Abstract

Abstract Background and Aims Currently, the precise mechanism of myeloperoxidase- anti-neutrophil cytoplasmic antibody associated glomerulonephritis (MPO-ANCA-GN) remains elusive. And there is a lack of dependable biomarkers for evaluating disease activity, therapeutic resistance, and risk of relapse. We try to seek valuable biomarkers and explore the mechanism of MPO-ANCA-GN by metabolomics. Method Urine and plasma samples from 63 MPO-ANCA-GN, 31 lupus nephritis (LN), 15 IgA nephropathy (IgAN), and 15 minimal change disease (MCD) patients and 30 HC were collected for metabolomics analysis. The samples were analyzed using Ultra Performance Liquid Chromatography (UPLC) and Tandem mass spectrometry (MS/MS). The different groups of samples were compared using Partial Least Squares-Discriminant Analysis. A Receiver Operator Characteristic (ROC) curve was constructed to assess the performance of the metabolite model in identifying active renal vasculitis. KEGG annotation and enrichment analysis were performed for key pathways. Results All metabolites in urine and plasma samples including hydrophilic compounds and hydrophobic compounds were identified. Compared with the disease control (DC) and HC, we observed 79 significantly upregulated metabolites (VIP>1, FDR<0.05, FC>1.5) and 32 downregulated metabolites (VIP>1, FDR <0.05, FC<0.67) in the plasma samples of MPO-ANCA-GN patients. KEGG enrichment analysis suggested that these upregulated metabolites were mainly associated with phenylalanine metabolism and galactose metabolism and downregulated metabolites were mainly associated with bile secretion, steroid biosynthesis, and ovarian steroidogenesis. Compared with the DC and HC, we identified a total of 122 differential metabolites in the urine samples of MPO-ANCA-GN patients, 40 of which were significantly upregulated (VIP>1, FDR<0.05, FC>1.5) and 68 of which significantly were downregulated (VIP>1, FDR <0.05, FC<0.67). Subsequently, KEGG analysis revealed that these upregulated metabolites were mainly enriched in glycerolipid metabolism, lipid and atherosclerosis, cholesterol metabolism, insulin resistance, regulation of lipolysis in adipocytes, vitamin digestion and absorption, fat digestion and absorption (Corrected P < 0.05). Downregulated metabolites were mainly enriched in steroid hormone biosynthesis (Corrected P < 0.05). Nine MPO-ANCA-GN patients with paired plasma and six MPO-ANCA-GN patients with paired urine during the active and remission phase were included in the study. A total of 504 differential metabolites in plasma samples were identified between the active and remission phase based on VIP value >1, P < 0.05, and FC >1.5 or FC < 0.6. Of these, 425 metabolites were downregulated, while 79 lipid metabolites were upregulated in the active group. MPO-ANCA-GN patients were divided into two groups according to Mayo Clinic/Renal Pathology Society Chronicity Score: Minimal-mild group and Moderate-severe group. In plasma samples, our data showed that 3-Methoxysalicylic Acid, Carnitine C20:5, and isoxanthopterin presented good ability in distinguishing between the minimal-mild group and the moderate-severe group, with an AUC > 0.7. In urine samples, cyclohexylamine and arachidonic acid (AUC > 0.8) can distinguish the two groups well. Conclusion We identified many novel potential metabolic biomarkers in urine and plasma samples for evaluating disease activity, therapeutic resistance, and risk of relapse in patients with MPO-ANCA-GN.

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