Kim Ji Eun, Suh Dong Ho, Park Yu Jin, Oh Chi Hyuk, Oh Shin Ju, Kang Hyeji, Ji Yosep, Kim Young Jin, Kim Weon, Jung Eun Sung, Lee Chang Kyun
Department of Gastroenterology, Center for Crohn's and Colitis, Kyung Hee University Hospital, Kyung Hee University College of Medicine, Seoul, South Korea.
HEM Pharma Inc., Suwon, Gyeonggi, South Korea.
Sci Rep. 2025 Feb 15;15(1):5661. doi: 10.1038/s41598-025-90160-7.
Inflammatory Bowel Disease (IBD), Crohn's disease (CD) and ulcerative colitis (UC), requires a combination of procedures and tests in diagnosis and discrimination. This study aimed to delineate specific serum metabolomic biomarkers that diagnose IBD and differentiate IBD subgroups. Serum samples and clinical metadata of the participants, IBD patients and Normal Controls (NC), were collected. Untargeted and targeted metabolomic analyses by high-resolution mass spectrometry and multivariate statistical approaches were applied. Further, Receiver Operating Characteristic (ROC) curves, pathways, and network analyses were conducted. Distinct clustering separated IBD patients from the NC, although the CD and UC subgroups overlapped in the non-targeted profiling. Targeted metabolomics revealed elevated tryptophan and indole-3-acetic acid levels and reduced primary-to-secondary bile acid ratios in both CD and UC patients. The differences in specific tryptophan metabolites between CD and UC were identified. The ROC analysis underscored the discriminatory power of the biomarkers (AUC values: NC vs. CD = 0.9738; NC vs. UC = 0.9887; UC vs. CD = 0.7140). Pathway analysis revealed alterations in glycerolipid metabolism, markedly differentiating UC from CD. Network analysis correlated metabolomic markers with the clinical phenotypes of IBD. Serum metabolomic biomarkers can precisely identify IBD, discriminate IBD subtypes, and further reveal the phenotypes of IBD.
炎症性肠病(IBD)、克罗恩病(CD)和溃疡性结肠炎(UC)的诊断与鉴别需要综合多种检查和测试。本研究旨在确定诊断IBD并区分IBD亚组的特定血清代谢组学生物标志物。收集了参与者、IBD患者和正常对照(NC)的血清样本及临床元数据。采用高分辨率质谱和多变量统计方法进行非靶向和靶向代谢组学分析。此外,还进行了受试者工作特征(ROC)曲线分析、通路分析和网络分析。尽管在非靶向分析中CD和UC亚组存在重叠,但IBD患者与NC之间有明显聚类区分。靶向代谢组学显示,CD和UC患者的色氨酸和吲哚 - 3 - 乙酸水平升高,初级胆汁酸与次级胆汁酸的比例降低。确定了CD和UC之间特定色氨酸代谢物的差异。ROC分析强调了生物标志物的鉴别能力(AUC值:NC与CD = 0.9738;NC与UC = 0.9887;UC与CD = 0.7140)。通路分析显示甘油olipid代谢存在改变,这显著区分了UC与CD。网络分析将代谢组学标志物与IBD的临床表型相关联。血清代谢组学生物标志物可以精确识别IBD,区分IBD亚型,并进一步揭示IBD的表型。 (注:原文中“glycerolipid”可能有误,推测可能是“glycerolipid metabolism”即甘油脂质代谢,但需结合原文完整信息进一步确认)