351
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Acton RJ, Yuan W, Gao F, Xia Y, Bourne E, Wozniak E, Bell J, Lillycrop K, Wang J, Dennison E, Harvey NC, Mein CA, Spector TD, Hysi PG, Cooper C, Bell CG. The genomic loci of specific human tRNA genes exhibit ageing-related DNA hypermethylation. Nat Commun 2021; 12:2655. [PMID: 33976121 PMCID: PMC8113476 DOI: 10.1038/s41467-021-22639-6] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2019] [Accepted: 03/05/2021] [Indexed: 02/03/2023] Open
Abstract
The epigenome has been shown to deteriorate with age, potentially impacting on ageing-related disease. tRNA, while arising from only ˜46 kb (<0.002% genome), is the second most abundant cellular transcript. tRNAs also control metabolic processes known to affect ageing, through core translational and additional regulatory roles. Here, we interrogate the DNA methylation state of the genomic loci of human tRNA. We identify a genomic enrichment for age-related DNA hypermethylation at tRNA loci. Analysis in 4,350 MeDIP-seq peripheral-blood DNA methylomes (16-82 years), identifies 44 and 21 hypermethylating specific tRNAs at study-and genome-wide significance, respectively, contrasting with none hypomethylating. Validation and replication (450k array and independent targeted Bisuphite-sequencing) supported the hypermethylation of this functional unit. Tissue-specificity is a significant driver, although the strongest consistent signals, also independent of major cell-type change, occur in tRNA-iMet-CAT-1-4 and tRNA-Ser-AGA-2-6. This study presents a comprehensive evaluation of the genomic DNA methylation state of human tRNA genes and reveals a discreet hypermethylation with advancing age.
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Affiliation(s)
- Richard J Acton
- William Harvey Research Institute, Barts & The London School of Medicine and Dentistry, Charterhouse Square, Queen Mary University of London, London, UK
- MRC Lifecourse Epidemiology Unit, University of Southampton, Southampton, UK
- Human Development and Health, Institute of Developmental Sciences, University of Southampton, Southampton, UK
| | - Wei Yuan
- Department of Twin Research & Genetic Epidemiology, St Thomas Hospital, King's College London, London, UK
- Institute of Cancer Research, Sutton, UK
| | - Fei Gao
- BGI-Shenzhen, Shenzhen, China
| | | | - Emma Bourne
- Barts & The London Genome Centre, Blizard Institute, Barts & The London School of Medicine and Dentistry, Queen Mary University of London, London, UK
| | - Eva Wozniak
- Barts & The London Genome Centre, Blizard Institute, Barts & The London School of Medicine and Dentistry, Queen Mary University of London, London, UK
| | - Jordana Bell
- Department of Twin Research & Genetic Epidemiology, St Thomas Hospital, King's College London, London, UK
| | - Karen Lillycrop
- Human Development and Health, Institute of Developmental Sciences, University of Southampton, Southampton, UK
| | - Jun Wang
- Shenzhen Digital Life Institute, Shenzhen, Guangdong, China
- iCarbonX, Zhuhai, Guangdong, China
- State Key Laboratory of Quality Research in Chinese Medicine, Macau University of Science and Technology, Taipa, Macau, China
| | - Elaine Dennison
- MRC Lifecourse Epidemiology Unit, University of Southampton, Southampton, UK
| | - Nicholas C Harvey
- MRC Lifecourse Epidemiology Unit, University of Southampton, Southampton, UK
| | - Charles A Mein
- Barts & The London Genome Centre, Blizard Institute, Barts & The London School of Medicine and Dentistry, Queen Mary University of London, London, UK
| | - Tim D Spector
- Department of Twin Research & Genetic Epidemiology, St Thomas Hospital, King's College London, London, UK
| | - Pirro G Hysi
- Department of Twin Research & Genetic Epidemiology, St Thomas Hospital, King's College London, London, UK
| | - Cyrus Cooper
- MRC Lifecourse Epidemiology Unit, University of Southampton, Southampton, UK
| | - Christopher G Bell
- William Harvey Research Institute, Barts & The London School of Medicine and Dentistry, Charterhouse Square, Queen Mary University of London, London, UK.
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352
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Parveen N, Dhawan S. DNA Methylation Patterning and the Regulation of Beta Cell Homeostasis. Front Endocrinol (Lausanne) 2021; 12:651258. [PMID: 34025578 PMCID: PMC8137853 DOI: 10.3389/fendo.2021.651258] [Citation(s) in RCA: 22] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/09/2021] [Accepted: 04/21/2021] [Indexed: 12/14/2022] Open
Abstract
Pancreatic beta cells play a central role in regulating glucose homeostasis by secreting the hormone insulin. Failure of beta cells due to reduced function and mass and the resulting insulin insufficiency can drive the dysregulation of glycemic control, causing diabetes. Epigenetic regulation by DNA methylation is central to shaping the gene expression patterns that define the fully functional beta cell phenotype and regulate beta cell growth. Establishment of stage-specific DNA methylation guides beta cell differentiation during fetal development, while faithful restoration of these signatures during DNA replication ensures the maintenance of beta cell identity and function in postnatal life. Lineage-specific transcription factor networks interact with methylated DNA at specific genomic regions to enhance the regulatory specificity and ensure the stability of gene expression patterns. Recent genome-wide DNA methylation profiling studies comparing islets from diabetic and non-diabetic human subjects demonstrate the perturbation of beta cell DNA methylation patterns, corresponding to the dysregulation of gene expression associated with mature beta cell state in diabetes. This article will discuss the molecular underpinnings of shaping the islet DNA methylation landscape, its mechanistic role in the specification and maintenance of the functional beta cell phenotype, and its dysregulation in diabetes. We will also review recent advances in utilizing beta cell specific DNA methylation patterns for the development of biomarkers for diabetes, and targeting DNA methylation to develop translational approaches for supplementing the functional beta cell mass deficit in diabetes.
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Affiliation(s)
| | - Sangeeta Dhawan
- Department of Translational Research and Cellular Therapeutics, Arthur Riggs Diabetes and Metabolism Research Institute, City of Hope, Duarte, CA, United States
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353
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Abstract
The human lifespan and quality of life depend on complex interactions among genetic, environmental, and lifestyle factors. Aging research has been remarkably advanced by the development of high-throughput "omics" technologies. Differences between chronological and biological ages, and identification of factors (eg, nutrition) that modulate the rate of aging can now be assessed at the individual level on the basis of telomere length, the epigenome, and the metabolome. Nevertheless, the understanding of the different responses of people to dietary factors, which is the focus of precision nutrition research, remains incomplete. The lack of reliable dietary assessment methods constitutes a significant challenge in nutrition research, especially in elderly populations. For practical and successful personalized diet advice, big data techniques are needed to analyze and integrate the relevant omics (ie, genomic, epigenomic, metabolomics) with an objective and longitudinal capture of individual nutritional and environmental information. Application of such techniques will provide the scientific evidence and knowledge needed to offer actionable, personalized health recommendations to transform the promise of personalized nutrition into reality.
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Affiliation(s)
- Jose M Ordovas
- Nutrition and Genomics Laboratory, JM-USDA-HNRCA at Tufts University, Boston, Massachusetts, USA
| | - Silvia Berciano
- Nutrition and Genomics Laboratory, JM-USDA-HNRCA at Tufts University, Boston, Massachusetts, USA
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354
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Teeuw J, Ori APS, Brouwer RM, de Zwarte SMC, Schnack HG, Hulshoff Pol HE, Ophoff RA. Accelerated aging in the brain, epigenetic aging in blood, and polygenic risk for schizophrenia. Schizophr Res 2021; 231:189-197. [PMID: 33882370 DOI: 10.1016/j.schres.2021.04.005] [Citation(s) in RCA: 27] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/13/2020] [Revised: 03/02/2021] [Accepted: 04/07/2021] [Indexed: 02/07/2023]
Abstract
Schizophrenia patients show signs of accelerated aging in cognitive and physiological domains. Both schizophrenia and accelerated aging, as measured by MRI brain images and epigenetic clocks, are correlated with increased mortality. However, the association between these aging measures have not yet been studied in schizophrenia patients. In schizophrenia patients and healthy subjects, accelerated aging was assessed in brain tissue using a longitudinal MRI (N = 715 scans; mean scan interval 3.4 year) and in blood using two epigenetic age clocks (N = 172). Differences ('gaps') between estimated ages and chronological ages were calculated, as well as the acceleration rate of brain aging. The correlations between these aging measures as well as with polygenic risk scores for schizophrenia (PRS; N = 394) were investigated. Brain aging and epigenetic aging were not significantly correlated. Polygenic risk for schizophrenia was significantly correlated with brain age gap, brain age acceleration rate, and negatively correlated with DNAmAge gap, but not with PhenoAge gap. However, after controlling for disease status and multiple comparisons correction, these effects were no longer significant. Our results imply that the (accelerated) aging observed in the brain and blood reflect distinct biological processes. Our findings will require replication in a larger cohort.
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Affiliation(s)
- Jalmar Teeuw
- Department of Psychiatry, UMC Brain Center, University Medical Center Utrecht, Utrecht, the Netherlands.
| | - Anil P S Ori
- Center for Neurobehavioral Genetics, University of California, Los Angeles, United States
| | - Rachel M Brouwer
- Department of Psychiatry, UMC Brain Center, University Medical Center Utrecht, Utrecht, the Netherlands
| | - Sonja M C de Zwarte
- Department of Psychiatry, UMC Brain Center, University Medical Center Utrecht, Utrecht, the Netherlands
| | - Hugo G Schnack
- Department of Psychiatry, UMC Brain Center, University Medical Center Utrecht, Utrecht, the Netherlands
| | - Hilleke E Hulshoff Pol
- Department of Psychiatry, UMC Brain Center, University Medical Center Utrecht, Utrecht, the Netherlands
| | - Roel A Ophoff
- Center for Neurobehavioral Genetics, University of California, Los Angeles, United States; Department of Psychiatry, Erasmus University Medical Center, Rotterdam, the Netherlands
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355
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González-Rodríguez P, Cheray M, Füllgrabe J, Salli M, Engskog-Vlachos P, Keane L, Cunha V, Lupa A, Li W, Ma Q, Dreij K, Rosenfeld MG, Joseph B. The DNA methyltransferase DNMT3A contributes to autophagy long-term memory. Autophagy 2021; 17:1259-1277. [PMID: 32876528 PMCID: PMC8143216 DOI: 10.1080/15548627.2020.1816664] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2019] [Revised: 08/18/2020] [Accepted: 08/19/2020] [Indexed: 10/25/2022] Open
Abstract
Macroautophagy/autophagy is a conserved catabolic pathway that targets cytoplasmic components for their degradation and recycling in an autophagosome-dependent lysosomal manner. Under physiological conditions, this process maintains cellular homeostasis. However, autophagy can be stimulated upon different forms of cellular stress, ranging from nutrient starvation to exposure to drugs. Thus, this pathway can be seen as a central component of the integrated and adaptive stress response. Here, we report that even brief induction of autophagy is coupled in vitro to a persistent downregulation of the expression of MAP1LC3 isoforms, which are key components of the autophagy core machinery. In fact, DNA-methylation mediated by de novo DNA methyltransferase DNMT3A of MAP1LC3 loci upon autophagy stimulation leads to the observed long-term decrease of MAP1LC3 isoforms at transcriptional level. Finally, we report that the downregulation of MAP1LC3 expression can be observed in vivo in zebrafish larvae and mice exposed to a transient autophagy stimulus. This epigenetic memory of autophagy provides some understanding of the long-term effect of autophagy induction and offers a possible mechanism for its decline upon aging, pathological conditions, or in response to treatment interventions.Abbreviations: ACTB: actin beta; ATG: autophagy-related; 5-Aza: 5-aza-2'-deoxycytidine; BafA1: bafilomycin A1; CBZ: carbamazepine; CDKN2A: cyclin dependent kinase inhibitor 2A; ChIP: chromatin immunoprecipitation; Clon.: clonidine; CpG: cytosine-guanine dinucleotide: DMSO: dimethyl sulfoxide; DNA: deoxyribonucleic acid; DNMT: DNA methyltransferase; DNMT1: DNA methyltransferase 1; DNMT3A: DNA methyltransferase alpha; DNMT3B: DNA methyltransferase beta; dpf: days post-fertilization; EBSS: Earle's balanced salt solution; EM: Zebrafish embryo medium; GABARAP: GABA type A receptor associated protein; GABARAPL1: GABA type A receptor associated protein like 1; GABARAPL2: GABA type A receptor associated protein like 2; GAPDH: glyceraldehyde-3-phosphate dehydrogenase; GRO-Seq: Global Run-On sequencing; MAP1LC3/LC3: microtubule-associated protein 1 light chain 3; MAP1LC3A: microtubule-associated protein 1 light chain 3 alpha; MAP1LC3B: microtubule-associated protein 1 light chain 3 beta; MAP1LC3B2: microtubule-associated protein 1 light chain 3 beta 2; MEM: minimum essential medium; MEF: mouse embryonic fibroblasts; mRNA: messenger RNA; MTOR: mechanistic target of rapamycin kinase; PBS: phosphate-buffered saline; PIK3C3: phosphatidylinositol 3-kinase catalytic subunit type 3; RB1CC1/FIP200: RB1 inducible coiled-coil 1; RT-qPCR: quantitative reverse transcription polymerase chain reaction; SQSTM1/p62: sequestosome 1; Starv.: starvation; Treh.: trehalose; ULK1: unc-51 like autophagy activating kinase 1.
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Affiliation(s)
- Patricia González-Rodríguez
- Institute of Environmental Medicine, Toxicology Unit, Karolinska Institutet, Stockholm, Sweden
- Department of Oncology-Pathology, Cancer Centrum Karolinska, Karolinska Institutet, Stockholm, Sweden
| | - Mathilde Cheray
- Institute of Environmental Medicine, Toxicology Unit, Karolinska Institutet, Stockholm, Sweden
- Department of Oncology-Pathology, Cancer Centrum Karolinska, Karolinska Institutet, Stockholm, Sweden
| | - Jens Füllgrabe
- Department of Oncology-Pathology, Cancer Centrum Karolinska, Karolinska Institutet, Stockholm, Sweden
- Department of Medical Genetics, Cambridge Institute for Medical Research, University of Cambridge, Cambridge, UK
| | - Maria Salli
- Department of Oncology-Pathology, Cancer Centrum Karolinska, Karolinska Institutet, Stockholm, Sweden
| | | | - Lily Keane
- Institute of Environmental Medicine, Toxicology Unit, Karolinska Institutet, Stockholm, Sweden
| | - Virginia Cunha
- Institute of Environmental Medicine, Biochemical Toxicology Unit, Karolinska Institutet, Stockholm, Sweden
| | - Agata Lupa
- Department of Oncology-Pathology, Cancer Centrum Karolinska, Karolinska Institutet, Stockholm, Sweden
| | - Wenbo Li
- Howard Hughes Medical Institute, Department of Medicine, School of Medicine, University of California, San Diego, California, USA
| | - Qi Ma
- Howard Hughes Medical Institute, Department of Medicine, School of Medicine, University of California, San Diego, California, USA
| | - Kristian Dreij
- Institute of Environmental Medicine, Biochemical Toxicology Unit, Karolinska Institutet, Stockholm, Sweden
| | - Michael G. Rosenfeld
- Howard Hughes Medical Institute, Department of Medicine, School of Medicine, University of California, San Diego, California, USA
| | - Bertrand Joseph
- Institute of Environmental Medicine, Toxicology Unit, Karolinska Institutet, Stockholm, Sweden
- Department of Oncology-Pathology, Cancer Centrum Karolinska, Karolinska Institutet, Stockholm, Sweden
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356
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Pasyukova EG, Symonenko AV, Rybina OY, Vaiserman AM. Epigenetic enzymes: A role in aging and prospects for pharmacological targeting. Ageing Res Rev 2021; 67:101312. [PMID: 33657446 DOI: 10.1016/j.arr.2021.101312] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2020] [Revised: 02/05/2021] [Accepted: 02/25/2021] [Indexed: 02/06/2023]
Abstract
The development of interventions aimed at improving healthspan is one of the priority tasks for the academic and public health authorities. It is also the main objective of a novel branch in biogerontological research, geroscience. According to the geroscience concept, targeting aging is an effective way to combat age-related disorders. Since aging is an exceptionally complex process, system-oriented integrated approaches seem most appropriate for such an interventional strategy. Given the high plasticity and adaptability of the epigenome, epigenome-targeted interventions appear highly promising in geroscience research. Pharmaceuticals targeted at mechanisms involved in epigenetic control of gene activity are actively developed and implemented to prevent and treat various aging-related conditions such as cardiometabolic, neurodegenerative, inflammatory disorders, and cancer. In this review, we describe the roles of epigenetic mechanisms in aging; characterize enzymes contributing to the regulation of epigenetic processes; particularly focus on epigenetic drugs, such as inhibitors of DNA methyltransferases and histone deacetylases that may potentially affect aging-associated diseases and longevity; and discuss possible caveats associated with the use of epigenetic drugs.
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Affiliation(s)
- Elena G Pasyukova
- Institute of Molecular Genetics of National Research Centre "Kurchatov Institute", Kurchatov Sq. 2, Moscow, 123182, Russia
| | - Alexander V Symonenko
- Institute of Molecular Genetics of National Research Centre "Kurchatov Institute", Kurchatov Sq. 2, Moscow, 123182, Russia
| | - Olga Y Rybina
- Institute of Molecular Genetics of National Research Centre "Kurchatov Institute", Kurchatov Sq. 2, Moscow, 123182, Russia; Federal State Budgetary Educational Institution of Higher Education «Moscow Pedagogical State University», M. Pirogovskaya Str. 1/1, Moscow, 119991, Russia
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357
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Dieckmann L, Lahti-Pulkkinen M, Kvist T, Lahti J, DeWitt PE, Cruceanu C, Laivuori H, Sammallahti S, Villa PM, Suomalainen-König S, Eriksson JG, Kajantie E, Raikkönen K, Binder EB, Czamara D. Characteristics of epigenetic aging across gestational and perinatal tissues. Clin Epigenetics 2021; 13:97. [PMID: 33926514 PMCID: PMC8082803 DOI: 10.1186/s13148-021-01080-y] [Citation(s) in RCA: 25] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2021] [Accepted: 04/14/2021] [Indexed: 12/11/2022] Open
Abstract
Background Epigenetic clocks have been used to indicate differences in biological states between individuals of same chronological age. However, so far, only few studies have examined epigenetic aging in newborns—especially regarding different gestational or perinatal tissues. In this study, we investigated which birth- and pregnancy-related variables are most important in predicting gestational epigenetic age acceleration or deceleration (i.e., the deviation between gestational epigenetic age estimated from the DNA methylome and chronological gestational age) in chorionic villus, placenta and cord blood tissues from two independent study cohorts (ITU, n = 639 and PREDO, n = 966). We further characterized the correspondence of epigenetic age deviations between these tissues. Results Among the most predictive factors of epigenetic age deviations in single tissues were child sex, birth length, maternal smoking during pregnancy, maternal mental disorders until childbirth, delivery mode and parity. However, the specific factors related to epigenetic age deviation and the direction of association differed across tissues. In individuals with samples available from more than one tissue, relative epigenetic age deviations were not correlated across tissues. Conclusion Gestational epigenetic age acceleration or deceleration was not related to more favorable or unfavorable factors in one direction in the investigated tissues, and the relative epigenetic age differed between tissues of the same person. This indicates that epigenetic age deviations associate with distinct, tissue specific, factors during the gestational and perinatal period. Our findings suggest that the epigenetic age of the newborn should be seen as a characteristic of a specific tissue, and less as a general characteristic of the child itself. Supplementary Information The online version contains supplementary material available at 10.1186/s13148-021-01080-y.
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Affiliation(s)
- Linda Dieckmann
- Department of Translational Psychiatry, Max Planck Institute of Psychiatry, München, Germany.,International Max Planck Research School for Translational Psychiatry, München, Germany
| | - Marius Lahti-Pulkkinen
- Department of Psychology and Logopedics, Faculty of Medicine, University of Helsinki, Helsinki, Finland.,National Institute for Health and Welfare, Helsinki, Finland.,Centre for Cardiovascular Science, Queen's Medical Research Institute, University of Edinburgh, Edinburgh, UK
| | - Tuomas Kvist
- Department of Psychology and Logopedics, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Jari Lahti
- Department of Psychology and Logopedics, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Peter E DeWitt
- Section of Informatics and Data Science, Department of Pediatrics, University of Colorado School of Medicine, Aurora, CO, USA
| | - Cristiana Cruceanu
- Department of Translational Psychiatry, Max Planck Institute of Psychiatry, München, Germany
| | - Hannele Laivuori
- Institute for Molecular Medicine Finland, HiLIFE, University of Helsinki, Human Genetics, Helsinki, Finland.,Medical and Clinical Genetics, University of Helsinki and Helsinki University Hospital, Helsinki, Finland.,Department of Obstetrics and Gynecology- Faculty of Medicine and Health Technology, Tampere University Hospital and Tampere University, Tampere, Finland
| | - Sara Sammallahti
- Department of Psychology and Logopedics, Faculty of Medicine, University of Helsinki, Helsinki, Finland.,National Institute for Health and Welfare, Helsinki, Finland.,Children's Hospital, Helsinki University Hospital and University of Helsinki, Helsinki, Finland.,Department of Child and Adolescent Psychiatry, Erasmus MC, Sophia Children's Hospital, Rotterdam, The Netherlands
| | - Pia M Villa
- Department of Obstetrics and Gynecology- Faculty of Medicine and Health Technology, Tampere University Hospital and Tampere University, Tampere, Finland.,Department of Obstetrics and Gynecology, Helsinki University Central Hospital, Helsinki, Finland.,Hyvinkää Hospital, Helsinki and Uusimaa Hospital District, Hyvinkää, Finland
| | - Sanna Suomalainen-König
- Medical and Clinical Genetics, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
| | - Johan G Eriksson
- Medical and Clinical Genetics, University of Helsinki and Helsinki University Hospital, Helsinki, Finland.,Folkhälsan Research Center, Helsinki, Finland.,Department of Obstetrics & Gynaecology and Human Potential Translational Research Programme, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore.,Singapore Institute for Clinical Sciences, Agency for Science, Technology and Research (A*STAR), Singapore, Singapore
| | - Eero Kajantie
- National Institute for Health and Welfare, Helsinki, Finland.,Children's Hospital, Helsinki University Hospital and University of Helsinki, Helsinki, Finland.,Faculty of Medicine, PEDEGO Research Unit, MRC Oulu, Oulu University Hospital and University of Oulu, Oulu, Finland.,Department of Clinical and Molecular Medicine, Norwegian University of Science and Technology, Trondheim, Norway
| | - Katri Raikkönen
- Department of Psychology and Logopedics, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Elisabeth B Binder
- Department of Translational Psychiatry, Max Planck Institute of Psychiatry, München, Germany.,Department of Psychiatry and Behavioral Sciences, School of Medicine, Emory University, Atlanta, GA, USA
| | - Darina Czamara
- Department of Translational Psychiatry, Max Planck Institute of Psychiatry, München, Germany.
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358
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Haque HMF, Rafsanjani M, Arifin F, Adilina S, Shatabda S. SubFeat: Feature subspacing ensemble classifier for function prediction of DNA, RNA and protein sequences. Comput Biol Chem 2021; 92:107489. [PMID: 33932779 DOI: 10.1016/j.compbiolchem.2021.107489] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/21/2020] [Revised: 03/07/2021] [Accepted: 04/19/2021] [Indexed: 11/16/2022]
Abstract
The information of a cell is primarily contained in deoxyribonucleic acid (DNA). There is a flow of DNA information to protein sequences via ribonucleic acids (RNA) through transcription and translation. These entities are vital for the genetic process. Recent epigenetics developments also show the importance of the genetic material and knowledge of their attributes and functions. However, the growth in these entities' available features or functionalities is still slow due to the time-consuming and expensive in vitro experimental methods. In this paper, we have proposed an ensemble classification algorithm called SubFeat to predict biological entities' functionalities from different types of datasets. Our model uses a feature subspace-based novel ensemble method. It divides the feature space into sub-spaces, which are then passed to learn individual classifier models. The ensemble is built on these base classifiers that use a weighted majority voting mechanism. SubFeat tested on four datasets comprising two DNA, one RNA, and one protein dataset, and it outperformed all the existing single classifiers and the ensemble classifiers. SubFeat is made available as a Python-based tool. We have made the package SubFeat available online along with a user manual. It is freely accessible from here: https://github.com/fazlulhaquejony/SubFeat.
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Affiliation(s)
- H M Fazlul Haque
- Department of Computer Science and Engineering, United International University, United City, Madani Avenue, Badda, Dhaka 1212, Bangladesh
| | - Muhammod Rafsanjani
- Department of Computer Science and Engineering, United International University, United City, Madani Avenue, Badda, Dhaka 1212, Bangladesh
| | - Fariha Arifin
- Department of Computer Science and Engineering, United International University, United City, Madani Avenue, Badda, Dhaka 1212, Bangladesh
| | - Sheikh Adilina
- Department of Computer Science and Engineering, United International University, United City, Madani Avenue, Badda, Dhaka 1212, Bangladesh
| | - Swakkhar Shatabda
- Department of Computer Science and Engineering, United International University, United City, Madani Avenue, Badda, Dhaka 1212, Bangladesh.
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359
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Clemens Z, Sivakumar S, Pius A, Sahu A, Shinde S, Mamiya H, Luketich N, Cui J, Dixit P, Hoeck JD, Kreuz S, Franti M, Barchowsky A, Ambrosio F. The biphasic and age-dependent impact of klotho on hallmarks of aging and skeletal muscle function. eLife 2021; 10:e61138. [PMID: 33876724 PMCID: PMC8118657 DOI: 10.7554/elife.61138] [Citation(s) in RCA: 25] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2020] [Accepted: 04/06/2021] [Indexed: 12/15/2022] Open
Abstract
Aging is accompanied by disrupted information flow, resulting from accumulation of molecular mistakes. These mistakes ultimately give rise to debilitating disorders including skeletal muscle wasting, or sarcopenia. To derive a global metric of growing 'disorderliness' of aging muscle, we employed a statistical physics approach to estimate the state parameter, entropy, as a function of genes associated with hallmarks of aging. Escalating network entropy reached an inflection point at old age, while structural and functional alterations progressed into oldest-old age. To probe the potential for restoration of molecular 'order' and reversal of the sarcopenic phenotype, we systemically overexpressed the longevity protein, Klotho, via AAV. Klotho overexpression modulated genes representing all hallmarks of aging in old and oldest-old mice, but pathway enrichment revealed directions of changes were, for many genes, age-dependent. Functional improvements were also age-dependent. Klotho improved strength in old mice, but failed to induce benefits beyond the entropic tipping point.
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Affiliation(s)
- Zachary Clemens
- Department of Physical Medicine & Rehabilitation, University of PittsburghPittsburghUnited States
- Department of Environmental and Occupational Health, University of PittsburghPittsburghUnited States
| | - Sruthi Sivakumar
- Department of Physical Medicine & Rehabilitation, University of PittsburghPittsburghUnited States
- Department of Bioengineering, University of PittsburghPittsburghUnited States
| | - Abish Pius
- Department of Physical Medicine & Rehabilitation, University of PittsburghPittsburghUnited States
- Department of Computational & Systems Biology, School of Medicine, University of PittsburghPittsburghUnited States
| | - Amrita Sahu
- Department of Physical Medicine & Rehabilitation, University of PittsburghPittsburghUnited States
| | - Sunita Shinde
- Department of Physical Medicine & Rehabilitation, University of PittsburghPittsburghUnited States
| | - Hikaru Mamiya
- Department of Bioengineering, University of PittsburghPittsburghUnited States
| | - Nathaniel Luketich
- Department of Bioengineering, University of PittsburghPittsburghUnited States
| | - Jian Cui
- Department of Computational & Systems Biology, School of Medicine, University of PittsburghPittsburghUnited States
| | - Purushottam Dixit
- Department of Physics, University of FloridaGainesvilleUnited States
| | - Joerg D Hoeck
- Department of Research Beyond Borders, Regenerative Medicine, Boehringer Ingelheim Pharmaceuticals, IncRheinGermany
| | - Sebastian Kreuz
- Department of Research Beyond Borders, Regenerative Medicine, Boehringer Ingelheim Pharmaceuticals, IncRheinGermany
| | - Michael Franti
- Department of Research Beyond Borders, Regenerative Medicine, Boehringer Ingelheim Pharmaceuticals, IncRheinGermany
| | - Aaron Barchowsky
- Department of Environmental and Occupational Health, University of PittsburghPittsburghUnited States
| | - Fabrisia Ambrosio
- Department of Physical Medicine & Rehabilitation, University of PittsburghPittsburghUnited States
- Department of Environmental and Occupational Health, University of PittsburghPittsburghUnited States
- Department of Bioengineering, University of PittsburghPittsburghUnited States
- McGowan Institute for Regenerative Medicine, University of PittsburghPittsburghUnited States
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360
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Ageing affects subtelomeric DNA methylation in blood cells from a large European population enrolled in the MARK-AGE study. GeroScience 2021; 43:1283-1302. [PMID: 33870444 PMCID: PMC8190237 DOI: 10.1007/s11357-021-00347-9] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2020] [Accepted: 02/23/2021] [Indexed: 11/23/2022] Open
Abstract
Ageing leaves characteristic traces in the DNA methylation make-up of the genome. However, the importance of DNA methylation in ageing remains unclear. The study of subtelomeric regions could give promising insights into this issue. Previously reported associations between susceptibility to age-related diseases and epigenetic instability at subtelomeres suggest that the DNA methylation profile of subtelomeres undergoes remodelling during ageing. In the present work, this hypothesis has been tested in the context of the European large-scale project MARK-AGE. In this cross-sectional study, we profiled the DNA methylation of chromosomes 5 and 21 subtelomeres, in more than 2000 age-stratified women and men recruited in eight European countries. The study included individuals from the general population as well as the offspring of nonagenarians and Down syndrome subjects, who served as putative models of delayed and accelerated ageing, respectively. Significant linear changes of subtelomeric DNA methylation with increasing age were detected in the general population, indicating that subtelomeric DNA methylation changes are typical signs of ageing. Data also show that, compared to the general population, the dynamics of age-related DNA methylation changes are attenuated in the offspring of centenarian, while they accelerate in Down syndrome individuals. This result suggests that subtelomeric DNA methylation changes reflect the rate of ageing progression. We next attempted to trace the age-related changes of subtelomeric methylation back to the influence of diverse variables associated with methylation variations in the population, including demographics, dietary/health habits and clinical parameters. Results indicate that the effects of age on subtelomeric DNA methylation are mostly independent of all other variables evaluated.
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361
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Rytel MR, Butler R, Eliot M, Braun JM, Houseman EA, Kelsey KT. DNA methylation in the adipose tissue and whole blood of Agent Orange-exposed Operation Ranch Hand veterans: a pilot study. Environ Health 2021; 20:43. [PMID: 33849548 PMCID: PMC8045317 DOI: 10.1186/s12940-021-00717-y] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2020] [Accepted: 03/08/2021] [Indexed: 05/26/2023]
Abstract
BACKGROUND Between 1962 and 1971, the US Air Force sprayed Agent Orange across Vietnam, exposing many soldiers to this dioxin-containing herbicide. Several negative health outcomes have been linked to Agent Orange exposure, but data is lacking on the effects this chemical has on the genome. Therefore, we sought to characterize the impact of Agent Orange exposure on DNA methylation in the whole blood and adipose tissue of veterans enrolled in the Air Force Health Study (AFHS). METHODS We received adipose tissue (n = 37) and whole blood (n = 42) from veterans in the AFHS. Study participants were grouped as having low, moderate, or high TCDD body burden based on their previously measured serum levels of dioxin. DNA methylation was assessed using the Illumina 450 K platform. RESULTS Epigenome-wide analysis indicated that there were no FDR-significantly methylated CpGs in either tissue with TCDD burden. However, 3 CpGs in the adipose tissue (contained within SLC9A3, LYNX1, and TNRC18) were marginally significantly (q < 0.1) hypomethylated, and 1 CpG in whole blood (contained within PTPRN2) was marginally significantly (q < 0.1) hypermethylated with high TCDD burden. Analysis for differentially methylated DNA regions yielded SLC9A3, among other regions in adipose tissue, to be significantly differentially methylated with higher TCDD burden. Comparing whole blood data to a study of dioxin exposed adults from Alabama identified a CpG within the gene SMO that was hypomethylated with dioxin exposure in both studies. CONCLUSION We found limited evidence of dioxin associated DNA methylation in adipose tissue and whole blood in this pilot study of Vietnam War veterans. Nevertheless, loci in the genes of SLC9A3 in adipose tissue, and PTPRN2 and SMO in whole blood, should be included in future exposure analyses.
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Affiliation(s)
- Matthew R. Rytel
- Department of Epidemiology, Brown University School of Public Health, Providence, RI 02912 USA
| | - Rondi Butler
- Department of Epidemiology, Brown University School of Public Health, Providence, RI 02912 USA
- Department of Pathology and Laboratory Medicine, Brown University School of Public Health, Providence, RI 02912 USA
| | - Melissa Eliot
- Department of Epidemiology, Brown University School of Public Health, Providence, RI 02912 USA
| | - Joseph M. Braun
- Department of Epidemiology, Brown University School of Public Health, Providence, RI 02912 USA
| | - E. Andres Houseman
- Statistical Bioinformatics, GlaxoSmithKline, 1250 S Collegeville Rd, Collegeville, PA 19426 USA
| | - Karl T. Kelsey
- Department of Epidemiology, Brown University School of Public Health, Providence, RI 02912 USA
- Department of Pathology and Laboratory Medicine, Brown University School of Public Health, Providence, RI 02912 USA
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362
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Hillary RF, Marioni RE. MethylDetectR: a software for methylation-based health profiling. Wellcome Open Res 2021; 5:283. [PMID: 33969230 PMCID: PMC8080939 DOI: 10.12688/wellcomeopenres.16458.2] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 04/01/2021] [Indexed: 12/23/2022] Open
Abstract
DNA methylation is an important biological process that involves the reversible addition of chemical tags called methyl groups to DNA and affects whether genes are active or inactive. Individual methylation profiles are determined by both genetic and environmental influences. Inter-individual variation in DNA methylation profiles can be exploited to estimate or predict a wide variety of human characteristics and disease risk profiles. Indeed, a number of methylation-based predictors of human traits have been developed and linked to important health outcomes. However, there is an unmet need to communicate the applicability and limitations of state-of-the-art methylation-based predictors to the wider community. To address this need, we have created a secure, web-based interactive platform called 'MethylDetectR' which automates the calculation of estimated values or scores for a variety of human traits using blood methylation data. These traits include age, lifestyle traits and high-density lipoprotein cholesterol. Methylation-based predictors often return scores on arbitrary scales. To provide meaning to these scores, users can interactively view how estimated trait scores for a given individual compare against other individuals in the sample. Users can optionally upload binary phenotypes and investigate how estimated traits vary according to case vs. control status for these phenotypes. Users can also view how different methylation-based predictors correlate with one another, and with phenotypic values for corresponding traits in a large reference sample (n = 4,450; Generation Scotland). The 'MethylDetectR' platform allows for the fast and secure calculation of DNA methylation-derived estimates for several human traits. This platform also helps to show the correlations between methylation-based scores and corresponding traits at the level of a sample, report estimated health profiles at an individual level, demonstrate how scores relate to important binary outcomes of interest and highlight the current limitations of molecular health predictors.
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Affiliation(s)
- Robert F. Hillary
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, Midlothian, EH4 2XU, UK
| | - Riccardo E. Marioni
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, Midlothian, EH4 2XU, UK
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363
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Petryk N, Bultmann S, Bartke T, Defossez PA. Staying true to yourself: mechanisms of DNA methylation maintenance in mammals. Nucleic Acids Res 2021; 49:3020-3032. [PMID: 33300031 PMCID: PMC8034647 DOI: 10.1093/nar/gkaa1154] [Citation(s) in RCA: 39] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2020] [Revised: 11/06/2020] [Accepted: 11/11/2020] [Indexed: 12/16/2022] Open
Abstract
DNA methylation is essential to development and cellular physiology in mammals. Faulty DNA methylation is frequently observed in human diseases like cancer and neurological disorders. Molecularly, this epigenetic mark is linked to other chromatin modifications and it regulates key genomic processes, including transcription and splicing. Each round of DNA replication generates two hemi-methylated copies of the genome. These must be converted back to symmetrically methylated DNA before the next S-phase, or the mark will fade away; therefore the maintenance of DNA methylation is essential. Mechanistically, the maintenance of this epigenetic modification takes place during and after DNA replication, and occurs within the very dynamic context of chromatin re-assembly. Here, we review recent discoveries and unresolved questions regarding the mechanisms, dynamics and fidelity of DNA methylation maintenance in mammals. We also discuss how it could be regulated in normal development and misregulated in disease.
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Affiliation(s)
- Nataliya Petryk
- Epigenetics and Cell Fate Centre, UMR7216 CNRS, Université de Paris, F-75013 Paris, France
| | - Sebastian Bultmann
- Department of Biology II, Human Biology and BioImaging, Ludwig-Maximilians-Universität München, 80539 Munich, Germany
| | - Till Bartke
- Institute of Functional Epigenetics, Helmholtz Zentrum München, 85764 Neuherberg, Germany
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364
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Nwanaji-Enwerem JC, Jackson CL, Ottinger MA, Cardenas A, James KA, Malecki KM, Chen JC, Geller AM, Mitchell UA. Adopting a "Compound" Exposome Approach in Environmental Aging Biomarker Research: A Call to Action for Advancing Racial Health Equity. ENVIRONMENTAL HEALTH PERSPECTIVES 2021; 129:45001. [PMID: 33822649 PMCID: PMC8043128 DOI: 10.1289/ehp8392] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/02/2020] [Revised: 02/24/2021] [Accepted: 03/15/2021] [Indexed: 05/02/2023]
Abstract
BACKGROUND In June 2020, the National Academies of Sciences, Engineering, and Medicine hosted a virtual workshop focused on integrating the science of aging and environmental health research. The concurrent COVID-19 pandemic and national attention on racism exposed shortcomings in the environmental research field's conceptualization and methodological use of race, which have subsequently hindered the ability of research to address racial health disparities. By the workshop's conclusion, the authors deduced that the utility of environmental aging biomarkers-aging biomarkers shown to be specifically influenced by environmental exposures-would be greatly diminished if these biomarkers are developed absent of considerations of broader societal factors-like structural racism-that impinge on racial health equity. OBJECTIVES The authors reached a post-workshop consensus recommendation: To advance racial health equity, a "compound" exposome approach should be widely adopted in environmental aging biomarker research. We present this recommendation here. DISCUSSION The authors believe that without explicit considerations of racial health equity, people in most need of the benefits afforded by a better understanding of the relationships between exposures and aging will be the least likely to receive them because biomarkers may not encompass cumulative impacts from their unique social and environmental stressors. Employing an exposome approach that allows for more comprehensive exposure-disease pathway characterization across broad domains, including the social exposome and neighborhood factors, is the first step. Exposome-centered study designs must then be supported with efforts aimed at increasing the recruitment and retention of racially diverse study populations and researchers and further "compounded" with strategies directed at improving the use and interpretation of race throughout the publication and dissemination process. This compound exposome approach maximizes the ability of our science to identify environmental aging biomarkers that explicate racial disparities in health and best positions the environmental research community to contribute to the elimination of racial health disparities. https://doi.org/10.1289/EHP8392.
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Affiliation(s)
- Jamaji C. Nwanaji-Enwerem
- Department of Environmental Health, Harvard T.H. Chan School of Public Health and MD/PhD Program, Harvard Medical School, Boston, Massachusetts, USA
- Division of Environmental Health Sciences, School of Public Health and Center for Computational Biology, University of California, Berkeley, Berkeley, California, USA
| | - Chandra L. Jackson
- Epidemiology Branch, National Institute of Environmental Health Sciences, National Institutes of Health (NIH), U.S. Department of Health and Human Services (U.S. HHS), Research Triangle Park, North Carolina, USA
- Intramural Program, National Institute on Minority Health and Health Disparities, NIH, U.S. HHS, Bethesda, Maryland, USA
| | - Mary Ann Ottinger
- Department of Biology and Biochemistry, University of Houston, Houston, Texas USA
| | - Andres Cardenas
- Division of Environmental Health Sciences, School of Public Health and Center for Computational Biology, University of California, Berkeley, Berkeley, California, USA
| | - Katherine A. James
- Department of Environmental and Occupational Health, Colorado School of Public Health, University of Colorado Anschutz Medical Campus, Aurora, Colorado, USA
| | - Kristen M.C. Malecki
- Department of Population Health Sciences, University of Wisconsin Madison School of Medicine and Public Health, Madison, Wisconsin, USA
| | - Jiu-Chiuan Chen
- Departments of Preventive Medicine and Neurology, Keck School of Medicine, University of Southern California, Los Angeles, California, USA
| | - Andrew M. Geller
- Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, North Carolina, USA
| | - Uchechi A. Mitchell
- Division of Community Health Sciences, School of Public Health, University of Illinois at Chicago, Chicago, Illinois, USA
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365
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Groen K, Lechner-Scott J, Pohl D, Levy M, Giovannoni G, Hawkes C. Can serum glial fibrillary acidic protein (GFAP) solve the longstanding problem of diagnosis and monitoring progressive multiple sclerosis. Mult Scler Relat Disord 2021; 50:102931. [PMID: 33926692 DOI: 10.1016/j.msard.2021.102931] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Affiliation(s)
- Kira Groen
- Hunter Medical Researc Institute, University of Newcastle, Australia; Hunter New England Area Health.
| | - Jeannette Lechner-Scott
- Hunter Medical Researc Institute, University of Newcastle, Australia; Hunter New England Area Health.
| | | | | | - Gavin Giovannoni
- Department of Neurology, Blizard Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London.
| | - Chris Hawkes
- Department of Neurology, Queen Mary University London, Neuroscience Centre.
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366
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Hannon E, Mansell G, Walker E, Nabais MF, Burrage J, Kepa A, Best-Lane J, Rose A, Heck S, Moffitt TE, Caspi A, Arseneault L, Mill J. Assessing the co-variability of DNA methylation across peripheral cells and tissues: Implications for the interpretation of findings in epigenetic epidemiology. PLoS Genet 2021; 17:e1009443. [PMID: 33739972 PMCID: PMC8011804 DOI: 10.1371/journal.pgen.1009443] [Citation(s) in RCA: 25] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2020] [Revised: 03/31/2021] [Accepted: 02/23/2021] [Indexed: 02/01/2023] Open
Abstract
Most epigenome-wide association studies (EWAS) quantify DNA methylation (DNAm) in peripheral tissues such as whole blood to identify positions in the genome where variation is statistically associated with a trait or exposure. As whole blood comprises a mix of cell types, it is unclear whether trait-associated DNAm variation is specific to an individual cellular population. We collected three peripheral tissues (whole blood, buccal epithelial and nasal epithelial cells) from thirty individuals. Whole blood samples were subsequently processed using fluorescence-activated cell sorting (FACS) to purify five constituent cell-types (monocytes, granulocytes, CD4+ T cells, CD8+ T cells, and B cells). DNAm was profiled in all eight sample-types from each individual using the Illumina EPIC array. We identified significant differences in both the level and variability of DNAm between different sample types, and DNAm data-derived estimates of age and smoking were found to differ dramatically across sample types from the same individual. We found that for the majority of loci variation in DNAm in individual blood cell types was only weakly predictive of variance in DNAm measured in whole blood, although the proportion of variance explained was greater than that explained by either buccal or nasal epithelial samples. Covariation across sample types was much higher for DNAm sites influenced by genetic factors. Overall, we observe that DNAm variation in whole blood is additively influenced by a combination of the major blood cell types. For a subset of sites, however, variable DNAm detected in whole blood can be attributed to variation in a single blood cell type providing potential mechanistic insight about EWAS findings. Our results suggest that associations between whole blood DNAm and traits or exposures reflect differences in multiple cell types and our data will facilitate the interpretation of findings in epigenetic epidemiology. As epigenetic variation is cell-type specific, an ongoing challenge in epigenetic epidemiology is how to interpret studies performed using bulk tissue (for example, whole blood) which comprises a mix of different cell types. In this study, we identified major differences in DNA methylation (DNAm) across multiple peripheral tissues and different blood cell types, with each sample type being characterized by a unique signature across multiple genomic loci. We demonstrate how these differences influence commonly used prediction scores derived from DNAm data for age and tobacco smoking, with estimates for the same individual being highly variable across tissues and cell types. Our results enabled us to assess the extent to which variable DNAm in each individual blood cell type relates to variation measured in whole blood. We found that although individual blood cell types predict more of the variation in DNAm in whole blood compared to buccal and nasal epithelial cells, the actual proportion of variance explained is relatively small, except for at sites where DNAm is under genetic control. Our data indicate that for most sites variation in multiple blood cell types additively combines to drive variation in DNAm measured in whole blood. Of note, for a subset of sites, variation in DNAm detected in whole blood can be attributed to a specific blood cell type, potentially facilitating the interpretation of EWAS findings.
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Affiliation(s)
- Eilis Hannon
- University of Exeter Medical School, University of Exeter Medical School, University of Exeter, Exeter, United Kingdom
| | - Georgina Mansell
- University of Exeter Medical School, University of Exeter Medical School, University of Exeter, Exeter, United Kingdom
| | - Emma Walker
- University of Exeter Medical School, University of Exeter Medical School, University of Exeter, Exeter, United Kingdom
| | - Marta F Nabais
- University of Exeter Medical School, University of Exeter Medical School, University of Exeter, Exeter, United Kingdom
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, Australia
| | - Joe Burrage
- University of Exeter Medical School, University of Exeter Medical School, University of Exeter, Exeter, United Kingdom
| | - Agnieszka Kepa
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom
| | - Janis Best-Lane
- Section of Anaesthetics, Pain Medicine and Intensive Care Medicine, Department of Surgery and Cancer, Imperial College London and Imperial College Healthcare NHS Trust, London, United Kingdom
- Imperial Clinical Trials Unit, Imperial College London, London, United Kingdom
| | - Anna Rose
- BRC Flow Cytometry Platform, NIHR GSTT/KCL Comprehensive Biomedical Research Centre, Guy's and St Thomas' NHS Foundation Trust, London, United Kingdom
| | - Suzanne Heck
- Biomedical Research Centre at Guy's and St Thomas' Hospitals and King's College London, Guy's and St Thomas' NHS Foundation Trust, London, United Kingdom
| | - Terrie E Moffitt
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom
- Department of Psychology and Neuroscience, Duke University, Durham, United States of America
- Center for Genomic and Computational Biology, Duke University, Durham, United States of America
- Department of Psychiatry and Behavioral Sciences, Duke University, Durham, NC, United States of America
| | - Avshalom Caspi
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom
- Department of Psychology and Neuroscience, Duke University, Durham, United States of America
- Center for Genomic and Computational Biology, Duke University, Durham, United States of America
- Department of Psychiatry and Behavioral Sciences, Duke University, Durham, NC, United States of America
| | - Louise Arseneault
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom
| | - Jonathan Mill
- University of Exeter Medical School, University of Exeter Medical School, University of Exeter, Exeter, United Kingdom
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367
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The Therapeutic Potential of Epigenome-Modifying Drugs in Cardiometabolic Disease. CURRENT GENETIC MEDICINE REPORTS 2021. [DOI: 10.1007/s40142-021-00198-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/21/2022]
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368
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Cell stretchers and the LINC complex in mechanotransduction. Arch Biochem Biophys 2021; 702:108829. [PMID: 33716002 DOI: 10.1016/j.abb.2021.108829] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2021] [Revised: 02/23/2021] [Accepted: 03/07/2021] [Indexed: 02/07/2023]
Abstract
How cells respond to mechanical forces from the surrounding environment is critical for cell survival and function. The LINC complex is a central component in the mechanotransduction pathway that transmits mechanical information from the cell surface to the nucleus. Through LINC complex functionality, the nucleus is able to respond to mechanical stress by altering nuclear structure, chromatin organization, and gene expression. The use of specialized devices that apply mechanical strain to cells have been central to investigating how mechanotransduction occurs, how cells respond to mechanical stress, and the role of the LINC complexes in these processes. A large variety of designs have been reported for these devices, with the most common type being cell stretchers. Here we highlight some of the salient features of cell stretchers and suggest some key parameters that should be considered when using these devices. We provide a brief overview of how the LINC complexes contribute to the cellular responses to mechanical strain. And finally, we suggest that stretchers may be a useful tool to study aging.
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369
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Health and longevity studies in C. elegans: the "healthy worm database" reveals strengths, weaknesses and gaps of test compound-based studies. Biogerontology 2021; 22:215-236. [PMID: 33683565 PMCID: PMC7973913 DOI: 10.1007/s10522-021-09913-2] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2020] [Accepted: 02/20/2021] [Indexed: 12/11/2022]
Abstract
Several biogerontology databases exist that focus on genetic or gene expression data linked to health as well as survival, subsequent to compound treatments or genetic manipulations in animal models. However, none of these has yet collected experimental results of compound-related health changes. Since quality of life is often regarded as more valuable than length of life, we aim to fill this gap with the “Healthy Worm Database” (http://healthy-worm-database.eu). Literature describing health-related compound studies in the aging model Caenorhabditis elegans was screened, and data for 440 compounds collected. The database considers 189 publications describing 89 different phenotypes measured in 2995 different conditions. Besides enabling a targeted search for promising compounds for further investigations, this database also offers insights into the research field of studies on healthy aging based on a frequently used model organism. Some weaknesses of C. elegans-based aging studies, like underrepresented phenotypes, especially concerning cognitive functions, as well as the convenience-based use of young worms as the starting point for compound treatment or phenotype measurement are discussed. In conclusion, the database provides an anchor for the search for compounds affecting health, with a link to public databases, and it further highlights some potential shortcomings in current aging research.
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370
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Bartke A, Hascup E, Hascup K, Masternak MM. Growth Hormone and Aging: New Findings. World J Mens Health 2021; 39:454-465. [PMID: 33663025 PMCID: PMC8255405 DOI: 10.5534/wjmh.200201] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2020] [Revised: 12/21/2020] [Accepted: 01/02/2021] [Indexed: 01/04/2023] Open
Abstract
Complex relationships between growth hormone (GH) signaling and mammalian aging continue to attract attention of many investigators. Recent results include evidence that the impact of GH on genome maintenance (DNA damage and repair) is drastically different in normal as compared to cancer cells, consistent with GH promoting aging and cancer progression. Impact of GH on DNA methylation was studied as a possible mechanism linking actions of GH during early life to the trajectory of aging. Animals with reduced or enhanced GH signaling and novel animals with adipocyte-specific deletion of GH receptors were used to elucidate the effects of GH on white and brown adipose tissue, including the impact of this hormone on lipolysis, fibrosis, and thermogenesis. Effects of GH on adipose tissue related to lipid and energy metabolism emerge as mechanistic links between GH, healthspan, and lifespan. Treatment of healthy men with a combination of GH, dehydroepiandrosterone, and metformin was reported to restore thymus function and reduce epigenetic age. Studies of human subjects with deficiency of GH or GH receptors and studies of mice with the same endocrine syndromes identified several phenotypic changes related (positively or negatively) to the previously reported predisposition to healthy aging. Results of these and other recent studies advance present understanding of the mechanisms by which GH influences aging and longevity and of the trade-offs involved.
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Affiliation(s)
- Andrzej Bartke
- Department of Internal Medicine, Southern Illinois University School of Medicine, Springfield, IL, USA.
| | - Erin Hascup
- Department of Neurology, Southern Illinois University School of Medicine, Springfield, IL, USA
| | - Kevin Hascup
- Department of Neurology, Southern Illinois University School of Medicine, Springfield, IL, USA
| | - Michal M Masternak
- Burnett School of Biomedical Sciences, College of Medicine, University of Central Florida, Orlando, FL, USA
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371
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Petersen CL, Christensen BC, Batsis JA. Weight management intervention identifies association of decreased DNA methylation age with improved functional age measures in older adults with obesity. Clin Epigenetics 2021; 13:46. [PMID: 33653394 PMCID: PMC7927264 DOI: 10.1186/s13148-021-01031-7] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2020] [Accepted: 02/14/2021] [Indexed: 11/26/2022] Open
Abstract
Background Assessing functional ability is an important component of understanding healthy aging. Objective measures of functional ability include grip strength, gait speed, sit-to-stand time, and 6-min walk distance. Using samples from a weight loss clinical trial in older adults with obesity, we examined the association between changes in physical function and DNA-methylation-based biological age at baseline and 12 weeks in 16 individuals. Peripheral blood DNA methylation was measured (pre/post) with the Illumina HumanMethylationEPIC array and the Hannum, Horvath, and PhenoAge DNA methylation age clocks were used. Linear regression models adjusted for chronological age and sex tested the relationship between DNA methylation age and grip strength, gait speed, sit-to-stand, and 6-min walk. Results Participant mean weight loss was 4.6 kg, and DNA methylation age decreased 0.8, 1.1, and 0.5 years using the Hannum, Horvath, and PhenoAge DNA methylation clocks respectively. Mean grip strength increased 3.2 kg. Decreased Hannum methylation age was significantly associated with increased grip strength (β = −0.30, p = 0.04), and increased gait speed (β = 0.02, p = 0.05), in adjusted models. Similarly, decreased methylation age using the PhenoAge clock was associated with significantly increased gait speed (β = 0.02, p = 0.04). A decrease in Horvath DNA methylation age and increase in physical functional ability did not demonstrate a significant association. Conclusions The observed relationship between increased physical functional ability and decreased biological age using DNA methylation clocks demonstrate the potential utility of DNA methylation clocks to assess interventional approaches to improve health in older obese adults. Trial registration: National Institute on Aging (NIA), NCT03104192. Posted April 7, 2017, https://clinicaltrials.gov/ct2/show/NCT03104192
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Affiliation(s)
- Curtis L Petersen
- The Dartmouth Institute for Health Policy, Williamson Translational Research Bld, 5., 1 Medical Center Drive, Lebanon, NH, 03766, USA. .,Quantitative Biomedical Sciences Program, Dartmouth, Hanover, NH, USA.
| | - Brock C Christensen
- Department of Epidemiology, Geisel School of Medicine at Dartmouth, Lebanon, NH, USA.,Department of Molecular and Systems Biology at Dartmouth, Lebanon, NH, USA
| | - John A Batsis
- The Dartmouth Institute for Health Policy, Williamson Translational Research Bld, 5., 1 Medical Center Drive, Lebanon, NH, 03766, USA.,Department of Medicine, Geisel School of Medicine at Dartmouth, Hanover, NH, USA.,Section of General Internal Medicine, Dartmouth-Hitchcock Medical Center, Lebanon, NH, USA.,Division of Geriatric Medicine, School of Medicine, and Department of Nutrition, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
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372
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Samoylova EM, Baklaushev VP. Cell Reprogramming Preserving Epigenetic Age: Advantages and Limitations. BIOCHEMISTRY (MOSCOW) 2021; 85:1035-1047. [PMID: 33050850 DOI: 10.1134/s0006297920090047] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
Abstract
Our understanding of cell aging advanced significantly since the discovery of this phenomenon by Hayflick and Moorhead in 1961. In addition to the well-known shortening of telomeric regions of chromosomes, cell aging is closely associated with changes of the DNA methylation profile. Establishing, maintaining, or reversing epigenetic age of a cell is central to the technology of cell reprogramming. Two distinct approaches - iPSC- and transdifferentiation-based cell reprogramming - affect differently epigenetic age of the cells. The iPSC-based reprogramming protocols are generally believed to result in the reversion of DNA methylation profiles towards less differentiated states, while the original methylation profiles are preserved in the direct trans-differentiation protocols. Clearly, in order to develop adequate model of CNS pathologies, one has to have thorough understanding of the biological roles of DNA methylation in the development, maintenance of functional activity, tissue and cell diversity, restructuring of neural networks during learning, as well as in aging-associated neuronal decline. Direct cell reprogramming is an excellent alternative and a valuable supplement to the iPSC-based technologies both as a source of mature cells for modeling of neurodegenerative diseases, and as a novel powerful strategy for in vivo cell replacement therapy. Further advancement of the regenerative and personalized medicine will strongly depend on optimization of the production of patient-specific autologous cells involving alternative approaches of direct and indirect cell reprogramming that take into account epigenetic age of the starting cell material.
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Affiliation(s)
- E M Samoylova
- Federal Research Clinical Center, FMBA of Russia, Moscow, 115682, Russia.
| | - V P Baklaushev
- Federal Research Clinical Center, FMBA of Russia, Moscow, 115682, Russia
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373
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Pirazzini C, Azevedo T, Baldelli L, Bartoletti-Stella A, Calandra-Buonaura G, Dal Molin A, Dimitri GM, Doykov I, Gómez-Garre P, Hägg S, Hällqvist J, Halsband C, Heywood W, Jesús S, Jylhävä J, Kwiatkowska KM, Labrador-Espinosa MA, Licari C, Maturo MG, Mengozzi G, Meoni G, Milazzo M, Periñán-Tocino MT, Ravaioli F, Sala C, Sambati L, Schade S, Schreglmann S, Spasov S, Tenori L, Williams D, Xumerle L, Zago E, Bhatia KP, Capellari S, Cortelli P, Garagnani P, Houlden H, Liò P, Luchinat C, Delledonne M, Mills K, Mir P, Mollenhauer B, Nardini C, Pedersen NL, Provini F, Strom S, Trenkwalder C, Turano P, Bacalini MG, Franceschi C. A geroscience approach for Parkinson's disease: Conceptual framework and design of PROPAG-AGEING project. Mech Ageing Dev 2021; 194:111426. [PMID: 33385396 DOI: 10.1016/j.mad.2020.111426] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2020] [Revised: 12/07/2020] [Accepted: 12/22/2020] [Indexed: 12/12/2022]
Abstract
Advanced age is the major risk factor for idiopathic Parkinson's disease (PD), but to date the biological relationship between PD and ageing remains elusive. Here we describe the rationale and the design of the H2020 funded project "PROPAG-AGEING", whose aim is to characterize the contribution of the ageing process to PD development. We summarize current evidences that support the existence of a continuum between ageing and PD and justify the use of a Geroscience approach to study PD. We focus in particular on the role of inflammaging, the chronic, low-grade inflammation characteristic of elderly physiology, which can propagate and transmit both locally and systemically. We then describe PROPAG-AGEING design, which is based on the multi-omic characterization of peripheral samples from clinically characterized drug-naïve and advanced PD, PD discordant twins, healthy controls and "super-controls", i.e. centenarians, who never showed clinical signs of motor disability, and their offspring. Omic results are then validated in a large number of samples, including in vitro models of dopaminergic neurons and healthy siblings of PD patients, who are at higher risk of developing PD, with the final aim of identifying the molecular perturbations that can deviate the trajectories of healthy ageing towards PD development.
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Affiliation(s)
- Chiara Pirazzini
- IRCCS Istituto delle Scienze Neurologiche di Bologna, Bologna, Italy
| | - Tiago Azevedo
- Department of Computer Science and Technology, University of Cambridge, Cambridge, United Kingdom
| | - Luca Baldelli
- Department of Biomedical and NeuroMotor Sciences (DiBiNeM), University of Bologna, Italy
| | | | - Giovanna Calandra-Buonaura
- IRCCS Istituto delle Scienze Neurologiche di Bologna, Bologna, Italy; Department of Biomedical and NeuroMotor Sciences (DiBiNeM), University of Bologna, Italy
| | | | - Giovanna Maria Dimitri
- Department of Computer Science and Technology, University of Cambridge, Cambridge, United Kingdom
| | - Ivan Doykov
- Centre for Inborn Errors of Metabolism, UCL Institute of Child Health, London, United Kingdom
| | - Pilar Gómez-Garre
- Hospital Universitario Virgen del Rocío/CSIC/Universidad de Sevilla, Unidad de Trastornos del Movimiento, Servicio de Neurología y NeurofisiologíaClínica, Instituto de Biomedicina de Sevilla, Seville, Spain; Centro de Investigación Biomédicaen Red sobreEnfermedades Neurodegenerativas (CIBERNED), Spain
| | - Sara Hägg
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Jenny Hällqvist
- Centre for Inborn Errors of Metabolism, UCL Institute of Child Health, London, United Kingdom
| | - Claire Halsband
- Department of Clinical Neurophysiology, University Medical Center Göttingen, Göttingen, Germany; Department of Gerontopsychiatry, Rhein-Mosel-Fachklinik, Andernach, Germany
| | - Wendy Heywood
- Centre for Inborn Errors of Metabolism, UCL Institute of Child Health, London, United Kingdom; NIHR Great Ormond Street Biomedical Research Centre, Great Ormond Street Hospital and UCL Great Ormond Street Institute of Child Health, London, United Kingdom
| | - Silvia Jesús
- Hospital Universitario Virgen del Rocío/CSIC/Universidad de Sevilla, Unidad de Trastornos del Movimiento, Servicio de Neurología y NeurofisiologíaClínica, Instituto de Biomedicina de Sevilla, Seville, Spain; Centro de Investigación Biomédicaen Red sobreEnfermedades Neurodegenerativas (CIBERNED), Spain
| | - Juulia Jylhävä
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | | | - Miguel A Labrador-Espinosa
- Hospital Universitario Virgen del Rocío/CSIC/Universidad de Sevilla, Unidad de Trastornos del Movimiento, Servicio de Neurología y NeurofisiologíaClínica, Instituto de Biomedicina de Sevilla, Seville, Spain; Centro de Investigación Biomédicaen Red sobreEnfermedades Neurodegenerativas (CIBERNED), Spain
| | - Cristina Licari
- CERM, University of Florence, Sesto Fiorentino, Florence, Italy
| | - Maria Giovanna Maturo
- Department of Biotechnological and Applied Clinical Sciences, University of L'Aquila, L'Aquila, Italy
| | - Giacomo Mengozzi
- IRCCS Istituto delle Scienze Neurologiche di Bologna, Bologna, Italy
| | | | - Maddalena Milazzo
- Department of Experimental, Diagnostic, and Specialty Medicine (DIMES), University of Bologna, Bologna, Italy
| | - Maria Teresa Periñán-Tocino
- Hospital Universitario Virgen del Rocío/CSIC/Universidad de Sevilla, Unidad de Trastornos del Movimiento, Servicio de Neurología y NeurofisiologíaClínica, Instituto de Biomedicina de Sevilla, Seville, Spain; Centro de Investigación Biomédicaen Red sobreEnfermedades Neurodegenerativas (CIBERNED), Spain
| | - Francesco Ravaioli
- Department of Experimental, Diagnostic, and Specialty Medicine (DIMES), University of Bologna, Bologna, Italy
| | - Claudia Sala
- Department of Physics and Astronomy, University of Bologna, Bologna, Italy
| | - Luisa Sambati
- IRCCS Istituto delle Scienze Neurologiche di Bologna, Bologna, Italy; Department of Biomedical and NeuroMotor Sciences (DiBiNeM), University of Bologna, Italy
| | - Sebastian Schade
- Department of Clinical Neurophysiology, University Medical Center Göttingen, Göttingen, Germany
| | - Sebastian Schreglmann
- Department of Clinical and Movement Neurosciences, UCL Queen Square Institute of Neurology, London, United Kingdom
| | - Simeon Spasov
- Department of Computer Science and Technology, University of Cambridge, Cambridge, United Kingdom
| | - Leonardo Tenori
- Consorzio Interuniversitario Risonanze Magnetiche di Metalloproteine (CIRMMP), Florence, Italy
| | - Dylan Williams
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | | | | | - Kailash P Bhatia
- Department of Clinical and Movement Neurosciences, UCL Queen Square Institute of Neurology, London, United Kingdom
| | - Sabina Capellari
- IRCCS Istituto delle Scienze Neurologiche di Bologna, Bologna, Italy; Department of Biomedical and NeuroMotor Sciences (DiBiNeM), University of Bologna, Italy
| | - Pietro Cortelli
- IRCCS Istituto delle Scienze Neurologiche di Bologna, Bologna, Italy; Department of Biomedical and NeuroMotor Sciences (DiBiNeM), University of Bologna, Italy
| | - Paolo Garagnani
- Department of Experimental, Diagnostic, and Specialty Medicine (DIMES), University of Bologna, Bologna, Italy
| | - Henry Houlden
- Department of Neuromuscular Disorders, UCL Queen Square Institute of Neurology, London, WC1N 3BG, United Kingdom
| | - Pietro Liò
- Department of Computer Science and Technology, University of Cambridge, Cambridge, United Kingdom
| | - Claudio Luchinat
- CERM, University of Florence, Sesto Fiorentino, Florence, Italy; Department of Chemistry "Ugo Schiff", University of Florence, Italy
| | | | - Kevin Mills
- Centre for Inborn Errors of Metabolism, UCL Institute of Child Health, London, United Kingdom; NIHR Great Ormond Street Biomedical Research Centre, Great Ormond Street Hospital and UCL Great Ormond Street Institute of Child Health, London, United Kingdom
| | - Pablo Mir
- Hospital Universitario Virgen del Rocío/CSIC/Universidad de Sevilla, Unidad de Trastornos del Movimiento, Servicio de Neurología y NeurofisiologíaClínica, Instituto de Biomedicina de Sevilla, Seville, Spain; Centro de Investigación Biomédicaen Red sobreEnfermedades Neurodegenerativas (CIBERNED), Spain
| | - Brit Mollenhauer
- Paracelsus-Elena-Klinik, Kassel, Germany; Department of Neurology, University Medical Centre Goettingen, Goettingen, Germany
| | - Christine Nardini
- Istituto per le Applicazioni del Calcolo Mauro Picone, CNR, Roma, Italy
| | - Nancy L Pedersen
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Federica Provini
- IRCCS Istituto delle Scienze Neurologiche di Bologna, Bologna, Italy; Department of Biomedical and NeuroMotor Sciences (DiBiNeM), University of Bologna, Italy
| | - Stephen Strom
- Department of Laboratory Medicine, Karolinska Institute and Karolinska Universitetssjukhuset, 171 76, Stockholm, Sweden
| | - Claudia Trenkwalder
- Paracelsus-Elena-Klinik, Kassel, Germany; Department of Neurosurgery, University Medical Center Göttingen, Germany
| | - Paola Turano
- CERM, University of Florence, Sesto Fiorentino, Florence, Italy; Department of Chemistry "Ugo Schiff", University of Florence, Italy
| | | | - Claudio Franceschi
- IRCCS Istituto delle Scienze Neurologiche di Bologna, Bologna, Italy; Laboratory of Systems Medicine of Healthy Aging and Department of Applied Mathematics, Lobachevsky University, Nizhny Novgorod, Russia
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374
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Pottinger TD, Khan SS, Zheng Y, Zhang W, Tindle HA, Allison M, Wells G, Shadyab AH, Nassir R, Martin LW, Manson JE, Lloyd-Jones DM, Greenland P, Baccarelli AA, Whitsel EA, Hou L. Association of cardiovascular health and epigenetic age acceleration. Clin Epigenetics 2021; 13:42. [PMID: 33632308 PMCID: PMC7905851 DOI: 10.1186/s13148-021-01028-2] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2020] [Accepted: 02/11/2021] [Indexed: 01/06/2023] Open
Abstract
Background Cardiovascular health (CVH) has been defined by the American Heart Association (AHA) as the presence of the “Life’s Simple 7” ideal lifestyle and clinical factors. CVH is known to predict longevity and freedom from cardiovascular disease, the leading cause of death for women in the United States. DNA methylation markers of aging have been aggregated into a composite epigenetic age score, which is associated with cardiovascular morbidity and mortality. However, it is unknown whether poor CVH is associated with acceleration of aging as measured by DNA methylation markers in epigenetic age.
Methods and results We performed a cross-sectional analysis of racially/ethnically diverse post-menopausal women enrolled in the Women’s Health Initiative cohort recruited between 1993 and 1998. Epigenetic age acceleration (EAA) was calculated using DNA methylation data on a subset of participants and the published Horvath and Hannum methods for intrinsic and extrinsic EAA. CVH was calculated using the AHA measures of CVH contributing to a 7-point score. We examined the association between CVH score and EAA using linear regression modeling adjusting for self-reported race/ethnicity and education. Among the 2,170 participants analyzed, 50% were white and mean age was 64 (7 SD) years. Higher or more favorable CVH scores were associated with lower extrinsic EAA (~ 6 months younger age per 1 point higher CVH score, p < 0.0001), and lower intrinsic EAA (3 months younger age per 1 point higher CVH score, p < 0.028).
Conclusions These cross-sectional observations suggest a possible mechanism by which ideal CVH is associated with greater longevity.
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Affiliation(s)
- Tess D Pottinger
- Center for Genetic Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA. .,Institute for Genomic Medicine, Columbia University, 701 West 168th Street, New York, NY, 10032, USA.
| | - Sadiya S Khan
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA.,Division of Cardiology, Department of Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Yinan Zheng
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Wei Zhang
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Hilary A Tindle
- Division of General Internal Medicine and Public Health, Vanderbilt University Medical Center, Nashville, TN, USA.,Geriatric Research Education and Clinical Centers (GRECC), Veterans Affairs Tennessee Valley Healthcare System, Nashville, TN, USA
| | - Matthew Allison
- Department of Family Medicine and Public Health, San Diego School of Medicine, University of California, La Jolla, CA, USA
| | | | - Aladdin H Shadyab
- Department of Family Medicine and Public Health, San Diego School of Medicine, University of California, La Jolla, CA, USA
| | - Rami Nassir
- University of California Davis, Davis, CA, USA
| | | | - JoAnn E Manson
- Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Donald M Lloyd-Jones
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Philip Greenland
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | | | - Eric A Whitsel
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC, USA.,Department of Medicine School of Medicine, University of North Carolina, Chapel Hill, NC, USA
| | - Lifang Hou
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
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375
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Hong SR, Shin KJ. Bisulfite-Converted DNA Quantity Evaluation: A Multiplex Quantitative Real-Time PCR System for Evaluation of Bisulfite Conversion. Front Genet 2021; 12:618955. [PMID: 33719336 PMCID: PMC7947210 DOI: 10.3389/fgene.2021.618955] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2020] [Accepted: 01/27/2021] [Indexed: 11/13/2022] Open
Abstract
Bisulfite (BS) conversion, which includes a series of chemical reactions using bisulfite, is a prerequisite to most DNA methylation analysis methods, and thus is an essential step in the associated research process. Unfortunately, BS conversion leads to the degradation or loss of DNA, which can hinder further downstream analysis. In addition, it is well known that incomplete BS conversion is crucial, as it causes an exaggeration of the DNA methylation level, which can adversely affect the results. Therefore, there have been many attempts to measure three key features of BS conversion: BS conversion efficiency, recovery, and degradation level. In this study, a multiplex quantitative real-time PCR system named BisQuE was suggested to simultaneously analyze three important aspects of the conversion step. By adopting cytosine-free PCR primers for two differently sized multicopy regions, the short amplicon and long amplicon were obtained from both the genomic and BS-converted DNA, thus enabling the obtaining of reliable and sensitive results and the calculation of the degradation level of the conversion step. Also, probes for detecting converted/unconverted templates and C-T indicators for inducing the formula were included in this assay to quantify BS-converted DNA in order to compute the conversion efficiency and recovery. Six BS conversion kits (EZ DNA Methylation-Lightning Kit, Premium Bisulfite kit, MethylEdge® Bisulfite Conversion System, EpiJET Bisulfite Conversion Kit, EpiTect Fast DNA Bisulfite Kit, and NEBNext® Enzymatic Methyl-seq Conversion Module) were tested in 20 samples using 50 ng of genomic DNA as an input with the BisQuE. The conversion efficiency, degradation levels, as well as recovery rates of the kits were investigated. A total of 99.61-99.90% conversion efficiency was perceived for five of the kits, while the NEBNext kit showed about 94%. The lowest degradation level was shown by the NEBNext kit, whereas the other kits were quite similar. The recovery rates of the kits were found to be within the range of 18-50%. A Qubit assay was also used to compare the recovery rate of BisQuE.
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Affiliation(s)
- Sae Rom Hong
- Department of Forensic Medicine and Brain Korea 21 PLUS Project for Medical Science, Yonsei University College of Medicine, Seoul, South Korea
| | - Kyoung-Jin Shin
- Department of Forensic Medicine and Brain Korea 21 PLUS Project for Medical Science, Yonsei University College of Medicine, Seoul, South Korea
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376
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Haas C, Neubauer J, Salzmann AP, Hanson E, Ballantyne J. Forensic transcriptome analysis using massively parallel sequencing. Forensic Sci Int Genet 2021; 52:102486. [PMID: 33657509 DOI: 10.1016/j.fsigen.2021.102486] [Citation(s) in RCA: 22] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2020] [Revised: 02/11/2021] [Accepted: 02/12/2021] [Indexed: 12/15/2022]
Abstract
The application of transcriptome analyses in forensic genetics has experienced tremendous growth and development in the past decade. The earliest studies and main applications were body fluid and tissue identification, using targeted RNA transcripts and a reverse transcription endpoint PCR method. A number of markers have been identified for the forensically most relevant body fluids and tissues and the method has been successfully used in casework. The introduction of Massively Parallel Sequencing (MPS) opened up new perspectives and opportunities to advance the field. Contrary to genomic DNA where two copies of an autosomal DNA segment are present in a cell, abundant RNA species are expressed in high copy numbers. Even whole transcriptome sequencing (RNA-Seq) of forensically relevant body fluids and of postmortem material was shown to be possible. This review gives an overview on forensic transcriptome analyses and applications. The methods cover whole transcriptome as well as targeted MPS approaches. High resolution forensic transcriptome analyses using MPS are being applied to body fluid/ tissue identification, determination of the age of stains and the age of the donor, the estimation of the post-mortem interval and to post mortem death investigations.
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Affiliation(s)
- Cordula Haas
- University of Zurich, Zurich Institute of Forensic Medicine, Forensic Genetics, Winterthurerstrasse 190/52, CH-8057 Zurich, Switzerland.
| | - Jacqueline Neubauer
- University of Zurich, Zurich Institute of Forensic Medicine, Forensic Genetics, Winterthurerstrasse 190/52, CH-8057 Zurich, Switzerland
| | - Andrea Patrizia Salzmann
- University of Zurich, Zurich Institute of Forensic Medicine, Forensic Genetics, Winterthurerstrasse 190/52, CH-8057 Zurich, Switzerland
| | - Erin Hanson
- National Center for Forensic Science, University of Central Florida, 12354 Research Parkway, Suite 225, Orlando, FL 32826, USA
| | - Jack Ballantyne
- National Center for Forensic Science, University of Central Florida, 12354 Research Parkway, Suite 225, Orlando, FL 32826, USA; Department of Chemistry, National Center for Forensic Science, University of Central Florida, 12354 Research Parkway, Suite 225, Orlando, FL 32826, USA
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377
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Abstract
Integrating the analysis of molecular data from different sources may improve our understanding of the effects of biological aging.
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Affiliation(s)
- Meeraj Kothari
- Butler Columbia Aging Center, Columbia University Mailman School of Public Health, New York, United States
| | - Daniel W Belsky
- Butler Columbia Aging Center, Columbia University Mailman School of Public Health, New York, United States.,Department of Epidemiology, Columbia University Mailman School of Public Health, New York, United States
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378
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Kassam I, Tan S, Gan FF, Saw WY, Tan LWL, Moong DKN, Soong R, Teo YY, Loh M. Genome-wide identification of cis DNA methylation quantitative trait loci in three Southeast Asian Populations. Hum Mol Genet 2021; 30:603-618. [PMID: 33547791 DOI: 10.1093/hmg/ddab038] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2020] [Revised: 01/25/2021] [Accepted: 01/28/2021] [Indexed: 12/12/2022] Open
Abstract
DNA methylation (DNAm) is an epigenetic modification that acts to regulate gene transcription, is essential for cellular processes and plays an important role in complex traits and disease. Variation in DNAm levels is influenced by both genetic and environmental factors. Several studies have examined the extent to which common genetic variation influences DNAm (i.e. mQTLs), however, an improved understanding of mQTLs across diverse human populations is needed to increase their utility in integrative genomic studies in order to further our understanding of complex trait and disease biology. Here, we systematically examine cis-mQTLs in three Southeast Asian populations in the Singapore Integrative Omics (iOmics) Study, comprised of Chinese (n = 93), Indians (n = 83) and Malays (n = 78). A total of 24 851 cis-mQTL probes were associated with at least one SNP in meta- and ethnicity-specific analyses at a stringent significance level. These cis-mQTL probes show significant differences in local SNP heritability between the ethnicities, enrichment in functionally relevant regions using data from the Roadmap Epigenomics Mapping Consortium and are associated with nearby genes and complex traits due to pleiotropy. Importantly, DNAm prediction performance and the replication of cis-mQTLs both within iOmics and between two independent mQTL studies in European and Bangladeshi individuals is best when the genetic distance between the ethnicities is small, with differences in cis-mQTLs likely due to differences in allele frequency and linkage disequilibrium. This study highlights the importance of, and opportunities from, extending investigation of the genetic control of DNAm to Southeast Asian populations.
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Affiliation(s)
- Irfahan Kassam
- Life Sciences Institute, National University of Singapore, Singapore 117456.,Saw Swee Hock School of Public Health, National University of Singapore, Singapore 117549
| | - Sili Tan
- KK Research Centre, KK Women's and Children's Hospital, Singapore 229899
| | - Fei Fei Gan
- Department of NUH Tissue Repository, National University Health System, Singapore 119228
| | - Woei-Yuh Saw
- Baker Heart and Diabetes Institute, Melbourne Victoria, Australia 3004
| | - Linda Wei-Lin Tan
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore 117549
| | - Don Kyin Nwe Moong
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore 117549
| | - Richie Soong
- Cancer Science Institute of Singapore, National University of Singapore, Singapore 117599
| | - Yik-Ying Teo
- Life Sciences Institute, National University of Singapore, Singapore 117456.,Saw Swee Hock School of Public Health, National University of Singapore, Singapore 117549
| | - Marie Loh
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore 308232.,Department of Epidemiology and Biostatistics, Imperial College London, London, United Kingdom W2 1PG.,Translational Laboratory in Genetic Medicine, Agency for Science, Technology and Research (ASTAR), Singapore 138648
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379
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Pischedda S, O'Connor D, Fairfax BP, Salas A, Martinon-Torres F, Pollard AJ, Trück J. Changes in epigenetic profiles throughout early childhood and their relationship to the response to pneumococcal vaccination. Clin Epigenetics 2021; 13:29. [PMID: 33541404 PMCID: PMC7860179 DOI: 10.1186/s13148-021-01012-w] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2020] [Accepted: 01/11/2021] [Indexed: 02/07/2023] Open
Abstract
Background Pneumococcal infections are a major cause of morbidity and mortality in young children and immaturity of the immune system partly underlies poor vaccine responses seen in the young. Emerging evidence suggests a key role for epigenetics in the maturation and regulation of the immune system in health and disease. The study aimed to investigate epigenetic changes in early life and to understand the relationship between the epigenome and antigen-specific antibody responses to pneumococcal vaccination. Methods The epigenetic profiles from 24 healthy children were analyzed at 12 months prior to a booster dose of the 13-valent pneumococcal conjugate vaccine (PCV-13), and at 24 months of age, using the Illumina Methylation 450 K assay and assessed for differences over time and between high and low vaccine responders. Results Our analysis revealed 721 significantly differentially methylated positions between 12 and 24 months (FDR < 0.01), with significant enrichment in pathways involved in the regulation of cell–cell adhesion and T cell activation. Comparing high and low vaccine responders, we identified differentially methylated CpG sites (P value < 0.01) associated with HLA-DPB1 and IL6. Conclusion These data imply that epigenetic changes that occur during early childhood may be associated with antigen-specific antibody responses to pneumococcal vaccines.
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Affiliation(s)
- Sara Pischedda
- Genetics, Vaccines and Infections and Pediatrics Research Group (GENVIP), Instituto de Investigación Sanitaria de Santiago, Santiago de Compostela, Spain. .,Translational Pediatrics and Infectious Diseases, Department of Pediatrics, Hospital Clínico Universitario de Santiago de Compostela, Santiago de Compostela, Spain. .,Hospital Clínico Universitario de Santiago (SERGAS), Unidade de Xenética, Instituto de Ciencias Forenses, Facultade de Medicina, Universidade de Santiago de Compostela, and GenPoB Research Group, Instituto de Investigaciones Sanitarias (IDIS), Galicia, Spain.
| | - Daniel O'Connor
- Oxford Vaccine Group, Department of Paediatrics, University of Oxford, and The NIHR Oxford Biomedical Research Centre, Oxford, UK.
| | - Benjamin P Fairfax
- MRC-Weatherall Institute of Molecular Medicine, University of Oxford, Oxford, UK
| | - Antonio Salas
- Genetics, Vaccines and Infections and Pediatrics Research Group (GENVIP), Instituto de Investigación Sanitaria de Santiago, Santiago de Compostela, Spain.,Hospital Clínico Universitario de Santiago (SERGAS), Unidade de Xenética, Instituto de Ciencias Forenses, Facultade de Medicina, Universidade de Santiago de Compostela, and GenPoB Research Group, Instituto de Investigaciones Sanitarias (IDIS), Galicia, Spain
| | - Federico Martinon-Torres
- Genetics, Vaccines and Infections and Pediatrics Research Group (GENVIP), Instituto de Investigación Sanitaria de Santiago, Santiago de Compostela, Spain.,Translational Pediatrics and Infectious Diseases, Department of Pediatrics, Hospital Clínico Universitario de Santiago de Compostela, Santiago de Compostela, Spain
| | - Andrew J Pollard
- Oxford Vaccine Group, Department of Paediatrics, University of Oxford, and The NIHR Oxford Biomedical Research Centre, Oxford, UK
| | - Johannes Trück
- Oxford Vaccine Group, Department of Paediatrics, University of Oxford, and The NIHR Oxford Biomedical Research Centre, Oxford, UK. .,Division of Immunology and Children's Research Center, University Children's Hospital Zurich, University of Zurich (UZH), Zurich, Switzerland.
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Dugué PA, Bassett JK, Wong EM, Joo JE, Li S, Yu C, Schmidt DF, Makalic E, Doo NW, Buchanan DD, Hodge AM, English DR, Hopper JL, Giles GG, Southey MC, Milne RL. Biological Aging Measures Based on Blood DNA Methylation and Risk of Cancer: A Prospective Study. JNCI Cancer Spectr 2021; 5:pkaa109. [PMID: 33442664 PMCID: PMC7791618 DOI: 10.1093/jncics/pkaa109] [Citation(s) in RCA: 27] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2020] [Revised: 09/16/2020] [Accepted: 10/29/2020] [Indexed: 02/07/2023] Open
Abstract
Background We previously investigated the association between 5 "first-generation" measures of epigenetic aging and cancer risk in the Melbourne Collaborative Cohort Study. This study assessed cancer risk associations for 3 recently developed methylation-based biomarkers of aging: PhenoAge, GrimAge, and predicted telomere length. Methods We estimated rate ratios (RRs) for the association between these 3 age-adjusted measures and risk of colorectal (N = 813), gastric (N = 165), kidney (N = 139), lung (N = 327), mature B-cell (N = 423), prostate (N = 846), and urothelial (N = 404) cancer using conditional logistic regression models. We also assessed associations by time since blood draw and by cancer subtype, and we investigated potential nonlinearity. Results We observed relatively strong associations of age-adjusted PhenoAge with risk of colorectal, kidney, lung, mature B-cell, and urothelial cancers (RR per SD was approximately 1.2-1.3). Similar findings were obtained for age-adjusted GrimAge, but the association with lung cancer risk was much larger (RR per SD = 1.82, 95% confidence interval [CI] = 1.44 to 2.30), after adjustment for smoking status, pack-years, starting age, time since quitting, and other cancer risk factors. Most associations appeared linear, larger than for the first-generation measures, and were virtually unchanged after adjustment for a large set of sociodemographic, lifestyle, and anthropometric variables. For cancer overall, the comprehensively adjusted rate ratio per SD was 1.13 (95% CI = 1.07 to 1.19) for PhenoAge and 1.12 (95% CI = 1.05 to 1.20) for GrimAge and appeared larger within 5 years of blood draw (RR = 1.29, 95% CI = 1.15 to 1.44 and 1.19, 95% CI = 1.06 to 1.33, respectively). Conclusions The methylation-based measures PhenoAge and GrimAge may provide insights into the relationship between biological aging and cancer and be useful to predict cancer risk, particularly for lung cancer.
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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
| | - Julie K Bassett
- Cancer Epidemiology Division, Cancer Council, Victoria, Melbourne, 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
- Department of Clinical Pathology, Melbourne Medical School, The University of Melbourne, Parkville, Victoria, Australia
| | - Shuai Li
- Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, Victoria, Australia
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Parkville, Victoria, Australia
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Chenglong Yu
- Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, Victoria, Australia
| | - Daniel F Schmidt
- Faculty of Information Technology, 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
| | - Nicole Wong Doo
- Cancer Epidemiology Division, Cancer Council, Victoria, Melbourne, Victoria, Australia
- Concord Clinical School, Faculty of Medicine and Health, The University of Sydney, New South Wales, Australia
| | - Daniel D Buchanan
- Department of Clinical Pathology, Colorectal Oncogenomics Group, Melbourne Medical School, The University of Melbourne, Parkville, Victoria, Australia
- Victorian Comprehensive Cancer Centre, University of Melbourne Centre for Cancer Research, Parkville, Victoria, Australia
- Genomic Medicine and Family Cancer Clinic, Royal Melbourne Hospital, Parkville, 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
| | - 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
| | - 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
| | - 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
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381
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Saluja H, Young GP, Kholmurodova F, Symonds EL. Variables Associated with Detection of Methylated BCAT1 or IKZF1 in Blood from Patients Without Colonoscopically Evident Colorectal Cancer. Cancer Epidemiol Biomarkers Prev 2021; 30:774-781. [PMID: 33500319 DOI: 10.1158/1055-9965.epi-20-1609] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2020] [Revised: 11/27/2020] [Accepted: 01/11/2021] [Indexed: 12/24/2022] Open
Abstract
BACKGROUND DNA methylated in BCAT1 and IKZF1 are promising circulating tumor DNA (ctDNA) biomarkers for colorectal cancer detection. This study tested for variables that might be associated with their detection in patients without colonoscopically evident colorectal cancer so-called false positives. METHODS A retrospective review of demographic and clinical variables was conducted on patients who were assayed for these biomarkers prior to a colonoscopy for any indication. Potential relationships between detection of these biomarkers and patient variables in patients without colorectal cancer were identified by logistic regression. An age- and sex-matched case-control study was undertaken to identify additional associations. RESULTS A total of 196 of 1,593 patients undergoing colonoscopy were positive for BCAT1 and/or IKZF1 methylation; 70 (35.7%) had confirmed diagnosis of colorectal cancer. Of the 126 false positives, biomarker levels were significantly lower than in those with colorectal cancer (P < 0.05), with the total cell-free circulating DNA concentration associated with biomarker detection (OR, 1.16; 95% CI, 1.10-1.22), and 83 (65.9%) of the non-colorectal cancer cases positive for methylated BCAT1 only. Age ≥70 years was the only demographic variable associated with biomarker detection (OR, 4.31; 95% CI, 1.50-12.41). No significant associations were seen with medications or comorbidities (P > 0.05). Four cases without colonoscopically evident colorectal cancer but with biomarker levels above the median for patients with colorectal cancer were diagnosed with metastatic adenocarcinoma within 1 year. CONCLUSIONS False-positive results were most commonly associated with detection of methylated BCAT1 only, as well as age ≥70 years. IMPACT In the absence of colonoscopically evident colorectal cancer, a high level of circulating methylated DNA warrants investigations for cancers at other sites.
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Affiliation(s)
- Hariti Saluja
- Department of Medicine, College of Medicine and Public Health, Flinders University, Bedford Park, South Australia
| | - Graeme P Young
- Cancer Research, Flinders Health and Medical Research Institute, College of Medicine and Public Health, Flinders University, Bedford Park, South Australia
| | - Feruza Kholmurodova
- Flinders Centre for Epidemiology and Biostatistics, College of Medicine and Public Health, Flinders University, Bedford Park, South Australia
| | - Erin L Symonds
- Cancer Research, Flinders Health and Medical Research Institute, College of Medicine and Public Health, Flinders University, Bedford Park, South Australia.
- Bowel Health Service, Flinders Medical Centre, Bedford Park, South Australia
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382
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Sun D, Layman TS, Jeong H, Chatterjee P, Grogan K, Merritt JR, Maney DL, Yi SV. Genome-wide variation in DNA methylation linked to developmental stage and chromosomal suppression of recombination in white-throated sparrows. Mol Ecol 2021; 30:3453-3467. [PMID: 33421223 PMCID: PMC8359194 DOI: 10.1111/mec.15793] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2020] [Revised: 11/25/2020] [Accepted: 01/04/2021] [Indexed: 12/14/2022]
Abstract
Much of our knowledge on regulatory impacts of DNA methylation has come from laboratory‐bred model organisms, which may not exhibit the full extent of variation found in wild populations. Here, we investigated naturally‐occurring variation in DNA methylation in a wild avian species, the white‐throated sparrow (Zonotrichia albicollis). This species offers exceptional opportunities for studying the link between genetic differentiation and phenotypic traits because of a nonrecombining chromosome pair linked to both plumage and behavioural phenotypes. Using novel single‐nucleotide resolution methylation maps and gene expression data, we show that DNA methylation and the expression of DNA methyltransferases are significantly higher in adults than in nestlings. Genes for which DNA methylation varied between nestlings and adults were implicated in development and cell differentiation and were located throughout the genome. In contrast, differential methylation between plumage morphs was concentrated in the nonrecombining chromosome pair. Interestingly, a large number of CpGs on the nonrecombining chromosome, localized to transposable elements, have undergone dramatic loss of DNA methylation since the split of the ZAL2 and ZAL2m chromosomes. Changes in methylation predicted changes in gene expression for both chromosomes. In summary, we demonstrate changes in genome‐wide DNA methylation that are associated with development and with specific functional categories of genes in white‐throated sparrows. Moreover, we observe substantial DNA methylation reprogramming associated with the suppression of recombination, with implications for genome integrity and gene expression divergence. These results offer an unprecedented view of ongoing epigenetic reprogramming in a wild population. see also the Perspective by Jordan A. Anderson and Jenny Tung.
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Affiliation(s)
- Dan Sun
- School of Biological Sciences, Institute for Bioengineering and Bioscience, Georgia Institute of Technology, Atlanta, GA, USA.,Department of Epigenetics and Molecular Carcinogenesis, The University of Texas MD Anderson Cancer Center, Smithville, TX, USA
| | - Thomas S Layman
- School of Biological Sciences, Institute for Bioengineering and Bioscience, Georgia Institute of Technology, Atlanta, GA, USA
| | - Hyeonsoo Jeong
- School of Biological Sciences, Institute for Bioengineering and Bioscience, Georgia Institute of Technology, Atlanta, GA, USA
| | - Paramita Chatterjee
- School of Biological Sciences, Institute for Bioengineering and Bioscience, Georgia Institute of Technology, Atlanta, GA, USA
| | - Kathleen Grogan
- Department of Psychology, Emory University, Atlanta, GA, USA
| | | | - Donna L Maney
- Department of Psychology, Emory University, Atlanta, GA, USA
| | - Soojin V Yi
- School of Biological Sciences, Institute for Bioengineering and Bioscience, Georgia Institute of Technology, Atlanta, GA, USA
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383
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Kovalenko TF, Morozova KV, Pavlyukov MS, Anufrieva KS, Bobrov MY, Gamisoniya AM, Ozolinya LA, Dobrokhotova YE, Shakhparonov MI, Patrushev LI. Methylation of the PTENP1 pseudogene as potential epigenetic marker of age-related changes in human endometrium. PLoS One 2021; 16:e0243093. [PMID: 33481830 PMCID: PMC7822536 DOI: 10.1371/journal.pone.0243093] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2020] [Accepted: 11/16/2020] [Indexed: 01/09/2023] Open
Abstract
The processed pseudogene PTENP1 is involved in the regulation of the expression of the PTEN and acts as a tumor suppressor in many types of malignances. In our previous study we showed that PTENP1 methylation is present not only in tumor, but also in normal endometrium tissues of women over 45 years old. Here we used methylation-specific PCR to analyze methylation status of CpG island located near promoter region of PTENP1 in malignant and non-malignant endometrium tissues collected from 236 women of different age groups. To confirm our results, we also analyzed RNA sequencing and microarray data from 431 women with endometrial cancer from TCGA database. We demonstrated that methylation of PTENP1 is significantly increased in older patients. We also found an age-dependent increase in the level of PTENP1 expression in endometrial tissue. According to our data, PTENP1 methylation elevates the level of the pseudogene sense transcript. In turn, a high level of this transcript correlates with a more favorable prognosis in endometrial cancer. The data obtained suggested that PTENP1 methylation is associated with age-related changes in normal and hyperplastic endometrial tissues. We assumed that age-related increase in PTENP1 methylation and subsequent elevation of its expression may serve as a protective mechanism aimed to prevent malignant transformation of endometrial tissue in women during the perimenopause, menopause, and postmenopause periods.
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Affiliation(s)
- Tatyana F. Kovalenko
- Laboratory of membrane bioenergetics, Shemyakin–Ovchinnikov Institute of Bioorganic Chemistry Russian Academy of Sciences, Moscow, Russia
- * E-mail:
| | - Ksenia V. Morozova
- Department of Obstetrics and Gynecology, Pirogov Russian National Research Medical University, Moscow, Russia
| | - Marat S. Pavlyukov
- Laboratory of membrane bioenergetics, Shemyakin–Ovchinnikov Institute of Bioorganic Chemistry Russian Academy of Sciences, Moscow, Russia
| | - Ksenia S. Anufrieva
- Center for Precision Genome Editing and Genetic Technologies for Biomedicine, Federal Research and Clinical Center of Physical-Chemical Medicine of Federal Medical Biological Agency, Moscow, Russia
- Laboratory of Cell Biology, Federal Research and Clinical Center of Physical-Chemical Medicine of Federal Medical Biological Agency, Moscow, Russia
- Moscow Institute of Physics and Technology (State University), Moscow Region, Russia
| | - Mikhail Yu. Bobrov
- Laboratory of Molecular Pathophysiology, Kulakov Research Center of Obstetrics, Gynecology and Perinatology, Ministry of Healthcare of Russian Federation, Moscow, Russia
| | - Alina M. Gamisoniya
- Laboratory of Molecular Pathophysiology, Kulakov Research Center of Obstetrics, Gynecology and Perinatology, Ministry of Healthcare of Russian Federation, Moscow, Russia
- Laboratory of oxylipins, Shemyakin–Ovchinnikov Institute of Bioorganic Chemistry Russian Academy of Sciences, Moscow, Russia
| | - Lyudmila A. Ozolinya
- Department of Obstetrics and Gynecology, Pirogov Russian National Research Medical University, Moscow, Russia
| | - Yulia E. Dobrokhotova
- Department of Obstetrics and Gynecology, Pirogov Russian National Research Medical University, Moscow, Russia
| | - Mikhail I. Shakhparonov
- Laboratory of membrane bioenergetics, Shemyakin–Ovchinnikov Institute of Bioorganic Chemistry Russian Academy of Sciences, Moscow, Russia
| | - Lev I. Patrushev
- Educational & scientific center, Shemyakin–Ovchinnikov Institute of Bioorganic Chemistry Russian Academy of Sciences, Moscow, Russia
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384
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Okazaki S, Otsuka I, Shinko Y, Horai T, Hirata T, Yamaki N, Sora I, Hishimoto A. Epigenetic Clock Analysis in Children With Fetal Alcohol Spectrum Disorder. Alcohol Clin Exp Res 2021; 45:329-337. [PMID: 33296097 DOI: 10.1111/acer.14532] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2020] [Accepted: 11/24/2020] [Indexed: 12/20/2022]
Abstract
BACKGROUND Fetal alcohol spectrum disorder (FASD) is characterized by severe clinical impairment, considerable social burden, and high mortality and morbidity, which are due to various malformations, sepsis, and cancer. As >50% of deaths from FASD occur during the first year of life, we hypothesized that there is the acceleration of biological aging in FASD. Several recent studies have established genome-wide DNA methylation (DNAm) profiles as "epigenetic clocks" that can estimate biological aging, and FASD has been associated with differential DNAm patterns. Therefore, we tested this hypothesis using epigenetic clocks. METHODS We investigated 5 DNAm-based measures of epigenetic age (HorvathAge, HannumAge, SkinBloodAge, PhenoAge, and GrimAge) and telomere length (DNAmTL) using 4 independent publicly available DNAm datasets; 2 datasets were derived from buccal epithelium, and the other 2 datasets were derived from peripheral blood. RESULTS Compared with controls, children with FASD exhibited an acceleration of GrimAge in 1 buccal and 2 blood datasets. No significant difference was found in other DNAm ages and DNAmTL. Meta-analyses showed a significant acceleration of GrimAge in the blood samples but not in the buccal samples. CONCLUSIONS This study provides novel evidence regarding accelerated epigenetic aging in children with FASD.
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Affiliation(s)
- Satoshi Okazaki
- From, Department of Psychiatry, (SO, IO, YS, THo, THi, NY, IS, AH), Kobe University Graduate School of Medicine, Kobe, Japan
| | - Ikuo Otsuka
- From, Department of Psychiatry, (SO, IO, YS, THo, THi, NY, IS, AH), Kobe University Graduate School of Medicine, Kobe, Japan
| | - Yutaka Shinko
- From, Department of Psychiatry, (SO, IO, YS, THo, THi, NY, IS, AH), Kobe University Graduate School of Medicine, Kobe, Japan
| | - Tadasu Horai
- From, Department of Psychiatry, (SO, IO, YS, THo, THi, NY, IS, AH), Kobe University Graduate School of Medicine, Kobe, Japan
| | - Takashi Hirata
- From, Department of Psychiatry, (SO, IO, YS, THo, THi, NY, IS, AH), Kobe University Graduate School of Medicine, Kobe, Japan
| | - Naruhisa Yamaki
- From, Department of Psychiatry, (SO, IO, YS, THo, THi, NY, IS, AH), Kobe University Graduate School of Medicine, Kobe, Japan
| | - Ichiro Sora
- From, Department of Psychiatry, (SO, IO, YS, THo, THi, NY, IS, AH), Kobe University Graduate School of Medicine, Kobe, Japan
| | - Akitoyo Hishimoto
- From, Department of Psychiatry, (SO, IO, YS, THo, THi, NY, IS, AH), Kobe University Graduate School of Medicine, Kobe, Japan.,Department of Psychiatry, (AH), Yokohama City University Graduate School of Medicine, Yokohama, Japan
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385
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Vaiserman A, Krasnienkov D. Telomere Length as a Marker of Biological Age: State-of-the-Art, Open Issues, and Future Perspectives. Front Genet 2021; 11:630186. [PMID: 33552142 PMCID: PMC7859450 DOI: 10.3389/fgene.2020.630186] [Citation(s) in RCA: 168] [Impact Index Per Article: 56.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2020] [Accepted: 12/21/2020] [Indexed: 12/21/2022] Open
Abstract
Telomere shortening is a well-known hallmark of both cellular senescence and organismal aging. An accelerated rate of telomere attrition is also a common feature of age-related diseases. Therefore, telomere length (TL) has been recognized for a long time as one of the best biomarkers of aging. Recent research findings, however, indicate that TL per se can only allow a rough estimate of aging rate and can hardly be regarded as a clinically important risk marker for age-related pathologies and mortality. Evidence is obtained that other indicators such as certain immune parameters, indices of epigenetic age, etc., could be stronger predictors of the health status and the risk of chronic disease. However, despite these issues and limitations, TL remains to be very informative marker in accessing the biological age when used along with other markers such as indices of homeostatic dysregulation, frailty index, epigenetic clock, etc. This review article is aimed at describing the current state of the art in the field and at discussing recent research findings and divergent viewpoints regarding the usefulness of leukocyte TL for estimating the human biological age.
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Affiliation(s)
- Alexander Vaiserman
- Laboratory of Epigenetics, D.F. Chebotarev Institute of Gerontology, Kyiv, Ukraine
| | - Dmytro Krasnienkov
- Laboratory of Epigenetics, D.F. Chebotarev Institute of Gerontology, Kyiv, Ukraine
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386
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Ming X, Zhu B, Li Y. Mitotic inheritance of DNA methylation: more than just copy and paste. J Genet Genomics 2021; 48:1-13. [PMID: 33771455 DOI: 10.1016/j.jgg.2021.01.006] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2020] [Revised: 01/13/2021] [Accepted: 01/22/2021] [Indexed: 12/14/2022]
Abstract
Decades of investigation on DNA methylation have led to deeper insights into its metabolic mechanisms and biological functions. This understanding was fueled by the recent development of genome editing tools and our improved capacity for analyzing the global DNA methylome in mammalian cells. This review focuses on the maintenance of DNA methylation patterns during mitotic cell division. We discuss the latest discoveries of the mechanisms for the inheritance of DNA methylation as a stable epigenetic memory. We also highlight recent evidence showing the rapid turnover of DNA methylation as a dynamic gene regulatory mechanism. A body of work has shown that altered DNA methylomes are common features in aging and disease. We discuss the potential links between methylation maintenance mechanisms and disease-associated methylation changes.
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Affiliation(s)
- Xuan Ming
- National Laboratory of Biomacromolecules, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China
| | - Bing Zhu
- National Laboratory of Biomacromolecules, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China; College of Life Sciences, University of Chinese Academy of Sciences, Beijing 100049, China.
| | - Yingfeng Li
- National Laboratory of Biomacromolecules, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China.
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387
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Kachroo P, Morrow JD, Vyhlidal CA, Gaedigk R, Silverman EK, Weiss ST, Tantisira KG, DeMeo DL. DNA methylation perturbations may link altered development and aging in the lung. Aging (Albany NY) 2021; 13:1742-1764. [PMID: 33468710 PMCID: PMC7880367 DOI: 10.18632/aging.202544] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2020] [Accepted: 12/18/2020] [Indexed: 12/12/2022]
Abstract
Fetal perturbations in DNA methylation during lung development may reveal insights into the enduring impacts on adult lung health and disease during aging that have not been explored altogether before. We studied the association between genome-wide DNA-methylation and post-conception age in fetal-lung (n=78, 42 exposed to in-utero-smoke (IUS)) tissue and chronological age in adult-lung tissue (n=160, 114 with Chronic Obstructive Pulmonary Disease) using multi-variate linear regression models with covariate adjustment and tested for effect modification by phenotypes. Overlapping age-associations were evaluated for functional and tissue-specific enrichment using the Genotype-Tissue-Expression (GTEx) project. We identified 244 age-associated differentially methylated positions and 878 regions overlapping between fetal and adult-lung tissues. Hyper-methylated CpGs (96%) were enriched in transcription factor activity (FDR adjusted P=2x10-33) and implicated in developmental processes including embryonic organ morphogenesis, neurogenesis and growth delay. Hypo-methylated CpGs (2%) were enriched in oxido-reductase activity and VEGFA-VEGFR2 Signaling. Twenty-one age-by-sex and eleven age-by-pack-years interactions were statistically significant (FDR<0.05) in adult-lung tissue. DNA methylation in transcription factors during development in fetal lung recapitulates in adult-lung tissue with aging. These findings reveal molecular mechanisms and pathways that may link disrupted development in early-life and age-associated lung diseases.
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Affiliation(s)
- Priyadarshini Kachroo
- Channing Division of Network Medicine, Brigham and Women's Hospital, Boston, MA 02115, USA
| | - Jarrett D. Morrow
- Channing Division of Network Medicine, Brigham and Women's Hospital, Boston, MA 02115, USA
| | | | - Roger Gaedigk
- Children's Mercy Hospital and Clinics, Kansas City, MO 64108, USA
| | - Edwin K. Silverman
- Channing Division of Network Medicine, Brigham and Women's Hospital, Boston, MA 02115, USA
- Division of Pulmonary and Critical Care Medicine, Brigham and Women's Hospital, Boston, MA 02115, USA
| | - Scott T. Weiss
- Channing Division of Network Medicine, Brigham and Women's Hospital, Boston, MA 02115, USA
| | - Kelan G. Tantisira
- Channing Division of Network Medicine, Brigham and Women's Hospital, Boston, MA 02115, USA
| | - Dawn L. DeMeo
- Channing Division of Network Medicine, Brigham and Women's Hospital, Boston, MA 02115, USA
- Division of Pulmonary and Critical Care Medicine, Brigham and Women's Hospital, Boston, MA 02115, USA
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388
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A chicken DNA methylation clock for the prediction of broiler health. Commun Biol 2021; 4:76. [PMID: 33462334 PMCID: PMC7814119 DOI: 10.1038/s42003-020-01608-7] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2020] [Accepted: 12/15/2020] [Indexed: 12/13/2022] Open
Abstract
The domestic chicken (Gallus gallus domesticus) is the globally most important source of commercially produced meat. While genetic approaches have played an important role in the development of chicken stocks, little is known about chicken epigenetics. We have systematically analyzed the chicken DNA methylation machinery and DNA methylation landscape. While overall DNA methylation distribution was similar to mammals, sperm DNA appeared hypomethylated, which correlates with the absence of the DNMT3L cofactor in the chicken genome. Additional analysis revealed the presence of low-methylated regions, which are conserved gene regulatory elements that show tissue-specific methylation patterns. We also used whole-genome bisulfite sequencing to generate 56 single-base resolution methylomes from various tissues and developmental time points to establish an LMR-based DNA methylation clock for broiler chicken age prediction. This clock was used to demonstrate epigenetic age acceleration in animals with experimentally induced inflammation. Our study provides detailed insights into the chicken methylome and suggests a novel application of the DNA methylation clock as a marker for livestock health. Raddatz, Lyko and colleagues use whole-genome bisulfite sequencing data to generate a methylation clock for chicken. This clock was able to detect age acceleration in broiler chickens under experimentally induced inflammation.
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389
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Daniels RD, Clouston SAP, Hall CB, Anderson KR, Bennett DA, Bromet EJ, Calvert GM, Carreón T, DeKosky ST, Diminich ED, Finch CE, Gandy S, Kreisl WC, Kritikos M, Kubale TL, Mielke MM, Peskind ER, Raskind MA, Richards M, Sano M, Santiago-Colón A, Sloan RP, Spiro A, Vasdev N, Luft BJ, Reissman DB. A Workshop on Cognitive Aging and Impairment in the 9/11-Exposed Population. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2021; 18:E681. [PMID: 33466931 PMCID: PMC7830144 DOI: 10.3390/ijerph18020681] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Received: 12/09/2020] [Revised: 01/09/2021] [Accepted: 01/12/2021] [Indexed: 12/11/2022]
Abstract
The terrorist attacks on 11 September 2001 potentially exposed more than 400,000 responders, workers, and residents to psychological and physical stressors, and numerous hazardous pollutants. In 2011, the World Trade Center Health Program (WTCHP) was mandated to monitor and treat persons with 9/11-related adverse health conditions and conduct research on physical and mental health conditions related to the attacks. Emerging evidence suggests that persons exposed to 9/11 may be at increased risk of developing mild cognitive impairment. To investigate further, the WTCHP convened a scientific workshop that examined the natural history of cognitive aging and impairment, biomarkers in the pathway of neurodegenerative diseases, the neuropathological changes associated with hazardous exposures, and the evidence of cognitive decline and impairment in the 9/11-exposed population. Invited participants included scientists actively involved in health-effects research of 9/11-exposed persons and other at-risk populations. Attendees shared relevant research results from their respective programs and discussed several options for enhancements to research and surveillance activities, including the development of a multi-institutional collaborative research network. The goal of this report is to outline the meeting's agenda and provide an overview of the presentation materials and group discussion.
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Affiliation(s)
- Robert D. Daniels
- World Trade Center Health Program, Centers for Disease Control and Prevention, National Institute for Occupational Safety and Health, Washington, DC 20201, USA; (K.R.A.); (G.M.C.); (T.C.); (T.L.K.); (A.S.-C.); (D.B.R.)
| | - Sean A. P. Clouston
- Renaissance School of Medicine, Stony Brook University, Stony Brook, NY 11794, USA; (S.A.P.C.); (E.J.B.); (E.D.D.); (M.K.); (B.J.L.)
| | - Charles B. Hall
- Department of Epidemiology & Population Health (Biostatistics), Albert Einstein College of Medicine, Bronx, NY 10461, USA;
| | - Kristi R. Anderson
- World Trade Center Health Program, Centers for Disease Control and Prevention, National Institute for Occupational Safety and Health, Washington, DC 20201, USA; (K.R.A.); (G.M.C.); (T.C.); (T.L.K.); (A.S.-C.); (D.B.R.)
| | - David A. Bennett
- Department of Neurological Sciences, Rush Medical College, Rush University, Chicago, IL 60612, USA;
| | - Evelyn J. Bromet
- Renaissance School of Medicine, Stony Brook University, Stony Brook, NY 11794, USA; (S.A.P.C.); (E.J.B.); (E.D.D.); (M.K.); (B.J.L.)
| | - Geoffrey M. Calvert
- World Trade Center Health Program, Centers for Disease Control and Prevention, National Institute for Occupational Safety and Health, Washington, DC 20201, USA; (K.R.A.); (G.M.C.); (T.C.); (T.L.K.); (A.S.-C.); (D.B.R.)
| | - Tania Carreón
- World Trade Center Health Program, Centers for Disease Control and Prevention, National Institute for Occupational Safety and Health, Washington, DC 20201, USA; (K.R.A.); (G.M.C.); (T.C.); (T.L.K.); (A.S.-C.); (D.B.R.)
| | - Steven T. DeKosky
- McKnight Brain Institute, University of Florida, Gainesville, FL 32611, USA;
| | - Erica D. Diminich
- Renaissance School of Medicine, Stony Brook University, Stony Brook, NY 11794, USA; (S.A.P.C.); (E.J.B.); (E.D.D.); (M.K.); (B.J.L.)
| | - Caleb E. Finch
- USC Leonard Davis School of Gerontology, Los Angeles, CA 90089, USA;
| | - Sam Gandy
- Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; (S.G.); (M.S.)
| | - William C. Kreisl
- Taub Institute for Research on Alzheimer’s Disease and the Aging Brain, New York, NY 10032, USA;
| | - Minos Kritikos
- Renaissance School of Medicine, Stony Brook University, Stony Brook, NY 11794, USA; (S.A.P.C.); (E.J.B.); (E.D.D.); (M.K.); (B.J.L.)
| | - Travis L. Kubale
- World Trade Center Health Program, Centers for Disease Control and Prevention, National Institute for Occupational Safety and Health, Washington, DC 20201, USA; (K.R.A.); (G.M.C.); (T.C.); (T.L.K.); (A.S.-C.); (D.B.R.)
| | - Michelle M. Mielke
- Division of Epidemiology and Department of Neurology, Department of Health Sciences Research, Mayo Clinic, Rochester, MN 55905, USA;
| | - Elaine R. Peskind
- Department of Psychiatry and Behavioral Sciences, University of Washington School of Medicine, Seattle, WA 98195, USA;
| | - Murray A. Raskind
- Northwest Mental Illness Research, Education and Clinical Center (MIRECC), VA Puget Sound Health Care System, Seattle, WA 98108, USA;
| | - Marcus Richards
- Faculty of Population Health Sciences, University College London, London WC1E 6BT, UK;
| | - Mary Sano
- Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; (S.G.); (M.S.)
| | - Albeliz Santiago-Colón
- World Trade Center Health Program, Centers for Disease Control and Prevention, National Institute for Occupational Safety and Health, Washington, DC 20201, USA; (K.R.A.); (G.M.C.); (T.C.); (T.L.K.); (A.S.-C.); (D.B.R.)
| | - Richard P. Sloan
- Division of Behavioral Medicine, Columbia University, New York, NY 10027, USA;
| | - Avron Spiro
- Boston University Schools of Public Health and Medicine and Veterans Affairs Boston Healthcare System, Boston, MA 02130, USA;
| | - Neil Vasdev
- Azrieli Centre for Neuro-Radiochemistry, Brain Health Imaging Centre, Centre for Addiction and Mental Health (CAMH) & Department of Psychiatry, University of Toronto, Toronto, ON M5S, Canada;
| | - Benjamin J. Luft
- Renaissance School of Medicine, Stony Brook University, Stony Brook, NY 11794, USA; (S.A.P.C.); (E.J.B.); (E.D.D.); (M.K.); (B.J.L.)
| | - Dori B. Reissman
- World Trade Center Health Program, Centers for Disease Control and Prevention, National Institute for Occupational Safety and Health, Washington, DC 20201, USA; (K.R.A.); (G.M.C.); (T.C.); (T.L.K.); (A.S.-C.); (D.B.R.)
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390
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Grodstein F, Lemos B, Yu L, Iatrou A, De Jager PL, Bennett DA. Characteristics of Epigenetic Clocks Across Blood and Brain Tissue in Older Women and Men. Front Neurosci 2021; 14:555307. [PMID: 33488342 PMCID: PMC7817909 DOI: 10.3389/fnins.2020.555307] [Citation(s) in RCA: 27] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2020] [Accepted: 12/09/2020] [Indexed: 01/22/2023] Open
Abstract
Epigenetic clocks are among the most promising biomarkers of aging. It is particularly important to establish biomarkers of brain aging to better understand neurodegenerative diseases. To advance application of epigenetic clocks-which were largely created with DNA methylation levels in blood samples-for use in brain, we need clearer evaluation of epigenetic clock behavior in brain, including direct comparisons of brain specimens with blood, a more accessible tissue for research. We leveraged data from the Religious Orders Study and Rush Memory and Aging Project to examine three established epigenetic clocks (Horvath, Hannum, PhenoAge clocks) and a newer clock, trained in cortical tissue. We calculated each clock in three different specimens: (1) antemortem CD4+ cells derived from blood (n = 41); (2) postmortem dorsolateral prefrontal cortex (DLPFC, n = 730); and (3) postmortem posterior cingulate cortex (PCC, n = 186), among older women and men, age 66-108 years at death. Across all clocks, epigenetic age calculated from blood and brain specimens was generally lower than chronologic age, although differences were smallest for the Cortical clock when calculated in the brain specimens. Nonetheless, we found that Pearson correlations of epigenetic to chronologic ages in brain specimens were generally reasonable for all clocks; correlations for the Horvath, Hannum, and PhenoAge clocks largely ranged from 0.5 to 0.7 (all p < 0.0001). The Cortical clock outperformed the other clocks, reaching a correlation of 0.83 in the DLFPC (p < 0.0001) for epigenetic vs. chronologic age. Nonetheless, epigenetic age was quite modestly correlated across blood and DLPFC in 41 participants with paired samples [Pearson r from 0.21 (p = 0.2) to 0.32 (p = 0.05)], indicating that broader research in neurodegeneration may benefit from clocks using CpG sites better conserved across blood and brain. Finally, in analyses stratified by sex, by pathologic diagnosis of Alzheimer disease, and by clinical diagnosis of Alzheimer dementia, correlations of epigenetic to chronologic age remained consistently high across all groups. Future research in brain aging will benefit from epigenetic clocks constructed in brain specimens, including exploration of any advantages of focusing on CpG sites conserved across brain and other tissue types.
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Affiliation(s)
- Francine Grodstein
- Rush Alzheimer’s Disease Center, Rush University Medical Center, Chicago, IL, United States
- Department of Internal Medicine, Rush University Medical Center, Chicago, IL, United States
| | - Bernardo Lemos
- Department of Environmental Health, Harvard TH Chan School of Public Health, Boston, MA, United States
| | - Lei Yu
- Rush Alzheimer’s Disease Center, Rush University Medical Center, Chicago, IL, United States
- Department of Neurological Sciences, Rush University Medical Center, Chicago, IL, United States
| | - Artemis Iatrou
- Rush Alzheimer’s Disease Center, Rush University Medical Center, Chicago, IL, United States
| | - Philip L. De Jager
- Department of Neurology and Taub Institute for Research on Alzheimer’s Disease and the Aging Brain, Center for Translational and Computational Neuroimmunology, Columbia University Irving Medical Center, New York, NY, United States
| | - David A. Bennett
- Rush Alzheimer’s Disease Center, Rush University Medical Center, Chicago, IL, United States
- Department of Neurological Sciences, Rush University Medical Center, Chicago, IL, United States
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391
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Chung M, Ruan M, Zhao N, Koestler DC, De Vivo I, Kelsey KT, Michaud DS. DNA methylation ageing clocks and pancreatic cancer risk: pooled analysis of three prospective nested case-control studies. Epigenetics 2021; 16:1306-1316. [PMID: 33315530 DOI: 10.1080/15592294.2020.1861401] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/22/2022] Open
Abstract
DNA methylation (DNAm) age may reflect age-related variations in biological changes and abnormalities related to ageing. DNAm age acceleration measures have been associated with a number of cancers, but to our knowledge, have not been examined in relation to pancreatic cancer risk or survival. DNAm levels in leukocytes of prediagnostic blood samples of 393 pancreatic cancer cases and 431 matched controls, pooled from three large prospective cohort studies, were used to estimate DNAm age, epigenetic age acceleration (AA), and intrinsic epigenetic age acceleration (IEAA) metrics. Logistic regression and Cox proportional hazard regression models were used to examine the relationship between the various AA and IEAA metrics and pancreatic cancer risk and survival, respectively. The results showed that pancreatic cancer risk was significantly increased across all IEAA metrics, ranging from 83% to 95% increased risk when comparing the third and highest quartiles to the lowest quartile of IEAA. Consistent with these findings, the results from multivariate spline regression analyses showed non-linear relationships between all three IEAA metrics and pancreatic cancer risk with apparent threshold effect including two turning points at minimal and at maximal risks, respectively. There is no evidence of a significant association between pancreatic cancer survival and any of the epigenetic AA or IEAA metrics. Our results indicate DNAm age acceleration, measured in blood prior to cancer diagnosis, is associated with an increased risk of pancreatic cancer in a complex nonlinear, dose-response manner. Epigenetic IEAA metrics may be a useful addition to current methods for pancreatic cancer risk prediction.
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Affiliation(s)
- Mei Chung
- Department of Public Health & Community Medicine, Tufts University School of Medicine, Tufts University, Boston, MA, USA
| | - Mengyuan Ruan
- Department of Public Health & Community Medicine, Tufts University School of Medicine, Tufts University, Boston, MA, USA
| | - Naisi Zhao
- Department of Public Health & Community Medicine, Tufts University School of Medicine, Tufts University, Boston, MA, USA
| | - Devin C Koestler
- Department of Biostatistics & Data Science, University of Kansas Medical Center, Kansas City, KS, USA.,University of Kansas Cancer Center, University of Kansas Medical Center, Kansas City, KS, USA
| | - Immaculata De Vivo
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Karl T Kelsey
- Department of Epidemiology, Brown University, Providence, RI, USA.,Department of Pathology and Laboratory Medicine, Brown University, Providence, RI, USA
| | - Dominique S Michaud
- Department of Public Health & Community Medicine, Tufts University School of Medicine, Tufts University, Boston, MA, USA
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392
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Alquezar C, Arya S, Kao AW. Tau Post-translational Modifications: Dynamic Transformers of Tau Function, Degradation, and Aggregation. Front Neurol 2021; 11:595532. [PMID: 33488497 PMCID: PMC7817643 DOI: 10.3389/fneur.2020.595532] [Citation(s) in RCA: 139] [Impact Index Per Article: 46.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2020] [Accepted: 12/07/2020] [Indexed: 12/11/2022] Open
Abstract
Post-translational modifications (PTMs) on tau have long been recognized as affecting protein function and contributing to neurodegeneration. The explosion of information on potential and observed PTMs on tau provides an opportunity to better understand these modifications in the context of tau homeostasis, which becomes perturbed with aging and disease. Prevailing views regard tau as a protein that undergoes abnormal phosphorylation prior to its accumulation into the toxic aggregates implicated in Alzheimer's disease (AD) and other tauopathies. However, the phosphorylation of tau may, in fact, represent part of the normal but interrupted function and catabolism of the protein. In addition to phosphorylation, tau undergoes another forms of post-translational modification including (but not limited to), acetylation, ubiquitination, glycation, glycosylation, SUMOylation, methylation, oxidation, and nitration. A holistic appreciation of how these PTMs regulate tau during health and are potentially hijacked in disease remains elusive. Recent studies have reinforced the idea that PTMs play a critical role in tau localization, protein-protein interactions, maintenance of levels, and modifying aggregate structure. These studies also provide tantalizing clues into the possibility that neurons actively choose how tau is post-translationally modified, in potentially competitive and combinatorial ways, to achieve broad, cellular programs commensurate with the distinctive environmental conditions found during development, aging, stress, and disease. Here, we review tau PTMs and describe what is currently known about their functional impacts. In addition, we classify these PTMs from the perspectives of protein localization, electrostatics, and stability, which all contribute to normal tau function and homeostasis. Finally, we assess the potential impact of tau PTMs on tau solubility and aggregation. Tau occupies an undoubtedly important position in the biology of neurodegenerative diseases. This review aims to provide an integrated perspective of how post-translational modifications actively, purposefully, and dynamically remodel tau function, clearance, and aggregation. In doing so, we hope to enable a more comprehensive understanding of tau PTMs that will positively impact future studies.
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Affiliation(s)
| | | | - Aimee W. Kao
- Department of Neurology, Memory and Aging Center, University of California, San Francisco, San Francisco, CA, United States
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393
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Proshkina EN, Solovev IA, Shaposhnikov MV, Moskalev AA. Key Molecular Mechanisms of Aging, Biomarkers, and Potential Interventions. Mol Biol 2021. [DOI: 10.1134/s0026893320060096] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/10/2023]
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394
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Saul D, Kosinsky RL. Epigenetics of Aging and Aging-Associated Diseases. Int J Mol Sci 2021; 22:ijms22010401. [PMID: 33401659 PMCID: PMC7794926 DOI: 10.3390/ijms22010401] [Citation(s) in RCA: 98] [Impact Index Per Article: 32.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2020] [Revised: 12/19/2020] [Accepted: 12/26/2020] [Indexed: 12/17/2022] Open
Abstract
Aging represents the multifactorial decline in physiological function of every living organism. Over the past decades, several hallmarks of aging have been defined, including epigenetic deregulation. Indeed, multiple epigenetic events were found altered across different species during aging. Epigenetic changes directly contributing to aging and aging-related diseases include the accumulation of histone variants, changes in chromatin accessibility, loss of histones and heterochromatin, aberrant histone modifications, and deregulated expression/activity of miRNAs. As a consequence, cellular processes are affected, which results in the development or progression of several human pathologies, including cancer, diabetes, osteoporosis, and neurodegenerative disorders. In this review, we focus on epigenetic mechanisms underlying aging-related processes in various species and describe how these deregulations contribute to human diseases.
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Affiliation(s)
- Dominik Saul
- Kogod Center on Aging and Division of Endocrinology, Mayo Clinic, 200 First St SW, Rochester, MN 55905, USA;
- Department of Trauma, Orthopedics and Reconstructive Surgery, Georg-August-University of Goettingen, 37075 Goettingen, Germany
| | - Robyn Laura Kosinsky
- Division of Gastroenterology and Hepatology, Mayo Clinic, 200 First St SW, Rochester, MN 55905, USA
- Correspondence: ; Tel.: +1-507-293-2386
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395
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Zulueta J, Demos AP, Vesel C, Ross M, Piscitello A, Hussain F, Langenecker SA, McInnis M, Nelson P, Ryan K, Leow A, Ajilore O. The Effects of Bipolar Disorder Risk on a Mobile Phone Keystroke Dynamics Based Biomarker of Brain Age. Front Psychiatry 2021; 12:739022. [PMID: 35002792 PMCID: PMC8727438 DOI: 10.3389/fpsyt.2021.739022] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/09/2021] [Accepted: 11/19/2021] [Indexed: 11/19/2022] Open
Abstract
Background: Research by our group and others have demonstrated the feasibility of using mobile phone derived metadata to model mood and cognition. Given the effects of age and mood on cognitive performance, it was hypothesized that using such data a model could be built to predict chronological age and that differences between predicted age and actual age could be a marker of pathology. Methods: These data were collected via the ongoing BiAffect study. Participants complete the Mood Disorders Questionnaire (MDQ), a screening questionnaire for bipolar disorder, and self-reported their birth year. Data were split into training and validation sets. Features derived from the smartphone kinematics were used to train random forest regression models to predict age. Prediction errors were compared between participants screening positive and negative on the MDQ. Results: Three hundred forty-four participants had analyzable data of which 227 had positive screens for bipolar disorder and 117 had negative screens. The absolute prediction error tended to be lower for participants with positive screens (median 4.50 years) than those with negative screens (median 7.92 years) (W = 508, p = 0.0049). The raw prediction error tended to be lower for participants with negative screens (median = -5.95 years) than those with positive screens (median = 0.55 years) (W = 1,037, p= 0.037). Conclusions: The tendency to underestimate the chronological age of participants screening negative for bipolar disorder compared to those screening positive is consistent with the finding that bipolar disorder may be associated with brain changes that could reflect pathological aging. This interesting result could also reflect that those who screen negative for bipolar disorder and who engaged in the study were more likely to have higher premorbid functioning. This work demonstrates that age-related changes may be detected via a passive smartphone kinematics based digital biomarker.
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Affiliation(s)
- John Zulueta
- Department of Psychiatry, University of Illinois at Chicago, Chicago, IL, United States
| | | | - Claudia Vesel
- Department of Bioengineering, University of Illinois at Chicago, Chicago, IL, United States
| | - Mindy Ross
- Graduate College, University of Illinois at Chicago, Chicago, IL, United States
| | - Andrea Piscitello
- Department of Psychiatry, University of Illinois at Chicago, Chicago, IL, United States
| | - Faraz Hussain
- Department of Psychiatry, University of Illinois at Chicago, Chicago, IL, United States
| | - Scott A Langenecker
- Department of Psychiatry, The University of Utah, Salt Lake City, UT, United States
| | - Melvin McInnis
- Department of Psychiatry, University of Michigan, Ann Arbor, MI, United States
| | - Peter Nelson
- College of Engineering, University of Illinois at Chicago, Chicago, IL, United States
| | - Kelly Ryan
- Department of Psychiatry, University of Michigan, Ann Arbor, MI, United States
| | - Alex Leow
- Department of Psychiatry, University of Illinois at Chicago, Chicago, IL, United States.,Department of Bioengineering, University of Illinois at Chicago, Chicago, IL, United States
| | - Olusola Ajilore
- Department of Psychiatry, University of Illinois at Chicago, Chicago, IL, United States
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396
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Liu S, Wang K, Svoboda LK, Rygiel CA, Neier K, Jones TR, Cavalcante RG, Colacino JA, Dolinoy DC, Sartor MA. Perinatal DEHP exposure induces sex- and tissue-specific DNA methylation changes in both juvenile and adult mice. ENVIRONMENTAL EPIGENETICS 2021; 7:dvab004. [PMID: 33986952 PMCID: PMC8107644 DOI: 10.1093/eep/dvab004] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/28/2020] [Revised: 02/12/2021] [Accepted: 03/17/2021] [Indexed: 05/04/2023]
Abstract
Di(2-ethylhexyl) phthalate (DEHP) is a type of phthalate plasticizer found in a variety of consumer products and poses a public health concern due to its metabolic and endocrine disruption activities. Dysregulation of epigenetic modifications, including DNA methylation, has been shown to be an important mechanism for the pathogenic effects of prenatal exposures, including phthalates. In this study, we used an established mouse model to study the effect of perinatal DEHP exposure on the DNA methylation profile in liver (a primary target tissue of DEHP) and blood (a common surrogate tissue) of both juvenile and adult mice. Despite exposure ceasing at 3 weeks of age (PND21), we identified thousands of sex-specific differential DNA methylation events in 5-month old mice, more than identified at PND21, both in blood and liver. Only a small number of these differentially methylated cytosines (DMCs) overlapped between the time points, or between tissues (i.e. liver and blood), indicating blood may not be an appropriate surrogate tissue to estimate the effects of DEHP exposure on liver DNA methylation. We detected sex-specific DMCs common between 3-week and 5-month samples, pointing to specific DNA methylation alterations that are consistent between weanling and adult mice. In summary, this is the first study to assess the genome-wide DNA methylation profiles in liver and blood at two different aged cohorts in response to perinatal DEHP exposure. Our findings cast light on the implications of using surrogate tissue instead of target tissue in human population-based studies and identify epigenetic biomarkers for DEHP exposure.
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Affiliation(s)
- Siyu Liu
- Department of Computational Medicine and Bioinformatics, University of Michigan, 500 S State St., Ann Arbor, MI 48109, USA
| | - Kai Wang
- Department of Computational Medicine and Bioinformatics, University of Michigan, 500 S State St., Ann Arbor, MI 48109, USA
| | - Laurie K Svoboda
- Environmental Health Sciences, University of Michigan, 500 S State St., Ann Arbor, MI 48109, USA
| | - Christine A Rygiel
- Environmental Health Sciences, University of Michigan, 500 S State St., Ann Arbor, MI 48109, USA
| | - Kari Neier
- Environmental Health Sciences, University of Michigan, 500 S State St., Ann Arbor, MI 48109, USA
| | - Tamara R Jones
- Environmental Health Sciences, University of Michigan, 500 S State St., Ann Arbor, MI 48109, USA
| | - Raymond G Cavalcante
- Epigenomics Core, University of Michigan, 500 S State St., Ann Arbor, MI 48109, USA
| | - Justin A Colacino
- Environmental Health Sciences, University of Michigan, 500 S State St., Ann Arbor, MI 48109, USA
- Nutritional Sciences, University of Michigan, 500 S State St., Ann Arbor, MI 48109, USA
| | - Dana C Dolinoy
- Correspondence address. Environmental Health Sciences, University of Michigan, 1415 Washington Heights, Ann Arbor, MI 48109-2029, USA. Tel: +734-647-3155; Fax: +734-936-7283; E-mail: (D.C.D.); Department of Computational Medicine and Bioinformatics, University of Michigan, 100 Washtenaw Ave., Ann Arbor, MI 48109-2218, USA . Tel: +734-763-8013; Fax: +734-615-6553; E-mail: (M.A.S.)
| | - Maureen A Sartor
- Correspondence address. Environmental Health Sciences, University of Michigan, 1415 Washington Heights, Ann Arbor, MI 48109-2029, USA. Tel: +734-647-3155; Fax: +734-936-7283; E-mail: (D.C.D.); Department of Computational Medicine and Bioinformatics, University of Michigan, 100 Washtenaw Ave., Ann Arbor, MI 48109-2218, USA . Tel: +734-763-8013; Fax: +734-615-6553; E-mail: (M.A.S.)
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397
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Han Y, Nikolić M, Gobs M, Franzen J, de Haan G, Geiger H, Wagner W. Targeted methods for epigenetic age predictions in mice. Sci Rep 2020; 10:22439. [PMID: 33384442 PMCID: PMC7775437 DOI: 10.1038/s41598-020-79509-2] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2020] [Accepted: 12/09/2020] [Indexed: 12/14/2022] Open
Abstract
Age-associated DNA methylation reflects aspect of biological aging—therefore epigenetic clocks for mice can elucidate how the aging process in this model organism is affected by specific treatments or genetic background. Initially, age-predictors for mice were trained for genome-wide DNA methylation profiles and we have recently described a targeted assay based on pyrosequencing of DNA methylation at only three age-associated genomic regions. Here, we established alternative approaches using droplet digital PCR (ddPCR) and barcoded bisulfite amplicon sequencing (BBA-seq). At individual CG dinucleotides (CpGs) the correlation of DNA methylation with chronological age was slightly higher for pyrosequencing and ddPCR as compared to BBA-seq. On the other hand, BBA-seq revealed that neighboring CpGs tend to be stochastically modified at murine age-associated regions. Furthermore, the binary sequel of methylated and non-methylated CpGs in individual reads can be used for single-read predictions, which may reflect heterogeneity in epigenetic aging. In comparison to C57BL/6 mice the single-read age-predictions using BBA-seq were also accelerated in the shorter-lived DBA/2 mice, and in C57BL/6 mice with a lifespan quantitative trait locus of DBA/2 mice. Taken together, we describe alternative targeted methods for epigenetic age predictions that provide new perspectives for aging-intervention studies in mice.
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Affiliation(s)
- Yang Han
- Helmholtz-Institute for Biomedical Engineering, Stem Cell Biology and Cellular Engineering, RWTH Aachen University Medical School, Pauwelsstraße 20, 52074, Aachen, Germany.,Institute for Biomedical Engineering - Cell Biology, University Hospital of RWTH Aachen, Aachen, Germany
| | - Miloš Nikolić
- Helmholtz-Institute for Biomedical Engineering, Stem Cell Biology and Cellular Engineering, RWTH Aachen University Medical School, Pauwelsstraße 20, 52074, Aachen, Germany.,Institute for Biomedical Engineering - Cell Biology, University Hospital of RWTH Aachen, Aachen, Germany
| | - Michael Gobs
- Helmholtz-Institute for Biomedical Engineering, Stem Cell Biology and Cellular Engineering, RWTH Aachen University Medical School, Pauwelsstraße 20, 52074, Aachen, Germany.,Institute for Biomedical Engineering - Cell Biology, University Hospital of RWTH Aachen, Aachen, Germany
| | - Julia Franzen
- Helmholtz-Institute for Biomedical Engineering, Stem Cell Biology and Cellular Engineering, RWTH Aachen University Medical School, Pauwelsstraße 20, 52074, Aachen, Germany.,Institute for Biomedical Engineering - Cell Biology, University Hospital of RWTH Aachen, Aachen, Germany
| | - Gerald de Haan
- Laboratory of Ageing Biology and Stem Cells, European Research Institute for the Biology of Ageing, University Medical Center Groningen, Groningen, the Netherlands
| | - Hartmut Geiger
- Institute of Molecular Medicine, Ulm University, 89081, Ulm, Germany
| | - Wolfgang Wagner
- Helmholtz-Institute for Biomedical Engineering, Stem Cell Biology and Cellular Engineering, RWTH Aachen University Medical School, Pauwelsstraße 20, 52074, Aachen, Germany. .,Institute for Biomedical Engineering - Cell Biology, University Hospital of RWTH Aachen, Aachen, Germany.
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398
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Hallmarks of Health. Cell 2020; 184:33-63. [PMID: 33340459 DOI: 10.1016/j.cell.2020.11.034] [Citation(s) in RCA: 227] [Impact Index Per Article: 56.8] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2020] [Revised: 09/09/2020] [Accepted: 11/19/2020] [Indexed: 12/16/2022]
Abstract
Health is usually defined as the absence of pathology. Here, we endeavor to define health as a compendium of organizational and dynamic features that maintain physiology. The biological causes or hallmarks of health include features of spatial compartmentalization (integrity of barriers and containment of local perturbations), maintenance of homeostasis over time (recycling and turnover, integration of circuitries, and rhythmic oscillations), and an array of adequate responses to stress (homeostatic resilience, hormetic regulation, and repair and regeneration). Disruption of any of these interlocked features is broadly pathogenic, causing an acute or progressive derailment of the system coupled to the loss of numerous stigmata of health.
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399
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Hillary RF, Marioni RE. MethylDetectR: a software for methylation-based health profiling. Wellcome Open Res 2020; 5:283. [PMID: 33969230 PMCID: PMC8080939 DOI: 10.12688/wellcomeopenres.16458.1] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 11/26/2020] [Indexed: 04/02/2024] Open
Abstract
DNA methylation is an important biological process which involves the reversible addition of chemical tags called methyl groups to DNA and affects whether genes are active or inactive. Individual methylation profiles are determined by both genetic and environmental influences. Inter-individual variation in DNA methylation profiles can be exploited to estimate or predict a wide variety of human characteristics and disease risk profiles. Indeed, a number of methylation-based predictors of human traits have been developed and linked to important health outcomes. However, there is an unmet need to communicate the applicability and limitations of state-of-the-art methylation-based predictors to the wider community. To address this, we created a secure, web-based interactive platform called 'MethylDetectR' which calculates estimated values or scores for a variety of human traits using blood methylation data. These traits include age, lifestyle traits, high-density lipoprotein cholesterol and the levels of 27 blood proteins related to inflammatory and neurological processes and disease. Methylation-based predictors often return scores on arbitrary scales. To provide meaning to these scores, users can interactively view how estimated trait scores for a given individual compare against other individuals in the sample. Users can optionally upload binary phenotypes and investigate how estimated traits vary according to case vs. control status for these phenotypes. Users can also view how different methylation-based predictors correlate with one another, and with phenotypic values for corresponding traits in a large reference sample (n = 4,450; Generation Scotland). The 'MethylDetectR' platform allows for the fast and secure calculation of DNA methylation-derived estimates for many human traits. This platform also helps to show the correlations between methylation-based scores and corresponding traits at the level of a sample, report estimated health profiles at an individual level, demonstrate how scores relate to important binary outcomes of interest and highlight the current limitations of molecular health predictors.
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Affiliation(s)
- Robert F. Hillary
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, Midlothian, EH4 2XU, UK
| | - Riccardo E. Marioni
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, Midlothian, EH4 2XU, UK
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Maulani C, Auerkari EI. Age estimation using DNA methylation technique in forensics: a systematic review. EGYPTIAN JOURNAL OF FORENSIC SCIENCES 2020. [DOI: 10.1186/s41935-020-00214-2] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022] Open
Abstract
AbstractBackgroundIn addition to the DNA sequence, epigenetic markers have become substantial forensic tools during the last decade. Estimating the age of an individual from human biological remains may provide information for a forensic investigation. Age estimation in molecular strategies can be obtained by telomere length, mRNa mutation, or by sjTRECs but the accuracy is not sufficient in forensic practice because of high margin error.Main bodyOne solution to this problem is to use DNA methylation methods. DNA methylation markers for tissue identification at age-associated CpG sites have been suggested as the most informative biomarkers for estimating the age of an unknown donor. This review aims to give an overview of DNA methylation profiling for estimating the age in cases of forensic relevance and the important aspects in determining the mean absolute deviation (MAD) or mean absolute error (MAE) of the estimated age. Online database searching was performed through PubMed, Scopus, and Google Scholar with keywords selected for forensic age estimation. Thirty-two studies were included in the review, with variable DNA samples but blood commonly as a source. Pyrosequencing and EpiTYPER were methods mostly used in DNA analysis. The MAD in the estimates from DNA methylation was about 3 to 5 years, which was better than other methods such as those based on telomere length or signal-joint T-cell receptor excision circles. The ELOVL2 gene was a commonly used DNA methylation marker in age estimation.ConclusionDNA methylation is a favorable candidate for estimating the age at the time of death in forensic profiling, with an uncertainty mean absolute deviation of about 3 to 5 years in the predicted age. The sample type, platform techniques used, and methods to construct age predictive models were important in determining the accuracy in mean absolute deviation or mean absolute error. The DNA methylation outcome suggests good potential to support conventional STR profiling in forensic cases.
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