<p>Membranous nephropathy (MN) is the most common cause of nephrotic syndrome in adults. Currently, MN diagnosis relies on either the presence of serum anti-phospholipase A2 receptor antibodies (αPLA2R Abs) or kidney biopsy. However, approximately 30% of patients with MN exhibit negative αPLA2R Ab, and the invasive nature of kidney biopsy limits its use in certain patients. This study aims to identify non-invasive biomarkers for predicting progression of MN and to compare the urinary metabolic profiles of patients with MN at different αPLA2R Ab statuses using urine metabolomics. Untargeted metabolomics was performed on urine samples that were retrospectively collected from biopsy-confirmed patients with MN (<i>n</i> = 73) and healthy controls (HC) (<i>n</i> = 79) using liquid chromatography-tandem mass spectrometry. Among the 156 identified endogenous metabolites, 35 primary urinary metabolite biomarkers were associated with MN. Diagnostic and predictive models for patients with MN and high-risk patients were established based on these biomarkers, respectively. Metabolic pathway analysis indicated that oxidative stress pathways may play a crucial role in the pathophysiology of MN. Additionally, two urinary metabolites (dodecanedioic acid [DDDA] and 5’-deoxy-5’-(methylthio)adenosine [MTA]) exhibited a significant negative association with αPLA2R Ab titer. In this study, we proved metabolomics is valuable for accurate diagnosis and early detection of MN by identifying novel urinary metabolites. Additionally, it may offer insights for future research and the development of novel therapeutic targets.</p>

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Discovery of non-invasive biomarkers for accurate detection of membranous nephropathy

  • Yufei Li,
  • Ji Hye Kim,
  • Jihyun Kang,
  • Seung Seok Han,
  • Joo-Youn Cho

摘要

Membranous nephropathy (MN) is the most common cause of nephrotic syndrome in adults. Currently, MN diagnosis relies on either the presence of serum anti-phospholipase A2 receptor antibodies (αPLA2R Abs) or kidney biopsy. However, approximately 30% of patients with MN exhibit negative αPLA2R Ab, and the invasive nature of kidney biopsy limits its use in certain patients. This study aims to identify non-invasive biomarkers for predicting progression of MN and to compare the urinary metabolic profiles of patients with MN at different αPLA2R Ab statuses using urine metabolomics. Untargeted metabolomics was performed on urine samples that were retrospectively collected from biopsy-confirmed patients with MN (n = 73) and healthy controls (HC) (n = 79) using liquid chromatography-tandem mass spectrometry. Among the 156 identified endogenous metabolites, 35 primary urinary metabolite biomarkers were associated with MN. Diagnostic and predictive models for patients with MN and high-risk patients were established based on these biomarkers, respectively. Metabolic pathway analysis indicated that oxidative stress pathways may play a crucial role in the pathophysiology of MN. Additionally, two urinary metabolites (dodecanedioic acid [DDDA] and 5’-deoxy-5’-(methylthio)adenosine [MTA]) exhibited a significant negative association with αPLA2R Ab titer. In this study, we proved metabolomics is valuable for accurate diagnosis and early detection of MN by identifying novel urinary metabolites. Additionally, it may offer insights for future research and the development of novel therapeutic targets.