Arrhythmic Gut Microbiome Signatures Predict Risk of Type 2 Diabetes

Journal: Cell Host & Microbe

Published: 2020-06-29

DOI: 10.1016/j.chom.2020.06.004

Affiliations: 19

Authors: 25

Go to article

Research Highlight

Time-stamped stool reveals risk of diabetes



The relative abundances of different bacteria in the gut wax and wane predictably over the course of 24 hours. In people with obesity and type 2 diabetes, however, this regular daily pattern is perturbed — a finding that functionally links circadian rhythms in the gut microbiome with metabolic disease.

A Technical University of Munich–led team used DNA sequencing data from time-stamped stool samples, coupled with machine-learning techniques, to identify 13 taxonomic groups of oscillating gut bacteria that showed disrupted rhythmicity in obese, diabetic individuals.

This arrhythmic signature allowed the researchers to develop a predictive model that, when combined with body mass index, could identify individuals at highest risk of developing type 2 diabetes.

Microbial rhythmicity could thus serve as a potential diagnostic biomarker to improve the care and management of people with type 2 diabetes.

Supported content

  1. Cell Host & Microbe 28, 258–272.e6 (2020). doi: 10.1016/j.chom.2020.06.004
Institutions Share
TUM Institute for Food and Health (ZIEL), Germany 0.22
Department of Twin Research and Genetic Epidemiology, KCL, United Kingdom (UK) 0.12
Helmholtz Zentrum München - German Research Center for Environmental Health (HMGU), Germany 0.11
German Diabetes Center - Leibniz Institute for Diabetes Research at Heinrich Heine University Düsseldorf (DDZ), Germany 0.11
TUM School of Life Sciences Weihenstephan (WZW), Germany 0.10
School of Microbiology, UCC, Ireland 0.06
APC Microbiome Institute, UCC, Ireland 0.06
Institute of Clinical Molecular Biology (IKMB), UKSH Kiel, Germany 0.06
TUM Chair of Nutrition and Immunology, Germany 0.06
German Center for Diabetes Research (DZD), Germany 0.04
Institute of Medical Microbiology, RWTH Aachen, Germany 0.02
Faculty of Medicine, CAU, Germany 0.02
Universitary Center of Health Sciences at Klinikum Augsburg (UNIKA-T), Germany 0.01
Faculty of Medicine, LMU, Germany 0.01