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. 2019 Oct 7;14(10):e0222394.
doi: 10.1371/journal.pone.0222394. eCollection 2019.

Gut microbiome diversity is associated with sleep physiology in humans

Affiliations

Gut microbiome diversity is associated with sleep physiology in humans

Robert P Smith et al. PLoS One. .

Abstract

The human gut microbiome can influence health through the brain-gut-microbiome axis. Growing evidence suggests that the gut microbiome can influence sleep quality. Previous studies that have examined sleep deprivation and the human gut microbiome have yielded conflicting results. A recent study found that sleep deprivation leads to changes in gut microbiome composition while a different study found that sleep deprivation does not lead to changes in gut microbiome. Accordingly, the relationship between sleep physiology and the gut microbiome remains unclear. To address this uncertainty, we used actigraphy to quantify sleep measures coupled with gut microbiome sampling to determine how the gut microbiome correlates with various measures of sleep physiology. We measured immune system biomarkers and carried out a neurobehavioral assessment as these variables might modify the relationship between sleep and gut microbiome composition. We found that total microbiome diversity was positively correlated with increased sleep efficiency and total sleep time, and was negatively correlated with wake after sleep onset. We found positive correlations between total microbiome diversity and interleukin-6, a cytokine previously noted for its effects on sleep. Analysis of microbiome composition revealed that within phyla richness of Bacteroidetes and Firmicutes were positively correlated with sleep efficiency, interleukin-6 concentrations and abstract thinking. Finally, we found that several taxa (Lachnospiraceae, Corynebacterium, and Blautia) were negatively correlated with sleep measures. Our findings initiate linkages between gut microbiome composition, sleep physiology, the immune system and cognition. They may lead to mechanisms to improve sleep through the manipulation of the gut microbiome.

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Conflict of interest statement

The authors have declared that no competing interests exist.

Figures

Fig 1
Fig 1. The interaction network between measures of sleep, microbiome diversity and cognitive performance.
Pearson correlation coefficients were used to generate the weight of each edge in the network. Heat map shown on image. Different colored circles indicate groupings of nodes with similar traits in the network (I = microbiome diversity, II = sleep, III = cognition). Raw data for correlations (outside of microbiome diversity control correlations) found in S1–S4 Figs. Directionality of interactions is not implied in this figure.
Fig 2
Fig 2. The association of richness and diversity within bacterial phyla, and with measures of sleep, IL-6 and cognition identified in our interaction network.
Only Pearson correlations coefficients with P ≤ 0.05 are shown.
Fig 3
Fig 3. Significant associations between bacterial taxa with measures of sleep, IL-6 and cognition identified in our interaction network.
Taxa were identified at the genus level unless otherwise indicated. Only Pearson correlations coefficients with P ≤ 0.05 are shown. Multiple boxes within the same column indicated significant associations between several operation taxonomic units (OTUs) and the node identified at the top of the column. Correlation coefficients and P values presented in S2 Table.

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