The anterior cingulate cortex neurophenotypes predict suitability for anti-TNF-α agents in Crohn's disease

Purpose The lack of biomarkers hinders precision use of anti-TNF-α agents in Crohn's disease (CD). In this real-world study, we aimed to develop and validate a machine learning model based on ACC-focused multiparametric MRI to predict patient suitability for anti-TNF-α agents. Materials and methods In this prospective dual-center study, 109 CD patients underwent baseline ACC-focused multiparametric MRI, MR enterography, ileocolonoscopy, and serum biomarker assessment. Using 11 machine learning algorithms, an ACC neurophenotype model was built from 584 features to stratify patients into high- or low-risk groups. Outcomes after 25 ± 4 months were compared between anti-TNF-α agents and conventional therapy using propensity-score matching (PSM) and inverse-probability-of-treatment weighting (IPTW), with subsequent validation in a DSS-induced colitis mouse model where stratified mice received anti-TNF-α agents or conventional treatment. Results The ACC model showed strong neurophenotype discrimination (AUC training = 0.921; AUC test = 0.861, both P < 0.050). Higher ACC neuro-scores correlated with increased blood-brain-barrier-permeability (elevated S100β), psychological distress, reductions in key serum neurotransmitters (tryptophan and histidine), and worse abdominal conditions (abdominal pain scores, intestinal inflammation) ( r = 0.189–0.578; all P < 0.050). Critically, high-risk patients derived significantly longer progression-free survival from anti-TNF-α agents versus conventional therapy ( P log-rank = 0.049), a benefit robust to PSM ( P log-rank = 0.029) and IPTW ( P log-rank = 0.049) adjustments, while low-risk patients showed no benefit. Similarly, in DSS-colitis mice, high-risk mice showed significantly greater improvement with anti-TNF-α agents than conventional therapy across brain (neuronal loss, S100β, microtubule-associated protein 2), systemic (IL-6), and intestinal (α-1-antitrypsin) metrics (all P < 0.050), whereas low-risk mice showed no such benefit. Conclusions An ACC-focused neurophenotype model derived from multiparametric MRI assessed brain-gut dysregulation, allowing for patient stratification to optimize selection of anti-TNF-α agents therapy in CD.