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Abstract Background The impact of the gut microbiome on the initiation and intensity of immune-related adverse events (irAEs) prompted by immune checkpoint inhibitors (ICIs) is widely acknowledged. Nevertheless, there is inconsistency in the gut microbial associations with irAEs reported across various studies. Methods We performed a comprehensive analysis leveraging a dataset that included published microbiome data (n = 317) and in-house generated data from 16S rRNA and shotgun metagenome samples of irAEs (n = 115). We utilized a machine learning-based approach, specifically the Random Forest (RF) algorithm, to construct a microbiome-based classifier capable of distinguishing between non-irAEs and irAEs. Additionally, we conducted a comprehensive analysis, integrating transcriptome and metagenome profiling, to explore potential underlying mechanisms. Results We identified specific microbial species capable of distinguishing between patients experiencing irAEs and non-irAEs. The RF classifier, developed using 14 microbial features, demonstrated robust discriminatory power between non-irAEs and irAEs (AUC = 0.88). Moreover, the predictive score from our classifier exhibited significant discriminative capability for identifying non-irAEs in two independent cohorts. Our functional analysis revealed that the altered microbiome in non-irAEs was characterized by an increased menaquinone biosynthesis, accompanied by elevated expression of rate-limiting enzymes menH and menC. Targeted metabolomics analysis further highlighted a notably higher abundance of menaquinone in the serum of patients who did not develop irAEs compared to the irAEs group. Conclusions Our study underscores the potential of microbial biomarkers for predicting the onset of irAEs and highlights menaquinone, a metabolite derived from the microbiome community, as a possible selective therapeutic agent for modulating the occurrence of irAEs.

Abstract Background Crohn’s disease (CD) is a chronic disease that may have an adverse impact on health-related quality of life (HRQoL). This study aimed to describe the HRQoL of CD patients and assess correlating factors using the EQ-5D-5L in China. Methods We recruited CD patients at Shanghai Renji Hospital from October 2018 to May 2019. The data collected included demographic and clinical information, medical expenditures, and EQ-5D-5L questionnaire responses. The chi-square test or Fisher’s exact test was applied to analyse the proportion of patients in subgroups at each level. After the selection of correlating variables by univariate analysis, multivariate regression analyses were used to explore the correlating factors of HRQoL in CD patients. Results A total of 202 CD inpatients with a mean disease duration of 3.3 years were enrolled in the study. A total of 71.8% of patients were males, and 49.5% of patients were aged between 30 and 49 years. The average EQ-5D-5L utility score was 0.85, with a standard deviation (SD) of 0.12. Males, ileum lesions, remission status, and lower expenditure predicted higher EQ-5D-5L scores. In each EQ-5D-5L dimension, the proportion of patients differed significantly by gender, disease activity and location subgroup. In the multivariate regression models, being in an active CD state and using antibiotics had significantly adverse impacts on HRQoL (p