A Shortened Diagnostic Interval and Its Associated Clinical Factors and Related Outcomes in Inflammatory Bowel Disease Patients from a Cohort Study in China.

Aim: The diagnosis of inflammatory bowel disease (IBD) worldwide is complicated and results in diagnostic delay. However, the diagnostic interval of IBD and the factors associated with diagnostic delay in patients in China have not been determined. Methods: We retrospectively analyzed clinical data of hospitalized IBD patients in Peking Union Medical College Hospital from January 1998 to January 2018. Patients were divided into non-delayed and delayed groups according to their diagnostic interval. Results: A total of 516 and 848 patients were confirmed to have Crohn's disease (CD) and ulcerative colitis (UC), respectively. The median diagnostic intervals were 6 and 20 months in patients with UC and CD, respectively (P<0.05). A decreasing trend in the diagnostic interval for IBD was observed over time, from 9 months to 1 month in UC patients and from 30 months to 3 months in CD patients. The longest diagnostic interval was 29.5 months in CD patients with first symptoms at the age of 51-60 years and 12.5 months in UC patients at the age of 41-50 years. In patients with CD, intestinal obstruction (OR=2.71), comorbid diabetes (OR=4.42), and appendectomy history (OR=2.18) were risk factors for diagnostic delay, whereas having fever as the first symptom may reduce its risk (OR=0.39). In patients with UC, the misdiagnosis of chronic enteritis (OR=2.10) was a risk factor for diagnostic delay. Conclusion: The diagnostic interval for IBD has decreased over the years. Some clinical manifestations, such as initial symptoms and age at symptom onset, may help to shorten this interval. Diseases such as tuberculosis and infectious enteritis should be considered during differentiation.

Dyslipidaemia Is Associated with Severe Disease Activity and Poor Prognosis in Ulcerative Colitis: A Retrospective Cohort Study in China.

Background: Clinical data on the correlation of dyslipidaemia with the long-term outcomes of ulcerative colitis (UC) are limited. This study aimed to evaluate the impact of lipid levels on disease activity and prognosis in UC. Methods: The retrospective data of UC patients who had detailed lipid profiles were collected from January 2003 to September 2020. All patients were followed-up to 30 September 2021. The long-term outcomes were UC-related surgery and tumorigenesis. Results: In total, 497 patients were included in the analysis. Compared to patients with normal lipid levels, those with dyslipidaemia commonly presented with more serious disease activity. Low high-density lipoprotein cholesterol (p < 0.05) levels were associated with higher risks of severe disease activity in UC. Regarding the long-term outcomes, patients with persistent dyslipidaemia were at higher risks of UC-related surgery (HR: 3.27, 95% CI: 1.86−5.75, p < 0.001) and tumorigenesis (HR: 7.92, 95% CI: 3.97−15.78, p < 0.001) and had shorter surgery- and tumour-free survival (p < 0.001) than patients with transient dyslipidaemia and normal lipid levels. Low levels of high-density lipoprotein cholesterol (p < 0.001) and apolipoprotein A1 (p < 0.05) were associated with higher risks of surgery and tumorigenesis. Conclusion: Persistent dyslipidaemia was associated with a higher risk of serious disease activity and worse long-term outcomes among patients with UC. Lipid patterns should be assessed to improve the management of high-risk patients with UC in the early phase.

Artificial Neural Network Analysis-Based Immune-Related Signatures of Primary Non-Response to Infliximab in Patients With Ulcerative Colitis.

Infliximab (IFX) is an effective medication for ulcerative colitis (UC) patients. However, one-third of UC patients show primary non-response (PNR) to IFX. Our study analyzed three Gene Expression Omnibus (GEO) datasets and used the RobustRankAggreg (RRA) algorithm to assist in identifying differentially expressed genes (DEGs) between IFX responders and non-responders. Then, an artificial intelligence (AI) technology, artificial neural network (ANN) analysis, was applied to validate the predictive value of the selected genes. The results showed that the combination of CDX2, CHP2, HSD11B2, RANK, NOX4, and VDR is a good predictor of patients' response to IFX therapy. The range of repeated overall area under the receiver-operating characteristic curve (AUC) was 0.850 ± 0.103. Moreover, we used an independent GEO dataset to further verify the value of the six DEGs in predicting PNR to IFX, which has a range of overall AUC of 0.759 ± 0.065. Since protein detection did not require fresh tissue and can avoid multiple biopsies, our study tried to discover whether the key information, analyzed by RNA levels, is suitable for protein detection. Therefore, immunohistochemistry (IHC) staining of colonic biopsy tissues from UC patients treated with IFX and a receiver-operating characteristic (ROC) analysis were used to further explore the clinical application value of the six DEGs at the protein level. The IHC staining of colon tissues from UC patients confirmed that VDR and RANK are significantly associated with IFX efficacy. Total IHC scores lower than 5 for VDR and lower than 7 for RANK had an AUC of 0.828 (95% CI: 0.665-0.991, p = 0.013) in predicting PNR to IFX. Collectively, we identified a predictive RNA model for PNR to IFX and explored an immune-related protein model based on the RNA model, including VDR and RANK, as a predictor of IFX non-response, and determined the cutoff value. The result showed a connection between the RNA and protein model, and both two models were available. However, the composite signature of VDR and RANK is more conducive to clinical application, which could be used to guide the preselection of patients who might benefit from pharmacological treatment in the future.