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      The Continuum of Aging and Age-Related Diseases: Common Mechanisms but Different Rates

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          Abstract

          Geroscience, the new interdisciplinary field that aims to understand the relationship between aging and chronic age-related diseases (ARDs) and geriatric syndromes (GSs), is based on epidemiological evidence and experimental data that aging is the major risk factor for such pathologies and assumes that aging and ARDs/GSs share a common set of basic biological mechanisms. A consequence is that the primary target of medicine is to combat aging instead of any single ARD/GSs one by one, as favored by the fragmentation into hundreds of specialties and sub-specialties. If the same molecular and cellular mechanisms underpin both aging and ARDs/GSs, a major question emerges: which is the difference, if any, between aging and ARDs/GSs? The hypothesis that ARDs and GSs such as frailty can be conceptualized as accelerated aging will be discussed by analyzing in particular frailty, sarcopenia, chronic obstructive pulmonary disease, cancer, neurodegenerative diseases such as Alzheimer and Parkinson as well as Down syndrome as an example of progeroid syndrome. According to this integrated view, aging and ARDs/GSs become part of a continuum where precise boundaries do not exist and the two extremes are represented by centenarians, who largely avoided or postponed most ARDs/GSs and are characterized by decelerated aging, and patients who suffered one or more severe ARDs in their 60s, 70s, and 80s and show signs of accelerated aging, respectively. In between these two extremes, there is a continuum of intermediate trajectories representing a sort of gray area. Thus, clinically different, classical ARDs/GSs are, indeed, the result of peculiar combinations of alterations regarding the same, limited set of basic mechanisms shared with the aging process. Whether an individual will follow a trajectory of accelerated or decelerated aging will depend on his/her genetic background interacting lifelong with environmental and lifestyle factors. If ARDs and GSs are manifestations of accelerated aging, it is urgent to identify markers capable of distinguishing between biological and chronological age to identify subjects at higher risk of developing ARDs and GSs. To this aim, we propose the use of DNA methylation, N-glycans profiling, and gut microbiota composition to complement the available disease-specific markers.

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          DNA methylation age of human tissues and cell types

          Background It is not yet known whether DNA methylation levels can be used to accurately predict age across a broad spectrum of human tissues and cell types, nor whether the resulting age prediction is a biologically meaningful measure. Results I developed a multi-tissue predictor of age that allows one to estimate the DNA methylation age of most tissues and cell types. The predictor, which is freely available, was developed using 8,000 samples from 82 Illumina DNA methylation array datasets, encompassing 51 healthy tissues and cell types. I found that DNA methylation age has the following properties: first, it is close to zero for embryonic and induced pluripotent stem cells; second, it correlates with cell passage number; third, it gives rise to a highly heritable measure of age acceleration; and, fourth, it is applicable to chimpanzee tissues. Analysis of 6,000 cancer samples from 32 datasets showed that all of the considered 20 cancer types exhibit significant age acceleration, with an average of 36 years. Low age-acceleration of cancer tissue is associated with a high number of somatic mutations and TP53 mutations, while mutations in steroid receptors greatly accelerate DNA methylation age in breast cancer. Finally, I characterize the 353 CpG sites that together form an aging clock in terms of chromatin states and tissue variance. Conclusions I propose that DNA methylation age measures the cumulative effect of an epigenetic maintenance system. This novel epigenetic clock can be used to address a host of questions in developmental biology, cancer and aging research.
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            DNA methylation age of blood predicts all-cause mortality in later life

            Background DNA methylation levels change with age. Recent studies have identified biomarkers of chronological age based on DNA methylation levels. It is not yet known whether DNA methylation age captures aspects of biological age. Results Here we test whether differences between people’s chronological ages and estimated ages, DNA methylation age, predict all-cause mortality in later life. The difference between DNA methylation age and chronological age (Δage) was calculated in four longitudinal cohorts of older people. Meta-analysis of proportional hazards models from the four cohorts was used to determine the association between Δage and mortality. A 5-year higher Δage is associated with a 21% higher mortality risk, adjusting for age and sex. After further adjustments for childhood IQ, education, social class, hypertension, diabetes, cardiovascular disease, and APOE e4 status, there is a 16% increased mortality risk for those with a 5-year higher Δage. A pedigree-based heritability analysis of Δage was conducted in a separate cohort. The heritability of Δage was 0.43. Conclusions DNA methylation-derived measures of accelerated aging are heritable traits that predict mortality independently of health status, lifestyle factors, and known genetic factors. Electronic supplementary material The online version of this article (doi:10.1186/s13059-015-0584-6) contains supplementary material, which is available to authorized users.
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              Chronic obstructive pulmonary disease in non-smokers.

              Chronic obstructive pulmonary disease (COPD) is a leading cause of morbidity and mortality worldwide. Tobacco smoking is established as a major risk factor, but emerging evidence suggests that other risk factors are important, especially in developing countries. An estimated 25-45% of patients with COPD have never smoked; the burden of non-smoking COPD is therefore much higher than previously believed. About 3 billion people, half the worldwide population, are exposed to smoke from biomass fuel compared with 1.01 billion people who smoke tobacco, which suggests that exposure to biomass smoke might be the biggest risk factor for COPD globally. We review the evidence for the association of COPD with biomass fuel, occupational exposure to dusts and gases, history of pulmonary tuberculosis, chronic asthma, respiratory-tract infections during childhood, outdoor air pollution, and poor socioeconomic status.
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                Author and article information

                Contributors
                Journal
                Front Med (Lausanne)
                Front Med (Lausanne)
                Front. Med.
                Frontiers in Medicine
                Frontiers Media S.A.
                2296-858X
                12 March 2018
                2018
                : 5
                : 61
                Affiliations
                [1] 1Institute of Neurological Sciences, University of Bologna, Bellaria Hospital , Bologna, Italy
                [2] 2Department of Experimental, Diagnostic and Specialty Medicine (DIMES), University of Bologna , Bologna, Italy
                [3] 3Clinical Chemistry, Department of Laboratory Medicine, Karolinska Institutet at Huddinge University Hospital , Stockholm, Sweden
                [4] 4Applied Biomedical Research Center (CRBA), S. Orsola-Malpighi Polyclinic , Bologna, Italy
                [5] 5CNR Institute of Molecular Genetics, Unit of Bologna , Bologna, Italy
                [6] 6Interdepartmental Center “L. Galvani” (CIG), University of Bologna , Bologna, Italy
                [7] 7Unit and Museum of History of Medicine, Department of Molecular Medicine, Sapienza University of Rome , Rome, Italy
                [8] 8Department of Experimental and Clinical Biomedical Sciences “Mario Serio”, University of Florence , Florence, Italy
                Author notes

                Edited by: Gil Atzmon, University of Haifa, Israel

                Reviewed by: Francesco Marotta, ReGenera Research Group, Italy; Marios Kyriazis, ELPIs Foundation for Indefinite Lifespans, United Kingdom

                *Correspondence: Aurelia Santoro, aurelia.santoro@ 123456unibo.it

                Senior coauthorship.

                Specialty section: This article was submitted to Geriatric Medicine, a section of the journal Frontiers in Medicine

                Article
                10.3389/fmed.2018.00061
                5890129
                29662881
                02cd0801-05b9-4291-a2ae-d0769afa4a85
                Copyright © 2018 Franceschi, Garagnani, Morsiani, Conte, Santoro, Grignolio, Monti, Capri and Salvioli.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 11 January 2018
                : 20 February 2018
                Page count
                Figures: 2, Tables: 1, Equations: 0, References: 295, Pages: 23, Words: 21778
                Funding
                Funded by: Fondazione Cariplo 10.13039/501100002803
                Award ID: 2015-0564, 2016-0835
                Funded by: Seventh Framework Programme 10.13039/100011102
                Award ID: HUMAN-602757
                Funded by: European Commission 10.13039/501100000780
                Award ID: ADAGE, PROPAGAGING-634821
                Funded by: Ministero della Salute 10.13039/501100003196
                Award ID: Ricerca Finalizzata GR-2013-02358026
                Categories
                Medicine
                Review

                aging,longevity,age-related diseases,inflammaging,biomarkers,geroscience

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