ArticleBMC medicine2022
Distinct metabolic biomarkers to distinguish IgG4-related disease from Sjogren's syndrome and pancreatic cancer and predict disease prognosis.
Article in BMC medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed, 14 citations in OpenAlex.
- Pathogenesis exploration of lgG4-related disease: From the traditional central dogma and its remodeling perspective.Chinese medical journal · 2026Review
- Discovery of biomarkers for primary Sj ögren's syndrome based on multi-omics data, construction of diagnostic models, and clinical correlation analysis.Arthritis research & therapy · 2026Article
- Identification of candidate biomarkers for diagnosis, disease activity, and relapse prediction in IgG4-related disease.Arthritis research & therapy · 2026Article
- UPLC-MS/MS-based metabolomics analysis identifies disease-associated metabolic signatures of B cells from patients with IgG4-RD.Frontiers in immunology · 2026Article
- Machine Learning-Driven Insights in Cancer Metabolomics: From Subtyping to Biomarker Discovery and Prognostic Modeling.Metabolites · 2025Review
- Omics in IgG4-related disease.Chinese medical journal · 2025Review
- Immune Profile Differences between IgG4-Related Diseases and Primary Sjögren's Syndrome.Journal of inflammation research · 2025Article
- Altered serum metabolome as an indicator of paraneoplasia or concomitant cancer in patients with rheumatic disease.Annals of the rheumatic diseases · 2024Article
- Altered plasma metabolites and inflammatory networks in HIV-1 infected patients with different immunological responses after long-term antiretroviral therapy.Frontiers in immunology · 2023Article
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Authors and funding
9 authors at 2 institutions in 1 country.
Funding
Abstract
backgroundThe 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.
methodsUntargeted 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.
resultsThe 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).
conclusionsOur 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.
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