Introduction

Functional gastrointestinal disorders (FGIDs), such as irritable bowel syndrome (IBS) and functional dyspepsia, are prevalent conditions within the field of Neurogastroenterology. These disorders have a profound impact on patients’ quality of life and demand a comprehensive biopsychosocial approach to care. Despite evidence in favor of integrated care, treatment remains largely pharmacological. To address this gap, our hospital established a dedicated Functional Neurogastroenterology Unit by incorporating a nurse trained in health coaching and Neuro-Linguistic Programming (NLP) supported by a custom GPT-based artificial intelligence (AI) tool aimed at enhancing patient communication and clinical decision-making.

Results & Findings

A descriptive observational study was conducted on nurse-led consultations between September 2024 and April 2025. The intervention integrated coaching sessions, Neuro-Linguistic Programming (NLP), and the use of a customized GPT-based system to support communication and care planning. Data collected included demographic characteristics, presenting symptoms, and referral patterns. Additionally, each patient was invited to write a personal narrative reflecting on their experience throughout the intervention.

Summary & Discussion

Forty-eight patients were attended during the study period (mean age: 38.6 years; 68.7% female). The most common diagnoses were functional dyspepsia, irritable bowel syndrome, and nonspecific digestive disorders. Frequently reported symptoms included bloating, epigastric pain, early satiety and burning. 20.8% of patients were referred to psychology services and 2.1% to psychiatry. Patient narratives revealed improvements in emotional self-regulation, greater sense of empowerment, and high levels of satisfaction. AI reduced administrative burden, improving focus on direct care, interdisciplinary communication, and adherence to treatment.

Conclusion

Coaching, NLP and AI are effective tools to address FGIDs from nursing, promoting personalized care and improving the patient's emotional well-being.

References

1.Alenazi, S. K., et al. (2024). Integrating Artificial Intelligence Technologies into Nursing Practice: Revolutionizing Patient Care and Healthcare Efficiency. Journal of International Crisis & Risk Communication Research (JICRCR), 7.
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Introduction

Very early onset inflammatory bowel disease (VEO-IBD) is often associated with a severe disease course and unique characteristics including an underlying monogenic defect. In this study, we identified new pathogenic mutations in CGNL1 associated with VEO-IBD and other inflammatory GI disease. CGNL1 (Cingulin Like 1) encodes an epithelial junctional protein whose function was previously unknown in the gastrointestinal tract.

Aims & Methods

Whole exome sequencing (WES) was performed on the affected patient with VEO-IBD and all first-degree relatives with IBD and other inflammatory disease. Intestinal epithelial organoids (IEOs) were generated from the affected patient and were characterized by transepithelial electrical resistance (TEER), FITC-dextran permeability assay on epithelial cell monolayer, immunostaining, RNA sequencing, and transmission electron microscopy (TEM). In addition, we generated a new Cgnl1^-/- mouse model, which was characterized using FITC-dextran permeability assay, TEM, dextran-sodium sulfate (DSS)-induced colitis, and infections by Citrobacter rodentium and Clostridioides difficile. Single-cell datasets were analyzed to determine CGNL1 expression in IBD, primary sclerosing cholangitis (PSC), and autoimmune hepatitis (AIH).

Results

In the affected patient with VEO-IBD who required early total colectomy and pouch formation with coexistent PSC and celiac disease, WES identified two rare, new, pathogenic variants in the CGNL1 gene. Both pathogenic variants were also present in the patient’s younger sister, who has a similar history including early-onset, fulminant ulcerative colitis requiring total colectomy with ileostomy and PSC-AIH overlap syndrome. Furthermore, multiple relatives of the patient suffer from IBD and other inflammatory conditions including celiac disease, eosinophilic esophagitis, and type-1 diabetes. The RNA and protein levels of CGNL1 were significantly diminished in the patient’s intestinal epithelial cells compared to that of healthy individuals and other IBD patients by RNA-seq, immunoblotting, and immunostaining. The patient’s IEOs from pouch body and pre-pouch ileum formed smaller 3D spheroids with altered cell composition and significantly impaired barrier function compared to those from healthy controls and other IBD patients. Immunofluorescence and TEM demonstrated that CGNL1 is required for the assembly of junctional complexes in human IEOs and an epithelial cell line. Similarly to findings from the patient, impaired junctional complexes in intestinal epithelial cells and elevated intestinal permeability were present in Cgnl1^-/- mice at steady state. Cgnl1^-/- mice showed substantial vulnerability to DSS-induced colitis and bacterial infections that directly compromise the epithelial barrier. In addition, 6-month-old Cgnl1^-/- mice exhibited spontaneous inflammation in the colon and terminal ileum due to disrupted intestinal barrier, which was microbiome-dependent. Furthermore, single-cell analysis revealed diminished expression of CGNL1 in the intestinal and hepatic epithelial cells from patients with IBD or PSC/AIH, respectively.

Conclusion

The pathogenic CGNL1 variants contribute to VEO-IBD by disrupting gut barrier integrity, as demonstrated by patient’s cells and novel murine models. This study expands our understanding of epithelial barrier impairment in the pathogenesis of VEO-IBD, and highlights intestinal epithelium as a therapeutic target in some IBD patients.

Introduction

Current therapies for inflammatory bowel disease (IBD) suppress inflammation rather than inhibiting underlying microbial drivers. Treatment failures of frontline interventions, including corticosteroids, can lead to dose escalation and risk of adverse effects.^1,2 Bacteria with pro-inflammatory potential, like adherent-invasive Escherichia coli (AIEC), have been postulated as a possible microbial driver in Crohn’s disease (CD), however, targeting these bacteria with precision in IBD remains challenging.^3,4 Most antibiotics have broad-spectrum activity and disturb the background microbiome, which may exacerbate inflammation.⁵ Attention has shifted towards bacteriophages, yet their underlying mechanisms of treating IBD, and how they may work as an adjunctive therapy, remains elusive.

Aims & Methods

We aimed to assess whether and how phage therapy, specific for a CD-associated bacterium, reduces colitis severity using gnotobiotic mouse models.
In vitro kill curves and biofilm challenges were used to identify lytic phage candidates. Adult germ-free C57BL/6 mice were colonized with altered Schaedler-flora (ASF) and E. coli NRG857c (NRG), a CD-associated isolate. After 3 weeks, mice were treated with an NRG-specific lytic phage (1x10⁹ PFU/dose; daily or TIW) or vehicle (PBS) for 2 weeks (n=6/group) and then exposed to 1 cycle of dextran sulfate sodium (2%; DSS) in drinking water. PBS-treated mice (n=6) not exposed to DSS served as controls. Phage treatment was also tested in a spontaneous model of colitis using C57BL/6NTac-Il10^em8Tac (IL-10^-/-) mice, treated weekly. Mice were monitored daily for weight, stool consistency, and occult blood. Fecal contents were cultured to determine bacterial load, and the expression of NRG fimS was quantified using qPCR as an assessment of virulence. At endpoint, colon tissues were collected for histological and immunohistochemistry analysis to quantify colitis severity and NRG infiltration, respectively. Additional C57BL/6 mice were colonized and treated as previously described. During colitis induction, mice received a low-dose of budesonide (2μg/day)⁶ (n=5) or vehicle (n=5) until endpoint. Mice were monitored daily for disease activity and colon tissues were collected for histological analysis. HPLC was used to determine active budesonide levels.

Results

HER259 was identified as a lytic phage against CD-associated AIEC NRG. In ASF and NRG colonized mice, HER259 reduced clinical symptoms (p< 0.001, p< 0.001) and histological scores (p< 0.0001, p< 0.001) in chemical induced and spontaneous colitis, respectively. A 1-log reduction in NRG bacterial load was observed in HER259-treated mice (p< 0.001). Reisolated NRG exhibited a reduced FimS ON/OFF ratio (p-value < 0.01). Immunohistochemistry revealed reduced infiltration of NRG into the lamina propria following HER259 treatment, with greater accumulation in the epithelium. HER259 treatment increased the efficacy of a sub-therapeutic dosing regimen of budesonide (p< 0.001), which was independent of microbial-based drug metabolism as determined by HPLC.

Conclusion

Our results demonstrate that lytic phage targeting a CD-associated bacterium attenuates colitis in two gnotobiotic mouse models. The intervention did not lead to complete eradication of the disease-driving agent, but instead modulated bacterial virulence mechanisms and enhanced responses to corticosteroid therapy. The data suggests that alternative mechanisms should be considered when translating phage therapy to treat IBD in clinical trials.

References

1. Yan, Y. et al. Commensal bacteria promote azathioprine therapy failure in inflammatory bowel disease via decreasing 6-mercaptopurine bioavailability. Cell Rep Med 4, 101153 (2023).
2. Nagayama, M., Gogokhia, L. & Longman, R. S. Precision microbiota therapy for IBD: premise and promise. Gut Microbes 17, 2489067 (2025).
3. Darfeuille-Michaud, A. et al. High prevalence of adherent-invasive Escherichia coli associated with ileal mucosa in Crohn’s disease. Gastroenterology 127, 412–421 (2004).
4. A, D.-M. et al. Presence of adherent Escherichia coli strains in ileal mucosa of patients with Crohn’s disease. Gastroenterology 115, 1405–1413 (1998).
5. Nelson, R. L., Suda, K. J. & Evans, C. T. Antibiotic treatment for Clostridium difficile-associated diarrhoea in adults. Cochrane Database Syst Rev 3, (2017).
6. Bercik, P. et al. Chronic gastrointestinal inflammation induces anxiety-like behavior and alters central nervous system biochemistry in mice. Gastroenterology 139, (2010).

Introduction

Artificial Intelligence (AI)- enabled endoscopy and histology offer accurate, objective, and rapid assessment of disease activity in Ulcerative Colitis (UC). Emerging multi-source AI models integrating diverse datasets may enhance standardised disease evaluation and outcome prediction.

Aims & Methods

This study aimed to develop a novel AI model fusing endoscopic and histological findings to improve the assessment of disease remission and predict early response to therapy in UC clinical trials. A novel multimodal AI fusion algorithm was developed by integrating paired endoscopic videos and histological whole-slide images (WSIs) from the phase 2 clinical trial of Mirikizumab in UC (NCT02589665). The endoscopy branch of the model was trained with 291 white-light videos, using a convolutional neural network to select informative frames and the BioMedCLIP foundational model to extract features. The histology branch utilised the CONCH foundational model and was fine-tuned on 291 WSIs to obtain patch-level features. Features from both modalities were aggregated and fused using multi-head self-attention. The model’s ability to assess histological remission and response to therapy at weeks 12 and 52 was evaluated. Histological remission was defined as Geboes ≤2B.0, while a response to therapy at different time points was based on histological remission or improvement (Geboes <3.1).

Results

The fusion model outperformed single-modality assessments for histological remission, achieving a sensitivity of 89.72% (95% CI: 82.35–94.76), specificity of 89.67% (95% CI: 84.34–93.67), and accuracy of 89.69% (95% CI: 85.61–92.94). It demonstrated remarkable performance in assessing response to therapy at 12 and 52 weeks, with sensitivity of 97.96% (95% CI: 89.15–99.95), specificity of 86.84% (95% CI: 71.91–95.59) and accuracy of 93.10% (95% CI 85.59 – 97.43) for histological remission at week 52. Substantial agreement was observed between the AI fusion model and central readout.

Conclusion

This innovative multimodal fusion AI model enhances the assessment of histological remission and accurately predicts response to therapy. By potentially standardising central readouts and enabling automated disease assessment, this novel tool marks a significant advancement towards precision medicine in clinical trials.

Disclosure

Marietta Iacucci received research grants and consultant fees from Olympus, Pentax, Eli Lilly, and Janssen. All other authors declare no competing interests.