Evaluation of inflammatory bowel disease activity in children using serum trefoil factor peptide

Diagnostic Procedures for Inflammatory Bowel Disease: Laboratory, Endoscopy, Pathology, Imaging, and Beyond

Diagnosing inflammatory bowel disease (IBD) can often be challenging, and differentiating between Crohn's disease and ulcerative colitis can be particularly difficult. Diagnostic procedures for IBD include laboratory tests, endoscopy, pathological tests, and imaging tests. Serological and stool tests can be easily performed in an outpatient setting and provide critical diagnostic clues. Although endoscopy is an invasive procedure, it offers essential diagnostic information and allows for tissue biopsy and therapeutic procedures. Video capsule endoscopy and device-assisted enteroscopy are endoscopic procedures used to evaluate the small bowel. In addition to endoscopy, magnetic resonance imaging, computed tomography, and ultrasound (US) are valuable tools for small bowel assessment. Among these, US is noninvasive and easily utilized, making its use highly practical in daily clinical practice. Endoscopic biopsy aids in the diagnosis of IBD and is crucial for assessing the histological activity of the disease, facilitating a thorough evaluation of disease remission, and aiding in the development of treatment strategies. Recent advances in artificial intelligence hold promise for enhancing various aspects of IBD management, including diagnosis, monitoring, and precision medicine. This review compiles current procedures and promising future tools for the diagnosis of IBD, providing comprehensive insights.

Emerging strategy towards mucosal healing in inflammatory bowel disease: what the future holds?

For decades, the therapeutic goal of conventional treatment among inflammatory bowel disease (IBD) patients is alleviating exacerbations in acute phase, maintaining remission, reducing recurrence, preventing complications, and increasing quality of life. However, the persistent mucosal/submucosal inflammation tends to cause irreversible changes in the intestinal structure, which can barely be redressed by conventional treatment. In the late 1990s, monoclonal biologics, mainly anti-TNF (tumor necrosis factor) drugs, were proven significantly helpful in inhibiting mucosal inflammation and improving prognosis in clinical trials. Meanwhile, mucosal healing (MH), as a key endoscopic and histological measurement closely associated with the severity of symptoms, has been proposed as primary outcome measures. With deeper comprehension of the mucosal microenvironment, stem cell niche, and underlying mucosal repair mechanisms, diverse potential strategies apart from monoclonal antibodies have been arising or undergoing clinical trials. Herein, we elucidate key steps or targets during the course of MH and review some promising treatment strategies capable of promoting MH in IBD.

Maternal Diet Determines Milk Microbiome Composition and Offspring Gut Colonization in Wistar Rats

Mother's milk contains a unique microbiome that plays a relevant role in offspring health. We hypothesize that maternal malnutrition during lactation might impact the microbial composition of milk and affect adequate offspring gut colonization, increasing the risk for later onset diseases. Then, Wistar rats were fed ad libitum (Control, C) food restriction (Undernourished, U) during gestation and lactation. After birth, offspring feces and milk stomach content were collected at lactating day (L)4, L14 and L18. The V3-V4 region of the bacterial 16S rRNA gene was sequenced to characterize bacterial communities. An analysis of beta diversity revealed significant disparities in microbial composition between groups of diet at L4 and L18 in both milk, and fecal samples. In total, 24 phyla were identified in milk and 18 were identified in feces, with Firmicutes, Proteobacteria, Actinobacteroidota and Bacteroidota collectively representing 96.1% and 97.4% of those identified, respectively. A higher abundance of Pasteurellaceae and Porphyromonas at L4, and of Gemella and Enterococcus at L18 were registered in milk samples from the U group. Lactobacillus was also significantly more abundant in fecal samples of the U group at L4. These microbial changes compromised the number and variety of milk-feces or feces-feces bacterial correlations. Moreover, increased offspring gut permeability and an altered expression of goblet cell markers TFF3 and KLF3 were observed in U pups. Our results suggest that altered microbial communication between mother and offspring through breastfeeding may explain, in part, the detrimental consequences of maternal malnutrition on offspring programming.

Tea (Camellia sinensis) ameliorates DSS-induced colitis and liver injury by inhibiting TLR4/NF-κB/NLRP3 inflammasome in mice

The gut-liver axis is a bidirectional relationship between the gut with its microbiota and the hepatic. Ulcerative colitis (UC) disrupts the intestinal barrier and influx of intestinal microorganisms and their products into the liver, which trigger liver injury. Tea consumption is associated with a low incidence of UC in Asian countries. In this study, we revealed the mechanisms of six types of tea water extracts (TWEs) obtained from the leaves of Camellia sinensis on the dextran sodium sulfate (DSS)-induced colitis and liver injury in mice. The TWEs significantly restored mucin production and increased the expression levels of tight junction (TJ) proteins such as zonula occludens-1 (ZO-1), occluding, and claudin-1. In addition, TWEs also reduced the levels of pro-inflammatory cytokines in the colon and liver tissue by inactivating the NF-κB/NLRP3. Moreover, TEWs treatment promoted the integrity of the intestinal barrier to reduce serum lipopolysaccharide (LPS) levels, thereby reducing liver injury caused by intestinal microbial translocation and LPS induction. Analysis of 16 S rRNA microbial sequencing revealed that tea water extracts (TWEs) restored the DSS-induced gut dysbiosis. Interestingly, our results showed that the degree of fermentation of tea leaves was negatively associated with the alleviation of DSS-induced colitis effects, and there was also an overall negative trend with colitis-induced liver injury, except for black tea. Taken together, tea consumption mitigated DSS-induced colitis and liver injury in mice via inhibiting the TLR4/NF-κB/NLRP3 inflammasome pathway.

Predictive models for endoscopic disease activity in patients with ulcerative colitis: Practical machine learning-based modeling and interpretation

Background

Endoscopic disease activity monitoring is important for the long-term management of patients with ulcerative colitis (UC), there is currently no widely accepted non-invasive method that can effectively predict endoscopic disease activity. We aimed to develop and validate machine learning (ML) models for predicting it, which are desired to reduce the frequency of endoscopic examinations and related costs.

Methods

The patients with a diagnosis of UC in two hospitals from January 2016 to January 2021 were enrolled in this study. Thirty nine clinical and laboratory variables were collected. All patients were divided into four groups based on MES or UCEIS scores. Logistic regression (LR) and four ML algorithms were applied to construct the prediction models. The performance of models was evaluated in terms of accuracy, sensitivity, precision, F1 score, and area under the receiver-operating characteristic curve (AUC). Then Shapley additive explanations (SHAP) was applied to determine the importance of the selected variables and interpret the ML models.

Results

A total of 420 patients were entered into the study. Twenty four variables showed statistical differences among the groups. After synthetic minority oversampling technique (SMOTE) oversampling and RFE variables selection, the random forests (RF) model with 23 variables in MES and the extreme gradient boosting (XGBoost) model with 21 variables in USEIS, had the greatest discriminatory ability (AUC = 0.8192 in MES and 0.8006 in UCEIS in the test set). The results obtained from SHAP showed that albumin, rectal bleeding, and CRP/ALB contributed the most to the overall model. In addition, the above three variables had a more balanced contribution to each classification under the MES than the UCEIS according to the SHAP values.

Conclusion

This proof-of-concept study demonstrated that the ML model could serve as an effective non-invasive approach to predicting endoscopic disease activity for patients with UC. RF and XGBoost, which were first introduced into data-based endoscopic disease activity prediction, are suitable for the present prediction modeling.

Biomarkers of Inflammation in Inflammatory Bowel Disease: How Long before Abandoning Single-Marker Approaches?

BACKGROUND

Inflammatory bowel disease (IBD) is a chronically relapsing disease with a continuous need for proactive monitoring to decide appropriate treatments and follow-up strategies. To date, gastrointestinal endoscopy with histologic examination of biopsies and contrast-enhanced imaging are mandatory techniques for the diagnosis and the activity assessment of IBD.

SUMMARY

In recent decades, many research efforts in the IBD field have been placed on finding non-invasive and reliable biomarkers of disease burden that can be easily tested in body fluids without impacting the quality of life of patients. Unfortunately, the ideal biomarker is yet to be discovered and recent studies have investigated the possibility to increase the accuracy of such measurements by combining different markers. In this review, we provide an update about the current knowledge on biomarkers of intestinal inflammation in IBD, focussing on disease diagnosis, correlation with endoscopic findings, and prediction of relapse. We also summarize composite scores of clinical and laboratory markers that have been recently proposed in various scenarios of disease activity. Key Messages: To date, only C-reactive protein and faecal calprotectin can be considered reliable markers of disease activity with demonstrated utility in IBD management. The combination of different parameters has recently shown higher accuracy and might substitute single-marker approaches in the future of research and clinical practice.