A network analysis to identify possible alterations among different physiological systems induced by head down tilt bed rest

Space flight introduces unique stressors, challenging the body’s homeostasis. Ground-based simulations, like the − 6° head-down tilt test (HDT), help study these effects. While studies have explored the impact of space flight, they often employ limited analysis, overlooking the interconnected nature of the body’s systems. This study investigates the feasibility of employing network analysis on data derived from a retrospective collection of head-down tilt bedrest experiments provided by the European Space Agency (ESA), identifying potential links among various physiological systems that may serve as novel targets for possible countermeasures. The ESA’s data from HDT bed rest experiments, involving 60 subjects aged 20–46, were used. The studies included bedrest durations of 5, 21, or 60 days, with various countermeasures. Data from the BRAG study was excluded due to its short duration. Measures from control groups in the remaining studies were analyzed, including serum and urinary markers, aerobic fitness, cardiovascular responses, hematocrit levels, muscle performance, neuro-vestibular function, body composition, and daily weight. Two networks, representing baseline and post-bedrest evaluations, were constructed using Spearman partial correlation, correcting for HDT duration, number of trials, and BMI. Network topology was described using clustering coefficient, efficiency, and centrality metrics. Community detection was performed with the Louvain method, and results were compared to null models. The networks, consisting of 59 nodes each, exhibited distinct components, with some segregation of the baroreflex sensitivity indeces, as confirmed by the increased number of communities detected, as expected due to the cardiovascular deconditioning induced by gravitational unloading. Notably, cardiovascular features, particularly those associated with the autonomic nervous system (ANS), and bone markers were central in the networks. In particular, indices related to the parasympathetic branch show a predominant role in the network over the sympathetic counterpart, probably associated with anatomical aspects, and the complexity measures that provide information about the nonlinear balance in the ANS. Furthermore, bone markers seem to be influenced not only by fitness and other musculoskeletal features but also by neurovestibular and ANS factors. This influence is likely due to the activation of the sympathetic β pathway, suggesting that the ANS represents a key potential therapeutic target for alleviating the negative effects of spaceflight and prolonged bed rest.