Background/Aims: Neutrophil to lymphocyte ratio (NLR) and platelet to lymphocyte ratio (PLR) can serve as biomarkers for diagnosing and assessing disease activity in ulcerative colitis (UC). We investigated their clinical significance in UC.Methods: We analyzed 48 patients with UC who underwent measurement of fecal calprotectin (FC) and endoscopy and 96 age- and sex-matched healthy controls. NLR and PLR were compared between the patients and healthy controls. The endoscopic activity was divided into 2 groups: group 1 (mild to moderate inflammation) and group 2 (severe inflammation) according to the Mayo endoscopic subscore in UC.Results: To diagnose UC, the optimal cutoff of NLR and PLR was 2.26 (sensitivity 54.2%; specificity 90.6%; positive likelihood ratio 5.778, 95% confidence interval [CI] 2.944–11.339; area under the curve [AUC] 0.774, 95% CI, 0.690–0.859) and 179.8 (sensitivity 35.4%; specificity 90.6%; positive likelihood ratio 3.778, 95% CI 1.821–7.838; AUC 0.654, 95% CI 0.556–0.753), respectively. The optimal cutoff to differentiate group 1 and group 2 was 3.44, 175.9, and 453 µg/g for NLR, PLR, and FC, respectively (sensitivity, 63.6% vs. 90.9% vs. 81.8%; specificity, 81.1% vs. 78.4% vs. 73.0%; positive likelihood ratio, 3.364 vs. 4.205 vs. 3.027; AUC, 0.714 vs. 0.897 vs. 0.813). PLR had the highest AUC and positive likelihood ratio.Conclusions: NLR and PLR help differentiate patients with UC from healthy controls. NLR, PLR, and FC indicate endoscopic activity and may reflect intestinal mucosal conditions.

Early intestinal resection in patients with Crohn’s disease (CD) is necessary due to a severe and complicating disease course. Herein, we aim to predict which patients with CD need early intestinal resection within 3 years of diagnosis, according to a tree-based machine learning technique. The single-nucleotide polymorphism (SNP) genotype data for 337 CD patients recruited from 15 hospitals were typed using the Korea Biobank Array. For external validation, an additional 126 CD patients were genotyped. The predictive model was trained using the 102 candidate SNPs and seven sets of clinical information (age, sex, cigarette smoking, disease location, disease behavior, upper gastrointestinal involvement, and perianal disease) by employing a tree-based machine learning method (CatBoost). The importance of each feature was measured using the Shapley Additive Explanations (SHAP) model. The final model comprised two clinical parameters (age and disease behavior) and four SNPs (rs28785174, rs60532570, rs13056955, and rs7660164). The combined clinical–genetic model predicted early surgery more accurately than a clinical-only model in both internal (area under the receiver operating characteristic (AUROC), 0.878 vs. 0.782; n = 51; p < 0.001) and external validation (AUROC, 0.836 vs. 0.805; n = 126; p < 0.001). Identification of genetic polymorphisms and clinical features enhanced the prediction of early intestinal resection in patients with CD.

Limited studies have examined the intestinal microbiota composition in relation to Crohn’s disease (CD) prognosis. We analyzed the differences in microbial communities and relevant metabolic pathways associated with prognostic variables in patients with CD. We applied 16S rRNA gene sequencing to analyze a cohort of 1110 CD and healthy control (HC) fecal samples. We categorized patients with CD into good (CD-G), intermediate (CD-I) and poor (CD-P) prognosis groups, according to the history of using biologics and intestinal resection. Microbiota α-diversity decreased more in CD-P than CD-G and CD-I. Microbiota ß-diversity in CD-P differed from that in CD-G and CD-I. Thirteen genera and 10 species showed differential abundance between CD-G and CD-P groups. Escherichia coli (p = 0.001) and species Producta (p = 0.01) and genera Lactobacillus (p = 0.003) and Coprococcus (p = 0.01) consistently showed differences between CD-G and CD-P groups after adjusting for confounding variables. Functional profiling suggested that the microbial catabolic pathways and pathways related to enterobacterial common antigen and lipopolysaccharide biosynthesis were better represented in the CD-P group than in the CD-G group, and E. coli were the top contributors to these pathways. CD prognosis is associated with altered microbiota composition and decreased diversity, and E. coli might be causally involved in CD progression, and may have adapted to live in inflammatory environments.