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Biomarkers of Metabolomics in Inflammatory Bowel Disease and Damp-Heat Syndrome: A Preliminary Study

AIMS: This study aims to investigate the potential biomarkers of inflammatory bowel disease (IBD) and IBD with damp-heat syndrome (IBD-DH) by metabolomics. METHODS: Plasma and urine samples were collected from 15 healthy controls and 30 IBD patients, including 15 IBD-DH and 15 IBD with spleen defici...

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Detalles Bibliográficos
Autores principales: Wu, Xingxing, Liu, Kexin, Wu, Qi, Wang, Mao, Chen, Xuelian, Li, Yuge, Qian, Lin, Li, Changyin, Dai, Guoliang, Zhang, Qide, Mu, Genglin, Wu, Jing, Shan, Zhaowei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9270137/
https://www.ncbi.nlm.nih.gov/pubmed/35815273
http://dx.doi.org/10.1155/2022/3319646
Descripción
Sumario:AIMS: This study aims to investigate the potential biomarkers of inflammatory bowel disease (IBD) and IBD with damp-heat syndrome (IBD-DH) by metabolomics. METHODS: Plasma and urine samples were collected from 15 healthy controls and 30 IBD patients, including 15 IBD-DH and 15 IBD with spleen deficiency syndrome (IBD-SD), which was coded as SF8G and SF70 according to the International Classification of Diseases Eleventh Revision (ICD-11) issued by World Health Organization. Pseudotargeted metabolomics method was used based on ultra-high-performance liquid chromatography-high-resolution mass spectrometry and triple-quadrupole mass spectrometry. RESULTS: Under the condition of false discovery rate (FDR) < 0.05, variable importance projection (VIP) > 1.0, and fold change (FC) > 1.5 or < 2/3, we found 57 plasma differential metabolites and 20 urinary differential metabolites in IBD. Then, with area under the curve (AUC) ≥ 0.85 and FC ≥ 2 or ≤ 0.3, 11 potential biomarkers were identified, such as acylcarnitine (ACar 20:4, ACar 18:1, and ACar 20:3), 3-indoleacetic acid, hippuric acid, and dehydroepiandrosterone sulfate, which is related to intestinal microbiota and immune response. However, less obvious differences were observed in IBD-DH when compared with IBD-SD. Under the condition of FDR < 0.2, VIP >1.0, and FC > 1.5 or < 2/3, we identified 16 plasma differential metabolites. In urine samples, IBD-DH and IBD-SD had the same metabolite pattern. With AUC ≥ 0.80, 7 differential plasma metabolites, mainly glycerophospholipids, were identified in IBD-DH. Kyoto Encyclopedia of Genes and Genomes analysis indicated that metabolic pathways, such as citrate cycle and amino acids metabolism, were mainly responsible for the distinction between IBD and healthy controls, whereas glycerophospholipid metabolism perturbation was not only a manifestation of IBD but also an important pathway to distinguish two subtypes defined by traditional medicine, IBD-DH and IBD-SD. CONCLUSION: In this study, we found that several metabolites of aromatic acids and lipid derivatives could act as potential biomarkers to discriminate IBD from healthy controls. Glycerophospholipids metabolites might be used to differentiate IBD-DH from IBD-SD.