Gut microbiome-based prediction of autoimmune neuroinflammation

Abstract

AbstractGut commensals are linked to neurodegenerative diseases, yet little is known about causal and functional roles of microbial risk factors in the gut–brain axis. Here, we employed a pre-clinical model of multiple sclerosis in mice harboring distinct complex microbiotas and six defined strain combinations of a functionally-characterized synthetic human microbiota. Discrete microbiota compositions resulted in different probabilities for development of severe autoimmune neuroinflammation. Nevertheless, assessing presence or the relative abundances of a suspected microbial risk factor failed to predict disease courses across different microbiota compositions. Importantly, we found considerable inter-individual disease course variations between mice harboring the same microbiota. Evaluation of multiple microbiome-associated functional characteristics and host immune responses demonstrated that the immunoglobulin A-coating index ofBacteroides ovatusbefore disease onset is a robust individual predictor for disease development. Our study highlights that the “microbial risk factor” concept needs to be seen in the context of a given microbial community network, and host-specific responses to that community must be considered when aiming for predicting disease risk based on microbiota characteristics.