Co-occurrence of gut microbiota dysbiosis and bile acid metabolism alteration is associated with psychological disorders in Crohn's disease.

This study aims to elucidate the relationships between gut microbiota, bile acid metabolism, and psychological comorbidity in Crohn's disease (CD). We profiled the fecal microbiota composition and quantified the bile acid pool of 39 CD patients and 14 healthy controls using 16S rRNA gene sequencing and liquid chromatography-tandem mass spectrometry, respectively. Significant reductions in the secondary bile acids, LCA and DCA, were found in both the feces and serum samples of CD patients, while the concentration of 7-DHCA was particularly higher in the serum of CD patients with psychological disorders. The fecal levels of HDCA and 12-DHCA of the CD patients were inversely correlated with their Self-Rated Depression Scale (SDS) scores, whereas the serum level of 7-DHCA was positively correlated with the SDS scores. In addition, the fecal levels of TDCA, TLCA, and TßMCA showed a positive correlation with the Self-Rated Anxiety Scale (SAS) scores. The fecal microbiota biodiversity was particularly declined in CD patients with psychological disorders. An enrichment of Ruminococcus gnavus in CD patients may cause psychological disorders by affecting the microbiota-gut-brain axis via its ability to degrade the gut barrier, regulate the tryptophan-kynurenine metabolism, and modulate bile acid metabolism. In addition, the overabundant Enterobacteriaceae and Lachnospiraceae in CD patients may contribute to psychological comorbidity via dysregulating their bile acids metabolism. Taken together, changes in the gut microbiota composition may cooperate with alterations in the bile acid metabolism that are involved in the development of psychological disorders in CD.

A random forest model predicts responses to infliximab in Crohn's disease based on clinical and serological parameters.

BACKGROUND: Infliximab (IFX) has revolutionised the treatment for Crohn's disease (CD) recently, while a part of patients show no response to it at the end of the induction period. We developed a random forest-based prediction tool to predict the response to IFX in CD patients. METHODS: This observational study retrospectively enrolled the patients diagnosed with active CD and received IFX treatment at the Gastroenterology Department in Xiangya Hospital of Central South University between January 2017 and December 2019. The baseline data were recorded in the beginning and were used as predictor variables to construct models to forecast the outcome of the response to IFX. RESULTS: Our cohort identified a total of 174 patients finally with a response rate of 29.3% (51/174). The area under the receiver operating characteristic curve (AUC) for the model, based on the random forest was 0.90 (95%CI: 0.82-0.98), compared to the logistic regression model with AUC of 0.68 (95%CI: 0.52-0.85). The optimal cut-off value of the random forest model was 0.34 with the specificity of 0.94, the sensitivity of 0.81 and the accuracy of 0.85. We demonstrated a strong association of IFX response with the levels of complement C3 (C3), high density lipoprotein, serum albumin, Controlling Nutritional Status (CONUT) score and visceral fat area/subcutaneous fat area ratio (VSR). CONCLUSION: A novel random forest model using the clinical and serological parameters of baseline data was established to identify CD patients with baseline inflammation to achieve IFX response. This model could be valuable for physicians, patients and insurers, which allows individualised therapy.