Antigen-driven colonic inflammation is associated with development of dysplasia in primary sclerosing cholangitis

Protective function of sclerosing cholangitis on IBD

OBJECTIVE

There is a strong clinical association between IBD and primary sclerosing cholangitis (PSC), a chronic disease of the liver characterised by biliary inflammation that leads to strictures and fibrosis. Approximately 60%-80% of people with PSC will also develop IBD (PSC-IBD). One hypothesis explaining this association would be that PSC drives IBD. Therefore, our aim was to test this hypothesis and to decipher the underlying mechanism.

DESIGN

Colitis severity was analysed in experimental mouse models of colitis and sclerosing cholangitis, and people with IBD and PSC-IBD. Foxp3+ Treg-cell infiltration was assessed by qPCR and flow cytometry. Microbiota profiling was carried out from faecal samples of people with IBD, PSC-IBD and mouse models recapitulating these diseases. Faecal microbiota samples collected from people with IBD and PSC-IBD were transplanted into germ-free mice followed by colitis induction.

RESULTS

We show that sclerosing cholangitis attenuated IBD in mouse models. Mechanistically, sclerosing cholangitis causes an altered intestinal microbiota composition, which promotes Foxp3+ Treg-cell expansion, and thereby protects against IBD. Accordingly, sclerosing cholangitis promotes IBD in the absence of Foxp3+ Treg cells. Furthermore, people with PSC-IBD have an increased Foxp3+ expression in the colon and an overall milder IBD severity. Finally, by transplanting faecal microbiota into gnotobiotic mice, we showed that the intestinal microbiota of people with PSC protects against colitis.

CONCLUSION

This study shows that PSC attenuates IBD and provides a comprehensive insight into the mechanisms involved in this effect.

Opening the doors of precision medicine: novel tools to assess intestinal barrier in inflammatory bowel disease and colitis-associated neoplasia

Mounting evidence underscores the pivotal role of the intestinal barrier and its convoluted network with diet and intestinal microbiome in the pathogenesis of inflammatory bowel disease (IBD) and colitis-associated colorectal cancer (CRC). Moreover, the bidirectional association of the intestinal barrier with the liver and brain, known as the gut-brain axis, plays a crucial role in developing complications, including extraintestinal manifestations of IBD and CRC metastasis. Consequently, barrier healing represents a crucial therapeutic target in these inflammatory-dependent disorders, with barrier assessment predicting disease outcomes, response to therapy and extraintestinal manifestations.New advanced technologies are revolutionising our understanding of the barrier paradigm, enabling the accurate assessment of the intestinal barrier and aiding in unravelling the complexity of the gut-brain axis. Cutting-edge endoscopic imaging techniques, such as ultra-high magnification endocytoscopy and probe-based confocal laser endomicroscopy, are new technologies allowing real-time exploration of the 'cellular' intestinal barrier. Additionally, novel advanced spatial imaging technology platforms, including multispectral imaging, upconversion nanoparticles, digital spatial profiling, optical spectroscopy and mass cytometry, enable a deep and comprehensive assessment of the 'molecular' and 'ultrastructural' barrier. In this promising landscape, artificial intelligence plays a pivotal role in standardising and integrating these novel tools, thereby contributing to barrier assessment and prediction of outcomes.Looking ahead, this integrated and comprehensive approach holds the promise of uncovering new therapeutic targets, breaking the therapeutic ceiling in IBD. Novel molecules, dietary interventions and microbiome modulation strategies aim to restore, reinforce, or modulate the gut-brain axis. These advancements have the potential for transformative and personalised approaches to managing IBD.

IL-17 signaling in primary sclerosing cholangitis patient-derived organoids

BACKGROUND

The pathogenesis of primary sclerosing cholangitis (PSC) is unclear, although studies implicate IL-17A as an inflammatory mediator in this disease. However, a direct assessment of IL-17 signaling in PSC cholangiocytes is lacking. In this study, we aimed to investigate and characterize the response of PSC extrahepatic cholangiocyte organoids (ECO) to IL-17A stimulation.

METHODS

Cholangiocytes obtained from patients with PSC and without PSC by endoscopic retrograde cholangiography were cultured as ECO. The ECO were treated with vehicle or IL-17A and assessed by transcriptomics, secretome analysis, and genome sequencing.

RESULTS

Unsupervised clustering of all integrated single-cell RNA sequencing data identified 8 cholangiocyte clusters that did not differ between PSC and non-PSC ECO. However, PSC ECO cells demonstrated a robust response to IL-17 treatment, as noted by an increased number of differentially expressed genes by transcriptomics and more abundant chemokine and cytokine expression and secretion. After rigorous filtering, genome sequencing identified candidate somatic variants shared among PSC ECO from unrelated individuals. However, no candidate rare variants in genes regulating the IL-17 pathway were identified, but rare variants regulating the MAPK signaling pathway were present in all PSC ECO.

CONCLUSIONS

PSC and non-PSC patient-derived ECO respond differently to IL-17 stimulation, implicating this pathway in the pathogenesis of PSC.

Exploring potential causal associations between autoimmune diseases and colorectal cancer using bidirectional Mendelian randomization

Several observational studies have revealed an association between autoimmune diseases (AIDs) and colorectal cancer (CRC), although their causal association remained controversial. Therefore, our study used a two-sample Mendelian randomization (MR) analysis to verify the causal association between AIDs and CRC. We employed three common MR approaches, including inverse variance weighted (IVW), weighted median, and MR-Egger methods, to assess the causal association between type 1 diabetes (T1D), systemic lupus erythematosus, rheumatoid arthritis, psoriasis, multiple sclerosis, juvenile idiopathic arthritis, celiac disease, and primary sclerosing cholangitis (PSC) and CRC. The reverse MR analysis was performed to assess the possibility of reverse causation. To evaluate the validity of the analysis, we also performed sensitivity analysis, such as the heterogeneity test, the horizontal pleiotropy test, and the leave-one-out sensitivity analysis, and validated the results in the validation cohort. Our results showed that genetically predicted T1D was nominally associated with a lower risk of CRC (IVW OR = 0.965, 95% CI = 0.939-0.992, P = 0.012). However, genetic susceptibility to psoriasis nominally increased the risk of CRC (IVW OR = 1.026, 95% CI = 1.002-1.050, P = 0.037). Genetically predicted PSC had a significant causal effect on the increasing risk of CRC (IVW OR = 1.038, 95% CI = 1.016-1.060, P = 5.85 × 10-4). Furthermore, the MR analysis between PSC and the CRC validation cohort indicated consistent results. We found no causal association between genetically predicted other five AIDs and CRC (P > 0.05). The results of reverse MR analysis showed that genetically predicted CRC had no causal effect on T1D, psoriasis, and PSC (P > 0.05). The sensitivity analysis demonstrated that the results of the MR analysis were reliable. Our findings help to understand the causal association between AIDs and CRC, which deserves further investigation.

Pseudo-spectral angle mapping for automated pixel-level analysis of highly multiplexed tissue image data

The rapid development of highly multiplexed microscopy systems has enabled the study of cells embedded within their native tissue, which is providing exciting insights into the spatial features of human disease [1]. However, computational methods for analyzing these high-content images are still emerging, and there is a need for more robust and generalizable tools for evaluating the cellular constituents and underlying stroma captured by high-plex imaging [2]. To address this need, we have adapted spectral angle mapping - an algorithm used widely in hyperspectral image analysis - to compress the channel dimension of high-plex immunofluorescence images. As many high-plex immunofluorescence imaging experiments probe unique sets of protein markers, existing cell and pixel classification models do not typically generalize well. Pseudospectral angle mapping (pSAM) uses reference pseudospectra - or pixel vectors - to assign each pixel in an image a similarity score to several cell class reference vectors, which are defined by each unique staining panel. Here, we demonstrate that the class maps provided by pSAM can directly provide insight into the prevalence of each class defined by reference pseudospectra. In a dataset of high-plex images of colon biopsies from patients with gut autoimmune conditions, sixteen pSAM class representation maps were combined with instance segmentation of cells to provide cell class predictions. Finally, pSAM detected a diverse set of structure and immune cells when applied to a novel dataset of kidney biopsies imaged with a 43-marker panel. In summary, pSAM provides a powerful and readily generalizable method for evaluating high-plex immunofluorescence image data.

IL-17 Signaling in Primary Sclerosing Cholangitis Patient-Derived Organoids

The pathogenesis of primary sclerosing cholangitis (PSC) is unclear, although studies implicate IL-17A as an inflammatory mediator in this disease. However, a direct assessment of IL-17 signaling in PSC cholangiocytes is lacking. In this study we aimed to investigate the response of PSC extrahepatic cholangiocyte organoids (ECO) to IL-17A stimulation. Cholangiocytes obtained from PSC and non-PSC patients by endoscopic retrograde cholangiography (ERC) were cultured as ECO. The ECO were treated with vehicle or IL-17A and assessed by transcriptomics, secretome analysis, and genome sequencing (GS). Unsupervised clustering of all integrated scRNA-seq data identified 8 cholangiocyte clusters which did not differ between PSC and non-PSC ECO. However, PSC ECO cells demonstrated a robust response to IL-17 treatment, noted by an increased number of differentially expressed genes (DEG) by transcriptomics, and more abundant chemokine and cytokine expression and secretion. After rigorous filtering, GS identified candidate somatic variants shared among PSC ECO from unrelated individuals. However, no candidate rare variants in genes regulating the IL-17 pathway were identified, but rare variants regulating the MAPK signaling pathway were present in all PSC ECO. In conclusion, PSC and non-PSC patient derived ECO respond differently to IL-17 stimulation implicating this pathway in the pathogenesis of PSC.