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Updated: Jul 21, 2026

Identification and Quantification of Deranged Metabolites in Critically Ill Patients Using NMR-Based Metabolomics
Published on: November 29, 2024
Serum metabolomics in pulmonary sarcoidosis: metabolic signatures across prognoses
Dafu Zhu1, Jianglong Chen2, Li Zhang1
1Department of Pulmonary and Critical Care Medicine, Shanghai Pulmonary Hospital, School of Medicine, Tongji University, Shanghai, 200433, China.
Background:
Sarcoidosis is a systemic inflammatory disease, primarily affecting the lungs, with a prognosis that varies widely among patients. While some patients recover spontaneously after diagnosis, others experience disease progression. Currently, the metabolomic profile associated with pulmonary sarcoidosis and its different clinical outcomes remains poorly understood.
Methods:
Serum samples from 29 pulmonary sarcoidosis patients and 10 healthy controls were analyzed using untargeted UPLC-MS/MS metabolomics. Univariate and multivariate analyses identified differentially expressed metabolites, followed by pathway enrichment to evaluate their biological relevance. Patients were further stratified into self-healing (n = 11) and progressive (n = 18) subgroups based on prognosis. Differential metabolites between subgroups were compared, potential biomarkers were selected, and their diagnostic performance assessed. Correlations with clinical parameters were also analyzed to explore associations with disease progression.
Results:
Sarcoidosis patients showed distinct serum metabolic profiles compared to healthy controls, with 10 upregulated and 199 downregulated metabolites. Pathway analysis indicated enrichment in amino acid, lipid, and immune-related pathways. Between prognostic subgroups, 25 differential metabolites were identified. Uric acid, testosterone sulfate, allopregnanolone sulfate, and 24,25-dihydroxyvitamin D3 emerged as key metabolites with prognostic value and moderate correlations with clinical parameters.
Conclusions:
This study highlights distinct serum metabolic profiles associated with sarcoidosis prognosis, suggesting that specific metabolic alterations may aid in monitoring and predicting disease outcomes. These findings offer a foundation for future research into personalized treatment and management strategies.
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