|
KMID : 1102220230420050591
|
|
Kidney Research and Clinical Practice
2023 Volume.42 No. 5 p.591 ~ p.605
|
|
|
Serum and urine metabolomic biomarkers for predicting prognosis in patients with immunoglobulin A nephropathy
|
|
Jeon You-Hyun
Lee Su-Jin
Kim Da-Woon
Kim Suhk-Mann
Bae Sun-Sik
Han Mi-Yeun
Seong Eun-Young
Song Sang-Heon
|
|
|
Abstract
|
|
|
Background : Immunoglobulin A nephropathy (IgAN) is the most prevalent form of glomerulonephritis worldwide. Prediction of disease progression in IgAN can help to provide individualized treatment based on accurate risk stratification.
Methods : We performed proton nuclear magnetic resonance-based metabolomics analyses of serum and urine samples from healthy controls, non-progressor (NP), and progressor (P) groups to identify metabolic profiles of IgAN disease progression. Metabolites that were significantly different between the NP and P groups were selected for pathway analysis. Subsequently, we analyzed multivariate area under the receiver operating characteristic (ROC) curves to evaluate the predictive power of metabolites associated with IgAN progression.
Results : We observed several distinct metabolic fingerprints of the P group involving the following metabolic pathways: glycolipid metabolism; valine, leucine, and isoleucine biosynthesis; aminoacyl-transfer RNA biosynthesis; glycine, serine, and threonine metabolism; and glyoxylate and dicarboxylate metabolism. In multivariate ROC analyses, the combinations of serum glycerol, threonine, and proteinuria (area under the curve [AUC], 0.923; 95% confidence interval [CI], 0.667-1.000) and of urinary leucine, valine, and proteinuria (AUC, 0.912; 95% CI, 0.667-1.000) showed the highest discriminatory ability to predict IgAN disease progression.
Conclusion : This study identified serum and urine metabolites profiles that can aid in the identification of progressive IgAN and proposed perturbed metabolic pathways associated with the identified metabolites.
|
|
|
KEYWORD
|
|
|
Disease progression, IgA nephropathy, Metabolic networks and pathways, Metabolomics
|
|
|
FullTexts / Linksout information
|
|
|
|
|
|
Listed journal information
|
|
|
|
|