Clinical and Translational Gastroenterology最新文献

Introduction: Pancreatitis-associated osteopathy is a clinically significant but mechanistically underexplored complication of pancreatic disease. We aimed to characterize stage-specific alterations in bone remodeling biomarkers across the spectrum of disease: recurrent acute pancreatitis (RAP) and chronic pancreatitis (CP).

Methods: In a cross-sectional analysis of North American Pancreatitis Study 2 participants, we measured serum mechanistic (sclerostin, dickkopf-1, receptor activator of nuclear factor κβ ligand, and osteoprotegerin), hormonal (fibroblast growth factor 23, insulin, and leptin), and modulatory (osteopontin, oncostatin, and osteoactivin) markers in controls (n = 30), RAP (n = 40), and CP (n = 40) using a multiplex assay. Group differences were assessed with ANOVA, Fisher exact test, and Kruskal-Wallis; multivariable regression identified predictors of biomarker variation.

Results: Eight of 10 biomarkers differed significantly among groups. Sclerostin, dickkopf-1, receptor activator of nuclear factor κβ ligand, and osteoprotegerin were elevated in RAP and CP vs controls, with the highest values in CP. The RANKL/OPG ratio was greatest in CP. Fibroblast growth factor 23 was increased in RAP, while insulin was reduced in CP. Osteopontin and oncostatin were elevated in pancreatitis groups, with osteopontin increasing progressively from control to RAP to CP. Several bone biomarker patterns varied by sex, tobacco, and alcohol use. Stepwise regression identified several significant predictors.

Discussion: These findings represent the most comprehensive bone metabolism biomarker profiling in pancreatitis to date, revealing stage-specific dysregulation of bone remodeling. Findings suggest a shift toward increased bone resorption and impaired formation with disease progression. Larger longitudinal studies are needed for marker validation, to clarify mechanisms, and guide targeted interventions to reduce bone loss and fracture risk in this high-risk population.

Introduction: Functional dyspepsia (FD), a disorder of gut-brain interaction defined by Rome IV criteria, overlaps frequently with irritable bowel syndrome (IBS) and reflux symptoms. Overlapping gastrointestinal (GI) disorders are associated with more psychological comorbidities and decreased quality of life, but data on physiological parameters in overlapping syndromes are scarce. The aim of this study was to evaluate the impact of overlapping disorders and FD subtypes on psychological and GI symptoms, as well as relevant physiological outcomes.

Methods: In total, 202 patients with predominant Rome IV FD symptoms and overlapping IBS and/or reflux were pooled from 7 studies conducted at University Hospitals Leuven. GI and psychological symptoms, as well as GI-related quality of life were recorded. Physiological measurements included salivary cortisol, gastric emptying, systemic and duodenal immune activation, and duodenal permeability.

Results: GI (Patient Assessment of Upper GI Symptom Severity and Leuven Postprandial Distress Scale [ P < 0.0001]) and psychological (anxiety [ P = 0.0014], depression [ P = 0.0017] and extraintestinal somatic symptoms [ P < 0.0001]) were more pronounced in FD with overlapping disorders, whereas all physiological parameters were similar. Patients with epigastric pain syndrome reported a milder symptom pattern compared with other FD subtypes, with similar physiological alterations. Duodenal eosinophils were associated with anxiety in FD, independent of overlapping GI disorders or subtype ( P = 0.043).

Discussion: The common overlap between FD, IBS, and reflux is characterized by a high GI-specific, psychological, and somatic symptom burden. By contrast, key pathophysiological parameters were not different between FD with and without overlapping disorders or between FD subtypes. Central integration of multiple GI manifestations rather than more severely impaired peripheral alterations is more likely to explain the high symptom burden in overlapping disorders.

Introduction: Despite the growing recognition of autoimmune hepatitis (AIH)-metabolic dysfunction-associated steatotic liver disease (MASLD) overlap, studies today are limited by small sample sizes. The aim of this study was to investigate the impact of MASLD on the outcomes of patients with AIH using large-scale real world data.

Methods: This cohort study used the TriNetX research network to identify US adults (≥18 years) with AIH. Patients were stratified into those with MASLD (AIH-MASLD cohort) and controls (AIH without MASLD). Propensity score matching (1:1) between AIH-MASLD and controls accounted for demographics, comorbidities, and treatments. Outcomes were classified as short-term (within 1 year after diagnosis) or long-term (within 10 years) outcomes.

Results: Among 4,798 records with AIH, 1,440 AIH-MASLD patients were propensity matched with 1,440 controls. AIH-MASLD patients demonstrated reduced 1-year risks of all-cause mortality (hazard ratio [HR] 0.66, 95% confidence interval [CI] 0.44-0.98) and immunosuppressive medication use (HR 0.69, 95% CI 0.63-0.76), along with increased 10-year risks of cirrhosis (HR 1.22, 95% CI 1.06-1.40) and hepatocellular carcinoma (HR 2.03, 95% CI 1.09-3.78) compared with controls.

Discussion: In summary, our study using real-world evidence showed a significant association between MASLD and worse clinical outcomes in patients with AIH. Future efforts should be targeted toward facilitating early detection and management of MASLD in patients with AIH.

Introduction: Glucagon-like peptide-1 receptor agonists (GLP-1RA) are increasingly used for managing diabetes and obesity. Although they improve glycemic control, they also delay gastrointestinal motility, potentially leading to inadequate bowel preparation for colonoscopy, which can increase the risk of missed lesions. This study aimed to evaluate the impact of GLP-1RA use on the quality of bowel preparation and on adenomas and sessile serrated polyp (SSP) detection.

Methods: We conducted a retrospective cohort study of outpatient screening and surveillance colonoscopies at a tertiary academic medical center. Adults who used a GLP-1RA within 1 week of their colonoscopy formed the treatment group; patients not on GLP-1RA (nonusers) who never used GLP-1RA served as controls. Propensity score weighting was applied for age, sex, BMI, race, diabetes status, and relevant medications. The subgroup analysis was stratified based on diabetes status and GLP-1RA use.

Results: Among 49,987 patients (4,269 GLP-1RA users, 45,718 nonusers), GLP-1RA use was associated with increased odds of inadequate bowel preparation (odds ratio [OR] 1.23, 95% confidence interval [CI] 1.04-1.46). No significant difference in SSP and adenoma detection was observed. In subgroup analysis, GLP-1RA users with diabetes had the highest odds of inadequate preparation (OR 1.88, 95% CI 1.59-2.24) and the lowest odds of SSP detection (OR 0.71, 95% CI 0.57-0.89).

Discussion: GLP-1RA use, particularly among patients with diabetes, is associated with higher odds of inadequate bowel preparation and lower SSP detection, whereas adenoma detection was unaffected. Tailored bowel-prep protocols for GLP-1RA users with diabetes should be evaluated prospectively.

Introduction: Crohn's disease (CD) and ulcerative colitis (UC) have overlapping symptoms, but they differ in pathology and treatment. Currently, distinguishing between these diseases involves invasive procedures such as colonoscopy and histopathology. Fecal proteins, stable and in direct contact with inflammation, offer a noninvasive alternative. This study focuses on using high-throughput data-independent acquisition mass spectrometry and machine learning to develop an accurate biomarker signature from complex stool samples.

Methods: Stool samples obtained from 69 active patients were analyzed. Analysis of the stool proteome led to the identification and quantification of approximately 1,250 proteins. The samples were divided into training and testing groups. After data processing, various feature selection algorithms were applied on the training group to determine proteins that were significantly different between the CD and UC groups. In addition, 6 machine learning algorithms were evaluated to identify the best-performing classifiers.

Results: Sixteen proteins were selected based on several feature selection algorithms, and 6 models were trained based on them. According to the performance metrics of each algorithm on the training data set, the Naive Bayes model was selected. For performance validation, the final predictive model was applied to 16 blind prospective samples as the test data set. Notably, the model achieved an area under the curve of 0.96 on both the training and test data sets, highlighting its robustness and stability.

Discussion: This study demonstrates the potential of combining multiple stool protein biomarkers through high-throughput data-independent acquisition mass spectrometry and machine learning tools to develop a predictive model for efficiently distinguishing CD from UC.

Introduction: Severe acute pancreatitis (SAP) is a life-threatening condition requiring early risk stratification. Although the Bedside Index for Severity in Acute Pancreatitis (BISAP) is widely used, its reliance on complex parameters limits its applicability in resource-constrained settings. This study introduces a decision tree model based on Classification and Regression Tree (CART) analysis, using neutrophil-to-lymphocyte ratio (NLR) and C-reactive protein (CRP), as a simpler alternative for early SAP prediction.

Methods: In a prospective cohort of 340 patients at National Hospital, Vietnam (November 2022-September 2023), NLR, CRP, and BISAP scores were assessed on admission. CART analysis was used to develop a decision tree, and model performance was compared with BISAP using receiver operating characteristic curves, decision curve analysis.

Results: The CART model identified NLR ≥11.4 and CRP ≥173.3 mg/L as optimal thresholds for SAP prediction. The model achieved an area under the curve 0.866 in the validation cohort, statistically comparable with BISAP (area under the curve = 0.900, P = 0.286). The model demonstrated high sensitivity (90.9%), specificity (84.5%), and accuracy (86.25%), confirming its robustness. Decision curve analysis highlighted similar clinical benefits with BISAP, but the CART-based model offered greater simplicity, making it ideal for resource-limited settings.

Discussion: The CART-derived decision tree using NLR and CRP provides an accessible and reliable tool for early SAP prediction. With performance comparable with BISAP but requiring fewer resources, this model supports rapid, evidence-based decision-making in clinical practice.

Introduction: Although colorectal cancer (CRC) screening has been incorporated into organized programs in many countries, a universally accepted noninvasive and efficient screening method remains unavailable. This study aimed to assess the diagnostic potential of volatile organic compounds in exhaled breath through electronic nose (eNose) for noninvasive CRC detection.

Methods: The Cyranose320 sensor device was used to collect and analyze breath samples. Supervised machine learning was applied to evaluate the diagnostic performance of the eNose in CRC detection, using a randomly assigned training and validation set. Two-thirds of the breath samples were used to train models, which were then validated on the remaining patients (external validation). Three machine learning methods were applied for classification: random forest, extreme gradient boosting (XGBoost), and quadratic discriminant analysis.

Results: A total of 105 patients with CRC and 101 healthy controls were included. After adjusting for baseline covariates (age, sex, smoking, and comorbidities), machine learning models based on volatile organic compound profiles could differentiate patients with CRC from healthy controls, achieving areas under the receiver operating characteristic curve (AUC) of at least 0.72 in both the training and validation sets. The final CRC classification models yielded AUCs of 0.93 for random forest, 0.88 for XGBoost, and 0.89 for quadratic discriminant analysis. Furthermore, eNose classified CRC by stage, with an AUC exceeding 0.70 for early and advanced disease.

Discussion: Exhaled breath analysis using an eNose may serve as a promising noninvasive method for CRC detection. Further studies with larger populations are needed to confirm its clinical impact.

Introduction: Acute variceal bleeding (AVB) is a severe complication of cirrhosis, with a 6-week mortality rate of up to 15%-20%. Early risk prediction is essential for guiding management. Model for End-Stage Liver Disease (MELD) 3.0, a refined version of the original MELD score, incorporates additional variables (sex, sodium, albumin, capped creatinine) to improve short-term mortality prediction. This study assessed MELD 3.0's use in predicting 6-week mortality in cirrhotic patients with AVB, in comparison with MELD, Glasgow-Blatchford Score (GBS), and Albumin, INR, Mental status, Systolic blood pressure, Age ≥ 65 (AIMS65).

Methods: A prospective cohort of cirrhotic patients with AVB admitted to Cho Ray Hospital (November 2023-May 2024) was studied. The primary outcome was 6-week mortality; in-hospital mortality was secondary. The predictive performance of MELD 3.0, MELD, GBS, and AIMS65 was evaluated using area under the receiver operating characteristic (AUROC).

Results: Among 212 patients, in-hospital and 6-week mortality rates were 4.7% and 19.8%, respectively. For in-hospital mortality, MELD 3.0 showed the highest AUROC (0.88), followed by MELD (0.80), AIMS65 (0.74), and GBS (0.59). For 6-week mortality, MELD 3.0 again outperformed others (AUROC: 0.81), vs MELD (0.75), AIMS65 (0.66), and GBS (0.61) (all P < 0.05). A MELD 3.0 cutoff ≥ 20 predicted >25% 6-week mortality (sensitivity 69.1%, specificity 83.5%).

Discussion: MELD 3.0 is a strong predictor of early mortality in cirrhotic patients with AVB. A cutoff ≥20 may help identify high-risk patients requiring prompt intensive care.

Introduction: Patients with inflammatory bowel disease (IBD) are at increased risk of herpes zoster and should receive the recombinant herpes zoster vaccine (RZV). We sought to assess the immunogenicity and safety of RZV series in patients receiving anti-tumor necrosis factor (TNF) therapy compared with those receiving vedolizumab.

Methods: This single-center prospective study enrolled patients with IBD on vedolizumab or anti-TNF monotherapy receiving RZV. Primary outcome assessed cell-mediated immunity (CMI) differences between groups postvaccination. Secondary outcomes included humoral response, sustained immunity, and safety monitoring for adverse events and IBD flares. Assessments occurred at baseline, 30, 240, and 425 days postvaccination. Statistical analyses included nonparametric Mann-Whitney U tests for between-group comparisons and Wilcoxon signed-rank tests for within-group changes, with significance set at P < 0.05.

Results: Thirty-three patients enrolled (16 vedolizumab, 17 anti-TNF). CMI responses increased postvaccination in both groups (median 56 cells/million [interquartile range {IQR} 21-102] vs 33 cells/million [IQR 11-73]; P = 0.13), with no significant difference between treatment groups. Both groups showed strong antibody responses to vaccination (preimmunization median: 349.9 mIU/mL [IQR 276.8-402.5] vs 90-day median: 605.0 mIU/mL [IQR 525.6-641.0]; P < 0.001). CMI responses remained elevated at both day 240 and 425 assessments. Antibody levels remained elevated through day 425 (549.1 mIU/mL, IQR 516.1-585.6), substantially higher than prevaccination levels. No IBD flares occurred; most adverse events were mild and transient.

Discussion: RZV demonstrated robust immunogenicity and favorable safety profile in patients with IBD receiving either vedolizumab or anti-TNF therapy. Both cellular and humoral immune responses persisted through 425 days postvaccination.

Introduction: Patients with immunoglobulin G4-related disease (IgG4-RD) have risk factors of metabolic bone disease (MBD), yet data are lacking on the prevalence of MBD in IgG4-RD. We assessed screening frequency and prevalence of MBD in patients with IgG4-RD with and without pancreatic involvement.

Methods: Using an IgG4-RD registry, we extracted details from medical records related to MBD in patients who actively followed in our system. Living patients with contact information available were invited to complete surveys detailing MBD and associated characteristics.

Results: Seventy patients met criteria for medical records review (n = 17 with pancreatic involvement). Fifty-one percent had taken proton-pump inhibitors, and 30% had investigator-determined MBD. Compared with the US population, the age-standardized prevalence of osteoporosis in the IgG4-RD cohort was higher among both female patients (28.1% vs 19.6%, P = 0.40) and male patients (8.3% vs 4.4%, P = 0.48), though this did not achieve statistical significance. Mean T-scores at all sites were numerically lower in patients with pancreatic involvement than those without (all P > 0.1). In patient-reported data (n = 105), despite 62% of patients reporting ≥3 months of glucocorticoid exposure, only 36% had a dual-energy x-ray absorptiometry performed. Of 15 patients for whom pharmacologic MBD treatment was recommended, 8 (53%) reported adherence to this recommendation.

Discussion: The burden of MBD and its risk factors is high in patients with IgG4-RD, yet screening and treatment is low. Although our study was underpowered to detect statistical differences, there may be a greater burden of MBD in patients with pancreatic involvement. Screening and treatment of MBD should be emphasized in these patients.