Gut metagenome in European women with normal, impaired and diabetic glucose control
Journal article, 2013

Type 2 diabetes (T2D) is a result of complex gene-environment interactions, and several risk factors have been identified, including age, family history, diet, sedentary lifestyle and obesity. Statistical models that combine known risk factors for T2D can partly identify individuals at high risk of developing the disease. However, these studies have so far indicated that human genetics contributes little to the models, whereas socio-demographic and environmental factors have greater influence(1). Recent evidence suggests the importance of the gut microbiota as an environmental factor, and an altered gut microbiota has been linked to metabolic diseases including obesity(2,3), diabetes(4) and cardiovascular disease(5). Here we use shotgun sequencing to characterize the faecal metagenome of 145 European women with normal, impaired or diabetic glucose control. We observe compositional and functional alterations in the metagenomes of women with T2D, and develop a mathematical model based on metagenomic profiles that identified T2D with high accuracy. We applied this model to women with impaired glucose tolerance, and show that it can identify women who have a diabetes-like metabolism. Furthermore, glucose control and medication were unlikely to have major confounding effects. We also applied our model to a recently described Chinese cohort(4) and show that the discriminant metagenomicmarkers for T2D differ between the European and Chinese cohorts. Therefore, metagenomic predictive tools for T2D should be specific for the age and geographical location of the populations studied.

Author

Fredrik Karlsson

Chalmers, Chemical and Biological Engineering, Life Sciences, System Biology

Valentina Tremaroli

University of Gothenburg

Intawat Nookaew

Chalmers, Chemical and Biological Engineering, Life Sciences, System Biology

Göran Bergström

University of Gothenburg

Carl Johan Behre

University of Gothenburg

Björn Fagerberg

University of Gothenburg

Jens B Nielsen

Chalmers, Chemical and Biological Engineering, Life Sciences, System Biology

Fredrik Bäckhed

University of Gothenburg

Nature

0028-0836 (ISSN) 1476-4687 (eISSN)

Vol. 498 7452 99-103

Areas of Advance

Information and Communication Technology

Life Science Engineering (2010-2018)

Subject Categories

Clinical Medicine

Infrastructure

C3SE (Chalmers Centre for Computational Science and Engineering)

DOI

10.1038/nature12198

More information

Created

10/7/2017