Published 2012 | Version v1
Journal article

A proton nuclear magnetic resonance-based metabonomics study of metabolic profiling in immunoglobulin a nephropathy

  • 1. 181st Hospital Guangxi, Central Laboratory, Laboratory of Metabolic Diseases Research, Guangxi Province (China)
  • 2. Guangxi Normal University, The Life Science College, Guangxi Province (China)
  • 3. Key Laboratory of Laboratory Medical Diagnostics of Education Ministry, Chongqiong Medical University, Chongqing (China)
  • 4. Clinical Medical Research Center, the Second Clinical Medical College of Jinan University (Shenzhen People's Hospital), Shenzhen, Guangdong Province (China)

Description

Objectives: Immunoglobulin A nephropathy is the most common cause of chronic renal failure among primary glomerulonephritis patients. The ability to diagnose immunoglobulin A nephropathy remains poor. However, renal biopsy is an inconvenient, invasive, and painful examination, and no reliable biomarkers have been developed for use in routine patient evaluations. The aims of the present study were to identify immunoglobulin A nephropathy patients, to identify useful biomarkers of immunoglobulin A nephropathy and to establish a human immunoglobulin A nephropathy metabolic profile. Methods: Serum samples were collected from immunoglobulin A nephropathy patients who were not using immunosuppressants. A pilot study was undertaken to determine disease-specific metabolite biomarker profiles in three groups: healthy controls (N = 23), low-risk patients in whom immunoglobulin A nephropathy was confirmed as grades I-II by renal biopsy (N = 23), and high-risk patients with nephropathies of grades IV-V (N = 12). Serum samples were analyzed using proton nuclear magnetic resonance spectroscopy and by applying multivariate pattern recognition analysis for disease classification. Results: Compared with the healthy controls, both the low-risk and high-risk patients had higher levels of phenylalanine, myo-inositol, lactate, L6 lipids ( CH-CH2-CH = O), L5 lipids (-CH2-C = O), and L3 lipids (-CH2-CH2-C = O) as well as lower levels of β-glucose, α-glucose, valine, tyrosine, phosphocholine, lysine, isoleucine, glycerolphosphocholine, glycine, glutamine, glutamate, alanine, acetate, 3-hydroxybutyrate, and 1-methylhistidine. Conclusions: These metabolites investigated in this study may serve as potential biomarkers of immunoglobulin A nephropathy. Point scoring of pattern recognition analysis was able to distinguish immunoglobulin A nephropathy patients from healthy controls. However, there were no obvious differences between the low-risk and high-risk groups in our research. These results offer new, sensitive and specific, noninvasive approaches that may be of great benefit to immunoglobulin A nephropathy patients by enabling earlier diagnosis. (author)

Availability note (English)

Available from http://www.scielo.br/pdf/clin/v67n4/v67n4a10.pdf

Additional details

Publishing Information

Journal Title
Clinics (Print)
Journal Volume
67
Journal Issue
4
Journal Page Range
p. 363-373
ISSN
1807-5932