The microbiota-gut-brain axis has emerged as a novel target in depression, a disorder with low treatment efficacy. However, the field is dominated by underpowered studies focusing on major depression not addressing microbiome functionality, compositional nature, or confounding factors. We applied a multi-omics approach combining pre-clinical models with three human cohorts including mild-depressed patients. Microbial functions and metabolites converging into glutamate/GABA metabolism, particularly proline, were linked to depression. Whole-brain dynamics revealed rich club network disruptions associated with depression and circulating proline. Proline supplementation in mice exacerbated depression along with microbial translocation. Human microbiota transplantation induced an emotional-impaired phenotype in mice and alterations in GABA-, proline-, and extracellular matrix-related pre-frontal cortex genes. Targeting the microbiome and dietary proline may open new windows for an efficient depression treatment.
Understanding the brain changes occurring during aging can provide new insights for developing treatments that alleviate or reverse cognitive decline. Neurostimulation techniques have emerged as potential treatments for brain disorders and to improve cognitive functions. Nevertheless, given the ethical restrictions of neurostimulation approaches, in silico perturbation protocols based on causal whole-brain models are fundamental to gaining a mechanistic understanding of brain dynamics. Furthermore, this strategy could serve as a more specific biomarker relating local activity with global brain dynamics. Here, we used a large resting-state fMRI dataset divided into middle-aged (N=310, aged < 65 years) and older adults (N=310, aged ≥ 65) to characterize brain states in each group as a probabilistic metastable substate (PMS) space, each with a probabilistic occurrence and frequency. Then, we fitted the PMS to a whole-brain model and applied in silico stimulations with different intensities in each node to force transitions from the brain states of the older group to the middle-age group. We found that the precuneus, a brain area belonging to the default mode network and the rich club, was the best stimulation target. These findings might have important implications for designing neurostimulation interventions to revert the effects of aging on whole-brain dynamics.
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