A team of researchers from the Technical University of Munich (TUM) has examined the importance of daytime-dependent fluctuations of the gut microbiome in relation to type 2 diabetes. Their study is one of the largest studies related to microbiomes and diabetes, encompassing more than 4,000 participants.
The study was recently published in Cell Host & Microbe in a paper titled, “Arrhythmic Gut Microbiome Signatures Predict Risk of Type 2 Diabetes,” and led by Dirk Haller, PhD, professor for nutrition and immunology at TUM.
“When certain gut bacteria do not follow a day-night rhythm, so if their number and function do not change over the course of the day, this can be an indicator for a potential type 2 diabetes disease. Knowing this can improve diagnosis and outlook of type 2 diabetes,” explains Silke Kiessling, Ph.D., chronobiologist and co-author.
Arrhythmic bacteria are a marker for potential disease. “Mathematical models also show that this microbial risk signature consisting of arrhythmic bacteria helps to diagnose diabetes,” explains Sandra Reitmeier, first author on the study.
The researchers analyzed data from an existing independent cohort by Helmholtz Zentrum München. “By comparing our data to cohorts in England, we could confirm that there is—among other things—a strong regional factor affecting the microbial ecosystem. Therefore, there is a demand for finding locally specified arrhythmic risk signatures,” stated Haller.
“We demonstrate in 1,976 subjects of a German population cohort (KORA) that specific microbiota members show 24-h oscillations in their relative abundance and identified 13 taxa with disrupted rhythmicity in type 2 diabetes (T2D). Cross-validated prediction models based on this signature similarly classified T2D. In an independent cohort (FoCus), disruption of microbial oscillation and the model for T2D classification was confirmed in 1,363 subjects. This arrhythmic risk signature was able to predict T2D in 699 KORA subjects five years after initial sampling, being most effective in combination with BMI. Shotgun metagenomic analysis functionally linked 26 metabolic pathways to the diurnal oscillation of gut bacteria. Thus, a cohort-specific risk pattern of arrhythmic taxa enables classification and prediction of T2D, suggesting a functional link between circadian rhythms and the microbiome in metabolic diseases,” the researchers wrote.
Haller noted, that “apart from bacteria and their variations over the course of the day, other parameters such as the body mass index play a role in being able to better predict a person’s future medical conditions.”
This research proves the hypothesis that changes in the microbiome have an effect on nutrition-related diseases. How gut bacteria’s changes during the day affect other microbiome-associated diseases may be subject to further scientific examination.
