Microbial Signature in Adipose Tissue of Crohn's Disease Patients.

Crohn's disease (CD) is characterized by compromised immune tolerance to the intestinal commensal microbiota, intestinal barrier inflammation, and hyperplasia of creeping fat (CF) and mesenteric adipose tissue (AT), which seems to be directly related to disease activity. Gut microbiota dysbiosis might be a determining factor in CD etiology, manifesting as a low microbial diversity and a high abundance of potentially pathogenic bacteria. We tested the hypothesis that CF is a reservoir of bacteria through 16S-rRNA sequencing of several AT depots of patients with active and inactive disease and controls. We found a microbiome signature within CF and mesenteric AT from patients, but not in subcutaneous fat. We failed to detect bacterial DNA in any fat depot of controls. Proteobacteria was the most abundant phylum in both CF and mesenteric AT, and positively correlated with fecal calprotectin/C-reactive protein. Notably, the clinical status of patients seemed to be related to the microbiome signature, as those with the inactive disease showed a reduction in the abundance of pathogenic bacteria. Predictive functional profiling revealed many metabolic pathways including lipopolysaccharide biosynthesis and sulfur metabolism overrepresented in active CD relative to that in inactive CD. Our findings demonstrate that microbiota dysbiosis associated with CD pathophysiology is reflected in AT and might contribute to disease severity.

PPARgamma mRNA expression is reduced in peripheral blood mononuclear cells after fat overload in patients with metabolic syndrome.

PPARgamma is a transcriptional regulator of metabolism; its activity can be modulated by direct binding of dietary lipids. The most prevalent human PPARgamma gene variant, Ala12, is associated with postprandial hypertriglyceridemia in patients with metabolic syndrome, although the mechanism whereby this polymorphism affects lipid homeostasis remains to be fully determined. Using peripheral blood mononuclear cells (PBMC), we studied the effect of the Pro12 and Ala12 polymorphisms on mRNA expression of PPARgamma and nuclear factor kappa B genes before and 3 and 4 h after fat overload. We also studied several biochemical and oxidative stress variables. Most of the indicators of oxidative stress were higher in patients with metabolic syndrome than in healthy subjects before and after fat overload. Patients also differed depending on whether they had the Pro12 or Ala12 variant in PBMC; PPARgamma expression was lower in healthy subjects compared with patients. After fat overload, circulating triglycerides and PPARgamma expression were positively correlated (r = 0.617, P < 0.05), and PPARgamma expression tended to be negatively correlated with 2 important markers of oxidative stress: plasma lipid peroxidation (r = -0.224, P < 0.1) and carbonylated proteins (CPro) (r = -0.340, P < 0.1) concentrations. We also found differences in several indicators of oxidative stress between Pro12 and Ala12 patients, including an increase in plasma CPro before and after fat overload in Ala12 but not Pro12 patients. These data provide evidence that the Ala12 sequence variant is associated with a worse metabolic profile than Pro12. This is related to differences in the expression of PPARgamma and to oxidative imbalance after fat overload.

The gut microbiota profile is associated with insulin action in humans.

The role of the gut microbiota in the induction of metabolic diseases has now been increasingly recognized worldwide. Indeed, a specific gut microbiota has been shown to characterize lean versus obese phenotypes both in humans and mice. We have also recently demonstrated that a precise gut microbiota is associated with the host's responsiveness to a high-fat diet. Therefore, we hypothesized that insulin resistance in humans could also be linked to a specific gut microbiota. To this aim, microbial DNA and RNA were extracted from the appendix contents of insulin-resistant versus insulin-sensitive obese subjects, matched for body mass index and age, and analyzed by DNA- and RNA-DGGE. Microbial DNA analysis showed that the patients fully segregated according to their degree of insulin action. Conversely, microbial RNA investigation showed that some degree of homology still existed between insulin-sensitive and insulin-resistant patients. Quantitative trait analysis, ordinary least squares regression, principal components regression, partial least squares, canonical correlation analysis, and canonical correspondence analysis also showed a net separation of the two phenotypes analyzed. We conclude that a specific gut microbial profile is associated with insulin action in humans.