Parameter
| Biomarker | Serum and urine metabolic fingerprints ( based on NPELDI-MS ) | Full name | Serum and urine metabolic fingerprints ( based on NPELDI-MS ) | Molecular Type | Metabolome |
|---|---|---|---|---|---|
| Molecular Formula | / | Molecular Weight | / | Core Functional Dimensions | Early diagnosis、Prognostic evaluation |
| Disease | Glomerulonephritis (GN) | Disease Subtypes | / | ||
| Organ | Kidney | Test Sample / Technology Platform | Serum、Urine（NPELDI-MS、Machine learning） | ||
| Pathobiological Mechanisms | The metabolic fingerprints were obtained by nanoparticle-enhanced laser desorption / ionization mass spectrometry. The model had high diagnostic efficiency for IgAN ( AUC = 0.81-0.95 ), and the dynamic changes of key metabolites reflected the prognosis. | ||||
| Clinical Availability Status | Research verification stage：The diagnostic efficiency is high, which needs to be verified by clinical transformation. | ||||
| Notes and Dynamics | The combination of mass spectrometry and machine learning to achieve non-invasive, accurate diagnosis and prognosis evaluation of IgAN is a typical case of metabolomics application. | ||||