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Metabolism of sleep and aging: Bridging the gap using metabolomics
Sleep is a conserved behavior across the evolutionary timescale. Almost all known animal species demonstrate sleep or sleep like states. Despite extensive study, the mechanistic aspects of sleep need are not very well characterized. Sleep appears to be needed to generate resources that are utilized...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
IOS Press
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6971829/ https://www.ncbi.nlm.nih.gov/pubmed/31984245 http://dx.doi.org/10.3233/NHA-180043 |
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author | Sengupta, Arjun Weljie, Aalim M. |
author_facet | Sengupta, Arjun Weljie, Aalim M. |
author_sort | Sengupta, Arjun |
collection | PubMed |
description | Sleep is a conserved behavior across the evolutionary timescale. Almost all known animal species demonstrate sleep or sleep like states. Despite extensive study, the mechanistic aspects of sleep need are not very well characterized. Sleep appears to be needed to generate resources that are utilized during the active stage/wakefulness as well as clearance of waste products that accumulate during wakefulness. From a metabolic perspective, this means sleep is crucial for anabolic activities. Decrease in anabolism and build-up of harmful catabolic waste products is also a hallmark of aging processes. Through this lens, sleep and aging processes are remarkably parallel— for example behavioral studies demonstrate an interaction between sleep and aging. Changes in sleep behavior affect neurocognitive phenotypes important in aging such as learning and memory, although the underlying connections are largely unknown. Here we draw inspiration from the similar metabolic effects of sleep and aging and posit that large scale metabolic phenotyping, commonly known as metabolomics, can shed light to interleaving effects of sleep, aging and progression of diseases related to aging. In this review, data from recent sleep and aging literature using metabolomics as principal molecular phenotyping methods is collated and compared. The present data suggests that metabolic effects of aging and sleep also demonstrate similarities, particularly in lipid metabolism and amino acid metabolism. Some of these changes also overlap with metabolomic data available from clinical studies of Alzheimer’s disease. Together, metabolomic technologies show promise in elucidating interleaving effects of sleep, aging and progression of aging disorders at a molecular level. |
format | Online Article Text |
id | pubmed-6971829 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | IOS Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-69718292020-01-22 Metabolism of sleep and aging: Bridging the gap using metabolomics Sengupta, Arjun Weljie, Aalim M. Nutr Healthy Aging Review Sleep is a conserved behavior across the evolutionary timescale. Almost all known animal species demonstrate sleep or sleep like states. Despite extensive study, the mechanistic aspects of sleep need are not very well characterized. Sleep appears to be needed to generate resources that are utilized during the active stage/wakefulness as well as clearance of waste products that accumulate during wakefulness. From a metabolic perspective, this means sleep is crucial for anabolic activities. Decrease in anabolism and build-up of harmful catabolic waste products is also a hallmark of aging processes. Through this lens, sleep and aging processes are remarkably parallel— for example behavioral studies demonstrate an interaction between sleep and aging. Changes in sleep behavior affect neurocognitive phenotypes important in aging such as learning and memory, although the underlying connections are largely unknown. Here we draw inspiration from the similar metabolic effects of sleep and aging and posit that large scale metabolic phenotyping, commonly known as metabolomics, can shed light to interleaving effects of sleep, aging and progression of diseases related to aging. In this review, data from recent sleep and aging literature using metabolomics as principal molecular phenotyping methods is collated and compared. The present data suggests that metabolic effects of aging and sleep also demonstrate similarities, particularly in lipid metabolism and amino acid metabolism. Some of these changes also overlap with metabolomic data available from clinical studies of Alzheimer’s disease. Together, metabolomic technologies show promise in elucidating interleaving effects of sleep, aging and progression of aging disorders at a molecular level. IOS Press 2019-12-19 /pmc/articles/PMC6971829/ /pubmed/31984245 http://dx.doi.org/10.3233/NHA-180043 Text en © 2019 – IOS Press and the authors. All rights reserved https://creativecommons.org/licenses/by-nc/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution Non-Commercial (CC BY-NC 4.0) License (https://creativecommons.org/licenses/by-nc/4.0/) , which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Review Sengupta, Arjun Weljie, Aalim M. Metabolism of sleep and aging: Bridging the gap using metabolomics |
title | Metabolism of sleep and aging: Bridging the gap using metabolomics |
title_full | Metabolism of sleep and aging: Bridging the gap using metabolomics |
title_fullStr | Metabolism of sleep and aging: Bridging the gap using metabolomics |
title_full_unstemmed | Metabolism of sleep and aging: Bridging the gap using metabolomics |
title_short | Metabolism of sleep and aging: Bridging the gap using metabolomics |
title_sort | metabolism of sleep and aging: bridging the gap using metabolomics |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6971829/ https://www.ncbi.nlm.nih.gov/pubmed/31984245 http://dx.doi.org/10.3233/NHA-180043 |
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