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Abstract Number: 2280

Serum Metabolomics As a Novel Diagnostic Approach for Systemic Lupus Erythematosus

Jun Saegusa1, Yasuhiro Irino2, Masaru Yoshida2, Shino Tanaka1, Yoshinori Kogata1, Goichi Kageyama1, Seiji Kawano1, Goh Tsuji3, Shunichi Kumagai3 and Akio Morinobu1, 1Rheumatology and Clinical Immunology, Kobe University Graduate School of Medicine, Kobe, Japan, 2The Integrated Center for Mass Spectrometry, Kobe University Graduate School of Medicine, Kobe University Graduate School of Medicine, Kobe, Japan, 3The Center for Rheumatic Diseases, Shinko Hospital, Kobe, Japan

Meeting: 2012 ACR/ARHP Annual Meeting

Keywords: Biomarkers and systemic lupus erythematosus (SLE)

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Session Information

Title: Systemic Lupus Erythematosus - Human Etiology and Pathogenesis

Session Type: Abstract Submissions (ACR)

Background/Purpose: Metabolomics, or metabolome analysis, is the comprehensive study of low-molecular-weight metabolites. The metabolome represents the metabolite profiles of all the cellular processes in a cell, tissue, organ, or organism. Notably, because the metabolome is the last step in the omics cascade before the phenotype, alterations in the levels of metabolites may better reflect the physiological and pathological characteristics of a disease than changes in gene or protein expressions. It is now apparent that cell metabolism has a tremendous impact on the function of various immune cells. In this study, we evaluated the differences in the serum metabolome between systemic lupus erythematosus (SLE) patients and healthy subjects, using gas chromatography/mass spectrometry (GC/MS), and sought to identify candidates for metabolic biomarkers.

Methods: Serum samples were obtained in the morning from fasting human patients with SLE (n=26) and healthy volunteers (n=26). Serum metabolite profiling was performed by GC/MS. The metabolic profiles of the patient and control groups were compared using multivariate statistical analysis.

Results: Sixty-two metabolites were detected in the serum. The level of 24 of them was significantly different in SLE patients compared to healthy controls. The 2D-plots of the principal component analysis (PCA) scores for all 62 metabolites showed distinct clustering for the two subject groups. The corresponding 2D-PCA- and partial least squares-discriminant analysis (PLS-DA)-loading plots revealed that variations in the levels of glutamic acid, ornithine, urea, tyrosine, and glycerol greatly contributed to the observed separation of the metabolomics profiles of the SLE patients and healthy controls. Furthermore, we demonstrated that the serum levels of glutamic acid and ornithine were significantly correlated with the SLE activity index (SLEDAI) score in the patient group.

Conclusion: Our study suggests that GC/MS-based serum metabolomics can serve as a novel diagnostic and monitoring tool for SLE, and that the pattern of variation in metabolite levels may be useful for understanding the pathophysiology of SLE and establishing novel therapeutic strategies.


Disclosure:

J. Saegusa,
None;

Y. Irino,
None;

M. Yoshida,
None;

S. Tanaka,
None;

Y. Kogata,
None;

G. Kageyama,
None;

S. Kawano,
None;

G. Tsuji,
None;

S. Kumagai,
None;

A. Morinobu,
None.

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