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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...

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Detalles Bibliográficos
Autores principales: Sengupta, Arjun, Weljie, Aalim M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: IOS Press 2019
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.
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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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