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      A Systematic Investigation into Aging Related Genes in Brain and Their Relationship with Alzheimer’s Disease

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      PLoS ONE
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          Abstract

          Aging, as a complex biological process, is accompanied by the accumulation of functional loses at different levels, which makes age to be the biggest risk factor to many neurological diseases. Even following decades of investigation, the process of aging is still far from being fully understood, especially at a systematic level. In this study, we identified aging related genes in brain by collecting the ones with sustained and consistent gene expression or DNA methylation changes in the aging process. Functional analysis with Gene Ontology to these genes suggested transcriptional regulators to be the most affected genes in the aging process. Transcription regulation analysis found some transcription factors, especially Specificity Protein 1 (SP1), to play important roles in regulating aging related gene expression. Module-based functional analysis indicated these genes to be associated with many well-known aging related pathways, supporting the validity of our approach to select aging related genes. Finally, we investigated the roles of aging related genes on Alzheimer’s Disease (AD). We found that aging and AD related genes both involved some common pathways, which provided a possible explanation why aging made the brain more vulnerable to Alzheimer’s Disease.

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          Most cited references43

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          Aging, Cellular Senescence, and Cancer

          For most species, aging promotes a host of degenerative pathologies that are characterized by debilitating losses of tissue or cellular function. However, especially among vertebrates, aging also promotes hyperplastic pathologies, the most deadly of which is cancer. In contrast to the loss of function that characterizes degenerating cells and tissues, malignant (cancerous) cells must acquire new (albeit aberrant) functions that allow them to develop into a lethal tumor. This review discusses the idea that, despite seemingly opposite characteristics, the degenerative and hyperplastic pathologies of aging are at least partly linked by a common biological phenomenon: a cellular stress response known as cellular senescence. The senescence response is widely recognized as a potent tumor suppressive mechanism. However, recent evidence strengthens the idea that it also drives both degenerative and hyperplastic pathologies, most likely by promoting chronic inflammation. Thus, the senescence response may be the result of antagonistically pleiotropic gene action.
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            Neural mechanisms of ageing and cognitive decline.

            During the past century, treatments for the diseases of youth and middle age have helped raise life expectancy significantly. However, cognitive decline has emerged as one of the greatest health threats of old age, with nearly 50% of adults over the age of 85 afflicted with Alzheimer's disease. Developing therapeutic interventions for such conditions demands a greater understanding of the processes underlying normal and pathological brain ageing. Recent advances in the biology of ageing in model organisms, together with molecular and systems-level studies of the brain, are beginning to shed light on these mechanisms and their potential roles in cognitive decline.
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              Epigenetic Predictor of Age

              From the moment of conception, we begin to age. A decay of cellular structures, gene regulation, and DNA sequence ages cells and organisms. DNA methylation patterns change with increasing age and contribute to age related disease. Here we identify 88 sites in or near 80 genes for which the degree of cytosine methylation is significantly correlated with age in saliva of 34 male identical twin pairs between 21 and 55 years of age. Furthermore, we validated sites in the promoters of three genes and replicated our results in a general population sample of 31 males and 29 females between 18 and 70 years of age. The methylation of three sites—in the promoters of the EDARADD, TOM1L1, and NPTX2 genes—is linear with age over a range of five decades. Using just two cytosines from these loci, we built a regression model that explained 73% of the variance in age, and is able to predict the age of an individual with an average accuracy of 5.2 years. In forensic science, such a model could estimate the age of a person, based on a biological sample alone. Furthermore, a measurement of relevant sites in the genome could be a tool in routine medical screening to predict the risk of age-related diseases and to tailor interventions based on the epigenetic bio-age instead of the chronological age.
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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                2016
                3 March 2016
                : 11
                : 3
                : e0150624
                Affiliations
                [1 ]Computational Modeling Sciences, Platform Technologies and Science, GlaxoSmithKline Research & Development, Shanghai, China
                [2 ]Neurodegeneration DPU, GlaxoSmithKline Research & Development, Shanghai, China
                The Florey Institute of Neuroscience and Mental Health, AUSTRALIA
                Author notes

                Competing Interests: All authors are employed by GlaxoSmithKline. Although this work was done in a commercial affiliation, this does not alter the authors’ adherence to PLOS ONE policies on sharing data and materials.

                Conceived and designed the experiments: GM HM. Analyzed the data: GM. Wrote the paper: GM HM. Performed annotation collection for diseases and aging: XZ.

                Article
                PONE-D-15-26006
                10.1371/journal.pone.0150624
                4777381
                26937969
                74049a29-f823-41ba-b7de-63781e599290
                © 2016 Meng et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 14 June 2015
                : 17 February 2016
                Page count
                Figures: 5, Tables: 2, Pages: 17
                Funding
                The authors received no specific funding for this work. GlaxoSmithKline provided support in the form of salaries for all the authors, but did not have any additional role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Biology and Life Sciences
                Genetics
                Gene Expression
                Gene Regulation
                Biology and Life Sciences
                Developmental Biology
                Organism Development
                Aging
                Biology and Life Sciences
                Physiology
                Physiological Processes
                Aging
                Medicine and Health Sciences
                Physiology
                Physiological Processes
                Aging
                Biology and Life Sciences
                Genetics
                Gene Expression
                Biology and life sciences
                Cell biology
                Chromosome biology
                Chromatin
                Chromatin modification
                DNA methylation
                Biology and life sciences
                Genetics
                Epigenetics
                Chromatin
                Chromatin modification
                DNA methylation
                Biology and life sciences
                Genetics
                Gene expression
                Chromatin
                Chromatin modification
                DNA methylation
                Biology and life sciences
                Genetics
                DNA
                DNA modification
                DNA methylation
                Biology and life sciences
                Biochemistry
                Nucleic acids
                DNA
                DNA modification
                DNA methylation
                Biology and life sciences
                Genetics
                Epigenetics
                DNA modification
                DNA methylation
                Biology and life sciences
                Genetics
                Gene expression
                DNA modification
                DNA methylation
                Medicine and Health Sciences
                Mental Health and Psychiatry
                Dementia
                Alzheimer Disease
                Medicine and Health Sciences
                Neurology
                Dementia
                Alzheimer Disease
                Medicine and Health Sciences
                Neurology
                Neurodegenerative Diseases
                Alzheimer Disease
                Biology and Life Sciences
                Genetics
                Gene Types
                Regulator Genes
                Biology and life sciences
                Genetics
                Gene expression
                DNA transcription
                Biology and life sciences
                Biochemistry
                Proteins
                DNA-binding proteins
                Transcription Factors
                Biology and Life Sciences
                Genetics
                Gene Expression
                Gene Regulation
                Transcription Factors
                Biology and Life Sciences
                Biochemistry
                Proteins
                Regulatory Proteins
                Transcription Factors
                Custom metadata
                All the used data are from GEO database ( http://www.ncbi.nlm.nih.gov/geo/) with the accession ID of: GSE15745, GSE30272, GSE5281, GSE26972, GSE48350, GSE37935. All these data are public available.

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                Uncategorized

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