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

posted on 2022-01-31, 21:45 authored by Matti O. Ruuskanen, Pande P. Erawijantari, Aki S. Havulinna, Yang Liu, Guillaume Méric, Jaakko Tuomilehto, Michael Inouye, Pekka Jousilahti, Veikko Salomaa, Mohit Jain, Rob Knight, Leo Lahti, Teemu J. Niiranen
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 31st, 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.


This research was supported in part by grants from the Finnish Cultural Foundation, the Finnish Foundation for Cardiovascular Research, the Emil Aaltonen Foundation, the Finnish Medical Foundation, the Sigrid Juselius Foundation, and the Academy of Finland (#338818 to M.O.R.; #321356 to A.S.H.; #295741, #307127 to L.L.; #321351 to T.J.N.). Additional support was provided by Illumina, Inc. and Janssen Pharmaceutica through their sponsorship of the Center for Microbiome Innovation at UCSD.


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