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      Age Drives Distortion of Brain Metabolic, Vascular and Cognitive Functions, and the Gut Microbiome

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          Abstract

          Advancing age is the top risk factor for the development of neurodegenerative disorders, including Alzheimer’s disease (AD). However, the contribution of aging processes to AD etiology remains unclear. Emerging evidence shows that reduced brain metabolic and vascular functions occur decades before the onset of cognitive impairments, and these reductions are highly associated with low-grade, chronic inflammation developed in the brain over time. Interestingly, recent findings suggest that the gut microbiota may also play a critical role in modulating immune responses in the brain via the brain-gut axis. In this study, our goal was to identify associations between deleterious changes in brain metabolism, cerebral blood flow (CBF), gut microbiome and cognition in aging, and potential implications for AD development. We conducted our study with a group of young mice (5–6 months of age) and compared those to old mice (18–20 months of age) by utilizing metabolic profiling, neuroimaging, gut microbiome analysis, behavioral assessments and biochemical assays. We found that compared to young mice, old mice had significantly increased levels of numerous amino acids and fatty acids that are highly associated with inflammation and AD biomarkers. In the gut microbiome analyses, we found that old mice had increased Firmicutes/ Bacteroidetes ratio and alpha diversity. We also found impaired blood-brain barrier (BBB) function and reduced CBF as well as compromised learning and memory and increased anxiety, clinical symptoms often seen in AD patients, in old mice. Our study suggests that the aging process involves deleterious changes in brain metabolic, vascular and cognitive functions, and gut microbiome structure and diversity, all which may lead to inflammation and thus increase the risk for AD. Future studies conducting comprehensive and integrative characterization of brain aging, including crosstalk with peripheral systems and factors, will be necessary to define the mechanisms underlying the shift from normal aging to pathological processes in the etiology of AD.

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          Most cited references 74

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          Through Ageing, and Beyond: Gut Microbiota and Inflammatory Status in Seniors and Centenarians

          Background Age-related physiological changes in the gastrointestinal tract, as well as modifications in lifestyle, nutritional behaviour, and functionality of the host immune system, inevitably affect the gut microbiota, resulting in a greater susceptibility to infections. Methodology/Principal Findings By using the Human Intestinal Tract Chip (HITChip) and quantitative PCR of 16S rRNA genes of Bacteria and Archaea, we explored the age-related differences in the gut microbiota composition among young adults, elderly, and centenarians, i.e subjects who reached the extreme limits of the human lifespan, living for over 100 years. We observed that the microbial composition and diversity of the gut ecosystem of young adults and seventy-years old people is highly similar but differs significantly from that of the centenarians. After 100 years of symbiotic association with the human host, the microbiota is characterized by a rearrangement in the Firmicutes population and an enrichment in facultative anaerobes, notably pathobionts. The presence of such a compromised microbiota in the centenarians is associated with an increased inflammatory status, also known as inflammageing, as determined by a range of peripheral blood inflammatory markers. This may be explained by a remodelling of the centenarians' microbiota, with a marked decrease in Faecalibacterium prauznitzii and relatives, symbiotic species with reported anti-inflammatory properties. As signature bacteria of the long life we identified specifically Eubacterium limosum and relatives that were more than ten-fold increased in the centenarians. Conclusions/Significance We provide evidence for the fact that the ageing process deeply affects the structure of the human gut microbiota, as well as its homeostasis with the host's immune system. Because of its crucial role in the host physiology and health status, age-related differences in the gut microbiota composition may be related to the progression of diseases and frailty in the elderly population.
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            R: A Language for Data Analysis and Graphics

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              Meta-analyses of human gut microbes associated with obesity and IBD.

              Recent studies have linked human gut microbes to obesity and inflammatory bowel disease, but consistent signals have been difficult to identify. Here we test for indicator taxa and general features of the microbiota that are generally consistent across studies of obesity and of IBD, focusing on studies involving high-throughput sequencing of the 16S rRNA gene (which we could process using a common computational pipeline). We find that IBD has a consistent signature across studies and allows high classification accuracy of IBD from non-IBD subjects, but that although subjects can be classified as lean or obese within each individual study with statistically significant accuracy, consistent with the ability of the microbiota to experimentally transfer this phenotype, signatures of obesity are not consistent between studies even when the data are analyzed with consistent methods. The results suggest that correlations between microbes and clinical conditions with different effect sizes (e.g. the large effect size of IBD versus the small effect size of obesity) may require different cohort selection and analysis strategies.
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                Author and article information

                Contributors
                Journal
                Front Aging Neurosci
                Front Aging Neurosci
                Front. Aging Neurosci.
                Frontiers in Aging Neuroscience
                Frontiers Media S.A.
                1663-4365
                25 September 2017
                2017
                : 9
                Affiliations
                1Sanders-Brown Center on Aging, University of Kentucky Lexington, KY, United States
                2Depatment of Pharmacology and Nutritional Science, University of Kentucky Lexington, KY, United States
                3Research Resources Center, University of Illinois at Chicago Chicago, IL, United States
                4Metabolon Inc. Durham, NC, United States
                5Department of Pharmaceutical Sciences, University of Kentucky Lexington, KY, United States
                6Department of Engineering, University of Kentucky Lexington, KY, United States
                Author notes

                Edited by: P. Hemachandra Reddy, Texas Tech University Health Sciences Center, United States

                Reviewed by: Ana I. Duarte, University of Coimbra, Portugal; Fan Liao, AbbVie Foundational Neuroscience Center, United States

                *Correspondence: Ai-Ling Lin ailing.lin@ 123456uky.edu
                Article
                10.3389/fnagi.2017.00298
                5622159
                Copyright © 2017 Hoffman, Parikh, Green, Chlipala, Mohney, Keaton, Bauer, Hartz and Lin.

                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) or licensor 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.

                Page count
                Figures: 5, Tables: 1, Equations: 0, References: 118, Pages: 14, Words: 12049
                Funding
                Funded by: National Institute on Aging 10.13039/100000049
                Award ID: K01AG040164, R01AG039621
                Funded by: National Institute of Diabetes and Digestive and Kidney Diseases 10.13039/100000062
                Award ID: T32DK007778
                Funded by: American Federation for Aging Research 10.13039/100000965
                Award ID: #A12474
                Funded by: National Institutes of Health 10.13039/100000002
                Award ID: S10RR029541, UL1TR000117
                Categories
                Neuroscience
                Original Research

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