We’ve all been told to eat more yogurt to “aid digestion”. That’s because yogurt and other fermented foods contain common strains of bacteria like Lactobacilli and Streptococcus thermophilus, which naturally occur in our GI tract. But our gut microflora might play an even greater role in staying healthy than just supplementing our digestive system. A new study compared the gut microbiota of healthy individuals to obese and diabetic individuals. Results indicate that the unhealthy individuals are significantly lacking certain strains of bacteria compared to healthy individuals. This would seem to suggest an association between metabolic disorders and gut microflora. If this is the case, then the role that our gut microbes play is more complex than just helping break down food our GI tract.
I can’t comment on the study’s internal validity without seeing full results and statistical methods. However, I’d guess that the study was sufficiently powered (n=81) to find associations. Given the abundance of recent research on how diet influences gut microflora and advances in treating inflammatory bowel disease by replenishing gut microbes, I am inclined to believe these results.
I’d like to see causal inference methods done to tease apart the relationship between bacterial strains and diseases like diabetes. As it stands, the study provides no causal evidence for the associations they find. A third variable could be confounding the association and might provide a better therapeutic target than the intestinal microflora.
Some work has been done modeling the gut microbiome as a social network, where nodes in the network represent a species of bacteria and edges represent co-occurence of species in an individual. I’d like to see more of this line of thought. Species of bacteria may have symbiotic relationships, for example, if one produces food for another. Others may have antagonistic relationships. These relationships between bacteria manifest as correlations in the data, which can cause problems in parametric analyses. Network-based methods can better handle this type of data and give greater insight into how groups of bacterial species might be involved with obesity and diabetes.