Role of metabolomic profile as a potential marker to discriminate membranous nephropathy from IgA nephropathy
Background Membranous nephropathy (MN) and IgA nephropathy (IgAN) are the most common primary glomerulopathies worldwide. The systemic metabolic changes in the progression of MN and IgAN are not fully understood. Methods A total of 87 and 70 patients with MN and IgAN, respectively, and 30 healthy controls were enrolled in this study. Untargeted metabolomics was performed to explore the differential metabolites and metabolic pathways in the early stage of MN and IgAN. To judge the diagnostic ability of biomarkers, receiver operating characteristic curve analysis (ROC) were performed. Results Principal component analysis (PCA) and orthogonal partial least-squares discriminant analysis (OPLS-DA) suggested that patients with MN and IgAN showed an obvious separation trend from the healthy controls. In addition, 155 and 148 metabolites were identified to be significantly altered in the MN and IgAN groups, respectively. Of these, 70 metabolites were markedly altered in both disease groups; six metabolites, including L-tryptophan, L-kynurenine, gamma-aminobutyric acid (GABA), indoleacetaldehyde, 5-hydroxyindoleacetylglycine, and N-alpha-acetyllysine, showed the opposite tendency. The most affected metabolic pathways included the amino acid metabolic pathways, citrate cycle, pantothenate and CoA biosynthesis, and hormone signaling pathways. Conclusions Substantial metabolic disorders occurred during the progression of MN and IgAN. L-tryptophan, L-kynurenine, GABA, indoleacetaldehyde, 5-hydroxyindoleacetylglycine, and N-alpha-acetyllysine may show potential as biomarkers for the identification of MN and IgAN..
| Medienart: |
E-Artikel |
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| Erscheinungsjahr: |
2023 |
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| Erschienen: |
2023 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:56 |
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| Enthalten in: |
International urology and nephrology - 56(2023), 2 vom: 15. Juli, Seite 635-651 |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
Qu, Yuchen [VerfasserIn] |
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| Links: |
Volltext [kostenfrei] |
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| Themen: |
IgA nephropathy |
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| Anmerkungen: |
© The Author(s) 2023 |
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| doi: |
10.1007/s11255-023-03691-1 |
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| funding: |
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| PPN (Katalog-ID): |
SPR054504430 |
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| 520 | |a Background Membranous nephropathy (MN) and IgA nephropathy (IgAN) are the most common primary glomerulopathies worldwide. The systemic metabolic changes in the progression of MN and IgAN are not fully understood. Methods A total of 87 and 70 patients with MN and IgAN, respectively, and 30 healthy controls were enrolled in this study. Untargeted metabolomics was performed to explore the differential metabolites and metabolic pathways in the early stage of MN and IgAN. To judge the diagnostic ability of biomarkers, receiver operating characteristic curve analysis (ROC) were performed. Results Principal component analysis (PCA) and orthogonal partial least-squares discriminant analysis (OPLS-DA) suggested that patients with MN and IgAN showed an obvious separation trend from the healthy controls. In addition, 155 and 148 metabolites were identified to be significantly altered in the MN and IgAN groups, respectively. Of these, 70 metabolites were markedly altered in both disease groups; six metabolites, including L-tryptophan, L-kynurenine, gamma-aminobutyric acid (GABA), indoleacetaldehyde, 5-hydroxyindoleacetylglycine, and N-alpha-acetyllysine, showed the opposite tendency. The most affected metabolic pathways included the amino acid metabolic pathways, citrate cycle, pantothenate and CoA biosynthesis, and hormone signaling pathways. Conclusions Substantial metabolic disorders occurred during the progression of MN and IgAN. L-tryptophan, L-kynurenine, GABA, indoleacetaldehyde, 5-hydroxyindoleacetylglycine, and N-alpha-acetyllysine may show potential as biomarkers for the identification of MN and IgAN. | ||
| 650 | 4 | |a Membranous nephropathy |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a IgA nephropathy |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Metabolomics |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Receiver operating characteristic (ROC) curve |7 (dpeaa)DE-He213 | |
| 700 | 1 | |a Wang, Yueyuan |4 aut | |
| 700 | 1 | |a Hu, Zhanhong |4 aut | |
| 700 | 1 | |a Su, Cunjin |4 aut | |
| 700 | 1 | |a Qian, Chenyue |4 aut | |
| 700 | 1 | |a Pan, Jie |4 aut | |
| 700 | 1 | |a Zhu, Ye |4 aut | |
| 700 | 1 | |a Shi, Aiming |4 aut | |
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