Volatile Organic Metabolites Identify Patients with Mesangial Proliferative Glomerulonephritis, IgA Nephropathy and Normal Controls.

Changsong Wang,Mingao Wang,Enyou Li,Lin Zhu,Hongshuang Tong,Xin Pi,Yue Feng,Yue Wang

doi:10.1038/srep14744

Abstract

Urinary volatile organic compounds (VOCs) analysis for kidney diseases has attracted a large amount of scientific interest recently, and urinary metabolite analysis has already been applied to many diseases. Urine was collected from 15 mesangial proliferative glomerulonephritis (MsPGN) patients, 21 IgA nephropathy (IgAN) patients and 15 healthy controls. Solid phase microextraction–chromatography– mass spectrometry (SPME-GC-MS) was used to analyse the urinary metabolites. The statistical methods principal component analysis (PCA) and orthogonal partial least-squares discriminant analysis (OPLSDA) were performed to process the final data. Five metabolites were significantly greater in the group of MsPGN patients than in the normal control group (P < 0.05) while three metabolites were found at increased levels in the group of IgAN patients compared with the normal controls (P < 0.05). In addition, five metabolites were significantly increased in the group of IgAN patients compared with the MsPGN patients (P < 0.05). These five metabolites may be specific biomarkers for distinguishing between MsPGN and IgAN. The analysis of urinary VOCs appears to have potential clinical applications as a diagnostic tool.

Highlights

The current gold standard for pathological diagnosis is renal biopsy because of its specificity
Our study used a gas chromatography-mass spectrometry (GC-MS) method combined with multivariate data analysis to discriminate the volatile organic compounds (VOCs) of IgA nephropathy (IgAN), mesangial proliferative glomerulonephritis (MsPGN) and normal samples, to discover potential biomarkers for IgAN and MsPGN in urinary VOCs
The separation trend for the experimental group and the control group was detected from the principal component analysis (PCA) (Fig. 1) and orthogonal partial least-squares discriminant analysis (OPLSDA) (Fig. 2) score plots; the tight clustering of samples in the OPLSDA score plot demonstrated that our approach was effective (Fig. 2)

Summary

Introduction

The current gold standard for pathological diagnosis is renal biopsy because of its specificity. Changes in externally affected biological systems over time for a variety of diseases[5]. Among these samples, urine is a complex biofluid with a rich metabolite composition that reflects various metabolic processes in the organism. As a result of its ease of collection, it has been widely used in metabolomic studies to investigate pathological conditions, such as inborn errors of metabolism, diabetes, and different types of cancer[6]. Koichi Matsumura et al.[12] demonstrated that urinary volatile organic compounds (VOCs) can assist in the diagnosis of lung cancer. When the renal system is impaired, VOCs in the urine may indicate corresponding changes. Our study used a gas chromatography-mass spectrometry (GC-MS) method combined with multivariate data analysis to discriminate the VOCs of IgAN, MsPGN and normal samples, to discover potential biomarkers for IgAN and MsPGN in urinary VOCs

Methods

Results

Conclusion