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Metabolic signatures of lymphangioleiomyomatosis in biofluids: nuclear magnetic resonance (NMR)-based metabonomics of blood plasma: a case-control study

BACKGROUND: Our aim was to analyze and compare the characteristics and differences of blood metabolites between lymphangioleiomyomatosis (LAM) patients and healthy controls, in order to find biomarkers that can be used for the diagnosis and classification of LAM. METHODS: Between January 2020 to Jan...

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Detalles Bibliográficos
Autores principales: Gu, Weili, Pan, Yingxin, Zhao, Wei, Liu, Jie, Meng, Ying
Formato: Online Artículo Texto
Lenguaje:English
Publicado: AME Publishing Company 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9929845/
https://www.ncbi.nlm.nih.gov/pubmed/36819539
http://dx.doi.org/10.21037/atm-22-6420
Descripción
Sumario:BACKGROUND: Our aim was to analyze and compare the characteristics and differences of blood metabolites between lymphangioleiomyomatosis (LAM) patients and healthy controls, in order to find biomarkers that can be used for the diagnosis and classification of LAM. METHODS: Between January 2020 to January 2022, 61 eligible LAM patients [51 sporadic LAM (S-LAM) and 10 tuberous sclerosis complex LAM (TSC-LAM)] from the First Affiliated Hospital of Guangzhou Medical University and 30 healthy controls were enrolled. Blood samples were taken for nuclear magnetic resonance (NMR) detection. Data analysis was performed by the umbrella program, and Wilcoxon analysis was used for comparisons between groups. The difference indicators were modeled by logistic regression. Diagnostic accuracy of the best predictive parameters was evaluated by the area under the receiver operating characteristic (ROC) curve (AUC), and the sensitivity and specificity were calculated. RESULTS: The indexes differed between LAM patients and healthy controls, S-LAM patients and healthy controls, and between TSC-LAM patients and healthy controls. There were two different metabolic indexes between S-LAM and TSC-LAM patients. After logistic regression modeling and ROC analysis, methionine (AUC =0.929, sensitivity =73.8%, specificity =100%, cut-off value =0.011 mmol/L) and acetic acid (AUC =0.966, sensitivity =95.1%, specificity =90%, cut-off value =0.006 mmol/L) had the highest diagnostic efficiency in LAM patients, and could be used to distinguish between affected and healthy people. Methionine was significantly associated with pneumothorax (P<0.05), and creatinine was significantly correlated with hysteromyoma (P<0.05). CONCLUSIONS: Methionine and acetic acid in the plasma of LAM patients are potential biomarkers. Methionine was also associated with pneumothorax in LAM patients. Also, acetone and creatinine were promising metabolic markers to distinguish S-LAM from TSC-LAM. NMR as a new non-invasive diagnostic method had a good discriminatory power for LAM.