Predictive Microbial Markers Distinguish Responders and Non-Responders to Adalimumab: A Step Toward Precision Medicine in Ulcerative Colitis.

Ulcerative colitis (UC) is a chronic, relapsing inflammatory disease of the colon, often associated with gut microbial dysbiosis. Although anti-TNF-α agents, such as Adalimumab (Cinnora®), are used to treat moderate-to-severe UC, the treatment response is highly variable. Identifying early microbial biomarkers of response could help support personalized therapeutic strategies and prevent unnecessary exposure to ineffective treatments. However, the long-term effects of anti-TNF therapy on both stool and mucosal microbiota remain poorly understood. This prospective longitudinal study included 23 corticosteroid-refractory or -dependent UC patients who started Adalimumab after endoscopy-confirmed flare-ups. Stool samples and inflamed colonic biopsies were collected at baseline, and 3 and 6 months. Microbiota profiling was performed using 16S rRNA sequencing. Microbial changes were analyzed over time and compared between responders (Mayo score 0-1) and non-responders (Mayo score ≥ 2). Sixty percent of patients achieved clinical remission. In responders, stool microbiota showed increased Bacteroidetes and decreased Proteobacteria abundances, along with an enrichment of beneficial taxa including Faecalibacterium prausnitzii, Bifidobacterium, and Akkermansia muciniphila. Mucosal microbiota exhibited persistent dysbiosis, characterized by an increase in Proteobacteria and a reduced Firmicutes/Proteobacteria ratio. Notably, responders showed distinct compartment-specific microbial changes, with a decrease in Gammaproteobacteria in stool and an increase in Corynebacterium in tissue. Adalimumab induces divergent microbial changes in stool and mucosa. While stool microbiota trends toward eubiosis in responders, persistent mucosal dysbiosis may reflect asymptomatic inflammation. These findings underscore the importance of niche-specific microbiome profiling in UC and support its integration into personalized treatment monitoring.