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Theou, O.

Publications and source records attributed to Theou, O..

2 recordsLinked to original sources

Effect of bedrest on the human gut and oral microbiome: implications for frailty

The physiological effects of spaceflight resemble those of ageing and prolonged inactivity, and ground-based microgravity analogs have emerged as promising models for studying frailty. The human microbiome is increasingly recognised for its role in age-associated decline, although precise mechanisms remain unclear. Here, we evaluate the gut and oral microbiomes of twenty-two participants, aged 55-65, who were enrolled in a head-down tilt bedrest (HDBR) study, the first Canadian HDBR study conducted in an older cohort. Participants were randomly assigned to an inactivity or multi-modality exercise intervention group for fourteen days of HDBR, followed by seven days of rehabilitation and additional follow-up appointments. Gut (n=343) and oral (n=344) taxonomic profiles were generated using V4/V5 16S rRNA gene sequencing from fecal and salivary samples collected throughout the study. Gut functional profiles were generated using metagenomic (n=86) and metabolomic (n=83) data. Frailty was measured using a 36-item frailty index. Inactivity-associated changes to the gut microbiome during HDBR included decreasing -diversity, decreasing Akkermansia and Lactobacillus, and increasing Bacteroides. Exercise-associated changes included increasing gut Roseburia. Interestingly, oral microbiome {beta}-diversity was more strongly associated with frailty than the gut. We conclude that inactivity-associated changes to the human microbiome could contribute to the early stages of frailty development, and that exercise can serve as an effective countermeasure against these effects. These results may inform strategies to preserve the health of both older adults facing prolonged periods of inactivity, as well as astronauts during longer space exploration missions. IMPORTANCEHealthy ageing carries significant demographic, economic, and public health implications globally, and both physical activity and human-associated microorganisms play important roles in its trajectory. Using microgravity simulation in older adults as a human frailty model, we show that short periods of inactivity could have significant effects on these microbial communities, particularly in the gut, which could further contribute to multi-system physiological decline and frailty pathogenesis. Participants who completed a daily, multi-modality exercise intervention did not exhibit these changes, which may help protect both older adults facing periods of inactivity and astronauts in the advent of longer space exploration missions. Interestingly, our results suggested that oral bacteria may be a more sensitive indicator of individual frailty levels than gut bacteria. Future research should ensure that functional aspects of human-associated microbial communities are thoroughly investigated, as these may offer deeper insight into their contributions to age-related decline.

microbiology↗

Probing the network structure of health deficits in human aging

Human aging leads to the stochastic accumulation of damage. We model an aging population using a stochastic network model. Individuals are modeled as a network of interacting nodes, representing health attributes. Nodes in the network stochastically damage and repair, with rates dependent on the state of their neighbors. Damaged nodes represent health deficits. The Frailty Index (FI) assesses age-related damage as the proportion of health deficits an individual has accumulated, from a selection of attributes. Here, we use computational, information-theoretic, and mean-field approaches to show that the degree distribution and degree correlations of the underlying network are important to the models ability to recover the behavior of observational health data. We use different measures of damage in the network to probe the structure of the network. We find that the behavior of different classes of observational health deficits (laboratory or clinical) is similar to the behavior of nodes of low or high degree in the model, respectively. This explains how damage can propagate within the network, leading towards individual mortality.

systems biology↗