The Luxembourg Institute of Health have released the results of a study connecting the gut microbiome to the neurodegenerative disease multiple sclerosis (MS).
The study
The investigation, which features in the journal Nature Microbiology, aimed to study if the gut microbiome has any influence over MS progression of susceptibility through a pre-clinical model of MS — experimental autoimmune encephalomyelitis (EAE).
The study included mice of differing genetic backgrounds and microbiome composition, and also investigated how the body’s immune system is impacted by the gut microbiome.
Since there is little knowledge on the risk predictors associated with multiple sclerosis, the researchers wanted to establish what biomarkers are present when patients are going through disease progression to assist diagnostics.
“This approach allowed us to better examine how individual host–microbe interactions affect disease predictability, thus overcoming the limitations of approaches that only look at the relative abundances of bacterial species between MS-affected and healthy individuals and which cannot explain the observed individual differences in disease susceptibility and progression,” explains Prof. Desai, leader of the Nutrition, Microbiome & Immunity research group at the LIH and lead author of the publication.
The results
The investigation highlighted the role of certain gut microbial factors in influencing the progression of MS, and also how susceptible an individual may be to the disease.
This included the abundance of Akkermansia muciniphila, a gut bacteria that, if abundant, has been correlated with disease in MS patients.
The team found that the presence of this bacterium and it’s impact on disease progression was heavily influenced by the presence of other bacteria in the gut, and the presence of certain other gut bacteria could significantly increase disease severity in patients.
“These findings suggest that the impact of specific bacteria on MS may depend on the broader microbial community context, and that focusing on combinations of species or microbial networks — rather than single species alone — is essential to predict disease courses across different microbiota compositions”, Prof. Desai adds.