Gut Microbiome Composition Is Predictive of Incident Type 2 Diabetes in a Population Cohort of 5,572 Finnish Adults

OBJECTIVE: To examine the previously unknown long-term association between gut microbiome composition and incident type 2 diabetes in a representative population cohort.

RESEARCH DESIGN AND METHODS: We collected fecal samples of 5 572 Finns (mean age 48.7 years, 54.1% women) in 2002 who were followed up for incident type 2 diabetes until Dec 31^st, 2017. The samples were sequenced using shotgun metagenomics. We examined associations between gut microbiome compositions and incident diabetes using multivariable-adjusted Cox regression models. We first used the Eastern Finland sub-population to obtain initial findings and validated these in the Western Finland sub-population.

RESULTS: Altogether 432 cases of incident diabetes occurred over the median follow-up of 15.8 years. We detected 4 species and 2 clusters consistently associated with incident diabetes in the validation models. These 4 species were Clostridium citroniae (HR, 1.21; 95% CI, 1.04-1.42), C. bolteae (HR, 1.20; 95% CI, 1.04-1.39), Tyzzerella nexilis (HR, 1.17; 95% CI, 1.01-1.36), and Ruminococcus gnavus (HR = 1.17; 95% CI, 1.01-1.36). The positively associated clusters, cluster 1 (HR, 1.18; 95% CI, 1.02-1.38) and cluster 5 (HR, 1.18; 95% CI, 1.02-1.36), mostly consisted of these same species.

CONCLUSIONS: We observed robust species-level taxonomic features predictive of incident type 2 diabetes over a long-term follow-up. These findings build on and extend previous mainly cross-sectional evidence and further support links between dietary habits, metabolic diseases, and type 2 diabetes that are modulated by the gut microbiome. The gut microbiome can potentially be used to improve the disease prediction and to uncover novel therapeutic targets for diabetes.