We aimed to describe the scope of the evidence on the relationship between neighborhood environmental characteristics and epigenetic age. METHODS Using scoping review following methods established by Arksey and O'Malley, we first defined our research questions and searched the literature in PubMed, PsycINFO, and EMBASE. Next, we selected the literature to be included, and finally, we analyzed and summarized the information. RESULTS Nine articles met the inclusion criteria. Most studies examined deprivation as the neighborhood characteristic of interest. While all studies were observational in design, the articles included diverse participants, including men and women, adults and children, and multiple ethnicities. Results demonstrated a relationship between the neighborhood environment and epigenetic age, whether the characteristic of interest is socioeconomic or physical. CONCLUSIONS Overall, studies concluded there was a relationship between neighborhood characteristics and epigenetic age, whether the characteristic of interest was socioeconomic or physical. However, findings varied based on how the neighborhood characteristic and/or epigenetic age was measured. Furthermore, a paucity of investigations on physical characteristics was noticeable and warrants increased attention.
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Affiliation(s)
- Pamela Jackson
- School of Public Health, University of Alabama at Birmingham, Birmingham, AL, USA
| | | | - Burel R. Goodin
- Department of Anesthesiology, Washington University Pain Center, Washington University School of Medicine in St. Louis, St. Louis, MO, USA
| | - Bertha A. Hidalgo
- School of Public Health, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Edwin N. Aroke
- School of Nursing, University of Alabama at Birmingham, Birmingham, AL, USA
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Obeid R, Rickens P, Heine GH, Emrich IE, Fliser D, Zawada AM, Bodis M, Geisel J. ELOVL2-methylation and renal and cardiovascular event in patients with chronic kidney disease. Eur J Clin Invest 2023; 53:e14068. [PMID: 37493252 DOI: 10.1111/eci.14068] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/22/2023] [Revised: 07/13/2023] [Accepted: 07/15/2023] [Indexed: 07/27/2023]
Abstract
BACKGROUND Methylation of the Elongation Of Very Long Chain Fatty Acids-Like 2 (ELOVL2) gene promoter may predict premature ageing and cardiovascular risk. METHODS We studied the cross-sectional associations between blood ELOVL2-methylation and cardiovascular risk factors in 350 patients with chronic kidney disease (CKD) stage G2-G4 aged between 22 and 90 years. In a follow-up study for a mean of 3.9 years, we investigated the association between baseline ELOVL2-methylation and renal or cardiovascular events including death. RESULTS ELOVL2-methylation at seven CpG cites increased with age (the correlation coefficients between 0.67 and 0.87, p < 0.001). The ELOVL2-CpGs methylation was lower in patients with CKD stage G2 versus those in stage G3a, G3b and G4, but the differences were explained by age. ELOVL2-CpGs methylation showed no correlations with cardiovascular risk factors after adjusting for age. During the follow-up, 64 patients showed deterioration in renal function or died and 77 showed cardiovascular events or died. The hazard ratio and 95% confidence intervals for renal or cardiovascular events according to baseline ELOVL2-CpGs methylation were not significant after adjustment for covariates. CONCLUSIONS ELOVL2-hypermethylation showed a strong association with age, but was not independently associated with cardiovascular risk factors or with future renal or cardiovascular events in patients with CKD. ELOVL2 gene methylation is not likely to be itself a cause for ageing or illnesses, but it could be rather influenced by other upstream processes that deserve investigation.
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Affiliation(s)
- Rima Obeid
- Department of Clinical Chemistry and Laboratory Medicine, Saarland University Hospital, Homburg, Germany
| | - Patricia Rickens
- Department of Clinical Chemistry and Laboratory Medicine, Saarland University Hospital, Homburg, Germany
| | - Gunnar Henrik Heine
- Agaplesion Markus Hospital, Medical Clinic II, Frankfurt am Main, Germany
- Department of Internal Medicine IV-Nephrology and Hypertension, Saarland University Hospital and Saarland University Faculty of Medicine, Homburg, Germany
| | - Insa E Emrich
- Saarland University Medical Center, Internal Medicine III - Cardiology, Angiology and Intensive Care Medicine, Homburg, Germany
| | - Danilo Fliser
- Department of Internal Medicine IV-Nephrology and Hypertension, Saarland University Hospital and Saarland University Faculty of Medicine, Homburg, Germany
| | - Adam M Zawada
- Department of Internal Medicine IV-Nephrology and Hypertension, Saarland University Hospital and Saarland University Faculty of Medicine, Homburg, Germany
| | - Marion Bodis
- Department of Clinical Chemistry and Laboratory Medicine, Saarland University Hospital, Homburg, Germany
| | - Jürgen Geisel
- Department of Clinical Chemistry and Laboratory Medicine, Saarland University Hospital, Homburg, Germany
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Zhang Y, Atkinson J, Burd CE, Graves J, Segal BM. Biological aging in multiple sclerosis. Mult Scler 2023; 29:1701-1708. [PMID: 37877740 PMCID: PMC10843499 DOI: 10.1177/13524585231204122] [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: 10/26/2023]
Abstract
Multiple sclerosis (MS) is most likely to adopt a progressive clinical course during middle age or beyond, and the number of older adults with MS is steadily increasing. Developing new strategies to manage progressive forms of MS, which do not respond to currently available disease-modifying therapies (DMTs), will require a deeper understanding of the mechanisms by which biological aging interacts with pathogenic pathways to propel disability accumulation. In experimental autoimmune encephalomyelitis (EAE), a widely used preclinical mouse model of MS, middle-aged animals experience a more severe and protracted clinical course than their younger counterparts. This exacerbated disease course is accompanied by persistent neuroinflammation. Clinical studies of age-related biomarkers, such as telomere length, senescence markers, and DNA methylation, suggest that biological aging is accelerated in people with MS compared with age- and sex-matched healthy controls. Furthermore, distinguishing biological age from chronological may afford more precision in determining aging effects in MS. Here we review the current literature on aging biology and its impact on MS pathogenesis. Future research on this topic may lead to the development of novel biomarkers and senotherapy agents that slow neurological decline in people with progressive MS by targeting relevant aging-related pathways.
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Affiliation(s)
- Yinan Zhang
- Department of Neurology, The Ohio State University Wexner
Medical Center, Columbus, OH
| | - Jeffrey Atkinson
- Department of Neurology, The Ohio State University Wexner
Medical Center, Columbus, OH
| | - Christin E. Burd
- Departments of Molecular Genetics, Cancer Biology and
Genetics, The Ohio State University, Columbus, OH
| | - Jennifer Graves
- Department of Neurosciences, University of California San
Diego, San Diego, CA
| | - Benjamin M. Segal
- Department of Neurology, The Ohio State University Wexner
Medical Center, Columbus, OH
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Sumida K, Mozhui K, Liang X, Mallisetty Y, Han Z, Kovesdy CP. Association of DNA methylation signatures with premature ageing and cardiovascular death in patients with end-stage kidney disease: a pilot epigenome-wide association study. Epigenetics 2023; 18:2214394. [PMID: 37207321 PMCID: PMC10202091 DOI: 10.1080/15592294.2023.2214394] [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: 12/29/2022] [Revised: 04/25/2023] [Accepted: 05/09/2023] [Indexed: 05/21/2023] Open
Abstract
Patients with end-stage kidney disease (ESKD) display features of premature aging. There is strong evidence that changes in DNA methylation (DNAm) contribute to age-related pathologies; however, little is known about their association with premature aging and cardiovascular mortality in patients with ESKD. We assayed genome-wide DNAm in a pilot case-control study of 60 hemodialysis patients with (n=30, cases) and without (n=30, controls) a fatal cardiovascular event. DNAm was profiled on the Illumina EPIC BeadChip. Four established DNAm clocks (i.e., Horvath-, Hannum-, Pheno-, and GrimAge) were used to estimate epigenetic age (DNAmAge). Epigenetic age acceleration (EAA) was derived as the residuals of regressing DNAmAge on chronological age (chroAge), and its association with cardiovascular death was examined using multivariable conditional logistic regression. An epigenome-wide association study (EWAS) was performed to identify differentially methylated CpGs associated with cardiovascular death. All clocks performed well at predicting chroAge (correlation between DNAmAges and chroAge of r=0.76-0.89), with GrimAge showing the largest deviation from chroAge (a mean of +21.3 years). There was no significant association of EAAs with cardiovascular death. In the EWAS, a CpG (cg22305782) in the FBXL19 gene had the strongest association with cardiovascular death with significantly lower DNAm in cases vs. controls (PFDR=2.0x10-6). FBXL19 is involved in cell apoptosis, inflammation, and adipogenesis. Overall, we observed more accelerated aging in patients with ESKD, although there was no significant association of EAAs with cardiovascular death. EWAS suggests a potential novel DNAm biomarker for premature cardiovascular mortality in ESKD.
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Affiliation(s)
- Keiichi Sumida
- Division of Nephrology, Department of Medicine, University of Tennessee Health Science Center, Memphis, TN, USA
| | - Khyobeni Mozhui
- Department of Preventive Medicine, University of Tennessee Health Science Center, Memphis, TN, USA
| | - Xiaoyu Liang
- Department of Epidemiology and Biostatistics, Michigan State University College of Human Medicine, East Lansing, MI, USA
| | - Yamini Mallisetty
- Division of Nephrology, Department of Medicine, University of Tennessee Health Science Center, Memphis, TN, USA
| | - Zhongji Han
- Division of Nephrology, Department of Medicine, University of Tennessee Health Science Center, Memphis, TN, USA
| | - Csaba P Kovesdy
- Division of Nephrology, Department of Medicine, University of Tennessee Health Science Center, Memphis, TN, USA
- Department of Preventive Medicine, University of Tennessee Health Science Center, Memphis, TN, USA
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Schmitz LL, Duffie E, Zhao W, Ratliff SM, Ding J, Liu Y, Merkin SS, Smith JA, Seeman T. Associations of Early-Life Adversity With Later-Life Epigenetic Aging Profiles in the Multi-Ethnic Study of Atherosclerosis. Am J Epidemiol 2023; 192:1991-2005. [PMID: 37579321 PMCID: PMC10988110 DOI: 10.1093/aje/kwad172] [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: 09/09/2022] [Revised: 06/28/2023] [Accepted: 08/09/2023] [Indexed: 08/16/2023] Open
Abstract
Epigenetic biomarkers of accelerated aging have been widely used to predict disease risk and may enhance our understanding of biological mechanisms between early-life adversity and disparities in aging. With respect to childhood adversity, most studies have used parental education or childhood disadvantage and/or have not examined the role played by socioemotional or physical abuse and trauma in epigenetic profiles at older ages. This study leveraged data from the Multi-Ethnic Study of Atherosclerosis (MESA) on experiences of threat and deprivation in participants' early lives (i.e., before the age of 18 years) to examine whether exposure to specific dimensions of early-life adversity is associated with epigenetic profiles at older ages that are indicative of accelerated biological aging. The sample included 842 MESA respondents with DNA methylation data collected between 2010 and 2012 who answered questions on early-life adversities in a 2018-2019 telephone follow-up. We found that experiences of deprivation, but not threat, were associated with later-life GrimAge epigenetic aging signatures that were developed to predict mortality risk. Results indicated that smoking behavior partially mediates this association, which suggests that lifestyle behaviors may act as downstream mechanisms between parental deprivation in early life and accelerated epigenetic aging in later life.
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Affiliation(s)
- Lauren L Schmitz
- Correspondence to Dr. Lauren L. Schmitz, Robert M. La Follette School of Public Affairs, University of Wisconsin–Madison, 1225 Observatory Drive, Madison, WI 53706 (e-mail: )
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Meir AY, Wang G, Hong X, Wang X, Liang L. Newborn DNA methylation age differentiates long-term weight trajectory: The Boston Birth Cohort. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.11.02.23297965. [PMID: 37961472 PMCID: PMC10635264 DOI: 10.1101/2023.11.02.23297965] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/15/2023]
Abstract
Background Gestational age (GEAA) estimated by newborn DNA methylation (GAmAge) is associated with maternal prenatal exposures and immediate birth outcomes. However, the association of GAmAge with long-term overweight or obesity (OWO) trajectories is yet to be determined. Methods GAmAge was calculated for 831 children from a US predominantly urban, low-income, multi-ethnic birth cohort using Illumina EPIC array and cord-blood DNA samples. Repeated anthropometric measurements aligned with pediatric primary care schedule allowed us to calculate body-mass-index percentiles (BMIPCT) at specific age and to define long-term weight trajectories from birth to 18 years. Results Four BMIPCT trajectory groups described the long-term weight trajectories: stable (consistent OWO: "early OWO"; constant normal weight: "NW") or non-stable (OWO by year 1 of follow-up: "late OWO"; OWO by year 6 of follow-up: "NW to very late OWO") BMIPCT. were used GAmAge was a predictor of long-term obesity, differentiating between group with consistently high BMIPCT and group with normal BMIPCT patterns and groups with late OWO development. Such differentiation can be observed in the age periods of birth to 1year, 3years, 6years, 10years, and 14years (p<0.05 for all; multivariate models adjusted for GEAA, maternal smoking, delivery method, and child's sex). Birth weight was a mediator for the GAmAge effect on OWO status for specific groups at multiple age periods. Conclusions GAmAge is associated with BMI trajectories from birth to age 18 years, independent of GEAA and birth weight. If further confirmed, GAmAge may serve as an early biomarker for future OWO risk.
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Naue J. Getting the chronological age out of DNA: using insights of age-dependent DNA methylation for forensic DNA applications. Genes Genomics 2023; 45:1239-1261. [PMID: 37253906 PMCID: PMC10504122 DOI: 10.1007/s13258-023-01392-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2023] [Accepted: 04/15/2023] [Indexed: 06/01/2023]
Abstract
BACKGROUND DNA analysis for forensic investigations has a long tradition with important developments and optimizations since its first application. Traditionally, short tandem repeats analysis has been the most powerful method for the identification of individuals. However, in addition, epigenetic changes, i.e., DNA methylation, came into focus of forensic DNA research. Chronological age prediction is one promising application to allow for narrowing the pool of possible individuals who caused a trace, as well as to support the identification of unknown bodies and for age verification of living individuals. OBJECTIVE This review aims to provide an overview of the current knowledge, possibilities, and (current) limitations about DNA methylation-based chronological age prediction with emphasis on forensic application. METHODS The development, implementation and application of age prediction tools requires a deep understanding about the biological background, the analysis methods, the age-dependent DNA methylation markers, as well as the mathematical models for age prediction and their evaluation. Furthermore, additional influences can have an impact. Therefore, the literature was evaluated in respect to these diverse topics. CONCLUSION The numerous research efforts in recent years have led to a rapid change in our understanding of the application of DNA methylation for chronological age prediction, which is now on the way to implementation and validation. Knowledge of the various aspects leads to a better understanding and allows a more informed interpretation of DNAm quantification results, as well as the obtained results by the age prediction tools.
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Affiliation(s)
- Jana Naue
- Institute of Forensic Medicine, Medical Center-University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany.
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73
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Henry JP. [Epigenetics and aging: How is epigenetics linked to aging?]. Med Sci (Paris) 2023; 39:732-737. [PMID: 37943133 DOI: 10.1051/medsci/2023122] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2023] Open
Abstract
Links between aging and epigenetics have been revealed by bio-mathematicians. Methylation of cytosine, which is a characteristic of the epigenome, varies with age on some ADN loci, increasing or decreasing. From an analysis of the methylome, algorithms giving an "epigenetic age" were obtained, strongly correlated with the age. Surprisingly, this approach could be applied consistently to different tissues or unpurified cells. It was successfully applied to tissues of 185 mammalian species. The epigenetic age of embryonic pluripotent stem cells is nearly zero and it decreases to "ground zero" during gastrulation. The average methylation curve as a function of age allows discrimination between slowly or rapidly aging individuals. At the present time, more than 10 different epigenetic clocks have been proposed for medical applications. The localization of aging-sensitive CpG pairs on the genome revealed networks of "co-methylation", involved in different functions such as regulation of morphogenesis or cell differentiation. From these studies, aging appears as a continuous process, with the epigenetic clock starting to "tick" in the embryo.
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Affiliation(s)
- Jean-Pierre Henry
- Ancien directeur de l'institut de biologie physico-chimique, Fondation Edmond de Rothschild, 13 rue Pierre et Marie Curie, 75005 Paris, France
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Napoli C, Coscioni E, Trama U, Strozziero MG, Benincasa G. An evidence-based debate on epigenetics and immunosenescence in COVID-19. CURRENT RESEARCH IN IMMUNOLOGY 2023; 4:100069. [PMID: 37781451 PMCID: PMC10539895 DOI: 10.1016/j.crimmu.2023.100069] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2023] [Revised: 09/01/2023] [Accepted: 09/06/2023] [Indexed: 10/03/2023] Open
Abstract
Immunosenescence contributes to the decline of immune function leading to a reduced ability to respond to severe coronavirus disease 2019 (COVID-19) in elderly patients. Clinical course of COVID-19 is widely heterogeneous and guided by the possible interplay between genetic background and epigenetic-sensitive mechanisms underlying the immunosenescence which could explain, at least in part, the higher percentage of disease severity in elderly individuals. The most convincing evidence regards the hypomethylation of the angiotensin-converting enzyme 2 (ACE2) promoter gene in lungs as well as the citrullination of histone H3 in neutrophils which have been associated with worsening of COVID-19 outcome in elderly patients. In contrast, centenarians who have showed milder symptoms have been associated to a younger "epigenetic age" based on DNA methylation profiles at specific genomic sites (epigenetic clock). Some large prospective studies showed that the acceleration of epigenetic aging as well as the shortening of telomeres were significantly associated with lymphopenia and poor outcome suggesting prognostic biomarkers in elderly COVID-19 patients. Furthermore, randomized clinical trials showed that statins, L-arginine, and resveratrol could mediate anti-inflammatory effects via indirect epigenetic interference and might improve COVID-19 outcome. Here, we discuss the epigenetic-sensitive events which might contribute to increase the risk of severity and mortality in older subjects and possible targeted therapies to counteract immunosenescence.
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Affiliation(s)
- Claudio Napoli
- Department of Advanced Medical and Surgical Sciences (DAMSS), University of Campania “Luigi Vanvitelli”, Naples, Italy
- U.O.C. Division of Clinical Immunology, Immunohematology, Transfusion Medicine and Transplant Immunology, Department of Internal Medicine and Specialistics, University of Campania “Luigi Vanvitelli”, Naples, Italy
| | - Enrico Coscioni
- Division of Cardiac Surgery, AOU San Giovanni di Dio e Ruggid'Aragona, 84131, Salerno, Italy
| | - Ugo Trama
- Regional Pharmaceutical Unit, Campania Region, 80143 Naples, Italy
| | - Maria Grazia Strozziero
- Department of Advanced Medical and Surgical Sciences (DAMSS), University of Campania “Luigi Vanvitelli”, Naples, Italy
- IRCCS Synlab SDN Naples Italy
| | - Giuditta Benincasa
- Department of Advanced Medical and Surgical Sciences (DAMSS), University of Campania “Luigi Vanvitelli”, Naples, Italy
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Yaskolka Meir A, Keller M, Hoffmann A, Rinott E, Tsaban G, Kaplan A, Zelicha H, Hagemann T, Ceglarek U, Isermann B, Shelef I, Blüher M, Stumvoll M, Li J, Haange SB, Engelmann B, Rolle-Kampczyk U, von Bergen M, Hu FB, Stampfer MJ, Kovacs P, Liang L, Shai I. The effect of polyphenols on DNA methylation-assessed biological age attenuation: the DIRECT PLUS randomized controlled trial. BMC Med 2023; 21:364. [PMID: 37743489 PMCID: PMC10519069 DOI: 10.1186/s12916-023-03067-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/18/2023] [Accepted: 07/31/2023] [Indexed: 09/26/2023] Open
Abstract
BACKGROUND Epigenetic age is an estimator of biological age based on DNA methylation; its discrepancy from chronologic age warrants further investigation. We recently reported that greater polyphenol intake benefitted ectopic fats, brain function, and gut microbiota profile, corresponding with elevated urine polyphenols. The effect of polyphenol-rich dietary interventions on biological aging is yet to be determined. METHODS We calculated different biological aging epigenetic clocks of different generations (Horvath2013, Hannum2013, Li2018, Horvath skin and blood2018, PhenoAge2018, PCGrimAge2022), their corresponding age and intrinsic age accelerations, and DunedinPACE, all based on DNA methylation (Illumina EPIC array; pre-specified secondary outcome) for 256 participants with abdominal obesity or dyslipidemia, before and after the 18-month DIRECT PLUS randomized controlled trial. Three interventions were assigned: healthy dietary guidelines, a Mediterranean (MED) diet, and a polyphenol-rich, low-red/processed meat Green-MED diet. Both MED groups consumed 28 g walnuts/day (+ 440 mg/day polyphenols). The Green-MED group consumed green tea (3-4 cups/day) and Mankai (Wolffia globosa strain) 500-ml green shake (+ 800 mg/day polyphenols). Adherence to the Green-MED diet was assessed by questionnaire and urine polyphenols metabolomics (high-performance liquid chromatography quadrupole time of flight). RESULTS Baseline chronological age (51.3 ± 10.6 years) was significantly correlated with all methylation age (mAge) clocks with correlations ranging from 0.83 to 0.95; p < 2.2e - 16 for all. While all interventions did not differ in terms of changes between mAge clocks, greater Green-Med diet adherence was associated with a lower 18-month relative change (i.e., greater mAge attenuation) in Li and Hannum mAge (beta = - 0.41, p = 0.004 and beta = - 0.38, p = 0.03, respectively; multivariate models). Greater Li mAge attenuation (multivariate models adjusted for age, sex, baseline mAge, and weight loss) was mostly affected by higher intake of Mankai (beta = - 1.8; p = 0.061) and green tea (beta = - 1.57; p = 0.0016) and corresponded with elevated urine polyphenols: hydroxytyrosol, tyrosol, and urolithin C (p < 0.05 for all) and urolithin A (p = 0.08), highly common in green plants. Overall, participants undergoing either MED-style diet had ~ 8.9 months favorable difference between the observed and expected Li mAge at the end of the intervention (p = 0.02). CONCLUSIONS This study showed that MED and green-MED diets with increased polyphenols intake, such as green tea and Mankai, are inversely associated with biological aging. To the best of our knowledge, this is the first clinical trial to indicate a potential link between polyphenol intake, urine polyphenols, and biological aging. TRIAL REGISTRATION ClinicalTrials.gov, NCT03020186.
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Affiliation(s)
- Anat Yaskolka Meir
- The Health & Nutrition Innovative International Research Center, Faculty of Health Sciences, Ben-Gurion University of the Negev, P.O. Box 653, 8410501, Be'er Sheva, Israel
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, 655 Huntington Avenue, Boston, MA, 02115, USA
| | - Maria Keller
- Helmholtz Institute for Metabolic, Obesity and Vascular Research (HI-MAG) of the Helmholtz Center Munich at the University of Leipzig and University Hospital Leipzig, 04103, Leipzig, Germany
- Medical Department III - Endocrinology, Nephrology, Rheumatology, University of Leipzig Medical Center, University of Leipzig, Liebigstrasse 21, 04103, Leipzig, Germany
| | - Anne Hoffmann
- Helmholtz Institute for Metabolic, Obesity and Vascular Research (HI-MAG) of the Helmholtz Center Munich at the University of Leipzig and University Hospital Leipzig, 04103, Leipzig, Germany
| | - Ehud Rinott
- The Health & Nutrition Innovative International Research Center, Faculty of Health Sciences, Ben-Gurion University of the Negev, P.O. Box 653, 8410501, Be'er Sheva, Israel
| | - Gal Tsaban
- The Health & Nutrition Innovative International Research Center, Faculty of Health Sciences, Ben-Gurion University of the Negev, P.O. Box 653, 8410501, Be'er Sheva, Israel
- Soroka University Medical Center, 84101, Be'er Sheva, Israel
| | - Alon Kaplan
- The Health & Nutrition Innovative International Research Center, Faculty of Health Sciences, Ben-Gurion University of the Negev, P.O. Box 653, 8410501, Be'er Sheva, Israel
| | - Hila Zelicha
- The Health & Nutrition Innovative International Research Center, Faculty of Health Sciences, Ben-Gurion University of the Negev, P.O. Box 653, 8410501, Be'er Sheva, Israel
| | - Tobias Hagemann
- Helmholtz Institute for Metabolic, Obesity and Vascular Research (HI-MAG) of the Helmholtz Center Munich at the University of Leipzig and University Hospital Leipzig, 04103, Leipzig, Germany
| | - Uta Ceglarek
- Institute of Laboratory Medicine, Clinical Chemistry, and Molecular Diagnostics, University of Leipzig Medical Center, 04103, Leipzig, Germany
| | - Berend Isermann
- Institute of Laboratory Medicine, Clinical Chemistry, and Molecular Diagnostics, University of Leipzig Medical Center, 04103, Leipzig, Germany
| | - Ilan Shelef
- Soroka University Medical Center, 84101, Be'er Sheva, Israel
| | - Matthias Blüher
- Helmholtz Institute for Metabolic, Obesity and Vascular Research (HI-MAG) of the Helmholtz Center Munich at the University of Leipzig and University Hospital Leipzig, 04103, Leipzig, Germany
- Medical Department III - Endocrinology, Nephrology, Rheumatology, University of Leipzig Medical Center, University of Leipzig, Liebigstrasse 21, 04103, Leipzig, Germany
| | - Michael Stumvoll
- Helmholtz Institute for Metabolic, Obesity and Vascular Research (HI-MAG) of the Helmholtz Center Munich at the University of Leipzig and University Hospital Leipzig, 04103, Leipzig, Germany
- Medical Department III - Endocrinology, Nephrology, Rheumatology, University of Leipzig Medical Center, University of Leipzig, Liebigstrasse 21, 04103, Leipzig, Germany
| | - Jun Li
- Division of Preventive Medicine, Department of Medicine, Brigham and Women's Hospital and, Harvard Medical School, Boston, MA, 02115, USA
| | - Sven-Bastian Haange
- Department of Molecular Systems Biology, Helmholtz Centre for Environmental Research GmbH, 04318, Leipzig, Germany
| | - Beatrice Engelmann
- Department of Molecular Systems Biology, Helmholtz Centre for Environmental Research GmbH, 04318, Leipzig, Germany
| | - Ulrike Rolle-Kampczyk
- Department of Molecular Systems Biology, Helmholtz Centre for Environmental Research GmbH, 04318, Leipzig, Germany
| | - Martin von Bergen
- Department of Molecular Systems Biology, Helmholtz Centre for Environmental Research GmbH, 04318, Leipzig, Germany
- Institute of Biochemistry, Faculty of Life Sciences, University of Leipzig, 04103, Leipzig, Germany
| | - Frank B Hu
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, 655 Huntington Avenue, Boston, MA, 02115, USA
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, 02115, USA
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, 02115, USA
| | - Meir J Stampfer
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, 02115, USA
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, 02115, USA
| | - Peter Kovacs
- Medical Department III - Endocrinology, Nephrology, Rheumatology, University of Leipzig Medical Center, University of Leipzig, Liebigstrasse 21, 04103, Leipzig, Germany.
| | - Liming Liang
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, 655 Huntington Avenue, Boston, MA, 02115, USA.
| | - Iris Shai
- The Health & Nutrition Innovative International Research Center, Faculty of Health Sciences, Ben-Gurion University of the Negev, P.O. Box 653, 8410501, Be'er Sheva, Israel.
- Helmholtz Institute for Metabolic, Obesity and Vascular Research (HI-MAG) of the Helmholtz Center Munich at the University of Leipzig and University Hospital Leipzig, 04103, Leipzig, Germany.
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, 02115, USA.
- Faculty of Medicine, Leipzig University, Leipzig, 04103, Germany.
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Varshavsky M, Harari G, Glaser B, Dor Y, Shemer R, Kaplan T. Accurate age prediction from blood using a small set of DNA methylation sites and a cohort-based machine learning algorithm. CELL REPORTS METHODS 2023; 3:100567. [PMID: 37751697 PMCID: PMC10545910 DOI: 10.1016/j.crmeth.2023.100567] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/20/2023] [Revised: 06/18/2023] [Accepted: 08/03/2023] [Indexed: 09/28/2023]
Abstract
Chronological age prediction from DNA methylation sheds light on human aging, health, and lifespan. Current clocks are mostly based on linear models and rely upon hundreds of sites across the genome. Here, we present GP-age, an epigenetic non-linear cohort-based clock for blood, based upon 11,910 methylomes. Using 30 CpG sites alone, GP-age outperforms state-of-the-art models, with a median accuracy of ∼2 years on held-out blood samples, for both array and sequencing-based data. We show that aging-related changes occur at multiple neighboring CpGs, with implications for using fragment-level analysis of sequencing data in aging research. By training three independent clocks, we show enrichment of donors with consistent deviation between predicted and actual age, suggesting individual rates of biological aging. Overall, we provide a compact yet accurate alternative to array-based clocks for blood, with applications in longitudinal aging research, forensic profiling, and monitoring epigenetic processes in transplantation medicine and cancer.
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Affiliation(s)
- Miri Varshavsky
- School of Computer Science and Engineering, The Hebrew University of Jerusalem, Jerusalem, Israel; The Center for Computational Medicine, The Hebrew University of Jerusalem, Jerusalem, Israel
| | - Gil Harari
- School of Computer Science and Engineering, The Hebrew University of Jerusalem, Jerusalem, Israel; Department of Developmental Biology and Cancer Research, Institute for Medical Research Israel-Canada, The Hebrew University-Hadassah Medical School, Jerusalem, Israel
| | - Benjamin Glaser
- Department of Endocrinology and Metabolism, Hadassah Medical Center and Faculty of Medicine, The Hebrew University of Jerusalem, Jerusalem, Israel
| | - Yuval Dor
- Department of Developmental Biology and Cancer Research, Institute for Medical Research Israel-Canada, The Hebrew University-Hadassah Medical School, Jerusalem, Israel; The Center for Computational Medicine, The Hebrew University of Jerusalem, Jerusalem, Israel
| | - Ruth Shemer
- Department of Developmental Biology and Cancer Research, Institute for Medical Research Israel-Canada, The Hebrew University-Hadassah Medical School, Jerusalem, Israel
| | - Tommy Kaplan
- School of Computer Science and Engineering, The Hebrew University of Jerusalem, Jerusalem, Israel; Department of Developmental Biology and Cancer Research, Institute for Medical Research Israel-Canada, The Hebrew University-Hadassah Medical School, Jerusalem, Israel; The Center for Computational Medicine, The Hebrew University of Jerusalem, Jerusalem, Israel.
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Shindo R, Tanifuji T, Okazaki S, Otsuka I, Shirai T, Mouri K, Horai T, Hishimoto A. Accelerated epigenetic aging and decreased natural killer cells based on DNA methylation in patients with untreated major depressive disorder. NPJ AGING 2023; 9:19. [PMID: 37673891 PMCID: PMC10482893 DOI: 10.1038/s41514-023-00117-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/12/2023] [Accepted: 06/29/2023] [Indexed: 09/08/2023]
Abstract
Major depressive disorder (MDD) is known to cause significant disability. Genome-wide DNA methylation (DNAm) profiles can be used to estimate biological aging and as epigenetic clocks. However, information on epigenetic clocks reported in MDD patients is inconsistent. Since antidepressants are likely confounders, we evaluated biological aging using various DNAm-based predictors in patients with MDD who had never received depression medication. A publicly available dataset consisting of whole blood samples from untreated MDD patients (n = 40) and controls (n = 40) was used. We analyzed five epigenetic clocks (HorvathAge, HannumAge, SkinBloodAge, PhenoAge, and GrimAge), DNAm-based telomere length (DNAmTL), and DNAm-based age-related plasma proteins (GrimAge components), as well as DNAm-based white blood cell composition. The results indicate that patients with untreated MDD were significantly associated with epigenetic aging acceleration in HannumAge and GrimAge. Furthermore, a decrease in natural killer cells, based on DNAm, was observed in patients with untreated MDD.
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Affiliation(s)
- Ryota Shindo
- Department of Psychiatry, Kobe University Graduate School of Medicine, Kobe, Japan
| | - Takaki Tanifuji
- Department of Psychiatry, Kobe University Graduate School of Medicine, Kobe, Japan
| | - Satoshi Okazaki
- Department of Psychiatry, Kobe University Graduate School of Medicine, Kobe, Japan.
| | - Ikuo Otsuka
- Department of Psychiatry, Kobe University Graduate School of Medicine, Kobe, Japan
| | - Toshiyuki Shirai
- Department of Psychiatry, Kobe University Graduate School of Medicine, Kobe, Japan
| | - Kentaro Mouri
- Department of Psychiatry, Kobe University Graduate School of Medicine, Kobe, Japan
| | - Tadasu Horai
- Department of Psychiatry, Kobe University Graduate School of Medicine, Kobe, Japan
| | - Akitoyo Hishimoto
- Department of Psychiatry, Kobe University Graduate School of Medicine, Kobe, Japan
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78
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Lu AT, Fei Z, Haghani A, Robeck TR, Zoller JA, Li CZ, Lowe R, Yan Q, Zhang J, Vu H, Ablaeva J, Acosta-Rodriguez VA, Adams DM, Almunia J, Aloysius A, Ardehali R, Arneson A, Baker CS, Banks G, Belov K, Bennett NC, Black P, Blumstein DT, Bors EK, Breeze CE, Brooke RT, Brown JL, Carter GG, Caulton A, Cavin JM, Chakrabarti L, Chatzistamou I, Chen H, Cheng K, Chiavellini P, Choi OW, Clarke SM, Cooper LN, Cossette ML, Day J, DeYoung J, DiRocco S, Dold C, Ehmke EE, Emmons CK, Emmrich S, Erbay E, Erlacher-Reid C, Faulkes CG, Ferguson SH, Finno CJ, Flower JE, Gaillard JM, Garde E, Gerber L, Gladyshev VN, Gorbunova V, Goya RG, Grant MJ, Green CB, Hales EN, Hanson MB, Hart DW, Haulena M, Herrick K, Hogan AN, Hogg CJ, Hore TA, Huang T, Izpisua Belmonte JC, Jasinska AJ, Jones G, Jourdain E, Kashpur O, Katcher H, Katsumata E, Kaza V, Kiaris H, Kobor MS, Kordowitzki P, Koski WR, Krützen M, Kwon SB, Larison B, Lee SG, Lehmann M, Lemaitre JF, Levine AJ, Li C, Li X, Lim AR, Lin DTS, Lindemann DM, Little TJ, Macoretta N, Maddox D, Matkin CO, Mattison JA, McClure M, Mergl J, Meudt JJ, Montano GA, Mozhui K, Munshi-South J, Naderi A, Nagy M, Narayan P, Nathanielsz PW, Nguyen NB, Niehrs C, O'Brien JK, O'Tierney Ginn P, Odom DT, Ophir AG, Osborn S, Ostrander EA, Parsons KM, Paul KC, Pellegrini M, Peters KJ, Pedersen AB, Petersen JL, Pietersen DW, Pinho GM, Plassais J, Poganik JR, Prado NA, Reddy P, Rey B, Ritz BR, Robbins J, Rodriguez M, Russell J, Rydkina E, Sailer LL, Salmon AB, Sanghavi A, Schachtschneider KM, Schmitt D, Schmitt T, Schomacher L, Schook LB, Sears KE, Seifert AW, Seluanov A, Shafer ABA, Shanmuganayagam D, Shindyapina AV, Simmons M, Singh K, Sinha I, Slone J, Snell RG, Soltanmaohammadi E, Spangler ML, Spriggs MC, Staggs L, Stedman N, Steinman KJ, Stewart DT, Sugrue VJ, Szladovits B, Takahashi JS, Takasugi M, Teeling EC, Thompson MJ, Van Bonn B, Vernes SC, Villar D, Vinters HV, Wallingford MC, Wang N, Wayne RK, Wilkinson GS, Williams CK, Williams RW, Yang XW, Yao M, Young BG, Zhang B, Zhang Z, Zhao P, Zhao Y, Zhou W, Zimmermann J, Ernst J, Raj K, Horvath S. Universal DNA methylation age across mammalian tissues. NATURE AGING 2023; 3:1144-1166. [PMID: 37563227 PMCID: PMC10501909 DOI: 10.1038/s43587-023-00462-6] [Citation(s) in RCA: 48] [Impact Index Per Article: 48.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/29/2022] [Accepted: 06/21/2023] [Indexed: 08/12/2023]
Abstract
Aging, often considered a result of random cellular damage, can be accurately estimated using DNA methylation profiles, the foundation of pan-tissue epigenetic clocks. Here, we demonstrate the development of universal pan-mammalian clocks, using 11,754 methylation arrays from our Mammalian Methylation Consortium, which encompass 59 tissue types across 185 mammalian species. These predictive models estimate mammalian tissue age with high accuracy (r > 0.96). Age deviations correlate with human mortality risk, mouse somatotropic axis mutations and caloric restriction. We identified specific cytosines with methylation levels that change with age across numerous species. These sites, highly enriched in polycomb repressive complex 2-binding locations, are near genes implicated in mammalian development, cancer, obesity and longevity. Our findings offer new evidence suggesting that aging is evolutionarily conserved and intertwined with developmental processes across all mammals.
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Affiliation(s)
- A T Lu
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
- Altos Labs, San Diego Institute of Science, San Diego, CA, USA
| | - Z Fei
- Department of Biostatistics, Fielding School of Public Health, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Statistics, University of California, Riverside, Riverside, CA, USA
| | - A Haghani
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
- Altos Labs, San Diego Institute of Science, San Diego, CA, USA
| | - T R Robeck
- Zoological SeaWorld Parks and Entertainment, Orlando, FL, USA
| | - J A Zoller
- Department of Biostatistics, Fielding School of Public Health, University of California, Los Angeles, Los Angeles, CA, USA
| | - C Z Li
- Department of Biostatistics, Fielding School of Public Health, University of California, Los Angeles, Los Angeles, CA, USA
| | - R Lowe
- Altos Labs, Cambridge Institute of Science, Cambridge, UK
| | - Q Yan
- Altos Labs, San Diego Institute of Science, San Diego, CA, USA
| | - J Zhang
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - H Vu
- Bioinformatics Interdepartmental Program, University of California, Los Angeles, CA, USA
- Department of Biological Chemistry, University of California, Los Angeles, Los Angeles, CA, USA
| | - J Ablaeva
- Department of Biology, University of Rochester, Rochester, NY, USA
| | - V A Acosta-Rodriguez
- Department of Neuroscience, Peter O'Donnell Jr. Brain Institute, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - D M Adams
- Department of Biology, University of Maryland, College Park, MD, USA
| | - J Almunia
- Loro Parque Fundacion, Puerto de la Cruz, Spain
| | - A Aloysius
- Department of Biology, University of Kentucky, Lexington, KY, USA
| | - R Ardehali
- Division of Cardiology, Department of Internal Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - A Arneson
- Bioinformatics Interdepartmental Program, University of California, Los Angeles, CA, USA
- Department of Biological Chemistry, University of California, Los Angeles, Los Angeles, CA, USA
| | - C S Baker
- Marine Mammal Institute, Oregon State University, Newport, OR, USA
| | - G Banks
- School of Science and Technology, Clifton Campus, Nottingham Trent University, Nottingham, UK
| | - K Belov
- School of Life and Environmental Sciences, the University of Sydney, Sydney, New South Wales, Australia
| | - N C Bennett
- Department of Zoology and Entomology, University of Pretoria, Hatfield, South Africa
| | - P Black
- Busch Gardens Tampa, Tampa, FL, USA
| | - D T Blumstein
- Department of Ecology and Evolutionary Biology, University of California, Los Angeles, Los Angeles, CA, USA
- Rocky Mountain Biological Laboratory, Crested Butte, CO, USA
| | - E K Bors
- Marine Mammal Institute, Oregon State University, Newport, OR, USA
| | - C E Breeze
- Altius Institute for Biomedical Sciences, Seattle, WA, USA
| | - R T Brooke
- Epigenetic Clock Development Foundation, Los Angeles, CA, USA
| | - J L Brown
- Center for Species Survival, Smithsonian Conservation Biology Institute, Front Royal, VA, USA
| | - G G Carter
- Department of Evolution, Ecology and Organismal Biology, The Ohio State University, Columbus, OH, USA
| | - A Caulton
- AgResearch, Invermay Agricultural Centre, Mosgiel, New Zealand
- Department of Biochemistry, University of Otago, Dunedin, New Zealand
| | - J M Cavin
- Gulf World, Dolphin Company, Panama City Beach, FL, USA
| | - L Chakrabarti
- School of Veterinary Medicine and Science, University of Nottingham, Nottingham, UK
| | - I Chatzistamou
- Department of Pathology, Microbiology and Immunology, School of Medicine, University of South Carolina, Columbia, SC, USA
| | - H Chen
- Department of Pharmacology, Addiction Science and Toxicology, the University of Tennessee Health Science Center, Memphis, TN, USA
| | - K Cheng
- Medical Informatics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - P Chiavellini
- Biochemistry Research Institute of La Plata, Histology and Pathology, School of Medicine, University of La Plata, La Plata, Argentina
| | - O W Choi
- Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - S M Clarke
- AgResearch, Invermay Agricultural Centre, Mosgiel, New Zealand
| | - L N Cooper
- Department of Anatomy and Neurobiology, Northeast Ohio Medical University, Rootstown, OH, USA
| | - M L Cossette
- Department of Environmental and Life Sciences, Trent University, Peterborough, Ontario, Canada
| | - J Day
- Taronga Institute of Science and Learning, Taronga Conservation Society Australia, Mosman, New South Wales, Australia
| | - J DeYoung
- Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - S DiRocco
- SeaWorld of Florida, Orlando, FL, USA
| | - C Dold
- Zoological Operations, SeaWorld Parks and Entertainment, Orlando, FL, USA
| | | | - C K Emmons
- Conservation Biology Division, Northwest Fisheries Science Center, National Marine Fisheries Service, National Oceanic and Atmospheric Administration, Seattle, WA, USA
| | - S Emmrich
- Departments of Biology and Medicine, University of Rochester, Rochester, NY, USA
| | - E Erbay
- Altos Labs, San Francisco, CA, USA
| | - C Erlacher-Reid
- SeaWorld of Florida, Orlando, FL, USA
- SeaWorld Orlando, Orlando, FL, USA
| | - C G Faulkes
- School of Biological and Behavioural Sciences, Queen Mary University of London, London, UK
| | - S H Ferguson
- Fisheries and Oceans Canada, Freshwater Institute, Winnipeg, Manitoba, Canada
- Department of Biological Sciences, University of Manitoba, Winnipeg, Manitoba, Canada
| | - C J Finno
- Department of Population Health and Reproduction, University of California, Davis School of Veterinary Medicine, Davis, CA, USA
| | | | - J M Gaillard
- Universite de Lyon, Universite Lyon 1, CNRS, Laboratoire de Biometrie et Biologie Evolutive, Villeurbanne, France
| | - E Garde
- Greenland Institute of Natural Resources, Nuuk, Greenland
| | - L Gerber
- Evolution and Ecology Research Centre, School of Biological, Earth and Environmental Sciences, UNSW Sydney, Sydney, New South Wales, Australia
| | - V N Gladyshev
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - V Gorbunova
- Departments of Biology and Medicine, University of Rochester, Rochester, NY, USA
| | - R G Goya
- Biochemistry Research Institute of La Plata, Histology and Pathology, School of Medicine, University of La Plata, La Plata, Argentina
| | - M J Grant
- Applied Translational Genetics Group, School of Biological Sciences, Centre for Brain Research, the University of Auckland, Auckland, New Zealand
| | - C B Green
- Department of Neuroscience, Peter O'Donnell Jr. Brain Institute, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - E N Hales
- Department of Population Health and Reproduction, University of California, Davis School of Veterinary Medicine, Davis, CA, USA
| | - M B Hanson
- Conservation Biology Division, Northwest Fisheries Science Center, National Marine Fisheries Service, National Oceanic and Atmospheric Administration, Seattle, WA, USA
| | - D W Hart
- Department of Zoology and Entomology, University of Pretoria, Hatfield, South Africa
| | - M Haulena
- Vancouver Aquarium, Vancouver, British Columbia, Canada
| | - K Herrick
- SeaWorld of California, San Diego, CA, USA
| | - A N Hogan
- Cancer Genetics and Comparative Genomics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - C J Hogg
- School of Life and Environmental Sciences, the University of Sydney, Sydney, New South Wales, Australia
| | - T A Hore
- Department of Anatomy, University of Otago, Dunedin, New Zealand
| | - T Huang
- Division of Human Genetics, Department of Pediatrics, University at Buffalo, Buffalo, NY, USA
- Division of Genetics and Metabolism, Oishei Children's Hospital, Buffalo, NY, USA
| | | | - A J Jasinska
- Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - G Jones
- School of Biological Sciences, University of Bristol, Bristol, UK
| | | | - O Kashpur
- Mother Infant Research Institute, Tufts Medical Center, Boston, MA, USA
| | - H Katcher
- Yuvan Research, Mountain View, CA, USA
| | | | - V Kaza
- Peromyscus Genetic Stock Center, University of South Carolina, Columbia, SC, USA
| | - H Kiaris
- Peromyscus Genetic Stock Center, University of South Carolina, Columbia, SC, USA
- Department of Drug Discovery and Biomedical Sciences, College of Pharmacy, University of South Carolina, Columbia, SC, USA
| | - M S Kobor
- Edwin S.H. Leong Healthy Aging Program, Centre for Molecular Medicine and Therapeutics, University of British Columbia, Vancouver, British Columbia, Canada
| | - P Kordowitzki
- Institute of Animal Reproduction and Food Research of the Polish Academy of Sciences, Olsztyn, Poland
- Institute for Veterinary Medicine, Nicolaus Copernicus University, Torun, Poland
| | - W R Koski
- LGL Limited, King City, Ontario, Canada
| | - M Krützen
- Evolutionary Genetics Group, Department of Evolutionary Anthropology, University of Zurich, Zurich, Switzerland
| | - S B Kwon
- Bioinformatics Interdepartmental Program, University of California, Los Angeles, CA, USA
- Department of Biological Chemistry, University of California, Los Angeles, Los Angeles, CA, USA
| | - B Larison
- Department of Ecology and Evolutionary Biology, UCLA, Los Angeles, CA, USA
- Center for Tropical Research, Institute for the Environment and Sustainability, UCLA, Los Angeles, CA, USA
| | - S G Lee
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - M Lehmann
- Biochemistry Research Institute of La Plata, Histology and Pathology, School of Medicine, University of La Plata, La Plata, Argentina
| | - J F Lemaitre
- Universite de Lyon, Universite Lyon 1, CNRS, Laboratoire de Biometrie et Biologie Evolutive, Villeurbanne, France
| | - A J Levine
- Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - C Li
- Texas Pregnancy and Life-course Health Center, Southwest National Primate Research Center, San Antonio, TX, USA
- Department of Animal Science, College of Agriculture and Natural Resources, Laramie, WY, USA
| | - X Li
- Technology Center for Genomics and Bioinformatics, Department of Pathology and Laboratory Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - A R Lim
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - D T S Lin
- Centre for Molecular Medicine and Therapeutics, BC Children's Hospital Research Institute, University of British Columbia, Vancouver, British Columbia, Canada
| | | | - T J Little
- Institute of Ecology and Evolution, School of Biological Sciences, University of Edinburgh, Edinburgh, UK
| | - N Macoretta
- Departments of Biology and Medicine, University of Rochester, Rochester, NY, USA
| | - D Maddox
- White Oak Conservation, Yulee, FL, USA
| | - C O Matkin
- North Gulf Oceanic Society, Homer, AK, USA
| | - J A Mattison
- Translational Gerontology Branch, National Institute on Aging Intramural Research Program, National Institutes of Health, Baltimore, MD, USA
| | | | - J Mergl
- Marineland of Canada, Niagara Falls, Ontario, Canada
| | - J J Meudt
- Biomedical and Genomic Research Group, Department of Animal and Dairy Sciences, University of Wisconsin-Madison, Madison, WI, USA
| | - G A Montano
- Zoological Operations, SeaWorld Parks and Entertainment, Orlando, FL, USA
| | - K Mozhui
- Department of Preventive Medicine, University of Tennessee Health Science Center, College of Medicine, Memphis, TN, USA
- Department of Genetics, Genomics and Informatics, University of Tennessee Health Science Center, College of Medicine, Memphis, TN, USA
| | - J Munshi-South
- Louis Calder Center-Biological Field Station, Department of Biological Sciences, Fordham University, Armonk, NY, USA
| | - A Naderi
- Department of Drug Discovery and Biomedical Sciences, College of Pharmacy, University of South Carolina, Columbia, SC, USA
| | - M Nagy
- Museum fur Naturkunde, Leibniz Institute for Evolution and Biodiversity Science, Berlin, Germany
| | - P Narayan
- Applied Translational Genetics Group, School of Biological Sciences, Centre for Brain Research, the University of Auckland, Auckland, New Zealand
| | - P W Nathanielsz
- Texas Pregnancy and Life-course Health Center, Southwest National Primate Research Center, San Antonio, TX, USA
- Department of Animal Science, College of Agriculture and Natural Resources, Laramie, WY, USA
| | - N B Nguyen
- Division of Cardiology, Department of Internal Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - C Niehrs
- Institute of Molecular Biology, Mainz, Germany
- Division of Molecular Embryology, DKFZ-ZMBH Alliance, Heidelberg, Germany
| | - J K O'Brien
- Taronga Institute of Science and Learning, Taronga Conservation Society Australia, Mosman, New South Wales, Australia
| | - P O'Tierney Ginn
- Mother Infant Research Institute, Tufts Medical Center, Boston, MA, USA
- Department of Obstetrics and Gynecology, Tufts University School of Medicine, Boston, MA, USA
| | - D T Odom
- Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge, UK
- Division of Regulatory Genomics and Cancer Evolution, Deutsches Krebsforschungszentrum, Heidelberg, Germany
| | - A G Ophir
- Department of Psychology, Cornell University, Ithaca, NY, USA
| | - S Osborn
- SeaWorld of Texas, San Antonio, TX, USA
| | - E A Ostrander
- Cancer Genetics and Comparative Genomics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - K M Parsons
- Conservation Biology Division, Northwest Fisheries Science Center, National Marine Fisheries Service, National Oceanic and Atmospheric Administration, Seattle, WA, USA
| | - K C Paul
- Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - M Pellegrini
- Department of Molecular Cell and Developmental Biology, University of California, Los Angeles, Los Angeles, CA, USA
| | - K J Peters
- Evolutionary Genetics Group, Department of Evolutionary Anthropology, University of Zurich, Zurich, Switzerland
- School of Earth, Atmospheric and Life Sciences, University of Wollongong, Wollongong, Australia
| | - A B Pedersen
- Institute of Evolutionary Biology, School of Biological Sciences, University of Edinburgh, Edinburgh, UK
| | - J L Petersen
- Department of Animal Science, University of Nebraska, Lincoln, NE, USA
| | - D W Pietersen
- Mammal Research Institute, Department of Zoology and Entomology, University of Pretoria, Hatfield, South Africa
| | - G M Pinho
- Department of Ecology and Evolutionary Biology, UCLA, Los Angeles, CA, USA
| | - J Plassais
- Cancer Genetics and Comparative Genomics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - J R Poganik
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - N A Prado
- Department of Biology, College of Arts and Science, Adelphi University, Garden City, NY, USA
| | - P Reddy
- Altos Labs, San Diego Institute of Science, San Diego, CA, USA
- Salk Institute for Biological Studies, La Jolla, CA, USA
| | - B Rey
- Universite de Lyon, Universite Lyon 1, CNRS, Laboratoire de Biometrie et Biologie Evolutive, Villeurbanne, France
| | - B R Ritz
- Department of Epidemiology, UCLA Fielding School of Public Health, Los Angeles, CA, USA
- Department of Environmental Health Sciences, UCLA Fielding School of Public Health, Los Angeles, CA, USA
- Department of Neurology, UCLA David Geffen School of Medicine, Los Angeles, CA, USA
| | - J Robbins
- Center for Coastal Studies, Provincetown, MA, USA
| | | | - J Russell
- SeaWorld of California, San Diego, CA, USA
| | - E Rydkina
- Departments of Biology and Medicine, University of Rochester, Rochester, NY, USA
| | - L L Sailer
- Department of Psychology, Cornell University, Ithaca, NY, USA
| | - A B Salmon
- The Sam and Ann Barshop Institute for Longevity and Aging Studies and Department of Molecular Medicine, UT Health San Antonio and the Geriatric Research Education and Clinical Center, South Texas Veterans Healthcare System, San Antonio, TX, USA
| | | | - K M Schachtschneider
- Department of Radiology, University of Illinois at Chicago, Chicago, IL, USA
- Department of Biochemistry and Molecular Genetics, University of Illinois at Chicago, Chicago, IL, USA
- National Center for Supercomputing Applications, University of Illinois at Urbana-Champaign, Urbana, IL, USA
| | - D Schmitt
- College of Agriculture, Missouri State University, Springfield, MO, USA
| | - T Schmitt
- SeaWorld of California, San Diego, CA, USA
| | | | - L B Schook
- Department of Radiology, University of Illinois at Chicago, Chicago, IL, USA
- Department of Animal Sciences, University of Illinois at Urbana-Champaign, Champaign, IL, USA
| | - K E Sears
- Department of Ecology and Evolutionary Biology, UCLA, Los Angeles, CA, USA
- Department of Molecular Cell and Developmental Biology, University of California, Los Angeles, Los Angeles, CA, USA
| | - A W Seifert
- Department of Biology, University of Kentucky, Lexington, KY, USA
| | - A Seluanov
- Departments of Biology and Medicine, University of Rochester, Rochester, NY, USA
| | - A B A Shafer
- Department of Forensic Science, Environmental and Life Sciences, Trent University, Peterborough, Ontario, Canada
| | - D Shanmuganayagam
- Biomedical and Genomic Research Group, Department of Animal and Dairy Sciences, University of Wisconsin-Madison, Madison, WI, USA
- Department of Surgery, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
| | - A V Shindyapina
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | | | - K Singh
- Shobhaben Pratapbhai Patel School of Pharmacy and Technology Management, SVKM'S NMIMS University, Mumbai, India
| | - I Sinha
- Department of Ecology and Evolutionary Biology, UCLA, Los Angeles, CA, USA
| | - J Slone
- Division of Human Genetics, Department of Pediatrics, University at Buffalo, Buffalo, NY, USA
| | - R G Snell
- Applied Translational Genetics Group, School of Biological Sciences, Centre for Brain Research, the University of Auckland, Auckland, New Zealand
| | - E Soltanmaohammadi
- Department of Drug Discovery and Biomedical Sciences, College of Pharmacy, University of South Carolina, Columbia, SC, USA
| | - M L Spangler
- Department of Animal Science, University of Nebraska, Lincoln, NE, USA
| | | | - L Staggs
- SeaWorld of Florida, Orlando, FL, USA
| | | | - K J Steinman
- Species Preservation Laboratory, SeaWorld San Diego, San Diego, CA, USA
| | - D T Stewart
- Biology Department, Acadia University, Wolfville, Nova Scotia, Canada
| | - V J Sugrue
- Department of Anatomy, University of Otago, Dunedin, New Zealand
| | - B Szladovits
- Department of Pathobiology and Population Sciences, Royal Veterinary College, Hatfield, UK
| | - J S Takahashi
- Department of Neuroscience, Peter O'Donnell Jr. Brain Institute, University of Texas Southwestern Medical Center, Dallas, TX, USA
- Howard Hughes Medical Institute, Department of Neuroscience, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - M Takasugi
- Departments of Biology and Medicine, University of Rochester, Rochester, NY, USA
| | - E C Teeling
- School of Biology and Environmental Science, University College Dublin, Dublin, Ireland
| | - M J Thompson
- Department of Molecular Cell and Developmental Biology, University of California, Los Angeles, Los Angeles, CA, USA
| | - B Van Bonn
- John G. Shedd Aquarium, Chicago, IL, USA
| | - S C Vernes
- School of Biology, the University of St Andrews, Fife, UK
- Neurogenetics of Vocal Communication Group, Max Planck Institute for Psycholinguistics, Nijmegen, the Netherlands
| | - D Villar
- Blizard Institute, Faculty of Medicine and Dentistry, Queen Mary University of London, London, UK
| | - H V Vinters
- Department of Pathology and Laboratory Medicine, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA
| | - M C Wallingford
- Mother Infant Research Institute, Tufts Medical Center, Boston, MA, USA
- Division of Obstetrics and Gynecology, Tufts University School of Medicine, Boston, MA, USA
| | - N Wang
- Center for Neurobehavioral Genetics, Jane and Terry Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA
| | - R K Wayne
- Department of Ecology and Evolutionary Biology, UCLA, Los Angeles, CA, USA
| | - G S Wilkinson
- Department of Biology, University of Maryland, College Park, MD, USA
| | - C K Williams
- Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - R W Williams
- Department of Genetics, Genomics and Informatics, University of Tennessee Health Science Center, College of Medicine, Memphis, TN, USA
| | - X W Yang
- Center for Neurobehavioral Genetics, Jane and Terry Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA
| | - M Yao
- Department of Biostatistics, Fielding School of Public Health, University of California, Los Angeles, Los Angeles, CA, USA
| | - B G Young
- Fisheries and Oceans Canada, Winnipeg, Manitoba, Canada
| | - B Zhang
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Z Zhang
- Departments of Biology and Medicine, University of Rochester, Rochester, NY, USA
| | - P Zhao
- Division of Cardiology, Department of Internal Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
- Eli and Edythe Broad Center of Regenerative Medicine and Stem Cell Research, University of California, Los Angeles, CA, USA
| | - Y Zhao
- Departments of Biology and Medicine, University of Rochester, Rochester, NY, USA
| | - W Zhou
- Center for Computational and Genomic Medicine, Children's Hospital of Philadelphia, Philadelphia, PA, USA
- Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - J Zimmermann
- Department of Mathematics and Technology, University of Applied Sciences Koblenz, Koblenz, Germany
| | - J Ernst
- Bioinformatics Interdepartmental Program, University of California, Los Angeles, CA, USA
- Department of Biological Chemistry, University of California, Los Angeles, Los Angeles, CA, USA
| | - K Raj
- Altos Labs, Cambridge Institute of Science, Cambridge, UK
| | - S Horvath
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA.
- Altos Labs, San Diego Institute of Science, San Diego, CA, USA.
- Department of Biostatistics, Fielding School of Public Health, University of California, Los Angeles, Los Angeles, CA, USA.
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Jones JD, Martinez S, Gonzalez I, Odom GJ, Comer SD. No evidence of accelerated epigenetic aging among black heroin users: A case vs control analysis. ADDICTION NEUROSCIENCE 2023; 7:100096. [PMID: 37388854 PMCID: PMC10305791 DOI: 10.1016/j.addicn.2023.100096] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/01/2023]
Abstract
This study sought to assess the association between illicit opioid use and accelerated epigenetic aging (A.K.A. DNAm Age) among people of African ancestry who use heroin. DNA was obtained from participants with opioid use disorder (OUD) who confirmed heroin as their primary drug of choice. Clinical inventories of drug use included: the Addiction Severity Index (ASI) Drug-Composite Score (range: 0-1), and Drug Abuse Screening Test (DAST-10; range: 0-10). A control group of participants of African ancestry who did not use heroin was recruited and matched to heroin users on sex, age, socioeconomic level, and smoking status. Methylation data were assessed in an epigenetic clock to determined and compare Epigenetic Age to Chronological Age (i.e., age acceleration or deceleration). Data were obtained from 32 controls [mean age 36.3 (±7.5) years] and 64 heroin users [mean age 48.1 (±6.6) years]. The experimental group used heroin for an average of 18.1 (±10.6) years, reported use of 6.4 (±6.1) bags of heroin/day, with a mean DAST-10 score of 7.0 (±2.6) and ASI Score of 0.33 (±0.19). Mean age acceleration for heroin users [+0.56 (± 9.5) years] was significantly (p< 0.05) lower than controls [+5.19 (± 9.1) years]. This study did not find evidence that heroin use causes epigenetic age acceleration.
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Affiliation(s)
- Jermaine D. Jones
- Department of Psychiatry, Division on Substance Use Disorders, New York State Psychiatric Institute, and Columbia University Irving Medical Center, 1051 Riverside Drive, New York, NY 10032, USA
| | - Suky Martinez
- Department of Psychiatry, Division on Substance Use Disorders, New York State Psychiatric Institute, and Columbia University Irving Medical Center, 1051 Riverside Drive, New York, NY 10032, USA
| | - Ingrid Gonzalez
- Department of Biostatistics, Robert Stempel College of Public Health, Florida International University, 1200 SW 8th St, Miami, FL 33174, USA
| | - Gabriel J. Odom
- Department of Biostatistics, Robert Stempel College of Public Health, Florida International University, 1200 SW 8th St, Miami, FL 33174, USA
| | - Sandra D. Comer
- Department of Psychiatry, Division on Substance Use Disorders, New York State Psychiatric Institute, and Columbia University Irving Medical Center, 1051 Riverside Drive, New York, NY 10032, USA
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Zhang ZZ, Moeckel C, Mustafa M, Pham H, Olson AE, Mehta D, Dorn LD, Engeland CG, Shenk CE. The association of epigenetic age acceleration and depressive and anxiety symptom severity among children recently exposed to substantiated maltreatment. J Psychiatr Res 2023; 165:7-13. [PMID: 37441927 PMCID: PMC10529086 DOI: 10.1016/j.jpsychires.2023.07.007] [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] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/05/2023] [Revised: 07/06/2023] [Accepted: 07/07/2023] [Indexed: 07/15/2023]
Abstract
Child maltreatment is a major risk factor for both depressive and anxiety disorders. However, many children exposed to maltreatment never meet diagnostic threshold for either disorder while experiencing only transitory symptoms post-exposure. Recent research suggests DNA methylation adds predictive value in explaining variation in the onset and course of multiple psychiatric disorders following exposure to child maltreatment. Epigenetic age acceleration (EAA), the biological aging of cells not attributable to chronological aging, is a stress-sensitive biomarker capturing genome-wide variation in DNA methylation with the potential to identify children who have been maltreated at greatest risk for depressive and anxiety disorders. The current study examined two EAA clocks appropriate for the pediatric population, the Horvath and Pediatric Buccal Epigenetic (PedBE) clocks, and their associations with depressive and anxiety symptom severity following child maltreatment. Children (N = 71) 8-15 years of age, all of whom were exposed to substantiated child maltreatment in the 12 months prior to study entry, were enrolled. Risk modeling adjusting for several confounders revealed that EAA estimated via the Horvath clock was significantly associated with more severe depressive and anxiety symptoms. The PedBE clock was not associated with either depressive or anxiety symptom severity. Sensitivity analyses demonstrated that EAA via the Horvath clock robustly predicted depressive and anxiety symptom severity across multiple modeling scenarios. Our findings advance existing research suggesting EAA, as estimated with the Horvath clock, may be a promising biomarker for identifying children at greatest risk for more severe depressive and anxiety symptoms following maltreatment.
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Affiliation(s)
- Zhenyu Z Zhang
- Department of Psychology, The Pennsylvania State University, University Park, PA, USA.
| | - Camille Moeckel
- The Pennsylvania State University College of Medicine, Hershey, PA, USA.
| | - Manal Mustafa
- The Pennsylvania State University College of Medicine, Hershey, PA, USA.
| | - Hung Pham
- The Child Study Center, Yale University, New Haven, CT, USA.
| | - Anneke E Olson
- Department of Human Development and Family Studies, The Pennsylvania State University, University Park, PA, USA.
| | - Divya Mehta
- Centre for Genomics and Personalised Health, Queensland University of Technology, Brisbane, Queensland, Australia; School of Biomedical Sciences, Queensland University of Technology, Brisbane, Queensland, Australia.
| | - Lorah D Dorn
- Ross and Carol Nese College of Nursing, The Pennsylvania State University, University Park, PA, USA.
| | - Christopher G Engeland
- Ross and Carol Nese College of Nursing, The Pennsylvania State University, University Park, PA, USA; Department of Biobehavioral Health, The Pennsylvania State University, University Park, PA, USA.
| | - Chad E Shenk
- The Pennsylvania State University College of Medicine, Hershey, PA, USA; Department of Human Development and Family Studies, The Pennsylvania State University, University Park, PA, USA.
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Liu R, Zhao E, Yu H, Yuan C, Abbas MN, Cui H. Methylation across the central dogma in health and diseases: new therapeutic strategies. Signal Transduct Target Ther 2023; 8:310. [PMID: 37620312 PMCID: PMC10449936 DOI: 10.1038/s41392-023-01528-y] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2023] [Revised: 05/23/2023] [Accepted: 05/25/2023] [Indexed: 08/26/2023] Open
Abstract
The proper transfer of genetic information from DNA to RNA to protein is essential for cell-fate control, development, and health. Methylation of DNA, RNAs, histones, and non-histone proteins is a reversible post-synthesis modification that finetunes gene expression and function in diverse physiological processes. Aberrant methylation caused by genetic mutations or environmental stimuli promotes various diseases and accelerates aging, necessitating the development of therapies to correct the disease-driver methylation imbalance. In this Review, we summarize the operating system of methylation across the central dogma, which includes writers, erasers, readers, and reader-independent outputs. We then discuss how dysregulation of the system contributes to neurological disorders, cancer, and aging. Current small-molecule compounds that target the modifiers show modest success in certain cancers. The methylome-wide action and lack of specificity lead to undesirable biological effects and cytotoxicity, limiting their therapeutic application, especially for diseases with a monogenic cause or different directions of methylation changes. Emerging tools capable of site-specific methylation manipulation hold great promise to solve this dilemma. With the refinement of delivery vehicles, these new tools are well positioned to advance the basic research and clinical translation of the methylation field.
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Affiliation(s)
- Ruochen Liu
- State Key Laboratory of Resource Insects, Medical Research Institute, Southwest University, Chongqing, 400715, China
- Jinfeng Laboratory, Chongqing, 401329, China
- Chongqing Engineering and Technology Research Center for Silk Biomaterials and Regenerative Medicine, Chongqing, 400716, China
- Engineering Research Center for Cancer Biomedical and Translational Medicine, Southwest University, Chongqing, 400715, China
| | - Erhu Zhao
- State Key Laboratory of Resource Insects, Medical Research Institute, Southwest University, Chongqing, 400715, China
- Jinfeng Laboratory, Chongqing, 401329, China
- Chongqing Engineering and Technology Research Center for Silk Biomaterials and Regenerative Medicine, Chongqing, 400716, China
- Engineering Research Center for Cancer Biomedical and Translational Medicine, Southwest University, Chongqing, 400715, China
| | - Huijuan Yu
- State Key Laboratory of Resource Insects, Medical Research Institute, Southwest University, Chongqing, 400715, China
| | - Chaoyu Yuan
- State Key Laboratory of Resource Insects, Medical Research Institute, Southwest University, Chongqing, 400715, China
| | - Muhammad Nadeem Abbas
- State Key Laboratory of Resource Insects, Medical Research Institute, Southwest University, Chongqing, 400715, China
- Jinfeng Laboratory, Chongqing, 401329, China
- Chongqing Engineering and Technology Research Center for Silk Biomaterials and Regenerative Medicine, Chongqing, 400716, China
- Engineering Research Center for Cancer Biomedical and Translational Medicine, Southwest University, Chongqing, 400715, China
| | - Hongjuan Cui
- State Key Laboratory of Resource Insects, Medical Research Institute, Southwest University, Chongqing, 400715, China.
- Jinfeng Laboratory, Chongqing, 401329, China.
- Chongqing Engineering and Technology Research Center for Silk Biomaterials and Regenerative Medicine, Chongqing, 400716, China.
- Engineering Research Center for Cancer Biomedical and Translational Medicine, Southwest University, Chongqing, 400715, China.
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Roy R, Kuo PL, Candia J, Sarantopoulou D, Ubaida-Mohien C, Hernandez D, Kaileh M, Arepalli S, Singh A, Bektas A, Kim J, Moore AZ, Tanaka T, McKelvey J, Zukley L, Nguyen C, Wallace T, Dunn C, Wood W, Piao Y, Coletta C, De S, Sen J, Weng NP, Sen R, Ferrucci L. Epigenetic signature of human immune aging in the GESTALT study. eLife 2023; 12:e86136. [PMID: 37589453 PMCID: PMC10506794 DOI: 10.7554/elife.86136] [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: 01/12/2023] [Accepted: 08/16/2023] [Indexed: 08/18/2023] Open
Abstract
Age-associated DNA methylation in blood cells convey information on health status. However, the mechanisms that drive these changes in circulating cells and their relationships to gene regulation are unknown. We identified age-associated DNA methylation sites in six purified blood-borne immune cell types (naive B, naive CD4+ and CD8+ T cells, granulocytes, monocytes, and NK cells) collected from healthy individuals interspersed over a wide age range. Of the thousands of age-associated sites, only 350 sites were differentially methylated in the same direction in all cell types and validated in an independent longitudinal cohort. Genes close to age-associated hypomethylated sites were enriched for collagen biosynthesis and complement cascade pathways, while genes close to hypermethylated sites mapped to neuronal pathways. In silico analyses showed that in most cell types, the age-associated hypo- and hypermethylated sites were enriched for ARNT (HIF1β) and REST transcription factor (TF) motifs, respectively, which are both master regulators of hypoxia response. To conclude, despite spatial heterogeneity, there is a commonality in the putative regulatory role with respect to TF motifs and histone modifications at and around these sites. These features suggest that DNA methylation changes in healthy aging may be adaptive responses to fluctuations of oxygen availability.
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Affiliation(s)
- Roshni Roy
- Laboratory of Molecular Biology and Immunology, National Institute on AgingBaltimoreUnited States
| | - Pei-Lun Kuo
- Translational Gerontology Branch, National Institute on AgingBaltimoreUnited States
| | - Julián Candia
- Translational Gerontology Branch, National Institute on AgingBaltimoreUnited States
| | - Dimitra Sarantopoulou
- Laboratory of Molecular Biology and Immunology, National Institute on AgingBaltimoreUnited States
| | | | - Dena Hernandez
- Laboratory of Neurogenetics, National Institute on AgingBethesdaUnited States
| | - Mary Kaileh
- Laboratory of Molecular Biology and Immunology, National Institute on AgingBaltimoreUnited States
| | - Sampath Arepalli
- Laboratory of Neurogenetics, National Institute on AgingBethesdaUnited States
| | - Amit Singh
- Laboratory of Molecular Biology and Immunology, National Institute on AgingBaltimoreUnited States
| | - Arsun Bektas
- Translational Gerontology Branch, National Institute on AgingBaltimoreUnited States
| | - Jaekwan Kim
- Laboratory of Molecular Biology and Immunology, National Institute on AgingBaltimoreUnited States
| | - Ann Z Moore
- Translational Gerontology Branch, National Institute on AgingBaltimoreUnited States
| | - Toshiko Tanaka
- Translational Gerontology Branch, National Institute on AgingBaltimoreUnited States
| | - Julia McKelvey
- Clinical Research Core, National Institute on AgingBaltimoreUnited States
| | - Linda Zukley
- Clinical Research Core, National Institute on AgingBaltimoreUnited States
| | - Cuong Nguyen
- Flow Cytometry Unit, National Institute on AgingBaltimoreUnited States
| | - Tonya Wallace
- Flow Cytometry Unit, National Institute on AgingBaltimoreUnited States
| | - Christopher Dunn
- Flow Cytometry Unit, National Institute on AgingBaltimoreUnited States
| | - William Wood
- Laboratory of Genetics and Genomics, National Institute on AgingBaltimoreUnited States
| | - Yulan Piao
- Laboratory of Genetics and Genomics, National Institute on AgingBaltimoreUnited States
| | - Christopher Coletta
- Laboratory of Genetics and Genomics, National Institute on AgingBaltimoreUnited States
| | - Supriyo De
- Laboratory of Genetics and Genomics, National Institute on AgingBaltimoreUnited States
| | - Jyoti Sen
- Laboratory of Clinical Investigation, National Institute on AgingBaltimoreUnited States
| | - Nan-ping Weng
- Laboratory of Molecular Biology and Immunology, National Institute on AgingBaltimoreUnited States
| | - Ranjan Sen
- Laboratory of Molecular Biology and Immunology, National Institute on AgingBaltimoreUnited States
| | - Luigi Ferrucci
- Translational Gerontology Branch, National Institute on AgingBaltimoreUnited States
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83
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Niemiec SS, Kechris K, Pattee J, Yang IV, Adgate JL, Calafat AM, Dabelea D, Starling AP. Prenatal exposures to per- and polyfluoroalkyl substances and epigenetic aging in umbilical cord blood: The Healthy Start study. ENVIRONMENTAL RESEARCH 2023; 231:116215. [PMID: 37224946 PMCID: PMC10330919 DOI: 10.1016/j.envres.2023.116215] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/06/2023] [Revised: 05/19/2023] [Accepted: 05/20/2023] [Indexed: 05/26/2023]
Abstract
BACKGROUND Per- and polyfluoroalkyl substances (PFAS) are ubiquitous, environmentally persistent chemicals, and prenatal exposures have been associated with adverse child health outcomes. Prenatal PFAS exposure may lead to epigenetic age acceleration (EAA), defined as the discrepancy between an individual's chronologic and epigenetic or biological age. OBJECTIVES We estimated associations of maternal serum PFAS concentrations with EAA in umbilical cord blood DNA methylation using linear regression, and a multivariable exposure-response function of the PFAS mixture using Bayesian kernel machine regression. METHODS Five PFAS were quantified in maternal serum (median: 27 weeks of gestation) among 577 mother-infant dyads from a prospective cohort. Cord blood DNA methylation data were assessed with the Illumina HumanMethylation450 array. EAA was calculated as the residuals from regressing gestational age on epigenetic age, calculated using a cord-blood specific epigenetic clock. Linear regression tested for associations between each maternal PFAS concentration with EAA. Bayesian kernel machine regression with hierarchical selection estimated an exposure-response function for the PFAS mixture. RESULTS In single pollutant models we observed an inverse relationship between perfluorodecanoate (PFDA) and EAA (-0.148 weeks per log-unit increase, 95% CI: -0.283, -0.013). Mixture analysis with hierarchical selection between perfluoroalkyl carboxylates and sulfonates indicated the carboxylates had the highest group posterior inclusion probability (PIP), or relative importance. Within this group, PFDA had the highest conditional PIP. Univariate predictor-response functions indicated PFDA and perfluorononanoate were inversely associated with EAA, while perfluorohexane sulfonate had a positive association with EAA. CONCLUSIONS Maternal mid-pregnancy serum concentrations of PFDA were negatively associated with EAA in cord blood, suggesting a pathway by which prenatal PFAS exposures may affect infant development. No significant associations were observed with other PFAS. Mixture models suggested opposite directions of association between perfluoroalkyl sulfonates and carboxylates. Future studies are needed to determine the importance of neonatal EAA for later child health outcomes.
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Affiliation(s)
- Sierra S Niemiec
- Center for Innovative Design and Analysis, Colorado School of Public Health, University of Colorado Anschutz Medical Campus, Aurora, CO, USA.
| | - Katerina Kechris
- Center for Innovative Design and Analysis, Colorado School of Public Health, University of Colorado Anschutz Medical Campus, Aurora, CO, USA; Department of Biostatistics and Informatics, Colorado School of Public Health, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Jack Pattee
- Center for Innovative Design and Analysis, Colorado School of Public Health, University of Colorado Anschutz Medical Campus, Aurora, CO, USA; Department of Biostatistics and Informatics, Colorado School of Public Health, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Ivana V Yang
- Division of Biomedical Informatics and Personalized Medicine, Department of Medicine, University of Colorado School of Medicine, Aurora, CO, USA; Center for Genes, Environment and Health, National Jewish Health, Denver, CO, USA; Department of Epidemiology, Colorado School of Public Health, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - John L Adgate
- Department of Environmental and Occupational Health, Colorado School of Public Health, University of Colorado, Aurora, CO, USA
| | - Antonia M Calafat
- Division of Laboratory Sciences, National Center for Environmental Health, Centers for Disease Control and Prevention, Atlanta, GA, USA
| | - Dana Dabelea
- Department of Epidemiology, Colorado School of Public Health, University of Colorado Anschutz Medical Campus, Aurora, CO, USA; Lifecourse Epidemiology of Adiposity and Diabetes (LEAD) Center, University of Colorado Anschutz Medical Campus, Aurora, CO, USA; Department of Pediatrics, School of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Anne P Starling
- Department of Epidemiology, Colorado School of Public Health, University of Colorado Anschutz Medical Campus, Aurora, CO, USA; Lifecourse Epidemiology of Adiposity and Diabetes (LEAD) Center, University of Colorado Anschutz Medical Campus, Aurora, CO, USA; Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
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84
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Bodelon C, Gierach GL, Hatch EE, Riseberg E, Hutchinson A, Yeager M, Sandler DP, Taylor JA, Hoover RN, Xu Z, Titus L, Palmer JR, Troisi R. In utero exposure to diethylstilbestrol and blood DNA methylation in adult women: Results from a meta-analysis of two cohort studies. ENVIRONMENTAL RESEARCH 2023; 231:115990. [PMID: 37149030 PMCID: PMC10442904 DOI: 10.1016/j.envres.2023.115990] [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: 02/13/2023] [Revised: 04/10/2023] [Accepted: 04/24/2023] [Indexed: 05/08/2023]
Abstract
BACKGROUND Prenatal exposure to diethylstilbestrol (DES) is associated with several adverse health outcomes. Animal studies have shown associations between prenatal DES exposure and DNA methylation. OBJECTIVE The aim of this study was to explore blood DNA methylation in women exposed and unexposed to DES in utero. METHODS Sixty women (40 exposed and 20 unexposed) in the National Cancer Institute's Combined DES Cohort Study and 199 women (99 exposed and 100 unexposed women) in the Sister Study Cohort were included in this analysis. Within each study, robust linear regression models were used to assess associations between DES exposure and blood DNA methylation. Study-specific associations were combined using fixed-effect meta-analysis with inverse variance weights. Our analysis focused on CpG sites located within nine candidate genes identified in animal models. We further explored whether in utero DES exposure was associated with age acceleration. RESULTS Blood DNA methylation levels at 10 CpG sites in six of the nine candidate genes were statistically significantly associated with prenatal DES exposure (P < 0.05) in this meta-analysis. Genes included EGF, EMB, EGFR, WNT11, FOS, and TGFB1, which are related to cell proliferation and differentiation. The most statistically significant CpG site was cg19830739 in gene EGF, and it was associated with lower methylation levels in women prenatally exposed to DES compared with those not exposed (P < 0.0001; false discovery rate<0.05). The association between prenatal DES exposure in utero and age acceleration was not statistically significant (P = 0.07 for meta-analyzed results). CONCLUSIONS There are few opportunities to investigate the effects of prenatal DES exposure. These findings suggest that in utero DES exposure may be associated with differential blood DNA methylation levels, which could mediate the increased risk of several adverse health outcomes observed in exposed women. Our findings need further evaluation using larger data sets.
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Affiliation(s)
- Clara Bodelon
- Integrative Tumor Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA.
| | - Gretchen L Gierach
- Integrative Tumor Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Elizabeth E Hatch
- Department of Epidemiology, Boston University School of Public Health, Boston University, Boston, MA, USA
| | - Emily Riseberg
- Department of Nutrition, Harvard T. H. Chan School of Public Health, Harvard University, Boston, MA, USA
| | - Amy Hutchinson
- Cancer Genomics Research Laboratory, Frederick National Laboratory for Cancer Research, Frederick, MD, USA
| | - Meredith Yeager
- Cancer Genomics Research Laboratory, Frederick National Laboratory for Cancer Research, Frederick, MD, USA
| | - Dale P Sandler
- Epidemiology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, NC, USA
| | - Jack A Taylor
- Epidemiology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, NC, USA; Epigenetic and Stem Cell Biology Laboratory, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, NC, USA
| | - Robert N Hoover
- Trans-Divisional Research Program, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Zongli Xu
- Epidemiology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, NC, USA
| | - Linda Titus
- Public Health, Muskie School of Public Service, University of Southern Maine, Portland, ME, USA
| | - Julie R Palmer
- Slone Epidemiology Center and Department of Medicine, Boston University School of Medicine, Boston University, Boston, MA, USA
| | - Rebecca Troisi
- Trans-Divisional Research Program, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA.
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85
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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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86
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Horvath S, Singh K, Raj K, Khairnar S, Sanghavi A, Shrivastava A, Zoller JA, Li CZ, Herenu CB, Canatelli-Mallat M, Lehmann M, Habazin S, Novokmet M, Vučković F, Woods LCS, Martinez AG, Wang T, Chiavellini P, Levine AJ, Chen H, Brooke RT, Gordevicius J, Lauc G, Goya RG, Katcher HL. Reversal of Biological Age in Multiple Rat Organs by Young Porcine Plasma Fraction. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.08.06.552148. [PMID: 37609328 PMCID: PMC10441355 DOI: 10.1101/2023.08.06.552148] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/24/2023]
Abstract
Young blood plasma is known to confer beneficial effects on various organs in mice and rats. However, it was not known whether plasma from young pigs rejuvenates old rat tissues at the epigenetic level; whether it alters the epigenetic clock, which is a highly accurate molecular biomarker of aging. To address this question, we developed and validated six different epigenetic clocks for rat tissues that are based on DNA methylation values derived from n=613 tissue samples. As indicated by their respective names, the rat pan-tissue clock can be applied to DNA methylation profiles from all rat tissues, while the rat brain-, liver-, and blood clocks apply to the corresponding tissue types. We also developed two epigenetic clocks that apply to both human and rat tissues by adding n=1366 human tissue samples to the training data. We employed these six rat clocks to investigate the rejuvenation effects of a porcine plasma fraction treatment in different rat tissues. The treatment more than halved the epigenetic ages of blood, heart, and liver tissue. A less pronounced, but statistically significant, rejuvenation effect could be observed in the hypothalamus. The treatment was accompanied by progressive improvement in the function of these organs as ascertained through numerous biochemical/physiological biomarkers and behavioral responses to assess cognitive functions. An immunoglobulin G (IgG) N-glycosylation pattern shift from pro- to anti-inflammatory also indicated reversal of glycan aging. Overall, this study demonstrates that a young porcine plasma-derived treatment markedly reverses aging in rats according to epigenetic clocks, IgG glycans, and other biomarkers of aging.
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Affiliation(s)
- Steve Horvath
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California, USA
- Department of Biostatistics, Fielding School of Public Health, University of California, Los Angeles, Los Angeles, California, USA
- Altos Labs, Cambridge, UK
| | - Kavita Singh
- Shobhaben Pratapbhai Patel School of Pharmacy and Technology Management, SVKM’S NMIMS University, Mumbai, India
| | | | - Shraddha Khairnar
- Shobhaben Pratapbhai Patel School of Pharmacy and Technology Management, SVKM’S NMIMS University, Mumbai, India
| | | | | | - Joseph A. Zoller
- Department of Biostatistics, Fielding School of Public Health, University of California, Los Angeles, Los Angeles, California, USA
| | - Caesar Z. Li
- Department of Biostatistics, Fielding School of Public Health, University of California, Los Angeles, Los Angeles, California, USA
| | - Claudia B. Herenu
- Institute for Experimental Pharmacology of Cordoba (IFEC), School of Chemical Sciences, National University of Cordoba, Cordoba, Argentina
| | - Martina Canatelli-Mallat
- Biochemistry Research Institute of La Plata – Histology B, Pathology B, School of Medicine, University of La Plata, La Plata CC 455 (zip 1900), Argentina
| | - Marianne Lehmann
- Biochemistry Research Institute of La Plata – Histology B, Pathology B, School of Medicine, University of La Plata, La Plata CC 455 (zip 1900), Argentina
| | | | | | | | - Leah C. Solberg Woods
- Wake Forest University School of Medicine, 1 Medical Center Drive, Winston Salem, NC 27157, USA
| | - Angel Garcia Martinez
- Department of Pharmacology, Addiction Science and Toxicology, The University of Tennessee Health Science Center, Memphis, TN 3993, USA
| | - Tengfei Wang
- Department of Pharmacology, Addiction Science and Toxicology, The University of Tennessee Health Science Center, Memphis, TN 3993, USA
| | - Priscila Chiavellini
- Biochemistry Research Institute of La Plata – Histology B, Pathology B, School of Medicine, University of La Plata, La Plata CC 455 (zip 1900), Argentina
| | - Andrew J. Levine
- Department of Neurology, David Geffen School of Medicine at the University of California, Los Angeles, CA, 90095, USA
| | - Hao Chen
- Department of Pharmacology, Addiction Science and Toxicology, The University of Tennessee Health Science Center, Memphis, TN 3993, USA
| | - Robert T Brooke
- Epigenetic Clock Development Foundation, Torrance, California, USA
| | | | - Gordan Lauc
- Genos Glycoscience Research Laboratory, Zagreb, Croatia
- Faculty of Pharmacy and Biochemistry, University of Zagreb, Zagreb, Croatia
| | - Rodolfo G. Goya
- Biochemistry Research Institute of La Plata – Histology B, Pathology B, School of Medicine, University of La Plata, La Plata CC 455 (zip 1900), Argentina
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87
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Singh M, El Sabbagh A, Lewis BR, Kanwar A, Terzic CM, Al-Hijji MA, Behfar A, Kirkland JL. Clinical Significance of Biological Age in Patients Undergoing Percutaneous Coronary Intervention. Mayo Clin Proc 2023; 98:1137-1152. [PMID: 37536804 DOI: 10.1016/j.mayocp.2023.03.022] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/01/2022] [Revised: 03/08/2023] [Accepted: 03/28/2023] [Indexed: 08/05/2023]
Abstract
OBJECTIVE To test whether biological age calculated using deficits, functional impairments, or their combination will provide improved estimation of long-term mortality among older adults undergoing percutaneous coronary intervention. PATIENTS AND METHODS Cardiovascular deficits, noncardiovascular deficits, and functional impairments were prospectively studied in 535 patients aged 55 years or older from August 1, 2014, to March 31, 2018. Models for biological age included deficits (acquired, increase with age, associated with worse prognosis, did not saturate early), functional impairments (subjective-help with daily activities, difficulty with sensory input, continence, weight, balance, mobility; or objective-timed up and go, functional reach), or their combination. RESULTS The mean ± SD age of the study patients was 72.1±9.5 years. For every 5-year increase in chronological age, the mean number of cardiovascular deficits increased from 2.36 among patients younger than 70 years to 3.44 in nonagenarians. The mean number of functional impairments increased from 2.15 for those younger than 70 years to 6.74 for nonagenarians. During a median follow-up of 2.05 years, 99 patients died. Significant improvement in the Harrell concordance index (C index) for prediction of long-term all-cause mortality was noted with biological age calculated from deficits and impairments compared with chronological age (0.77 vs 0.65; P<.001) and when estimating biological age via functional impairments alone vs chronological age (0.75 vs 0.65; P<.001) but not via deficits alone (0.71 vs 0.65; P=.08). Biological age estimates from subjective functional impairments captured most of the prognostic information related to all-cause and noncardiac mortality, whereas deficit-based estimation favored cardiovascular mortality. CONCLUSION The derivation of biological age from deficits and functional impairments provides a major improvement in the estimation of survival as estimated by chronological age.
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Affiliation(s)
- Mandeep Singh
- Department of Cardiovascular Medicine, Mayo Clinic, Rochester, MN.
| | | | - Bradley R Lewis
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN
| | - Amrit Kanwar
- Department of Cardiovascular Medicine, Mayo Clinic, Rochester, MN
| | - Carmen M Terzic
- Department of Cardiovascular Medicine, Mayo Clinic, Rochester, MN
| | | | - Atta Behfar
- Department of Cardiovascular Medicine, Mayo Clinic, Rochester, MN
| | - James L Kirkland
- Robert and Arlene Kogod Center on Aging, Mayo Clinic, Rochester, MN
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88
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Jackson P, Spector AL, Strath LJ, Antoine LH, Li P, Goodin BR, Hidalgo BA, Kempf MC, Gonzalez CE, Jones AC, Foster TC, Peterson JA, Quinn T, Huo Z, Fillingim R, Cruz-Almeida Y, Aroke EN. Epigenetic age acceleration mediates the relationship between neighborhood deprivation and pain severity in adults with or at risk for knee osteoarthritis pain. Soc Sci Med 2023; 331:116088. [PMID: 37473540 PMCID: PMC10407756 DOI: 10.1016/j.socscimed.2023.116088] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2023] [Revised: 06/08/2023] [Accepted: 07/08/2023] [Indexed: 07/22/2023]
Abstract
An estimated 250 million people worldwide suffer from knee osteoarthritis (KOA), with older adults having greater risk. Like other age-related diseases, residents of high-deprivation neighborhoods experience worse KOA pain outcomes compared to their more affluent neighbors. The purpose of this study was to examine the relationship between neighborhood deprivation and pain severity in KOA and the influence of epigenetic age acceleration (EpAA) on that relationship. The sample of 128 participants was mostly female (60.9%), approximately half non-Hispanic Black (49.2%), and had a mean age of 58 years. Spearman bivariate correlations revealed that pain severity positively correlated with EpAA (ρ = 0.47, p ≤ 0.001) and neighborhood deprivation (ρ = 0.25, p = 0.004). We found a positive significant relationship between neighborhood deprivation and EpAA (ρ = 0.47, p ≤ 0.001). Results indicate a mediating relationship between neighborhood deprivation (predictor), EpAA (mediator), and pain severity (outcome variable). There was a significant indirect effect of neighborhood deprivation on pain severity through EpAA, as the mediator accounted for a moderate portion of the total effect, PM = 0.44. Epigenetic age acceleration may act as a mechanism through which neighborhood deprivation leads to worse KOA pain outcomes and may play a role in the well-documented relationship between the neighborhood of residence and age-related diseases.
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Affiliation(s)
- Pamela Jackson
- School of Public Health, University of Alabama at Birmingham, 1720 2nd Avenue South, Birmingham, AL, 35294, USA.
| | - Antoinette L Spector
- School of Rehabilitation Sciences and Technology, University of Wisconsin-Milwaukee, PO Box 413, Milwaukee, WI, 53201, USA; Pain Research and Intervention Center of Excellence (PRICE), University of Florida, 2004 Mowry Road, Gainesville, FL, 32610, USA.
| | - Larissa J Strath
- Department of Community Dentistry and Behavioral Science, University of Florida, 1329 16th Street Southwest, Gainesville, FL, 32608, USA; Pain Research and Intervention Center of Excellence (PRICE), University of Florida, 2004 Mowry Road, Gainesville, FL, 32610, USA.
| | - Lisa H Antoine
- Department of Psychology, University of Alabama at Birmingham, 1720 2nd Avenue South, Birmingham, AL, 35294, USA.
| | - Peng Li
- School of Nursing, University of Alabama at Birmingham, 1720 2nd Avenue South, Birmingham, AL, 35294, USA.
| | - Burel R Goodin
- Washington University Pain Center, Department of Anesthesiology, Washington University School of Medicine in St. Louis, USA.
| | - Bertha A Hidalgo
- School of Public Health, University of Alabama at Birmingham, 1720 2nd Avenue South, Birmingham, AL, 35294, USA.
| | - Mirjam-Colette Kempf
- School of Nursing, University of Alabama at Birmingham, 1720 2nd Avenue South, Birmingham, AL, 35294, USA.
| | - Cesar E Gonzalez
- Department of Psychology, University of Alabama at Birmingham, 1720 2nd Avenue South, Birmingham, AL, 35294, USA.
| | - Alana C Jones
- School of Public Health, University of Alabama at Birmingham, 1720 2nd Avenue South, Birmingham, AL, 35294, USA.
| | - Thomas C Foster
- Department of Neuroscience, University of Florida, 1149 Newell Dr, Gainesville, FL, 32610, USA.
| | - Jessica A Peterson
- Pain Research and Intervention Center of Excellence (PRICE), University of Florida, 2004 Mowry Road, Gainesville, FL, 32610, USA.
| | - Tammie Quinn
- Department of Psychology, University of Alabama at Birmingham, 1720 2nd Avenue South, Birmingham, AL, 35294, USA.
| | - Zhiguang Huo
- Department of Biostatistics, University of Florida, 2004 Mowry Road, Gainesville, FL, 32603, USA.
| | - Roger Fillingim
- Department of Community Dentistry and Behavioral Science, University of Florida, 1329 16th Street Southwest, Gainesville, FL, 32608, USA; Pain Research and Intervention Center of Excellence (PRICE), University of Florida, 2004 Mowry Road, Gainesville, FL, 32610, USA.
| | - Yenisel Cruz-Almeida
- Department of Community Dentistry and Behavioral Science, University of Florida, 1329 16th Street Southwest, Gainesville, FL, 32608, USA; Pain Research and Intervention Center of Excellence (PRICE), University of Florida, 2004 Mowry Road, Gainesville, FL, 32610, USA; Department of Neuroscience, University of Florida, 1149 Newell Dr, Gainesville, FL, 32610, USA.
| | - Edwin N Aroke
- School of Nursing, University of Alabama at Birmingham, 1720 2nd Avenue South, Birmingham, AL, 35294, USA.
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89
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Dugué PA, Yu C, Hodge AM, Wong EM, Joo JE, Jung CH, Schmidt D, Makalic E, Buchanan DD, Severi G, English DR, Hopper JL, Milne RL, Giles GG, Southey MC. Methylation scores for smoking, alcohol consumption and body mass index and risk of seven types of cancer. Int J Cancer 2023; 153:489-498. [PMID: 36919377 DOI: 10.1002/ijc.34513] [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: 01/28/2021] [Revised: 03/16/2021] [Accepted: 03/22/2021] [Indexed: 03/16/2023]
Abstract
Methylation marks of exposure to health risk factors may be useful markers of cancer risk as they might better capture current and past exposures than questionnaires, and reflect different individual responses to exposure. We used data from seven case-control studies nested within the Melbourne Collaborative Cohort Study of blood DNA methylation and risk of colorectal, gastric, kidney, lung, prostate and urothelial cancer, and B-cell lymphoma (N cases = 3123). Methylation scores (MS) for smoking, body mass index (BMI), and alcohol consumption were calculated based on published data as weighted averages of methylation values. Rate ratios (RR) and 95% confidence intervals for association with cancer risk were estimated using conditional logistic regression and expressed per SD increase of the MS, with and without adjustment for health-related confounders. The contribution of MS to discriminate cases from controls was evaluated using the area under the curve (AUC). After confounder adjustment, we observed: large associations (RR = 1.5-1.7) with lung cancer risk for smoking MS; moderate associations (RR = 1.2-1.3) with urothelial cancer risk for smoking MS and with mature B-cell neoplasm risk for BMI and alcohol MS; moderate to small associations (RR = 1.1-1.2) for BMI and alcohol MS with several cancer types and cancer overall. Generally small AUC increases were observed after inclusion of several MS in the same model (colorectal, gastric, kidney, urothelial cancers: +3%; lung cancer: +7%; B-cell neoplasms: +8%). Methylation scores for smoking, BMI and alcohol consumption show independent associations with cancer risk, and may provide some improvements in risk prediction.
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Affiliation(s)
- Pierre-Antoine Dugué
- Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, Victoria, Australia
- Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, Victoria, Australia
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Parkville, Victoria, Australia
| | - Chenglong Yu
- Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, Victoria, Australia
| | - Allison M Hodge
- Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, Victoria, Australia
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Parkville, Victoria, Australia
| | - Ee Ming Wong
- Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, Victoria, Australia
- Department of Clinical Pathology, Melbourne Medical School, The University of Melbourne, Parkville, Victoria, Australia
| | - JiHoon E Joo
- Colorectal Oncogenomics Group, Department of Clinical Pathology, Melbourne Medical School, The University of Melbourne, Parkville, Victoria, Australia
| | - Chol-Hee Jung
- Melbourne Bioinformatics, University of Melbourne, Parkville, Victoria, Australia
| | - Daniel Schmidt
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Parkville, Victoria, Australia
- Department of Data Science and AI, Faculty of IT, Monash University, Clayton, Victoria, Australia
| | - Enes Makalic
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Parkville, Victoria, Australia
| | - Daniel D Buchanan
- Colorectal Oncogenomics Group, Department of Clinical Pathology, Melbourne Medical School, The University of Melbourne, Parkville, Victoria, Australia
- Melbourne Bioinformatics, University of Melbourne, Parkville, Victoria, Australia
- Genomic Medicine and Family Cancer Clinic, Royal Melbourne Hospital, Parkville, Victoria, Australia
| | - Gianluca Severi
- Centre de Recherche en Epidémiologie et Santé des Populations (CESP, Inserm U1018), Facultés de Médecine Universités Paris-Saclay, UVSQ, Gustave Roussy, Villejuif, France
| | - Dallas R English
- Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, Victoria, Australia
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Parkville, Victoria, Australia
| | - John L Hopper
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Parkville, Victoria, Australia
| | - Roger L Milne
- Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, Victoria, Australia
- Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, Victoria, Australia
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Parkville, Victoria, Australia
| | - Graham G Giles
- Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, Victoria, Australia
- Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, Victoria, Australia
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Parkville, Victoria, Australia
| | - Melissa C Southey
- Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, Victoria, Australia
- Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, Victoria, Australia
- Department of Clinical Pathology, Melbourne Medical School, The University of Melbourne, Parkville, Victoria, Australia
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90
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Simpson DJ, Zhao Q, Olova NN, Dabrowski J, Xie X, Latorre‐Crespo E, Chandra T. Region-based epigenetic clock design improves RRBS-based age prediction. Aging Cell 2023; 22:e13866. [PMID: 37170475 PMCID: PMC10410054 DOI: 10.1111/acel.13866] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2023] [Revised: 04/20/2023] [Accepted: 04/21/2023] [Indexed: 05/13/2023] Open
Abstract
Recent studies suggest that epigenetic rejuvenation can be achieved using drugs that mimic calorie restriction and techniques such as reprogramming-induced rejuvenation. To effectively test rejuvenation in vivo, mouse models are the safest alternative. However, we have found that the recent epigenetic clocks developed for mouse reduced-representation bisulphite sequencing (RRBS) data have significantly poor performance when applied to external datasets. We show that the sites captured and the coverage of key CpGs required for age prediction vary greatly between datasets, which likely contributes to the lack of transferability in RRBS clocks. To mitigate these coverage issues in RRBS-based age prediction, we present two novel design strategies that use average methylation over large regions rather than individual CpGs, whereby regions are defined by sliding windows (e.g. 5 kb), or density-based clustering of CpGs. We observe improved correlation and error in our regional blood clocks (RegBCs) compared to published individual-CpG-based techniques when applied to external datasets. The RegBCs are also more robust when applied to low coverage data and detect a negative age acceleration in mice undergoing calorie restriction. Our RegBCs offer a proof of principle that age prediction of RRBS datasets can be improved by accounting for multiple CpGs over a region, which negates the lack of read depth currently hindering individual-CpG-based approaches.
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Affiliation(s)
- Daniel J. Simpson
- MRC Human Genetics Unit, MRC Institute of Genetics and CancerUniversity of EdinburghEdinburghUK
| | - Qian Zhao
- MRC Human Genetics Unit, MRC Institute of Genetics and CancerUniversity of EdinburghEdinburghUK
| | - Nelly N. Olova
- MRC Human Genetics Unit, MRC Institute of Genetics and CancerUniversity of EdinburghEdinburghUK
| | - Jan Dabrowski
- MRC Human Genetics Unit, MRC Institute of Genetics and CancerUniversity of EdinburghEdinburghUK
| | - Xiaoxiao Xie
- MRC Human Genetics Unit, MRC Institute of Genetics and CancerUniversity of EdinburghEdinburghUK
| | - Eric Latorre‐Crespo
- MRC Human Genetics Unit, MRC Institute of Genetics and CancerUniversity of EdinburghEdinburghUK
| | - Tamir Chandra
- MRC Human Genetics Unit, MRC Institute of Genetics and CancerUniversity of EdinburghEdinburghUK
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91
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Luo Q, Dwaraka VB, Chen Q, Tong H, Zhu T, Seale K, Raffaele JM, Zheng SC, Mendez TL, Chen Y, Carreras N, Begum S, Mendez K, Voisin S, Eynon N, Lasky-Su JA, Smith R, Teschendorff AE. A meta-analysis of immune-cell fractions at high resolution reveals novel associations with common phenotypes and health outcomes. Genome Med 2023; 15:59. [PMID: 37525279 PMCID: PMC10388560 DOI: 10.1186/s13073-023-01211-5] [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: 03/08/2023] [Accepted: 07/10/2023] [Indexed: 08/02/2023] Open
Abstract
BACKGROUND Changes in cell-type composition of tissues are associated with a wide range of diseases and environmental risk factors and may be causally implicated in disease development and progression. However, these shifts in cell-type fractions are often of a low magnitude, or involve similar cell subtypes, making their reliable identification challenging. DNA methylation profiling in a tissue like blood is a promising approach to discover shifts in cell-type abundance, yet studies have only been performed at a relatively low cellular resolution and in isolation, limiting their power to detect shifts in tissue composition. METHODS Here we derive a DNA methylation reference matrix for 12 immune-cell types in human blood and extensively validate it with flow-cytometric count data and in whole-genome bisulfite sequencing data of sorted cells. Using this reference matrix, we perform a directional Stouffer and fixed effects meta-analysis comprising 23,053 blood samples from 22 different cohorts, to comprehensively map associations between the 12 immune-cell fractions and common phenotypes. In a separate cohort of 4386 blood samples, we assess associations between immune-cell fractions and health outcomes. RESULTS Our meta-analysis reveals many associations of cell-type fractions with age, sex, smoking and obesity, many of which we validate with single-cell RNA sequencing. We discover that naïve and regulatory T-cell subsets are higher in women compared to men, while the reverse is true for monocyte, natural killer, basophil, and eosinophil fractions. Decreased natural killer counts associated with smoking, obesity, and stress levels, while an increased count correlates with exercise and sleep. Analysis of health outcomes revealed that increased naïve CD4 + T-cell and N-cell fractions associated with a reduced risk of all-cause mortality independently of all major epidemiological risk factors and baseline co-morbidity. A machine learning predictor built only with immune-cell fractions achieved a C-index value for all-cause mortality of 0.69 (95%CI 0.67-0.72), which increased to 0.83 (0.80-0.86) upon inclusion of epidemiological risk factors and baseline co-morbidity. CONCLUSIONS This work contributes an extensively validated high-resolution DNAm reference matrix for blood, which is made freely available, and uses it to generate a comprehensive map of associations between immune-cell fractions and common phenotypes, including health outcomes.
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Affiliation(s)
- Qi Luo
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, 320 Yue Yang Road, Shanghai, 200031, China
| | - Varun B Dwaraka
- TruDiagnostics, 881 Corporate Dr., Lexington, KY, 40503, USA
| | - Qingwen Chen
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, 02115, USA
| | - Huige Tong
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, 320 Yue Yang Road, Shanghai, 200031, China
| | - Tianyu Zhu
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, 320 Yue Yang Road, Shanghai, 200031, China
| | - Kirsten Seale
- Institute for Health and Sport (iHeS), Victoria University, Footscray, VIC, 3011, Australia
| | - Joseph M Raffaele
- PhysioAge LLC, 30 Central Park South / Suite 8A, New York, NY, 10019, USA
| | - Shijie C Zheng
- Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, USA
| | - Tavis L Mendez
- TruDiagnostics, 881 Corporate Dr., Lexington, KY, 40503, USA
| | - Yulu Chen
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, 02115, USA
| | | | - Sofina Begum
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, 02115, USA
| | - Kevin Mendez
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, 02115, USA
| | - Sarah Voisin
- Institute for Health and Sport (iHeS), Victoria University, Footscray, VIC, 3011, Australia
| | - Nir Eynon
- Australian Regenerative Medicine Institute, Monash University, Clayton, VIC, 3800, Australia
| | - Jessica A Lasky-Su
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, 02115, USA.
| | - Ryan Smith
- TruDiagnostics, 881 Corporate Dr., Lexington, KY, 40503, USA.
| | - Andrew E Teschendorff
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, 320 Yue Yang Road, Shanghai, 200031, China.
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92
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Kusters CDJ, Paul KC, Lu AT, Ferrucci L, Ritz BR, Binder AM, Horvath S. Higher testosterone and testosterone/estradiol ratio in men are associated with better epigenetic estimators of mortality risk. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.02.16.23285997. [PMID: 36865294 PMCID: PMC9980235 DOI: 10.1101/2023.02.16.23285997] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/25/2023]
Abstract
Introduction Sex hormones are hypothesized to drive sex-specific health disparities. Here, we study the association between sex steroid hormones and DNA methylation-based (DNAm) biomarkers of age and mortality risk including Pheno Age Acceleration (AA), Grim AA, and DNAm-based estimators of Plasminogen Activator Inhibitor 1 (PAI1), and leptin concentrations. Methods We pooled data from three population-based cohorts, the Framingham Heart Study Offspring Cohort (FHS), the Baltimore Longitudinal Study of Aging (BLSA), and the InCHIANTI Study, including 1,062 postmenopausal women without hormone therapy and 1,612 men of European descent. Sex hormone concentrations were standardized with mean 0 and standard deviation of 1, for each study and sex separately. Sex-stratified analyses using a linear mixed regression were performed, with a Benjamini-Hochberg (BH) adjustment for multiple testing. Sensitivity analysis was performed excluding the previously used training-set for the development of Pheno and Grim age. Results Sex Hormone Binding Globulin (SHBG) is associated with a decrease in DNAm PAI1 among men (per 1 standard deviation (SD): -478 pg/mL; 95%CI: -614 to -343; P:1e-11; BH-P: 1e-10), and women (-434 pg/mL; 95%CI: -589 to -279; P:1e-7; BH-P:2e-6). The testosterone/estradiol (TE) ratio was associated with a decrease in Pheno AA (-0.41 years; 95%CI: -0.70 to -0.12; P:0.01; BH-P: 0.04), and DNAm PAI1 (-351 pg/mL; 95%CI: -486 to -217; P:4e-7; BH-P:3e-6) among men. In men, 1 SD increase in total testosterone was associated with a decrease in DNAm PAI1 (-481 pg/mL; 95%CI: -613 to -349; P:2e-12; BH-P:6e-11). Conclusion SHBG was associated with lower DNAm PAI1 among men and women. Higher testosterone and testosterone/estradiol ratio were associated with lower DNAm PAI and a younger epigenetic age in men. A decrease in DNAm PAI1 is associated with lower mortality and morbidity risk indicating a potential protective effect of testosterone on lifespan and conceivably cardiovascular health via DNAm PAI1.
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Affiliation(s)
- Cynthia DJ Kusters
- Department of Human Genetics, David Geffen School of Medicine, Los Angeles, CA, USA
| | - Kimberly C Paul
- Department of Neurology, David Geffen School of Medicine, Los Angeles, CA, USA
| | - Ake T Lu
- Department of Human Genetics, David Geffen School of Medicine, Los Angeles, CA, USA
- Altos Labs, San Diego, USA
| | - Luigi Ferrucci
- Longitudinal Studies Section, Translational Gerontology Branch, National Institute on Aging, National Institutes of Health, Baltimore, USA
| | - Beate R Ritz
- Department of Neurology, David Geffen School of Medicine, Los Angeles, CA, USA
- Department of Epidemiology, UCLA Fielding School of Public Health, Los Angeles, CA, USA
- Department of Environmental Health, UCLA Fielding School of Public Health, Los Angeles, CA, USA
| | - Alexandra M Binder
- Department of Epidemiology, UCLA Fielding School of Public Health, Los Angeles, CA, USA
- Population Sciences in the Pacific Program, University of Hawaii Cancer Center, Honolulu, Hawaii, USA
| | - Steve Horvath
- Department of Human Genetics, David Geffen School of Medicine, Los Angeles, CA, USA
- Altos Labs, San Diego, USA
- Population Sciences in the Pacific Program, University of Hawaii Cancer Center, Honolulu, Hawaii, USA
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93
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Bernardino JI, Alejos B, Rodriguez-Centeno J, Esteban-Cantos A, Mora-Rojas B, Montejano R, De Miguel R, Montero-Alonso M, Ayerdi O, Hernández-Gutierrez C, Curran A, Arribas JR, Rodés B. Monocyte Activation and Ageing Biomarkers in the Development of Cardiovascular Ischaemic Events or Diabetes in People with HIV. Microorganisms 2023; 11:1818. [PMID: 37512990 PMCID: PMC10385988 DOI: 10.3390/microorganisms11071818] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2023] [Revised: 07/05/2023] [Accepted: 07/13/2023] [Indexed: 07/30/2023] Open
Abstract
We investigated whether blood telomere length (TL), epigenetic age acceleration (EAA), and soluble inflammatory monocyte cytokines are associated with cardiovascular events or diabetes (DM) in people living with HIV (PLHIV). This was a case-control study nested in the Spanish HIV/AIDS Cohort (CoRIS). Cases with myocardial infarction, stroke, sudden death, or diabetes after starting antiretroviral therapy were included with the available samples and controls matched for sex, age, tobacco use, pre-ART CD4 cell count, viral load, and sample time-point. TL (T/S ratio) was analysed by quantitative PCR and EAA with DNA methylation changes by next-generation sequencing using the Weidner formula. Conditional logistic regression was used to explore the association with cardiometabolic events. In total, 180 participants (94 cases (22 myocardial infarction/sudden death, 12 strokes, and 60 DM) and 94 controls) were included. Of these, 84% were male, median (IQR) age 46 years (40-56), 53% were current smokers, and 22% had CD4 count ≤ 200 cells/mm3 and a median (IQR) log viral load of 4.52 (3.77-5.09). TL and EAA were similar in the cases and controls. There were no significant associations between TL, EAA, and monocyte cytokines with cardiometabolic events. TL and EAA were mildly negatively correlated with sCD14 (rho = -0.23; p = 0.01) and CCL2/MCP-1 (rho = -0.17; p = 0.02). We found no associations between TL, EAA, and monocyte cytokines with cardiovascular events or diabetes. Further studies are needed to elucidate the clinical value of epigenetic biomarkers and TL in PLHIV.
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Affiliation(s)
- Jose I Bernardino
- Unidad de VIH, Hospital Universitario La Paz, IdiPAZ, 28046 Madrid, Spain
- CIBERINFECC, Instituto de Salud Carlos III, 28029 Madrid, Spain
| | - Belen Alejos
- Centro Nacional de Epidemiología, Instituto de Salud Carlos III, 28029 Madrid, Spain
| | - Javier Rodriguez-Centeno
- CIBERINFECC, Instituto de Salud Carlos III, 28029 Madrid, Spain
- HIV/AIDS and Infectious Diseases Research Group, IdiPAZ, 28046 Madrid, Spain
| | - Andrés Esteban-Cantos
- CIBERINFECC, Instituto de Salud Carlos III, 28029 Madrid, Spain
- HIV/AIDS and Infectious Diseases Research Group, IdiPAZ, 28046 Madrid, Spain
| | - Beatriz Mora-Rojas
- CIBERINFECC, Instituto de Salud Carlos III, 28029 Madrid, Spain
- HIV/AIDS and Infectious Diseases Research Group, IdiPAZ, 28046 Madrid, Spain
| | - Rocío Montejano
- Unidad de VIH, Hospital Universitario La Paz, IdiPAZ, 28046 Madrid, Spain
- CIBERINFECC, Instituto de Salud Carlos III, 28029 Madrid, Spain
| | - Rosa De Miguel
- Unidad de VIH, Hospital Universitario La Paz, IdiPAZ, 28046 Madrid, Spain
- CIBERINFECC, Instituto de Salud Carlos III, 28029 Madrid, Spain
| | - Marta Montero-Alonso
- Unidad de Enfermedades Infecciosas, Hospital Universitario y Politécnico La Fe, 46026 Valencia, Spain
| | - Oskar Ayerdi
- Centro Sanitario Sandoval, Hospital Clínico San Carlos, IdiSSSC, 28010 Madrid, Spain
| | - Cristina Hernández-Gutierrez
- Departamento de Medicina Interna, Hospital Universitario Príncipe de Asturias, Alcalá de Henares, 28805 Madrid, Spain
| | - Adriá Curran
- Departamento Enfermedades Infecciosas, Hospital Universitari Vall d'Hebron, VHIR, 08035 Barcelona, Spain
| | - Jose R Arribas
- Unidad de VIH, Hospital Universitario La Paz, IdiPAZ, 28046 Madrid, Spain
- CIBERINFECC, Instituto de Salud Carlos III, 28029 Madrid, Spain
| | - Berta Rodés
- CIBERINFECC, Instituto de Salud Carlos III, 28029 Madrid, Spain
- HIV/AIDS and Infectious Diseases Research Group, IdiPAZ, 28046 Madrid, Spain
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94
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Walton E, Baltramonaityte V, Calhoun V, Heijmans BT, Thompson PM, Cecil CAM. A systematic review of neuroimaging epigenetic research: calling for an increased focus on development. Mol Psychiatry 2023; 28:2839-2847. [PMID: 37185958 PMCID: PMC10615743 DOI: 10.1038/s41380-023-02067-2] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/23/2022] [Revised: 03/03/2023] [Accepted: 04/03/2023] [Indexed: 05/17/2023]
Abstract
Epigenetic mechanisms, such as DNA methylation (DNAm), have gained increasing attention as potential biomarkers and mechanisms underlying risk for neurodevelopmental, psychiatric and other brain-based disorders. Yet, surprisingly little is known about the extent to which DNAm is linked to individual differences in the brain itself, and how these associations may unfold across development - a time of life when many of these disorders emerge. Here, we systematically review evidence from the nascent field of Neuroimaging Epigenetics, combining structural or functional neuroimaging measures with DNAm, and the extent to which the developmental period (birth to adolescence) is represented in these studies. We identified 111 articles published between 2011-2021, out of which only a minority (21%) included samples under 18 years of age. Most studies were cross-sectional (85%), employed a candidate-gene approach (67%), and examined DNAm-brain associations in the context of health and behavioral outcomes (75%). Nearly half incorporated genetic data, and a fourth investigated environmental influences. Overall, studies support a link between peripheral DNAm and brain imaging measures, but there is little consistency in specific findings and it remains unclear whether DNAm markers present a cause, correlate or consequence of brain alterations. Overall, there is large heterogeneity in sample characteristics, peripheral tissue and brain outcome examined as well as the methods used. Sample sizes were generally low to moderate (median nall = 98, ndevelopmental = 80), and attempts at replication or meta-analysis were rare. Based on the strengths and weaknesses of existing studies, we propose three recommendations on how advance the field of Neuroimaging Epigenetics. We advocate for: (1) a greater focus on developmentally oriented research (i.e. pre-birth to adolescence); (2) the analysis of large, prospective, pediatric cohorts with repeated measures of DNAm and imaging to assess directionality; and (3) collaborative, interdisciplinary science to identify robust signals, triangulate findings and enhance translational potential.
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Affiliation(s)
- Esther Walton
- Department of Psychology, University of Bath, Bath, UK.
| | | | - Vince Calhoun
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science, Georgia State University, Georgia Institute of Technology, Emory University, Atlanta, GA, USA
| | - Bastiaan T Heijmans
- Molecular Epidemiology, Dept. of Biomedical Data Sciences, Leiden University Medical Center, Leiden, The Netherlands
| | - Paul M Thompson
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging & Informatics Institute, Keck School of Medicine of the University of Southern California, Marina del Rey, CA, USA
| | - Charlotte A M Cecil
- Molecular Epidemiology, Dept. of Biomedical Data Sciences, Leiden University Medical Center, Leiden, The Netherlands
- Department of Child and Adolescent Psychiatry/Psychology, Erasmus University Medical Center Rotterdam, Rotterdam, The Netherlands
- Department of Epidemiology, Erasmus University Medical Center Rotterdam, Rotterdam, The Netherlands
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95
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Salignon J, Faridani OR, Miliotis T, Janssens GE, Chen P, Zarrouki B, Sandberg R, Davidsson P, Riedel CG. Age prediction from human blood plasma using proteomic and small RNA data: a comparative analysis. Aging (Albany NY) 2023; 15:5240-5265. [PMID: 37341993 PMCID: PMC10333066 DOI: 10.18632/aging.204787] [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: 08/30/2022] [Accepted: 05/26/2023] [Indexed: 06/22/2023]
Abstract
Aging clocks, built from comprehensive molecular data, have emerged as promising tools in medicine, forensics, and ecological research. However, few studies have compared the suitability of different molecular data types to predict age in the same cohort and whether combining them would improve predictions. Here, we explored this at the level of proteins and small RNAs in 103 human blood plasma samples. First, we used a two-step mass spectrometry approach measuring 612 proteins to select and quantify 21 proteins that changed in abundance with age. Notably, proteins increasing with age were enriched for components of the complement system. Next, we used small RNA sequencing to select and quantify a set of 315 small RNAs that changed in abundance with age. Most of these were microRNAs (miRNAs), downregulated with age, and predicted to target genes related to growth, cancer, and senescence. Finally, we used the collected data to build age-predictive models. Among the different types of molecules, proteins yielded the most accurate model (R² = 0.59 ± 0.02), followed by miRNAs as the best-performing class of small RNAs (R² = 0.54 ± 0.02). Interestingly, the use of protein and miRNA data together improved predictions (R2 = 0.70 ± 0.01). Future work using larger sample sizes and a validation dataset will be necessary to confirm these results. Nevertheless, our study suggests that combining proteomic and miRNA data yields superior age predictions, possibly by capturing a broader range of age-related physiological changes. It will be interesting to determine if combining different molecular data types works as a general strategy to improve future aging clocks.
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Affiliation(s)
- Jérôme Salignon
- Department of Medicine, Integrated Cardio Metabolic Centre (ICMC), Karolinska Institutet, Huddinge 14157, Sweden
- Department of Biosciences and Nutrition, Karolinska Institutet, Huddinge 14157, Sweden
| | - Omid R. Faridani
- Department of Medicine, Integrated Cardio Metabolic Centre (ICMC), Karolinska Institutet, Huddinge 14157, Sweden
- Lowy Cancer Research Centre, School of Medical Sciences, University of New South Wales, Sydney, Australia
- Garvan Institute of Medical Research, Sydney, Australia
| | - Tasso Miliotis
- Translational Science and Experimental Medicine, Research and Early Development, Cardiovascular, Renal and Metabolism, BioPharmaceuticals R&D, AstraZeneca, Gothenburg, Sweden
| | - Georges E. Janssens
- Department of Medicine, Integrated Cardio Metabolic Centre (ICMC), Karolinska Institutet, Huddinge 14157, Sweden
| | - Ping Chen
- Department of Medicine, Integrated Cardio Metabolic Centre (ICMC), Karolinska Institutet, Huddinge 14157, Sweden
| | - Bader Zarrouki
- Bioscience Metabolism, Research and Early Development, Cardiovascular, Renal and Metabolism, BioPharmaceuticals R&D, AstraZeneca, Gothenburg, Sweden
| | - Rickard Sandberg
- Department of Medicine, Integrated Cardio Metabolic Centre (ICMC), Karolinska Institutet, Huddinge 14157, Sweden
- Department of Cellular and Molecular Biology, Ludwig Institute for Cancer Research, Karolinska Institutet, Solna 17165, Sweden
| | - Pia Davidsson
- Translational Science and Experimental Medicine, Research and Early Development, Cardiovascular, Renal and Metabolism, BioPharmaceuticals R&D, AstraZeneca, Gothenburg, Sweden
| | - Christian G. Riedel
- Department of Medicine, Integrated Cardio Metabolic Centre (ICMC), Karolinska Institutet, Huddinge 14157, Sweden
- Department of Biosciences and Nutrition, Karolinska Institutet, Huddinge 14157, Sweden
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96
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Ventham NT, Kennedy NA, Kalla R, Adams AT, Noble A, Ennis H, Mowat C, Dunlop MG, Satsangi J. Genome-Wide Methylation Profiling in 229 Patients With Crohn's Disease Requiring Intestinal Resection: Epigenetic Analysis of the Trial of Prevention of Post-operative Crohn's Disease (TOPPIC). Cell Mol Gastroenterol Hepatol 2023; 16:431-450. [PMID: 37331566 PMCID: PMC10372903 DOI: 10.1016/j.jcmgh.2023.06.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/04/2022] [Revised: 06/02/2023] [Accepted: 06/02/2023] [Indexed: 06/20/2023]
Abstract
BACKGROUND & AIMS DNA methylation alterations may provide important insights into gene-environment interaction in cancer, aging, and complex diseases, such as inflammatory bowel disease (IBD). We aim first to determine whether the circulating DNA methylome in patients requiring surgery may predict Crohn's disease (CD) recurrence following intestinal resection; and second to compare the circulating methylome seen in patients with established CD with that we had reported in a series of inception cohorts. METHODS TOPPIC was a placebo-controlled, randomized controlled trial of 6-mercaptopurine at 29 UK centers in patients with CD undergoing ileocolic resection between 2008 and 2012. Genomic DNA was extracted from whole blood samples from 229 of the 240 patients taken before intestinal surgery and analyzed using 450KHumanMethylation and Infinium Omni Express Exome arrays (Illumina, San Diego, CA). Coprimary objectives were to determine whether methylation alterations may predict clinical disease recurrence; and to assess whether the epigenetic alterations previously reported in newly diagnosed IBD were present in the patients with CD recruited into the TOPPIC study. Differential methylation and variance analysis was performed comparing patients with and without clinical evidence of recurrence. Secondary analyses included investigation of methylation associations with smoking, genotype (MeQTLs), and chronologic age. Validation of our previously published case-control observation of the methylome was performed using historical control data (CD, n = 123; Control, n = 198). RESULTS CD recurrence in patients following surgery is associated with 5 differentially methylated positions (Holm P < .05), including probes mapping to WHSC1 (P = 4.1 × 10-9, Holm P = .002) and EFNA3 (P = 4.9 × 10-8, Holm P = .02). Five differentially variable positions are demonstrated in the group of patients with evidence of disease recurrence including a probe mapping to MAD1L1 (P = 6.4 × 10-5). DNA methylation clock analyses demonstrated significant age acceleration in CD compared with control subjects (GrimAge + 2 years; 95% confidence interval, 1.2-2.7 years), with some evidence for accelerated aging in patients with CD with disease recurrence following surgery (GrimAge +1.04 years; 95% confidence interval, -0.04 to 2.22). Significant methylation differences between CD cases and control subjects were seen by comparing this cohort in conjunction with previously published control data, including validation of our previously described differentially methylated positions (RPS6KA2 P = 1.2 × 10-19, SBNO2 = 1.2 × 10-11) and regions (TXK [false discovery rate, P = 3.6 × 10-14], WRAP73 [false discovery rate, P = 1.9 × 10-9], VMP1 [false discovery rate, P = 1.7 × 10-7], and ITGB2 [false discovery rate, P = 1.4 × 10-7]). CONCLUSIONS We demonstrate differential methylation and differentially variable methylation in patients developing clinical recurrence within 3 years of surgery. Moreover, we report replication of the CD-associated methylome, previously characterized only in adult and pediatric inception cohorts, in patients with medically refractory disease needing surgery.
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Affiliation(s)
- Nicholas T Ventham
- Centre for Genomic and Experimental Medicine, The University of Edinburgh, Edinburgh, Midlothian, United Kingdom.
| | - Nicholas A Kennedy
- Centre for Genomic and Experimental Medicine, The University of Edinburgh, Edinburgh, Midlothian, United Kingdom
| | - Rahul Kalla
- Centre for Genomic and Experimental Medicine, The University of Edinburgh, Edinburgh, Midlothian, United Kingdom
| | - Alex T Adams
- Centre for Genomic and Experimental Medicine, The University of Edinburgh, Edinburgh, Midlothian, United Kingdom
| | - Alexandra Noble
- Centre for Genomic and Experimental Medicine, The University of Edinburgh, Edinburgh, Midlothian, United Kingdom
| | - Holly Ennis
- Centre for Genomic and Experimental Medicine, The University of Edinburgh, Edinburgh, Midlothian, United Kingdom
| | - Craig Mowat
- Centre for Genomic and Experimental Medicine, The University of Edinburgh, Edinburgh, Midlothian, United Kingdom
| | - Malcolm G Dunlop
- Centre for Genomic and Experimental Medicine, The University of Edinburgh, Edinburgh, Midlothian, United Kingdom
| | - Jack Satsangi
- Centre for Genomic and Experimental Medicine, The University of Edinburgh, Edinburgh, Midlothian, United Kingdom
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97
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Singh P, Gollapalli K, Mangiola S, Schranner D, Yusuf MA, Chamoli M, Shi SL, Bastos BL, Nair T, Riermeier A, Vayndorf EM, Wu JZ, Nilakhe A, Nguyen CQ, Muir M, Kiflezghi MG, Foulger A, Junker A, Devine J, Sharan K, Chinta SJ, Rajput S, Rane A, Baumert P, Schönfelder M, Iavarone F, Lorenzo GD, Kumari S, Gupta A, Sarkar R, Khyriem C, Chawla AS, Sharma A, Sarper N, Chattopadhyay N, Biswal BK, Settembre C, Nagarajan P, Targoff KL, Picard M, Gupta S, Velagapudi V, Papenfuss AT, Kaya A, Ferreira MG, Kennedy BK, Andersen JK, Lithgow GJ, Ali AM, Mukhopadhyay A, Palotie A, Kastenmüller G, Kaeberlein M, Wackerhage H, Pal B, Yadav VK. Taurine deficiency as a driver of aging. Science 2023; 380:eabn9257. [PMID: 37289866 PMCID: PMC10630957 DOI: 10.1126/science.abn9257] [Citation(s) in RCA: 64] [Impact Index Per Article: 64.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/01/2022] [Accepted: 04/14/2023] [Indexed: 06/10/2023]
Abstract
Aging is associated with changes in circulating levels of various molecules, some of which remain undefined. We find that concentrations of circulating taurine decline with aging in mice, monkeys, and humans. A reversal of this decline through taurine supplementation increased the health span (the period of healthy living) and life span in mice and health span in monkeys. Mechanistically, taurine reduced cellular senescence, protected against telomerase deficiency, suppressed mitochondrial dysfunction, decreased DNA damage, and attenuated inflammaging. In humans, lower taurine concentrations correlated with several age-related diseases and taurine concentrations increased after acute endurance exercise. Thus, taurine deficiency may be a driver of aging because its reversal increases health span in worms, rodents, and primates and life span in worms and rodents. Clinical trials in humans seem warranted to test whether taurine deficiency might drive aging in humans.
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Affiliation(s)
- Parminder Singh
- Metabolic Research Laboratories, National Institute of Immunology; New Delhi, India
| | - Kishore Gollapalli
- Vagelos College of Physicians and Surgeons, Columbia University; New York, USA
| | - Stefano Mangiola
- Department of Medical Biology, University of Melbourne; Melbourne, Australia
- School of Cancer Medicine, La Trobe University; Bundoora, Australia
- Olivia Newton-John Cancer Research Institute; Heidelberg, Australia
| | - Daniela Schranner
- Exercise Biology Group, Technical University of Munich; Munich, Germany
- Institute of Computational Biology, Helmholtz Zentrum München; Neuherberg, Germany
| | - Mohd Aslam Yusuf
- Department of Bioengineering, Integral University; Lucknow, India
| | - Manish Chamoli
- Buck Institute of Age Research, 8001 Redwood Blvd; California, USA
| | - Sting L. Shi
- Vagelos College of Physicians and Surgeons, Columbia University; New York, USA
| | - Bruno Lopes Bastos
- Institute for Research on Cancer and Aging of Nice (IRCAN); Nice, France
| | - Tripti Nair
- Molecular Aging Laboratory, National Institute of Immunology; New Delhi, India
| | - Annett Riermeier
- Exercise Biology Group, Technical University of Munich; Munich, Germany
| | - Elena M. Vayndorf
- Department of Laboratory Medicine and Pathology, University of Washington; WA, USA
| | - Judy Z. Wu
- Department of Laboratory Medicine and Pathology, University of Washington; WA, USA
| | - Aishwarya Nilakhe
- Metabolic Research Laboratories, National Institute of Immunology; New Delhi, India
| | - Christina Q. Nguyen
- Department of Laboratory Medicine and Pathology, University of Washington; WA, USA
| | - Michael Muir
- Department of Laboratory Medicine and Pathology, University of Washington; WA, USA
| | - Michael G. Kiflezghi
- Department of Laboratory Medicine and Pathology, University of Washington; WA, USA
| | - Anna Foulger
- Buck Institute of Age Research, 8001 Redwood Blvd; California, USA
| | - Alex Junker
- Department of Neurology, Columbia University; New York, USA
| | - Jack Devine
- Department of Neurology, Columbia University; New York, USA
| | - Kunal Sharan
- Mouse Genetics Project, Wellcome Sanger Institute; Cambridge, UK
| | | | - Swati Rajput
- Division of Endocrinology, CSIR-Central Drug Research Institute; Lucknow, India
| | - Anand Rane
- Buck Institute of Age Research, 8001 Redwood Blvd; California, USA
| | - Philipp Baumert
- Exercise Biology Group, Technical University of Munich; Munich, Germany
| | | | | | | | - Swati Kumari
- Metabolic Research Laboratories, National Institute of Immunology; New Delhi, India
| | - Alka Gupta
- Metabolic Research Laboratories, National Institute of Immunology; New Delhi, India
| | - Rajesh Sarkar
- Metabolic Research Laboratories, National Institute of Immunology; New Delhi, India
| | - Costerwell Khyriem
- Harry Perkins Institute of Medical Research; Perth, Australia
- Curtin Medical School, Curtin University; Perth, Australia
| | - Amanpreet S. Chawla
- Immunobiology Laboratory, National Institute of Immunology; New Delhi, India
- MRC-Protein Phosphorylation and Ubiquitination Unit, University of Dundee; Dundee, UK
| | - Ankur Sharma
- Harry Perkins Institute of Medical Research; Perth, Australia
- Curtin Medical School, Curtin University; Perth, Australia
| | - Nazan Sarper
- Pediatrics and Pediatric Hematology, Kocaeli University Hospital; Kocaeli, Turkey
| | | | - Bichitra K. Biswal
- Metabolic Research Laboratories, National Institute of Immunology; New Delhi, India
| | - Carmine Settembre
- Telethon Institute of Genetics and Medicine (TIGEM); Pozzuoli, Italy
- Department of Clinical Medicine and Surgery, Federico II University; Naples, Italy
| | - Perumal Nagarajan
- Primate Research Facility, National Institute of Immunology; New Delhi, India
- Small Animal Research Facility, National Institute of Immunology; New Delhi, India
| | - Kimara L. Targoff
- Division of Cardiology, Department of Pediatrics, Columbia University; New York, USA
| | - Martin Picard
- Department of Neurology, Columbia University; New York, USA
| | - Sarika Gupta
- Metabolic Research Laboratories, National Institute of Immunology; New Delhi, India
| | - Vidya Velagapudi
- Institute for Molecular Medicine Finland FIMM, University of Helsinki; Helsinki, Finland
| | | | - Alaattin Kaya
- Department of Biology, Virginia Commonwealth University; Virginia, USA
| | | | - Brian K. Kennedy
- 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
- Departments of Biochemistry and Physiology, Yong Loo Lin School of Medicine, National University of Singapore; Singapore, Singapore
| | | | | | - Abdullah Mahmood Ali
- Department of Medicine, Columbia University Irving Medical Center; New York, USA
| | - Arnab Mukhopadhyay
- Molecular Aging Laboratory, National Institute of Immunology; New Delhi, India
| | - Aarno Palotie
- Institute for Molecular Medicine Finland FIMM, University of Helsinki; Helsinki, Finland
- Broad Institute of Harvard and MIT; Cambridge, USA
- Analytic and Translational Genetics Unit, Massachusetts General Hospital; Boston, USA
| | - Gabi Kastenmüller
- Institute of Computational Biology, Helmholtz Zentrum München; Neuherberg, Germany
| | - Matt Kaeberlein
- Department of Laboratory Medicine and Pathology, University of Washington; WA, USA
| | | | - Bhupinder Pal
- Department of Medical Biology, University of Melbourne; Melbourne, Australia
- School of Cancer Medicine, La Trobe University; Bundoora, Australia
| | - Vijay K. Yadav
- Metabolic Research Laboratories, National Institute of Immunology; New Delhi, India
- Vagelos College of Physicians and Surgeons, Columbia University; New York, USA
- Mouse Genetics Project, Wellcome Sanger Institute; Cambridge, UK
- Department of Genetics and Development, Columbia University; New York, USA
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98
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Heany SJ, Levine AJ, Lesosky M, Phillips N, Fouche JP, Myer L, Zar HJ, Stein DJ, Horvath S, Hoare J. Persistent accelerated epigenetic ageing in a longitudinal cohort of vertically infected HIV-positive adolescents. J Neurovirol 2023; 29:272-282. [PMID: 37179258 PMCID: PMC10404174 DOI: 10.1007/s13365-023-01130-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2022] [Revised: 10/24/2022] [Accepted: 03/28/2023] [Indexed: 05/15/2023]
Abstract
We have previously shown accelerated ageing in adolescents perinatally infected with HIV (PHIV +), based on discrepancies between epigenetic and chronological age. The current study examines follow-up longitudinal patterns of epigenetic ageing and the association of epigenetic ageing with cognition as well as whole brain structure changes in PHIV + and healthy controls enrolled in the Cape Town Adolescent Antiretroviral Cohort Study (CTAAC). The Illumina EPIC array was used to generate blood DNA methylation data from 60 PHIV + adolescents and 36 age-matched controls aged 9-12 years old at baseline and again at a 36-month follow-up. Epigenetic clock software estimated two measures of epigenetic age acceleration: extrinsic epigenetic accelerated ageing (EEAA) and age acceleration difference (AAD) at both time points. At follow-up, each participant completed neuropsychological testing, structural magnetic resonance imaging, and diffusion tensor imaging. At follow-up, PHIV infection remains associated with increased EEAA and AAD. Accelerated epigenetic ageing remained positively associated with viral load and negatively associated with CD4 ratio. EEAA was positively associated with whole brain grey matter volume and alterations in whole brain white matter integrity. AAD and EEAA were not associated with cognitive function within the PHIV + group. Measures of epigenetic ageing, as detected in DNA methylation patterns, remain increased in PHIV + adolescents across a 36-month period. Associations between epigenetic ageing measures, viral biomarkers, and alterations in brain micro- and macrostructure also persist at 36-month follow-up. Further study should determine if epigenetic age acceleration is associated with cognitive functional changes due to brain alterations in later life.
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Affiliation(s)
- Sarah J Heany
- SA MRC Unit On Risk & Resilience in Mental Disorders, Department of Psychiatry and Mental Health, University of Cape Town, Cape Town, South Africa.
- Neuroscience Institute, University of Cape Town, Cape Town, South Africa.
| | - Andrew J Levine
- Department of Neurology, David Geffen School of Medicineat the , University of California, Los Angeles, Los Angeles, CA, USA
| | - Maia Lesosky
- Division of Epidemiology and Biostatistics, School of Public Health & Family Medicine, University of Cape Town, Cape Town, South Africa
| | - Nicole Phillips
- SA MRC Unit On Risk & Resilience in Mental Disorders, Department of Psychiatry and Mental Health, University of Cape Town, Cape Town, South Africa
- Neuroscience Institute, University of Cape Town, Cape Town, South Africa
| | - Jean-Paul Fouche
- SA MRC Unit On Risk & Resilience in Mental Disorders, Department of Psychiatry and Mental Health, University of Cape Town, Cape Town, South Africa
- Neuroscience Institute, University of Cape Town, Cape Town, South Africa
| | - Landon Myer
- Centre for Infectious Disease Epidemiology and Research, Division of Epidemiology and Biostatistics, School of Public Health & Family Medicine, University of Cape Town, Cape Town, South Africa
| | - Heather J Zar
- Department of Paediatrics and Child Health, Red Cross War Memorial Children's Hospital, Cape Town, South Africa
- Medical Research Council Unit On Child and Adolescent Health, University of Cape Town, Cape Town, South Africa
| | - Dan J Stein
- SA MRC Unit On Risk & Resilience in Mental Disorders, Department of Psychiatry and Mental Health, University of Cape Town, Cape Town, South Africa
- Neuroscience Institute, University of Cape Town, Cape Town, South Africa
| | - Steve Horvath
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Biostatistics, School of Public Health, University of California, Los Angeles, Los Angeles, CA, USA
| | - Jacqueline Hoare
- SA MRC Unit On Risk & Resilience in Mental Disorders, Department of Psychiatry and Mental Health, University of Cape Town, Cape Town, South Africa
- Neuroscience Institute, University of Cape Town, Cape Town, South Africa
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99
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Milicic L, Porter T, Vacher M, Laws SM. Utility of DNA Methylation as a Biomarker in Aging and Alzheimer's Disease. J Alzheimers Dis Rep 2023; 7:475-503. [PMID: 37313495 PMCID: PMC10259073 DOI: 10.3233/adr-220109] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2022] [Accepted: 04/23/2023] [Indexed: 06/15/2023] Open
Abstract
Epigenetic mechanisms such as DNA methylation have been implicated in a number of diseases including cancer, heart disease, autoimmune disorders, and neurodegenerative diseases. While it is recognized that DNA methylation is tissue-specific, a limitation for many studies is the ability to sample the tissue of interest, which is why there is a need for a proxy tissue such as blood, that is reflective of the methylation state of the target tissue. In the last decade, DNA methylation has been utilized in the design of epigenetic clocks, which aim to predict an individual's biological age based on an algorithmically defined set of CpGs. A number of studies have found associations between disease and/or disease risk with increased biological age, adding weight to the theory of increased biological age being linked with disease processes. Hence, this review takes a closer look at the utility of DNA methylation as a biomarker in aging and disease, with a particular focus on Alzheimer's disease.
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Affiliation(s)
- Lidija Milicic
- Centre for Precision Health, Edith Cowan University, Joondalup, Western Australia, Australia
- Collaborative Genomics and Translation Group, Edith Cowan University, Joondalup, Western Australia, Australia
- School of Medical and Health Sciences, Edith Cowan University, Joondalup, Western Australia, Australia
| | - Tenielle Porter
- Centre for Precision Health, Edith Cowan University, Joondalup, Western Australia, Australia
- Collaborative Genomics and Translation Group, Edith Cowan University, Joondalup, Western Australia, Australia
- School of Medical and Health Sciences, Edith Cowan University, Joondalup, Western Australia, Australia
- Curtin Medical School, Curtin University, Bentley, Western Australia, Australia
| | - Michael Vacher
- Centre for Precision Health, Edith Cowan University, Joondalup, Western Australia, Australia
- CSIRO Health and Biosecurity, Australian e-Health Research Centre, Floreat, Western Australia
| | - Simon M. Laws
- Centre for Precision Health, Edith Cowan University, Joondalup, Western Australia, Australia
- Collaborative Genomics and Translation Group, Edith Cowan University, Joondalup, Western Australia, Australia
- School of Medical and Health Sciences, Edith Cowan University, Joondalup, Western Australia, Australia
- Curtin Medical School, Curtin University, Bentley, Western Australia, Australia
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100
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Carlund O, Norberg A, Osterman P, Landfors M, Degerman S, Hultdin M. DNA methylation variations and epigenetic aging in telomere biology disorders. Sci Rep 2023; 13:7955. [PMID: 37193737 DOI: 10.1038/s41598-023-34922-1] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2023] [Accepted: 05/10/2023] [Indexed: 05/18/2023] Open
Abstract
Telomere Biology Disorders (TBDs) are characterized by mutations in telomere-related genes leading to short telomeres and premature aging but with no strict correlation between telomere length and disease severity. Epigenetic alterations are also markers of aging and we aimed to evaluate whether DNA methylation (DNAm) could be part of the pathogenesis of TBDs. In blood from 35 TBD cases, genome-wide DNAm were analyzed and the cases were grouped based on relative telomere length (RTL): short (S), with RTL close to normal controls, and extremely short (ES). TBD cases had increased epigenetic age and DNAm alterations were most prominent in the ES-RTL group. Thus, the differentially methylated (DM) CpG sites could be markers of short telomeres but could also be one of the mechanisms contributing to disease phenotype since DNAm alterations were observed in symptomatic, but not asymptomatic, cases with S-RTL. Furthermore, two or more DM-CpGs were identified in four genes previously linked to TBD or telomere length (PRDM8, SMC4, VARS, and WNT6) and in three genes that were novel in telomere biology (MAS1L, NAV2, and TM4FS1). The DM-CpGs in these genes could be markers of aging in hematological cells, but they could also be of relevance for the progression of TBD.
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Affiliation(s)
- Olivia Carlund
- Department of Medical Biosciences, Pathology, Umeå University, Umeå, Sweden
| | - Anna Norberg
- Department of Medical Biosciences, Medical and Clinical Genetics, Umeå University, Umeå, Sweden
| | - Pia Osterman
- Department of Medical Biosciences, Pathology, Umeå University, Umeå, Sweden
| | - Mattias Landfors
- Department of Medical Biosciences, Pathology, Umeå University, Umeå, Sweden
| | - Sofie Degerman
- Department of Medical Biosciences, Pathology, Umeå University, Umeå, Sweden
- Department of Clinical Microbiology, Umeå University, Umeå, Sweden
| | - Magnus Hultdin
- Department of Medical Biosciences, Pathology, Umeå University, Umeå, Sweden.
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