Archives of medical research · 2019
Metabolomic Analysis of Membranous Glomerulonephritis: Identification of a Diagnostic Panel and Pathogenic Pathways.
СтатьяПоддержка исследования: вне правительства СШАНазвание и аннотация: Перевод в очереди
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Taherkhani Amir, Nafar Mohsen, Arefi-Oskouie Afsaneh, Broumandnia Nasrin, Parvin Mahmoud, Mahmoudieh Leila, Kalantari Shiva
Аннотация
BACKGROUND: Primary membranous glomerulonephritis (MGN) is a major cause of nephrotic syndrome in adults. Its diagnosis is based on invasive biopsy, and the current traditional serum or urinary biomarkers, such as the anti-phospholipase A2 receptor, are not adequately sensitive or specific.
AIM OF THE STUDY: Our purpose is to identify a sensitive and specific noninvasive panel of biomarkers for the diagnosis of MGN by using metabolomic techniques and to explore the pathogenic pathways that are involved in disease development.
METHODS: The urine metabolome of 66 MGN patients, 31 healthy controls, and 72 disease controls, were analyzed using nuclear magnetic resonance (NMR) and gas chromatography-tandem mass spectrometry (GC-MS/MS). Advanced multivariate statistical analyses were performed for the construction of diagnostic models and biomarker discovery. Receiver operating characteristic (ROC) curve analysis was used to suggest the most sensitive and specific diagnostic panel.
RESULTS: The NMR-based diagnostic model showed allantoic acid and deoxyuridine as the most overrepresented and underrepresented biomarkers, respectively differentiating MGN from both control groups. The GC-MS/MS-based diagnostic model showed oxalic acid as the most overrepresented biomarker and 2-hydroxyglutaric acid lactone as the only underrepresented specific biomarker. A panel of a combination of the most accurate predictors of NMR and GC-MS/MS was composed of α-hydroxybutyric acid, 3,4-Dihydroxymandelic acid, 5α-cholestanone, 2-hydroxyglutaric acid lactone, nicotinamide, epicoprostanol, and palmitic acid. Nine impaired pathways were identified in MGN, such as pyrimidine metabolism and NAD salvage.
CONCLUSIONS: This comprehensive metabolomic study of MGN indicates a panel of promising biomarkers, which is complementary to current traditional biomarkers, and needs to be validated in a larger cohort.
AIM OF THE STUDY: Our purpose is to identify a sensitive and specific noninvasive panel of biomarkers for the diagnosis of MGN by using metabolomic techniques and to explore the pathogenic pathways that are involved in disease development.
METHODS: The urine metabolome of 66 MGN patients, 31 healthy controls, and 72 disease controls, were analyzed using nuclear magnetic resonance (NMR) and gas chromatography-tandem mass spectrometry (GC-MS/MS). Advanced multivariate statistical analyses were performed for the construction of diagnostic models and biomarker discovery. Receiver operating characteristic (ROC) curve analysis was used to suggest the most sensitive and specific diagnostic panel.
RESULTS: The NMR-based diagnostic model showed allantoic acid and deoxyuridine as the most overrepresented and underrepresented biomarkers, respectively differentiating MGN from both control groups. The GC-MS/MS-based diagnostic model showed oxalic acid as the most overrepresented biomarker and 2-hydroxyglutaric acid lactone as the only underrepresented specific biomarker. A panel of a combination of the most accurate predictors of NMR and GC-MS/MS was composed of α-hydroxybutyric acid, 3,4-Dihydroxymandelic acid, 5α-cholestanone, 2-hydroxyglutaric acid lactone, nicotinamide, epicoprostanol, and palmitic acid. Nine impaired pathways were identified in MGN, such as pyrimidine metabolism and NAD salvage.
CONCLUSIONS: This comprehensive metabolomic study of MGN indicates a panel of promising biomarkers, which is complementary to current traditional biomarkers, and needs to be validated in a larger cohort.