Distinct metabolic biomarkers to distinguish IgG4-related disease from Sjogren's syndrome and pancreatic cancer and predict disease prognosis

• Published in: BMC medicine 2022-12, Vol.20 (1), p.497-12, Article 497
• Main Authors: Yan, Songxin, Peng, Yu, Wu, Ziyan, Cheng, Linlin, Li, Haolong, Xu, Honglin, Huang, Yuan, Zhang, Wen, Li, Yongzhe
• Format: Article
• Language: English
• Subjects: Analysis; Biological markers; Biomarkers; Comparative analysis; Development and progression; Diagnosis; Humans; Immunoglobulin G4-related disease; Immunoglobulin G4-Related Disease - diagnosis; Immunological deficiency syndromes; Metabolome; Pancreatic diseases; Pancreatic Neoplasms - diagnosis; Prognosis; Sjogren's syndrome; Sjogren's Syndrome - diagnosis; Sjogren's Syndrome - metabolism
• ISSN: 1741-7015; 1741-7015
• DOI: 10.1186/s12916-022-02700-x

The pathogenesis of immunoglobulin G4-related disease (IgG4-RD) remains unclear. IgG4-RD often mimics other diseases, including pancreatic cancer (PC) and Sjogren's syndrome (SS), which may easily lead to misdiagnosis. This study was performed to explore the metabolite changes and potential biomarkers of IgG4-RD and other misdiagnosed diseases. Untargeted liquid chromatography-tandem mass spectrometry metabolomics profiling of plasma samples from a cohort comprising healthy controls (HCs) and patients with IgG4-RD (n = 87), PC (n = 33), and SS (n = 31) was performed. A random forest machine learning model was used to verify the relevance of the identified metabolites in the diagnosis of different diseases and the prediction of disease prognosis. The ATP-binding cassette transporter pathway was found to be most closely related to IgG4-RD, which was significantly up-regulated in the IgG4-RD group than in all the matched groups. Five metabolites were proved to be valuable biomarkers for IgG4-RD. Caftaric acid, maltotetraose, D-glutamic acid, 1-stearoyl-2-arachidonoyl-sn-glycero-3-phosphoserine, and hydroxyproline were useful in distinguishing between IgG4-RD, PC, SS, and HC [area under the curve (AUC) = 1]. A combination of phenylalanine betaine, 1-(1z-hexadecenyl)-sn-glycero-3-phosphocholine, Pi 40:8, uracil, and N1-methyl-2-pyridone-5-carboxamide showed a moderate value in predicting relapse in patients with IgG4-RD (AUC = 0.8). Our findings revealed the metabolite changes of IgG4-RD and provide new insights for deepening our understanding of IgG4-RD despite the lack of validation in external cohorts. Metabolomic biomarkers have significance in the clinical diagnosis and disease prognosis of IgG4-RD.