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

Abstract

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. 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, diabetes and cardiovascular disease. 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 and show that the discriminant metagenomic markers 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.

Metabolic syndrome and nonalcoholic fatty liver disease: Is insulin resistance the link?

“…This was associated with increased butyrateproducing bacteria (mainly Roseburia and Eubacterium halii) in feces. This study was supported by others investigations that observed decreased butyrate-producing bacteria in the gut microbiota of diabetic patients (Karlsson et al, 2013;Qin et al, 2012). Butyrate is a short-chain fatty acids produced by the intestinal bacteria through a fermentation process (Cummings, 1981).…”

Subspecies in the global human gut microbiome

“…The TLR5 receptor in human epithelial cells (colonocytes) recognizes the flagellum and induces a downstream cascade which results in initiation of pro‐inflammatory pathways and secretion of IL‐8 (Neville et al , 2013). Such low‐grade inflammation has been repeatedly linked to obesity, increased insulin resistance, and diabetes (Gregor & Hotamisligil, 2011) providing a potential explanation for our observation that BMI and insulin resistance are significantly higher in individuals who predominantly harbor the flagellum‐carrying subspecies (MGSS2 and MGSS3) in the Danish (Le Chatelier et al , 2013) and Swedish (Karlsson et al , 2013) cohorts (Fig 3D). This association is independent of the specific abundance of the subspecies in the individuals.…”

“…In addition to these global associations, separate statistical tests within each study cohort revealed a strong negative association between type 2 diabetes status specifically in Chinese individuals (Qin et al , 2012) and Bacteroides coprocola MGSS3 , which is enriched in healthy individuals (Fisher test P ‐value 2.98e‐05). This association was, however, not significant in the two type 2 diabetes case–control studies with smaller cohorts (Karlsson et al , 2013; Le Chatelier et al , 2013). …”

“…To this end, we assessed the microbial genetic landscape of 2,144 deeply sequenced human stool metagenomes from nine countries, spanning three continents, including published (Huttenhower et al , 2012; Qin et al , 2012; Karlsson et al , 2013; Le Chatelier et al , 2013; Zeller et al , 2014) as well as 298 newly generated ones (Table EV1). The newly sequenced samples include a Kazakh cohort as well as three individuals from Germany that have been sampled over an extended period of time (see Materials and Methods).…”

“…Specifically, we used 239 stool samples from the HMP (Huttenhower et al , 2012) collected from 139 US American individuals, as well as 676 oral samples from the same individuals; 156 samples from as many Austrian individuals (Yu et al , 2015); 368 Chinese samples (Qin et al , 2012); 387 Danish samples from the MetaHIT cohort; 156 French and 40 German samples (Zeller et al , 2014); 126 novel German samples collected from 26 individuals; 172 novel Kazakh samples from 86 individuals; 359 Spanish samples from MetaHIT; and 145 Swedish samples (Karlsson et al , 2013; Table EV1). Informed consent was obtained from the German individuals through the my.microbes project (http://my.microbes.eu).…”