Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2020 Aug 12;28(2):258-272.e6.
doi: 10.1016/j.chom.2020.06.004. Epub 2020 Jul 2.

Arrhythmic Gut Microbiome Signatures Predict Risk of Type 2 Diabetes

Sandra Reitmeier  1 , Silke Kiessling  1 , Thomas Clavel  2 , Markus List  3 , Eduardo L Almeida  4 , Tarini S Ghosh  4 , Klaus Neuhaus  5 , Harald Grallert  6 , Jakob Linseisen  7 , Thomas Skurk  5 , Beate Brandl  5 , Taylor A Breuninger  6 , Martina Troll  6 , Wolfgang Rathmann  8 , Birgit Linkohr  6 , Hans Hauner  9 , Matthias Laudes  10 , Andre Franke  11 , Caroline I Le Roy  12 , Jordana T Bell  12 , Tim Spector  12 , Jan Baumbach  3 , Paul W O'Toole  4 , Annette Peters  13 , Dirk Haller  14
Affiliations
Free article

Arrhythmic Gut Microbiome Signatures Predict Risk of Type 2 Diabetes

Sandra Reitmeier et al. Cell Host Microbe. .
Free article

Abstract

Lifestyle, obesity, and the gut microbiome are important risk factors for metabolic disorders. 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 5 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.

Keywords: amplicon sequencing; circadian rhythms; diurnal oscillations; human intestinal microbiota; machine learning; metagenomics; obesity; population-based cohorts; prediction; type 2 diabetes.

PubMed Disclaimer

Conflict of interest statement

Declaration of Interests The authors declare no competing interests.

Comment in

Similar articles

See all similar articles

Cited by

See all "Cited by" articles

Publication types

MeSH terms

LinkOut - more resources